Theory of sampling: four critical success factors before analysis.

PubMed

Wagner, Claas; Esbensen, Kim H

2015-01-01

Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.

Effects of holding time and measurement error on culturing Legionella in environmental water samples.

PubMed

Flanders, W Dana; Kirkland, Kimberly H; Shelton, Brian G

2014-10-01

Outbreaks of Legionnaires' disease require environmental testing of water samples from potentially implicated building water systems to identify the source of exposure. A previous study reports a large impact on Legionella sample results due to shipping and delays in sample processing. Specifically, this same study, without accounting for measurement error, reports more than half of shipped samples tested had Legionella levels that arbitrarily changed up or down by one or more logs, and the authors attribute this result to shipping time. Accordingly, we conducted a study to determine the effects of sample holding/shipping time on Legionella sample results while taking into account measurement error, which has previously not been addressed. We analyzed 159 samples, each split into 16 aliquots, of which one-half (8) were processed promptly after collection. The remaining half (8) were processed the following day to assess impact of holding/shipping time. A total of 2544 samples were analyzed including replicates. After accounting for inherent measurement error, we found that the effect of holding time on observed Legionella counts was small and should have no practical impact on interpretation of results. Holding samples increased the root mean squared error by only about 3-8%. Notably, for only one of 159 samples, did the average of the 8 replicate counts change by 1 log. Thus, our findings do not support the hypothesis of frequent, significant (≥= 1 log10 unit) Legionella colony count changes due to holding. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagayama, T.; Bailey, J. E.; Loisel, G. P.

Iron opacity calculations presently disagree with measurements at an electron temperature of ~180–195 eV and an electron density of (2–4)×10 22cm –3, conditions similar to those at the base of the solar convection zone. The measurements use x rays to volumetrically heat a thin iron sample that is tamped with low-Z materials. The opacity is inferred from spectrally resolved x-ray transmission measurements. Plasma self-emission, tamper attenuation, and temporal and spatial gradients can all potentially cause systematic errors in the measured opacity spectra. In this article we quantitatively evaluate these potential errors with numerical investigations. The analysis exploits computer simulations thatmore » were previously found to reproduce the experimentally measured plasma conditions. The simulations, combined with a spectral synthesis model, enable evaluations of individual and combined potential errors in order to estimate their potential effects on the opacity measurement. Lastly, the results show that the errors considered here do not account for the previously observed model-data discrepancies.« less

Outliers: A Potential Data Problem.

ERIC Educational Resources Information Center

Douzenis, Cordelia; Rakow, Ernest A.

Outliers, extreme data values relative to others in a sample, may distort statistics that assume internal levels of measurement and normal distribution. The outlier may be a valid value or an error. Several procedures are available for identifying outliers, and each may be applied to errors of prediction from the regression lines for utility in a…

Nearly two decades using the check-type to prevent ABO incompatible transfusions: one institution's experience.

PubMed

Figueroa, Priscila I; Ziman, Alyssa; Wheeler, Christine; Gornbein, Jeffrey; Monson, Michael; Calhoun, Loni

2006-09-01

To detect miscollected (wrong blood in tube [WBIT]) samples, our institution requires a second independently drawn sample (check-type [CT]) on previously untyped, non-group O patients who are likely to require transfusion. During the 17-year period addressed by this report, 94 WBIT errors were detected: 57% by comparison with a historic blood type, 7% by the CT, and 35% by other means. The CT averted 5 potential ABO-incompatible transfusions. Our corrected WBIT error rate is 1 in 3,713 for verified samples tested between 2000 and 2003, the period for which actual number of CTs performed was available. The estimated rate of WBIT for the 17-year period is 1 in 2,262 samples. ABO-incompatible transfusions due to WBIT-type errors are avoided by comparison of current blood type results with a historic type, and the CT is an effective way to create a historic type.

Numerical investigations of potential systematic uncertainties in iron opacity measurements at solar interior temperatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagayama, T.; Bailey, J. E.; Loisel, G. P.

Iron opacity calculations presently disagree with measurements at an electron temperature of ~180–195 eV and an electron density of (2–4)×10 22cm –3, conditions similar to those at the base of the solar convection zone. The measurements use x rays to volumetrically heat a thin iron sample that is tamped with low-Z materials. The opacity is inferred from spectrally resolved x-ray transmission measurements. Plasma self-emission, tamper attenuation, and temporal and spatial gradients can all potentially cause systematic errors in the measured opacity spectra. In this article we quantitatively evaluate these potential errors with numerical investigations. The analysis exploits computer simulations thatmore » were previously found to reproduce the experimentally measured plasma conditions. The simulations, combined with a spectral synthesis model, enable evaluations of individual and combined potential errors in order to estimate their potential effects on the opacity measurement. Lastly, the results show that the errors considered here do not account for the previously observed model-data discrepancies.« less

Numerical investigations of potential systematic uncertainties in iron opacity measurements at solar interior temperatures

DOE PAGES

Nagayama, T.; Bailey, J. E.; Loisel, G. P.; ...

2017-06-26

Iron opacity calculations presently disagree with measurements at an electron temperature of ~180–195 eV and an electron density of (2–4)×10 22cm –3, conditions similar to those at the base of the solar convection zone. The measurements use x rays to volumetrically heat a thin iron sample that is tamped with low-Z materials. The opacity is inferred from spectrally resolved x-ray transmission measurements. Plasma self-emission, tamper attenuation, and temporal and spatial gradients can all potentially cause systematic errors in the measured opacity spectra. In this article we quantitatively evaluate these potential errors with numerical investigations. The analysis exploits computer simulations thatmore » were previously found to reproduce the experimentally measured plasma conditions. The simulations, combined with a spectral synthesis model, enable evaluations of individual and combined potential errors in order to estimate their potential effects on the opacity measurement. Lastly, the results show that the errors considered here do not account for the previously observed model-data discrepancies.« less

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

The utility of point count surveys to predict wildlife interactions with wind energy facilities: An example focused on golden eagles

USGS Publications Warehouse

Sur, Maitreyi; Belthoff, James R.; Bjerre, Emily R.; Millsap, Brian A.; Katzner, Todd

2018-01-01

Wind energy development is rapidly expanding in North America, often accompanied by requirements to survey potential facility locations for existing wildlife. Within the USA, golden eagles (Aquila chrysaetos) are among the most high-profile species of birds that are at risk from wind turbines. To minimize golden eagle fatalities in areas proposed for wind development, modified point count surveys are usually conducted to estimate use by these birds. However, it is not always clear what drives variation in the relationship between on-site point count data and actual use by eagles of a wind energy project footprint. We used existing GPS-GSM telemetry data, collected at 15 min intervals from 13 golden eagles in 2012 and 2013, to explore the relationship between point count data and eagle use of an entire project footprint. To do this, we overlaid the telemetry data on hypothetical project footprints and simulated a variety of point count sampling strategies for those footprints. We compared the time an eagle was found in the sample plots with the time it was found in the project footprint using a metric we called “error due to sampling”. Error due to sampling for individual eagles appeared to be influenced by interactions between the size of the project footprint (20, 40, 90 or 180 km2) and the sampling type (random, systematic or stratified) and was greatest on 90 km2 plots. However, use of random sampling resulted in lowest error due to sampling within intermediate sized plots. In addition sampling intensity and sampling frequency both influenced the effectiveness of point count sampling. Although our work focuses on individual eagles (not the eagle populations typically surveyed in the field), our analysis shows both the utility of simulations to identify specific influences on error and also potential improvements to sampling that consider the context-specific manner that point counts are laid out on the landscape.

Non-linear matter power spectrum covariance matrix errors and cosmological parameter uncertainties

NASA Astrophysics Data System (ADS)

Blot, L.; Corasaniti, P. S.; Amendola, L.; Kitching, T. D.

2016-06-01

The covariance of the matter power spectrum is a key element of the analysis of galaxy clustering data. Independent realizations of observational measurements can be used to sample the covariance, nevertheless statistical sampling errors will propagate into the cosmological parameter inference potentially limiting the capabilities of the upcoming generation of galaxy surveys. The impact of these errors as function of the number of realizations has been previously evaluated for Gaussian distributed data. However, non-linearities in the late-time clustering of matter cause departures from Gaussian statistics. Here, we address the impact of non-Gaussian errors on the sample covariance and precision matrix errors using a large ensemble of N-body simulations. In the range of modes where finite volume effects are negligible (0.1 ≲ k [h Mpc-1] ≲ 1.2), we find deviations of the variance of the sample covariance with respect to Gaussian predictions above ˜10 per cent at k > 0.3 h Mpc-1. Over the entire range these reduce to about ˜5 per cent for the precision matrix. Finally, we perform a Fisher analysis to estimate the effect of covariance errors on the cosmological parameter constraints. In particular, assuming Euclid-like survey characteristics we find that a number of independent realizations larger than 5000 is necessary to reduce the contribution of sampling errors to the cosmological parameter uncertainties at subpercent level. We also show that restricting the analysis to large scales k ≲ 0.2 h Mpc-1 results in a considerable loss in constraining power, while using the linear covariance to include smaller scales leads to an underestimation of the errors on the cosmological parameters.

Simulations of the Sampling Distribution of the Mean Do Not Necessarily Mislead and Can Facilitate Learning

ERIC Educational Resources Information Center

Lane, David M.

2015-01-01

Recently Watkins, Bargagliotti, and Franklin (2014) discovered that simulations of the sampling distribution of the mean can mislead students into concluding that the mean of the sampling distribution of the mean depends on sample size. This potential error arises from the fact that the mean of a simulated sampling distribution will tend to be…

Classification based upon gene expression data: bias and precision of error rates.

PubMed

Wood, Ian A; Visscher, Peter M; Mengersen, Kerrie L

2007-06-01

Gene expression data offer a large number of potentially useful predictors for the classification of tissue samples into classes, such as diseased and non-diseased. The predictive error rate of classifiers can be estimated using methods such as cross-validation. We have investigated issues of interpretation and potential bias in the reporting of error rate estimates. The issues considered here are optimization and selection biases, sampling effects, measures of misclassification rate, baseline error rates, two-level external cross-validation and a novel proposal for detection of bias using the permutation mean. Reporting an optimal estimated error rate incurs an optimization bias. Downward bias of 3-5% was found in an existing study of classification based on gene expression data and may be endemic in similar studies. Using a simulated non-informative dataset and two example datasets from existing studies, we show how bias can be detected through the use of label permutations and avoided using two-level external cross-validation. Some studies avoid optimization bias by using single-level cross-validation and a test set, but error rates can be more accurately estimated via two-level cross-validation. In addition to estimating the simple overall error rate, we recommend reporting class error rates plus where possible the conditional risk incorporating prior class probabilities and a misclassification cost matrix. We also describe baseline error rates derived from three trivial classifiers which ignore the predictors. R code which implements two-level external cross-validation with the PAMR package, experiment code, dataset details and additional figures are freely available for non-commercial use from http://www.maths.qut.edu.au/profiles/wood/permr.jsp

Learning from Past Classification Errors: Exploring Methods for Improving the Performance of a Deep Learning-based Building Extraction Model through Quantitative Analysis of Commission Errors for Optimal Sample Selection

NASA Astrophysics Data System (ADS)

Swan, B.; Laverdiere, M.; Yang, L.

2017-12-01

In the past five years, deep Convolutional Neural Networks (CNN) have been increasingly favored for computer vision applications due to their high accuracy and ability to generalize well in very complex problems; however, details of how they function and in turn how they may be optimized are still imperfectly understood. In particular, their complex and highly nonlinear network architecture, including many hidden layers and self-learned parameters, as well as their mathematical implications, presents open questions about how to effectively select training data. Without knowledge of the exact ways the model processes and transforms its inputs, intuition alone may fail as a guide to selecting highly relevant training samples. Working in the context of improving a CNN-based building extraction model used for the LandScan USA gridded population dataset, we have approached this problem by developing a semi-supervised, highly-scalable approach to select training samples from a dataset of identified commission errors. Due to the large scope this project, tens of thousands of potential samples could be derived from identified commission errors. To efficiently trim those samples down to a manageable and effective set for creating additional training sample, we statistically summarized the spectral characteristics of areas with rates of commission errors at the image tile level and grouped these tiles using affinity propagation. Highly representative members of each commission error cluster were then used to select sites for training sample creation. The model will be incrementally re-trained with the new training data to allow for an assessment of how the addition of different types of samples affects the model performance, such as precision and recall rates. By using quantitative analysis and data clustering techniques to select highly relevant training samples, we hope to improve model performance in a manner that is resource efficient, both in terms of training process and in sample creation.

Simulated rRNA/DNA Ratios Show Potential To Misclassify Active Populations as Dormant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steven, Blaire; Hesse, Cedar; Soghigian, John

The use of rRNA/DNA ratios derived from surveys of rRNA sequences in RNA and DNA extracts is an appealing but poorly validated approach to infer the activity status of environmental microbes. To improve the interpretation of rRNA/DNA ratios, we performed simulations to investigate the effects of community structure, rRNA amplification, and sampling depth on the accuracy of rRNA/DNA ratios in classifying bacterial populations as “active” or “dormant.” Community structure was an insignificant factor. In contrast, the extent of rRNA amplification that occurs as cells transition from dormant to growing had a significant effect (P < 0.0001) on classification accuracy, withmore » misclassification errors ranging from 16 to 28%, depending on the rRNA amplification model. The error rate increased to 47% when communities included a mixture of rRNA amplification models, but most of the inflated error was false negatives (i.e., active populations misclassified as dormant). Sampling depth also affected error rates (P < 0.001). Inadequate sampling depth produced various artifacts that are characteristic of rRNA/DNA ratios generated from real communities. These data show important constraints on the use of rRNA/DNA ratios to infer activity status. Whereas classification of populations as active based on rRNA/DNA ratios appears generally valid, classification of populations as dormant is potentially far less accurate.« less

Simulated rRNA/DNA Ratios Show Potential To Misclassify Active Populations as Dormant

DOE PAGES

Steven, Blaire; Hesse, Cedar; Soghigian, John; ...

2017-03-31

The use of rRNA/DNA ratios derived from surveys of rRNA sequences in RNA and DNA extracts is an appealing but poorly validated approach to infer the activity status of environmental microbes. To improve the interpretation of rRNA/DNA ratios, we performed simulations to investigate the effects of community structure, rRNA amplification, and sampling depth on the accuracy of rRNA/DNA ratios in classifying bacterial populations as “active” or “dormant.” Community structure was an insignificant factor. In contrast, the extent of rRNA amplification that occurs as cells transition from dormant to growing had a significant effect (P < 0.0001) on classification accuracy, withmore » misclassification errors ranging from 16 to 28%, depending on the rRNA amplification model. The error rate increased to 47% when communities included a mixture of rRNA amplification models, but most of the inflated error was false negatives (i.e., active populations misclassified as dormant). Sampling depth also affected error rates (P < 0.001). Inadequate sampling depth produced various artifacts that are characteristic of rRNA/DNA ratios generated from real communities. These data show important constraints on the use of rRNA/DNA ratios to infer activity status. Whereas classification of populations as active based on rRNA/DNA ratios appears generally valid, classification of populations as dormant is potentially far less accurate.« less

An investigation into false-negative transthoracic fine needle aspiration and core biopsy specimens.

PubMed

Minot, Douglas M; Gilman, Elizabeth A; Aubry, Marie-Christine; Voss, Jesse S; Van Epps, Sarah G; Tuve, Delores J; Sciallis, Andrew P; Henry, Michael R; Salomao, Diva R; Lee, Peter; Carlson, Stephanie K; Clayton, Amy C

2014-12-01

Transthoracic fine needle aspiration (TFNA)/core needle biopsy (CNB) under computed tomography (CT) guidance has proved useful in the assessment of pulmonary nodules. We sought to determine the TFNA false-negative (FN) rate at our institution and identify potential causes of FN diagnoses. Medical records were reviewed from 1,043 consecutive patients who underwent CT-guided TFNA with or without CNB of lung nodules over a 5-year time period (2003-2007). Thirty-seven FN cases of "negative" TFNA/CNB with malignant outcome were identified with 36 cases available for review, of which 35 had a corresponding CNB. Cases were reviewed independently (blinded to original diagnosis) by three pathologists with 15 age- and sex-matched positive and negative controls. Diagnosis (i.e., nondiagnostic, negative or positive for malignancy, atypical or suspicious) and qualitative assessments were recorded. Consensus diagnosis was suspicious or positive in 10 (28%) of 36 TFNA cases and suspicious in 1 (3%) of 35 CNB cases, indicating potential interpretive errors. Of the 11 interpretive errors (including both suspicious and positive cases), 8 were adenocarcinomas, 1 squamous cell carcinoma, 1 metastatic renal cell carcinoma, and 1 lymphoma. The remaining 25 FN cases (69.4%) were considered sampling errors and consisted of 7 adenocarcinomas, 3 nonsmall cell carcinomas, 3 lymphomas, 2 squamous cell carcinomas, and 2 renal cell carcinomas. Interpretive and sampling error cases were more likely to abut the pleura, while histopathologically, they tended to be necrotic and air-dried. The overall FN rate in this patient cohort is 3.5% (1.1% interpretive and 2.4% sampling errors). © 2014 Wiley Periodicals, Inc.

Random and systematic sampling error when hooking fish to monitor skin fluke (Benedenia seriolae) and gill fluke (Zeuxapta seriolae) burden in Australian farmed yellowtail kingfish (Seriola lalandi).

PubMed

Fensham, J R; Bubner, E; D'Antignana, T; Landos, M; Caraguel, C G B

2018-05-01

The Australian farmed yellowtail kingfish (Seriola lalandi, YTK) industry monitor skin fluke (Benedenia seriolae) and gill fluke (Zeuxapta seriolae) burden by pooling the fluke count of 10 hooked YTK. The random and systematic error of this sampling strategy was evaluated to assess potential impact on treatment decisions. Fluke abundance (fluke count per fish) in a study cage (estimated 30,502 fish) was assessed five times using the current sampling protocol and its repeatability was estimated the repeatability coefficient (CR) and the coefficient of variation (CV). Individual body weight, fork length, fluke abundance, prevalence, intensity (fluke count per infested fish) and density (fluke count per Kg of fish) were compared between 100 hooked and 100 seined YTK (assumed representative of the entire population) to estimate potential selection bias. Depending on the fluke species and age category, CR (expected difference in parasite count between 2 sampling iterations) ranged from 0.78 to 114 flukes per fish. Capturing YTK by hooking increased the selection of fish of a weight and length in the lowest 5th percentile of the cage (RR = 5.75, 95% CI: 2.06-16.03, P-value = 0.0001). These lower end YTK had on average an extra 31 juveniles and 6 adults Z. seriolae per Kg of fish and an extra 3 juvenile and 0.4 adult B. seriolae per Kg of fish, compared to the rest of the cage population (P-value < 0.05). Hooking YTK on the edge of the study cage biases sampling towards the smallest and most heavily infested fish in the population, resulting in poor repeatability (more variability amongst sampled fish) and an overestimation of parasite burden in the population. In this particular commercial situation these finding supported that health management program, where the finding of an underestimation of parasite burden could provide a production impact on the study population. In instances where fish populations and parasite burdens are more homogenous, sampling error may be less severe. Sampling error when capturing fish from sea cage is difficult to predict. The amplitude and direction of this error should be investigated for a given cultured fish species across a range of parasite burden and fish profile scenarios. Copyright © 2018 Elsevier B.V. All rights reserved.

Characterizing Air Pollution Exposure Misclassification Errors Using Detailed Cell Phone Location Data

NASA Astrophysics Data System (ADS)

Yu, H.; Russell, A. G.; Mulholland, J. A.

2017-12-01

In air pollution epidemiologic studies with spatially resolved air pollution data, exposures are often estimated using the home locations of individual subjects. Due primarily to lack of data or logistic difficulties, the spatiotemporal mobility of subjects are mostly neglected, which are expected to result in exposure misclassification errors. In this study, we applied detailed cell phone location data to characterize potential exposure misclassification errors associated with home-based exposure estimation of air pollution. The cell phone data sample consists of 9,886 unique simcard IDs collected on one mid-week day in October, 2013 from Shenzhen, China. The Community Multi-scale Air Quality model was used to simulate hourly ambient concentrations of six chosen pollutants at 3 km spatial resolution, which were then fused with observational data to correct for potential modeling biases and errors. Air pollution exposure for each simcard ID was estimated by matching hourly pollutant concentrations with detailed location data for corresponding IDs. Finally, the results were compared with exposure estimates obtained using the home location method to assess potential exposure misclassification errors. Our results show that the home-based method is likely to have substantial exposure misclassification errors, over-estimating exposures for subjects with higher exposure levels and under-estimating exposures for those with lower exposure levels. This has the potential to lead to a bias-to-the-null in the health effect estimates. Our findings suggest that the use of cell phone data has the potential for improving the characterization of exposure and exposure misclassification in air pollution epidemiology studies.

Rapid discrimination between buffalo and cow milk and detection of adulteration of buffalo milk with cow milk using synchronous fluorescence spectroscopy in combination with multivariate methods.

PubMed

Durakli Velioglu, Serap; Ercioglu, Elif; Boyaci, Ismail Hakki

2017-05-01

This research paper describes the potential of synchronous fluorescence (SF) spectroscopy for authentication of buffalo milk, a favourable raw material in the production of some premium dairy products. Buffalo milk is subjected to fraudulent activities like many other high priced foodstuffs. The current methods widely used for the detection of adulteration of buffalo milk have various disadvantages making them unattractive for routine analysis. Thus, the aim of the present study was to assess the potential of SF spectroscopy in combination with multivariate methods for rapid discrimination between buffalo and cow milk and detection of the adulteration of buffalo milk with cow milk. SF spectra of cow and buffalo milk samples were recorded between 400-550 nm excitation range with Δλ of 10-100 nm, in steps of 10 nm. The data obtained for ∆λ = 10 nm were utilised to classify the samples using principal component analysis (PCA), and detect the adulteration level of buffalo milk with cow milk using partial least square (PLS) methods. Successful discrimination of samples and detection of adulteration of buffalo milk with limit of detection value (LOD) of 6% are achieved with the models having root mean square error of calibration (RMSEC) and the root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) values of 2, 7, and 4%, respectively. The results reveal the potential of SF spectroscopy for rapid authentication of buffalo milk.

Impact of Design Effects in Large-Scale District and State Assessments

ERIC Educational Resources Information Center

Phillips, Gary W.

2015-01-01

This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…

IMPROVED SPECTROPHOTOMETRIC CALIBRATION OF THE SDSS-III BOSS QUASAR SAMPLE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Margala, Daniel; Kirkby, David; Dawson, Kyle

2016-11-10

We present a model for spectrophotometric calibration errors in observations of quasars from the third generation of the Sloan Digital Sky Survey Baryon Oscillation Spectroscopic Survey (BOSS) and describe the correction procedure we have developed and applied to this sample. Calibration errors are primarily due to atmospheric differential refraction and guiding offsets during each exposure. The corrections potentially reduce the systematics for any studies of BOSS quasars, including the measurement of baryon acoustic oscillations using the Ly α forest. Our model suggests that, on average, the observed quasar flux in BOSS is overestimated by ∼19% at 3600 Å and underestimatedmore » by ∼24% at 10,000 Å. Our corrections for the entire BOSS quasar sample are publicly available.« less

Incidence of speech recognition errors in the emergency department.

PubMed

Goss, Foster R; Zhou, Li; Weiner, Scott G

2016-09-01

Physician use of computerized speech recognition (SR) technology has risen in recent years due to its ease of use and efficiency at the point of care. However, error rates between 10 and 23% have been observed, raising concern about the number of errors being entered into the permanent medical record, their impact on quality of care and medical liability that may arise. Our aim was to determine the incidence and types of SR errors introduced by this technology in the emergency department (ED). Level 1 emergency department with 42,000 visits/year in a tertiary academic teaching hospital. A random sample of 100 notes dictated by attending emergency physicians (EPs) using SR software was collected from the ED electronic health record between January and June 2012. Two board-certified EPs annotated the notes and conducted error analysis independently. An existing classification schema was adopted to classify errors into eight errors types. Critical errors deemed to potentially impact patient care were identified. There were 128 errors in total or 1.3 errors per note, and 14.8% (n=19) errors were judged to be critical. 71% of notes contained errors, and 15% contained one or more critical errors. Annunciation errors were the highest at 53.9% (n=69), followed by deletions at 18.0% (n=23) and added words at 11.7% (n=15). Nonsense errors, homonyms and spelling errors were present in 10.9% (n=14), 4.7% (n=6), and 0.8% (n=1) of notes, respectively. There were no suffix or dictionary errors. Inter-annotator agreement was 97.8%. This is the first estimate at classifying speech recognition errors in dictated emergency department notes. Speech recognition errors occur commonly with annunciation errors being the most frequent. Error rates were comparable if not lower than previous studies. 15% of errors were deemed critical, potentially leading to miscommunication that could affect patient care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Per-pixel bias-variance decomposition of continuous errors in data-driven geospatial modeling: A case study in environmental remote sensing

NASA Astrophysics Data System (ADS)

Gao, Jing; Burt, James E.

2017-12-01

This study investigates the usefulness of a per-pixel bias-variance error decomposition (BVD) for understanding and improving spatially-explicit data-driven models of continuous variables in environmental remote sensing (ERS). BVD is a model evaluation method originated from machine learning and have not been examined for ERS applications. Demonstrated with a showcase regression tree model mapping land imperviousness (0-100%) using Landsat images, our results showed that BVD can reveal sources of estimation errors, map how these sources vary across space, reveal the effects of various model characteristics on estimation accuracy, and enable in-depth comparison of different error metrics. Specifically, BVD bias maps can help analysts identify and delineate model spatial non-stationarity; BVD variance maps can indicate potential effects of ensemble methods (e.g. bagging), and inform efficient training sample allocation - training samples should capture the full complexity of the modeled process, and more samples should be allocated to regions with more complex underlying processes rather than regions covering larger areas. Through examining the relationships between model characteristics and their effects on estimation accuracy revealed by BVD for both absolute and squared errors (i.e. error is the absolute or the squared value of the difference between observation and estimate), we found that the two error metrics embody different diagnostic emphases, can lead to different conclusions about the same model, and may suggest different solutions for performance improvement. We emphasize BVD's strength in revealing the connection between model characteristics and estimation accuracy, as understanding this relationship empowers analysts to effectively steer performance through model adjustments.

Intraoperative visualization and assessment of electromagnetic tracking error

NASA Astrophysics Data System (ADS)

Harish, Vinyas; Ungi, Tamas; Lasso, Andras; MacDonald, Andrew; Nanji, Sulaiman; Fichtinger, Gabor

2015-03-01

Electromagnetic tracking allows for increased flexibility in designing image-guided interventions, however it is well understood that electromagnetic tracking is prone to error. Visualization and assessment of the tracking error should take place in the operating room with minimal interference with the clinical procedure. The goal was to achieve this ideal in an open-source software implementation in a plug and play manner, without requiring programming from the user. We use optical tracking as a ground truth. An electromagnetic sensor and optical markers are mounted onto a stylus device, pivot calibrated for both trackers. Electromagnetic tracking error is defined as difference of tool tip position between electromagnetic and optical readings. Multiple measurements are interpolated into the thin-plate B-spline transform visualized in real time using 3D Slicer. All tracked devices are used in a plug and play manner through the open-source SlicerIGT and PLUS extensions of the 3D Slicer platform. Tracking error was measured multiple times to assess reproducibility of the method, both with and without placing ferromagnetic objects in the workspace. Results from exhaustive grid sampling and freehand sampling were similar, indicating that a quick freehand sampling is sufficient to detect unexpected or excessive field distortion in the operating room. The software is available as a plug-in for the 3D Slicer platforms. Results demonstrate potential for visualizing electromagnetic tracking error in real time for intraoperative environments in feasibility clinical trials in image-guided interventions.

Enumerating Sparse Organisms in Ships’ Ballast Water: Why Counting to 10 Is Not So Easy

PubMed Central

2011-01-01

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships’ ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed. PMID:21434685

Enumerating sparse organisms in ships' ballast water: why counting to 10 is not so easy.

PubMed

Miller, A Whitman; Frazier, Melanie; Smith, George E; Perry, Elgin S; Ruiz, Gregory M; Tamburri, Mario N

2011-04-15

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships' ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed.

Lexical Diversity and Omission Errors as Predictors of Language Ability in the Narratives of Sequential Spanish-English Bilinguals: A Cross-Language Comparison

ERIC Educational Resources Information Center

Jacobson, Peggy F.; Walden, Patrick R.

2013-01-01

Purpose: This study explored the utility of language sample analysis for evaluating language ability in school-age Spanish-English sequential bilingual children. Specifically, the relative potential of lexical diversity and word/morpheme omission as predictors of typical or atypical language status was evaluated. Method: Narrative samples were…

Quantifying differences in the impact of variable chemistry on equilibrium uranium(VI) adsorption properties of aquifer sediments

USGS Publications Warehouse

Stoliker, Deborah L.; Kent, Douglas B.; Zachara, John M.

2011-01-01

Uranium adsorption-desorption on sediment samples collected from the Hanford 300-Area, Richland, WA varied extensively over a range of field-relevant chemical conditions, complicating assessment of possible differences in equilibrium adsorption properties. Adsorption equilibrium was achieved in 500-1000 h although dissolved uranium concentrations increased over thousands of hours owing to changes in aqueous chemical composition driven by sediment-water reactions. A nonelectrostatic surface complexation reaction, >SOH + UO22+ + 2CO32- = >SOUO2(CO3HCO3)2-, provided the best fit to experimental data for each sediment sample resulting in a range of conditional equilibrium constants (logKc) from 21.49 to 21.76. Potential differences in uranium adsorption properties could be assessed in plots based on the generalized mass-action expressions yielding linear trends displaced vertically by differences in logKc values. Using this approach, logKc values for seven sediment samples were not significantly different. However, a significant difference in adsorption properties between one sediment sample and the fines (Kc uncertainty were improved by capturing all data points within experimental errors. The mass-action expression plots demonstrate that applying models outside the range of conditions used in model calibration greatly increases potential errors.

Accelerating Convergence in Molecular Dynamics Simulations of Solutes in Lipid Membranes by Conducting a Random Walk along the Bilayer Normal.

PubMed

Neale, Chris; Madill, Chris; Rauscher, Sarah; Pomès, Régis

2013-08-13

All molecular dynamics simulations are susceptible to sampling errors, which degrade the accuracy and precision of observed values. The statistical convergence of simulations containing atomistic lipid bilayers is limited by the slow relaxation of the lipid phase, which can exceed hundreds of nanoseconds. These long conformational autocorrelation times are exacerbated in the presence of charged solutes, which can induce significant distortions of the bilayer structure. Such long relaxation times represent hidden barriers that induce systematic sampling errors in simulations of solute insertion. To identify optimal methods for enhancing sampling efficiency, we quantitatively evaluate convergence rates using generalized ensemble sampling algorithms in calculations of the potential of mean force for the insertion of the ionic side chain analog of arginine in a lipid bilayer. Umbrella sampling (US) is used to restrain solute insertion depth along the bilayer normal, the order parameter commonly used in simulations of molecular solutes in lipid bilayers. When US simulations are modified to conduct random walks along the bilayer normal using a Hamiltonian exchange algorithm, systematic sampling errors are eliminated more rapidly and the rate of statistical convergence of the standard free energy of binding of the solute to the lipid bilayer is increased 3-fold. We compute the ratio of the replica flux transmitted across a defined region of the order parameter to the replica flux that entered that region in Hamiltonian exchange simulations. We show that this quantity, the transmission factor, identifies sampling barriers in degrees of freedom orthogonal to the order parameter. The transmission factor is used to estimate the depth-dependent conformational autocorrelation times of the simulation system, some of which exceed the simulation time, and thereby identify solute insertion depths that are prone to systematic sampling errors and estimate the lower bound of the amount of sampling that is required to resolve these sampling errors. Finally, we extend our simulations and verify that the conformational autocorrelation times estimated by the transmission factor accurately predict correlation times that exceed the simulation time scale-something that, to our knowledge, has never before been achieved.

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

PubMed Central

Xu, Chonggang; Gertner, George

2013-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

PubMed

Xu, Chonggang; Gertner, George

2011-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

Problems in determining the surface density of the Galactic disk

NASA Technical Reports Server (NTRS)

Statler, Thomas S.

1989-01-01

A new method is presented for determining the local surface density of the Galactic disk from distance and velocity measurements of stars toward the Galactic poles. The procedure is fully three-dimensional, approximating the Galactic potential by a potential of Staeckel form and using the analytic third integral to treat the tilt and the change of shape of the velocity ellipsoid consistently. Applying the procedure to artificial data superficially resembling the K dwarf sample of Kuijken and Gilmore (1988, 1989), it is shown that the current best estimates of local disk surface density are uncertain by at least 30 percent. Of this, about 25 percent is due to the size of the velocity sample, about 15 percent comes from uncertainties in the rotation curve and the solar galactocentric distance, and about 10 percent from ignorance of the shape of the velocity distribution above z = 1 kpc, the errors adding in quadrature. Increasing the sample size by a factor of 3 will reduce the error to 20 percent. To achieve 10 percent accuracy, observations will be needed along other lines of sight to constrain the shape of the velocity ellipsoid.

EEG Frequency Changes Prior to Making Errors in an Easy Stroop Task

PubMed Central

Atchley, Rachel; Klee, Daniel; Oken, Barry

2017-01-01

Background: Mind-wandering is a form of off-task attention that has been associated with negative affect and rumination. The goal of this study was to assess potential electroencephalographic markers of task-unrelated thought, or mind-wandering state, as related to error rates during a specialized cognitive task. We used EEG to record frontal frequency band activity while participants completed a Stroop task that was modified to induce boredom, task-unrelated thought, and therefore mind-wandering. Methods: A convenience sample of 27 older adults (50–80 years) completed a computerized Stroop matching task. Half of the Stroop trials were congruent (word/color match), and the other half were incongruent (mismatched). Behavioral data and EEG recordings were assessed. EEG analysis focused on the 1-s epochs prior to stimulus presentation in order to compare trials followed by correct versus incorrect responses. Results: Participants made errors on 9% of incongruent trials. There were no errors on congruent trials. There was a decrease in alpha and theta band activity during the epochs followed by error responses. Conclusion: Although replication of these results is necessary, these findings suggest that potential mind-wandering, as evidenced by errors, can be characterized by a decrease in alpha and theta activity compared to on-task, accurate performance periods. PMID:29163101

Mass discharge in a tracer plume: Evaluation of the Theissen Polygon Method

PubMed Central

Mackay, Douglas M.; Einarson, Murray D.; Kaiser, Phil M.; Nozawa-Inoue, Mamie; Goyal, Sham; Chakraborty, Irina; Rasa, Ehsan; Scow, Kate M.

2013-01-01

A tracer plume was created within a thin aquifer by injection for 299 days of two adjacent “sub-plumes” to represent one type of plume heterogeneity encountered in practice. The plume was monitored by snapshot sampling of transects of fully screened wells. The mass injection rate and total mass injected were known. Using all wells in each transect (0.77 m well spacing, 1.4 points/m2 sampling density), the Theissen Polygon Method (TPM) yielded apparently accurate mass discharge (Md) estimates at 3 transects for 12 snapshots. When applied to hypothetical sparser transects using subsets of the wells with average spacing and sampling density from 1.55 to 5.39 m and 0.70 to 0.20 points/m2, respectively, the TPM accuracy depended on well spacing and location of the wells in the hypothesized transect with respect to the sub-plumes. Potential error was relatively low when the well spacing was less than the widths of the sub-plumes (> 0.35 points/m2). Potential error increased for well spacing similar to or greater than the sub-plume widths, or when less than 1% of the plume area was sampled. For low density sampling of laterally heterogeneous plumes, small changes in groundwater flow direction can lead to wide fluctuations in Md estimates by the TPM. However, sampling conducted when flow is known or likely to be in a preferred direction can potentially allow more useful comparisons of Md over multiyear time frames, such as required for performance evaluation of natural attenuation or engineered remediation systems. PMID:22324777

Analyzing the errors of DFT approximations for compressed water systems

NASA Astrophysics Data System (ADS)

Alfè, D.; Bartók, A. P.; Csányi, G.; Gillan, M. J.

2014-07-01

We report an extensive study of the errors of density functional theory (DFT) approximations for compressed water systems. The approximations studied are based on the widely used PBE and BLYP exchange-correlation functionals, and we characterize their errors before and after correction for 1- and 2-body errors, the corrections being performed using the methods of Gaussian approximation potentials. The errors of the uncorrected and corrected approximations are investigated for two related types of water system: first, the compressed liquid at temperature 420 K and density 1.245 g/cm3 where the experimental pressure is 15 kilobars; second, thermal samples of compressed water clusters from the trimer to the 27-mer. For the liquid, we report four first-principles molecular dynamics simulations, two generated with the uncorrected PBE and BLYP approximations and a further two with their 1- and 2-body corrected counterparts. The errors of the simulations are characterized by comparing with experimental data for the pressure, with neutron-diffraction data for the three radial distribution functions, and with quantum Monte Carlo (QMC) benchmarks for the energies of sets of configurations of the liquid in periodic boundary conditions. The DFT errors of the configuration samples of compressed water clusters are computed using QMC benchmarks. We find that the 2-body and beyond-2-body errors in the liquid are closely related to similar errors exhibited by the clusters. For both the liquid and the clusters, beyond-2-body errors of DFT make a substantial contribution to the overall errors, so that correction for 1- and 2-body errors does not suffice to give a satisfactory description. For BLYP, a recent representation of 3-body energies due to Medders, Babin, and Paesani [J. Chem. Theory Comput. 9, 1103 (2013)] gives a reasonably good way of correcting for beyond-2-body errors, after which the remaining errors are typically 0.5 mEh ≃ 15 meV/monomer for the liquid and the clusters.

Analyzing the errors of DFT approximations for compressed water systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alfè, D.; London Centre for Nanotechnology, UCL, London WC1H 0AH; Thomas Young Centre, UCL, London WC1H 0AH

We report an extensive study of the errors of density functional theory (DFT) approximations for compressed water systems. The approximations studied are based on the widely used PBE and BLYP exchange-correlation functionals, and we characterize their errors before and after correction for 1- and 2-body errors, the corrections being performed using the methods of Gaussian approximation potentials. The errors of the uncorrected and corrected approximations are investigated for two related types of water system: first, the compressed liquid at temperature 420 K and density 1.245 g/cm{sup 3} where the experimental pressure is 15 kilobars; second, thermal samples of compressed watermore » clusters from the trimer to the 27-mer. For the liquid, we report four first-principles molecular dynamics simulations, two generated with the uncorrected PBE and BLYP approximations and a further two with their 1- and 2-body corrected counterparts. The errors of the simulations are characterized by comparing with experimental data for the pressure, with neutron-diffraction data for the three radial distribution functions, and with quantum Monte Carlo (QMC) benchmarks for the energies of sets of configurations of the liquid in periodic boundary conditions. The DFT errors of the configuration samples of compressed water clusters are computed using QMC benchmarks. We find that the 2-body and beyond-2-body errors in the liquid are closely related to similar errors exhibited by the clusters. For both the liquid and the clusters, beyond-2-body errors of DFT make a substantial contribution to the overall errors, so that correction for 1- and 2-body errors does not suffice to give a satisfactory description. For BLYP, a recent representation of 3-body energies due to Medders, Babin, and Paesani [J. Chem. Theory Comput. 9, 1103 (2013)] gives a reasonably good way of correcting for beyond-2-body errors, after which the remaining errors are typically 0.5 mE{sub h} ≃ 15 meV/monomer for the liquid and the clusters.« less

Psychrometric measurement of soil water potential: Stability of calibration and test of pressure-plate samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, T.L.; Gee, G.W.; Heller, P.R.

1990-08-01

A commercially available thermocouple psychrometer sample changer (Decagon SC-10A) was used to measure the water potential of field soils ranging in texture from sand to silty clay loam over a range of {minus}0.5 to {minus}20.0 MPa. The standard error of prediction based on regression statistics was generally between 0.04 and 0.14 MPa at {minus}5 MPa. Replacing the measuring junction of the unit changed the calibration slightly; however, it did not significantly alter measurement accuracy. Calibration curves measured throughout a year of testing are consistent and indicate no systematic drift in calibration. Most measurement uncertainty is produced by shifts in themore » intercept in the calibration equation rather than the slope. Both the variability in intercept and the regression error seem to be random. Measurements taken with the SC-10A show that water potential in both sand and silt loam samples removed from 1.5-MPa pressure plates was often 0.5 to 1.0 MPa greater than the 1.5-MPa applied pressure. Limited data from 0.5-MPa pressure plates show close agreement between SC-10A measurements and pressure applied to these more permeable plates.« less

Alterations in Neural Control of Constant Isometric Contraction with the Size of Error Feedback

PubMed Central

Hwang, Ing-Shiou; Lin, Yen-Ting; Huang, Wei-Min; Yang, Zong-Ru; Hu, Chia-Ling; Chen, Yi-Ching

2017-01-01

Discharge patterns from a population of motor units (MUs) were estimated with multi-channel surface electromyogram and signal processing techniques to investigate parametric differences in low-frequency force fluctuations, MU discharges, and force-discharge relation during static force-tracking with varying sizes of execution error presented via visual feedback. Fourteen healthy adults produced isometric force at 10% of maximal voluntary contraction through index abduction under three visual conditions that scaled execution errors with different amplification factors. Error-augmentation feedback that used a high amplification factor (HAF) to potentiate visualized error size resulted in higher sample entropy, mean frequency, ratio of high-frequency components, and spectral dispersion of force fluctuations than those of error-reducing feedback using a low amplification factor (LAF). In the HAF condition, MUs with relatively high recruitment thresholds in the dorsal interosseous muscle exhibited a larger coefficient of variation for inter-spike intervals and a greater spectral peak of the pooled MU coherence at 13–35 Hz than did those in the LAF condition. Manipulation of the size of error feedback altered the force-discharge relation, which was characterized with non-linear approaches such as mutual information and cross sample entropy. The association of force fluctuations and global discharge trace decreased with increasing error amplification factor. Our findings provide direct neurophysiological evidence that favors motor training using error-augmentation feedback. Amplification of the visualized error size of visual feedback could enrich force gradation strategies during static force-tracking, pertaining to selective increases in the discharge variability of higher-threshold MUs that receive greater common oscillatory inputs in the β-band. PMID:28125658

Relationship Between Patients' Perceptions of Care Quality and Health Care Errors in 11 Countries: A Secondary Data Analysis.

PubMed

Hincapie, Ana L; Slack, Marion; Malone, Daniel C; MacKinnon, Neil J; Warholak, Terri L

2016-01-01

Patients may be the most reliable reporters of some aspects of the health care process; their perspectives should be considered when pursuing changes to improve patient safety. The authors evaluated the association between patients' perceived health care quality and self-reported medical, medication, and laboratory errors in a multinational sample. The analysis was conducted using the 2010 Commonwealth Fund International Health Policy Survey, a multinational consumer survey conducted in 11 countries. Quality of care was measured by a multifaceted construct developed using Rasch techniques. After adjusting for potentially important confounding variables, an increase in respondents' perceptions of care coordination decreased the odds of self-reporting medical errors, medication errors, and laboratory errors (P < .001). As health care stakeholders continue to search for initiatives that improve care experiences and outcomes, this study's results emphasize the importance of guaranteeing integrated care.

Reduction in specimen labeling errors after implementation of a positive patient identification system in phlebotomy.

PubMed

Morrison, Aileen P; Tanasijevic, Milenko J; Goonan, Ellen M; Lobo, Margaret M; Bates, Michael M; Lipsitz, Stuart R; Bates, David W; Melanson, Stacy E F

2010-06-01

Ensuring accurate patient identification is central to preventing medical errors, but it can be challenging. We implemented a bar code-based positive patient identification system for use in inpatient phlebotomy. A before-after design was used to evaluate the impact of the identification system on the frequency of mislabeled and unlabeled samples reported in our laboratory. Labeling errors fell from 5.45 in 10,000 before implementation to 3.2 in 10,000 afterward (P = .0013). An estimated 108 mislabeling events were prevented by the identification system in 1 year. Furthermore, a workflow step requiring manual preprinting of labels, which was accompanied by potential labeling errors in about one quarter of blood "draws," was removed as a result of the new system. After implementation, a higher percentage of patients reported having their wristband checked before phlebotomy. Bar code technology significantly reduced the rate of specimen identification errors.

The power of vertical geolocation of atmospheric profiles from GNSS radio occultation.

PubMed

Scherllin-Pirscher, Barbara; Steiner, Andrea K; Kirchengast, Gottfried; Schwärz, Marc; Leroy, Stephen S

2017-02-16

High-resolution measurements from Global Navigation Satellite System (GNSS) radio occultation (RO) provide atmospheric profiles with independent information on altitude and pressure. This unique property is of crucial advantage when analyzing atmospheric characteristics that require joint knowledge of altitude and pressure or other thermodynamic atmospheric variables. Here we introduce and demonstrate the utility of this independent information from RO and discuss the computation, uncertainty, and use of RO atmospheric profiles on isohypsic coordinates-mean sea level altitude and geopotential height-as well as on thermodynamic coordinates (pressure and potential temperature). Using geopotential height as vertical grid, we give information on errors of RO-derived temperature, pressure, and potential temperature profiles and provide an empirical error model which accounts for seasonal and latitudinal variations. The observational uncertainty of individual temperature/pressure/potential temperature profiles is about 0.7 K/0.15%/1.4 K in the tropopause region. It gradually increases into the stratosphere and decreases toward the lower troposphere. This decrease is due to the increasing influence of background information. The total climatological error of mean atmospheric fields is, in general, dominated by the systematic error component. We use sampling error-corrected climatological fields to demonstrate the power of having different and accurate vertical coordinates available. As examples we analyze characteristics of the location of the tropopause for geopotential height, pressure, and potential temperature coordinates as well as seasonal variations of the midlatitude jet stream core. This highlights the broad applicability of RO and the utility of its versatile vertical geolocation for investigating the vertical structure of the troposphere and stratosphere.

Quality assessment of gasoline using comprehensive two-dimensional gas chromatography combined with unfolded partial least squares: A reliable approach for the detection of gasoline adulteration.

PubMed

Parastar, Hadi; Mostafapour, Sara; Azimi, Gholamhasan

2016-01-01

Comprehensive two-dimensional gas chromatography and flame ionization detection combined with unfolded-partial least squares is proposed as a simple, fast and reliable method to assess the quality of gasoline and to detect its potential adulterants. The data for the calibration set are first baseline corrected using a two-dimensional asymmetric least squares algorithm. The number of significant partial least squares components to build the model is determined using the minimum value of root-mean square error of leave-one out cross validation, which was 4. In this regard, blends of gasoline with kerosene, white spirit and paint thinner as frequently used adulterants are used to make calibration samples. Appropriate statistical parameters of regression coefficient of 0.996-0.998, root-mean square error of prediction of 0.005-0.010 and relative error of prediction of 1.54-3.82% for the calibration set show the reliability of the developed method. In addition, the developed method is externally validated with three samples in validation set (with a relative error of prediction below 10.0%). Finally, to test the applicability of the proposed strategy for the analysis of real samples, five real gasoline samples collected from gas stations are used for this purpose and the gasoline proportions were in range of 70-85%. Also, the relative standard deviations were below 8.5% for different samples in the prediction set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Low power arcjet system spacecraft impacts

NASA Technical Reports Server (NTRS)

Pencil, Eric J.; Sarmiento, Charles J.; Lichtin, D. A.; Palchefsky, J. W.; Bogorad, A. L.

1993-01-01

Potential plume contamination of spacecraft surfaces was investigated by positioning spacecraft material samples relative to an arcjet thruster. Samples in the simulated solar array region were exposed to the cold gas arcjet plume for 40 hrs to address concerns about contamination by backstreaming diffusion pump oil. Except for one sample, no significant changes were measured in absorptance and emittance within experimental error. Concerns about surface property degradation due to electrostatic discharges led to the investigation of the discharge phenomenon of charged samples during arcjet ignition. Short duration exposure of charged samples demonstrated that potential differences are consistently and completely eliminated within the first second of exposure to a weakly ionized plume. The spark discharge mechanism was not the discharge phenomenon. The results suggest that the arcjet could act as a charge control device on spacecraft.

Optimal number of features as a function of sample size for various classification rules.

PubMed

Hua, Jianping; Xiong, Zixiang; Lowey, James; Suh, Edward; Dougherty, Edward R

2005-04-15

Given the joint feature-label distribution, increasing the number of features always results in decreased classification error; however, this is not the case when a classifier is designed via a classification rule from sample data. Typically (but not always), for fixed sample size, the error of a designed classifier decreases and then increases as the number of features grows. The potential downside of using too many features is most critical for small samples, which are commonplace for gene-expression-based classifiers for phenotype discrimination. For fixed sample size and feature-label distribution, the issue is to find an optimal number of features. Since only in rare cases is there a known distribution of the error as a function of the number of features and sample size, this study employs simulation for various feature-label distributions and classification rules, and across a wide range of sample and feature-set sizes. To achieve the desired end, finding the optimal number of features as a function of sample size, it employs massively parallel computation. Seven classifiers are treated: 3-nearest-neighbor, Gaussian kernel, linear support vector machine, polynomial support vector machine, perceptron, regular histogram and linear discriminant analysis. Three Gaussian-based models are considered: linear, nonlinear and bimodal. In addition, real patient data from a large breast-cancer study is considered. To mitigate the combinatorial search for finding optimal feature sets, and to model the situation in which subsets of genes are co-regulated and correlation is internal to these subsets, we assume that the covariance matrix of the features is blocked, with each block corresponding to a group of correlated features. Altogether there are a large number of error surfaces for the many cases. These are provided in full on a companion website, which is meant to serve as resource for those working with small-sample classification. For the companion website, please visit http://public.tgen.org/tamu/ofs/ e-dougherty@ee.tamu.edu.

Signal Analysis Algorithms for Optimized Fitting of Nonresonant Laser Induced Thermal Acoustics Damped Sinusoids

NASA Technical Reports Server (NTRS)

Balla, R. Jeffrey; Miller, Corey A.

2008-01-01

This study seeks a numerical algorithm which optimizes frequency precision for the damped sinusoids generated by the nonresonant LITA technique. It compares computed frequencies, frequency errors, and fit errors obtained using five primary signal analysis methods. Using variations on different algorithms within each primary method, results from 73 fits are presented. Best results are obtained using an AutoRegressive method. Compared to previous results using Prony s method, single shot waveform frequencies are reduced approx.0.4% and frequency errors are reduced by a factor of approx.20 at 303K to approx. 0.1%. We explore the advantages of high waveform sample rates and potential for measurements in low density gases.

Long-term care physical environments--effect on medication errors.

PubMed

Mahmood, Atiya; Chaudhury, Habib; Gaumont, Alana; Rust, Tiana

2012-01-01

Few studies examine physical environmental factors and their effects on staff health, effectiveness, work errors and job satisfaction. To address this gap, this study aims to examine environmental features and their role in medication and nursing errors in long-term care facilities. A mixed methodological strategy was used. Data were collected via focus groups, observing medication preparation and administration, and a nursing staff survey in four facilities. The paper reveals that, during the medication preparation phase, physical design, such as medication room layout, is a major source of potential errors. During medication administration, social environment is more likely to contribute to errors. Interruptions, noise and staff shortages were particular problems. The survey's relatively small sample size needs to be considered when interpreting the findings. Also, actual error data could not be included as existing records were incomplete. The study offers several relatively low-cost recommendations to help staff reduce medication errors. Physical environmental factors are important when addressing measures to reduce errors. The findings of this study underscore the fact that the physical environment's influence on the possibility of medication errors is often neglected. This study contributes to the scarce empirical literature examining the relationship between physical design and patient safety.

Effects of tree-to-tree variations on sap flux-based transpiration estimates in a forested watershed

NASA Astrophysics Data System (ADS)

Kume, Tomonori; Tsuruta, Kenji; Komatsu, Hikaru; Kumagai, Tomo'omi; Higashi, Naoko; Shinohara, Yoshinori; Otsuki, Kyoichi

2010-05-01

To estimate forest stand-scale water use, we assessed how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (Fd) and sapwood area (AS_tree) measurements of individual trees. In a Japanese cypress plantation, we measured Fd and AS_tree in all trees (n = 58) within a 20 × 20 m study plot, which was divided into four 10 × 10 subplots. We calculated E from stand AS_tree (AS_stand) and mean stand Fd (JS) values. Using Monte Carlo analyses, we examined potential errors associated with sample sizes in E, AS_stand, and JS by using the original AS_tree and Fd data sets. Consequently, we defined optimal sample sizes of 10 and 15 for AS_stand and JS estimates, respectively, in the 20 × 20 m plot. Sample sizes greater than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for JS changed according to plot size (e.g., 10 × 10 m and 10 × 20 m), while the optimal sample sizes for AS_stand did not. As well, the optimal sample sizes for JS did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in Fd vary among different plots, and that plot size to capture tree-to-tree variations in Fd is an important factor. This study also discusses planning balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.

Energy Storage Sizing Taking Into Account Forecast Uncertainties and Receding Horizon Operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baker, Kyri; Hug, Gabriela; Li, Xin

Energy storage systems (ESS) have the potential to be very beneficial for applications such as reducing the ramping of generators, peak shaving, and balancing not only the variability introduced by renewable energy sources, but also the uncertainty introduced by errors in their forecasts. Optimal usage of storage may result in reduced generation costs and an increased use of renewable energy. However, optimally sizing these devices is a challenging problem. This paper aims to provide the tools to optimally size an ESS under the assumption that it will be operated under a model predictive control scheme and that the forecast ofmore » the renewable energy resources include prediction errors. A two-stage stochastic model predictive control is formulated and solved, where the optimal usage of the storage is simultaneously determined along with the optimal generation outputs and size of the storage. Wind forecast errors are taken into account in the optimization problem via probabilistic constraints for which an analytical form is derived. This allows for the stochastic optimization problem to be solved directly, without using sampling-based approaches, and sizing the storage to account not only for a wide range of potential scenarios, but also for a wide range of potential forecast errors. In the proposed formulation, we account for the fact that errors in the forecast affect how the device is operated later in the horizon and that a receding horizon scheme is used in operation to optimally use the available storage.« less

Analysis of Compression Algorithm in Ground Collision Avoidance Systems (Auto-GCAS)

NASA Technical Reports Server (NTRS)

Schmalz, Tyler; Ryan, Jack

2011-01-01

Automatic Ground Collision Avoidance Systems (Auto-GCAS) utilizes Digital Terrain Elevation Data (DTED) stored onboard a plane to determine potential recovery maneuvers. Because of the current limitations of computer hardware on military airplanes such as the F-22 and F-35, the DTED must be compressed through a lossy technique called binary-tree tip-tilt. The purpose of this study is to determine the accuracy of the compressed data with respect to the original DTED. This study is mainly interested in the magnitude of the error between the two as well as the overall distribution of the errors throughout the DTED. By understanding how the errors of the compression technique are affected by various factors (topography, density of sampling points, sub-sampling techniques, etc.), modifications can be made to the compression technique resulting in better accuracy. This, in turn, would minimize unnecessary activation of A-GCAS during flight as well as maximizing its contribution to fighter safety.

Type I error probability spending for post-market drug and vaccine safety surveillance with binomial data.

PubMed

Silva, Ivair R

2018-01-15

Type I error probability spending functions are commonly used for designing sequential analysis of binomial data in clinical trials, but it is also quickly emerging for near-continuous sequential analysis of post-market drug and vaccine safety surveillance. It is well known that, for clinical trials, when the null hypothesis is not rejected, it is still important to minimize the sample size. Unlike in post-market drug and vaccine safety surveillance, that is not important. In post-market safety surveillance, specially when the surveillance involves identification of potential signals, the meaningful statistical performance measure to be minimized is the expected sample size when the null hypothesis is rejected. The present paper shows that, instead of the convex Type I error spending shape conventionally used in clinical trials, a concave shape is more indicated for post-market drug and vaccine safety surveillance. This is shown for both, continuous and group sequential analysis. Copyright © 2017 John Wiley & Sons, Ltd.

The potential for error in sampling

Treesearch

Jack Lewis

2000-01-01

Editor's note: The measurement of water quality parameters in environmental laboratories follows standard quality control protocols using methodologies approved by the U.S. Environmental Protection Agency. However, little attention has been given to quality assurance and quality control in activities outside the laboratory. This article describes some of those...

Brief communication: the relation between standard error of the estimate and sample size of histomorphometric aging methods.

PubMed

Hennig, Cheryl; Cooper, David

2011-08-01

Histomorphometric aging methods report varying degrees of precision, measured through Standard Error of the Estimate (SEE). These techniques have been developed from variable samples sizes (n) and the impact of n on reported aging precision has not been rigorously examined in the anthropological literature. This brief communication explores the relation between n and SEE through a review of the literature (abstracts, articles, book chapters, theses, and dissertations), predictions based upon sampling theory and a simulation. Published SEE values for age prediction, derived from 40 studies, range from 1.51 to 16.48 years (mean 8.63; sd: 3.81 years). In general, these values are widely distributed for smaller samples and the distribution narrows as n increases--a pattern expected from sampling theory. For the two studies that have samples in excess of 200 individuals, the SEE values are very similar (10.08 and 11.10 years) with a mean of 10.59 years. Assuming this mean value is a 'true' characterization of the error at the population level, the 95% confidence intervals for SEE values from samples of 10, 50, and 150 individuals are on the order of ± 4.2, 1.7, and 1.0 years, respectively. While numerous sources of variation potentially affect the precision of different methods, the impact of sample size cannot be overlooked. The uncertainty associated with SEE values derived from smaller samples complicates the comparison of approaches based upon different methodology and/or skeletal elements. Meaningful comparisons require larger samples than have frequently been used and should ideally be based upon standardized samples. Copyright © 2011 Wiley-Liss, Inc.

The potential for geostationary remote sensing of NO2 to improve weather prediction

NASA Astrophysics Data System (ADS)

Liu, X.; Mizzi, A. P.; Anderson, J. L.; Fung, I. Y.; Cohen, R. C.

2017-12-01

Observations of surface winds remain sparse making it challenging to simulate and predict the weather in circumstances of light winds that are most important for poor air quality. Direct measurements of short-lived chemicals from space might be a solution to this challenge. Here we investigate the application of data assimilation of NO­2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of surface wind fields. Specifically, synthetic NO2 observations are sampled from a "nature run (NR)" regarded as the true atmosphere. Then NO2 observations are assimilated using EAKF methods into a "control run (CR)" which differs from the NR in the wind field. Wind errors are generated by introducing (1) errors in the initial conditions, (2) creating a model error by using two different formulations for the planetary boundary layer, (3) and by combining both of these effects. Assimilation of NO2 column observations succeeds in reducing wind errors, indicating the prospects for future geostationary atmospheric composition measurements to improve weather forecasting are substantial. We find that due to the temporal heterogeneity of wind errors, the success of this application favors chemical observations of high frequency, such as those from geostationary platform. We also show the potential to improve soil moisture field by assimilating NO­2 columns.

Lead theft--a study of the "uniqueness" of lead from church roofs.

PubMed

Bond, John W; Hainsworth, Sarah V; Lau, Tien L

2013-07-01

In the United Kingdom, theft of lead is common, particularly from churches and other public buildings with lead roofs. To assess the potential to distinguish lead from different sources, 41 samples of lead from 24 church roofs in Northamptonshire, U.K, have been analyzed for relative abundance of trace elements and isotopes of lead using X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry, respectively. XRF revealed the overall presence of 12 trace elements with the four most abundant, calcium, phosphorus, silicon, and sulfur, showing a large weight percentage standard error of the mean of all samples suggesting variation in the weight percentage of these elements between different church roofs. Multiple samples from the same roofs, but different lead sheets, showed much lower weight percentage standard errors of the mean suggesting similar trace element concentrations. Lead isotope ratios were similar for all samples. Factors likely to affect the occurrence of these trace elements are discussed. © 2013 American Academy of Forensic Sciences.

Experimental verification of stopping-power prediction from single- and dual-energy computed tomography in biological tissues

NASA Astrophysics Data System (ADS)

Möhler, Christian; Russ, Tom; Wohlfahrt, Patrick; Elter, Alina; Runz, Armin; Richter, Christian; Greilich, Steffen

2018-01-01

An experimental setup for consecutive measurement of ion and x-ray absorption in tissue or other materials is introduced. With this setup using a 3D-printed sample container, the reference stopping-power ratio (SPR) of materials can be measured with an uncertainty of below 0.1%. A total of 65 porcine and bovine tissue samples were prepared for measurement, comprising five samples each of 13 tissue types representing about 80% of the total body mass (three different muscle and fatty tissues, liver, kidney, brain, heart, blood, lung and bone). Using a standard stoichiometric calibration for single-energy CT (SECT) as well as a state-of-the-art dual-energy CT (DECT) approach, SPR was predicted for all tissues and then compared to the measured reference. With the SECT approach, the SPRs of all tissues were predicted with a mean error of (-0.84  ±  0.12)% and a mean absolute error of (1.27  ±  0.12)%. In contrast, the DECT-based SPR predictions were overall consistent with the measured reference with a mean error of (-0.02  ±  0.15)% and a mean absolute error of (0.10  ±  0.15)%. Thus, in this study, the potential of DECT to decrease range uncertainty could be confirmed in biological tissue.

Gram-stain plus MALDI-TOF MS (Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry) for a rapid diagnosis of urinary tract infection.

PubMed

Burillo, Almudena; Rodríguez-Sánchez, Belén; Ramiro, Ana; Cercenado, Emilia; Rodríguez-Créixems, Marta; Bouza, Emilio

2014-01-01

Microbiological confirmation of a urinary tract infection (UTI) takes 24-48 h. In the meantime, patients are usually given empirical antibiotics, sometimes inappropriately. We assessed the feasibility of sequentially performing a Gram stain and MALDI-TOF MS mass spectrometry (MS) on urine samples to anticipate clinically useful information. In May-June 2012, we randomly selected 1000 urine samples from patients with suspected UTI. All were Gram stained and those yielding bacteria of a single morphotype were processed for MALDI-TOF MS. Our sequential algorithm was correlated with the standard semiquantitative urine culture result as follows: Match, the information provided was anticipative of culture result; Minor error, the information provided was partially anticipative of culture result; Major error, the information provided was incorrect, potentially leading to inappropriate changes in antimicrobial therapy. A positive culture was obtained in 242/1000 samples. The Gram stain revealed a single morphotype in 207 samples, which were subjected to MALDI-TOF MS. The diagnostic performance of the Gram stain was: sensitivity (Se) 81.3%, specificity (Sp) 93.2%, positive predictive value (PPV) 81.3%, negative predictive value (NPV) 93.2%, positive likelihood ratio (+LR) 11.91, negative likelihood ratio (-LR) 0.20 and accuracy 90.0% while that of MALDI-TOF MS was: Se 79.2%, Sp 73.5, +LR 2.99, -LR 0.28 and accuracy 78.3%. The use of both techniques provided information anticipative of the culture result in 82.7% of cases, information with minor errors in 13.4% and information with major errors in 3.9%. Results were available within 1 h. Our serial algorithm provided information that was consistent or showed minor errors for 96.1% of urine samples from patients with suspected UTI. The clinical impacts of this rapid UTI diagnosis strategy need to be assessed through indicators of adequacy of treatment such as a reduced time to appropriate empirical treatment or earlier withdrawal of unnecessary antibiotics.

Data-quality measures for stakeholder-implemented watershed-monitoring programs

USGS Publications Warehouse

Greve, Adrienne I.

2002-01-01

Community-based watershed groups, many of which collect environmental data, have steadily increased in number over the last decade. The data generated by these programs are often underutilized due to uncertainty in the quality of data produced. The incorporation of data-quality measures into stakeholder monitoring programs lends statistical validity to data. Data-quality measures are divided into three steps: quality assurance, quality control, and quality assessment. The quality-assurance step attempts to control sources of error that cannot be directly quantified. This step is part of the design phase of a monitoring program and includes clearly defined, quantifiable objectives, sampling sites that meet the objectives, standardized protocols for sample collection, and standardized laboratory methods. Quality control (QC) is the collection of samples to assess the magnitude of error in a data set due to sampling, processing, transport, and analysis. In order to design a QC sampling program, a series of issues needs to be considered: (1) potential sources of error, (2) the type of QC samples, (3) inference space, (4) the number of QC samples, and (5) the distribution of the QC samples. Quality assessment is the process of evaluating quality-assurance measures and analyzing the QC data in order to interpret the environmental data. Quality assessment has two parts: one that is conducted on an ongoing basis as the monitoring program is running, and one that is conducted during the analysis of environmental data. The discussion of the data-quality measures is followed by an example of their application to a monitoring program in the Big Thompson River watershed of northern Colorado.

Satellite Sampling and Retrieval Errors in Regional Monthly Rain Estimates from TMI AMSR-E, SSM/I, AMSU-B and the TRMM PR

NASA Technical Reports Server (NTRS)

Fisher, Brad; Wolff, David B.

2010-01-01

Passive and active microwave rain sensors onboard earth-orbiting satellites estimate monthly rainfall from the instantaneous rain statistics collected during satellite overpasses. It is well known that climate-scale rain estimates from meteorological satellites incur sampling errors resulting from the process of discrete temporal sampling and statistical averaging. Sampling and retrieval errors ultimately become entangled in the estimation of the mean monthly rain rate. The sampling component of the error budget effectively introduces statistical noise into climate-scale rain estimates that obscure the error component associated with the instantaneous rain retrieval. Estimating the accuracy of the retrievals on monthly scales therefore necessitates a decomposition of the total error budget into sampling and retrieval error quantities. This paper presents results from a statistical evaluation of the sampling and retrieval errors for five different space-borne rain sensors on board nine orbiting satellites. Using an error decomposition methodology developed by one of the authors, sampling and retrieval errors were estimated at 0.25 resolution within 150 km of ground-based weather radars located at Kwajalein, Marshall Islands and Melbourne, Florida. Error and bias statistics were calculated according to the land, ocean and coast classifications of the surface terrain mask developed for the Goddard Profiling (GPROF) rain algorithm. Variations in the comparative error statistics are attributed to various factors related to differences in the swath geometry of each rain sensor, the orbital and instrument characteristics of the satellite and the regional climatology. The most significant result from this study found that each of the satellites incurred negative longterm oceanic retrieval biases of 10 to 30%.

Prevalence and types of preanalytical error in hematology laboratory of a tertiary care hospital in South India.

PubMed

Arul, Pitchaikaran; Pushparaj, Magesh; Pandian, Kanmani; Chennimalai, Lingasamy; Rajendran, Karthika; Selvaraj, Eniya; Masilamani, Suresh

2018-01-01

An important component of laboratory medicine is preanalytical phase. Since laboratory report plays a major role in patient management, more importance should be given to the quality of laboratory tests. The present study was undertaken to find the prevalence and types of preanalytical errors at a tertiary care hospital in South India. In this cross-sectional study, a total of 118,732 samples ([62,474 outpatient department [OPD] and 56,258 inpatient department [IPD]) were received in hematology laboratory. These samples were analyzed for preanalytical errors such as misidentification, incorrect vials, inadequate samples, clotted samples, diluted samples, and hemolyzed samples. The overall prevalence of preanalytical errors found was 513 samples, which is 0.43% of the total number of samples received. The most common preanalytical error observed was inadequate samples followed by clotted samples. Overall frequencies (both OPD and IPD) of preanalytical errors such as misidentification, incorrect vials, inadequate samples, clotted samples, diluted samples, and hemolyzed samples were 0.02%, 0.05%, 0.2%, 0.12%, 0.02%, and 0.03%, respectively. The present study concluded that incorrect phlebotomy techniques due to lack of awareness is the main reason for preanalytical errors. This can be avoided by proper communication and coordination between laboratory and wards, proper training and continuing medical education programs for laboratory and paramedical staffs, and knowledge of the intervening factors that can influence laboratory results.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Quality Assurance of NCI Thesaurus by Mining Structural-Lexical Patterns

PubMed Central

Abeysinghe, Rashmie; Brooks, Michael A.; Talbert, Jeffery; Licong, Cui

2017-01-01

Quality assurance of biomedical terminologies such as the National Cancer Institute (NCI) Thesaurus is an essential part of the terminology management lifecycle. We investigate a structural-lexical approach based on non-lattice subgraphs to automatically identify missing hierarchical relations and missing concepts in the NCI Thesaurus. We mine six structural-lexical patterns exhibiting in non-lattice subgraphs: containment, union, intersection, union-intersection, inference-contradiction, and inference union. Each pattern indicates a potential specific type of error and suggests a potential type of remediation. We found 809 non-lattice subgraphs with these patterns in the NCI Thesaurus (version 16.12d). Domain experts evaluated a random sample of 50 small non-lattice subgraphs, of which 33 were confirmed to contain errors and make correct suggestions (33/50 = 66%). Of the 25 evaluated subgraphs revealing multiple patterns, 22 were verified correct (22/25 = 88%). This shows the effectiveness of our structurallexical-pattern-based approach in detecting errors and suggesting remediations in the NCI Thesaurus. PMID:29854100

The Measurement of Ammonia in Human Breath and its Potential in Clinical Diagnostics.

PubMed

Brannelly, N T; Hamilton-Shield, J P; Killard, A J

2016-11-01

Ammonia is an important component of metabolism and is involved in many physiological processes. During normal physiology, levels of blood ammonia are between 11 and 50 µM. Elevated blood ammonia levels are associated with a variety of pathological conditions such as liver and kidney dysfunction, Reye's syndrome and a variety of inborn errors of metabolism including urea cycle disorders (UCD), organic acidaemias and hyperinsulinism/hyperammonaemia syndrome in which ammonia may reach levels in excess of 1 mM. It is highly neurotoxic and so effective measurement is critical for assessing and monitoring disease severity and treatment. Ammonia is also a potential biomarker in exercise physiology and studies of drug metabolism. Current ammonia testing is based on blood sampling, which is inconvenient and can be subject to significant analytical errors due to the quality of the sample draw, its handling and preparation for analysis. Blood ammonia is in gaseous equilibrium with the lungs. Recent research has demonstrated the potential use of breath ammonia as a non-invasive means of measuring systemic ammonia. This requires measurement of ammonia in real breath samples with associated temperature, humidity and gas characteristics at concentrations between 50 and several thousand parts per billion. This review explores the diagnostic applications of ammonia measurement and the impact that the move from blood to breath analysis could have on how these processes and diseases are studied and managed.

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

Preanalytical Errors in Hematology Laboratory- an Avoidable Incompetence.

PubMed

HarsimranKaur, Vikram Narang; Selhi, Pavneet Kaur; Sood, Neena; Singh, Aminder

2016-01-01

Quality assurance in the hematology laboratory is a must to ensure laboratory users of reliable test results with high degree of precision and accuracy. Even after so many advances in hematology laboratory practice, pre-analytical errors remain a challenge for practicing pathologists. This study was undertaken with an objective to evaluate the types and frequency of preanalytical errors in hematology laboratory of our center. All the samples received in the Hematology Laboratory of Dayanand Medical College and Hospital, Ludhiana, India over a period of one year (July 2013-July 2014) were included in the study and preanalytical variables like clotted samples, quantity not sufficient, wrong sample, without label, wrong label were studied. Of 471,006 samples received in the laboratory, preanalytical errors, as per the above mentioned categories was found in 1802 samples. The most common error was clotted samples (1332 samples, 0.28% of the total samples) followed by quantity not sufficient (328 sample, 0.06%), wrong sample (96 samples, 0.02%), without label (24 samples, 0.005%) and wrong label (22 samples, 0.005%). Preanalytical errors are frequent in laboratories and can be corrected by regular analysis of the variables involved. Rectification can be done by regular education of the staff.

Removing systematic errors in interionic potentials of mean force computed in molecular simulations using reaction-field-based electrostatics

PubMed Central

Baumketner, Andrij

2009-01-01

The performance of reaction-field methods to treat electrostatic interactions is tested in simulations of ions solvated in water. The potential of mean force between sodium chloride pair of ions and between side chains of lysine and aspartate are computed using umbrella sampling and molecular dynamics simulations. It is found that in comparison with lattice sum calculations, the charge-group-based approaches to reaction-field treatments produce a large error in the association energy of the ions that exhibits strong systematic dependence on the size of the simulation box. The atom-based implementation of the reaction field is seen to (i) improve the overall quality of the potential of mean force and (ii) remove the dependence on the size of the simulation box. It is suggested that the atom-based truncation be used in reaction-field simulations of mixed media. PMID:19292522

Measuring myokines with cardiovascular functions: pre-analytical variables affecting the analytical output.

PubMed

Lombardi, Giovanni; Sansoni, Veronica; Banfi, Giuseppe

2017-08-01

In the last few years, a growing number of molecules have been associated to an endocrine function of the skeletal muscle. Circulating myokine levels, in turn, have been associated with several pathophysiological conditions including the cardiovascular ones. However, data from different studies are often not completely comparable or even discordant. This would be due, at least in part, to the whole set of situations related to the preparation of the patient prior to blood sampling, blood sampling procedure, processing and/or store. This entire process constitutes the pre-analytical phase. The importance of the pre-analytical phase is often not considered. However, in routine diagnostics, the 70% of the errors are in this phase. Moreover, errors during the pre-analytical phase are carried over in the analytical phase and affects the final output. In research, for example, when samples are collected over a long time and by different laboratories, a standardized procedure for sample collecting and the correct procedure for sample storage are acknowledged. In this review, we discuss the pre-analytical variables potentially affecting the measurement of myokines with cardiovascular functions.

Identifying the causes of road crashes in Europe

PubMed Central

Thomas, Pete; Morris, Andrew; Talbot, Rachel; Fagerlind, Helen

2013-01-01

This research applies a recently developed model of accident causation, developed to investigate industrial accidents, to a specially gathered sample of 997 crashes investigated in-depth in 6 countries. Based on the work of Hollnagel the model considers a collision to be a consequence of a breakdown in the interaction between road users, vehicles and the organisation of the traffic environment. 54% of road users experienced interpretation errors while 44% made observation errors and 37% planning errors. In contrast to other studies only 11% of drivers were identified as distracted and 8% inattentive. There was remarkably little variation in these errors between the main road user types. The application of the model to future in-depth crash studies offers the opportunity to identify new measures to improve safety and to mitigate the social impact of collisions. Examples given include the potential value of co-driver advisory technologies to reduce observation errors and predictive technologies to avoid conflicting interactions between road users. PMID:24406942

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

NASA Technical Reports Server (NTRS)

Holdaway, Daniel; Yang, Yuekui

2016-01-01

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

Potential of near-infrared hyperspectral reflectance imaging for screening of farm feed contamination

NASA Astrophysics Data System (ADS)

Wang, Wenbo; Paliwal, Jitendra

2005-09-01

With the outbreak of Bovine Spongiform Encephalopathy (BSE) (commonly known as mad cow disease) in 1987 in the United Kingdom and a recent case discovered in Alberta, more and more emphasis is placed on food and farm feed quality and safety issues internationally. The disease is believed to be spread through farm feed contamination by animal byproducts in the form of meat-and-bone-meal (MBM). The paper reviewed the available techniques necessary to the enforcement of legislation concerning the feed safety issues. The standard microscopy method, although highly sensitive, is laborious and costly. A method to routinely screen farm feed contamination certainly helps to reduce the complexity of safety inspection. A hyperspectral imaging system working in the near-infrared wavelength region of 1100-1600 nm was used to study the possibility of detection of ground broiler feed contamination by ground pork. Hyperspectral images of raw broiler feed, ground broiler feed, ground pork, and contaminated feed samples were acquired. Raw broiler feed samples were found to possess comparatively large spectral variations due to light scattering effect. Ground feed adulterated with 1%, 3%, 5%, and 10% of ground pork was tested to identify feed contamination. Discriminant analysis using Mahalanobis distance showed that the model trained using pure ground feed samples and pure ground pork samples resulted in 100% false negative errors for all test replicates of contaminated samples. A discriminant model trained with pure ground feed samples and 10% contamination level samples resulted in 12.5% false positive error and 0% false negative error.

An error criterion for determining sampling rates in closed-loop control systems

NASA Technical Reports Server (NTRS)

Brecher, S. M.

1972-01-01

The determination of an error criterion which will give a sampling rate for adequate performance of linear, time-invariant closed-loop, discrete-data control systems was studied. The proper modelling of the closed-loop control system for characterization of the error behavior, and the determination of an absolute error definition for performance of the two commonly used holding devices are discussed. The definition of an adequate relative error criterion as a function of the sampling rate and the parameters characterizing the system is established along with the determination of sampling rates. The validity of the expressions for the sampling interval was confirmed by computer simulations. Their application solves the problem of making a first choice in the selection of sampling rates.

Prevalence of Pre-Analytical Errors in Clinical Chemistry Diagnostic Labs in Sulaimani City of Iraqi Kurdistan

PubMed Central

2017-01-01

Background Laboratory testing is roughly divided into three phases: a pre-analytical phase, an analytical phase and a post-analytical phase. Most analytical errors have been attributed to the analytical phase. However, recent studies have shown that up to 70% of analytical errors reflect the pre-analytical phase. The pre-analytical phase comprises all processes from the time a laboratory request is made by a physician until the specimen is analyzed at the lab. Generally, the pre-analytical phase includes patient preparation, specimen transportation, specimen collection and storage. In the present study, we report the first comprehensive assessment of the frequency and types of pre-analytical errors at the Sulaimani diagnostic labs in Iraqi Kurdistan. Materials and Methods Over 2 months, 5500 venous blood samples were observed in 10 public diagnostic labs of Sulaimani City. The percentages of rejected samples and types of sample inappropriateness were evaluated. The percentage of each of the following pre-analytical errors were recorded: delay in sample transportation, clotted samples, expired reagents, hemolyzed samples, samples not on ice, incorrect sample identification, insufficient sample, tube broken in centrifuge, request procedure errors, sample mix-ups, communication conflicts, misinterpreted orders, lipemic samples, contaminated samples and missed physician’s request orders. The difference between the relative frequencies of errors observed in the hospitals considered was tested using a proportional Z test. In particular, the survey aimed to discover whether analytical errors were recorded and examine the types of platforms used in the selected diagnostic labs. Results The analysis showed a high prevalence of improper sample handling during the pre-analytical phase. In appropriate samples, the percentage error was as high as 39%. The major reasons for rejection were hemolyzed samples (9%), incorrect sample identification (8%) and clotted samples (6%). Most quality control schemes at Sulaimani hospitals focus only on the analytical phase, and none of the pre-analytical errors were recorded. Interestingly, none of the labs were internationally accredited; therefore, corrective actions are needed at these hospitals to ensure better health outcomes. Internal and External Quality Assessment Schemes (EQAS) for the pre-analytical phase at Sulaimani clinical laboratories should be implemented at public hospitals. Furthermore, lab personnel, particularly phlebotomists, need continuous training on the importance of sample quality to obtain accurate test results. PMID:28107395

Prevalence of Pre-Analytical Errors in Clinical Chemistry Diagnostic Labs in Sulaimani City of Iraqi Kurdistan.

PubMed

Najat, Dereen

2017-01-01

Laboratory testing is roughly divided into three phases: a pre-analytical phase, an analytical phase and a post-analytical phase. Most analytical errors have been attributed to the analytical phase. However, recent studies have shown that up to 70% of analytical errors reflect the pre-analytical phase. The pre-analytical phase comprises all processes from the time a laboratory request is made by a physician until the specimen is analyzed at the lab. Generally, the pre-analytical phase includes patient preparation, specimen transportation, specimen collection and storage. In the present study, we report the first comprehensive assessment of the frequency and types of pre-analytical errors at the Sulaimani diagnostic labs in Iraqi Kurdistan. Over 2 months, 5500 venous blood samples were observed in 10 public diagnostic labs of Sulaimani City. The percentages of rejected samples and types of sample inappropriateness were evaluated. The percentage of each of the following pre-analytical errors were recorded: delay in sample transportation, clotted samples, expired reagents, hemolyzed samples, samples not on ice, incorrect sample identification, insufficient sample, tube broken in centrifuge, request procedure errors, sample mix-ups, communication conflicts, misinterpreted orders, lipemic samples, contaminated samples and missed physician's request orders. The difference between the relative frequencies of errors observed in the hospitals considered was tested using a proportional Z test. In particular, the survey aimed to discover whether analytical errors were recorded and examine the types of platforms used in the selected diagnostic labs. The analysis showed a high prevalence of improper sample handling during the pre-analytical phase. In appropriate samples, the percentage error was as high as 39%. The major reasons for rejection were hemolyzed samples (9%), incorrect sample identification (8%) and clotted samples (6%). Most quality control schemes at Sulaimani hospitals focus only on the analytical phase, and none of the pre-analytical errors were recorded. Interestingly, none of the labs were internationally accredited; therefore, corrective actions are needed at these hospitals to ensure better health outcomes. Internal and External Quality Assessment Schemes (EQAS) for the pre-analytical phase at Sulaimani clinical laboratories should be implemented at public hospitals. Furthermore, lab personnel, particularly phlebotomists, need continuous training on the importance of sample quality to obtain accurate test results.

Experimental investigation of observation error in anuran call surveys

USGS Publications Warehouse

McClintock, B.T.; Bailey, L.L.; Pollock, K.H.; Simons, T.R.

2010-01-01

Occupancy models that account for imperfect detection are often used to monitor anuran and songbird species occurrence. However, presenceabsence data arising from auditory detections may be more prone to observation error (e.g., false-positive detections) than are sampling approaches utilizing physical captures or sightings of individuals. We conducted realistic, replicated field experiments using a remote broadcasting system to simulate simple anuran call surveys and to investigate potential factors affecting observation error in these studies. Distance, time, ambient noise, and observer abilities were the most important factors explaining false-negative detections. Distance and observer ability were the best overall predictors of false-positive errors, but ambient noise and competing species also affected error rates for some species. False-positive errors made up 5 of all positive detections, with individual observers exhibiting false-positive rates between 0.5 and 14. Previous research suggests false-positive errors of these magnitudes would induce substantial positive biases in standard estimators of species occurrence, and we recommend practices to mitigate for false positives when developing occupancy monitoring protocols that rely on auditory detections. These recommendations include additional observer training, limiting the number of target species, and establishing distance and ambient noise thresholds during surveys. ?? 2010 The Wildlife Society.

78 FR 28597 - State Median Income Estimates for a Four-Person Household: Notice of the Federal Fiscal Year (FFY...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-15

....gov/acs/www/ or contact the Census Bureau's Social, Economic, and Housing Statistics Division at (301...) Sampling Error, which consists of the error that arises from the use of probability sampling to create the... direction; and (2) Sampling Error, which consists of the error that arises from the use of probability...

Cancer diagnosis by infrared spectroscopy: methodological aspects

NASA Astrophysics Data System (ADS)

Jackson, Michael; Kim, Keith; Tetteh, John; Mansfield, James R.; Dolenko, Brion; Somorjai, Raymond L.; Orr, F. W.; Watson, Peter H.; Mantsch, Henry H.

1998-04-01

IR spectroscopy is proving to be a powerful tool for the study and diagnosis of cancer. The application of IR spectroscopy to the analysis of cultured tumor cells and grading of breast cancer sections is outlined. Potential sources of error in spectral interpretation due to variations in sample histology and artifacts associated with sample storage and preparation are discussed. The application of statistical techniques to assess differences between spectra and to non-subjectively classify spectra is demonstrated.

Toward optical guidance during endoscopic ultrasound-guided fine needle aspirations of pancreatic masses using single fiber reflectance spectroscopy: a feasibility study

NASA Astrophysics Data System (ADS)

Stegehuis, Paulien L.; Boogerd, Leonora S. F.; Inderson, Akin; Veenendaal, Roeland A.; van Gerven, P.; Bonsing, Bert A.; Sven Mieog, J.; Amelink, Arjen; Veselic, Maud; Morreau, Hans; van de Velde, Cornelis J. H.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke; Robinson, Dominic J.; Vahrmeijer, Alexander L.

2017-02-01

Endoscopic ultrasound-guided fine needle aspirations (EUS-FNA) of pancreatic masses suffer from sample errors and low-negative predictive values. Fiber-optic spectroscopy in the visible to near-infrared wavelength spectrum can noninvasively extract physiological parameters from tissue and has the potential to guide the sampling process and reduce sample errors. We assessed the feasibility of single fiber (SF) reflectance spectroscopy measurements during EUS-FNA of pancreatic masses and its ability to distinguish benign from malignant pancreatic tissue. A single optical fiber was placed inside a 19-gauge biopsy needle during EUS-FNA and at least three reflectance measurements were taken prior to FNA. Spectroscopy measurements did not cause any related adverse events and prolonged procedure time with ˜5 min. An accurate correlation between spectroscopy measurements and cytology could be made in nine patients (three benign and six malignant). The oxygen saturation and bilirubin concentration were significantly higher in benign tissue compared with malignant tissue (55% versus 21%, p=0.038; 166 μmol/L versus 17 μmol/L, p=0.039, respectively). To conclude, incorporation of SF spectroscopy during EUS-FNA was feasible, safe, and relatively quick to perform. The optical properties of benign and malignant pancreatic tissue are different, implying that SF spectroscopy can potentially guide the FNA sampling.

Quantifying Differences in the Impact of Variable Chemistry on Equilibrium Uranium(VI) Adsorption Properties of Aquifer Sediments

PubMed Central

2011-01-01

Uranium adsorption–desorption on sediment samples collected from the Hanford 300-Area, Richland, WA varied extensively over a range of field-relevant chemical conditions, complicating assessment of possible differences in equilibrium adsorption properties. Adsorption equilibrium was achieved in 500–1000 h although dissolved uranium concentrations increased over thousands of hours owing to changes in aqueous chemical composition driven by sediment-water reactions. A nonelectrostatic surface complexation reaction, >SOH + UO22+ + 2CO32- = >SOUO2(CO3HCO3)2–, provided the best fit to experimental data for each sediment sample resulting in a range of conditional equilibrium constants (logKc) from 21.49 to 21.76. Potential differences in uranium adsorption properties could be assessed in plots based on the generalized mass-action expressions yielding linear trends displaced vertically by differences in logKc values. Using this approach, logKc values for seven sediment samples were not significantly different. However, a significant difference in adsorption properties between one sediment sample and the fines (<0.063 mm) of another could be demonstrated despite the fines requiring a different reaction stoichiometry. Estimates of logKc uncertainty were improved by capturing all data points within experimental errors. The mass-action expression plots demonstrate that applying models outside the range of conditions used in model calibration greatly increases potential errors. PMID:21923109

Quantifying differences in the impact of variable chemistry on equilibrium Uranium(VI) adsorption properties of aquifer sediments.

PubMed

Stoliker, Deborah L; Kent, Douglas B; Zachara, John M

2011-10-15

Uranium adsorption-desorption on sediment samples collected from the Hanford 300-Area, Richland, WA varied extensively over a range of field-relevant chemical conditions, complicating assessment of possible differences in equilibrium adsorption properties. Adsorption equilibrium was achieved in 500-1000 h although dissolved uranium concentrations increased over thousands of hours owing to changes in aqueous chemical composition driven by sediment-water reactions. A nonelectrostatic surface complexation reaction, >SOH + UO₂²⁺ + 2CO₃²⁻ = >SOUO₂(CO₃HCO₃)²⁻, provided the best fit to experimental data for each sediment sample resulting in a range of conditional equilibrium constants (logK(c)) from 21.49 to 21.76. Potential differences in uranium adsorption properties could be assessed in plots based on the generalized mass-action expressions yielding linear trends displaced vertically by differences in logK(c) values. Using this approach, logK(c) values for seven sediment samples were not significantly different. However, a significant difference in adsorption properties between one sediment sample and the fines (< 0.063 mm) of another could be demonstrated despite the fines requiring a different reaction stoichiometry. Estimates of logK(c) uncertainty were improved by capturing all data points within experimental errors. The mass-action expression plots demonstrate that applying models outside the range of conditions used in model calibration greatly increases potential errors.

Metadynamics convergence law in a multidimensional system

NASA Astrophysics Data System (ADS)

Crespo, Yanier; Marinelli, Fabrizio; Pietrucci, Fabio; Laio, Alessandro

2010-05-01

Metadynamics is a powerful sampling technique that uses a nonequilibrium history-dependent process to reconstruct the free-energy surface as a function of the relevant collective variables s . In Bussi [Phys. Rev. Lett. 96, 090601 (2006)] it is proved that, in a Langevin process, metadynamics provides an unbiased estimate of the free energy F(s) . We here study the convergence properties of this approach in a multidimensional system, with a Hamiltonian depending on several variables. Specifically, we show that in a Monte Carlo metadynamics simulation of an Ising model the time average of the history-dependent potential converge to F(s) with the same law of an umbrella sampling performed in optimal conditions (i.e., with a bias exactly equal to the negative of the free energy). Remarkably, after a short transient, the error becomes approximately independent on the filling speed, showing that even in out-of-equilibrium conditions metadynamics allows recovering an accurate estimate of F(s) . These results have been obtained introducing a functional form of the history-dependent potential that avoids the onset of systematic errors near the boundaries of the free-energy landscape.

Metadynamics convergence law in a multidimensional system.

PubMed

Crespo, Yanier; Marinelli, Fabrizio; Pietrucci, Fabio; Laio, Alessandro

2010-05-01

Metadynamics is a powerful sampling technique that uses a nonequilibrium history-dependent process to reconstruct the free-energy surface as a function of the relevant collective variables s . In Bussi [Phys. Rev. Lett. 96, 090601 (2006)] it is proved that, in a Langevin process, metadynamics provides an unbiased estimate of the free energy F(s) . We here study the convergence properties of this approach in a multidimensional system, with a Hamiltonian depending on several variables. Specifically, we show that in a Monte Carlo metadynamics simulation of an Ising model the time average of the history-dependent potential converge to F(s) with the same law of an umbrella sampling performed in optimal conditions (i.e., with a bias exactly equal to the negative of the free energy). Remarkably, after a short transient, the error becomes approximately independent on the filling speed, showing that even in out-of-equilibrium conditions metadynamics allows recovering an accurate estimate of F(s) . These results have been obtained introducing a functional form of the history-dependent potential that avoids the onset of systematic errors near the boundaries of the free-energy landscape.

Chemistry of groundwater discharge inferred from longitudinal river sampling

NASA Astrophysics Data System (ADS)

Batlle-Aguilar, J.; Harrington, G. A.; Leblanc, M.; Welch, C.; Cook, P. G.

2014-02-01

We present an approach for identifying groundwater discharge chemistry and quantifying spatially distributed groundwater discharge into rivers based on longitudinal synoptic sampling and flow gauging of a river. The method is demonstrated using a 450 km reach of a tropical river in Australia. Results obtained from sampling for environmental tracers, major ions, and selected trace element chemistry were used to calibrate a steady state one-dimensional advective transport model of tracer distribution along the river. The model closely reproduced river discharge and environmental tracer and chemistry composition along the study length. It provided a detailed longitudinal profile of groundwater inflow chemistry and discharge rates, revealing that regional fractured mudstones in the central part of the catchment contributed up to 40% of all groundwater discharge. Detailed analysis of model calibration errors and modeled/measured groundwater ion ratios elucidated that groundwater discharging in the top of the catchment is a mixture of local groundwater and bank storage return flow, making the method potentially useful to differentiate between local and regional sourced groundwater discharge. As the error in tracer concentration induced by a flow event applies equally to any conservative tracer, we show that major ion ratios can still be resolved with minimal error when river samples are collected during transient flow conditions. The ability of the method to infer groundwater inflow chemistry from longitudinal river sampling is particularly attractive in remote areas where access to groundwater is limited or not possible, and for identification of actual fluxes of salts and/or specific contaminant sources.

Reducing user error in dipstick urinalysis with a low-cost slipping manifold and mobile phone platform (Conference Presentation)

NASA Astrophysics Data System (ADS)

Smith, Gennifer T.; Dwork, Nicholas; Khan, Saara A.; Millet, Matthew; Magar, Kiran; Javanmard, Mehdi; Bowden, Audrey K.

2017-03-01

Urinalysis dipsticks were designed to revolutionize urine-based medical diagnosis. They are cheap, extremely portable, and have multiple assays patterned on a single platform. They were also meant to be incredibly easy to use. Unfortunately, there are many aspects in both the preparation and the analysis of the dipsticks that are plagued by user error. This high error is one reason that dipsticks have failed to flourish in both the at-home market and in low-resource settings. Sources of error include: inaccurate volume deposition, varying lighting conditions, inconsistent timing measurements, and misinterpreted color comparisons. We introduce a novel manifold and companion software for dipstick urinalysis that eliminates the aforementioned error sources. A micro-volume slipping manifold ensures precise sample delivery, an opaque acrylic box guarantees consistent lighting conditions, a simple sticker-based timing mechanism maintains accurate timing, and custom software that processes video data captured by a mobile phone ensures proper color comparisons. We show that the results obtained with the proposed device are as accurate and consistent as a properly executed dip-and-wipe method, the industry gold-standard, suggesting the potential for this strategy to enable confident urinalysis testing. Furthermore, the proposed all-acrylic slipping manifold is reusable and low in cost, making it a potential solution for at-home users and low-resource settings.

The potential for geostationary remote sensing of NO2 to improve weather prediction

NASA Astrophysics Data System (ADS)

Liu, X.; Mizzi, A. P.; Anderson, J. L.; Fung, I. Y.; Cohen, R. C.

2016-12-01

Observations of surface winds remain sparse making it challenging to simulate and predict the weather in circumstances of light winds that are most important for poor air quality. Direct measurements of short-lived chemicals from space might be a solution to this challenge. Here we investigate the application of data assimilation of NO­2 columns as will be observed from geostationary orbit to improve predictions and retrospective analysis of surface wind fields. Specifically, synthetic NO2 observations are sampled from a "nature run (NR)" regarded as the true atmosphere. Then NO2 observations are assimilated using EAKF methods into a "control run (CR)" which differs from the NR in the wind field. Wind errors are generated by introducing (1) errors in the initial conditions, (2) creating a model error by using two different formulations for the planetary boundary layer, (3) and by combining both of these effects. The assimilation reduces wind errors by up to 50%, indicating the prospects for future geostationary atmospheric composition measurements to improve weather forecasting are substantial. We also examine the assimilation sensitivity to the data assimilation window length. We find that due to the temporal heterogeneity of wind errors, the success of this application favors chemical observations of high frequency, such as those from geostationary platform. We also show the potential to improve soil moisture field by assimilating NO­2 columns.

Using the Sampling Margin of Error to Assess the Interpretative Validity of Student Evaluations of Teaching

ERIC Educational Resources Information Center

James, David E.; Schraw, Gregory; Kuch, Fred

2015-01-01

We present an equation, derived from standard statistical theory, that can be used to estimate sampling margin of error for student evaluations of teaching (SETs). We use the equation to examine the effect of sample size, response rates and sample variability on the estimated sampling margin of error, and present results in four tables that allow…

Bias, Confounding, and Interaction: Lions and Tigers, and Bears, Oh My!

PubMed

Vetter, Thomas R; Mascha, Edward J

2017-09-01

Epidemiologists seek to make a valid inference about the causal effect between an exposure and a disease in a specific population, using representative sample data from a specific population. Clinical researchers likewise seek to make a valid inference about the association between an intervention and outcome(s) in a specific population, based upon their randomly collected, representative sample data. Both do so by using the available data about the sample variable to make a valid estimate about its corresponding or underlying, but unknown population parameter. Random error in an experiment can be due to the natural, periodic fluctuation or variation in the accuracy or precision of virtually any data sampling technique or health measurement tool or scale. In a clinical research study, random error can be due to not only innate human variability but also purely chance. Systematic error in an experiment arises from an innate flaw in the data sampling technique or measurement instrument. In the clinical research setting, systematic error is more commonly referred to as systematic bias. The most commonly encountered types of bias in anesthesia, perioperative, critical care, and pain medicine research include recall bias, observational bias (Hawthorne effect), attrition bias, misclassification or informational bias, and selection bias. A confounding variable is a factor associated with both the exposure of interest and the outcome of interest. A confounding variable (confounding factor or confounder) is a variable that correlates (positively or negatively) with both the exposure and outcome. Confounding is typically not an issue in a randomized trial because the randomized groups are sufficiently balanced on all potential confounding variables, both observed and nonobserved. However, confounding can be a major problem with any observational (nonrandomized) study. Ignoring confounding in an observational study will often result in a "distorted" or incorrect estimate of the association or treatment effect. Interaction among variables, also known as effect modification, exists when the effect of 1 explanatory variable on the outcome depends on the particular level or value of another explanatory variable. Bias and confounding are common potential explanations for statistically significant associations between exposure and outcome when the true relationship is noncausal. Understanding interactions is vital to proper interpretation of treatment effects. These complex concepts should be consistently and appropriately considered whenever one is not only designing but also analyzing and interpreting data from a randomized trial or observational study.

Assessment of ecologic regression in the study of lung cancer and indoor radon.

PubMed

Stidley, C A; Samet, J M

1994-02-01

Ecologic regression studies conducted to assess the cancer risk of indoor radon to the general population are subject to methodological limitations, and they have given seemingly contradictory results. The authors use simulations to examine the effects of two major methodological problems that affect these studies: measurement error and misspecification of the risk model. In a simulation study of the effect of measurement error caused by the sampling process used to estimate radon exposure for a geographic unit, both the effect of radon and the standard error of the effect estimate were underestimated, with greater bias for smaller sample sizes. In another simulation study, which addressed the consequences of uncontrolled confounding by cigarette smoking, even small negative correlations between county geometric mean annual radon exposure and the proportion of smokers resulted in negative average estimates of the radon effect. A third study considered consequences of using simple linear ecologic models when the true underlying model relation between lung cancer and radon exposure is nonlinear. These examples quantify potential biases and demonstrate the limitations of estimating risks from ecologic studies of lung cancer and indoor radon.

An alternative index of satellite telemetry location error

USGS Publications Warehouse

Keating, Kim A.

1994-01-01

Existing indices of satellite telemetry error offer objective standards for censoring poor locations, but have drawbacks. Examining distances and relative directions between consecutive satellite telemetry locations, I developed an alternative error index, ξ, and compared its performance with that of the location quality index, NQ (Serv. Argos 1988). In controlled tests, ξ was more (P ≤ 0.005) effective for improving precision than was a threshold of NQ > 1. The ξ index also conferred greater control over the trade off between sample size and precision, making ξ more cost-effective than NQ. Performances of ξ and NQ were otherwise comparable. In field tests with bighorn sheep (Ovis canadensis), rejecting locations where ξ ≥ 1.5 km reduced (P 1 and 63% fewer data were censored, so that the extent of animals' movements was better indicated by using ξ rather than NQ. Because use of ξ may lead to underestimating the number of long-range, short-term forays (especially when the frequency of forays is high relative to sampling frequency), potential bias should be considered before using ξ. Nonetheless, ξ should be a useful alternative to NQ in many animal-tracking studies.

Reliable LC-MS quantitative glycomics using iGlycoMab stable isotope labeled glycans as internal standards.

PubMed

Zhou, Shiyue; Tello, Nadia; Harvey, Alex; Boyes, Barry; Orlando, Ron; Mechref, Yehia

2016-06-01

Glycans have numerous functions in various biological processes and participate in the progress of diseases. Reliable quantitative glycomic profiling techniques could contribute to the understanding of the biological functions of glycans, and lead to the discovery of potential glycan biomarkers for diseases. Although LC-MS is a powerful analytical tool for quantitative glycomics, the variation of ionization efficiency and MS intensity bias are influencing quantitation reliability. Internal standards can be utilized for glycomic quantitation by MS-based methods to reduce variability. In this study, we used stable isotope labeled IgG2b monoclonal antibody, iGlycoMab, as an internal standard to reduce potential for errors and to reduce variabililty due to sample digestion, derivatization, and fluctuation of nanoESI efficiency in the LC-MS analysis of permethylated N-glycans released from model glycoproteins, human blood serum, and breast cancer cell line. We observed an unanticipated degradation of isotope labeled glycans, tracked a source of such degradation, and optimized a sample preparation protocol to minimize degradation of the internal standard glycans. All results indicated the effectiveness of using iGlycoMab to minimize errors originating from sample handling and instruments. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Localized strain measurements of the intervertebral disc annulus during biaxial tensile testing.

PubMed

Karakolis, Thomas; Callaghan, Jack P

2015-01-01

Both inter-lamellar and intra-lamellar failures of the annulus have been described as potential modes of disc herniation. Attempts to characterize initial lamellar failure of the annulus have involved tensile testing of small tissue samples. The purpose of this study was to evaluate a method of measuring local surface strains through image analysis of a tensile test conducted on an isolated sample of annular tissue in order to enhance future studies of intervertebral disc failure. An annulus tissue sample was biaxial strained to 10%. High-resolution images captured the tissue surface throughout testing. Three test conditions were evaluated: submerged, non-submerged and marker. Surface strains were calculated for the two non-marker conditions based on motion of virtual tracking points. Tracking algorithm parameters (grid resolution and template size) were varied to determine the effect on estimated strains. Accuracy of point tracking was assessed through a comparison of the non-marker conditions to a condition involving markers placed on tissue surface. Grid resolution had a larger effect on local strain than template size. Average local strain error ranged from 3% to 9.25% and 0.1% to 2.0%, for the non-submerged and submerged conditions, respectively. Local strain estimation has a relatively high potential for error. Submerging the tissue provided superior strain estimates.

Application of failure mode and effect analysis in an assisted reproduction technology laboratory.

PubMed

Intra, Giulia; Alteri, Alessandra; Corti, Laura; Rabellotti, Elisa; Papaleo, Enrico; Restelli, Liliana; Biondo, Stefania; Garancini, Maria Paola; Candiani, Massimo; Viganò, Paola

2016-08-01

Assisted reproduction technology laboratories have a very high degree of complexity. Mismatches of gametes or embryos can occur, with catastrophic consequences for patients. To minimize the risk of error, a multi-institutional working group applied failure mode and effects analysis (FMEA) to each critical activity/step as a method of risk assessment. This analysis led to the identification of the potential failure modes, together with their causes and effects, using the risk priority number (RPN) scoring system. In total, 11 individual steps and 68 different potential failure modes were identified. The highest ranked failure modes, with an RPN score of 25, encompassed 17 failures and pertained to "patient mismatch" and "biological sample mismatch". The maximum reduction in risk, with RPN reduced from 25 to 5, was mostly related to the introduction of witnessing. The critical failure modes in sample processing were improved by 50% in the RPN by focusing on staff training. Three indicators of FMEA success, based on technical skill, competence and traceability, have been evaluated after FMEA implementation. Witnessing by a second human operator should be introduced in the laboratory to avoid sample mix-ups. These findings confirm that FMEA can effectively reduce errors in assisted reproduction technology laboratories. Copyright © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Model dependence and its effect on ensemble projections in CMIP5

NASA Astrophysics Data System (ADS)

Abramowitz, G.; Bishop, C.

2013-12-01

Conceptually, the notion of model dependence within climate model ensembles is relatively simple - modelling groups share a literature base, parametrisations, data sets and even model code - the potential for dependence in sampling different climate futures is clear. How though can this conceptual problem inform a practical solution that demonstrably improves the ensemble mean and ensemble variance as an estimate of system uncertainty? While some research has already focused on error correlation or error covariance as a candidate to improve ensemble mean estimates, a complete definition of independence must at least implicitly subscribe to an ensemble interpretation paradigm, such as the 'truth-plus-error', 'indistinguishable', or more recently 'replicate Earth' paradigm. Using a definition of model dependence based on error covariance within the replicate Earth paradigm, this presentation will show that accounting for dependence in surface air temperature gives cooler projections in CMIP5 - by as much as 20% globally in some RCPs - although results differ significantly for each RCP, especially regionally. The fact that the change afforded by accounting for dependence across different RCPs is different is not an inconsistent result. Different numbers of submissions to each RCP by different modelling groups mean that differences in projections from different RCPs are not entirely about RCP forcing conditions - they also reflect different sampling strategies.

Quantitative, Comparable Coherent Anti-Stokes Raman Scattering (CARS) Spectroscopy: Correcting Errors in Phase Retrieval

PubMed Central

Camp, Charles H.; Lee, Young Jong; Cicerone, Marcus T.

2017-01-01

Coherent anti-Stokes Raman scattering (CARS) microspectroscopy has demonstrated significant potential for biological and materials imaging. To date, however, the primary mechanism of disseminating CARS spectroscopic information is through pseudocolor imagery, which explicitly neglects a vast majority of the hyperspectral data. Furthermore, current paradigms in CARS spectral processing do not lend themselves to quantitative sample-to-sample comparability. The primary limitation stems from the need to accurately measure the so-called nonresonant background (NRB) that is used to extract the chemically-sensitive Raman information from the raw spectra. Measurement of the NRB on a pixel-by-pixel basis is a nontrivial task; thus, reference NRB from glass or water are typically utilized, resulting in error between the actual and estimated amplitude and phase. In this manuscript, we present a new methodology for extracting the Raman spectral features that significantly suppresses these errors through phase detrending and scaling. Classic methods of error-correction, such as baseline detrending, are demonstrated to be inaccurate and to simply mask the underlying errors. The theoretical justification is presented by re-developing the theory of phase retrieval via the Kramers-Kronig relation, and we demonstrate that these results are also applicable to maximum entropy method-based phase retrieval. This new error-correction approach is experimentally applied to glycerol spectra and tissue images, demonstrating marked consistency between spectra obtained using different NRB estimates, and between spectra obtained on different instruments. Additionally, in order to facilitate implementation of these approaches, we have made many of the tools described herein available free for download. PMID:28819335

Analysis of methods commonly used in biomedicine for treatment versus control comparison of very small samples.

PubMed

Ristić-Djurović, Jasna L; Ćirković, Saša; Mladenović, Pavle; Romčević, Nebojša; Trbovich, Alexander M

2018-04-01

A rough estimate indicated that use of samples of size not larger than ten is not uncommon in biomedical research and that many of such studies are limited to strong effects due to sample sizes smaller than six. For data collected from biomedical experiments it is also often unknown if mathematical requirements incorporated in the sample comparison methods are satisfied. Computer simulated experiments were used to examine performance of methods for qualitative sample comparison and its dependence on the effectiveness of exposure, effect intensity, distribution of studied parameter values in the population, and sample size. The Type I and Type II errors, their average, as well as the maximal errors were considered. The sample size 9 and the t-test method with p = 5% ensured error smaller than 5% even for weak effects. For sample sizes 6-8 the same method enabled detection of weak effects with errors smaller than 20%. If the sample sizes were 3-5, weak effects could not be detected with an acceptable error; however, the smallest maximal error in the most general case that includes weak effects is granted by the standard error of the mean method. The increase of sample size from 5 to 9 led to seven times more accurate detection of weak effects. Strong effects were detected regardless of the sample size and method used. The minimal recommended sample size for biomedical experiments is 9. Use of smaller sizes and the method of their comparison should be justified by the objective of the experiment. Copyright © 2018 Elsevier B.V. All rights reserved.

On the Ability of Space- Based Passive and Active Remote Sensing Observations of CO2 to Detect Flux Perturbations to the Carbon Cycle

NASA Technical Reports Server (NTRS)

Crowell, Sean M. R.; Kawa, S. Randolph; Browell, Edward V.; Hammerling, Dorit M.; Moore, Berrien; Schaefer, Kevin; Doney, Scott C.

2018-01-01

Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT (Greenhouse Gases Observing Satellite) and OCO-2 (Orbiting Carbon Observatory 2), however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint. Plain Language Summary: Active and passive remote sensors show the potential to provide unprecedented information on the carbon cycle. With the all-season sampling, active remote sensors are more capable of constraining high-latitude emissions. The reduced sensitivity to cloud and aerosol also makes active sensors more capable of providing information in cloudy and polluted scenes with sufficient accuracy. These experiments account for errors that are fundamental to the top-down approach for constraining emissions, and even including these sources of error, we show that satellite remote sensors are critical for understanding the carbon cycle.

Measurement uncertainty associated with chromatic confocal profilometry for 3D surface texture characterization of natural human enamel.

PubMed

Mullan, F; Bartlett, D; Austin, R S

2017-06-01

To investigate the measurement performance of a chromatic confocal profilometer for quantification of surface texture of natural human enamel in vitro. Contributions to the measurement uncertainty from all potential sources of measurement error using a chromatic confocal profilometer and surface metrology software were quantified using a series of surface metrology calibration artifacts and pre-worn enamel samples. The 3D surface texture analysis protocol was optimized across 0.04mm 2 of natural and unpolished enamel undergoing dietary acid erosion (pH 3.2, titratable acidity 41.3mmolOH/L). Flatness deviations due to the x, y stage mechanical movement were the major contribution to the measurement uncertainty; with maximum Sz flatness errors of 0.49μm. Whereas measurement noise; non-linearity's in x, y, z and enamel sample dimensional instability contributed minimal errors. The measurement errors were propagated into an uncertainty budget following a Type B uncertainty evaluation in order to calculate the Standard Combined Uncertainty (u c ), which was ±0.28μm. Statistically significant increases in the median (IQR) roughness (Sa) of the polished samples occurred after 15 (+0.17 (0.13)μm), 30 (+0.12 (0.09)μm) and 45 (+0.18 (0.15)μm) min of erosion (P<0.001 vs. baseline). In contrast, natural unpolished enamel samples revealed a statistically significant decrease in Sa roughness of -0.14 (0.34) μm only after 45min erosion (P<0.05s vs. baseline). The main contribution to measurement uncertainty using chromatic confocal profilometry was from flatness deviations however by optimizing measurement protocols the profilometer successfully characterized surface texture changes in enamel from erosive wear in vitro. Copyright © 2017 The Academy of Dental Materials. All rights reserved.

The preliminary development and testing of a global trigger tool to detect error and patient harm in primary-care records.

PubMed

de Wet, C; Bowie, P

2009-04-01

A multi-method strategy has been proposed to understand and improve the safety of primary care. The trigger tool is a relatively new method that has shown promise in American and secondary healthcare settings. It involves the focused review of a random sample of patient records using a series of "triggers" that alert reviewers to potential errors and previously undetected adverse events. To develop and test a global trigger tool to detect errors and adverse events in primary-care records. Trigger tool development was informed by previous research and content validated by expert opinion. The tool was applied by trained reviewers who worked in pairs to conduct focused audits of 100 randomly selected electronic patient records in each of five urban general practices in central Scotland. Review of 500 records revealed 2251 consultations and 730 triggers. An adverse event was found in 47 records (9.4%), indicating that harm occurred at a rate of one event per 48 consultations. Of these, 27 were judged to be preventable (42%). A further 17 records (3.4%) contained evidence of a potential adverse event. Harm severity was low to moderate for most patients (82.9%). Error and harm rates were higher in those aged > or =60 years, and most were medication-related (59%). The trigger tool was successful in identifying undetected patient harm in primary-care records and may be the most reliable method for achieving this. However, the feasibility of its routine application is open to question. The tool may have greater utility as a research rather than an audit technique. Further testing in larger, representative study samples is required.

Outpatient Prescribing Errors and the Impact of Computerized Prescribing

PubMed Central

Gandhi, Tejal K; Weingart, Saul N; Seger, Andrew C; Borus, Joshua; Burdick, Elisabeth; Poon, Eric G; Leape, Lucian L; Bates, David W

2005-01-01

Background Medication errors are common among inpatients and many are preventable with computerized prescribing. Relatively little is known about outpatient prescribing errors or the impact of computerized prescribing in this setting. Objective To assess the rates, types, and severity of outpatient prescribing errors and understand the potential impact of computerized prescribing. Design Prospective cohort study in 4 adult primary care practices in Boston using prescription review, patient survey, and chart review to identify medication errors, potential adverse drug events (ADEs) and preventable ADEs. Participants Outpatients over age 18 who received a prescription from 24 participating physicians. Results We screened 1879 prescriptions from 1202 patients, and completed 661 surveys (response rate 55%). Of the prescriptions, 143 (7.6%; 95% confidence interval (CI) 6.4% to 8.8%) contained a prescribing error. Three errors led to preventable ADEs and 62 (43%; 3% of all prescriptions) had potential for patient injury (potential ADEs); 1 was potentially life-threatening (2%) and 15 were serious (24%). Errors in frequency (n=77, 54%) and dose (n=26, 18%) were common. The rates of medication errors and potential ADEs were not significantly different at basic computerized prescribing sites (4.3% vs 11.0%, P=.31; 2.6% vs 4.0%, P=.16) compared to handwritten sites. Advanced checks (including dose and frequency checking) could have prevented 95% of potential ADEs. Conclusions Prescribing errors occurred in 7.6% of outpatient prescriptions and many could have harmed patients. Basic computerized prescribing systems may not be adequate to reduce errors. More advanced systems with dose and frequency checking are likely needed to prevent potentially harmful errors. PMID:16117752

75 FR 26780 - State Median Income Estimate for a Four-Person Family: Notice of the Federal Fiscal Year (FFY...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-12

... Household Economic Statistics Division at (301) 763-3243. Under the advice of the Census Bureau, HHS..., which consists of the error that arises from the use of probability sampling to create the sample. For...) Sampling Error, which consists of the error that arises from the use of probability sampling to create the...

An evaluation of potential sampling locations in a reservoir with emphasis on conserved spatial correlation structure.

PubMed

Yenilmez, Firdes; Düzgün, Sebnem; Aksoy, Aysegül

2015-01-01

In this study, kernel density estimation (KDE) was coupled with ordinary two-dimensional kriging (OK) to reduce the number of sampling locations in measurement and kriging of dissolved oxygen (DO) concentrations in Porsuk Dam Reservoir (PDR). Conservation of the spatial correlation structure in the DO distribution was a target. KDE was used as a tool to aid in identification of the sampling locations that would be removed from the sampling network in order to decrease the total number of samples. Accordingly, several networks were generated in which sampling locations were reduced from 65 to 10 in increments of 4 or 5 points at a time based on kernel density maps. DO variograms were constructed, and DO values in PDR were kriged. Performance of the networks in DO estimations were evaluated through various error metrics, standard error maps (SEM), and whether the spatial correlation structure was conserved or not. Results indicated that smaller number of sampling points resulted in loss of information in regard to spatial correlation structure in DO. The minimum representative sampling points for PDR was 35. Efficacy of the sampling location selection method was tested against the networks generated by experts. It was shown that the evaluation approach proposed in this study provided a better sampling network design in which the spatial correlation structure of DO was sustained for kriging.

Errors in radial velocity variance from Doppler wind lidar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, H.; Barthelmie, R. J.; Doubrawa, P.

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Errors in radial velocity variance from Doppler wind lidar

DOE PAGES

Wang, H.; Barthelmie, R. J.; Doubrawa, P.; ...

2016-08-29

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Using cell phone location to assess misclassification errors in air pollution exposure estimation.

PubMed

Yu, Haofei; Russell, Armistead; Mulholland, James; Huang, Zhijiong

2018-02-01

Air pollution epidemiologic and health impact studies often rely on home addresses to estimate individual subject's pollution exposure. In this study, we used detailed cell phone location data, the call detail record (CDR), to account for the impact of spatiotemporal subject mobility on estimates of ambient air pollutant exposure. This approach was applied on a sample with 9886 unique simcard IDs in Shenzhen, China, on one mid-week day in October 2013. Hourly ambient concentrations of six chosen pollutants were simulated by the Community Multi-scale Air Quality model fused with observational data, and matched with detailed location data for these IDs. The results were compared with exposure estimates using home addresses to assess potential exposure misclassification errors. We found the misclassifications errors are likely to be substantial when home location alone is applied. The CDR based approach indicates that the home based approach tends to over-estimate exposures for subjects with higher exposure levels and under-estimate exposures for those with lower exposure levels. Our results show that the cell phone location based approach can be used to assess exposure misclassification error and has the potential for improving exposure estimates in air pollution epidemiology studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Applying Ancestry and Sex Computation as a Quality Control Tool in Targeted Next-Generation Sequencing.

PubMed

Mathias, Patrick C; Turner, Emily H; Scroggins, Sheena M; Salipante, Stephen J; Hoffman, Noah G; Pritchard, Colin C; Shirts, Brian H

2016-03-01

To apply techniques for ancestry and sex computation from next-generation sequencing (NGS) data as an approach to confirm sample identity and detect sample processing errors. We combined a principal component analysis method with k-nearest neighbors classification to compute the ancestry of patients undergoing NGS testing. By combining this calculation with X chromosome copy number data, we determined the sex and ancestry of patients for comparison with self-report. We also modeled the sensitivity of this technique in detecting sample processing errors. We applied this technique to 859 patient samples with reliable self-report data. Our k-nearest neighbors ancestry screen had an accuracy of 98.7% for patients reporting a single ancestry. Visual inspection of principal component plots was consistent with self-report in 99.6% of single-ancestry and mixed-ancestry patients. Our model demonstrates that approximately two-thirds of potential sample swaps could be detected in our patient population using this technique. Patient ancestry can be estimated from NGS data incidentally sequenced in targeted panels, enabling an inexpensive quality control method when coupled with patient self-report. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Type I error probabilities based on design-stage strategies with applications to noninferiority trials.

PubMed

Rothmann, Mark

2005-01-01

When testing the equality of means from two different populations, a t-test or large sample normal test tend to be performed. For these tests, when the sample size or design for the second sample is dependent on the results of the first sample, the type I error probability is altered for each specific possibility in the null hypothesis. We will examine the impact on the type I error probabilities for two confidence interval procedures and procedures using test statistics when the design for the second sample or experiment is dependent on the results from the first sample or experiment (or series of experiments). Ways for controlling a desired maximum type I error probability or a desired type I error rate will be discussed. Results are applied to the setting of noninferiority comparisons in active controlled trials where the use of a placebo is unethical.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

Auditing as part of the terminology design life cycle.

PubMed

Min, Hua; Perl, Yehoshua; Chen, Yan; Halper, Michael; Geller, James; Wang, Yue

2006-01-01

To develop and test an auditing methodology for detecting errors in medical terminologies satisfying systematic inheritance. This methodology is based on various abstraction taxonomies that provide high-level views of a terminology and highlight potentially erroneous concepts. Our auditing methodology is based on dividing concepts of a terminology into smaller, more manageable units. First, we divide the terminology's concepts into areas according to their relationships/roles. Then each multi-rooted area is further divided into partial-areas (p-areas) that are singly-rooted. Each p-area contains a set of structurally and semantically uniform concepts. Two kinds of abstraction networks, called the area taxonomy and p-area taxonomy, are derived. These taxonomies form the basis for the auditing approach. Taxonomies tend to highlight potentially erroneous concepts in areas and p-areas. Human reviewers can focus their auditing efforts on the limited number of problematic concepts following two hypotheses on the probable concentration of errors. A sample of the area taxonomy and p-area taxonomy for the Biological Process (BP) hierarchy of the National Cancer Institute Thesaurus (NCIT) was derived from the application of our methodology to its concepts. These views led to the detection of a number of different kinds of errors that are reported, and to confirmation of the hypotheses on error concentration in this hierarchy. Our auditing methodology based on area and p-area taxonomies is an efficient tool for detecting errors in terminologies satisfying systematic inheritance of roles, and thus facilitates their maintenance. This methodology concentrates a domain expert's manual review on portions of the concepts with a high likelihood of errors.

Covariate Measurement Error Correction Methods in Mediation Analysis with Failure Time Data

PubMed Central

Zhao, Shanshan

2014-01-01

Summary Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This paper focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error and error associated with temporal variation. The underlying model with the ‘true’ mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling design. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. PMID:25139469

Covariate measurement error correction methods in mediation analysis with failure time data.

PubMed

Zhao, Shanshan; Prentice, Ross L

2014-12-01

Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This article focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error, and error associated with temporal variation. The underlying model with the "true" mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling designs. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. © 2014, The International Biometric Society.

Speech abilities in preschool children with speech sound disorder with and without co-occurring language impairment.

PubMed

Macrae, Toby; Tyler, Ann A

2014-10-01

The authors compared preschool children with co-occurring speech sound disorder (SSD) and language impairment (LI) to children with SSD only in their numbers and types of speech sound errors. In this post hoc quasi-experimental study, independent samples t tests were used to compare the groups in the standard score from different tests of articulation/phonology, percent consonants correct, and the number of omission, substitution, distortion, typical, and atypical error patterns used in the production of different wordlists that had similar levels of phonetic and structural complexity. In comparison with children with SSD only, children with SSD and LI used similar numbers but different types of errors, including more omission patterns ( p < .001, d = 1.55) and fewer distortion patterns ( p = .022, d = 1.03). There were no significant differences in substitution, typical, and atypical error pattern use. Frequent omission error pattern use may reflect a more compromised linguistic system characterized by absent phonological representations for target sounds (see Shriberg et al., 2005). Research is required to examine the diagnostic potential of early frequent omission error pattern use in predicting later diagnoses of co-occurring SSD and LI and/or reading problems.

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

PubMed

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

Single molecule targeted sequencing for cancer gene mutation detection.

PubMed

Gao, Yan; Deng, Liwei; Yan, Qin; Gao, Yongqian; Wu, Zengding; Cai, Jinsen; Ji, Daorui; Li, Gailing; Wu, Ping; Jin, Huan; Zhao, Luyang; Liu, Song; Ge, Liangjin; Deem, Michael W; He, Jiankui

2016-05-19

With the rapid decline in cost of sequencing, it is now affordable to examine multiple genes in a single disease-targeted clinical test using next generation sequencing. Current targeted sequencing methods require a separate step of targeted capture enrichment during sample preparation before sequencing. Although there are fast sample preparation methods available in market, the library preparation process is still relatively complicated for physicians to use routinely. Here, we introduced an amplification-free Single Molecule Targeted Sequencing (SMTS) technology, which combined targeted capture and sequencing in one step. We demonstrated that this technology can detect low-frequency mutations using artificially synthesized DNA sample. SMTS has several potential advantages, including simple sample preparation thus no biases and errors are introduced by PCR reaction. SMTS has the potential to be an easy and quick sequencing technology for clinical diagnosis such as cancer gene mutation detection, infectious disease detection, inherited condition screening and noninvasive prenatal diagnosis.

Clinical biochemistry laboratory rejection rates due to various types of preanalytical errors.

PubMed

Atay, Aysenur; Demir, Leyla; Cuhadar, Serap; Saglam, Gulcan; Unal, Hulya; Aksun, Saliha; Arslan, Banu; Ozkan, Asuman; Sutcu, Recep

2014-01-01

Preanalytical errors, along the process from the beginning of test requests to the admissions of the specimens to the laboratory, cause the rejection of samples. The aim of this study was to better explain the reasons of rejected samples, regarding to their rates in certain test groups in our laboratory. This preliminary study was designed on the rejected samples in one-year period, based on the rates and types of inappropriateness. Test requests and blood samples of clinical chemistry, immunoassay, hematology, glycated hemoglobin, coagulation and erythrocyte sedimentation rate test units were evaluated. Types of inappropriateness were evaluated as follows: improperly labelled samples, hemolysed, clotted specimen, insufficient volume of specimen and total request errors. A total of 5,183,582 test requests from 1,035,743 blood collection tubes were considered. The total rejection rate was 0.65 %. The rejection rate of coagulation group was significantly higher (2.28%) than the other test groups (P < 0.001) including insufficient volume of specimen error rate as 1.38%. Rejection rates of hemolysis, clotted specimen and insufficient volume of sample error were found to be 8%, 24% and 34%, respectively. Total request errors, particularly, for unintelligible requests were 32% of the total for inpatients. The errors were especially attributable to unintelligible requests of inappropriate test requests, improperly labelled samples for inpatients and blood drawing errors especially due to insufficient volume of specimens in a coagulation test group. Further studies should be performed after corrective and preventive actions to detect a possible decrease in rejecting samples.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

Generalized Variance Function Applications in Forestry

Treesearch

James Alegria; Charles T. Scott; Charles T. Scott

1991-01-01

Adequately predicting the sampling errors of tabular data can reduce printing costs by eliminating the need to publish separate sampling error tables. Two generalized variance functions (GVFs) found in the literature and three GVFs derived for this study were evaluated for their ability to predict the sampling error of tabular forestry estimates. The recommended GVFs...

Interval sampling methods and measurement error: a computer simulation.

PubMed

Wirth, Oliver; Slaven, James; Taylor, Matthew A

2014-01-01

A simulation study was conducted to provide a more thorough account of measurement error associated with interval sampling methods. A computer program simulated the application of momentary time sampling, partial-interval recording, and whole-interval recording methods on target events randomly distributed across an observation period. The simulation yielded measures of error for multiple combinations of observation period, interval duration, event duration, and cumulative event duration. The simulations were conducted up to 100 times to yield measures of error variability. Although the present simulation confirmed some previously reported characteristics of interval sampling methods, it also revealed many new findings that pertain to each method's inherent strengths and weaknesses. The analysis and resulting error tables can help guide the selection of the most appropriate sampling method for observation-based behavioral assessments. © Society for the Experimental Analysis of Behavior.

Moments and Root-Mean-Square Error of the Bayesian MMSE Estimator of Classification Error in the Gaussian Model.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2014-06-01

The most important aspect of any classifier is its error rate, because this quantifies its predictive capacity. Thus, the accuracy of error estimation is critical. Error estimation is problematic in small-sample classifier design because the error must be estimated using the same data from which the classifier has been designed. Use of prior knowledge, in the form of a prior distribution on an uncertainty class of feature-label distributions to which the true, but unknown, feature-distribution belongs, can facilitate accurate error estimation (in the mean-square sense) in circumstances where accurate completely model-free error estimation is impossible. This paper provides analytic asymptotically exact finite-sample approximations for various performance metrics of the resulting Bayesian Minimum Mean-Square-Error (MMSE) error estimator in the case of linear discriminant analysis (LDA) in the multivariate Gaussian model. These performance metrics include the first, second, and cross moments of the Bayesian MMSE error estimator with the true error of LDA, and therefore, the Root-Mean-Square (RMS) error of the estimator. We lay down the theoretical groundwork for Kolmogorov double-asymptotics in a Bayesian setting, which enables us to derive asymptotic expressions of the desired performance metrics. From these we produce analytic finite-sample approximations and demonstrate their accuracy via numerical examples. Various examples illustrate the behavior of these approximations and their use in determining the necessary sample size to achieve a desired RMS. The Supplementary Material contains derivations for some equations and added figures.

Quantizing and sampling considerations in digital phased-locked loops

NASA Technical Reports Server (NTRS)

Hurst, G. T.; Gupta, S. C.

1974-01-01

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

Ultra-deep mutant spectrum profiling: improving sequencing accuracy using overlapping read pairs.

PubMed

Chen-Harris, Haiyin; Borucki, Monica K; Torres, Clinton; Slezak, Tom R; Allen, Jonathan E

2013-02-12

High throughput sequencing is beginning to make a transformative impact in the area of viral evolution. Deep sequencing has the potential to reveal the mutant spectrum within a viral sample at high resolution, thus enabling the close examination of viral mutational dynamics both within- and between-hosts. The challenge however, is to accurately model the errors in the sequencing data and differentiate real viral mutations, particularly those that exist at low frequencies, from sequencing errors. We demonstrate that overlapping read pairs (ORP) -- generated by combining short fragment sequencing libraries and longer sequencing reads -- significantly reduce sequencing error rates and improve rare variant detection accuracy. Using this sequencing protocol and an error model optimized for variant detection, we are able to capture a large number of genetic mutations present within a viral population at ultra-low frequency levels (<0.05%). Our rare variant detection strategies have important implications beyond viral evolution and can be applied to any basic and clinical research area that requires the identification of rare mutations.

Reducing errors in aircraft atmospheric inversion estimates of point-source emissions: the Aliso Canyon natural gas leak as a natural tracer experiment

NASA Astrophysics Data System (ADS)

Gourdji, S. M.; Yadav, V.; Karion, A.; Mueller, K. L.; Conley, S.; Ryerson, T.; Nehrkorn, T.; Kort, E. A.

2018-04-01

Urban greenhouse gas (GHG) flux estimation with atmospheric measurements and modeling, i.e. the ‘top-down’ approach, can potentially support GHG emission reduction policies by assessing trends in surface fluxes and detecting anomalies from bottom-up inventories. Aircraft-collected GHG observations also have the potential to help quantify point-source emissions that may not be adequately sampled by fixed surface tower-based atmospheric observing systems. Here, we estimate CH4 emissions from a known point source, the Aliso Canyon natural gas leak in Los Angeles, CA from October 2015–February 2016, using atmospheric inverse models with airborne CH4 observations from twelve flights ≈4 km downwind of the leak and surface sensitivities from a mesoscale atmospheric transport model. This leak event has been well-quantified previously using various methods by the California Air Resources Board, thereby providing high confidence in the mass-balance leak rate estimates of (Conley et al 2016), used here for comparison to inversion results. Inversions with an optimal setup are shown to provide estimates of the leak magnitude, on average, within a third of the mass balance values, with remaining errors in estimated leak rates predominantly explained by modeled wind speed errors of up to 10 m s‑1, quantified by comparing airborne meteorological observations with modeled values along the flight track. An inversion setup using scaled observational wind speed errors in the model-data mismatch covariance matrix is shown to significantly reduce the influence of transport model errors on spatial patterns and estimated leak rates from the inversions. In sum, this study takes advantage of a natural tracer release experiment (i.e. the Aliso Canyon natural gas leak) to identify effective approaches for reducing the influence of transport model error on atmospheric inversions of point-source emissions, while suggesting future potential for integrating surface tower and aircraft atmospheric GHG observations in top-down urban emission monitoring systems.

Standardized error severity score (ESS) ratings to quantify risk associated with child restraint system (CRS) and booster seat misuse.

PubMed

Rudin-Brown, Christina M; Kramer, Chelsea; Langerak, Robin; Scipione, Andrea; Kelsey, Shelley

2017-11-17

Although numerous research studies have reported high levels of error and misuse of child restraint systems (CRS) and booster seats in experimental and real-world scenarios, conclusions are limited because they provide little information regarding which installation issues pose the highest risk and thus should be targeted for change. Beneficial to legislating bodies and researchers alike would be a standardized, globally relevant assessment of the potential injury risk associated with more common forms of CRS and booster seat misuse, which could be applied with observed error frequency-for example, in car seat clinics or during prototype user testing-to better identify and characterize the installation issues of greatest risk to safety. A group of 8 leading world experts in CRS and injury biomechanics, who were members of an international child safety project, estimated the potential injury severity associated with common forms of CRS and booster seat misuse. These injury risk error severity score (ESS) ratings were compiled and compared to scores from previous research that had used a similar procedure but with fewer respondents. To illustrate their application, and as part of a larger study examining CRS and booster seat labeling requirements, the new standardized ESS ratings were applied to objective installation performance data from 26 adult participants who installed a convertible (rear- vs. forward-facing) CRS and booster seat in a vehicle, and a child test dummy in the CRS and booster seat, using labels that only just met minimal regulatory requirements. The outcome measure, the risk priority number (RPN), represented the composite scores of injury risk and observed installation error frequency. Variability within the sample of ESS ratings in the present study was smaller than that generated in previous studies, indicating better agreement among experts on what constituted injury risk. Application of the new standardized ESS ratings to installation performance data revealed several areas of misuse of the CRS/booster seat associated with high potential injury risk. Collectively, findings indicate that standardized ESS ratings are useful for estimating injury risk potential associated with real-world CRS and booster seat installation errors.

Real-time absorption and scattering characterization of slab-shaped turbid samples obtained by a combination of angular and spatially resolved measurements.

PubMed

Dam, Jan S; Yavari, Nazila; Sørensen, Søren; Andersson-Engels, Stefan

2005-07-10

We present a fast and accurate method for real-time determination of the absorption coefficient, the scattering coefficient, and the anisotropy factor of thin turbid samples by using simple continuous-wave noncoherent light sources. The three optical properties are extracted from recordings of angularly resolved transmittance in addition to spatially resolved diffuse reflectance and transmittance. The applied multivariate calibration and prediction techniques are based on multiple polynomial regression in combination with a Newton--Raphson algorithm. The numerical test results based on Monte Carlo simulations showed mean prediction errors of approximately 0.5% for all three optical properties within ranges typical for biological media. Preliminary experimental results are also presented yielding errors of approximately 5%. Thus the presented methods show a substantial potential for simultaneous absorption and scattering characterization of turbid media.

Importance of anthropogenic climate impact, sampling error and urban development in sewer system design.

PubMed

Egger, C; Maurer, M

2015-04-15

Urban drainage design relying on observed precipitation series neglects the uncertainties associated with current and indeed future climate variability. Urban drainage design is further affected by the large stochastic variability of precipitation extremes and sampling errors arising from the short observation periods of extreme precipitation. Stochastic downscaling addresses anthropogenic climate impact by allowing relevant precipitation characteristics to be derived from local observations and an ensemble of climate models. This multi-climate model approach seeks to reflect the uncertainties in the data due to structural errors of the climate models. An ensemble of outcomes from stochastic downscaling allows for addressing the sampling uncertainty. These uncertainties are clearly reflected in the precipitation-runoff predictions of three urban drainage systems. They were mostly due to the sampling uncertainty. The contribution of climate model uncertainty was found to be of minor importance. Under the applied greenhouse gas emission scenario (A1B) and within the period 2036-2065, the potential for urban flooding in our Swiss case study is slightly reduced on average compared to the reference period 1981-2010. Scenario planning was applied to consider urban development associated with future socio-economic factors affecting urban drainage. The impact of scenario uncertainty was to a large extent found to be case-specific, thus emphasizing the need for scenario planning in every individual case. The results represent a valuable basis for discussions of new drainage design standards aiming specifically to include considerations of uncertainty. Copyright © 2015 Elsevier Ltd. All rights reserved.

Seasonal variation in size-dependent survival of juvenile Atlantic salmon (Salmo salar): Performance of multistate capture-mark-recapture models

USGS Publications Warehouse

Letcher, B.H.; Horton, G.E.

2008-01-01

We estimated the magnitude and shape of size-dependent survival (SDS) across multiple sampling intervals for two cohorts of stream-dwelling Atlantic salmon (Salmo salar) juveniles using multistate capture-mark-recapture (CMR) models. Simulations designed to test the effectiveness of multistate models for detecting SDS in our system indicated that error in SDS estimates was low and that both time-invariant and time-varying SDS could be detected with sample sizes of >250, average survival of >0.6, and average probability of capture of >0.6, except for cases of very strong SDS. In the field (N ??? 750, survival 0.6-0.8 among sampling intervals, probability of capture 0.6-0.8 among sampling occasions), about one-third of the sampling intervals showed evidence of SDS, with poorer survival of larger fish during the age-2+ autumn and quadratic survival (opposite direction between cohorts) during age-1+ spring. The varying magnitude and shape of SDS among sampling intervals suggest a potential mechanism for the maintenance of the very wide observed size distributions. Estimating SDS using multistate CMR models appears complementary to established approaches, can provide estimates with low error, and can be used to detect intermittent SDS. ?? 2008 NRC Canada.

Analysis of shockless dynamic compression data on solids to multi-megabar pressures: Application to tantalum

DOE PAGES

Davis, Jean -Paul; Brown, Justin L.; Knudson, Marcus D.; ...

2014-11-26

In this research, magnetically-driven, planar shockless-compression experiments to multi-megabar pressures were performed on tantalum samples using a stripline target geometry. Free-surface velocity waveforms were measured in 15 cases; nine of these in a dual-sample configuration with two samples of different thicknesses on opposing electrodes, and six in a single-sample configuration with a bare electrode opposite the sample. Details are given on the application of inverse Lagrangian analysis (ILA) to these data, including potential sources of error. The most significant source of systematic error, particularly for single-sample experiments, was found to arise from the pulse-shape dependent free-surface reflected wave interactions withmore » the deviatoric-stress response of tantalum. This could cause local, possibly temporary, unloading of material from a ramp compressed state, and thus multi-value response in wave speed that invalidates the free-surface to in-material velocity mapping step of ILA. By averaging all 15 data sets, a final result for the principal quasi-isentrope of tantalum in stress-strain was obtained to a peak longitudinal stress of 330 GPa with conservative uncertainty bounds of ±4.5% in stress. The result agrees well with a tabular equation of state developed at Los Alamos National Laboratory.« less

Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

PubMed

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

Ensemble codes involving hippocampal neurons are at risk during delayed performance tests.

PubMed

Hampson, R E; Deadwyler, S A

1996-11-26

Multielectrode recording techniques were used to record ensemble activity from 10 to 16 simultaneously active CA1 and CA3 neurons in the rat hippocampus during performance of a spatial delayed-nonmatch-to-sample task. Extracted sources of variance were used to assess the nature of two different types of errors that accounted for 30% of total trials. The two types of errors included ensemble "miscodes" of sample phase information and errors associated with delay-dependent corruption or disappearance of sample information at the time of the nonmatch response. Statistical assessment of trial sequences and associated "strength" of hippocampal ensemble codes revealed that miscoded error trials always followed delay-dependent error trials in which encoding was "weak," indicating that the two types of errors were "linked." It was determined that the occurrence of weakly encoded, delay-dependent error trials initiated an ensemble encoding "strategy" that increased the chances of being correct on the next trial and avoided the occurrence of further delay-dependent errors. Unexpectedly, the strategy involved "strongly" encoding response position information from the prior (delay-dependent) error trial and carrying it forward to the sample phase of the next trial. This produced a miscode type error on trials in which the "carried over" information obliterated encoding of the sample phase response on the next trial. Application of this strategy, irrespective of outcome, was sufficient to reorient the animal to the proper between trial sequence of response contingencies (nonmatch-to-sample) and boost performance to 73% correct on subsequent trials. The capacity for ensemble analyses of strength of information encoding combined with statistical assessment of trial sequences therefore provided unique insight into the "dynamic" nature of the role hippocampus plays in delay type memory tasks.

Using snowball sampling method with nurses to understand medication administration errors.

PubMed

Sheu, Shuh-Jen; Wei, Ien-Lan; Chen, Ching-Huey; Yu, Shu; Tang, Fu-In

2009-02-01

We aimed to encourage nurses to release information about drug administration errors to increase understanding of error-related circumstances and to identify high-alert situations. Drug administration errors represent the majority of medication errors, but errors are underreported. Effective ways are lacking to encourage nurses to actively report errors. Snowball sampling was conducted to recruit participants. A semi-structured questionnaire was used to record types of error, hospital and nurse backgrounds, patient consequences, error discovery mechanisms and reporting rates. Eighty-five nurses participated, reporting 328 administration errors (259 actual, 69 near misses). Most errors occurred in medical surgical wards of teaching hospitals, during day shifts, committed by nurses working fewer than two years. Leading errors were wrong drugs and doses, each accounting for about one-third of total errors. Among 259 actual errors, 83.8% resulted in no adverse effects; among remaining 16.2%, 6.6% had mild consequences and 9.6% had serious consequences (severe reaction, coma, death). Actual errors and near misses were discovered mainly through double-check procedures by colleagues and nurses responsible for errors; reporting rates were 62.5% (162/259) vs. 50.7% (35/69) and only 3.5% (9/259) vs. 0% (0/69) were disclosed to patients and families. High-alert situations included administration of 15% KCl, insulin and Pitocin; using intravenous pumps; and implementation of cardiopulmonary resuscitation (CPR). Snowball sampling proved to be an effective way to encourage nurses to release details concerning medication errors. Using empirical data, we identified high-alert situations. Strategies for reducing drug administration errors by nurses are suggested. Survey results suggest that nurses should double check medication administration in known high-alert situations. Nursing management can use snowball sampling to gather error details from nurses in a non-reprimanding atmosphere, helping to establish standard operational procedures for known high-alert situations.

Population size estimation in Yellowstone wolves with error-prone noninvasive microsatellite genotypes.

PubMed

Creel, Scott; Spong, Goran; Sands, Jennifer L; Rotella, Jay; Zeigle, Janet; Joe, Lawrence; Murphy, Kerry M; Smith, Douglas

2003-07-01

Determining population sizes can be difficult, but is essential for conservation. By counting distinct microsatellite genotypes, DNA from noninvasive samples (hair, faeces) allows estimation of population size. Problems arise because genotypes from noninvasive samples are error-prone, but genotyping errors can be reduced by multiple polymerase chain reaction (PCR). For faecal genotypes from wolves in Yellowstone National Park, error rates varied substantially among samples, often above the 'worst-case threshold' suggested by simulation. Consequently, a substantial proportion of multilocus genotypes held one or more errors, despite multiple PCR. These genotyping errors created several genotypes per individual and caused overestimation (up to 5.5-fold) of population size. We propose a 'matching approach' to eliminate this overestimation bias.

Ten years of preanalytical monitoring and control: Synthetic Balanced Score Card Indicator

PubMed Central

López-Garrigós, Maite; Flores, Emilio; Santo-Quiles, Ana; Gutierrez, Mercedes; Lugo, Javier; Lillo, Rosa; Leiva-Salinas, Carlos

2015-01-01

Introduction Preanalytical control and monitoring continue to be an important issue for clinical laboratory professionals. The aim of the study was to evaluate a monitoring system of preanalytical errors regarding not suitable samples for analysis, based on different indicators; to compare such indicators in different phlebotomy centres; and finally to evaluate a single synthetic preanalytical indicator that may be included in the balanced scorecard management system (BSC). Materials and methods We collected individual and global preanalytical errors in haematology, coagulation, chemistry, and urine samples analysis. We also analyzed a synthetic indicator that represents the sum of all types of preanalytical errors, expressed in a sigma level. We studied the evolution of those indicators over time and compared indicator results by way of the comparison of proportions and Chi-square. Results There was a decrease in the number of errors along the years (P < 0.001). This pattern was confirmed in primary care patients, inpatients and outpatients. In blood samples, fewer errors occurred in outpatients, followed by inpatients. Conclusion We present a practical and effective methodology to monitor unsuitable sample preanalytical errors. The synthetic indicator results summarize overall preanalytical sample errors, and can be used as part of BSC management system. PMID:25672466

Inspection error and its adverse effects - A model with implications for practitioners

NASA Technical Reports Server (NTRS)

Collins, R. D., Jr.; Case, K. E.; Bennett, G. K.

1978-01-01

Inspection error has clearly been shown to have adverse effects upon the results desired from a quality assurance sampling plan. These effects upon performance measures have been well documented from a statistical point of view. However, little work has been presented to convince the QC manager of the unfavorable cost consequences resulting from inspection error. This paper develops a very general, yet easily used, mathematical cost model. The basic format of the well-known Guthrie-Johns model is used. However, it is modified as required to assess the effects of attributes sampling errors of the first and second kind. The economic results, under different yet realistic conditions, will no doubt be of interest to QC practitioners who face similar problems daily. Sampling inspection plans are optimized to minimize economic losses due to inspection error. Unfortunately, any error at all results in some economic loss which cannot be compensated for by sampling plan design; however, improvements over plans which neglect the presence of inspection error are possible. Implications for human performance betterment programs are apparent, as are trade-offs between sampling plan modification and inspection and training improvements economics.

Potential benefit of electronic pharmacy claims data to prevent medication history errors and resultant inpatient order errors

PubMed Central

Palmer, Katherine A; Shane, Rita; Wu, Cindy N; Bell, Douglas S; Diaz, Frank; Cook-Wiens, Galen; Jackevicius, Cynthia A

2016-01-01

Objective We sought to assess the potential of a widely available source of electronic medication data to prevent medication history errors and resultant inpatient order errors. Methods We used admission medication history (AMH) data from a recent clinical trial that identified 1017 AMH errors and 419 resultant inpatient order errors among 194 hospital admissions of predominantly older adult patients on complex medication regimens. Among the subset of patients for whom we could access current Surescripts electronic pharmacy claims data (SEPCD), two pharmacists independently assessed error severity and our main outcome, which was whether SEPCD (1) was unrelated to the medication error; (2) probably would not have prevented the error; (3) might have prevented the error; or (4) probably would have prevented the error. Results Seventy patients had both AMH errors and current, accessible SEPCD. SEPCD probably would have prevented 110 (35%) of 315 AMH errors and 46 (31%) of 147 resultant inpatient order errors. When we excluded the least severe medication errors, SEPCD probably would have prevented 99 (47%) of 209 AMH errors and 37 (61%) of 61 resultant inpatient order errors. SEPCD probably would have prevented at least one AMH error in 42 (60%) of 70 patients. Conclusion When current SEPCD was available for older adult patients on complex medication regimens, it had substantial potential to prevent AMH errors and resultant inpatient order errors, with greater potential to prevent more severe errors. Further study is needed to measure the benefit of SEPCD in actual use at hospital admission. PMID:26911817

Application of Multivariable Analysis and FTIR-ATR Spectroscopy to the Prediction of Properties in Campeche Honey

PubMed Central

Pat, Lucio; Ali, Bassam; Guerrero, Armando; Córdova, Atl V.; Garduza, José P.

2016-01-01

Attenuated total reflectance-Fourier transform infrared spectrometry and chemometrics model was used for determination of physicochemical properties (pH, redox potential, free acidity, electrical conductivity, moisture, total soluble solids (TSS), ash, and HMF) in honey samples. The reference values of 189 honey samples of different botanical origin were determined using Association Official Analytical Chemists, (AOAC), 1990; Codex Alimentarius, 2001, International Honey Commission, 2002, methods. Multivariate calibration models were built using partial least squares (PLS) for the measurands studied. The developed models were validated using cross-validation and external validation; several statistical parameters were obtained to determine the robustness of the calibration models: (PCs) optimum number of components principal, (SECV) standard error of cross-validation, (R 2 cal) coefficient of determination of cross-validation, (SEP) standard error of validation, and (R 2 val) coefficient of determination for external validation and coefficient of variation (CV). The prediction accuracy for pH, redox potential, electrical conductivity, moisture, TSS, and ash was good, while for free acidity and HMF it was poor. The results demonstrate that attenuated total reflectance-Fourier transform infrared spectrometry is a valuable, rapid, and nondestructive tool for the quantification of physicochemical properties of honey. PMID:28070445

Application of multibounce attenuated total reflectance fourier transform infrared spectroscopy and chemometrics for determination of aspartame in soft drinks.

PubMed

Khurana, Harpreet Kaur; Cho, Il Kyu; Shim, Jae Yong; Li, Qing X; Jun, Soojin

2008-02-13

Aspartame is a low-calorie sweetener commonly used in soft drinks; however, the maximum usage dose is limited by the U.S. Food and Drug Administration. Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance sampling accessory and partial least-squares regression (PLS) was used for rapid determination of aspartame in soft drinks. On the basis of spectral characterization, the highest R2 value, and lowest PRESS value, the spectral region between 1600 and 1900 cm(-1) was selected for quantitative estimation of aspartame. The potential of FTIR spectroscopy for aspartame quantification was examined and validated by the conventional HPLC method. Using the FTIR method, aspartame contents in four selected carbonated diet soft drinks were found to average from 0.43 to 0.50 mg/mL with prediction errors ranging from 2.4 to 5.7% when compared with HPLC measurements. The developed method also showed a high degree of accuracy because real samples were used for calibration, thus minimizing potential interference errors. The FTIR method developed can be suitably used for routine quality control analysis of aspartame in the beverage-manufacturing sector.

Lean six sigma methodologies improve clinical laboratory efficiency and reduce turnaround times.

PubMed

Inal, Tamer C; Goruroglu Ozturk, Ozlem; Kibar, Filiz; Cetiner, Salih; Matyar, Selcuk; Daglioglu, Gulcin; Yaman, Akgun

2018-01-01

Organizing work flow is a major task of laboratory management. Recently, clinical laboratories have started to adopt methodologies such as Lean Six Sigma and some successful implementations have been reported. This study used Lean Six Sigma to simplify the laboratory work process and decrease the turnaround time by eliminating non-value-adding steps. The five-stage Six Sigma system known as define, measure, analyze, improve, and control (DMAIC) is used to identify and solve problems. The laboratory turnaround time for individual tests, total delay time in the sample reception area, and percentage of steps involving risks of medical errors and biological hazards in the overall process are measured. The pre-analytical process in the reception area was improved by eliminating 3 h and 22.5 min of non-value-adding work. Turnaround time also improved for stat samples from 68 to 59 min after applying Lean. Steps prone to medical errors and posing potential biological hazards to receptionists were reduced from 30% to 3%. Successful implementation of Lean Six Sigma significantly improved all of the selected performance metrics. This quality-improvement methodology has the potential to significantly improve clinical laboratories. © 2017 Wiley Periodicals, Inc.

Numerical modeling of the divided bar measurements

NASA Astrophysics Data System (ADS)

LEE, Y.; Keehm, Y.

2011-12-01

The divided-bar technique has been used to measure thermal conductivity of rocks and fragments in heat flow studies. Though widely used, divided-bar measurements can have errors, which are not systematically quantified yet. We used an FEM and performed a series of numerical studies to evaluate various errors in divided-bar measurements and to suggest more reliable measurement techniques. A divided-bar measurement should be corrected against lateral heat loss on the sides of rock samples, and the thermal resistance at the contacts between the rock sample and the bar. We first investigated how the amount of these corrections would change by the thickness and thermal conductivity of rock samples through numerical modeling. When we fixed the sample thickness as 10 mm and varied thermal conductivity, errors in the measured thermal conductivity ranges from 2.02% for 1.0 W/m/K to 7.95% for 4.0 W/m/K. While we fixed thermal conductivity as 1.38 W/m/K and varied the sample thickness, we found that the error ranges from 2.03% for the 30 mm-thick sample to 11.43% for the 5 mm-thick sample. After corrections, a variety of error analyses for divided-bar measurements were conducted numerically. Thermal conductivity of two thin standard disks (2 mm in thickness) located at the top and the bottom of the rock sample slightly affects the accuracy of thermal conductivity measurements. When the thermal conductivity of a sample is 3.0 W/m/K and that of two standard disks is 0.2 W/m/K, the relative error in measured thermal conductivity is very small (~0.01%). However, the relative error would reach up to -2.29% for the same sample when thermal conductivity of two disks is 0.5 W/m/K. The accuracy of thermal conductivity measurements strongly depends on thermal conductivity and the thickness of thermal compound that is applied to reduce thermal resistance at contacts between the rock sample and the bar. When the thickness of thermal compound (0.29 W/m/K) is 0.03 mm, we found that the relative error in measured thermal conductivity is 4.01%, while the relative error can be very significant (~12.2%) if the thickness increases to 0.1 mm. Then, we fixed the thickness (0.03 mm) and varied thermal conductivity of the thermal compound. We found that the relative error with an 1.0 W/m/K compound is 1.28%, and the relative error with a 0.29 W/m/K is 4.06%. When we repeated this test with a different thickness of the thermal compound (0.1 mm), the relative error with an 1.0 W/m/K compound is 3.93%, and that with a 0.29 W/m/K is 12.2%. In addition, the cell technique by Sass et al.(1971), which is widely used to measure thermal conductivity of rock fragments, was evaluated using the FEM modeling. A total of 483 isotropic and homogeneous spherical rock fragments in the sample holder were used to test numerically the accuracy of the cell technique. The result shows the relative error of -9.61% for rock fragments with the thermal conductivity of 2.5 W/m/K. In conclusion, we report quantified errors in the divided-bar and the cell technique for thermal conductivity measurements for rocks and fragments. We found that the FEM modeling can accurately mimic these measurement techniques and can help us to estimate measurement errors quantitatively.

Evaluation of causes and frequency of medication errors during information technology downtime.

PubMed

Hanuscak, Tara L; Szeinbach, Sheryl L; Seoane-Vazquez, Enrique; Reichert, Brendan J; McCluskey, Charles F

2009-06-15

The causes and frequency of medication errors occurring during information technology downtime were evaluated. Individuals from a convenience sample of 78 hospitals who were directly responsible for supporting and maintaining clinical information systems (CISs) and automated dispensing systems (ADSs) were surveyed using an online tool between February 2007 and May 2007 to determine if medication errors were reported during periods of system downtime. The errors were classified using the National Coordinating Council for Medication Error Reporting and Prevention severity scoring index. The percentage of respondents reporting downtime was estimated. Of the 78 eligible hospitals, 32 respondents with CIS and ADS responsibilities completed the online survey for a response rate of 41%. For computerized prescriber order entry, patch installations and system upgrades caused an average downtime of 57% over a 12-month period. Lost interface and interface malfunction were reported for centralized and decentralized ADSs, with an average downtime response of 34% and 29%, respectively. The average downtime response was 31% for software malfunctions linked to clinical decision-support systems. Although patient harm did not result from 30 (54%) medication errors, the potential for harm was present for 9 (16%) of these errors. Medication errors occurred during CIS and ADS downtime despite the availability of backup systems and standard protocols to handle periods of system downtime. Efforts should be directed to reduce the frequency and length of down-time in order to minimize medication errors during such downtime.

Prevalence and reporting of recruitment, randomisation and treatment errors in clinical trials: A systematic review.

PubMed

Yelland, Lisa N; Kahan, Brennan C; Dent, Elsa; Lee, Katherine J; Voysey, Merryn; Forbes, Andrew B; Cook, Jonathan A

2018-06-01

Background/aims In clinical trials, it is not unusual for errors to occur during the process of recruiting, randomising and providing treatment to participants. For example, an ineligible participant may inadvertently be randomised, a participant may be randomised in the incorrect stratum, a participant may be randomised multiple times when only a single randomisation is permitted or the incorrect treatment may inadvertently be issued to a participant at randomisation. Such errors have the potential to introduce bias into treatment effect estimates and affect the validity of the trial, yet there is little motivation for researchers to report these errors and it is unclear how often they occur. The aim of this study is to assess the prevalence of recruitment, randomisation and treatment errors and review current approaches for reporting these errors in trials published in leading medical journals. Methods We conducted a systematic review of individually randomised, phase III, randomised controlled trials published in New England Journal of Medicine, Lancet, Journal of the American Medical Association, Annals of Internal Medicine and British Medical Journal from January to March 2015. The number and type of recruitment, randomisation and treatment errors that were reported and how they were handled were recorded. The corresponding authors were contacted for a random sample of trials included in the review and asked to provide details on unreported errors that occurred during their trial. Results We identified 241 potentially eligible articles, of which 82 met the inclusion criteria and were included in the review. These trials involved a median of 24 centres and 650 participants, and 87% involved two treatment arms. Recruitment, randomisation or treatment errors were reported in 32 in 82 trials (39%) that had a median of eight errors. The most commonly reported error was ineligible participants inadvertently being randomised. No mention of recruitment, randomisation or treatment errors was found in the remaining 50 of 82 trials (61%). Based on responses from 9 of the 15 corresponding authors who were contacted regarding recruitment, randomisation and treatment errors, between 1% and 100% of the errors that occurred in their trials were reported in the trial publications. Conclusion Recruitment, randomisation and treatment errors are common in individually randomised, phase III trials published in leading medical journals, but reporting practices are inadequate and reporting standards are needed. We recommend researchers report all such errors that occurred during the trial and describe how they were handled in trial publications to improve transparency in reporting of clinical trials.

Simulation techniques for estimating error in the classification of normal patterns

NASA Technical Reports Server (NTRS)

Whitsitt, S. J.; Landgrebe, D. A.

1974-01-01

Methods of efficiently generating and classifying samples with specified multivariate normal distributions were discussed. Conservative confidence tables for sample sizes are given for selective sampling. Simulation results are compared with classified training data. Techniques for comparing error and separability measure for two normal patterns are investigated and used to display the relationship between the error and the Chernoff bound.

A Simple Method for Decreasing the Liquid Junction Potential in a Flow-through-Type Differential pH Sensor Probe Consisting of pH-FETs by Exerting Spatiotemporal Control of the Liquid Junction

PubMed Central

Yamada, Akira; Mohri, Satoshi; Nakamura, Michihiro; Naruse, Keiji

2015-01-01

The liquid junction potential (LJP), the phenomenon that occurs when two electrolyte solutions of different composition come into contact, prevents accurate measurements in potentiometry. The effect of the LJP is usually remarkable in measurements of diluted solutions with low buffering capacities or low ion concentrations. Our group has constructed a simple method to eliminate the LJP by exerting spatiotemporal control of a liquid junction (LJ) formed between two solutions, a sample solution and a baseline solution (BLS), in a flow-through-type differential pH sensor probe. The method was contrived based on microfluidics. The sensor probe is a differential measurement system composed of two ion-sensitive field-effect transistors (ISFETs) and one Ag/AgCl electrode. With our new method, the border region of the sample solution and BLS is vibrated in order to mix solutions and suppress the overshoot after the sample solution is suctioned into the sensor probe. Compared to the conventional method without vibration, our method shortened the settling time from over two min to 15 s and reduced the measurement error by 86% to within 0.060 pH. This new method will be useful for improving the response characteristics and decreasing the measurement error of many apparatuses that use LJs. PMID:25835300

Quality of major ion and total dissolved solids data from groundwater sampled by the National Water-Quality Assessment Program, 1992–2010

USGS Publications Warehouse

Gross, Eliza L.; Lindsey, Bruce D.; Rupert, Michael G.

2012-01-01

Field blank samples help determine the frequency and magnitude of contamination bias, and replicate samples help determine the sampling variability (error) of measured analyte concentrations. Quality control data were evaluated for calcium, magnesium, sodium, potassium, chloride, sulfate, fluoride, silica, and total dissolved solids. A 99-percent upper confidence limit is calculated from field blanks to assess the potential for contamination bias. For magnesium, potassium, chloride, sulfate, and fluoride, potential contamination in more than 95 percent of environmental samples is less than or equal to the common maximum reporting level. Contamination bias has little effect on measured concentrations greater than 4.74 mg/L (milligrams per liter) for calcium, 14.98 mg/L for silica, 4.9 mg/L for sodium, and 120 mg/L for total dissolved solids. Estimates of sampling variability are calculated for high and low ranges of concentration for major ions and total dissolved solids. Examples showing the calculation of confidence intervals and how to determine whether measured differences between two water samples are significant are presented.

Adverse Drug Events caused by Serious Medication Administration Errors

PubMed Central

Sawarkar, Abhivyakti; Keohane, Carol A.; Maviglia, Saverio; Gandhi, Tejal K; Poon, Eric G

2013-01-01

OBJECTIVE To determine how often serious or life-threatening medication administration errors with the potential to cause patient harm (or potential adverse drug events) result in actual patient harm (or adverse drug events (ADEs)) in the hospital setting. DESIGN Retrospective chart review of clinical events that transpired following observed medication administration errors. BACKGROUND Medication errors are common at the medication administration stage for hospitalized patients. While many of these errors are considered capable of causing patient harm, it is not clear how often patients are actually harmed by these errors. METHODS In a previous study where 14,041 medication administrations in an acute-care hospital were directly observed, investigators discovered 1271 medication administration errors, of which 133 had the potential to cause serious or life-threatening harm to patients and were considered serious or life-threatening potential ADEs. In the current study, clinical reviewers conducted detailed chart reviews of cases where a serious or life-threatening potential ADE occurred to determine if an actual ADE developed following the potential ADE. Reviewers further assessed the severity of the ADE and attribution to the administration error. RESULTS Ten (7.5% [95% C.I. 6.98, 8.01]) actual adverse drug events or ADEs resulted from the 133 serious and life-threatening potential ADEs, of which 6 resulted in significant, three in serious, and one life threatening injury. Therefore 4 (3% [95% C.I. 2.12, 3.6]) serious and life threatening potential ADEs led to serious or life threatening ADEs. Half of the ten actual ADEs were caused by dosage or monitoring errors for anti-hypertensives. The life threatening ADE was caused by an error that was both a transcription and a timing error. CONCLUSION Potential ADEs at the medication administration stage can cause serious patient harm. Given previous estimates of serious or life-threatening potential ADE of 1.33 per 100 medication doses administered, in a hospital where 6 million doses are administered per year, about 4000 preventable ADEs would be attributable to medication administration errors annually. PMID:22791691

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

Short communication: determination of potential 5-hydroxymethyl-2-furaldehyde and 2-furaldehyde compounds in follow-on milks and infant formulas using the high-performance liquid chromatography method.

PubMed

Er Demirhan, B; Demirhan, B; Sönmez, C; Torul, H; Tamer, U; Yentür, G

2015-02-01

The aim of present study was to determine the levels of potential 5-hydroxymethyl-2-furaldehyde (HMF) and 2-furaldehyde (F) in 109 baby food samples (60 follow-on milks, 49 cereal- and milk-based infant formulas) obtained from different markets in Ankara (Turkey). Potential HMF and F compounds were determined by HPLC. Mean levels (± standard error) of HMF and F of follow-on milk samples were found to be 237.85±18.25 and 9.44±0.39 µg/100mL, respectively. Regarding the infant formulas, mean levels of HMF and F were found to be 905.41±91.94 and 13.22±1.21 µg/100g. As a result, potential HMF was determined in all of the samples; potential F was determined in all the samples except 1. The mean levels of potential HMF and F of infant formulas were higher than mean levels of potential HMF and F of follow-on milks. In addition, HMF and F values of some samples with an imminent expiration date were found to be higher than HMF and F values of the other samples. At present, no limits have been established in the Turkish Food Codex (TFC) for furfural compounds concentrations in infant formula and milks. Establishing limits related to these compounds would be important for protecting the quality of infant foods. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Auditing as Part of the Terminology Design Life Cycle

PubMed Central

Min, Hua; Perl, Yehoshua; Chen, Yan; Halper, Michael; Geller, James; Wang, Yue

2006-01-01

Objective To develop and test an auditing methodology for detecting errors in medical terminologies satisfying systematic inheritance. This methodology is based on various abstraction taxonomies that provide high-level views of a terminology and highlight potentially erroneous concepts. Design Our auditing methodology is based on dividing concepts of a terminology into smaller, more manageable units. First, we divide the terminology’s concepts into areas according to their relationships/roles. Then each multi-rooted area is further divided into partial-areas (p-areas) that are singly-rooted. Each p-area contains a set of structurally and semantically uniform concepts. Two kinds of abstraction networks, called the area taxonomy and p-area taxonomy, are derived. These taxonomies form the basis for the auditing approach. Taxonomies tend to highlight potentially erroneous concepts in areas and p-areas. Human reviewers can focus their auditing efforts on the limited number of problematic concepts following two hypotheses on the probable concentration of errors. Results A sample of the area taxonomy and p-area taxonomy for the Biological Process (BP) hierarchy of the National Cancer Institute Thesaurus (NCIT) was derived from the application of our methodology to its concepts. These views led to the detection of a number of different kinds of errors that are reported, and to confirmation of the hypotheses on error concentration in this hierarchy. Conclusion Our auditing methodology based on area and p-area taxonomies is an efficient tool for detecting errors in terminologies satisfying systematic inheritance of roles, and thus facilitates their maintenance. This methodology concentrates a domain expert’s manual review on portions of the concepts with a high likelihood of errors. PMID:16929044

The Effect of Random Error on Diagnostic Accuracy Illustrated with the Anthropometric Diagnosis of Malnutrition

PubMed Central

2016-01-01

Background It is often thought that random measurement error has a minor effect upon the results of an epidemiological survey. Theoretically, errors of measurement should always increase the spread of a distribution. Defining an illness by having a measurement outside an established healthy range will lead to an inflated prevalence of that condition if there are measurement errors. Methods and results A Monte Carlo simulation was conducted of anthropometric assessment of children with malnutrition. Random errors of increasing magnitude were imposed upon the populations and showed that there was an increase in the standard deviation with each of the errors that became exponentially greater with the magnitude of the error. The potential magnitude of the resulting error of reported prevalence of malnutrition were compared with published international data and found to be of sufficient magnitude to make a number of surveys and the numerous reports and analyses that used these data unreliable. Conclusions The effect of random error in public health surveys and the data upon which diagnostic cut-off points are derived to define “health” has been underestimated. Even quite modest random errors can more than double the reported prevalence of conditions such as malnutrition. Increasing sample size does not address this problem, and may even result in less accurate estimates. More attention needs to be paid to the selection, calibration and maintenance of instruments, measurer selection, training & supervision, routine estimation of the likely magnitude of errors using standardization tests, use of statistical likelihood of error to exclude data from analysis and full reporting of these procedures in order to judge the reliability of survey reports. PMID:28030627

Theoretical and experimental errors for in situ measurements of plant water potential.

PubMed

Shackel, K A

1984-07-01

Errors in psychrometrically determined values of leaf water potential caused by tissue resistance to water vapor exchange and by lack of thermal equilibrium were evaluated using commercial in situ psychrometers (Wescor Inc., Logan, UT) on leaves of Tradescantia virginiana (L.). Theoretical errors in the dewpoint method of operation for these sensors were demonstrated. After correction for these errors, in situ measurements of leaf water potential indicated substantial errors caused by tissue resistance to water vapor exchange (4 to 6% reduction in apparent water potential per second of cooling time used) resulting from humidity depletions in the psychrometer chamber during the Peltier condensation process. These errors were avoided by use of a modified procedure for dewpoint measurement. Large changes in apparent water potential were caused by leaf and psychrometer exposure to moderate levels of irradiance. These changes were correlated with relatively small shifts in psychrometer zero offsets (-0.6 to -1.0 megapascals per microvolt), indicating substantial errors caused by nonisothermal conditions between the leaf and the psychrometer. Explicit correction for these errors is not possible with the current psychrometer design.

Theoretical and Experimental Errors for In Situ Measurements of Plant Water Potential 1

PubMed Central

Shackel, Kenneth A.

1984-01-01

Errors in psychrometrically determined values of leaf water potential caused by tissue resistance to water vapor exchange and by lack of thermal equilibrium were evaluated using commercial in situ psychrometers (Wescor Inc., Logan, UT) on leaves of Tradescantia virginiana (L.). Theoretical errors in the dewpoint method of operation for these sensors were demonstrated. After correction for these errors, in situ measurements of leaf water potential indicated substantial errors caused by tissue resistance to water vapor exchange (4 to 6% reduction in apparent water potential per second of cooling time used) resulting from humidity depletions in the psychrometer chamber during the Peltier condensation process. These errors were avoided by use of a modified procedure for dewpoint measurement. Large changes in apparent water potential were caused by leaf and psychrometer exposure to moderate levels of irradiance. These changes were correlated with relatively small shifts in psychrometer zero offsets (−0.6 to −1.0 megapascals per microvolt), indicating substantial errors caused by nonisothermal conditions between the leaf and the psychrometer. Explicit correction for these errors is not possible with the current psychrometer design. PMID:16663701

Biostatistical analysis of quantitative immunofluorescence microscopy images.

PubMed

Giles, C; Albrecht, M A; Lam, V; Takechi, R; Mamo, J C

2016-12-01

Semiquantitative immunofluorescence microscopy has become a key methodology in biomedical research. Typical statistical workflows are considered in the context of avoiding pseudo-replication and marginalising experimental error. However, immunofluorescence microscopy naturally generates hierarchically structured data that can be leveraged to improve statistical power and enrich biological interpretation. Herein, we describe a robust distribution fitting procedure and compare several statistical tests, outlining their potential advantages/disadvantages in the context of biological interpretation. Further, we describe tractable procedures for power analysis that incorporates the underlying distribution, sample size and number of images captured per sample. The procedures outlined have significant potential for increasing understanding of biological processes and decreasing both ethical and financial burden through experimental optimization. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Efficient Computation of Anharmonic Force Constants via q-space, with Application to Graphene

NASA Astrophysics Data System (ADS)

Kornbluth, Mordechai; Marianetti, Chris

We present a new approach for extracting anharmonic force constants from a sparse sampling of the anharmonic dynamical tensor. We calculate the derivative of the energy with respect to q-space displacements (phonons) and strain, which guarantees the absence of supercell image errors. Central finite differences provide a well-converged quadratic error tail for each derivative, separating the contribution of each anharmonic order. These derivatives populate the anharmonic dynamical tensor in a sparse mesh that bounds the Brillouin Zone, which ensures comprehensive sampling of q-space while exploiting small-cell calculations for efficient, high-throughput computation. This produces a well-converged and precisely-defined dataset, suitable for big-data approaches. We transform this sparsely-sampled anharmonic dynamical tensor to real-space anharmonic force constants that obey full space-group symmetries by construction. Machine-learning techniques identify the range of real-space interactions. We show the entire process executed for graphene, up to and including the fifth-order anharmonic force constants. This method successfully calculates strain-based phonon renormalization in graphene, even under large strains, which solves a major shortcoming of previous potentials.

Modeling misidentification errors that result from use of genetic tags in capture-recapture studies

USGS Publications Warehouse

Yoshizaki, J.; Brownie, C.; Pollock, K.H.; Link, W.A.

2011-01-01

Misidentification of animals is potentially important when naturally existing features (natural tags) such as DNA fingerprints (genetic tags) are used to identify individual animals. For example, when misidentification leads to multiple identities being assigned to an animal, traditional estimators tend to overestimate population size. Accounting for misidentification in capture-recapture models requires detailed understanding of the mechanism. Using genetic tags as an example, we outline a framework for modeling the effect of misidentification in closed population studies when individual identification is based on natural tags that are consistent over time (non-evolving natural tags). We first assume a single sample is obtained per animal for each capture event, and then generalize to the case where multiple samples (such as hair or scat samples) are collected per animal per capture occasion. We introduce methods for estimating population size and, using a simulation study, we show that our new estimators perform well for cases with moderately high capture probabilities or high misidentification rates. In contrast, conventional estimators can seriously overestimate population size when errors due to misidentification are ignored. ?? 2009 Springer Science+Business Media, LLC.

Performance monitoring during associative learning and its relation to obsessive-compulsive characteristics.

PubMed

Doñamayor, Nuria; Dinani, Jakob; Römisch, Manuel; Ye, Zheng; Münte, Thomas F

2014-10-01

Neural responses to performance errors and external feedback have been suggested to be altered in obsessive-compulsive disorder. In the current study, an associative learning task was used in healthy participants assessed for obsessive-compulsive symptoms by the OCI-R questionnaire. The task included a condition with equivocal feedback that did not inform about the participants' performance. Following incorrect responses, an error-related negativity and an error positivity were observed. In the feedback phase, the largest feedback-related negativity was observed following equivocal feedback. Theta and beta oscillatory components were found following incorrect and correct responses, respectively, and an increase in theta power was associated with negative and equivocal feedback. Changes over time were also explored as an indicator for possible learning effects. Finally, event-related potentials and oscillatory components were found to be uncorrelated with OCI-R scores in the current non-clinical sample. Copyright © 2014 Elsevier B.V. All rights reserved.

Bayesian assessment of overtriage and undertriage at a level I trauma centre.

PubMed

DiDomenico, Paul B; Pietzsch, Jan B; Paté-Cornell, M Elisabeth

2008-07-13

We analysed the trauma triage system at a specific level I trauma centre to assess rates of over- and undertriage and to support recommendations for system improvements. The triage process is designed to estimate the severity of patient injury and allocate resources accordingly, with potential errors of overestimation (overtriage) consuming excess resources and underestimation (undertriage) potentially leading to medical errors.We first modelled the overall trauma system using risk analysis methods to understand interdependencies among the actions of the participants. We interviewed six experienced trauma surgeons to obtain their expert opinion of the over- and undertriage rates occurring in the trauma centre. We then assessed actual over- and undertriage rates in a random sample of 86 trauma cases collected over a six-week period at the same centre. We employed Bayesian analysis to quantitatively combine the data with the prior probabilities derived from expert opinion in order to obtain posterior distributions. The results were estimates of overtriage and undertriage in 16.1 and 4.9% of patients, respectively. This Bayesian approach, which provides a quantitative assessment of the error rates using both case data and expert opinion, provides a rational means of obtaining a best estimate of the system's performance. The overall approach that we describe in this paper can be employed more widely to analyse complex health care delivery systems, with the objective of reduced errors, patient risk and excess costs.

Psychrometric Measurement of Leaf Water Potential: Lack of Error Attributable to Leaf Permeability.

PubMed

Barrs, H D

1965-07-02

A report that low permeability could cause gross errors in psychrometric determinations of water potential in leaves has not been confirmed. No measurable error from this source could be detected for either of two types of thermocouple psychrometer tested on four species, each at four levels of water potential. No source of error other than tissue respiration could be demonstrated.

"Bed Side" Human Milk Analysis in the Neonatal Intensive Care Unit: A Systematic Review.

PubMed

Fusch, Gerhard; Kwan, Celia; Kotrri, Gynter; Fusch, Christoph

2017-03-01

Human milk analyzers can measure macronutrient content in native breast milk to tailor adequate supplementation with fortifiers. This article reviews all studies using milk analyzers, including (i) evaluation of devices, (ii) the impact of different conditions on the macronutrient analysis of human milk, and (iii) clinical trials to improve growth. Results lack consistency, potentially due to systematic errors in the validation of the device, or pre-analytical sample preparation errors like homogenization. It is crucial to introduce good laboratory and clinical practice when using these devices; otherwise a non-validated clinical usage can severely affect growth outcomes of infants. Copyright © 2016 Elsevier Inc. All rights reserved.

Paediatric in-patient prescribing errors in Malaysia: a cross-sectional multicentre study.

PubMed

Khoo, Teik Beng; Tan, Jing Wen; Ng, Hoong Phak; Choo, Chong Ming; Bt Abdul Shukor, Intan Nor Chahaya; Teh, Siao Hean

2017-06-01

Background There is a lack of large comprehensive studies in developing countries on paediatric in-patient prescribing errors in different settings. Objectives To determine the characteristics of in-patient prescribing errors among paediatric patients. Setting General paediatric wards, neonatal intensive care units and paediatric intensive care units in government hospitals in Malaysia. Methods This is a cross-sectional multicentre study involving 17 participating hospitals. Drug charts were reviewed in each ward to identify the prescribing errors. All prescribing errors identified were further assessed for their potential clinical consequences, likely causes and contributing factors. Main outcome measures Incidence, types, potential clinical consequences, causes and contributing factors of the prescribing errors. Results The overall prescribing error rate was 9.2% out of 17,889 prescribed medications. There was no significant difference in the prescribing error rates between different types of hospitals or wards. The use of electronic prescribing had a higher prescribing error rate than manual prescribing (16.9 vs 8.2%, p < 0.05). Twenty eight (1.7%) prescribing errors were deemed to have serious potential clinical consequences and 2 (0.1%) were judged to be potentially fatal. Most of the errors were attributed to human factors, i.e. performance or knowledge deficit. The most common contributing factors were due to lack of supervision or of knowledge. Conclusions Although electronic prescribing may potentially improve safety, it may conversely cause prescribing errors due to suboptimal interfaces and cumbersome work processes. Junior doctors need specific training in paediatric prescribing and close supervision to reduce prescribing errors in paediatric in-patients.

Dysfunctional error-related processing in incarcerated youth with elevated psychopathic traits

PubMed Central

Maurer, J. Michael; Steele, Vaughn R.; Cope, Lora M.; Vincent, Gina M.; Stephen, Julia M.; Calhoun, Vince D.; Kiehl, Kent A.

2016-01-01

Adult psychopathic offenders show an increased propensity towards violence, impulsivity, and recidivism. A subsample of youth with elevated psychopathic traits represent a particularly severe subgroup characterized by extreme behavioral problems and comparable neurocognitive deficits as their adult counterparts, including perseveration deficits. Here, we investigate response-locked event-related potential (ERP) components (the error-related negativity [ERN/Ne] related to early error-monitoring processing and the error-related positivity [Pe] involved in later error-related processing) in a sample of incarcerated juvenile male offenders (n = 100) who performed a response inhibition Go/NoGo task. Psychopathic traits were assessed using the Hare Psychopathy Checklist: Youth Version (PCL:YV). The ERN/Ne and Pe were analyzed with classic windowed ERP components and principal component analysis (PCA). Using linear regression analyses, PCL:YV scores were unrelated to the ERN/Ne, but were negatively related to Pe mean amplitude. Specifically, the PCL:YV Facet 4 subscale reflecting antisocial traits emerged as a significant predictor of reduced amplitude of a subcomponent underlying the Pe identified with PCA. This is the first evidence to suggest a negative relationship between adolescent psychopathy scores and Pe mean amplitude. PMID:26930170

Designing image segmentation studies: Statistical power, sample size and reference standard quality.

PubMed

Gibson, Eli; Hu, Yipeng; Huisman, Henkjan J; Barratt, Dean C

2017-12-01

Segmentation algorithms are typically evaluated by comparison to an accepted reference standard. The cost of generating accurate reference standards for medical image segmentation can be substantial. Since the study cost and the likelihood of detecting a clinically meaningful difference in accuracy both depend on the size and on the quality of the study reference standard, balancing these trade-offs supports the efficient use of research resources. In this work, we derive a statistical power calculation that enables researchers to estimate the appropriate sample size to detect clinically meaningful differences in segmentation accuracy (i.e. the proportion of voxels matching the reference standard) between two algorithms. Furthermore, we derive a formula to relate reference standard errors to their effect on the sample sizes of studies using lower-quality (but potentially more affordable and practically available) reference standards. The accuracy of the derived sample size formula was estimated through Monte Carlo simulation, demonstrating, with 95% confidence, a predicted statistical power within 4% of simulated values across a range of model parameters. This corresponds to sample size errors of less than 4 subjects and errors in the detectable accuracy difference less than 0.6%. The applicability of the formula to real-world data was assessed using bootstrap resampling simulations for pairs of algorithms from the PROMISE12 prostate MR segmentation challenge data set. The model predicted the simulated power for the majority of algorithm pairs within 4% for simulated experiments using a high-quality reference standard and within 6% for simulated experiments using a low-quality reference standard. A case study, also based on the PROMISE12 data, illustrates using the formulae to evaluate whether to use a lower-quality reference standard in a prostate segmentation study. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The role of misclassification in estimating proportions and an estimator of misclassification probability

Treesearch

Patrick L. Zimmerman; Greg C. Liknes

2010-01-01

Dot grids are often used to estimate the proportion of land cover belonging to some class in an aerial photograph. Interpreter misclassification is an often-ignored source of error in dot-grid sampling that has the potential to significantly bias proportion estimates. For the case when the true class of items is unknown, we present a maximum-likelihood estimator of...

Flux Sampling Errors for Aircraft and Towers

NASA Technical Reports Server (NTRS)

Mahrt, Larry

1998-01-01

Various errors and influences leading to differences between tower- and aircraft-measured fluxes are surveyed. This survey is motivated by reports in the literature that aircraft fluxes are sometimes smaller than tower-measured fluxes. Both tower and aircraft flux errors are larger with surface heterogeneity due to several independent effects. Surface heterogeneity may cause tower flux errors to increase with decreasing wind speed. Techniques to assess flux sampling error are reviewed. Such error estimates suffer various degrees of inapplicability in real geophysical time series due to nonstationarity of tower time series (or inhomogeneity of aircraft data). A new measure for nonstationarity is developed that eliminates assumptions on the form of the nonstationarity inherent in previous methods. When this nonstationarity measure becomes large, the surface energy imbalance increases sharply. Finally, strategies for obtaining adequate flux sampling using repeated aircraft passes and grid patterns are outlined.

Measuring coverage in MNCH: total survey error and the interpretation of intervention coverage estimates from household surveys.

PubMed

Eisele, Thomas P; Rhoda, Dale A; Cutts, Felicity T; Keating, Joseph; Ren, Ruilin; Barros, Aluisio J D; Arnold, Fred

2013-01-01

Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low- and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used.

Measuring Coverage in MNCH: Total Survey Error and the Interpretation of Intervention Coverage Estimates from Household Surveys

PubMed Central

Eisele, Thomas P.; Rhoda, Dale A.; Cutts, Felicity T.; Keating, Joseph; Ren, Ruilin; Barros, Aluisio J. D.; Arnold, Fred

2013-01-01

Nationally representative household surveys are increasingly relied upon to measure maternal, newborn, and child health (MNCH) intervention coverage at the population level in low- and middle-income countries. Surveys are the best tool we have for this purpose and are central to national and global decision making. However, all survey point estimates have a certain level of error (total survey error) comprising sampling and non-sampling error, both of which must be considered when interpreting survey results for decision making. In this review, we discuss the importance of considering these errors when interpreting MNCH intervention coverage estimates derived from household surveys, using relevant examples from national surveys to provide context. Sampling error is usually thought of as the precision of a point estimate and is represented by 95% confidence intervals, which are measurable. Confidence intervals can inform judgments about whether estimated parameters are likely to be different from the real value of a parameter. We recommend, therefore, that confidence intervals for key coverage indicators should always be provided in survey reports. By contrast, the direction and magnitude of non-sampling error is almost always unmeasurable, and therefore unknown. Information error and bias are the most common sources of non-sampling error in household survey estimates and we recommend that they should always be carefully considered when interpreting MNCH intervention coverage based on survey data. Overall, we recommend that future research on measuring MNCH intervention coverage should focus on refining and improving survey-based coverage estimates to develop a better understanding of how results should be interpreted and used. PMID:23667331

Near Infrared Spectroscopy Detection and Quantification of Herbal Medicines Adulterated with Sibutramine.

PubMed

da Silva, Neirivaldo Cavalcante; Honorato, Ricardo Saldanha; Pimentel, Maria Fernanda; Garrigues, Salvador; Cervera, Maria Luisa; de la Guardia, Miguel

2015-09-01

There is an increasing demand for herbal medicines in weight loss treatment. Some synthetic chemicals, such as sibutramine (SB), have been detected as adulterants in herbal formulations. In this study, two strategies using near infrared (NIR) spectroscopy have been developed to evaluate potential adulteration of herbal medicines with SB: a qualitative screening approach and a quantitative methodology based on multivariate calibration. Samples were composed by products commercialized as herbal medicines, as well as by laboratory adulterated samples. Spectra were obtained in the range of 14,000-4000 per cm. Using PLS-DA, a correct classification of 100% was achieved for the external validation set. In the quantitative approach, the root mean squares error of prediction (RMSEP), for both PLS and MLR models, was 0.2% w/w. The results prove the potential of NIR spectroscopy and multivariate calibration in quantifying sibutramine in adulterated herbal medicines samples. © 2015 American Academy of Forensic Sciences.

Discrepancies in reporting the CAG repeat lengths for Huntington's disease

PubMed Central

Quarrell, Oliver W; Handley, Olivia; O'Donovan, Kirsty; Dumoulin, Christine; Ramos-Arroyo, Maria; Biunno, Ida; Bauer, Peter; Kline, Margaret; Landwehrmeyer, G Bernhard

2012-01-01

Huntington's disease results from a CAG repeat expansion within the Huntingtin gene; this is measured routinely in diagnostic laboratories. The European Huntington's Disease Network REGISTRY project centrally measures CAG repeat lengths on fresh samples; these were compared with the original results from 121 laboratories across 15 countries. We report on 1326 duplicate results; a discrepancy in reporting the upper allele occurred in 51% of cases, this reduced to 13.3% and 9.7% when we applied acceptable measurement errors proposed by the American College of Medical Genetics and the Draft European Best Practice Guidelines, respectively. Duplicate results were available for 1250 lower alleles; discrepancies occurred in 40% of cases. Clinically significant discrepancies occurred in 4.0% of cases with a potential unexplained misdiagnosis rate of 0.3%. There was considerable variation in the discrepancy rate among 10 of the countries participating in this study. Out of 1326 samples, 348 were re-analysed by an accredited diagnostic laboratory, based in Germany, with concordance rates of 93% and 94% for the upper and lower alleles, respectively. This became 100% if the acceptable measurement errors were applied. The central laboratory correctly reported allele sizes for six standard reference samples, blind to the known result. Our study differs from external quality assessment (EQA) schemes in that these are duplicate results obtained from a large sample of patients across the whole diagnostic range. We strongly recommend that laboratories state an error rate for their measurement on the report, participate in EQA schemes and use reference materials regularly to adjust their own internal standards. PMID:21811303

Adaptive control of theophylline therapy: importance of blood sampling times.

PubMed

D'Argenio, D Z; Khakmahd, K

1983-10-01

A two-observation protocol for estimating theophylline clearance during a constant-rate intravenous infusion is used to examine the importance of blood sampling schedules with regard to the information content of resulting concentration data. Guided by a theory for calculating maximally informative sample times, population simulations are used to assess the effect of specific sampling times on the precision of resulting clearance estimates and subsequent predictions of theophylline plasma concentrations. The simulations incorporated noise terms for intersubject variability, dosing errors, sample collection errors, and assay error. Clearance was estimated using Chiou's method, least squares, and a Bayesian estimation procedure. The results of these simulations suggest that clinically significant estimation and prediction errors may result when using the above two-point protocol for estimating theophylline clearance if the time separating the two blood samples is less than one population mean elimination half-life.

Reducing representativeness and sampling errors in radio occultation-radiosonde comparisons

NASA Astrophysics Data System (ADS)

Gilpin, Shay; Rieckh, Therese; Anthes, Richard

2018-05-01

Radio occultation (RO) and radiosonde (RS) comparisons provide a means of analyzing errors associated with both observational systems. Since RO and RS observations are not taken at the exact same time or location, temporal and spatial sampling errors resulting from atmospheric variability can be significant and inhibit error analysis of the observational systems. In addition, the vertical resolutions of RO and RS profiles vary and vertical representativeness errors may also affect the comparison. In RO-RS comparisons, RO observations are co-located with RS profiles within a fixed time window and distance, i.e. within 3-6 h and circles of radii ranging between 100 and 500 km. In this study, we first show that vertical filtering of RO and RS profiles to a common vertical resolution reduces representativeness errors. We then test two methods of reducing horizontal sampling errors during RO-RS comparisons: restricting co-location pairs to within ellipses oriented along the direction of wind flow rather than circles and applying a spatial-temporal sampling correction based on model data. Using data from 2011 to 2014, we compare RO and RS differences at four GCOS Reference Upper-Air Network (GRUAN) RS stations in different climatic locations, in which co-location pairs were constrained to a large circle ( ˜ 666 km radius), small circle ( ˜ 300 km radius), and ellipse parallel to the wind direction ( ˜ 666 km semi-major axis, ˜ 133 km semi-minor axis). We also apply a spatial-temporal sampling correction using European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim) gridded data. Restricting co-locations to within the ellipse reduces root mean square (RMS) refractivity, temperature, and water vapor pressure differences relative to RMS differences within the large circle and produces differences that are comparable to or less than the RMS differences within circles of similar area. Applying the sampling correction shows the most significant reduction in RMS differences, such that RMS differences are nearly identical to the sampling correction regardless of the geometric constraints. We conclude that implementing the spatial-temporal sampling correction using a reliable model will most effectively reduce sampling errors during RO-RS comparisons; however, if a reliable model is not available, restricting spatial comparisons to within an ellipse parallel to the wind flow will reduce sampling errors caused by horizontal atmospheric variability.

Increasing point-count duration increases standard error

USGS Publications Warehouse

Smith, W.P.; Twedt, D.J.; Hamel, P.B.; Ford, R.P.; Wiedenfeld, D.A.; Cooper, R.J.

1998-01-01

We examined data from point counts of varying duration in bottomland forests of west Tennessee and the Mississippi Alluvial Valley to determine if counting interval influenced sampling efficiency. Estimates of standard error increased as point count duration increased both for cumulative number of individuals and species in both locations. Although point counts appear to yield data with standard errors proportional to means, a square root transformation of the data may stabilize the variance. Using long (>10 min) point counts may reduce sample size and increase sampling error, both of which diminish statistical power and thereby the ability to detect meaningful changes in avian populations.

An adaptive interpolation scheme for molecular potential energy surfaces

NASA Astrophysics Data System (ADS)

Kowalewski, Markus; Larsson, Elisabeth; Heryudono, Alfa

2016-08-01

The calculation of potential energy surfaces for quantum dynamics can be a time consuming task—especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm based on polyharmonic splines combined with a partition of unity approach. The adaptive node refinement allows to greatly reduce the number of sample points by employing a local error estimate. The algorithm and its scaling behavior are evaluated for a model function in 2, 3, and 4 dimensions. The developed algorithm allows for a more rapid and reliable interpolation of a potential energy surface within a given accuracy compared to the non-adaptive version.

On using summary statistics from an external calibration sample to correct for covariate measurement error.

PubMed

Guo, Ying; Little, Roderick J; McConnell, Daniel S

2012-01-01

Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

Effect of temporal sampling and timing for soil moisture measurements at field scale

NASA Astrophysics Data System (ADS)

Snapir, B.; Hobbs, S.

2012-04-01

Estimating soil moisture at field scale is valuable for various applications such as irrigation scheduling in cultivated watersheds, flood and drought prediction, waterborne disease spread assessment, or even determination of mobility with lightweight vehicles. Synthetic aperture radar on satellites in low Earth orbit can provide fine resolution images with a repeat time of a few days. For an Earth observing satellite, the choice of the orbit is driven in particular by the frequency of measurements required to meet a certain accuracy in retrieving the parameters of interest. For a given target, having only one image every week may not enable to capture the full dynamic range of soil moisture - soil moisture can change significantly within a day when rainfall occurs. Hence this study focuses on the effect of temporal sampling and timing of measurements in terms of error on the retrieved signal. All the analyses are based on in situ measurements of soil moisture (acquired every 30 min) from the OzNet Hydrological Monitoring Network in Australia for different fields over several years. The first study concerns sampling frequency. Measurements at different frequencies were simulated by sub-sampling the original data. Linear interpolation was used to estimate the missing intermediate values, and then this time series was compared to the original. The difference between these two signals is computed for different levels of sub-sampling. Results show that the error increases linearly when the interval is less than 1 day. For intervals longer than a day, a sinusoidal component appears on top of the linear growth due to the diurnal variation of surface soil moisture. Thus, for example, the error with measurements every 4.5 days can be slightly less than the error with measurements every 2 days. Next, for a given sampling interval, this study evaluated the effect of the time during the day at which measurements are made. Of course when measurements are very frequent the time of acquisition does not matter, but when few measurements are available (sampling interval > 1 day), the time of acquisition can be important. It is shown that with daily measurements the error can double depending on the time of acquisition. This result is very sensitive to the phase of the sinusoidal variation of soil moisture. For example, in autumn for a given field with soil moisture ranging from 7.08% to 11.44% (mean and standard deviation being respectively 8.68% and 0.74%), daily measurements at 2 pm lead to a mean error of 0.47% v/v, while daily measurements at 9 am/pm produce a mean error of 0.24% v/v. The minimum of the sinusoid occurs every afternoon around 2 pm, after interpolation, measurements acquired at this time underestimate soil moisture, whereas measurements around 9 am/pm correspond to nodes of the sinusoid, hence they represent the average soil moisture. These results concerning the frequency and the timing of measurements can potentially drive the schedule of satellite image acquisition over some fields.

Comparison of several analytical methods for the determination of tin in geochemical samples as a function of tin speciation

USGS Publications Warehouse

Kane, J.S.; Evans, J.R.; Jackson, J.C.

1989-01-01

Accurate and precise determinations of tin in geological materials are needed for fundamental studies of tin geochemistry, and for tin prospecting purposes. Achieving the required accuracy is difficult because of the different matrices in which Sn can occur (i.e. sulfides, silicates and cassiterite), and because of the variability of literature values for Sn concentrations in geochemical reference materials. We have evaluated three methods for the analysis of samples for Sn concentration: graphite furnace atomic absorption spectrometry (HGA-AAS) following iodide extraction, inductively coupled plasma atomic emission spectrometry (ICP-OES), and energy-dispersive X-ray fluorescence (EDXRF) spectrometry. Two of these methods (HGA-AAS and ICP-OES) required sample decomposition either by acid digestion or fusion, while the third (EDXRF) was performed directly on the powdered sample. Analytical details of all three methods, their potential errors, and the steps necessary to correct these errors were investigated. Results showed that similar accuracy was achieved from all methods for unmineralized samples, which contain no known Sn-bearing phase. For mineralized samples, which contain Sn-bearing minerals, either cassiterite or stannous sulfides, only EDXRF and fusion ICP-OES methods provided acceptable accuracy. This summary of our study provides information which helps to assure correct interpretation of data bases for underlying geochemical processes, regardless of method of data collection and its inherent limitations. ?? 1989.

Evaluation of process errors in bed load sampling using a Dune Model

USGS Publications Warehouse

Gomez, Basil; Troutman, Brent M.

1997-01-01

Reliable estimates of the streamwide bed load discharge obtained using sampling devices are dependent upon good at-a-point knowledge across the full width of the channel. Using field data and information derived from a model that describes the geometric features of a dune train in terms of a spatial process observed at a fixed point in time, we show that sampling errors decrease as the number of samples collected increases, and the number of traverses of the channel over which the samples are collected increases. It also is preferable that bed load sampling be conducted at a pace which allows a number of bed forms to pass through the sampling cross section. The situations we analyze and simulate pertain to moderate transport conditions in small rivers. In such circumstances, bed load sampling schemes typically should involve four or five traverses of a river, and the collection of 20–40 samples at a rate of five or six samples per hour. By ensuring that spatial and temporal variability in the transport process is accounted for, such a sampling design reduces both random and systematic errors and hence minimizes the total error involved in the sampling process.

Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

PubMed

Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

2014-09-09

Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

Measurement error: Implications for diagnosis and discrepancy models of developmental dyslexia.

PubMed

Cotton, Sue M; Crewther, David P; Crewther, Sheila G

2005-08-01

The diagnosis of developmental dyslexia (DD) is reliant on a discrepancy between intellectual functioning and reading achievement. Discrepancy-based formulae have frequently been employed to establish the significance of the difference between 'intelligence' and 'actual' reading achievement. These formulae, however, often fail to take into consideration test reliability and the error associated with a single test score. This paper provides an illustration of the potential effects that test reliability and measurement error can have on the diagnosis of dyslexia, with particular reference to discrepancy models. The roles of reliability and standard error of measurement (SEM) in classic test theory are also briefly reviewed. This is followed by illustrations of how SEM and test reliability can aid with the interpretation of a simple discrepancy-based formula of DD. It is proposed that a lack of consideration of test theory in the use of discrepancy-based models of DD can lead to misdiagnosis (both false positives and false negatives). Further, misdiagnosis in research samples affects reproducibility and generalizability of findings. This in turn, may explain current inconsistencies in research on the perceptual, sensory, and motor correlates of dyslexia.

Electron Beam Propagation Through a Magnetic Wiggler with Random Field Errors

DTIC Science & Technology

1989-08-21

Another quantity of interest is the vector potential 6.A,.(:) associated with the field error 6B,,,(:). Defining the normalized vector potentials ba = ebA...then follows that the correlation of the normalized vector potential errors is given by 1 . 12 (-a.(zj)a.,(z2)) = a,k,, dz’ , dz" (bBE(z’)bB , (z")) a2...Throughout the following, terms of order O(z:/z) will be neglected. Similarly, for the y-component of the normalized vector potential errors, one

Sampling Error in a Particulate Mixture: An Analytical Chemistry Experiment.

ERIC Educational Resources Information Center

Kratochvil, Byron

1980-01-01

Presents an undergraduate experiment demonstrating sampling error. Selected as the sampling system is a mixture of potassium hydrogen phthalate and sucrose; using a self-zeroing, automatically refillable buret to minimize titration time of multiple samples and employing a dilute back-titrant to obtain high end-point precision. (CS)

Minimizing Artifacts and Biases in Chamber-Based Measurements of Soil Respiration

NASA Astrophysics Data System (ADS)

Davidson, E. A.; Savage, K.

2001-05-01

Soil respiration is one of the largest and most important fluxes of carbon in terrestrial ecosystems. The objectives of this paper are to review concerns about uncertainties of chamber-based measurements of CO2 emissions from soils, to evaluate the direction and magnitude of these potential errors, and to explain procedures that minimize these errors and biases. Disturbance of diffusion gradients cause underestimate of fluxes by less than 15% in most cases, and can be partially corrected for with curve fitting and/or can be minimized by using brief measurement periods. Under-pressurization or over-pressurization of the chamber caused by flow restrictions in air circulating designs can cause large errors, but can also be avoided with properly sized chamber vents and unrestricted flows. Somewhat larger pressure differentials are observed under windy conditions, and the accuracy of measurements made under such conditions needs more research. Spatial and temporal heterogeneity can be addressed with appropriate chamber sizes and numbers and frequency of sampling. For example, means of 8 randomly chosen flux measurements from a population of 36 measurements made with 300 cm2 chambers in tropical forests and pastures were within 25% of the full population mean 98% of the time and were within 10% of the full population mean 70% of the time. Comparisons of chamber-based measurements with tower-based measurements of total ecosystem respiration require analysis of the scale of variation within the purported tower footprint. In a forest at Howland, Maine, the differences in soil respiration rates among very poorly drained and well drained soils were large, but they mostly were fortuitously cancelled when evaluated for purported tower footprints of 600-2100 m length. While all of these potential sources of measurement error and sampling biases must be carefully considered, properly designed and deployed chambers provide a reliable means of accurately measuring soil respiration in terrestrial ecosystems.

Acute Respiratory Distress Syndrome Measurement Error. Potential Effect on Clinical Study Results

PubMed Central

Cooke, Colin R.; Iwashyna, Theodore J.; Hofer, Timothy P.

2016-01-01

Rationale: Identifying patients with acute respiratory distress syndrome (ARDS) is a recognized challenge. Experts often have only moderate agreement when applying the clinical definition of ARDS to patients. However, no study has fully examined the implications of low reliability measurement of ARDS on clinical studies. Objectives: To investigate how the degree of variability in ARDS measurement commonly reported in clinical studies affects study power, the accuracy of treatment effect estimates, and the measured strength of risk factor associations. Methods: We examined the effect of ARDS measurement error in randomized clinical trials (RCTs) of ARDS-specific treatments and cohort studies using simulations. We varied the reliability of ARDS diagnosis, quantified as the interobserver reliability (κ-statistic) between two reviewers. In RCT simulations, patients identified as having ARDS were enrolled, and when measurement error was present, patients without ARDS could be enrolled. In cohort studies, risk factors as potential predictors were analyzed using reviewer-identified ARDS as the outcome variable. Measurements and Main Results: Lower reliability measurement of ARDS during patient enrollment in RCTs seriously degraded study power. Holding effect size constant, the sample size necessary to attain adequate statistical power increased by more than 50% as reliability declined, although the result was sensitive to ARDS prevalence. In a 1,400-patient clinical trial, the sample size necessary to maintain similar statistical power increased to over 1,900 when reliability declined from perfect to substantial (κ = 0.72). Lower reliability measurement diminished the apparent effectiveness of an ARDS-specific treatment from a 15.2% (95% confidence interval, 9.4–20.9%) absolute risk reduction in mortality to 10.9% (95% confidence interval, 4.7–16.2%) when reliability declined to moderate (κ = 0.51). In cohort studies, the effect on risk factor associations was similar. Conclusions: ARDS measurement error can seriously degrade statistical power and effect size estimates of clinical studies. The reliability of ARDS measurement warrants careful attention in future ARDS clinical studies. PMID:27159648

Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 1: comparison of uniresponse and multiresponse designs using PopDes.

PubMed

Chenel, Marylore; Bouzom, François; Aarons, Leon; Ogungbenro, Kayode

2008-12-01

To determine the optimal sampling time design of a drug-drug interaction (DDI) study for the estimation of apparent clearances (CL/F) of two co-administered drugs (SX, a phase I compound, potentially a CYP3A4 inhibitor, and MDZ, a reference CYP3A4 substrate) without any in vivo data using physiologically based pharmacokinetic (PBPK) predictions, population PK modelling and multiresponse optimal design. PBPK models were developed with AcslXtreme using only in vitro data to simulate PK profiles of both drugs when they were co-administered. Then, using simulated data, population PK models were developed with NONMEM and optimal sampling times were determined by optimizing the determinant of the population Fisher information matrix with PopDes using either two uniresponse designs (UD) or a multiresponse design (MD) with joint sampling times for both drugs. Finally, the D-optimal sampling time designs were evaluated by simulation and re-estimation with NONMEM by computing the relative root mean squared error (RMSE) and empirical relative standard errors (RSE) of CL/F. There were four and five optimal sampling times (=nine different sampling times) in the UDs for SX and MDZ, respectively, whereas there were only five sampling times in the MD. Whatever design and compound, CL/F was well estimated (RSE < 20% for MDZ and <25% for SX) and expected RSEs from PopDes were in the same range as empirical RSEs. Moreover, there was no bias in CL/F estimation. Since MD required only five sampling times compared to the two UDs, D-optimal sampling times of the MD were included into a full empirical design for the proposed clinical trial. A joint paper compares the designs with real data. This global approach including PBPK simulations, population PK modelling and multiresponse optimal design allowed, without any in vivo data, the design of a clinical trial, using sparse sampling, capable of estimating CL/F of the CYP3A4 substrate and potential inhibitor when co-administered together.

Estimating tree biomass regressions and their error, proceedings of the workshop on tree biomass regression functions and their contribution to the error

Treesearch

Eric H. Wharton; Tiberius Cunia

1987-01-01

Proceedings of a workshop co-sponsored by the USDA Forest Service, the State University of New York, and the Society of American Foresters. Presented were papers on the methodology of sample tree selection, tree biomass measurement, construction of biomass tables and estimation of their error, and combining the error of biomass tables with that of the sample plots or...

Colour coding for blood collection tube closures - a call for harmonisation.

PubMed

Simundic, Ana-Maria; Cornes, Michael P; Grankvist, Kjell; Lippi, Giuseppe; Nybo, Mads; Ceriotti, Ferruccio; Theodorsson, Elvar; Panteghini, Mauro

2015-02-01

At least one in 10 patients experience adverse events while receiving hospital care. Many of the errors are related to laboratory diagnostics. Efforts to reduce laboratory errors over recent decades have primarily focused on the measurement process while pre- and post-analytical errors including errors in sampling, reporting and decision-making have received much less attention. Proper sampling and additives to the samples are essential. Tubes and additives are identified not only in writing on the tubes but also by the colour of the tube closures. Unfortunately these colours have not been standardised, running the risk of error when tubes from one manufacturer are replaced by the tubes from another manufacturer that use different colour coding. EFLM therefore supports the worldwide harmonisation of the colour coding for blood collection tube closures and labels in order to reduce the risk of pre-analytical errors and improve the patient safety.

Radar error statistics for the space shuttle

NASA Technical Reports Server (NTRS)

Lear, W. M.

1979-01-01

Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection

PubMed Central

Gordon, Nicholas; Griffiths, Thomas; Kraemer, John D; Siedner, Mark J

2017-01-01

Background The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. Objective We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term “validation relaxation.” Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. Methods We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of “required” constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. Results The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. Conclusions A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy. PMID:28821474

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection.

PubMed

Kenny, Avi; Gordon, Nicholas; Griffiths, Thomas; Kraemer, John D; Siedner, Mark J

2017-08-18

The use of mobile devices for data collection in developing world settings is becoming increasingly common and may offer advantages in data collection quality and efficiency relative to paper-based methods. However, mobile data collection systems can hamper many standard quality assurance techniques due to the lack of a hardcopy backup of data. Consequently, mobile health data collection platforms have the potential to generate datasets that appear valid, but are susceptible to unidentified database design flaws, areas of miscomprehension by enumerators, and data recording errors. We describe the design and evaluation of a strategy for estimating data error rates and assessing enumerator performance during electronic data collection, which we term "validation relaxation." Validation relaxation involves the intentional omission of data validation features for select questions to allow for data recording errors to be committed, detected, and monitored. We analyzed data collected during a cluster sample population survey in rural Liberia using an electronic data collection system (Open Data Kit). We first developed a classification scheme for types of detectable errors and validation alterations required to detect them. We then implemented the following validation relaxation techniques to enable data error conduct and detection: intentional redundancy, removal of "required" constraint, and illogical response combinations. This allowed for up to 11 identifiable errors to be made per survey. The error rate was defined as the total number of errors committed divided by the number of potential errors. We summarized crude error rates and estimated changes in error rates over time for both individuals and the entire program using logistic regression. The aggregate error rate was 1.60% (125/7817). Error rates did not differ significantly between enumerators (P=.51), but decreased for the cohort with increasing days of application use, from 2.3% at survey start (95% CI 1.8%-2.8%) to 0.6% at day 45 (95% CI 0.3%-0.9%; OR=0.969; P<.001). The highest error rate (84/618, 13.6%) occurred for an intentional redundancy question for a birthdate field, which was repeated in separate sections of the survey. We found low error rates (0.0% to 3.1%) for all other possible errors. A strategy of removing validation rules on electronic data capture platforms can be used to create a set of detectable data errors, which can subsequently be used to assess group and individual enumerator error rates, their trends over time, and categories of data collection that require further training or additional quality control measures. This strategy may be particularly useful for identifying individual enumerators or systematic data errors that are responsive to enumerator training and is best applied to questions for which errors cannot be prevented through training or software design alone. Validation relaxation should be considered as a component of a holistic data quality assurance strategy. ©Avi Kenny, Nicholas Gordon, Thomas Griffiths, John D Kraemer, Mark J Siedner. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 18.08.2017.

Effect of bar-code technology on the safety of medication administration.

PubMed

Poon, Eric G; Keohane, Carol A; Yoon, Catherine S; Ditmore, Matthew; Bane, Anne; Levtzion-Korach, Osnat; Moniz, Thomas; Rothschild, Jeffrey M; Kachalia, Allen B; Hayes, Judy; Churchill, William W; Lipsitz, Stuart; Whittemore, Anthony D; Bates, David W; Gandhi, Tejal K

2010-05-06

Serious medication errors are common in hospitals and often occur during order transcription or administration of medication. To help prevent such errors, technology has been developed to verify medications by incorporating bar-code verification technology within an electronic medication-administration system (bar-code eMAR). We conducted a before-and-after, quasi-experimental study in an academic medical center that was implementing the bar-code eMAR. We assessed rates of errors in order transcription and medication administration on units before and after implementation of the bar-code eMAR. Errors that involved early or late administration of medications were classified as timing errors and all others as nontiming errors. Two clinicians reviewed the errors to determine their potential to harm patients and classified those that could be harmful as potential adverse drug events. We observed 14,041 medication administrations and reviewed 3082 order transcriptions. Observers noted 776 nontiming errors in medication administration on units that did not use the bar-code eMAR (an 11.5% error rate) versus 495 such errors on units that did use it (a 6.8% error rate)--a 41.4% relative reduction in errors (P<0.001). The rate of potential adverse drug events (other than those associated with timing errors) fell from 3.1% without the use of the bar-code eMAR to 1.6% with its use, representing a 50.8% relative reduction (P<0.001). The rate of timing errors in medication administration fell by 27.3% (P<0.001), but the rate of potential adverse drug events associated with timing errors did not change significantly. Transcription errors occurred at a rate of 6.1% on units that did not use the bar-code eMAR but were completely eliminated on units that did use it. Use of the bar-code eMAR substantially reduced the rate of errors in order transcription and in medication administration as well as potential adverse drug events, although it did not eliminate such errors. Our data show that the bar-code eMAR is an important intervention to improve medication safety. (ClinicalTrials.gov number, NCT00243373.) 2010 Massachusetts Medical Society

Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia

PubMed Central

Doubková, Marcela; Van Dijk, Albert I.J.M.; Sabel, Daniel; Wagner, Wolfgang; Blöschl, Günter

2012-01-01

The Sentinel-1 will carry onboard a C-band radar instrument that will map the European continent once every four days and the global land surface at least once every twelve days with finest 5 × 20 m spatial resolution. The high temporal sampling rate and operational configuration make Sentinel-1 of interest for operational soil moisture monitoring. Currently, updated soil moisture data are made available at 1 km spatial resolution as a demonstration service using Global Mode (GM) measurements from the Advanced Synthetic Aperture Radar (ASAR) onboard ENVISAT. The service demonstrates the potential of the C-band observations to monitor variations in soil moisture. Importantly, a retrieval error estimate is also available; these are needed to assimilate observations into models. The retrieval error is estimated by propagating sensor errors through the retrieval model. In this work, the existing ASAR GM retrieval error product is evaluated using independent top soil moisture estimates produced by the grid-based landscape hydrological model (AWRA-L) developed within the Australian Water Resources Assessment system (AWRA). The ASAR GM retrieval error estimate, an assumed prior AWRA-L error estimate and the variance in the respective datasets were used to spatially predict the root mean square error (RMSE) and the Pearson's correlation coefficient R between the two datasets. These were compared with the RMSE calculated directly from the two datasets. The predicted and computed RMSE showed a very high level of agreement in spatial patterns as well as good quantitative agreement; the RMSE was predicted within accuracy of 4% of saturated soil moisture over 89% of the Australian land mass. Predicted and calculated R maps corresponded within accuracy of 10% over 61% of the continent. The strong correspondence between the predicted and calculated RMSE and R builds confidence in the retrieval error model and derived ASAR GM error estimates. The ASAR GM and Sentinel-1 have the same basic physical measurement characteristics, and therefore very similar retrieval error estimation method can be applied. Because of the expected improvements in radiometric resolution of the Sentinel-1 backscatter measurements, soil moisture estimation errors can be expected to be an order of magnitude less than those for ASAR GM. This opens the possibility for operationally available medium resolution soil moisture estimates with very well-specified errors that can be assimilated into hydrological or crop yield models, with potentially large benefits for land-atmosphere fluxes, crop growth, and water balance monitoring and modelling. PMID:23483015

Mass load estimation errors utilizing grab sampling strategies in a karst watershed

USGS Publications Warehouse

Fogle, A.W.; Taraba, J.L.; Dinger, J.S.

2003-01-01

Developing a mass load estimation method appropriate for a given stream and constituent is difficult due to inconsistencies in hydrologic and constituent characteristics. The difficulty may be increased in flashy flow conditions such as karst. Many projects undertaken are constrained by budget and manpower and do not have the luxury of sophisticated sampling strategies. The objectives of this study were to: (1) examine two grab sampling strategies with varying sampling intervals and determine the error in mass load estimates, and (2) determine the error that can be expected when a grab sample is collected at a time of day when the diurnal variation is most divergent from the daily mean. Results show grab sampling with continuous flow to be a viable data collection method for estimating mass load in the study watershed. Comparing weekly, biweekly, and monthly grab sampling, monthly sampling produces the best results with this method. However, the time of day the sample is collected is important. Failure to account for diurnal variability when collecting a grab sample may produce unacceptable error in mass load estimates. The best time to collect a sample is when the diurnal cycle is nearest the daily mean.

Small sample sizes in the study of ontogenetic allometry; implications for palaeobiology

PubMed Central

Vavrek, Matthew J.

2015-01-01

Quantitative morphometric analyses, particularly ontogenetic allometry, are common methods used in quantifying shape, and changes therein, in both extinct and extant organisms. Due to incompleteness and the potential for restricted sample sizes in the fossil record, palaeobiological analyses of allometry may encounter higher rates of error. Differences in sample size between fossil and extant studies and any resulting effects on allometric analyses have not been thoroughly investigated, and a logical lower threshold to sample size is not clear. Here we show that studies based on fossil datasets have smaller sample sizes than those based on extant taxa. A similar pattern between vertebrates and invertebrates indicates this is not a problem unique to either group, but common to both. We investigate the relationship between sample size, ontogenetic allometric relationship and statistical power using an empirical dataset of skull measurements of modern Alligator mississippiensis. Across a variety of subsampling techniques, used to simulate different taphonomic and/or sampling effects, smaller sample sizes gave less reliable and more variable results, often with the result that allometric relationships will go undetected due to Type II error (failure to reject the null hypothesis). This may result in a false impression of fewer instances of positive/negative allometric growth in fossils compared to living organisms. These limitations are not restricted to fossil data and are equally applicable to allometric analyses of rare extant taxa. No mathematically derived minimum sample size for ontogenetic allometric studies is found; rather results of isometry (but not necessarily allometry) should not be viewed with confidence at small sample sizes. PMID:25780770

Assessing the statistical significance of the achieved classification error of classifiers constructed using serum peptide profiles, and a prescription for random sampling repeated studies for massive high-throughput genomic and proteomic studies.

PubMed

Lyons-Weiler, James; Pelikan, Richard; Zeh, Herbert J; Whitcomb, David C; Malehorn, David E; Bigbee, William L; Hauskrecht, Milos

2005-01-01

Peptide profiles generated using SELDI/MALDI time of flight mass spectrometry provide a promising source of patient-specific information with high potential impact on the early detection and classification of cancer and other diseases. The new profiling technology comes, however, with numerous challenges and concerns. Particularly important are concerns of reproducibility of classification results and their significance. In this work we describe a computational validation framework, called PACE (Permutation-Achieved Classification Error), that lets us assess, for a given classification model, the significance of the Achieved Classification Error (ACE) on the profile data. The framework compares the performance statistic of the classifier on true data samples and checks if these are consistent with the behavior of the classifier on the same data with randomly reassigned class labels. A statistically significant ACE increases our belief that a discriminative signal was found in the data. The advantage of PACE analysis is that it can be easily combined with any classification model and is relatively easy to interpret. PACE analysis does not protect researchers against confounding in the experimental design, or other sources of systematic or random error. We use PACE analysis to assess significance of classification results we have achieved on a number of published data sets. The results show that many of these datasets indeed possess a signal that leads to a statistically significant ACE.

Efficient hierarchical trans-dimensional Bayesian inversion of magnetotelluric data

NASA Astrophysics Data System (ADS)

Xiang, Enming; Guo, Rongwen; Dosso, Stan E.; Liu, Jianxin; Dong, Hao; Ren, Zhengyong

2018-06-01

This paper develops an efficient hierarchical trans-dimensional (trans-D) Bayesian algorithm to invert magnetotelluric (MT) data for subsurface geoelectrical structure, with unknown geophysical model parameterization (the number of conductivity-layer interfaces) and data-error models parameterized by an auto-regressive (AR) process to account for potential error correlations. The reversible-jump Markov-chain Monte Carlo algorithm, which adds/removes interfaces and AR parameters in birth/death steps, is applied to sample the trans-D posterior probability density for model parameterization, model parameters, error variance and AR parameters, accounting for the uncertainties of model dimension and data-error statistics in the uncertainty estimates of the conductivity profile. To provide efficient sampling over the multiple subspaces of different dimensions, advanced proposal schemes are applied. Parameter perturbations are carried out in principal-component space, defined by eigen-decomposition of the unit-lag model covariance matrix, to minimize the effect of inter-parameter correlations and provide effective perturbation directions and length scales. Parameters of new layers in birth steps are proposed from the prior, instead of focused distributions centred at existing values, to improve birth acceptance rates. Parallel tempering, based on a series of parallel interacting Markov chains with successively relaxed likelihoods, is applied to improve chain mixing over model dimensions. The trans-D inversion is applied in a simulation study to examine the resolution of model structure according to the data information content. The inversion is also applied to a measured MT data set from south-central Australia.

SAMPLING DISTRIBUTIONS OF ERROR IN MULTIDIMENSIONAL SCALING.

ERIC Educational Resources Information Center

STAKE, ROBERT E.; AND OTHERS

AN EMPIRICAL STUDY WAS MADE OF THE ERROR FACTORS IN MULTIDIMENSIONAL SCALING (MDS) TO REFINE THE USE OF MDS FOR MORE EXPERT MANIPULATION OF SCALES USED IN EDUCATIONAL MEASUREMENT. THE PURPOSE OF THE RESEARCH WAS TO GENERATE TABLES OF THE SAMPLING DISTRIBUTIONS THAT ARE NECESSARY FOR DISCRIMINATING BETWEEN ERROR AND NONERROR MDS DIMENSIONS. THE…

Error Identification, Labeling, and Correction in Written Business Communication

ERIC Educational Resources Information Center

Quible, Zane K.

2004-01-01

This article used a writing sample that contained 27 sentence-level errors of the type found by corporate America to be annoying and bothersome. Five categories of errors were included in the sample: grammar, punctuation, spelling, writing style, and business communication concepts. Students in a written business communication course were asked…

Medication errors: a prospective cohort study of hand-written and computerised physician order entry in the intensive care unit.

PubMed

Shulman, Rob; Singer, Mervyn; Goldstone, John; Bellingan, Geoff

2005-10-05

The study aimed to compare the impact of computerised physician order entry (CPOE) without decision support with hand-written prescribing (HWP) on the frequency, type and outcome of medication errors (MEs) in the intensive care unit. Details of MEs were collected before, and at several time points after, the change from HWP to CPOE. The study was conducted in a London teaching hospital's 22-bedded general ICU. The sampling periods were 28 weeks before and 2, 10, 25 and 37 weeks after introduction of CPOE. The unit pharmacist prospectively recorded details of MEs and the total number of drugs prescribed daily during the data collection periods, during the course of his normal chart review. The total proportion of MEs was significantly lower with CPOE (117 errors from 2429 prescriptions, 4.8%) than with HWP (69 errors from 1036 prescriptions, 6.7%) (p < 0.04). The proportion of errors reduced with time following the introduction of CPOE (p < 0.001). Two errors with CPOE led to patient harm requiring an increase in length of stay and, if administered, three prescriptions with CPOE could potentially have led to permanent harm or death. Differences in the types of error between systems were noted. There was a reduction in major/moderate patient outcomes with CPOE when non-intercepted and intercepted errors were combined (p = 0.01). The mean baseline APACHE II score did not differ significantly between the HWP and the CPOE periods (19.4 versus 20.0, respectively, p = 0.71). Introduction of CPOE was associated with a reduction in the proportion of MEs and an improvement in the overall patient outcome score (if intercepted errors were included). Moderate and major errors, however, remain a significant concern with CPOE.

Rib biomechanical properties exhibit diagnostic potential for accurate ageing in forensic investigations

PubMed Central

Bonicelli, Andrea; Xhemali, Bledar; Kranioti, Elena F.

2017-01-01

Age estimation remains one of the most challenging tasks in forensic practice when establishing a biological profile of unknown skeletonised remains. Morphological methods based on developmental markers of bones can provide accurate age estimates at a young age, but become highly unreliable for ages over 35 when all developmental markers disappear. This study explores the changes in the biomechanical properties of bone tissue and matrix, which continue to change with age even after skeletal maturity, and their potential value for age estimation. As a proof of concept we investigated the relationship of 28 variables at the macroscopic and microscopic level in rib autopsy samples from 24 individuals. Stepwise regression analysis produced a number of equations one of which with seven variables showed an R2 = 0.949; a mean residual error of 2.13 yrs ±0.4 (SD) and a maximum residual error value of 2.88 yrs. For forensic purposes, by using only bench top machines in tests which can be carried out within 36 hrs, a set of just 3 variables produced an equation with an R2 = 0.902 a mean residual error of 3.38 yrs ±2.6 (SD) and a maximum observed residual error 9.26yrs. This method outstrips all existing age-at-death methods based on ribs, thus providing a novel lab based accurate tool in the forensic investigation of human remains. The present application is optimised for fresh (uncompromised by taphonomic conditions) remains, but the potential of the principle and method is vast once the trends of the biomechanical variables are established for other environmental conditions and circumstances. PMID:28520764

Medication dosing errors and associated factors in hospitalized pediatric patients from the South Area of the West Bank - Palestine.

PubMed

Al-Ramahi, Rowa'; Hmedat, Bayan; Alnjajrah, Eman; Manasrah, Israa; Radwan, Iqbal; Alkhatib, Maram

2017-09-01

Medication dosing errors are a significant global concern and can cause serious medical consequences for patients. Pediatric patients are at increased risk of dosing errors due to differences in medication pharmacodynamics and pharmacokinetics. The aims of this study were to find the rate of medication dosing errors in hospitalized pediatric patients and possible associated factors. The study was an observational cohort study including pediatric inpatients less than 16 years from three governmental hospitals from the West Bank/Palestine during one month in 2014, and sample size was 400 pediatric inpatients from these three hospitals. Pediatric patients' medical records were reviewed. Patients' weight, age, medical conditions, all prescribed medications, their doses and frequency were documented. Then the doses of medications were evaluated. Among 400 patients, the medications prescribed were 949 medications, 213 of them (22.4%) were out of the recommended range, and 160 patients (40.0%) were prescribed one or more potentially inappropriate doses. The most common cause of hospital admission was sepsis which presented 14.3% of cases, followed by fever (13.5%) and meningitis (10.0%). The most commonly used medications were ampicillin in 194 cases (20.4%), ceftriaxone in 182 cases (19.2%), and cefotaxime in 144 cases (12.0%). No significant association was found between potentially inappropriate doses and gender or hospital (chi-square test p -value > 0.05).The results showed that patients with lower body weight, who had a higher number of medications and stayed in hospital for a longer time, were more likely to have inappropriate doses. Potential medication dosing errors were high among pediatric hospitalized patients in Palestine. Younger patients, patients with lower body weight, who were prescribed higher number of medications and stayed in hospital for a longer time were more likely to have inappropriate doses, so these populations require special care. Many children were hospitalized for infectious causes and antibiotics were widely used. Strategies to reduce pediatric medication dosing errors are recommended.

Ex vivo validation of photo-magnetic imaging.

PubMed

Luk, Alex; Nouizi, Farouk; Erkol, Hakan; Unlu, Mehmet B; Gulsen, Gultekin

2017-10-15

We recently introduced a new high-resolution diffuse optical imaging technique termed photo-magnetic imaging (PMI), which utilizes magnetic resonance thermometry (MRT) to monitor the 3D temperature distribution induced in a medium illuminated with a near-infrared light. The spatiotemporal temperature distribution due to light absorption can be accurately estimated using a combined photon propagation and heat diffusion model. High-resolution optical absorption images are then obtained by iteratively minimizing the error between the measured and modeled temperature distributions. We have previously demonstrated the feasibility of PMI with experimental studies using tissue simulating agarose phantoms. In this Letter, we present the preliminary ex vivo PMI results obtained with a chicken breast sample. Similarly to the results obtained on phantoms, the reconstructed images reveal that PMI can quantitatively resolve an inclusion with a 3 mm diameter embedded deep in a biological tissue sample with only 10% error. These encouraging results demonstrate the high performance of PMI in ex vivo biological tissue and its potential for in vivo imaging.

Frozen section analysis of margins for head and neck tumor resections: reduction of sampling errors with a third histologic level.

PubMed

Olson, Stephen M; Hussaini, Mohammad; Lewis, James S

2011-05-01

Frozen section analysis is an essential tool for assessing margins intra-operatively to assure complete resection. Many institutions evaluate surgical defect edge tissue provided by the surgeon after the main lesion has been removed. With the increasing use of transoral laser microsurgery, this method is becoming even more prevalent. We sought to evaluate error rates at our large academic institution and to see if sampling errors could be reduced by the simple method change of taking an additional third section on these specimens. All head and neck tumor resection cases from January 2005 through August 2008 with margins evaluated by frozen section were identified by database search. These cases were analyzed by cutting two levels during frozen section and a third permanent section later. All resection cases from August 2008 through July 2009 were identified as well. These were analyzed by cutting three levels during frozen section (the third a 'much deeper' level) and a fourth permanent section later. Error rates for both of these periods were determined. Errors were separated into sampling and interpretation types. There were 4976 total frozen section specimens from 848 patients. The overall error rate was 2.4% for all frozen sections where just two levels were evaluated and was 2.5% when three levels were evaluated (P=0.67). The sampling error rate was 1.6% for two-level sectioning and 1.2% for three-level sectioning (P=0.42). However, when considering only the frozen section cases where tumor was ultimately identified (either at the time of frozen section or on permanent sections) the sampling error rate for two-level sectioning was 15.3 versus 7.4% for three-level sectioning. This difference was statistically significant (P=0.006). Cutting a single additional 'deeper' level at the time of frozen section identifies more tumor-bearing specimens and may reduce the number of sampling errors.

Quantifying the potential impact of measurement error in an investigation of autism spectrum disorder (ASD).

PubMed

Heavner, Karyn; Newschaffer, Craig; Hertz-Picciotto, Irva; Bennett, Deborah; Burstyn, Igor

2014-05-01

The Early Autism Risk Longitudinal Investigation (EARLI), an ongoing study of a risk-enriched pregnancy cohort, examines genetic and environmental risk factors for autism spectrum disorders (ASDs). We simulated the potential effects of both measurement error (ME) in exposures and misclassification of ASD-related phenotype (assessed as Autism Observation Scale for Infants (AOSI) scores) on measures of association generated under this study design. We investigated the impact on the power to detect true associations with exposure and the false positive rate (FPR) for a non-causal correlate of exposure (X2, r=0.7) for continuous AOSI score (linear model) versus dichotomised AOSI (logistic regression) when the sample size (n), degree of ME in exposure, and strength of the expected (true) OR (eOR)) between exposure and AOSI varied. Exposure was a continuous variable in all linear models and dichotomised at one SD above the mean in logistic models. Simulations reveal complex patterns and suggest that: (1) There was attenuation of associations that increased with eOR and ME; (2) The FPR was considerable under many scenarios; and (3) The FPR has a complex dependence on the eOR, ME and model choice, but was greater for logistic models. The findings will stimulate work examining cost-effective strategies to reduce the impact of ME in realistic sample sizes and affirm the importance for EARLI of investment in biological samples that help precisely quantify a wide range of environmental exposures.

Nematode Damage Functions: The Problems of Experimental and Sampling Error

PubMed Central

Ferris, H.

1984-01-01

The development and use of pest damage functions involves measurement and experimental errors associated with cultural, environmental, and distributional factors. Damage predictions are more valuable if considered with associated probability. Collapsing population densities into a geometric series of population classes allows a pseudo-replication removal of experimental and sampling error in damage function development. Recognition of the nature of sampling error for aggregated populations allows assessment of probability associated with the population estimate. The product of the probabilities incorporated in the damage function and in the population estimate provides a basis for risk analysis of the yield loss prediction and the ensuing management decision. PMID:19295865

Development of a Portable Binary Chlorine Dioxide Generator for Decontamination

DTIC Science & Technology

2010-03-01

chlorine dioxide forms slowly from chlorite solutions through either acid release or a radical chain reaction that we observed at neutral pH. Task 7... Chlorine dioxide and water in methanol - no agent control F. 5.25% Bleach G. Methanol only 3.0 PROCEDURES 3.1 METHOD VALIDATION The reaction...error range in gas chromatography measurements. For the chlorine dioxide containing samples, mass spectra were analyzed to determine potential

Selection Bias in Students' Evaluation of Teaching: Causes of Student Absenteeism and Its Consequences for Course Ratings and Rankings

ERIC Educational Resources Information Center

Wolbring, Tobias; Treischl, Edgar

2016-01-01

Systematic sampling error due to self-selection is a common topic in methodological research and a key challenge for every empirical study. Since selection bias is often not sufficiently considered as a potential flaw in research on and evaluations in higher education, the aim of this paper is to raise awareness for the topic using the case of…

Improving qPCR telomere length assays: Controlling for well position effects increases statistical power.

PubMed

Eisenberg, Dan T A; Kuzawa, Christopher W; Hayes, M Geoffrey

2015-01-01

Telomere length (TL) is commonly measured using quantitative PCR (qPCR). Although, easier than the southern blot of terminal restriction fragments (TRF) TL measurement method, one drawback of qPCR is that it introduces greater measurement error and thus reduces the statistical power of analyses. To address a potential source of measurement error, we consider the effect of well position on qPCR TL measurements. qPCR TL data from 3,638 people run on a Bio-Rad iCycler iQ are reanalyzed here. To evaluate measurement validity, correspondence with TRF, age, and between mother and offspring are examined. First, we present evidence for systematic variation in qPCR TL measurements in relation to thermocycler well position. Controlling for these well-position effects consistently improves measurement validity and yields estimated improvements in statistical power equivalent to increasing sample sizes by 16%. We additionally evaluated the linearity of the relationships between telomere and single copy gene control amplicons and between qPCR and TRF measures. We find that, unlike some previous reports, our data exhibit linear relationships. We introduce the standard error in percent, a superior method for quantifying measurement error as compared to the commonly used coefficient of variation. Using this measure, we find that excluding samples with high measurement error does not improve measurement validity in our study. Future studies using block-based thermocyclers should consider well position effects. Since additional information can be gleaned from well position corrections, rerunning analyses of previous results with well position correction could serve as an independent test of the validity of these results. © 2015 Wiley Periodicals, Inc.

The preclinical pharmacological profile of WAY-132983, a potent M1 preferring agonist.

PubMed

Bartolomeo, A C; Morris, H; Buccafusco, J J; Kille, N; Rosenzweig-Lipson, S; Husbands, M G; Sabb, A L; Abou-Gharbia, M; Moyer, J A; Boast, C A

2000-02-01

Muscarinic M1 preferring agonists may improve cognitive deficits associated with Alzheimer's disease. Side effect assessment of the M1 preferring agonist WAY-132983 showed significant salivation (10 mg/kg i.p. or p.o.) and produced dose-dependent hypothermia after i. p. or p.o. administration. WAY-132983 significantly reduced scopolamine (0.3 mg/kg i.p.)-induced hyperswimming in mice. Cognitive assessment in rats used pretrained animals in a forced choice, 1-h delayed nonmatch-to-sample radial arm maze task. WAY-132983 (0.3 mg/kg i.p) significantly reduced scopolamine (0.3 mg/kg s.c.)-induced errors. Oral WAY-132983 attenuated scopolamine-induced errors; that is, errors produced after combining scopolamine and WAY-132983 (to 3 mg/kg p.o.) were not significantly increased compared with those of vehicle-treated control animals, whereas errors after scopolamine were significantly higher than those of control animals. With the use of miniosmotic pumps, 0.03 mg/kg/day (s.c.) WAY-132983 significantly reduced AF64A (3 nmol/3 microliter/lateral ventricle)-induced errors. Verification of AF64A cholinotoxicity showed significantly lower choline acetyltransferase activity in the hippocampi of AF64A-treated animals, with no significant changes in the striatal or frontal cortex. Cognitive assessment in primates involved the use of pretrained aged animals in a visual delayed match-to-sample procedure. Oral WAY-132983 significantly increased the number of correct responses during short and long delay interval testing. These effects were also apparent 24 h after administration. WAY-132983 exhibited cognitive benefit at doses lower than those producing undesirable effects; therefore, WAY-132983 is a potential candidate for improving the cognitive status of patients with Alzheimer's disease.

Validation of Metrics as Error Predictors

NASA Astrophysics Data System (ADS)

Mendling, Jan

In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.

Inferences about landbird abundance from count data: recent advances and future directions

USGS Publications Warehouse

Nichols, J.D.; Thomas, L.; Conn, P.B.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

We summarize results of a November 2006 workshop dealing with recent research on the estimation of landbird abundance from count data. Our conceptual framework includes a decomposition of the probability of detecting a bird potentially exposed to sampling efforts into four separate probabilities. Primary inference methods are described and include distance sampling, multiple observers, time of detection, and repeated counts. The detection parameters estimated by these different approaches differ, leading to different interpretations of resulting estimates of density and abundance. Simultaneous use of combinations of these different inference approaches can not only lead to increased precision but also provides the ability to decompose components of the detection process. Recent efforts to test the efficacy of these different approaches using natural systems and a new bird radio test system provide sobering conclusions about the ability of observers to detect and localize birds in auditory surveys. Recent research is reported on efforts to deal with such potential sources of error as bird misclassification, measurement error, and density gradients. Methods for inference about spatial and temporal variation in avian abundance are outlined. Discussion topics include opinions about the need to estimate detection probability when drawing inference about avian abundance, methodological recommendations based on the current state of knowledge and suggestions for future research.

Spatial sampling considerations of the CERES (Clouds and Earth Radiant Energy System) instrument

NASA Astrophysics Data System (ADS)

Smith, G. L.; Manalo-Smith, Natividdad; Priestley, Kory

2014-10-01

The CERES (Clouds and Earth Radiant Energy System) instrument is a scanning radiometer with three channels for measuring Earth radiation budget. At present CERES models are operating aboard the Terra, Aqua and Suomi/NPP spacecraft and flights of CERES instruments are planned for the JPSS-1 spacecraft and its successors. CERES scans from one limb of the Earth to the other and back. The footprint size grows with distance from nadir simply due to geometry so that the size of the smallest features which can be resolved from the data increases and spatial sampling errors increase with nadir angle. This paper presents an analysis of the effect of nadir angle on spatial sampling errors of the CERES instrument. The analysis performed in the Fourier domain. Spatial sampling errors are created by smoothing of features which are the size of the footprint and smaller, or blurring, and inadequate sampling, that causes aliasing errors. These spatial sampling errors are computed in terms of the system transfer function, which is the Fourier transform of the point response function, the spacing of data points and the spatial spectrum of the radiance field.

Sampling methods for titica vine (Heteropsis spp.) inventory in a tropical forest

Treesearch

Carine Klauberg; Edson Vidal; Carlos Alberto Silva; Michelliny de M. Bentes; Andrew Thomas Hudak

2016-01-01

Titica vine provides useful raw fiber material. Using sampling schemes that reduce sampling error can provide direction for sustainable forest management of this vine. Sampling systematically with rectangular plots (10× 25 m) promoted lower error and greater accuracy in the inventory of titica vines in tropical rainforest.

Invention and validation of an automated camera system that uses optical character recognition to identify patient name mislabeled samples.

PubMed

Hawker, Charles D; McCarthy, William; Cleveland, David; Messinger, Bonnie L

2014-03-01

Mislabeled samples are a serious problem in most clinical laboratories. Published error rates range from 0.39/1000 to as high as 1.12%. Standardization of bar codes and label formats has not yet achieved the needed improvement. The mislabel rate in our laboratory, although low compared with published rates, prompted us to seek a solution to achieve zero errors. To reduce or eliminate our mislabeled samples, we invented an automated device using 4 cameras to photograph the outside of a sample tube. The system uses optical character recognition (OCR) to look for discrepancies between the patient name in our laboratory information system (LIS) vs the patient name on the customer label. All discrepancies detected by the system's software then require human inspection. The system was installed on our automated track and validated with production samples. We obtained 1 009 830 images during the validation period, and every image was reviewed. OCR passed approximately 75% of the samples, and no mislabeled samples were passed. The 25% failed by the system included 121 samples actually mislabeled by patient name and 148 samples with spelling discrepancies between the patient name on the customer label and the patient name in our LIS. Only 71 of the 121 mislabeled samples detected by OCR were found through our normal quality assurance process. We have invented an automated camera system that uses OCR technology to identify potential mislabeled samples. We have validated this system using samples transported on our automated track. Full implementation of this technology offers the possibility of zero mislabeled samples in the preanalytic stage.

Distribution of the Determinant of the Sample Correlation Matrix: Monte Carlo Type One Error Rates.

ERIC Educational Resources Information Center

Reddon, John R.; And Others

1985-01-01

Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)

A robust clustering algorithm for identifying problematic samples in genome-wide association studies.

PubMed

Bellenguez, Céline; Strange, Amy; Freeman, Colin; Donnelly, Peter; Spencer, Chris C A

2012-01-01

High-throughput genotyping arrays provide an efficient way to survey single nucleotide polymorphisms (SNPs) across the genome in large numbers of individuals. Downstream analysis of the data, for example in genome-wide association studies (GWAS), often involves statistical models of genotype frequencies across individuals. The complexities of the sample collection process and the potential for errors in the experimental assay can lead to biases and artefacts in an individual's inferred genotypes. Rather than attempting to model these complications, it has become a standard practice to remove individuals whose genome-wide data differ from the sample at large. Here we describe a simple, but robust, statistical algorithm to identify samples with atypical summaries of genome-wide variation. Its use as a semi-automated quality control tool is demonstrated using several summary statistics, selected to identify different potential problems, and it is applied to two different genotyping platforms and sample collections. The algorithm is written in R and is freely available at www.well.ox.ac.uk/chris-spencer chris.spencer@well.ox.ac.uk Supplementary data are available at Bioinformatics online.

Understanding the dynamics of correct and error responses in free recall: evidence from externalized free recall.

PubMed

Unsworth, Nash; Brewer, Gene A; Spillers, Gregory J

2010-06-01

The dynamics of correct and error responses in a variant of delayed free recall were examined in the present study. In the externalized free recall paradigm, participants were presented with lists of words and were instructed to subsequently recall not only the words that they could remember from the most recently presented list, but also any other words that came to mind during the recall period. Externalized free recall is useful for elucidating both sampling and postretrieval editing processes, thereby yielding more accurate estimates of the total number of error responses, which are typically sampled and subsequently edited during free recall. The results indicated that the participants generally sampled correct items early in the recall period and then transitioned to sampling more erroneous responses. Furthermore, the participants generally terminated their search after sampling too many errors. An examination of editing processes suggested that the participants were quite good at identifying errors, but this varied systematically on the basis of a number of factors. The results from the present study are framed in terms of generate-edit models of free recall.

Mental representation of symbols as revealed by vocabulary errors in two bonobos (Pan paniscus).

PubMed

Lyn, Heidi

2007-10-01

Error analysis has been used in humans to detect implicit representations and categories in language use. The present study utilizes the same technique to report on mental representations and categories in symbol use from two bonobos (Pan paniscus). These bonobos have been shown in published reports to comprehend English at the level of a two-and-a-half year old child and to use a keyboard with over 200 visuographic symbols (lexigrams). In this study, vocabulary test errors from over 10 years of data revealed auditory, visual, and spatio-temporal generalizations (errors were more likely items that looked like sounded like, or were frequently associated with the sample item in space or in time), as well as hierarchical and conceptual categorizations. These error data, like those of humans, are a result of spontaneous responding rather than specific training and do not solely depend upon the sample mode (e.g. auditory similarity errors are not universally more frequent with an English sample, nor were visual similarity errors universally more frequent with a photograph sample). However, unlike humans, these bonobos do not make errors based on syntactical confusions (e.g. confusing semantically unrelated nouns), suggesting that they may not separate syntactical and semantic information. These data suggest that apes spontaneously create a complex, hierarchical, web of representations when exposed to a symbol system.

Evaluation of Preanalytical Quality Indicators by Six Sigma and Pareto`s Principle.

PubMed

Kulkarni, Sweta; Ramesh, R; Srinivasan, A R; Silvia, C R Wilma Delphine

2018-01-01

Preanalytical steps are the major sources of error in clinical laboratory. The analytical errors can be corrected by quality control procedures but there is a need for stringent quality checks in preanalytical area as these processes are done outside the laboratory. Sigma value depicts the performance of laboratory and its quality measures. Hence in the present study six sigma and Pareto principle was applied to preanalytical quality indicators to evaluate the clinical biochemistry laboratory performance. This observational study was carried out for a period of 1 year from November 2015-2016. A total of 1,44,208 samples and 54,265 test requisition forms were screened for preanalytical errors like missing patient information, sample collection details in forms and hemolysed, lipemic, inappropriate, insufficient samples and total number of errors were calculated and converted into defects per million and sigma scale. Pareto`s chart was drawn using total number of errors and cumulative percentage. In 75% test requisition forms diagnosis was not mentioned and sigma value of 0.9 was obtained and for other errors like sample receiving time, stat and type of sample sigma values were 2.9, 2.6, and 2.8 respectively. For insufficient sample and improper ratio of blood to anticoagulant sigma value was 4.3. Pareto`s chart depicts out of 80% of errors in requisition forms, 20% is contributed by missing information like diagnosis. The development of quality indicators, application of six sigma and Pareto`s principle are quality measures by which not only preanalytical, the total testing process can be improved.

Dissociable Genetic Contributions to Error Processing: A Multimodal Neuroimaging Study

PubMed Central

Agam, Yigal; Vangel, Mark; Roffman, Joshua L.; Gallagher, Patience J.; Chaponis, Jonathan; Haddad, Stephen; Goff, Donald C.; Greenberg, Jennifer L.; Wilhelm, Sabine; Smoller, Jordan W.; Manoach, Dara S.

2014-01-01

Background Neuroimaging studies reliably identify two markers of error commission: the error-related negativity (ERN), an event-related potential, and functional MRI activation of the dorsal anterior cingulate cortex (dACC). While theorized to reflect the same neural process, recent evidence suggests that the ERN arises from the posterior cingulate cortex not the dACC. Here, we tested the hypothesis that these two error markers also have different genetic mediation. Methods We measured both error markers in a sample of 92 comprised of healthy individuals and those with diagnoses of schizophrenia, obsessive-compulsive disorder or autism spectrum disorder. Participants performed the same task during functional MRI and simultaneously acquired magnetoencephalography and electroencephalography. We examined the mediation of the error markers by two single nucleotide polymorphisms: dopamine D4 receptor (DRD4) C-521T (rs1800955), which has been associated with the ERN and methylenetetrahydrofolate reductase (MTHFR) C677T (rs1801133), which has been associated with error-related dACC activation. We then compared the effects of each polymorphism on the two error markers modeled as a bivariate response. Results We replicated our previous report of a posterior cingulate source of the ERN in healthy participants in the schizophrenia and obsessive-compulsive disorder groups. The effect of genotype on error markers did not differ significantly by diagnostic group. DRD4 C-521T allele load had a significant linear effect on ERN amplitude, but not on dACC activation, and this difference was significant. MTHFR C677T allele load had a significant linear effect on dACC activation but not ERN amplitude, but the difference in effects on the two error markers was not significant. Conclusions DRD4 C-521T, but not MTHFR C677T, had a significant differential effect on two canonical error markers. Together with the anatomical dissociation between the ERN and error-related dACC activation, these findings suggest that these error markers have different neural and genetic mediation. PMID:25010186

Prescription errors before and after introduction of electronic medication alert system in a pediatric emergency department.

PubMed

Sethuraman, Usha; Kannikeswaran, Nirupama; Murray, Kyle P; Zidan, Marwan A; Chamberlain, James M

2015-06-01

Prescription errors occur frequently in pediatric emergency departments (PEDs).The effect of computerized physician order entry (CPOE) with electronic medication alert system (EMAS) on these is unknown. The objective was to compare prescription errors rates before and after introduction of CPOE with EMAS in a PED. The hypothesis was that CPOE with EMAS would significantly reduce the rate and severity of prescription errors in the PED. A prospective comparison of a sample of outpatient, medication prescriptions 5 months before and after CPOE with EMAS implementation (7,268 before and 7,292 after) was performed. Error types and rates, alert types and significance, and physician response were noted. Medication errors were deemed significant if there was a potential to cause life-threatening injury, failure of therapy, or an adverse drug effect. There was a significant reduction in the errors per 100 prescriptions (10.4 before vs. 7.3 after; absolute risk reduction = 3.1, 95% confidence interval [CI] = 2.2 to 4.0). Drug dosing error rates decreased from 8 to 5.4 per 100 (absolute risk reduction = 2.6, 95% CI = 1.8 to 3.4). Alerts were generated for 29.6% of prescriptions, with 45% involving drug dose range checking. The sensitivity of CPOE with EMAS in identifying errors in prescriptions was 45.1% (95% CI = 40.8% to 49.6%), and the specificity was 57% (95% CI = 55.6% to 58.5%). Prescribers modified 20% of the dosing alerts, resulting in the error not reaching the patient. Conversely, 11% of true dosing alerts for medication errors were overridden by the prescribers: 88 (11.3%) resulted in medication errors, and 684 (88.6%) were false-positive alerts. A CPOE with EMAS was associated with a decrease in overall prescription errors in our PED. Further system refinements are required to reduce the high false-positive alert rates. © 2015 by the Society for Academic Emergency Medicine.

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications.

PubMed

Graf, Alexandra C; Bauer, Peter; Glimm, Ekkehard; Koenig, Franz

2014-07-01

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Improved Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.;

Lexical diversity and omission errors as predictors of language ability in the narratives of sequential Spanish-English bilinguals: a cross-language comparison.

PubMed

Jacobson, Peggy F; Walden, Patrick R

2013-08-01

This study explored the utility of language sample analysis for evaluating language ability in school-age Spanish-English sequential bilingual children. Specifically, the relative potential of lexical diversity and word/morpheme omission as predictors of typical or atypical language status was evaluated. Narrative samples were obtained from 48 bilingual children in both of their languages using the suggested narrative retell protocol and coding conventions as per Systematic Analysis of Language Transcripts (SALT; Miller & Iglesias, 2008) software. An additional lexical diversity measure, VocD, was also calculated. A series of logistical hierarchical regressions explored the utility of the number of different words, VocD statistic, and word and morpheme omissions in each language for predicting language status. Omission errors turned out to be the best predictors of bilingual language impairment at all ages, and this held true across languages. Although lexical diversity measures did not predict typical or atypical language status, the measures were significantly related to oral language proficiency in English and Spanish. The results underscore the significance of omission errors in bilingual language impairment while simultaneously revealing the limitations of lexical diversity measures as indicators of impairment. The relationship between lexical diversity and oral language proficiency highlights the importance of considering relative language proficiency in bilingual assessment.

On the isobaric space of 25-hydroxyvitamin D in human serum: potential for interferences in liquid chromatography/tandem mass spectrometry, systematic errors and accuracy issues.

PubMed

Qi, Yulin; Geib, Timon; Schorr, Pascal; Meier, Florian; Volmer, Dietrich A

2015-01-15

Isobaric interferences in human serum can potentially influence the measured concentration levels of 25-hydroxyvitamin D [25(OH)D], when low resolving power liquid chromatography/tandem mass spectrometry (LC/MS/MS) instruments and non-specific MS/MS product ions are employed for analysis. In this study, we provide a detailed characterization of these interferences and a technical solution to reduce the associated systematic errors. Detailed electrospray ionization Fourier transform ion cyclotron resonance (FTICR) high-resolution mass spectrometry (HRMS) experiments were used to characterize co-extracted isobaric components of 25(OH)D from human serum. Differential ion mobility spectrometry (DMS), as a gas-phase ion filter, was implemented on a triple quadrupole mass spectrometer for separation of the isobars. HRMS revealed the presence of multiple isobaric compounds in extracts of human serum for different sample preparation methods. Several of these isobars had the potential to increase the peak areas measured for 25(OH)D on low-resolution MS instruments. A major isobaric component was identified as pentaerythritol oleate, a technical lubricant, which was probably an artifact from the analytical instrumentation. DMS was able to remove several of these isobars prior to MS/MS, when implemented on the low-resolution triple quadrupole mass spectrometer. It was shown in this proof-of-concept study that DMS-MS has the potential to significantly decrease systematic errors, and thus improve accuracy of vitamin D measurements using LC/MS/MS. Copyright © 2014 John Wiley & Sons, Ltd.

Chemistry and haematology sample rejection and clinical impact in a tertiary laboratory in Cape Town.

PubMed

Jacobsz, Lourens A; Zemlin, Annalise E; Roos, Mark J; Erasmus, Rajiv T

2011-10-14

Recent publications report that up to 70% of total laboratory errors occur in the pre-analytical phase. Identification of specific problems highlights pre-analytic processes susceptible to errors. The rejection of unsuitable samples can lead to delayed turnaround time and affect patient care. A retrospective audit was conducted investigating the rejection rate of routine blood specimens received at chemistry and haematology laboratories over a 2-week period. The reasons for rejection and potential clinical impact of these rejections were investigated. Thirty patient files were randomly selected and examined to assess the impact of these rejections on clinical care. A total of 32,910 specimens were received during the study period, of which 481 were rejected, giving a rejection rate of 1.46%. The main reasons for rejection were inappropriate clotting (30%) and inadequate sample volume (22%). Only 51.7% of rejected samples were repeated and the average time for a repeat sample to reach the laboratory was about 5 days (121 h). Of the repeated samples, 5.1% had results within critical values. Examination of patient folders showed that in 40% of cases the rejection of samples had an impact on patient care. The evaluation of pre-analytical processes in the laboratory, with regard to sample rejection, allowed one to identify problem areas where improvement is necessary. Rejected samples due to factors out of the laboratory's control had a definite impact on patient care and can thus affect customer satisfaction. Clinicians should be aware of these factors to prevent such rejections.

45 CFR 98.102 - Content of Error Rate Reports.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Funds and State Matching and Maintenance-of-Effort (MOE Funds): (1) Percentage of cases with an error... cases in the sample with an error compared to the total number of cases in the sample; (2) Percentage of cases with an improper payment (both over and under payments), expressed as the total number of cases in...

Detecting genotyping errors and describing black bear movement in northern Idaho

Treesearch

Michael K. Schwartz; Samuel A. Cushman; Kevin S. McKelvey; Jim Hayden; Cory Engkjer

2006-01-01

Non-invasive genetic sampling has become a favored tool to enumerate wildlife. Genetic errors, caused by poor quality samples, can lead to substantial biases in numerical estimates of individuals. We demonstrate how the computer program DROPOUT can detect amplification errors (false alleles and allelic dropout) in a black bear (Ursus americanus) dataset collected in...

A Linguistic Analysis of Errors in the Compositions of Arba Minch University Students

ERIC Educational Resources Information Center

Tizazu, Yoseph

2014-01-01

This study reports the dominant linguistic errors that occur in the written productions of Arba Minch University (hereafter AMU) students. A sample of paragraphs was collected for two years from students ranging from freshmen to graduating level. The sampled compositions were then coded, described, and explained using error analysis method. Both…

Reducing error and improving efficiency during vascular interventional radiology: implementation of a preprocedural team rehearsal.

PubMed

Morbi, Abigail H M; Hamady, Mohamad S; Riga, Celia V; Kashef, Elika; Pearch, Ben J; Vincent, Charles; Moorthy, Krishna; Vats, Amit; Cheshire, Nicholas J W; Bicknell, Colin D

2012-08-01

To determine the type and frequency of errors during vascular interventional radiology (VIR) and design and implement an intervention to reduce error and improve efficiency in this setting. Ethical guidance was sought from the Research Services Department at Imperial College London. Informed consent was not obtained. Field notes were recorded during 55 VIR procedures by a single observer. Two blinded assessors identified failures from field notes and categorized them into one or more errors by using a 22-part classification system. The potential to cause harm, disruption to procedural flow, and preventability of each failure was determined. A preprocedural team rehearsal (PPTR) was then designed and implemented to target frequent preventable potential failures. Thirty-three procedures were observed subsequently to determine the efficacy of the PPTR. Nonparametric statistical analysis was used to determine the effect of intervention on potential failure rates, potential to cause harm and procedural flow disruption scores (Mann-Whitney U test), and number of preventable failures (Fisher exact test). Before intervention, 1197 potential failures were recorded, of which 54.6% were preventable. A total of 2040 errors were deemed to have occurred to produce these failures. Planning error (19.7%), staff absence (16.2%), equipment unavailability (12.2%), communication error (11.2%), and lack of safety consciousness (6.1%) were the most frequent errors, accounting for 65.4% of the total. After intervention, 352 potential failures were recorded. Classification resulted in 477 errors. Preventable failures decreased from 54.6% to 27.3% (P < .001) with implementation of PPTR. Potential failure rates per hour decreased from 18.8 to 9.2 (P < .001), with no increase in potential to cause harm or procedural flow disruption per failure. Failures during VIR procedures are largely because of ineffective planning, communication error, and equipment difficulties, rather than a result of technical or patient-related issues. Many of these potential failures are preventable. A PPTR is an effective means of targeting frequent preventable failures, reducing procedural delays and improving patient safety.

Representation of deformable motion for compression of dynamic cardiac image data

NASA Astrophysics Data System (ADS)

Weinlich, Andreas; Amon, Peter; Hutter, Andreas; Kaup, André

2012-02-01

We present a new approach for efficient estimation and storage of tissue deformation in dynamic medical image data like 3-D+t computed tomography reconstructions of human heart acquisitions. Tissue deformation between two points in time can be described by means of a displacement vector field indicating for each voxel of a slice, from which position in the previous slice at a fixed position in the third dimension it has moved to this position. Our deformation model represents the motion in a compact manner using a down-sampled potential function of the displacement vector field. This function is obtained by a Gauss-Newton minimization of the estimation error image, i. e., the difference between the current and the deformed previous slice. For lossless or lossy compression of volume slices, the potential function and the error image can afterwards be coded separately. By assuming deformations instead of translational motion, a subsequent coding algorithm using this method will achieve better compression ratios for medical volume data than with conventional block-based motion compensation known from video coding. Due to the smooth prediction without block artifacts, particularly whole-image transforms like wavelet decomposition as well as intra-slice prediction methods can benefit from this approach. We show that with discrete cosine as well as with Karhunen-Lo`eve transform the method can achieve a better energy compaction of the error image than block-based motion compensation while reaching approximately the same prediction error energy.

USGS Blind Sample Project: monitoring and evaluating laboratory analytical quality

USGS Publications Warehouse

Ludtke, Amy S.; Woodworth, Mark T.

1997-01-01

The U.S. Geological Survey (USGS) collects and disseminates information about the Nation's water resources. Surface- and ground-water samples are collected and sent to USGS laboratories for chemical analyses. The laboratories identify and quantify the constituents in the water samples. Random and systematic errors occur during sample handling, chemical analysis, and data processing. Although all errors cannot be eliminated from measurements, the magnitude of their uncertainty can be estimated and tracked over time. Since 1981, the USGS has operated an independent, external, quality-assurance project called the Blind Sample Project (BSP). The purpose of the BSP is to monitor and evaluate the quality of laboratory analytical results through the use of double-blind quality-control (QC) samples. The information provided by the BSP assists the laboratories in detecting and correcting problems in the analytical procedures. The information also can aid laboratory users in estimating the extent that laboratory errors contribute to the overall errors in their environmental data.

Comparing and Combining Data across Multiple Sources via Integration of Paired-sample Data to Correct for Measurement Error

PubMed Central

Huang, Yunda; Huang, Ying; Moodie, Zoe; Li, Sue; Self, Steve

2014-01-01

Summary In biomedical research such as the development of vaccines for infectious diseases or cancer, measures from the same assay are often collected from multiple sources or laboratories. Measurement error that may vary between laboratories needs to be adjusted for when combining samples across laboratories. We incorporate such adjustment in comparing and combining independent samples from different labs via integration of external data, collected on paired samples from the same two laboratories. We propose: 1) normalization of individual level data from two laboratories to the same scale via the expectation of true measurements conditioning on the observed; 2) comparison of mean assay values between two independent samples in the Main study accounting for inter-source measurement error; and 3) sample size calculations of the paired-sample study so that hypothesis testing error rates are appropriately controlled in the Main study comparison. Because the goal is not to estimate the true underlying measurements but to combine data on the same scale, our proposed methods do not require that the true values for the errorprone measurements are known in the external data. Simulation results under a variety of scenarios demonstrate satisfactory finite sample performance of our proposed methods when measurement errors vary. We illustrate our methods using real ELISpot assay data generated by two HIV vaccine laboratories. PMID:22764070

Quantifying errors without random sampling.

PubMed

Phillips, Carl V; LaPole, Luwanna M

2003-06-12

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision. We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sampling, such as limiting reported significant figures. We present simple methods for doing such quantifications, and for incorporating them into calculations. More complicated methods become necessary when multiple sources of uncertainty must be combined. We demonstrate that Monte Carlo simulation, using available software, can estimate the uncertainty resulting from complicated calculations with many sources of uncertainty. We apply the method to the current estimate of the annual incidence of foodborne illness in the United States. Quantifying uncertainty from systematic errors is practical. Reporting this uncertainty would more honestly represent study results, help show the probability that estimated values fall within some critical range, and facilitate better targeting of further research.

DNA Barcoding through Quaternary LDPC Codes

PubMed Central

Tapia, Elizabeth; Spetale, Flavio; Krsticevic, Flavia; Angelone, Laura; Bulacio, Pilar

2015-01-01

For many parallel applications of Next-Generation Sequencing (NGS) technologies short barcodes able to accurately multiplex a large number of samples are demanded. To address these competitive requirements, the use of error-correcting codes is advised. Current barcoding systems are mostly built from short random error-correcting codes, a feature that strongly limits their multiplexing accuracy and experimental scalability. To overcome these problems on sequencing systems impaired by mismatch errors, the alternative use of binary BCH and pseudo-quaternary Hamming codes has been proposed. However, these codes either fail to provide a fine-scale with regard to size of barcodes (BCH) or have intrinsic poor error correcting abilities (Hamming). Here, the design of barcodes from shortened binary BCH codes and quaternary Low Density Parity Check (LDPC) codes is introduced. Simulation results show that although accurate barcoding systems of high multiplexing capacity can be obtained with any of these codes, using quaternary LDPC codes may be particularly advantageous due to the lower rates of read losses and undetected sample misidentification errors. Even at mismatch error rates of 10−2 per base, 24-nt LDPC barcodes can be used to multiplex roughly 2000 samples with a sample misidentification error rate in the order of 10−9 at the expense of a rate of read losses just in the order of 10−6. PMID:26492348

DNA Barcoding through Quaternary LDPC Codes.

PubMed

Tapia, Elizabeth; Spetale, Flavio; Krsticevic, Flavia; Angelone, Laura; Bulacio, Pilar

2015-01-01

For many parallel applications of Next-Generation Sequencing (NGS) technologies short barcodes able to accurately multiplex a large number of samples are demanded. To address these competitive requirements, the use of error-correcting codes is advised. Current barcoding systems are mostly built from short random error-correcting codes, a feature that strongly limits their multiplexing accuracy and experimental scalability. To overcome these problems on sequencing systems impaired by mismatch errors, the alternative use of binary BCH and pseudo-quaternary Hamming codes has been proposed. However, these codes either fail to provide a fine-scale with regard to size of barcodes (BCH) or have intrinsic poor error correcting abilities (Hamming). Here, the design of barcodes from shortened binary BCH codes and quaternary Low Density Parity Check (LDPC) codes is introduced. Simulation results show that although accurate barcoding systems of high multiplexing capacity can be obtained with any of these codes, using quaternary LDPC codes may be particularly advantageous due to the lower rates of read losses and undetected sample misidentification errors. Even at mismatch error rates of 10(-2) per base, 24-nt LDPC barcodes can be used to multiplex roughly 2000 samples with a sample misidentification error rate in the order of 10(-9) at the expense of a rate of read losses just in the order of 10(-6).

Autonomous spatially adaptive sampling in experiments based on curvature, statistical error and sample spacing with applications in LDA measurements

NASA Astrophysics Data System (ADS)

Theunissen, Raf; Kadosh, Jesse S.; Allen, Christian B.

2015-06-01

Spatially varying signals are typically sampled by collecting uniformly spaced samples irrespective of the signal content. For signals with inhomogeneous information content, this leads to unnecessarily dense sampling in regions of low interest or insufficient sample density at important features, or both. A new adaptive sampling technique is presented directing sample collection in proportion to local information content, capturing adequately the short-period features while sparsely sampling less dynamic regions. The proposed method incorporates a data-adapted sampling strategy on the basis of signal curvature, sample space-filling, variable experimental uncertainty and iterative improvement. Numerical assessment has indicated a reduction in the number of samples required to achieve a predefined uncertainty level overall while improving local accuracy for important features. The potential of the proposed method has been further demonstrated on the basis of Laser Doppler Anemometry experiments examining the wake behind a NACA0012 airfoil and the boundary layer characterisation of a flat plate.

Eigenvector method for umbrella sampling enables error analysis

PubMed Central

Thiede, Erik H.; Van Koten, Brian; Weare, Jonathan; Dinner, Aaron R.

2016-01-01

Umbrella sampling efficiently yields equilibrium averages that depend on exploring rare states of a model by biasing simulations to windows of coordinate values and then combining the resulting data with physical weighting. Here, we introduce a mathematical framework that casts the step of combining the data as an eigenproblem. The advantage to this approach is that it facilitates error analysis. We discuss how the error scales with the number of windows. Then, we derive a central limit theorem for averages that are obtained from umbrella sampling. The central limit theorem suggests an estimator of the error contributions from individual windows, and we develop a simple and computationally inexpensive procedure for implementing it. We demonstrate this estimator for simulations of the alanine dipeptide and show that it emphasizes low free energy pathways between stable states in comparison to existing approaches for assessing error contributions. Our work suggests the possibility of using the estimator and, more generally, the eigenvector method for umbrella sampling to guide adaptation of the simulation parameters to accelerate convergence. PMID:27586912

Experiences with Lean Six Sigma as improvement strategy to reduce parenteral medication administration errors and associated potential risk of harm.

PubMed

van de Plas, Afke; Slikkerveer, Mariëlle; Hoen, Saskia; Schrijnemakers, Rick; Driessen, Johanna; de Vries, Frank; van den Bemt, Patricia

2017-01-01

In this controlled before-after study the effect of improvements, derived from Lean Six Sigma strategy, on parenteral medication administration errors and the potential risk of harm was determined. During baseline measurement, on control versus intervention ward, at least one administration error occurred in 14 (74%) and 6 (46%) administrations with potential risk of harm in 6 (32%) and 1 (8%) administrations. Most administration errors with high potential risk of harm occurred in bolus injections: 8 (57%) versus 2 (67%) bolus injections were injected too fast with a potential risk of harm in 6 (43%) and 1 (33%) bolus injections on control and intervention ward. Implemented improvement strategies, based on major causes of too fast administration of bolus injections, were: Substitution of bolus injections by infusions, education, availability of administration information and drug round tabards. Post intervention, on the control ward in 76 (76%) administrations at least one error was made (RR 1.03; CI95:0.77-1.38), with a potential risk of harm in 14 (14%) administrations (RR 0.45; CI95:0.20-1.02). In 40 (68%) administrations on the intervention ward at least one error occurred (RR 1.47; CI95:0.80-2.71) but no administrations were associated with a potential risk of harm. A shift in wrong duration administration errors from bolus injections to infusions, with a reduction of potential risk of harm, seems to have occurred on the intervention ward. Although data are insufficient to prove an effect, Lean Six Sigma was experienced as a suitable strategy to select tailored improvements. Further studies are required to prove the effect of the strategy on parenteral medication administration errors.

Experiences with Lean Six Sigma as improvement strategy to reduce parenteral medication administration errors and associated potential risk of harm

PubMed Central

van de Plas, Afke; Slikkerveer, Mariëlle; Hoen, Saskia; Schrijnemakers, Rick; Driessen, Johanna; de Vries, Frank; van den Bemt, Patricia

2017-01-01

In this controlled before-after study the effect of improvements, derived from Lean Six Sigma strategy, on parenteral medication administration errors and the potential risk of harm was determined. During baseline measurement, on control versus intervention ward, at least one administration error occurred in 14 (74%) and 6 (46%) administrations with potential risk of harm in 6 (32%) and 1 (8%) administrations. Most administration errors with high potential risk of harm occurred in bolus injections: 8 (57%) versus 2 (67%) bolus injections were injected too fast with a potential risk of harm in 6 (43%) and 1 (33%) bolus injections on control and intervention ward. Implemented improvement strategies, based on major causes of too fast administration of bolus injections, were: Substitution of bolus injections by infusions, education, availability of administration information and drug round tabards. Post intervention, on the control ward in 76 (76%) administrations at least one error was made (RR 1.03; CI95:0.77-1.38), with a potential risk of harm in 14 (14%) administrations (RR 0.45; CI95:0.20-1.02). In 40 (68%) administrations on the intervention ward at least one error occurred (RR 1.47; CI95:0.80-2.71) but no administrations were associated with a potential risk of harm. A shift in wrong duration administration errors from bolus injections to infusions, with a reduction of potential risk of harm, seems to have occurred on the intervention ward. Although data are insufficient to prove an effect, Lean Six Sigma was experienced as a suitable strategy to select tailored improvements. Further studies are required to prove the effect of the strategy on parenteral medication administration errors. PMID:28674608

Assessment of the spatial variability in tall wheatgrass forage using LANDSAT 8 satellite imagery to delineate potential management zones.

PubMed

Cicore, Pablo; Serrano, João; Shahidian, Shakib; Sousa, Adelia; Costa, José Luis; da Silva, José Rafael Marques

2016-09-01

Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m(2) in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500 °C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVInov) and 10 December 2014 (NDVIdec) because the potential AB was highly associated with NDVInov and NDVIdec (r (2)  = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVInov and NDVIdec, respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.

Decreasing Errors in Reading-Related Matching to Sample Using a Delayed-Sample Procedure

ERIC Educational Resources Information Center

Doughty, Adam H.; Saunders, Kathryn J.

2009-01-01

Two men with intellectual disabilities initially demonstrated intermediate accuracy in two-choice matching-to-sample (MTS) procedures. A printed-letter identity MTS procedure was used with 1 participant, and a spoken-to-printed-word MTS procedure was used with the other participant. Errors decreased substantially under a delayed-sample procedure,…

Detecting fluid leakage of a reservoir dam based on streaming self-potential measurements

NASA Astrophysics Data System (ADS)

Song, Seo Young; Kim, Bitnarae; Nam, Myung Jin; Lim, Sung Keun

2015-04-01

Between many reservoir dams for agriculture in suburban area of South Korea, water leakage has been reported several times. The dam under consideration in this study, which is located in Gyeong-buk, in the south-east of the Korean Peninsula, was reported to have a large leakage at the right foot of downstream side of the reservoir dam. For the detection of the leakage, not only geological survey but also geophysical explorations have been made for precision safety diagnosis, since the leakage can lead to dam failure. Geophysical exploration includes both electrical-resistivity and self-potential surveys, while geological surveys water permeability test, standard penetration test, and sampling for undisturbed sample during the course of the drilling investigation. The geophysical explorations were made not only along the top of dam but also transverse the heel of dam. The leakage of water installations can change the known-heterogeneous structure of the dam body but also cause streaming spontaneous (self) potential (SP) anomaly, which can be detected by electrical resistivity and SP measurements, respectively. For the interpretation of streaming SP, we used trial-and-error method by comparing synthetic SP data with field SP data for model update. For the computation, we first invert the resistivity data to obtain the distorted resistivity structure of the dam levee then make three-dimensional electrical-resistivity modeling for the streaming potential distribution of the dam levee. Our simulation algorithm of streaming SP distribution based on the integrated finite difference scheme computes two-dimensional (2D) SP distribution based on the distribution of calculated flow velocities of fluid for a given permeability structure together with physical properties. This permeability is repeatedly updated based on error between synthetic and field SP data, until the synthetic data match the field data. Through this trial-and-error-based SP interpretation, we locate the leakage of reservoir-water formed locally inside the levee body of the reservoir dam within the limitation due to the 2D nature of stream SP simulation.

Intravenous Chemotherapy Compounding Errors in a Follow-Up Pan-Canadian Observational Study.

PubMed

Gilbert, Rachel E; Kozak, Melissa C; Dobish, Roxanne B; Bourrier, Venetia C; Koke, Paul M; Kukreti, Vishal; Logan, Heather A; Easty, Anthony C; Trbovich, Patricia L

2018-05-01

Intravenous (IV) compounding safety has garnered recent attention as a result of high-profile incidents, awareness efforts from the safety community, and increasingly stringent practice standards. New research with more-sensitive error detection techniques continues to reinforce that error rates with manual IV compounding are unacceptably high. In 2014, our team published an observational study that described three types of previously unrecognized and potentially catastrophic latent chemotherapy preparation errors in Canadian oncology pharmacies that would otherwise be undetectable. We expand on this research and explore whether additional potential human failures are yet to be addressed by practice standards. Field observations were conducted in four cancer center pharmacies in four Canadian provinces from January 2013 to February 2015. Human factors specialists observed and interviewed pharmacy managers, oncology pharmacists, pharmacy technicians, and pharmacy assistants as they carried out their work. Emphasis was on latent errors (potential human failures) that could lead to outcomes such as wrong drug, dose, or diluent. Given the relatively short observational period, no active failures or actual errors were observed. However, 11 latent errors in chemotherapy compounding were identified. In terms of severity, all 11 errors create the potential for a patient to receive the wrong drug or dose, which in the context of cancer care, could lead to death or permanent loss of function. Three of the 11 practices were observed in our previous study, but eight were new. Applicable Canadian and international standards and guidelines do not explicitly address many of the potentially error-prone practices observed. We observed a significant degree of risk for error in manual mixing practice. These latent errors may exist in other regions where manual compounding of IV chemotherapy takes place. Continued efforts to advance standards, guidelines, technological innovation, and chemical quality testing are needed.

Effect of Bar-code Technology on the Incidence of Medication Dispensing Errors and Potential Adverse Drug Events in a Hospital Pharmacy

PubMed Central

Poon, Eric G; Cina, Jennifer L; Churchill, William W; Mitton, Patricia; McCrea, Michelle L; Featherstone, Erica; Keohane, Carol A; Rothschild, Jeffrey M; Bates, David W; Gandhi, Tejal K

2005-01-01

We performed a direct observation pre-post study to evaluate the impact of barcode technology on medication dispensing errors and potential adverse drug events in the pharmacy of a tertiary-academic medical center. We found that barcode technology significantly reduced the rate of target dispensing errors leaving the pharmacy by 85%, from 0.37% to 0.06%. The rate of potential adverse drug events (ADEs) due to dispensing errors was also significantly reduced by 63%, from 0.19% to 0.069%. In a 735-bed hospital where 6 million doses of medications are dispensed per year, this technology is expected to prevent about 13,000 dispensing errors and 6,000 potential ADEs per year. PMID:16779372

Progressive statistics for studies in sports medicine and exercise science.

PubMed

Hopkins, William G; Marshall, Stephen W; Batterham, Alan M; Hanin, Juri

2009-01-01

Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.

Evaluation of errors in quantitative determination of asbestos in rock

NASA Astrophysics Data System (ADS)

Baietto, Oliviero; Marini, Paola; Vitaliti, Martina

2016-04-01

The quantitative determination of the content of asbestos in rock matrices is a complex operation which is susceptible to important errors. The principal methodologies for the analysis are Scanning Electron Microscopy (SEM) and Phase Contrast Optical Microscopy (PCOM). Despite the PCOM resolution is inferior to that of SEM, PCOM analysis has several advantages, including more representativity of the analyzed sample, more effective recognition of chrysotile and a lower cost. The DIATI LAA internal methodology for the analysis in PCOM is based on a mild grinding of a rock sample, its subdivision in 5-6 grain size classes smaller than 2 mm and a subsequent microscopic analysis of a portion of each class. The PCOM is based on the optical properties of asbestos and of the liquids with note refractive index in which the particles in analysis are immersed. The error evaluation in the analysis of rock samples, contrary to the analysis of airborne filters, cannot be based on a statistical distribution. In fact for airborne filters a binomial distribution (Poisson), which theoretically defines the variation in the count of fibers resulting from the observation of analysis fields, chosen randomly on the filter, can be applied. The analysis in rock matrices instead cannot lean on any statistical distribution because the most important object of the analysis is the size of the of asbestiform fibers and bundles of fibers observed and the resulting relationship between the weights of the fibrous component compared to the one granular. The error evaluation generally provided by public and private institutions varies between 50 and 150 percent, but there are not, however, specific studies that discuss the origin of the error or that link it to the asbestos content. Our work aims to provide a reliable estimation of the error in relation to the applied methodologies and to the total content of asbestos, especially for the values close to the legal limits. The error assessments must be made through the repetition of the same analysis on the same sample to try to estimate the error on the representativeness of the sample and the error related to the sensitivity of the operator, in order to provide a sufficiently reliable uncertainty of the method. We used about 30 natural rock samples with different asbestos content, performing 3 analysis on each sample to obtain a trend sufficiently representative of the percentage. Furthermore we made on one chosen sample 10 repetition of the analysis to try to define more specifically the error of the methodology.

Quantifying Uncertainty in Instantaneous Orbital Data Products of TRMM over Indian Subcontinent

NASA Astrophysics Data System (ADS)

Jayaluxmi, I.; Nagesh, D.

2013-12-01

In the last 20 years, microwave radiometers have taken satellite images of earth's weather proving to be a valuable tool for quantitative estimation of precipitation from space. However, along with the widespread acceptance of microwave based precipitation products, it has also been recognized that they contain large uncertainties. While most of the uncertainty evaluation studies focus on the accuracy of rainfall accumulated over time (e.g., season/year), evaluation of instantaneous rainfall intensities from satellite orbital data products are relatively rare. These instantaneous products are known to potentially cause large uncertainties during real time flood forecasting studies at the watershed scale. Especially over land regions, where the highly varying land surface emissivity offer a myriad of complications hindering accurate rainfall estimation. The error components of orbital data products also tend to interact nonlinearly with hydrologic modeling uncertainty. Keeping these in mind, the present study fosters the development of uncertainty analysis using instantaneous satellite orbital data products (version 7 of 1B11, 2A25, 2A23) derived from the passive and active sensors onboard Tropical Rainfall Measuring Mission (TRMM) satellite, namely TRMM microwave imager (TMI) and Precipitation Radar (PR). The study utilizes 11 years of orbital data from 2002 to 2012 over the Indian subcontinent and examines the influence of various error sources on the convective and stratiform precipitation types. Analysis conducted over the land regions of India investigates three sources of uncertainty in detail. These include 1) Errors due to improper delineation of rainfall signature within microwave footprint (rain/no rain classification), 2) Uncertainty offered by the transfer function linking rainfall with TMI low frequency channels and 3) Sampling errors owing to the narrow swath and infrequent visits of TRMM sensors. Case study results obtained during the Indian summer monsoon months of June-September are presented using contingency table statistics, performance diagram, scatter plots and probability density functions. Our study demonstrates that theory of copula can be efficiently used to represent the highly non linear dependency structure of rainfall with respect to TMI low frequency channels of 19, 21, 37 GHz. This questions the exclusive usage of high frequency 85 GHz channel for TMI overland rainfall retrieval algorithms. Further, the PR sampling errors revealed using a statistical bootstrap technique was found to incur relative sampling errors <30% (for 2 degree grids) over India whose magnitudes were biased towards stratiform rainfall type and sampling technique employed. These findings clearly document that proper characterization of error structure offered by TMI and PR has wider implications for decision making prior to incorporating the resulting orbital products for basin scale hydrologic modeling.

Self-Reported and Observed Punitive Parenting Prospectively Predicts Increased Error-Related Brain Activity in Six-Year-Old Children.

PubMed

Meyer, Alexandria; Proudfit, Greg Hajcak; Bufferd, Sara J; Kujawa, Autumn J; Laptook, Rebecca S; Torpey, Dana C; Klein, Daniel N

2015-07-01

The error-related negativity (ERN) is a negative deflection in the event-related potential (ERP) occurring approximately 50 ms after error commission at fronto-central electrode sites and is thought to reflect the activation of a generic error monitoring system. Several studies have reported an increased ERN in clinically anxious children, and suggest that anxious children are more sensitive to error commission--although the mechanisms underlying this association are not clear. We have previously found that punishing errors results in a larger ERN, an effect that persists after punishment ends. It is possible that learning-related experiences that impact sensitivity to errors may lead to an increased ERN. In particular, punitive parenting might sensitize children to errors and increase their ERN. We tested this possibility in the current study by prospectively examining the relationship between parenting style during early childhood and children's ERN approximately 3 years later. Initially, 295 parents and children (approximately 3 years old) participated in a structured observational measure of parenting behavior, and parents completed a self-report measure of parenting style. At a follow-up assessment approximately 3 years later, the ERN was elicited during a Go/No-Go task, and diagnostic interviews were completed with parents to assess child psychopathology. Results suggested that both observational measures of hostile parenting and self-report measures of authoritarian parenting style uniquely predicted a larger ERN in children 3 years later. We previously reported that children in this sample with anxiety disorders were characterized by an increased ERN. A mediation analysis indicated that ERN magnitude mediated the relationship between harsh parenting and child anxiety disorder. Results suggest that parenting may shape children's error processing through environmental conditioning and thereby risk for anxiety, although future work is needed to confirm this hypothesis.

Assessing the accuracy and feasibility of a refractive error screening program conducted by school teachers in pre-primary and primary schools in Thailand.

PubMed

Teerawattananon, Kanlaya; Myint, Chaw-Yin; Wongkittirux, Kwanjai; Teerawattananon, Yot; Chinkulkitnivat, Bunyong; Orprayoon, Surapong; Kusakul, Suwat; Tengtrisorn, Supaporn; Jenchitr, Watanee

2014-01-01

As part of the development of a system for the screening of refractive error in Thai children, this study describes the accuracy and feasibility of establishing a program conducted by teachers. To assess the accuracy and feasibility of screening by teachers. A cross-sectional descriptive and analytical study was conducted in 17 schools in four provinces representing four geographic regions in Thailand. A two-staged cluster sampling was employed to compare the detection rate of refractive error among eligible students between trained teachers and health professionals. Serial focus group discussions were held for teachers and parents in order to understand their attitude towards refractive error screening at schools and the potential success factors and barriers. The detection rate of refractive error screening by teachers among pre-primary school children is relatively low (21%) for mild visual impairment but higher for moderate visual impairment (44%). The detection rate for primary school children is high for both levels of visual impairment (52% for mild and 74% for moderate). The focus group discussions reveal that both teachers and parents would benefit from further education regarding refractive errors and that the vast majority of teachers are willing to conduct a school-based screening program. Refractive error screening by health professionals in pre-primary and primary school children is not currently implemented in Thailand due to resource limitations. However, evidence suggests that a refractive error screening program conducted in schools by teachers in the country is reasonable and feasible because the detection and treatment of refractive error in very young generations is important and the screening program can be implemented and conducted with relatively low costs.

Dynamic Method for Identifying Collected Sample Mass

NASA Technical Reports Server (NTRS)

Carson, John

2008-01-01

G-Sample is designed for sample collection missions to identify the presence and quantity of sample material gathered by spacecraft equipped with end effectors. The software method uses a maximum-likelihood estimator to identify the collected sample's mass based on onboard force-sensor measurements, thruster firings, and a dynamics model of the spacecraft. This makes sample mass identification a computation rather than a process requiring additional hardware. Simulation examples of G-Sample are provided for spacecraft model configurations with a sample collection device mounted on the end of an extended boom. In the absence of thrust knowledge errors, the results indicate that G-Sample can identify the amount of collected sample mass to within 10 grams (with 95-percent confidence) by using a force sensor with a noise and quantization floor of 50 micrometers. These results hold even in the presence of realistic parametric uncertainty in actual spacecraft inertia, center-of-mass offset, and first flexibility modes. Thrust profile knowledge is shown to be a dominant sensitivity for G-Sample, entering in a nearly one-to-one relationship with the final mass estimation error. This means thrust profiles should be well characterized with onboard accelerometers prior to sample collection. An overall sample-mass estimation error budget has been developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

Primer ID Validates Template Sampling Depth and Greatly Reduces the Error Rate of Next-Generation Sequencing of HIV-1 Genomic RNA Populations

PubMed Central

Zhou, Shuntai; Jones, Corbin; Mieczkowski, Piotr

2015-01-01

ABSTRACT Validating the sampling depth and reducing sequencing errors are critical for studies of viral populations using next-generation sequencing (NGS). We previously described the use of Primer ID to tag each viral RNA template with a block of degenerate nucleotides in the cDNA primer. We now show that low-abundance Primer IDs (offspring Primer IDs) are generated due to PCR/sequencing errors. These artifactual Primer IDs can be removed using a cutoff model for the number of reads required to make a template consensus sequence. We have modeled the fraction of sequences lost due to Primer ID resampling. For a typical sequencing run, less than 10% of the raw reads are lost to offspring Primer ID filtering and resampling. The remaining raw reads are used to correct for PCR resampling and sequencing errors. We also demonstrate that Primer ID reveals bias intrinsic to PCR, especially at low template input or utilization. cDNA synthesis and PCR convert ca. 20% of RNA templates into recoverable sequences, and 30-fold sequence coverage recovers most of these template sequences. We have directly measured the residual error rate to be around 1 in 10,000 nucleotides. We use this error rate and the Poisson distribution to define the cutoff to identify preexisting drug resistance mutations at low abundance in an HIV-infected subject. Collectively, these studies show that >90% of the raw sequence reads can be used to validate template sampling depth and to dramatically reduce the error rate in assessing a genetically diverse viral population using NGS. IMPORTANCE Although next-generation sequencing (NGS) has revolutionized sequencing strategies, it suffers from serious limitations in defining sequence heterogeneity in a genetically diverse population, such as HIV-1 due to PCR resampling and PCR/sequencing errors. The Primer ID approach reveals the true sampling depth and greatly reduces errors. Knowing the sampling depth allows the construction of a model of how to maximize the recovery of sequences from input templates and to reduce resampling of the Primer ID so that appropriate multiplexing can be included in the experimental design. With the defined sampling depth and measured error rate, we are able to assign cutoffs for the accurate detection of minority variants in viral populations. This approach allows the power of NGS to be realized without having to guess about sampling depth or to ignore the problem of PCR resampling, while also being able to correct most of the errors in the data set. PMID:26041299

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

An adaptive interpolation scheme for molecular potential energy surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kowalewski, Markus, E-mail: mkowalew@uci.edu; Larsson, Elisabeth; Heryudono, Alfa

The calculation of potential energy surfaces for quantum dynamics can be a time consuming task—especially when a high level of theory for the electronic structure calculation is required. We propose an adaptive interpolation algorithm based on polyharmonic splines combined with a partition of unity approach. The adaptive node refinement allows to greatly reduce the number of sample points by employing a local error estimate. The algorithm and its scaling behavior are evaluated for a model function in 2, 3, and 4 dimensions. The developed algorithm allows for a more rapid and reliable interpolation of a potential energy surface within amore » given accuracy compared to the non-adaptive version.« less

Student Errors in Fractions and Possible Causes of These Errors

ERIC Educational Resources Information Center

Aksoy, Nuri Can; Yazlik, Derya Ozlem

2017-01-01

In this study, it was aimed to determine the errors and misunderstandings of 5th and 6th grade middle school students in fractions and operations with fractions. For this purpose, the case study model, which is a qualitative research design, was used in the research. In the study, maximum diversity sampling, which is a purposeful sampling method,…

Estimation of sampling error uncertainties in observed surface air temperature change in China

NASA Astrophysics Data System (ADS)

Hua, Wei; Shen, Samuel S. P.; Weithmann, Alexander; Wang, Huijun

2017-08-01

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K2 while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K2. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)-1 occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)-1 in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

USGS Publications Warehouse

Sethi, Suresh; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick R.; Fuller, Angela K.; Hare, Matthew P.

2016-01-01

Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

Errors in causal inference: an organizational schema for systematic error and random error.

PubMed

Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

2016-11-01

To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.

GY SAMPLING THEORY AND GEOSTATISTICS: ALTERNATE MODELS OF VARIABILITY IN CONTINUOUS MEDIA

EPA Science Inventory

In the sampling theory developed by Pierre Gy, sample variability is modeled as the sum of a set of seven discrete error components. The variogram used in geostatisties provides an alternate model in which several of Gy's error components are combined in a continuous mode...

Error tolerance analysis of wave diagnostic based on coherent modulation imaging in high power laser system

NASA Astrophysics Data System (ADS)

Pan, Xingchen; Liu, Cheng; Zhu, Jianqiang

2018-02-01

Coherent modulation imaging providing fast convergence speed and high resolution with single diffraction pattern is a promising technique to satisfy the urgent demands for on-line multiple parameter diagnostics with single setup in high power laser facilities (HPLF). However, the influence of noise on the final calculated parameters concerned has not been investigated yet. According to a series of simulations with twenty different sampling beams generated based on the practical parameters and performance of HPLF, the quantitative analysis based on statistical results was first investigated after considering five different error sources. We found the background noise of detector and high quantization error will seriously affect the final accuracy and different parameters have different sensitivity to different noise sources. The simulation results and the corresponding analysis provide the potential directions to further improve the final accuracy of parameter diagnostics which is critically important to its formal applications in the daily routines of HPLF.

Statistically Controlling for Confounding Constructs Is Harder than You Think

PubMed Central

Westfall, Jacob; Yarkoni, Tal

2016-01-01

Social scientists often seek to demonstrate that a construct has incremental validity over and above other related constructs. However, these claims are typically supported by measurement-level models that fail to consider the effects of measurement (un)reliability. We use intuitive examples, Monte Carlo simulations, and a novel analytical framework to demonstrate that common strategies for establishing incremental construct validity using multiple regression analysis exhibit extremely high Type I error rates under parameter regimes common in many psychological domains. Counterintuitively, we find that error rates are highest—in some cases approaching 100%—when sample sizes are large and reliability is moderate. Our findings suggest that a potentially large proportion of incremental validity claims made in the literature are spurious. We present a web application (http://jakewestfall.org/ivy/) that readers can use to explore the statistical properties of these and other incremental validity arguments. We conclude by reviewing SEM-based statistical approaches that appropriately control the Type I error rate when attempting to establish incremental validity. PMID:27031707

Identification errors in the blood transfusion laboratory: a still relevant issue for patient safety.

PubMed

Lippi, Giuseppe; Plebani, Mario

2011-04-01

Remarkable technological advances and increased awareness have both contributed to decrease substantially the uncertainty of the analytical phase, so that the manually intensive preanalytical activities currently represent the leading sources of errors in laboratory and transfusion medicine. Among preanalytical errors, misidentification and mistransfusion are still regarded as a considerable problem, posing serious risks for patient health and carrying huge expenses for the healthcare system. As such, a reliable policy of risk management should be readily implemented, developing through a multifaceted approach to prevent or limit the adverse outcomes related to transfusion reactions from blood incompatibility. This strategy encompasses root cause analysis, compliance with accreditation requirements, strict adherence to standard operating procedures, guidelines and recommendations for specimen collection, use of positive identification devices, rejection of potentially misidentified specimens, informatics data entry, query host communication, automated systems for patient identification and sample labeling and an adequate and safe environment. Copyright © 2011 Elsevier Ltd. All rights reserved.

A random-sampling high dimensional model representation neural network for building potential energy surfaces

NASA Astrophysics Data System (ADS)

Manzhos, Sergei; Carrington, Tucker

2006-08-01

We combine the high dimensional model representation (HDMR) idea of Rabitz and co-workers [J. Phys. Chem. 110, 2474 (2006)] with neural network (NN) fits to obtain an effective means of building multidimensional potentials. We verify that it is possible to determine an accurate many-dimensional potential by doing low dimensional fits. The final potential is a sum of terms each of which depends on a subset of the coordinates. This form facilitates quantum dynamics calculations. We use NNs to represent HDMR component functions that minimize error mode term by mode term. This NN procedure makes it possible to construct high-order component functions which in turn enable us to determine a good potential. It is shown that the number of available potential points determines the order of the HDMR which should be used.

A random-sampling high dimensional model representation neural network for building potential energy surfaces.

PubMed

Manzhos, Sergei; Carrington, Tucker

2006-08-28

We combine the high dimensional model representation (HDMR) idea of Rabitz and co-workers [J. Phys. Chem. 110, 2474 (2006)] with neural network (NN) fits to obtain an effective means of building multidimensional potentials. We verify that it is possible to determine an accurate many-dimensional potential by doing low dimensional fits. The final potential is a sum of terms each of which depends on a subset of the coordinates. This form facilitates quantum dynamics calculations. We use NNs to represent HDMR component functions that minimize error mode term by mode term. This NN procedure makes it possible to construct high-order component functions which in turn enable us to determine a good potential. It is shown that the number of available potential points determines the order of the HDMR which should be used.

Bioavailability and Methylation Potential of Mercury Sulfides in Sediments

DTIC Science & Technology

2014-08-01

such as size separation (i.e. filtration with a particular pore size or molecular weight cutoff) or metal-ligand complexation from experimentally ...and 6 nM HgS microparticles. The error bars represent ±1 s.d. for duplicate samples. Results of Hg fractionation by filtration and (ultra... results from filtration (Figures S2). These differences in the data indicated that the nHgS dissolution rate could be overestimated by the filtration data

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales-review and recommendations.

PubMed

Vanguelova, E I; Bonifacio, E; De Vos, B; Hoosbeek, M R; Berger, T W; Vesterdal, L; Armolaitis, K; Celi, L; Dinca, L; Kjønaas, O J; Pavlenda, P; Pumpanen, J; Püttsepp, Ü; Reidy, B; Simončič, P; Tobin, B; Zhiyanski, M

2016-11-01

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.

[Modal failure analysis and effects in the detection of errors in the transport of samples to the clinical laboratory].

PubMed

Parés-Pollán, L; Gonzalez-Quintana, A; Docampo-Cordeiro, J; Vargas-Gallego, C; García-Álvarez, G; Ramos-Rodríguez, V; Diaz Rubio-García, M P

2014-01-01

Owing to the decrease in values of biochemical glucose parameter in some samples from external extraction centres, and the risk this implies to patient safety; it was decided to apply an adaptation of the «Health Services Failure Mode and Effects Analysis» (HFMEA) to manage risk during the pre-analytical phase of sample transportation from external centres to clinical laboratories. A retrospective study of glucose parameter was conducted during two consecutive months. The analysis was performed in its different phases: to define the HFMEA topic, assemble the team, graphically describe the process, conduct a hazard analysis, design the intervention and indicators, and identify a person to be responsible for ensuring completion of each action. The results of glucose parameter in one of the transport routes, were significantly lower (P=.006). The errors and potential causes of this problem were analysed, and criteria of criticality and detectability were applied (score≥8) in the decision tree. It was decided to: develop a document management system; reorganise extractions and transport routes in some centres; quality control of the sample container ice-packs, and the time and temperature during transportation. This work proposes quality indicators for controlling time and temperature of transported samples in the pre-analytical phase. Periodic review of certain laboratory parameters can help to detect problems in transporting samples. The HFMEA technique is useful for the clinical laboratory. Copyright © 2013 SECA. Published by Elsevier Espana. All rights reserved.

Maximum inflation of the type 1 error rate when sample size and allocation rate are adapted in a pre-planned interim look.

PubMed

Graf, Alexandra C; Bauer, Peter

2011-06-30

We calculate the maximum type 1 error rate of the pre-planned conventional fixed sample size test for comparing the means of independent normal distributions (with common known variance) which can be yielded when sample size and allocation rate to the treatment arms can be modified in an interim analysis. Thereby it is assumed that the experimenter fully exploits knowledge of the unblinded interim estimates of the treatment effects in order to maximize the conditional type 1 error rate. The 'worst-case' strategies require knowledge of the unknown common treatment effect under the null hypothesis. Although this is a rather hypothetical scenario it may be approached in practice when using a standard control treatment for which precise estimates are available from historical data. The maximum inflation of the type 1 error rate is substantially larger than derived by Proschan and Hunsberger (Biometrics 1995; 51:1315-1324) for design modifications applying balanced samples before and after the interim analysis. Corresponding upper limits for the maximum type 1 error rate are calculated for a number of situations arising from practical considerations (e.g. restricting the maximum sample size, not allowing sample size to decrease, allowing only increase in the sample size in the experimental treatment). The application is discussed for a motivating example. Copyright © 2011 John Wiley & Sons, Ltd.

[Errors in Peruvian medical journals references].

PubMed

Huamaní, Charles; Pacheco-Romero, José

2009-01-01

References are fundamental in our studies; an adequate selection is asimportant as an adequate description. To determine the number of errors in a sample of references found in Peruvian medical journals. We reviewed 515 scientific papers references selected by systematic randomized sampling and corroborated reference information with the original document or its citation in Pubmed, LILACS or SciELO-Peru. We found errors in 47,6% (245) of the references, identifying 372 types of errors; the most frequent were errors in presentation style (120), authorship (100) and title (100), mainly due to spelling mistakes (91). References error percentage was high, varied and multiple. We suggest systematic revision of references in the editorial process as well as to extend the discussion on this theme. references, periodicals, research, bibliometrics.

Medication Errors in Vietnamese Hospitals: Prevalence, Potential Outcome and Associated Factors

PubMed Central

Nguyen, Huong-Thao; Nguyen, Tuan-Dung; van den Heuvel, Edwin R.; Haaijer-Ruskamp, Flora M.; Taxis, Katja

2015-01-01

Background Evidence from developed countries showed that medication errors are common and harmful. Little is known about medication errors in resource-restricted settings, including Vietnam. Objectives To determine the prevalence and potential clinical outcome of medication preparation and administration errors, and to identify factors associated with errors. Methods This was a prospective study conducted on six wards in two urban public hospitals in Vietnam. Data of preparation and administration errors of oral and intravenous medications was collected by direct observation, 12 hours per day on 7 consecutive days, on each ward. Multivariable logistic regression was applied to identify factors contributing to errors. Results In total, 2060 out of 5271 doses had at least one error. The error rate was 39.1% (95% confidence interval 37.8%- 40.4%). Experts judged potential clinical outcomes as minor, moderate, and severe in 72 (1.4%), 1806 (34.2%) and 182 (3.5%) doses. Factors associated with errors were drug characteristics (administration route, complexity of preparation, drug class; all p values < 0.001), and administration time (drug round, p = 0.023; day of the week, p = 0.024). Several interactions between these factors were also significant. Nurse experience was not significant. Higher error rates were observed for intravenous medications involving complex preparation procedures and for anti-infective drugs. Slightly lower medication error rates were observed during afternoon rounds compared to other rounds. Conclusions Potentially clinically relevant errors occurred in more than a third of all medications in this large study conducted in a resource-restricted setting. Educational interventions, focusing on intravenous medications with complex preparation procedure, particularly antibiotics, are likely to improve patient safety. PMID:26383873

Prescribing Errors Involving Medication Dosage Forms

PubMed Central

Lesar, Timothy S

2002-01-01

CONTEXT Prescribing errors involving medication dose formulations have been reported to occur frequently in hospitals. No systematic evaluations of the characteristics of errors related to medication dosage formulation have been performed. OBJECTIVE To quantify the characteristics, frequency, and potential adverse patient effects of prescribing errors involving medication dosage forms . DESIGN Evaluation of all detected medication prescribing errors involving or related to medication dosage forms in a 631-bed tertiary care teaching hospital. MAIN OUTCOME MEASURES Type, frequency, and potential for adverse effects of prescribing errors involving or related to medication dosage forms. RESULTS A total of 1,115 clinically significant prescribing errors involving medication dosage forms were detected during the 60-month study period. The annual number of detected errors increased throughout the study period. Detailed analysis of the 402 errors detected during the last 16 months of the study demonstrated the most common errors to be: failure to specify controlled release formulation (total of 280 cases; 69.7%) both when prescribing using the brand name (148 cases; 36.8%) and when prescribing using the generic name (132 cases; 32.8%); and prescribing controlled delivery formulations to be administered per tube (48 cases; 11.9%). The potential for adverse patient outcome was rated as potentially “fatal or severe” in 3 cases (0.7%), and “serious” in 49 cases (12.2%). Errors most commonly involved cardiovascular agents (208 cases; 51.7%). CONCLUSIONS Hospitalized patients are at risk for adverse outcomes due to prescribing errors related to inappropriate use of medication dosage forms. This information should be considered in the development of strategies to prevent adverse patient outcomes resulting from such errors. PMID:12213138

Introduction to the Application of Web-Based Surveys.

ERIC Educational Resources Information Center

Timmerman, Annemarie

This paper discusses some basic assumptions and issues concerning web-based surveys. Discussion includes: assumptions regarding cost and ease of use; disadvantages of web-based surveys, concerning the inability to compensate for four common errors of survey research: coverage error, sampling error, measurement error and nonresponse error; and…

Amelogenin test: From forensics to quality control in clinical and biochemical genomics.

PubMed

Francès, F; Portolés, O; González, J I; Coltell, O; Verdú, F; Castelló, A; Corella, D

2007-01-01

The increasing number of samples from the biomedical genetic studies and the number of centers participating in the same involves increasing risk of mistakes in the different sample handling stages. We have evaluated the usefulness of the amelogenin test for quality control in sample identification. Amelogenin test (frequently used in forensics) was undertaken on 1224 individuals participating in a biomedical study. Concordance between referred sex in the database and amelogenin test was estimated. Additional sex-error genetic detecting systems were developed. The overall concordance rate was 99.84% (1222/1224). Two samples showed a female amelogenin test outcome, being codified as males in the database. The first, after checking sex-specific biochemical and clinical profile data was found to be due to a codification error in the database. In the second, after checking the database, no apparent error was discovered because a correct male profile was found. False negatives in amelogenin male sex determination were discarded by additional tests, and feminine sex was confirmed. A sample labeling error was revealed after a new DNA extraction. The amelogenin test is a useful quality control tool for detecting sex-identification errors in large genomic studies, and can contribute to increase its validity.

Human Factors Process Task Analysis: Liquid Oxygen Pump Acceptance Test Procedure at the Advanced Technology Development Center

NASA Technical Reports Server (NTRS)

Diorio, Kimberly A.; Voska, Ned (Technical Monitor)

2002-01-01

This viewgraph presentation provides information on Human Factors Process Failure Modes and Effects Analysis (HF PFMEA). HF PFMEA includes the following 10 steps: Describe mission; Define System; Identify human-machine; List human actions; Identify potential errors; Identify factors that effect error; Determine likelihood of error; Determine potential effects of errors; Evaluate risk; Generate solutions (manage error). The presentation also describes how this analysis was applied to a liquid oxygen pump acceptance test.

Multiple category-lot quality assurance sampling: a new classification system with application to schistosomiasis control.

PubMed

Olives, Casey; Valadez, Joseph J; Brooker, Simon J; Pagano, Marcello

2012-01-01

Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa. We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n=15 and n=25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa. Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n=15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error. This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools.

Evaluation of visible and near-infrared spectroscopy as a tool for assessing fiber fineness during mechanical preparation of dew-retted flax.

PubMed

Sharma, H S S; Reinard, N

2004-12-01

Flax fiber must be mechanically prepared to improve fineness and homogeneity of the sliver before chemical processing and wet-spinning. The changes in fiber characteristics are monitored by an airflow method, which is labor intensive and requires 90 minutes to process one sample. This investigation was carried out to develop robust visible and near-infrared calibrations that can be used as a rapid tool for quality assessment of input fibers and changes in fineness at the doubling (blending), first, second, third, and fourth drawing frames, and at the roving stage. The partial least squares (PLS) and principal component regression (PCR) methods were employed to generate models from different segments of the spectra (400-1100, 1100-1700, 1100-2498, 1700-2498, and 400-2498 nm) and a calibration set consisting of 462 samples obtained from the six processing stages. The calibrations were successfully validated with an independent set of 97 samples, and standard errors of prediction of 2.32 and 2.62 dtex were achieved with the best PLS (400-2498 nm) and PCR (1100-2498 nm) models, respectively. An optimized PLS model of the visible-near-infrared (vis-NIR) spectra explained 97% of the variation (R(2) = 0.97) in the sample set with a standard error of calibration (SEC) of 2.45 dtex and a standard error of cross-validation (SECV) of 2.51 dtex R(2) = 0.96). The mean error of the reference airflow method was 1.56 dtex, which is more accurate than the NIR calibration. The improvement in fiber fineness of the validation set obtained from the six production lines was predicted with an error range of -6.47 to +7.19 dtex for input fibers, -1.44 to +5.77 dtex for blended fibers at the doubling, and -4.72 to +3.59 dtex at the drawing frame stages. This level of precision is adequate for wet-spinners to monitor fiber fineness of input fibers and during the preparation of fibers. The advantage of visNIR spectroscopy is the potential capability of the technique to assess fineness and other important quality characteristics of a fiber sample simultaneously in less than 30 minutes; the disadvantages are the expensive instrumentation and the expertise required for operating the instrument compared to the reference method. These factors need to be considered by the industry before installing an off-line NIR system for predicting quality parameters of input materials and changes in fiber characteristics during mechanical processing.

Density dependence and climate effects in Rocky Mountain elk: an application of regression with instrumental variables for population time series with sampling error.

PubMed

Creel, Scott; Creel, Michael

2009-11-01

1. Sampling error in annual estimates of population size creates two widely recognized problems for the analysis of population growth. First, if sampling error is mistakenly treated as process error, one obtains inflated estimates of the variation in true population trajectories (Staples, Taper & Dennis 2004). Second, treating sampling error as process error is thought to overestimate the importance of density dependence in population growth (Viljugrein et al. 2005; Dennis et al. 2006). 2. In ecology, state-space models are used to account for sampling error when estimating the effects of density and other variables on population growth (Staples et al. 2004; Dennis et al. 2006). In econometrics, regression with instrumental variables is a well-established method that addresses the problem of correlation between regressors and the error term, but requires fewer assumptions than state-space models (Davidson & MacKinnon 1993; Cameron & Trivedi 2005). 3. We used instrumental variables to account for sampling error and fit a generalized linear model to 472 annual observations of population size for 35 Elk Management Units in Montana, from 1928 to 2004. We compared this model with state-space models fit with the likelihood function of Dennis et al. (2006). We discuss the general advantages and disadvantages of each method. Briefly, regression with instrumental variables is valid with fewer distributional assumptions, but state-space models are more efficient when their distributional assumptions are met. 4. Both methods found that population growth was negatively related to population density and winter snow accumulation. Summer rainfall and wolf (Canis lupus) presence had much weaker effects on elk (Cervus elaphus) dynamics [though limitation by wolves is strong in some elk populations with well-established wolf populations (Creel et al. 2007; Creel & Christianson 2008)]. 5. Coupled with predictions for Montana from global and regional climate models, our results predict a substantial reduction in the limiting effect of snow accumulation on Montana elk populations in the coming decades. If other limiting factors do not operate with greater force, population growth rates would increase substantially.

Automated storm water sampling on small watersheds

USGS Publications Warehouse

Harmel, R.D.; King, K.W.; Slade, R.M.

2003-01-01

Few guidelines are currently available to assist in designing appropriate automated storm water sampling strategies for small watersheds. Therefore, guidance is needed to develop strategies that achieve an appropriate balance between accurate characterization of storm water quality and loads and limitations of budget, equipment, and personnel. In this article, we explore the important sampling strategy components (minimum flow threshold, sampling interval, and discrete versus composite sampling) and project-specific considerations (sampling goal, sampling and analysis resources, and watershed characteristics) based on personal experiences and pertinent field and analytical studies. These components and considerations are important in achieving the balance between sampling goals and limitations because they determine how and when samples are taken and the potential sampling error. Several general recommendations are made, including: setting low minimum flow thresholds, using flow-interval or variable time-interval sampling, and using composite sampling to limit the number of samples collected. Guidelines are presented to aid in selection of an appropriate sampling strategy based on user's project-specific considerations. Our experiences suggest these recommendations should allow implementation of a successful sampling strategy for most small watershed sampling projects with common sampling goals.

Evaluation and mitigation of potential errors in radiochromic film dosimetry due to film curvature at scanning.

PubMed

Palmer, Antony L; Bradley, David A; Nisbet, Andrew

2015-03-08

This work considers a previously overlooked uncertainty present in film dosimetry which results from moderate curvature of films during the scanning process. Small film samples are particularly susceptible to film curling which may be undetected or deemed insignificant. In this study, we consider test cases with controlled induced curvature of film and with film raised horizontally above the scanner plate. We also evaluate the difference in scans of a film irradiated with a typical brachytherapy dose distribution with the film naturally curved and with the film held flat on the scanner. Typical naturally occurring curvature of film at scanning, giving rise to a maximum height 1 to 2 mm above the scan plane, may introduce dose errors of 1% to 4%, and considerably reduce gamma evaluation passing rates when comparing film-measured doses with treatment planning system-calculated dose distributions, a common application of film dosimetry in radiotherapy. The use of a triple-channel dosimetry algorithm appeared to mitigate the error due to film curvature compared to conventional single-channel film dosimetry. The change in pixel value and calibrated reported dose with film curling or height above the scanner plate may be due to variations in illumination characteristics, optical disturbances, or a Callier-type effect. There is a clear requirement for physically flat films at scanning to avoid the introduction of a substantial error source in film dosimetry. Particularly for small film samples, a compression glass plate above the film is recommended to ensure flat-film scanning. This effect has been overlooked to date in the literature.

Quantification of errors in ordinal outcome scales using shannon entropy: effect on sample size calculations.

PubMed

Mandava, Pitchaiah; Krumpelman, Chase S; Shah, Jharna N; White, Donna L; Kent, Thomas A

2013-01-01

Clinical trial outcomes often involve an ordinal scale of subjective functional assessments but the optimal way to quantify results is not clear. In stroke, the most commonly used scale, the modified Rankin Score (mRS), a range of scores ("Shift") is proposed as superior to dichotomization because of greater information transfer. The influence of known uncertainties in mRS assessment has not been quantified. We hypothesized that errors caused by uncertainties could be quantified by applying information theory. Using Shannon's model, we quantified errors of the "Shift" compared to dichotomized outcomes using published distributions of mRS uncertainties and applied this model to clinical trials. We identified 35 randomized stroke trials that met inclusion criteria. Each trial's mRS distribution was multiplied with the noise distribution from published mRS inter-rater variability to generate an error percentage for "shift" and dichotomized cut-points. For the SAINT I neuroprotectant trial, considered positive by "shift" mRS while the larger follow-up SAINT II trial was negative, we recalculated sample size required if classification uncertainty was taken into account. Considering the full mRS range, error rate was 26.1%±5.31 (Mean±SD). Error rates were lower for all dichotomizations tested using cut-points (e.g. mRS 1; 6.8%±2.89; overall p<0.001). Taking errors into account, SAINT I would have required 24% more subjects than were randomized. We show when uncertainty in assessments is considered, the lowest error rates are with dichotomization. While using the full range of mRS is conceptually appealing, a gain of information is counter-balanced by a decrease in reliability. The resultant errors need to be considered since sample size may otherwise be underestimated. In principle, we have outlined an approach to error estimation for any condition in which there are uncertainties in outcome assessment. We provide the user with programs to calculate and incorporate errors into sample size estimation.

Sampling Theory and Confidence Intervals for Effect Sizes: Using ESCI To Illustrate "Bouncing"; Confidence Intervals.

ERIC Educational Resources Information Center

Du, Yunfei

This paper discusses the impact of sampling error on the construction of confidence intervals around effect sizes. Sampling error affects the location and precision of confidence intervals. Meta-analytic resampling demonstrates that confidence intervals can haphazardly bounce around the true population parameter. Special software with graphical…

STATISTICAL DISTRIBUTIONS OF PARTICULATE MATTER AND THE ERROR ASSOCIATED WITH SAMPLING FREQUENCY. (R828678C010)

EPA Science Inventory

The distribution of particulate matter (PM) concentrations has an impact on human health effects and the setting of PM regulations. Since PM is commonly sampled on less than daily schedules, the magnitude of sampling errors needs to be determined. Daily PM data from Spokane, W...

Impact of Educational Activities in Reducing Pre-Analytical Laboratory Errors

PubMed Central

Al-Ghaithi, Hamed; Pathare, Anil; Al-Mamari, Sahimah; Villacrucis, Rodrigo; Fawaz, Naglaa; Alkindi, Salam

2017-01-01

Objectives Pre-analytic errors during diagnostic laboratory investigations can lead to increased patient morbidity and mortality. This study aimed to ascertain the effect of educational nursing activities on the incidence of pre-analytical errors resulting in non-conforming blood samples. Methods This study was conducted between January 2008 and December 2015. All specimens received at the Haematology Laboratory of the Sultan Qaboos University Hospital, Muscat, Oman, during this period were prospectively collected and analysed. Similar data from 2007 were collected retrospectively and used as a baseline for comparison. Non-conforming samples were defined as either clotted samples, haemolysed samples, use of the wrong anticoagulant, insufficient quantities of blood collected, incorrect/lack of labelling on a sample or lack of delivery of a sample in spite of a sample request. From 2008 onwards, multiple educational training activities directed at the hospital nursing staff and nursing students primarily responsible for blood collection were implemented on a regular basis. Results After initiating corrective measures in 2008, a progressive reduction in the percentage of non-conforming samples was observed from 2009 onwards. Despite a 127.84% increase in the total number of specimens received, there was a significant reduction in non-conforming samples from 0.29% in 2007 to 0.07% in 2015, resulting in an improvement of 75.86% (P <0.050). In particular, specimen identification errors decreased by 0.056%, with a 96.55% improvement. Conclusion Targeted educational activities directed primarily towards hospital nursing staff had a positive impact on the quality of laboratory specimens by significantly reducing pre-analytical errors. PMID:29062553

Impact of Educational Activities in Reducing Pre-Analytical Laboratory Errors: A quality initiative.

PubMed

Al-Ghaithi, Hamed; Pathare, Anil; Al-Mamari, Sahimah; Villacrucis, Rodrigo; Fawaz, Naglaa; Alkindi, Salam

2017-08-01

Pre-analytic errors during diagnostic laboratory investigations can lead to increased patient morbidity and mortality. This study aimed to ascertain the effect of educational nursing activities on the incidence of pre-analytical errors resulting in non-conforming blood samples. This study was conducted between January 2008 and December 2015. All specimens received at the Haematology Laboratory of the Sultan Qaboos University Hospital, Muscat, Oman, during this period were prospectively collected and analysed. Similar data from 2007 were collected retrospectively and used as a baseline for comparison. Non-conforming samples were defined as either clotted samples, haemolysed samples, use of the wrong anticoagulant, insufficient quantities of blood collected, incorrect/lack of labelling on a sample or lack of delivery of a sample in spite of a sample request. From 2008 onwards, multiple educational training activities directed at the hospital nursing staff and nursing students primarily responsible for blood collection were implemented on a regular basis. After initiating corrective measures in 2008, a progressive reduction in the percentage of non-conforming samples was observed from 2009 onwards. Despite a 127.84% increase in the total number of specimens received, there was a significant reduction in non-conforming samples from 0.29% in 2007 to 0.07% in 2015, resulting in an improvement of 75.86% ( P <0.050). In particular, specimen identification errors decreased by 0.056%, with a 96.55% improvement. Targeted educational activities directed primarily towards hospital nursing staff had a positive impact on the quality of laboratory specimens by significantly reducing pre-analytical errors.

A Combined Fabrication and Instrumentation Platform for Sample Preparation.

PubMed

Guckenberger, David J; Thomas, Peter C; Rothbauer, Jacob; LaVanway, Alex J; Anderson, Meghan; Gilson, Dan; Fawcett, Kevin; Berto, Tristan; Barrett, Kevin; Beebe, David J; Berry, Scott M

2014-06-01

While potentially powerful, access to molecular diagnostics is substantially limited in the developing world. Here we present an approach to reduced cost molecular diagnostic instrumentation that has the potential to empower developing world communities by reducing costs through streamlining the sample preparation process. In addition, this instrument is capable of producing its own consumable devices on demand, reducing reliance on assay suppliers. Furthermore, this instrument is designed with an "open" architecture, allowing users to visually observe the assay process and make modifications as necessary (as opposed to traditional "black box" systems). This open environment enables integration of microfluidic fabrication and viral RNA purification onto an easy-to-use modular system via the use of interchangeable trays. Here we employ this system to develop a protocol to fabricate microfluidic devices and then use these devices to isolate viral RNA from serum for the measurement of human immunodeficiency virus (HIV) viral load. Results obtained from this method show significantly reduced error compared with similar nonautomated sample preparation processes. © 2014 Society for Laboratory Automation and Screening.

Sample Training Based Wildfire Segmentation by 2D Histogram θ-Division with Minimum Error

PubMed Central

Dong, Erqian; Sun, Mingui; Jia, Wenyan; Zhang, Dengyi; Yuan, Zhiyong

2013-01-01

A novel wildfire segmentation algorithm is proposed with the help of sample training based 2D histogram θ-division and minimum error. Based on minimum error principle and 2D color histogram, the θ-division methods were presented recently, but application of prior knowledge on them has not been explored. For the specific problem of wildfire segmentation, we collect sample images with manually labeled fire pixels. Then we define the probability function of error division to evaluate θ-division segmentations, and the optimal angle θ is determined by sample training. Performances in different color channels are compared, and the suitable channel is selected. To further improve the accuracy, the combination approach is presented with both θ-division and other segmentation methods such as GMM. Our approach is tested on real images, and the experiments prove its efficiency for wildfire segmentation. PMID:23878526

Comparisons of refractive errors between twins and singletons in Chinese school-age samples.

PubMed

Hur, Yoon-Mi; Zheng, Yingfeng; Huang, Wenyong; Ding, Xiaohu; He, Mingguang

2009-02-01

Studies have reported that refractive errors are associated with premature births. As twins have higher prevalence of prematurity than singletons, it is important to assess similarity of the prevalence of refractive errors in twins and singletons for proper interpretations and generalizations of the findings from twin studies. We compared refractive errors and diopter hours between 561 pairs of twins and 3757 singletons who are representative of school-age children (7-15 years) residing in an urban area of southern China. We found that the means and variances of the continuous measurement of spherical equivalent refractive error and diopter hours were not significantly different between twins and singletons. Although the prevalence of myopia was comparable between twins and singletons, that of hyperopia and astigmatism was slightly but significantly higher in twins than in singletons. These results are inconsistent with those of adult studies that showed no differences in refractive errors between twins and singletons. Given that the sample size of twins is relatively small and that this study is the first to demonstrate minor differences in refractive errors between twins and singletons, future replications are necessary to determine whether the slightly higher prevalence of refractive errors in twins than in singletons found in this study was due to a sampling error or to the developmental delay often observed in twins in childhood.

Using EHR Data to Detect Prescribing Errors in Rapidly Discontinued Medication Orders.

PubMed

Burlison, Jonathan D; McDaniel, Robert B; Baker, Donald K; Hasan, Murad; Robertson, Jennifer J; Howard, Scott C; Hoffman, James M

2018-01-01

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use. Our objectives were to assess a method to retrospectively detect prescribing errors, to characterize the identified errors, and to identify potential improvement opportunities. Electronically submitted medication orders from 28 randomly selected days that were discontinued within 120 minutes of submission were reviewed and categorized as most likely errors, nonerrors, or not enough information to determine status. Identified errors were evaluated by amount of time elapsed from original submission to discontinuation, error type, staff position, and potential clinical significance. Pearson's chi-square test was used to compare rates of errors across prescriber types. In all, 147 errors were identified in 305 medication orders. The method was most effective for orders that were discontinued within 90 minutes. Duplicate orders were most common; physicians in training had the highest error rate ( p  < 0.001), and 24 errors were potentially clinically significant. None of the errors were voluntarily reported. It is possible to identify prescribing errors in rapidly discontinued medication orders by using retrospective methods that do not require interrupting prescribers to discuss order details. Future research could validate our methods in different clinical settings. Regular use of this measure could help determine the causes of prescribing errors, track performance, and identify and evaluate interventions to improve prescribing systems and processes. Schattauer GmbH Stuttgart.

Constructing a multidimensional free energy surface like a spider weaving a web.

PubMed

Chen, Changjun

2017-10-15

Complete free energy surface in the collective variable space provides important information of the reaction mechanisms of the molecules. But, sufficient sampling in the collective variable space is not easy. The space expands quickly with the number of the collective variables. To solve the problem, many methods utilize artificial biasing potentials to flatten out the original free energy surface of the molecule in the simulation. Their performances are sensitive to the definitions of the biasing potentials. Fast-growing biasing potential accelerates the sampling speed but decreases the accuracy of the free energy result. Slow-growing biasing potential gives an optimized result but needs more simulation time. In this article, we propose an alternative method. It adds the biasing potential to a representative point of the molecule in the collective variable space to improve the conformational sampling. And the free energy surface is calculated from the free energy gradient in the constrained simulation, not given by the negative of the biasing potential as previous methods. So the presented method does not require the biasing potential to remove all the barriers and basins on the free energy surface exactly. Practical applications show that the method in this work is able to produce the accurate free energy surfaces for different molecules in a short time period. The free energy errors are small in the cases of various biasing potentials. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Understanding the nature of errors in nursing: using a model to analyse critical incident reports of errors which had resulted in an adverse or potentially adverse event.

PubMed

Meurier, C E

2000-07-01

Human errors are common in clinical practice, but they are under-reported. As a result, very little is known of the types, antecedents and consequences of errors in nursing practice. This limits the potential to learn from errors and to make improvement in the quality and safety of nursing care. The aim of this study was to use an Organizational Accident Model to analyse critical incidents of errors in nursing. Twenty registered nurses were invited to produce a critical incident report of an error (which had led to an adverse event or potentially could have led to an adverse event) they had made in their professional practice and to write down their responses to the error using a structured format. Using Reason's Organizational Accident Model, supplemental information was then collected from five of the participants by means of an individual in-depth interview to explore further issues relating to the incidents they had reported. The detailed analysis of one of the incidents is discussed in this paper, demonstrating the effectiveness of this approach in providing insight into the chain of events which may lead to an adverse event. The case study approach using critical incidents of clinical errors was shown to provide relevant information regarding the interaction of organizational factors, local circumstances and active failures (errors) in producing an adverse or potentially adverse event. It is suggested that more use should be made of this approach to understand how errors are made in practice and to take appropriate preventative measures.

Procrustes-based geometric morphometrics on MRI images: An example of inter-operator bias in 3D landmarks and its impact on big datasets.

PubMed

Daboul, Amro; Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea

2018-01-01

Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'.

Procrustes-based geometric morphometrics on MRI images: An example of inter-operator bias in 3D landmarks and its impact on big datasets

PubMed Central

Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea

2018-01-01

Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'. PMID:29787586

Sample Size and Statistical Conclusions from Tests of Fit to the Rasch Model According to the Rasch Unidimensional Measurement Model (Rumm) Program in Health Outcome Measurement.

PubMed

Hagell, Peter; Westergren, Albert

Sample size is a major factor in statistical null hypothesis testing, which is the basis for many approaches to testing Rasch model fit. Few sample size recommendations for testing fit to the Rasch model concern the Rasch Unidimensional Measurement Models (RUMM) software, which features chi-square and ANOVA/F-ratio based fit statistics, including Bonferroni and algebraic sample size adjustments. This paper explores the occurrence of Type I errors with RUMM fit statistics, and the effects of algebraic sample size adjustments. Data with simulated Rasch model fitting 25-item dichotomous scales and sample sizes ranging from N = 50 to N = 2500 were analysed with and without algebraically adjusted sample sizes. Results suggest the occurrence of Type I errors with N less then or equal to 500, and that Bonferroni correction as well as downward algebraic sample size adjustment are useful to avoid such errors, whereas upward adjustment of smaller samples falsely signal misfit. Our observations suggest that sample sizes around N = 250 to N = 500 may provide a good balance for the statistical interpretation of the RUMM fit statistics studied here with respect to Type I errors and under the assumption of Rasch model fit within the examined frame of reference (i.e., about 25 item parameters well targeted to the sample).

Automated process for solvent separation of organic/inorganic substance

DOEpatents

Schweighardt, F.K.

1986-07-29

There is described an automated process for the solvent separation of organic/inorganic substances that operates continuously and unattended and eliminates potential errors resulting from subjectivity and the aging of the sample during analysis. In the process, metered amounts of one or more solvents are passed sequentially through a filter containing the sample under the direction of a microprocessor control apparatus. The mixture in the filter is agitated by ultrasonic cavitation for a timed period and the filtrate is collected. The filtrate of each solvent extraction is collected individually and the residue on the filter element is collected to complete the extraction process. 4 figs.

Automated process for solvent separation of organic/inorganic substance

DOEpatents

Schweighardt, Frank K.

1986-01-01

There is described an automated process for the solvent separation of organic/inorganic substances that operates continuously and unattended and eliminates potential errors resulting from subjectivity and the aging of the sample during analysis. In the process, metered amounts of one or more solvents are passed sequentially through a filter containing the sample under the direction of a microprocessor control apparatus. The mixture in the filter is agitated by ultrasonic cavitation for a timed period and the filtrate is collected. The filtrate of each solvent extraction is collected individually and the residue on the filter element is collected to complete the extraction process.

Automated apparatus for solvent separation of a coal liquefaction product stream

DOEpatents

Schweighardt, Frank K.

1985-01-01

An automated apparatus for the solvent separation of a coal liquefaction product stream that operates continuously and unattended and eliminates potential errors resulting from subjectivity and the aging of the sample during analysis. In use of the apparatus, metered amounts of one or more solvents are passed sequentially through a filter containing the sample under the direction of a microprocessor control means. The mixture in the filter is agitated by means of ultrasonic cavitation for a timed period and the filtrate is collected. The filtrate of each solvent extraction is collected individually and the residue on the filter element is collected to complete the extraction process.

Prediction of texture and colour of dry-cured ham by visible and near infrared spectroscopy using a fiber optic probe.

PubMed

García-Rey, R M; García-Olmo, J; De Pedro, E; Quiles-Zafra, R; Luque de Castro, M D

2005-06-01

The potential of visible and near infrared spectroscopy to predict texture and colour of dry-cured ham samples was investigated. Sensory evaluation was performed on 117 boned and cross-sectioned dry-cured ham samples. Slices of approximate thickness 4cm were cut, vacuum-packaged and kept under frozen storage until spectral analysis. Then, Biceps femoris muscle from the thawed slices was taken and scanned (400-2200nm) using a fiber optic probe. The exploratory analysis using principal component analysis shows that there are two ham groups according to the appearance or not of defects. Then, a K nearest neighbours was used to classify dry-cured hams into defective or no defective classes. The overall accuracy of the classification as a function of pastiness was 88.5%; meanwhile, according to colour was 79.7%. Partial least squares regression was used to formulate prediction equations for pastiness and colour. The correlation coefficients of calibration and cross-validation were 0.97 and 0.86 for optimal equation predicting pastiness, and 0.82 and 0.69 for optimal equation predicting colour. The standard error of cross-validation for predicting pastiness and colour is between 1 and 2 times the standard deviation of the reference method (the error involved in the sensory evaluation by the experts). The magnitude of this error demonstrates the good precision of the methods for predicting pastiness and colour. Furthermore, the samples were classified into defective or no defective classes, with a correct classification of 94.2% according to pasty texture evaluation and 75.7% as regard to colour evaluation.

Predicting forest insect flight activity: A Bayesian network approach

PubMed Central

Pawson, Stephen M.; Marcot, Bruce G.; Woodberry, Owen G.

2017-01-01

Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model’s predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways. PMID:28953904

A New Method for Estimation of Emissions and Sources of Measurements Error in the Silicon Refining Process

NASA Astrophysics Data System (ADS)

Næss, Mari k.; Kero, Ida; Tranell, Gabriella

2013-08-01

In the production of metallurgical grade silicon (MG-Si), fugitive emissions are a serious concern due to the health risks associated with the fumes formed in different parts of the production. The fumes are also a potential environmental hazard. Yet, the chemical composition of the fumes from most process steps in the silicon plant, such as oxidative refining ladle, remains unknown. This in turn constitutes a problem with respect to the correct assessment of the environmental impact and working conditions. A comprehensive industrial measurement campaign was performed at the Elkem Salten MG-Si production plant in Norway. Samples of the ingoing and outgoing mass flows were analyzed by high-resolution inductively coupled plasma mass spectrometry, with respect to 62 elements. In every step of the sampling and sample treatment processes, possible sources of error have been identified and quantified, including process variation, mass measurement accuracy, and contamination risk. Total measurement errors for all elements in all phases are established. The method is applied to estimate the order of magnitude of the elemental emissions via the fumes from the tapping and refining processes, with respect to production mass and year. The elements with higher concentrations in the fume than slag and refined silicon include Ag, Bi, Cd, Cu, In, K, Mg, Na, Pb, Rb, Se, Sn, Tl, and Zn: all being present in the ppm range. This work constitutes new and vital information to enable the correct assessment of the environmental impact and working conditions at an MG-Si plant.

Small Body GN and C Research Report: G-SAMPLE - An In-Flight Dynamical Method for Identifying Sample Mass [External Release Version

NASA Technical Reports Server (NTRS)

Carson, John M., III; Bayard, David S.

2006-01-01

G-SAMPLE is an in-flight dynamical method for use by sample collection missions to identify the presence and quantity of collected sample material. The G-SAMPLE method implements a maximum-likelihood estimator to identify the collected sample mass, based on onboard force sensor measurements, thruster firings, and a dynamics model of the spacecraft. With G-SAMPLE, sample mass identification becomes a computation rather than an extra hardware requirement; the added cost of cameras or other sensors for sample mass detection is avoided. Realistic simulation examples are provided for a spacecraft configuration with a sample collection device mounted on the end of an extended boom. In one representative example, a 1000 gram sample mass is estimated to within 110 grams (95% confidence) under realistic assumptions of thruster profile error, spacecraft parameter uncertainty, and sensor noise. For convenience to future mission design, an overall sample-mass estimation error budget is developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.

Elucidation of cross-species proteomic effects in human and hominin bone proteome identification through a bioinformatics experiment.

PubMed

Welker, F

2018-02-20

The study of ancient protein sequences is increasingly focused on the analysis of older samples, including those of ancient hominins. The analysis of such ancient proteomes thereby potentially suffers from "cross-species proteomic effects": the loss of peptide and protein identifications at increased evolutionary distances due to a larger number of protein sequence differences between the database sequence and the analyzed organism. Error-tolerant proteomic search algorithms should theoretically overcome this problem at both the peptide and protein level; however, this has not been demonstrated. If error-tolerant searches do not overcome the cross-species proteomic issue then there might be inherent biases in the identified proteomes. Here, a bioinformatics experiment is performed to test this using a set of modern human bone proteomes and three independent searches against sequence databases at increasing evolutionary distances: the human (0 Ma), chimpanzee (6-8 Ma) and orangutan (16-17 Ma) reference proteomes, respectively. Incorrectly suggested amino acid substitutions are absent when employing adequate filtering criteria for mutable Peptide Spectrum Matches (PSMs), but roughly half of the mutable PSMs were not recovered. As a result, peptide and protein identification rates are higher in error-tolerant mode compared to non-error-tolerant searches but did not recover protein identifications completely. Data indicates that peptide length and the number of mutations between the target and database sequences are the main factors influencing mutable PSM identification. The error-tolerant results suggest that the cross-species proteomics problem is not overcome at increasing evolutionary distances, even at the protein level. Peptide and protein loss has the potential to significantly impact divergence dating and proteome comparisons when using ancient samples as there is a bias towards the identification of conserved sequences and proteins. Effects are minimized between moderately divergent proteomes, as indicated by almost complete recovery of informative positions in the search against the chimpanzee proteome (≈90%, 6-8 Ma). This provides a bioinformatic background to future phylogenetic and proteomic analysis of ancient hominin proteomes, including the future description of novel hominin amino acid sequences, but also has negative implications for the study of fast-evolving proteins in hominins, non-hominin animals, and ancient bacterial proteins in evolutionary contexts.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications.

PubMed

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Accounting for Sampling Error When Inferring Population Synchrony from Time-Series Data: A Bayesian State-Space Modelling Approach with Applications

PubMed Central

Santin-Janin, Hugues; Hugueny, Bernard; Aubry, Philippe; Fouchet, David; Gimenez, Olivier; Pontier, Dominique

2014-01-01

Background Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. Methodology/Principal findings The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. Conclusion/Significance The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates. PMID:24489839

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

Determining Optimal Location and Numbers of Sample Transects for Characterization of UXO Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

BILISOLY, ROGER L.; MCKENNA, SEAN A.

2003-01-01

Previous work on sample design has been focused on constructing designs for samples taken at point locations. Significantly less work has been done on sample design for data collected along transects. A review of approaches to point and transect sampling design shows that transects can be considered as a sequential set of point samples. Any two sampling designs can be compared through using each one to predict the value of the quantity being measured on a fixed reference grid. The quality of a design is quantified in two ways: computing either the sum or the product of the eigenvalues ofmore » the variance matrix of the prediction error. An important aspect of this analysis is that the reduction of the mean prediction error variance (MPEV) can be calculated for any proposed sample design, including one with straight and/or meandering transects, prior to taking those samples. This reduction in variance can be used as a ''stopping rule'' to determine when enough transect sampling has been completed on the site. Two approaches for the optimization of the transect locations are presented. The first minimizes the sum of the eigenvalues of the predictive error, and the second minimizes the product of these eigenvalues. Simulated annealing is used to identify transect locations that meet either of these objectives. This algorithm is applied to a hypothetical site to determine the optimal locations of two iterations of meandering transects given a previously existing straight transect. The MPEV calculation is also used on both a hypothetical site and on data collected at the Isleta Pueblo to evaluate its potential as a stopping rule. Results show that three or four rounds of systematic sampling with straight parallel transects covering 30 percent or less of the site, can reduce the initial MPEV by as much as 90 percent. The amount of reduction in MPEV can be used as a stopping rule, but the relationship between MPEV and the results of excavation versus no-further-action decisions is site specific and cannot be calculated prior to the sampling. It may be advantageous to use the reduction in MPEV as a stopping rule for systematic sampling across the site that can then be followed by focused sampling in areas identified has having UXO during the systematic sampling. The techniques presented here provide answers to the questions of ''Where to sample?'' and ''When to stop?'' and are capable of running in near real time to support iterative site characterization campaigns.« less

Advanced diffraction-based overlay for double patterning

NASA Astrophysics Data System (ADS)

Li, Jie; Liu, Yongdong; Dasari, Prasad; Hu, Jiangtao; Smith, Nigel; Kritsun, Oleg; Volkman, Catherine

2010-03-01

Diffraction based overlay (DBO) technologies have been developed to address the tighter overlay control challenges as the dimensions of integrated circuit continue to shrink. Several studies published recently have demonstrated that the performance of DBO technologies has the potential to meet the overlay metrology budget for 22nm technology node. However, several hurdles must be cleared before DBO can be used in production. One of the major hurdles is that most DBO technologies require specially designed targets that consist of multiple measurement pads, which consume too much space and increase measurement time. A more advanced spectroscopic ellipsometry (SE) technology-Mueller Matrix SE (MM-SE) is developed to address the challenge. We use a double patterning sample to demonstrate the potential of MM-SE as a DBO candidate. Sample matrix (the matrix that describes the effects of the sample on the incident optical beam) obtained from MM-SE contains up to 16 elements. We show that the Mueller elements from the off-diagonal 2x2 blocks respond to overlay linearly and are zero when overlay errors are absent. This superior property enables empirical DBO (eDBO) using two pads per direction. Furthermore, the rich information in Mueller matrix and its direct response to overlay make it feasible to extract overlay errors from only one pad per direction using modeling approach (mDBO). We here present the Mueller overlay results using both eDBO and mDBO and compare the results with image-based overlay (IBO) and CD-SEM results. We also report the tool induced shifts (TIS) and dynamic repeatability.

A Reassessment of the Precision of Carbonate Clumped Isotope Measurements: Implications for Calibrations and Paleoclimate Reconstructions

NASA Astrophysics Data System (ADS)

Fernandez, Alvaro; Müller, Inigo A.; Rodríguez-Sanz, Laura; van Dijk, Joep; Looser, Nathan; Bernasconi, Stefano M.

2017-12-01

Carbonate clumped isotopes offer a potentially transformational tool to interpret Earth's history, but the proxy is still limited by poor interlaboratory reproducibility. Here, we focus on the uncertainties that result from the analysis of only a few replicate measurements to understand the extent to which unconstrained errors affect calibration relationships and paleoclimate reconstructions. We find that highly precise data can be routinely obtained with multiple replicate analyses, but this is not always done in many laboratories. For instance, using published estimates of external reproducibilities we find that typical clumped isotope measurements (three replicate analyses) have margins of error at the 95% confidence level (CL) that are too large for many applications. These errors, however, can be systematically reduced with more replicate measurements. Second, using a Monte Carlo-type simulation we demonstrate that the degree of disagreement on published calibration slopes is about what we should expect considering the precision of Δ47 data, the number of samples and replicate analyses, and the temperature range covered in published calibrations. Finally, we show that the way errors are typically reported in clumped isotope data can be problematic and lead to the impression that data are more precise than warranted. We recommend that uncertainties in Δ47 data should no longer be reported as the standard error of a few replicate measurements. Instead, uncertainties should be reported as margins of error at a specified confidence level (e.g., 68% or 95% CL). These error bars are a more realistic indication of the reliability of a measurement.

Evaluation and optimization of sampling errors for the Monte Carlo Independent Column Approximation

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Barker, W. Howard

2004-07-01

The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average broadband radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. McICA's sampling errors are evaluated here using a global climate model (GCM) dataset and a correlated-k distribution (CKD) radiation scheme. Two approaches to reduce McICA's sampling variance are discussed. The first is to simply restrict all of McICA's samples to cloudy regions. This avoids wasting precious few samples on essentially homogeneous clear skies. Clear-sky fluxes need to be computed separately for this approach, but this is usually done in GCMs for diagnostic purposes anyway. Second, accuracy can be improved by repeated sampling, and averaging those CKD terms with large cloud radiative effects. Although this naturally increases computational costs over the standard CKD model, random errors for fluxes and heating rates are reduced by typically 50% to 60%, for the present radiation code, when the total number of samples is increased by 50%. When both variance reduction techniques are applied simultaneously, globally averaged flux and heating rate random errors are reduced by a factor of #3.

Missense mutations of MLH1 and MSH2 genes detected in patients with gastrointestinal cancer are associated with exonic splicing enhancers and silencers

PubMed Central

ZHU, MING; CHEN, HUI-MEI; WANG, YA-PING

2013-01-01

The MLH1 and MSH2 genes in DNA mismatch repair are important in the pathogenesis of gastrointestinal cancer. Recent studies of normal and alternative splicing suggest that the deleterious effects of missense mutations may in fact be splicing-related when they are located in exonic splicing enhancers (ESEs) or exonic splicing silencers (ESSs). In this study, we used ESE-finder and FAS-ESS software to analyze the potential ESE/ESS motifs of the 114 missense mutations detected in the two genes in East Asian gastrointestinal cancer patients. In addition, we used the SIFT tool to functionally analyze these mutations. The amount of the ESE losses (68) was 51.1% higher than the ESE gains (45) of all the mutations. However, the amount of the ESS gains (27) was 107.7% higher than the ESS losses (13). In total, 56 (49.1%) mutations possessed a potential exonic splicing regulator (ESR) error. Eighty-one mutations (71.1%) were predicted to be deleterious with a lower tolerance index as detected by the Sorting Intolerant from Tolerant (SIFT) tool. Among these, 38 (33.3%) mutations were predicted to be functionally deleterious and possess one potential ESR error, while 18 (15.8%) mutations were predicted to be functionally deleterious and exhibit two potential ESR errors. These may be more likely to affect exon splicing. Our results indicated that there is a strong correlation between missense mutations in MLH1 and MSH2 genes detected in East Asian gastrointestinal cancer patients and ESR motifs. In order to correctly understand the molecular nature of mutations, splicing patterns should be compared between wild-type and mutant samples. PMID:23760103

A design of experiments approach to validation sampling for logistic regression modeling with error-prone medical records.

PubMed

Ouyang, Liwen; Apley, Daniel W; Mehrotra, Sanjay

2016-04-01

Electronic medical record (EMR) databases offer significant potential for developing clinical hypotheses and identifying disease risk associations by fitting statistical models that capture the relationship between a binary response variable and a set of predictor variables that represent clinical, phenotypical, and demographic data for the patient. However, EMR response data may be error prone for a variety of reasons. Performing a manual chart review to validate data accuracy is time consuming, which limits the number of chart reviews in a large database. The authors' objective is to develop a new design-of-experiments-based systematic chart validation and review (DSCVR) approach that is more powerful than the random validation sampling used in existing approaches. The DSCVR approach judiciously and efficiently selects the cases to validate (i.e., validate whether the response values are correct for those cases) for maximum information content, based only on their predictor variable values. The final predictive model will be fit using only the validation sample, ignoring the remainder of the unvalidated and unreliable error-prone data. A Fisher information based D-optimality criterion is used, and an algorithm for optimizing it is developed. The authors' method is tested in a simulation comparison that is based on a sudden cardiac arrest case study with 23 041 patients' records. This DSCVR approach, using the Fisher information based D-optimality criterion, results in a fitted model with much better predictive performance, as measured by the receiver operating characteristic curve and the accuracy in predicting whether a patient will experience the event, than a model fitted using a random validation sample. The simulation comparisons demonstrate that this DSCVR approach can produce predictive models that are significantly better than those produced from random validation sampling, especially when the event rate is low. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197: 2013 Accuracy Criteria, Consensus and Surveillance Error Grid Analyses, and Insulin Dosing Error Modeling in a Hospital Setting.

PubMed

Bedini, José Luis; Wallace, Jane F; Pardo, Scott; Petruschke, Thorsten

2015-10-07

Blood glucose monitoring is an essential component of diabetes management. Inaccurate blood glucose measurements can severely impact patients' health. This study evaluated the performance of 3 blood glucose monitoring systems (BGMS), Contour® Next USB, FreeStyle InsuLinx®, and OneTouch® Verio™ IQ, under routine hospital conditions. Venous blood samples (N = 236) obtained for routine laboratory procedures were collected at a Spanish hospital, and blood glucose (BG) concentrations were measured with each BGMS and with the available reference (hexokinase) method. Accuracy of the 3 BGMS was compared according to ISO 15197:2013 accuracy limit criteria, by mean absolute relative difference (MARD), consensus error grid (CEG) and surveillance error grid (SEG) analyses, and an insulin dosing error model. All BGMS met the accuracy limit criteria defined by ISO 15197:2013. While all measurements of the 3 BGMS were within low-risk zones in both error grid analyses, the Contour Next USB showed significantly smaller MARDs between reference values compared to the other 2 BGMS. Insulin dosing errors were lowest for the Contour Next USB than compared to the other systems. All BGMS fulfilled ISO 15197:2013 accuracy limit criteria and CEG criterion. However, taking together all analyses, differences in performance of potential clinical relevance may be observed. Results showed that Contour Next USB had lowest MARD values across the tested glucose range, as compared with the 2 other BGMS. CEG and SEG analyses as well as calculation of the hypothetical bolus insulin dosing error suggest a high accuracy of the Contour Next USB. © 2015 Diabetes Technology Society.

Risk management: correct patient and specimen identification in a surgical pathology laboratory. The experience of Infermi Hospital, Rimini, Italy.

PubMed

Fabbretti, G

2010-06-01

Because of its complex nature, surgical pathology practice is prone to error. In this report, we describe our methods for reducing error as much as possible during the pre-analytical and analytical phases. This was achieved by revising procedures, and by using computer technology and automation. Most mistakes are the result of human error in the identification and matching of patient and samples. To avoid faulty data interpretation, we employed a new comprehensive computer system that acquires all patient ID information directly from the hospital's database with a remote order entry; it also provides label and request forms via-Web where clinical information is required before sending the sample. Both patient and sample are identified directly and immediately at the site where the surgical procedures are performed. Barcode technology is used to input information at every step and automation is used for sample blocks and slides to avoid errors that occur when information is recorded or transferred by hand. Quality control checks occur at every step of the process to ensure that none of the steps are left to chance and that no phase is dependent on a single operator. The system also provides statistical analysis of errors so that new strategies can be implemented to avoid repetition. In addition, the staff receives frequent training on avoiding errors and new developments. The results have been shown promising results with a very low error rate (0.27%). None of these compromised patient health and all errors were detected before the release of the diagnosis report.

How allele frequency and study design affect association test statistics with misrepresentation errors.

PubMed

Escott-Price, Valentina; Ghodsi, Mansoureh; Schmidt, Karl Michael

2014-04-01

We evaluate the effect of genotyping errors on the type-I error of a general association test based on genotypes, showing that, in the presence of errors in the case and control samples, the test statistic asymptotically follows a scaled non-central $\\chi ^2$ distribution. We give explicit formulae for the scaling factor and non-centrality parameter for the symmetric allele-based genotyping error model and for additive and recessive disease models. They show how genotyping errors can lead to a significantly higher false-positive rate, growing with sample size, compared with the nominal significance levels. The strength of this effect depends very strongly on the population distribution of the genotype, with a pronounced effect in the case of rare alleles, and a great robustness against error in the case of large minor allele frequency. We also show how these results can be used to correct $p$-values.

The effect of covariate mean differences on the standard error and confidence interval for the comparison of treatment means.

PubMed

Liu, Xiaofeng Steven

2011-05-01

The use of covariates is commonly believed to reduce the unexplained error variance and the standard error for the comparison of treatment means, but the reduction in the standard error is neither guaranteed nor uniform over different sample sizes. The covariate mean differences between the treatment conditions can inflate the standard error of the covariate-adjusted mean difference and can actually produce a larger standard error for the adjusted mean difference than that for the unadjusted mean difference. When the covariate observations are conceived of as randomly varying from one study to another, the covariate mean differences can be related to a Hotelling's T(2) . Using this Hotelling's T(2) statistic, one can always find a minimum sample size to achieve a high probability of reducing the standard error and confidence interval width for the adjusted mean difference. ©2010 The British Psychological Society.

Sampling for pharmaceuticals and personal care products (PPCPs) and illicit drugs in wastewater systems: are your conclusions valid? A critical review.

PubMed

Ort, Christoph; Lawrence, Michael G; Rieckermann, Jörg; Joss, Adriano

2010-08-15

The analysis of 87 peer-reviewed journal articles reveals that sampling for pharmaceuticals and personal care products (PPCPs) and illicit drugs in sewers and sewage treatment plant influents is mostly carried out according to existing tradition or standard laboratory protocols. Less than 5% of all studies explicitly consider internationally acknowledged guidelines or methods for the experimental design of monitoring campaigns. In the absence of a proper analysis of the system under investigation, the importance of short-term pollutant variations was typically not addressed. Therefore, due to relatively long sampling intervals, potentially inadequate sampling modes, or insufficient documentation, it remains unclear for the majority of reviewed studies whether observed variations can be attributed to "real" variations or if they simply reflect sampling artifacts. Based on results from previous and current work, the present paper demonstrates that sampling errors can lead to overinterpretation of measured data and ultimately, wrong conclusions. Depending on catchment size, sewer type, sampling setup, substance of interest, and accuracy of analytical method, avoidable sampling artifacts can range from "not significant" to "100% or more" for different compounds even within the same study. However, in most situations sampling errors can be reduced greatly, and sampling biases can be eliminated completely, by choosing an appropriate sampling mode and frequency. This is crucial, because proper sampling will help to maximize the value of measured data for the experimental assessment of the fate of PPCPs as well as for the formulation and validation of mathematical models. The trend from reporting presence or absence of a compound in "clean" water samples toward the quantification of PPCPs in raw wastewater requires not only sophisticated analytical methods but also adapted sampling methods. With increasing accuracy of chemical analyses, inappropriate sampling increasingly represents the major source of inaccuracy. A condensed step-by-step Sampling Guide is proposed as a starting point for future studies.

Asymmetric affective forecasting errors and their correlation with subjective well-being

PubMed Central

2018-01-01

Aims Social scientists have postulated that the discrepancy between achievements and expectations affects individuals' subjective well-being. Still, little has been done to qualify and quantify such a psychological effect. Our empirical analysis assesses the consequences of positive and negative affective forecasting errors—the difference between realized and expected subjective well-being—on the subsequent level of subjective well-being. Data We use longitudinal data on a representative sample of 13,431 individuals from the German Socio-Economic Panel. In our sample, 52% of individuals are females, average age is 43 years, average years of education is 11.4 and 27% of our sample lives in East Germany. Subjective well-being (measured by self-reported life satisfaction) is assessed on a 0–10 discrete scale and its sample average is equal to 6.75 points. Methods We develop a simple theoretical framework to assess the consequences of positive and negative affective forecasting errors—the difference between realized and expected subjective well-being—on the subsequent level of subjective well-being, properly accounting for the endogenous adjustment of expectations to positive and negative affective forecasting errors, and use it to derive testable predictions. Given the theoretical framework, we estimate two panel-data equations, the first depicting the association between positive and negative affective forecasting errors and the successive level of subjective well-being and the second describing the correlation between subjective well-being expectations for the future and hedonic failures and successes. Our models control for individual fixed effects and a large battery of time-varying demographic characteristics, health and socio-economic status. Results and conclusions While surpassing expectations is uncorrelated with subjective well-being, failing to match expectations is negatively associated with subsequent realizations of subjective well-being. Expectations are positively (negatively) correlated to positive (negative) forecasting errors. We speculate that in the first case the positive adjustment in expectations is strong enough to cancel out the potential positive effects on subjective well-being of beaten expectations, while in the second case it is not, and individuals persistently bear the negative emotional consequences of not achieving expectations. PMID:29513685

Dating young geomorphic surfaces using age of colonizing Douglas fir in southwestern Washington and northwestern Oregon, USA

USGS Publications Warehouse

Pierson, T.C.

2007-01-01

Dating of dynamic, young (<500 years) geomorphic landforms, particularly volcanofluvial features, requires higher precision than is possible with radiocarbon dating. Minimum ages of recently created landforms have long been obtained from tree-ring ages of the oldest trees growing on new surfaces. But to estimate the year of landform creation requires that two time corrections be added to tree ages obtained from increment cores: (1) the time interval between stabilization of the new landform surface and germination of the sampled trees (germination lag time or GLT); and (2) the interval between seedling germination and growth to sampling height, if the trees are not cored at ground level. The sum of these two time intervals is the colonization time gap (CTG). Such time corrections have been needed for more precise dating of terraces and floodplains in lowland river valleys in the Cascade Range, where significant eruption-induced lateral shifting and vertical aggradation of channels can occur over years to decades, and where timing of such geomorphic changes can be critical to emergency planning. Earliest colonizing Douglas fir (Pseudotsuga menziesii) were sampled for tree-ring dating at eight sites on lowland (<750 m a.s.l.), recently formed surfaces of known age near three Cascade volcanoes - Mount Rainier, Mount St. Helens and Mount Hood - in southwestern Washington and northwestern Oregon. Increment cores or stem sections were taken at breast height and, where possible, at ground level from the largest, oldest-looking trees at each study site. At least ten trees were sampled at each site unless the total of early colonizers was less. Results indicate that a correction of four years should be used for GLT and 10 years for CTG if the single largest (and presumed oldest) Douglas fir growing on a surface of unknown age is sampled. This approach would have a potential error of up to 20 years. Error can be reduced by sampling the five largest Douglas fir instead of the single largest. A GLT correction of 5 years should be added to the mean ring-count age of the five largest trees growing on the surface being dated, if the trees are cored at ground level. This correction would have an approximate error of ??5 years. If the trees are cored at about 1.4 m above the round surface (breast height), a CTG correction of 11 years should be added to the mean age of the five sampled trees (with an error of about ??7 years).

Structured methods for identifying and correcting potential human errors in aviation operations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, W.R.

1997-10-01

Human errors have been identified as the source of approximately 60% of the incidents and accidents that occur in commercial aviation. It can be assumed that a very large number of human errors occur in aviation operations, even though in most cases the redundancies and diversities built into the design of aircraft systems prevent the errors from leading to serious consequences. In addition, when it is acknowledged that many system failures have their roots in human errors that occur in the design phase, it becomes apparent that the identification and elimination of potential human errors could significantly decrease the risksmore » of aviation operations. This will become even more critical during the design of advanced automation-based aircraft systems as well as next-generation systems for air traffic management. Structured methods to identify and correct potential human errors in aviation operations have been developed and are currently undergoing testing at the Idaho National Engineering and Environmental Laboratory (INEEL).« less

Physical layer one-time-pad data encryption through synchronized semiconductor laser networks

NASA Astrophysics Data System (ADS)

Argyris, Apostolos; Pikasis, Evangelos; Syvridis, Dimitris

2016-02-01

Semiconductor lasers (SL) have been proven to be a key device in the generation of ultrafast true random bit streams. Their potential to emit chaotic signals under conditions with desirable statistics, establish them as a low cost solution to cover various needs, from large volume key generation to real-time encrypted communications. Usually, only undemanding post-processing is needed to convert the acquired analog timeseries to digital sequences that pass all established tests of randomness. A novel architecture that can generate and exploit these true random sequences is through a fiber network in which the nodes are semiconductor lasers that are coupled and synchronized to central hub laser. In this work we show experimentally that laser nodes in such a star network topology can synchronize with each other through complex broadband signals that are the seed to true random bit sequences (TRBS) generated at several Gb/s. The potential for each node to access real-time generated and synchronized with the rest of the nodes random bit streams, through the fiber optic network, allows to implement an one-time-pad encryption protocol that mixes the synchronized true random bit sequence with real data at Gb/s rates. Forward-error correction methods are used to reduce the errors in the TRBS and the final error rate at the data decoding level. An appropriate selection in the sampling methodology and properties, as well as in the physical properties of the chaotic seed signal through which network locks in synchronization, allows an error free performance.

Follow-up of negative MRI-targeted prostate biopsies: when are we missing cancer?

PubMed

Gold, Samuel A; Hale, Graham R; Bloom, Jonathan B; Smith, Clayton P; Rayn, Kareem N; Valera, Vladimir; Wood, Bradford J; Choyke, Peter L; Turkbey, Baris; Pinto, Peter A

2018-05-21

Multiparametric magnetic resonance imaging (mpMRI) has improved clinicians' ability to detect clinically significant prostate cancer (csPCa). Combining or fusing these images with the real-time imaging of transrectal ultrasound (TRUS) allows urologists to better sample lesions with a targeted biopsy (Tbx) leading to the detection of greater rates of csPCa and decreased rates of low-risk PCa. In this review, we evaluate the technical aspects of the mpMRI-guided Tbx procedure to identify possible sources of error and provide clinical context to a negative Tbx. A literature search was conducted of possible reasons for false-negative TBx. This includes discussion on false-positive mpMRI findings, termed "PCa mimics," that may incorrectly suggest high likelihood of csPCa as well as errors during Tbx resulting in inexact image fusion or biopsy needle placement. Despite the strong negative predictive value associated with Tbx, concerns of missed disease often remain, especially with MR-visible lesions. This raises questions about what to do next after a negative Tbx result. Potential sources of error can arise from each step in the targeted biopsy process ranging from "PCa mimics" or technical errors during mpMRI acquisition to failure to properly register MRI and TRUS images on a fusion biopsy platform to technical or anatomic limits on needle placement accuracy. A better understanding of these potential pitfalls in the mpMRI-guided Tbx procedure will aid interpretation of a negative Tbx, identify areas for improving technical proficiency, and improve both physician understanding of negative Tbx and patient-management options.

Architecture-Led Safety Analysis of the Joint Multi-Role (JMR) Joint Common Architecture (JCA) Demonstration System

DTIC Science & Technology

2015-12-01

relevant system components (i.e., their component type declarations) have been anno - tated with EMV2 error source or propagation declarations and hazard...contributors. They are recorded as EMV2 anno - tations for each of the ASSA. Figure 40 shows a sampling of potential hazard contributors by the functional...2012] Leveson, N., Engineering a Safer World. MIT Press. 2012. [Parnas 1991] Parnas, D. & Madey, J . Functional Documentation for Computer Systems

Development and evaluation of an up-converting phosphor technology-based lateral flow assay for rapid detection of Francisella tularensis.

PubMed

Hua, Fei; Zhang, Pingping; Zhang, Fuli; Zhao, Yong; Li, Chunfeng; Sun, Chongyun; Wang, Xiaochen; Yang, Ruifu; Wang, Chengbin; Yu, Ailian; Zhou, Lei

2015-11-26

Francisella tularensis is a potential biowarfare/bioterrorism agent and zoonotic pathogen that causes tularemia; thus, surveillance of F. tularensis and first-level emergency response using point-of-care testing (POCT) are essential. The UPT-LF POCT assay was established to quantitatively detect F. tularensis within 15 min, and the sensitivity of the assay was 10(4) CFU · mL(-1) (100 CFU/test). The linear quantitative range covered five orders of magnitude, and the coefficients of variation were less than 10%. Except Shigella dysenteriae, UPT-LF showed excellent specificity to four strains that are also potential biowarfare/bioterrorism agents and 13 food-borne pathogenic strains. Samples with pH 2-13, high ion strengths (≥ 2 mol · L(-1) solution of KCl and NaCl), high viscosities (≤ 50 mg · mL(-1) PEG20000 or ≥ 20% glycerol), and high concentrations of biomacromolecules (≥ 400 mg · mL(-1) bovine serum albumin or ≥ 80 mg · mL(-1) casein) showed little influence on the assay. For practical utilization, the tolerance limits for seven powders and eight viscera were determined, and operation errors of liquid measurement demonstrated a minor influence on the strip. Ftu-UPT-LF is a candidate POCT method because of its excellent sensitivity, specificity, and stability in complex samples, as well as low operation error.

Sampling Versus Filtering in Large-Eddy Simulations

NASA Technical Reports Server (NTRS)

Debliquy, O.; Knaepen, B.; Carati, D.; Wray, A. A.

2004-01-01

A LES formalism in which the filter operator is replaced by a sampling operator is proposed. The unknown quantities that appear in the LES equations originate only from inadequate resolution (Discretization errors). The resulting viewpoint seems to make a link between finite difference approaches and finite element methods. Sampling operators are shown to commute with nonlinearities and to be purely projective. Moreover, their use allows an unambiguous definition of the LES numerical grid. The price to pay is that sampling never commutes with spatial derivatives and the commutation errors must be modeled. It is shown that models for the discretization errors may be treated using the dynamic procedure. Preliminary results, using the Smagorinsky model, are very encouraging.

Error-related negativities elicited by monetary loss and cues that predict loss.

PubMed

Dunning, Jonathan P; Hajcak, Greg

2007-11-19

Event-related potential studies have reported error-related negativity following both error commission and feedback indicating errors or monetary loss. The present study examined whether error-related negativities could be elicited by a predictive cue presented prior to both the decision and subsequent feedback in a gambling task. Participants were presented with a cue that indicated the probability of reward on the upcoming trial (0, 50, and 100%). Results showed a negative deflection in the event-related potential in response to loss cues compared with win cues; this waveform shared a similar latency and morphology with the traditional feedback error-related negativity.

Medication Administration Errors in an Adult Emergency Department of a Tertiary Health Care Facility in Ghana.

PubMed

Acheampong, Franklin; Tetteh, Ashalley Raymond; Anto, Berko Panyin

2016-12-01

This study determined the incidence, types, clinical significance, and potential causes of medication administration errors (MAEs) at the emergency department (ED) of a tertiary health care facility in Ghana. This study used a cross-sectional nonparticipant observational technique. Study participants (nurses) were observed preparing and administering medication at the ED of a 2000-bed tertiary care hospital in Accra, Ghana. The observations were then compared with patients' medication charts, and identified errors were clarified with staff for possible causes. Of the 1332 observations made, involving 338 patients and 49 nurses, 362 had errors, representing 27.2%. However, the error rate excluding "lack of drug availability" fell to 12.8%. Without wrong time error, the error rate was 22.8%. The 2 most frequent error types were omission (n = 281, 77.6%) and wrong time (n = 58, 16%) errors. Omission error was mainly due to unavailability of medicine, 48.9% (n = 177). Although only one of the errors was potentially fatal, 26.7% were definitely clinically severe. The common themes that dominated the probable causes of MAEs were unavailability, staff factors, patient factors, prescription, and communication problems. This study gives credence to similar studies in different settings that MAEs occur frequently in the ED of hospitals. Most of the errors identified were not potentially fatal; however, preventive strategies need to be used to make life-saving processes such as drug administration in such specialized units error-free.

Robotic liquid handling and automation in epigenetics.

PubMed

Gaisford, Wendy

2012-10-01

Automated liquid-handling robots and high-throughput screening (HTS) are widely used in the pharmaceutical industry for the screening of large compound libraries, small molecules for activity against disease-relevant target pathways, or proteins. HTS robots capable of low-volume dispensing reduce assay setup times and provide highly accurate and reproducible dispensing, minimizing variation between sample replicates and eliminating the potential for manual error. Low-volume automated nanoliter dispensers ensure accuracy of pipetting within volume ranges that are difficult to achieve manually. In addition, they have the ability to potentially expand the range of screening conditions from often limited amounts of valuable sample, as well as reduce the usage of expensive reagents. The ability to accurately dispense lower volumes provides the potential to achieve a greater amount of information than could be otherwise achieved using manual dispensing technology. With the emergence of the field of epigenetics, an increasing number of drug discovery companies are beginning to screen compound libraries against a range of epigenetic targets. This review discusses the potential for the use of low-volume liquid handling robots, for molecular biological applications such as quantitative PCR and epigenetics.

A framework for a critical assessment of the quality of epidemiological studies of driver health and accident risk.

PubMed

Elvik, Rune

2011-11-01

A large number of studies have tried to assess how various aspects of driver health influence driver involvement in accidents. The objective of this paper is to provide a framework for a critical assessment of the quality these studies from a methodological point of view. Examples are given of how various sources of bias and confounding can produce study findings that are highly misleading. Ten potential sources of error and bias in epidemiological studies of the contribution of driver health impairments to road accidents are discussed: (1) Poor description of the medical conditions whose effects are studied (measurement error). (2) Inadequate control for the effects of exposure on accident rate. (3) Sampling endogeneity with respect to assessment for fitness to drive (outcome-based sampling; self-selection bias). (4) Combined exposure to several risk factors. (5) Poor control for potentially confounding factors. (6) Failure to specify potentially moderating factors (interaction effects). (7) Failure to consider a severity gradient with respect to the effect of health impairments. (8) Failure to specify the compliance of drivers with medical treatments or treatment effectiveness. (9) No data on the population prevalence of various health conditions. (10) The use of multiple study approaches and methods making the comparison and synthesis of findings difficult. Examples are given of how all these items may influence the findings of a single study or make synthesising findings from multiple studies difficult. A checklist for assessing study quality is provided. Copyright © 2011 Elsevier Ltd. All rights reserved.

Large Sample Confidence Limits for Goodman and Kruskal's Proportional Prediction Measure TAU-b

ERIC Educational Resources Information Center

Berry, Kenneth J.; Mielke, Paul W.

1976-01-01

A Fortran Extended program which computes Goodman and Kruskal's Tau-b, its asymmetrical counterpart, Tau-a, and three sets of confidence limits for each coefficient under full multinomial and proportional stratified sampling is presented. A correction of an error in the calculation of the large sample standard error of Tau-b is discussed.…

On Two-Stage Multiple Comparison Procedures When There Are Unequal Sample Sizes in the First Stage.

ERIC Educational Resources Information Center

Wilcox, Rand R.

1984-01-01

Two stage multiple-comparison procedures give an exact solution to problems of power and Type I errors, but require equal sample sizes in the first stage. This paper suggests a method of evaluating the experimentwise Type I error probability when the first stage has unequal sample sizes. (Author/BW)

Techniques for Down-Sampling a Measured Surface Height Map for Model Validation

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2012-01-01

This software allows one to down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. The software tool of the current two new techniques can be used in all optical model validation processes involving large space optical surfaces

Distribution of the two-sample t-test statistic following blinded sample size re-estimation.

PubMed

Lu, Kaifeng

2016-05-01

We consider the blinded sample size re-estimation based on the simple one-sample variance estimator at an interim analysis. We characterize the exact distribution of the standard two-sample t-test statistic at the final analysis. We describe a simulation algorithm for the evaluation of the probability of rejecting the null hypothesis at given treatment effect. We compare the blinded sample size re-estimation method with two unblinded methods with respect to the empirical type I error, the empirical power, and the empirical distribution of the standard deviation estimator and final sample size. We characterize the type I error inflation across the range of standardized non-inferiority margin for non-inferiority trials, and derive the adjusted significance level to ensure type I error control for given sample size of the internal pilot study. We show that the adjusted significance level increases as the sample size of the internal pilot study increases. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Field evaluation of the error arising from inadequate time averaging in the standard use of depth-integrating suspended-sediment samplers

USGS Publications Warehouse

Topping, David J.; Rubin, David M.; Wright, Scott A.; Melis, Theodore S.

2011-01-01

Several common methods for measuring suspended-sediment concentration in rivers in the United States use depth-integrating samplers to collect a velocity-weighted suspended-sediment sample in a subsample of a river cross section. Because depth-integrating samplers are always moving through the water column as they collect a sample, and can collect only a limited volume of water and suspended sediment, they collect only minimally time-averaged data. Four sources of error exist in the field use of these samplers: (1) bed contamination, (2) pressure-driven inrush, (3) inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration, and (4) inadequate time averaging. The first two of these errors arise from misuse of suspended-sediment samplers, and the third has been the subject of previous study using data collected in the sand-bedded Middle Loup River in Nebraska. Of these four sources of error, the least understood source of error arises from the fact that depth-integrating samplers collect only minimally time-averaged data. To evaluate this fourth source of error, we collected suspended-sediment data between 1995 and 2007 at four sites on the Colorado River in Utah and Arizona, using a P-61 suspended-sediment sampler deployed in both point- and one-way depth-integrating modes, and D-96-A1 and D-77 bag-type depth-integrating suspended-sediment samplers. These data indicate that the minimal duration of time averaging during standard field operation of depth-integrating samplers leads to an error that is comparable in magnitude to that arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration. This random error arising from inadequate time averaging is positively correlated with grain size and does not largely depend on flow conditions or, for a given size class of suspended sediment, on elevation above the bed. Averaging over time scales >1 minute is the likely minimum duration required to result in substantial decreases in this error. During standard two-way depth integration, a depth-integrating suspended-sediment sampler collects a sample of the water-sediment mixture during two transits at each vertical in a cross section: one transit while moving from the water surface to the bed, and another transit while moving from the bed to the water surface. As the number of transits is doubled at an individual vertical, this error is reduced by ~30 percent in each size class of suspended sediment. For a given size class of suspended sediment, the error arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration depends only on the number of verticals collected, whereas the error arising from inadequate time averaging depends on both the number of verticals collected and the number of transits collected at each vertical. Summing these two errors in quadrature yields a total uncertainty in an equal-discharge-increment (EDI) or equal-width-increment (EWI) measurement of the time-averaged velocity-weighted suspended-sediment concentration in a river cross section (exclusive of any laboratory-processing errors). By virtue of how the number of verticals and transits influences the two individual errors within this total uncertainty, the error arising from inadequate time averaging slightly dominates that arising from inadequate sampling of the cross-stream spatial structure in suspended-sediment concentration. Adding verticals to an EDI or EWI measurement is slightly more effective in reducing the total uncertainty than adding transits only at each vertical, because a new vertical contributes both temporal and spatial information. However, because collection of depth-integrated samples at more transits at each vertical is generally easier and faster than at more verticals, addition of a combination of verticals and transits is likely a more practical approach to reducing the total uncertainty in most field situatio

Two-sample binary phase 2 trials with low type I error and low sample size

PubMed Central

Litwin, Samuel; Basickes, Stanley; Ross, Eric A.

2017-01-01

Summary We address design of two-stage clinical trials comparing experimental and control patients. Our end-point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p0 and alternative that it is p0 among controls and p1 > p0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E ≥ m, with two-sample rules of the form E – C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. PMID:28118686

[Exploration of the concept of genetic drift in genetics teaching of undergraduates].

PubMed

Wang, Chun-ming

2016-01-01

Genetic drift is one of the difficulties in teaching genetics due to its randomness and probability which could easily cause conceptual misunderstanding. The “sampling error" in its definition is often misunderstood because of the research method of “sampling", which disturbs the results and causes the random changes in allele frequency. I analyzed and compared the definitions of genetic drift in domestic and international genetic textbooks, and found that the definitions containing “sampling error" are widely adopted but are interpreted correctly in only a few textbooks. Here, the history of research on genetic drift, i.e., the contributions of Wright, Fisher and Kimura, is introduced. Moreover, I particularly describe two representative articles recently published about genetic drift teaching of undergraduates, which point out that misconceptions are inevitable for undergraduates during the studying process and also provide a preliminary solution. Combined with my own teaching practice, I suggest that the definition of genetic drift containing “sampling error" can be adopted with further interpretation, i.e., “sampling error" is random sampling among gametes when generating the next generation of alleles which is equivalent to a random sampling of all gametes participating in mating in gamete pool and has no relationship with artificial sampling in general genetics studies. This article may provide some help in genetics teaching.

Thermal properties of nonstoichiometry uranium dioxide

NASA Astrophysics Data System (ADS)

Kavazauri, R.; Pokrovskiy, S. A.; Baranov, V. G.; Tenishev, A. V.

2016-04-01

In this paper, was developed a method of oxidation pure uranium dioxide to a predetermined deviation from the stoichiometry. Oxidation was carried out using the thermogravimetric method on NETZSCH STA 409 CD with a solid electrolyte galvanic cell for controlling the oxygen potential of the environment. 4 samples uranium oxide were obtained with a different ratio of oxygen-to-metal: O / U = 2.002, O / U = 2.005, O / U = 2.015, O / U = 2.033. For the obtained samples were determined basic thermal characteristics of the heat capacity, thermal diffusivity, thermal conductivity. The error of heat capacity determination is equal to 5%. Thermal diffusivity and thermal conductivity of the samples decreased with increasing deviation from stoichiometry. For the sample with O / M = 2.033, difference of both values with those of stoichiometric uranium dioxide is close to 50%.

Novel measuring strategies in neutron interferometry

NASA Astrophysics Data System (ADS)

Bonse, Ulrich; Wroblewski, Thomas

1985-04-01

Angular misalignment of a sample in a single crystal neutron interferometer leads to systematic errors of the effective sample thickness and in this way to errors in the determination of the coherent scattering length. The misalignment can be determined and the errors can be corrected by a second measurement at a different angular sample position. Furthermore, a method has been developed which allows supervision of the wavelength during the measurements. These two techniques were tested by determining the scattering length of copper. A value of bc = 7.66(4) fm was obtained which is in excellent agreement with previous measurements.

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.

PubMed

Lin, Johnny; Bentler, Peter M

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.

Development of a Direct Spectrophotometric and Chemometric Method for Determining Food Dye Concentrations.

PubMed

Arroz, Erin; Jordan, Michael; Dumancas, Gerard G

2017-07-01

An ultraviolet visible (UV-Vis) spectrophotometric and partial least squares (PLS) chemometric method was developed for the simultaneous determination of erythrosine B (red), Brilliant Blue, and tartrazine (yellow) dyes. A training set (n = 64) was generated using a full factorial design and its accuracy was tested in a test set (n = 13) using a Box-Behnken design. The test set garnered a root mean square error (RMSE) of 1.79 × 10 -7 for blue, 4.59 × 10 -7 for red, and 1.13 × 10 -6 for yellow dyes. The relatively small RMSE suggests only a small difference between predicted versus measured concentrations, demonstrating the accuracy of our model. The relative error of prediction (REP) for the test set were 11.73%, 19.52%, 19.38%, for blue, red, and yellow dyes, respectively. A comparable overlay between the actual candy samples and their replicated synthetic spectra were also obtained indicating the model as a potentially accurate method for determining concentrations of dyes in food samples.

A rapid method for detection of fumonisins B1 and B2 in corn meal using Fourier transform near infrared (FT-NIR) spectroscopy implemented with integrating sphere.

PubMed

Gaspardo, B; Del Zotto, S; Torelli, E; Cividino, S R; Firrao, G; Della Riccia, G; Stefanon, B

2012-12-01

Fourier transform near infrared (FT-NIR) spectroscopy is an analytical procedure generally used to detect organic compounds in food. In this work the ability to predict fumonisin B(1)+B(2) contents in corn meal using an FT-NIR spectrophotometer, equipped with an integration sphere, was assessed. A total of 143 corn meal samples were collected in Friuli Venezia Giulia Region (Italy) and used to define a 15 principal components regression model, applying partial least square regression algorithm with full cross validation as internal validation. External validation was performed to 25 unknown samples. Coefficients of correlation, root mean square error and standard error of calibration were 0.964, 0.630 and 0.632, respectively and the external validation confirmed a fair potential of the model in predicting FB(1)+FB(2) concentration. Results suggest that FT-NIR analysis is a suitable method to detect FB(1)+FB(2) in corn meal and to discriminate safe meals from those contaminated. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multivariate Welch t-test on distances

PubMed Central

2016-01-01

Motivation: Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method, however, suffers from loss of power and type I error inflation in the presence of heteroscedasticity and sample size imbalances. Results: We develop a solution in the form of a distance-based Welch t-test, TW2, for two sample potentially unbalanced and heteroscedastic data. We demonstrate empirically the desirable type I error and power characteristics of the new test. We compare the performance of PERMANOVA and TW2 in reanalysis of two existing microbiome datasets, where the methodology has originated. Availability and Implementation: The source code for methods and analysis of this article is available at https://github.com/alekseyenko/Tw2. Further guidance on application of these methods can be obtained from the author. Contact: alekseye@musc.edu PMID:27515741

Multivariate Welch t-test on distances.

PubMed

Alekseyenko, Alexander V

2016-12-01

Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method, however, suffers from loss of power and type I error inflation in the presence of heteroscedasticity and sample size imbalances. We develop a solution in the form of a distance-based Welch t-test, [Formula: see text], for two sample potentially unbalanced and heteroscedastic data. We demonstrate empirically the desirable type I error and power characteristics of the new test. We compare the performance of PERMANOVA and [Formula: see text] in reanalysis of two existing microbiome datasets, where the methodology has originated. The source code for methods and analysis of this article is available at https://github.com/alekseyenko/Tw2 Further guidance on application of these methods can be obtained from the author. alekseye@musc.edu. © The Author 2016. Published by Oxford University Press.

Seabed roughness parameters from joint backscatter and reflection inversion at the Malta Plateau.

PubMed

Steininger, Gavin; Holland, Charles W; Dosso, Stan E; Dettmer, Jan

2013-09-01

This paper presents estimates of seabed roughness and geoacoustic parameters and uncertainties on the Malta Plateau, Mediterranean Sea, by joint Bayesian inversion of mono-static backscatter and spherical wave reflection-coefficient data. The data are modeled using homogeneous fluid sediment layers overlying an elastic basement. The scattering model assumes a randomly rough water-sediment interface with a von Karman roughness power spectrum. Scattering and reflection data are inverted simultaneously using a population of interacting Markov chains to sample roughness and geoacoustic parameters as well as residual error parameters. Trans-dimensional sampling is applied to treat the number of sediment layers and the order (zeroth or first) of an autoregressive error model (to represent potential residual correlation) as unknowns. Results are considered in terms of marginal posterior probability profiles and distributions, which quantify the effective data information content to resolve scattering/geoacoustic structure. Results indicate well-defined scattering (roughness) parameters in good agreement with existing measurements, and a multi-layer sediment profile over a high-speed (elastic) basement, consistent with independent knowledge of sand layers over limestone.

Comparing interval estimates for small sample ordinal CFA models

PubMed Central

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research. PMID:26579002

Comparing interval estimates for small sample ordinal CFA models.

PubMed

Natesan, Prathiba

2015-01-01

Robust maximum likelihood (RML) and asymptotically generalized least squares (AGLS) methods have been recommended for fitting ordinal structural equation models. Studies show that some of these methods underestimate standard errors. However, these studies have not investigated the coverage and bias of interval estimates. An estimate with a reasonable standard error could still be severely biased. This can only be known by systematically investigating the interval estimates. The present study compares Bayesian, RML, and AGLS interval estimates of factor correlations in ordinal confirmatory factor analysis models (CFA) for small sample data. Six sample sizes, 3 factor correlations, and 2 factor score distributions (multivariate normal and multivariate mildly skewed) were studied. Two Bayesian prior specifications, informative and relatively less informative were studied. Undercoverage of confidence intervals and underestimation of standard errors was common in non-Bayesian methods. Underestimated standard errors may lead to inflated Type-I error rates. Non-Bayesian intervals were more positive biased than negatively biased, that is, most intervals that did not contain the true value were greater than the true value. Some non-Bayesian methods had non-converging and inadmissible solutions for small samples and non-normal data. Bayesian empirical standard error estimates for informative and relatively less informative priors were closer to the average standard errors of the estimates. The coverage of Bayesian credibility intervals was closer to what was expected with overcoverage in a few cases. Although some Bayesian credibility intervals were wider, they reflected the nature of statistical uncertainty that comes with the data (e.g., small sample). Bayesian point estimates were also more accurate than non-Bayesian estimates. The results illustrate the importance of analyzing coverage and bias of interval estimates, and how ignoring interval estimates can be misleading. Therefore, editors and policymakers should continue to emphasize the inclusion of interval estimates in research.

Prescribing errors during hospital inpatient care: factors influencing identification by pharmacists.

PubMed

Tully, Mary P; Buchan, Iain E

2009-12-01

To investigate the prevalence of prescribing errors identified by pharmacists in hospital inpatients and the factors influencing error identification rates by pharmacists throughout hospital admission. 880-bed university teaching hospital in North-west England. Data about prescribing errors identified by pharmacists (median: 9 (range 4-17) collecting data per day) when conducting routine work were prospectively recorded on 38 randomly selected days over 18 months. Proportion of new medication orders in which an error was identified; predictors of error identification rate, adjusted for workload and seniority of pharmacist, day of week, type of ward or stage of patient admission. 33,012 new medication orders were reviewed for 5,199 patients; 3,455 errors (in 10.5% of orders) were identified for 2,040 patients (39.2%; median 1, range 1-12). Most were problem orders (1,456, 42.1%) or potentially significant errors (1,748, 50.6%); 197 (5.7%) were potentially serious; 1.6% (n = 54) were potentially severe or fatal. Errors were 41% (CI: 28-56%) more likely to be identified at patient's admission than at other times, independent of confounders. Workload was the strongest predictor of error identification rates, with 40% (33-46%) less errors identified on the busiest days than at other times. Errors identified fell by 1.9% (1.5-2.3%) for every additional chart checked, independent of confounders. Pharmacists routinely identify errors but increasing workload may reduce identification rates. Where resources are limited, they may be better spent on identifying and addressing errors immediately after admission to hospital.

Blood gas testing and related measurements: National recommendations on behalf of the Croatian Society of Medical Biochemistry and Laboratory Medicine.

PubMed

Dukić, Lora; Kopčinović, Lara Milevoj; Dorotić, Adrijana; Baršić, Ivana

2016-10-15

Blood gas analysis (BGA) is exposed to risks of errors caused by improper sampling, transport and storage conditions. The Clinical and Laboratory Standards Institute (CLSI) generated documents with recommendations for avoidance of potential errors caused by sample mishandling. Two main documents related to BGA issued by the CLSI are GP43-A4 (former H11-A4) Procedures for the collection of arterial blood specimens; approved standard - fourth edition, and C46-A2 Blood gas and pH analysis and related measurements; approved guideline - second edition. Practices related to processing of blood gas samples are not standardized in the Republic of Croatia. Each institution has its own protocol for ordering, collection and analysis of blood gases. Although many laboratories use state of the art analyzers, still many preanalytical procedures remain unchanged. The objective of the Croatian Society of Medical Biochemistry and Laboratory Medicine (CSMBLM) is to standardize the procedures for BGA based on CLSI recommendations. The Working Group for Blood Gas Testing as part of the Committee for the Scientific Professional Development of the CSMBLM prepared a set of recommended protocols for sampling, transport, storage and processing of blood gas samples based on relevant CLSI documents, relevant literature search and on the results of Croatian survey study on practices and policies in acid-base testing. Recommendations are intended for laboratory professionals and all healthcare workers involved in blood gas processing.

Blood gas testing and related measurements: National recommendations on behalf of the Croatian Society of Medical Biochemistry and Laboratory Medicine

PubMed Central

Dukić, Lora; Kopčinović, Lara Milevoj; Dorotić, Adrijana; Baršić, Ivana

2016-01-01

Blood gas analysis (BGA) is exposed to risks of errors caused by improper sampling, transport and storage conditions. The Clinical and Laboratory Standards Institute (CLSI) generated documents with recommendations for avoidance of potential errors caused by sample mishandling. Two main documents related to BGA issued by the CLSI are GP43-A4 (former H11-A4) Procedures for the collection of arterial blood specimens; approved standard – fourth edition, and C46-A2 Blood gas and pH analysis and related measurements; approved guideline – second edition. Practices related to processing of blood gas samples are not standardized in the Republic of Croatia. Each institution has its own protocol for ordering, collection and analysis of blood gases. Although many laboratories use state of the art analyzers, still many preanalytical procedures remain unchanged. The objective of the Croatian Society of Medical Biochemistry and Laboratory Medicine (CSMBLM) is to standardize the procedures for BGA based on CLSI recommendations. The Working Group for Blood Gas Testing as part of the Committee for the Scientific Professional Development of the CSMBLM prepared a set of recommended protocols for sampling, transport, storage and processing of blood gas samples based on relevant CLSI documents, relevant literature search and on the results of Croatian survey study on practices and policies in acid-base testing. Recommendations are intended for laboratory professionals and all healthcare workers involved in blood gas processing. PMID:27812301

Evaluation of a UMLS Auditing Process of Semantic Type Assignments

PubMed Central

Gu, Huanying; Hripcsak, George; Chen, Yan; Morrey, C. Paul; Elhanan, Gai; Cimino, James J.; Geller, James; Perl, Yehoshua

2007-01-01

The UMLS is a terminological system that integrates many source terminologies. Each concept in the UMLS is assigned one or more semantic types from the Semantic Network, an upper level ontology for biomedicine. Due to the complexity of the UMLS, errors exist in the semantic type assignments. Finding assignment errors may unearth modeling errors. Even with sophisticated tools, discovering assignment errors requires manual review. In this paper we describe the evaluation of an auditing project of UMLS semantic type assignments. We studied the performance of the auditors who reviewed potential errors. We found that four auditors, interacting according to a multi-step protocol, identified a high rate of errors (one or more errors in 81% of concepts studied) and that results were sufficiently reliable (0.67 to 0.70) for the two most common types of errors. However, reliability was low for each individual auditor, suggesting that review of potential errors is resource-intensive. PMID:18693845

Clarification of terminology in medication errors: definitions and classification.

PubMed

Ferner, Robin E; Aronson, Jeffrey K

2006-01-01

We have previously described and analysed some terms that are used in drug safety and have proposed definitions. Here we discuss and define terms that are used in the field of medication errors, particularly terms that are sometimes misunderstood or misused. We also discuss the classification of medication errors. A medication error is a failure in the treatment process that leads to, or has the potential to lead to, harm to the patient. Errors can be classified according to whether they are mistakes, slips, or lapses. Mistakes are errors in the planning of an action. They can be knowledge based or rule based. Slips and lapses are errors in carrying out an action - a slip through an erroneous performance and a lapse through an erroneous memory. Classification of medication errors is important because the probabilities of errors of different classes are different, as are the potential remedies.

A method to correct sampling ghosts in historic near-infrared Fourier transform spectrometer (FTS) measurements

NASA Astrophysics Data System (ADS)

Dohe, S.; Sherlock, V.; Hase, F.; Gisi, M.; Robinson, J.; Sepúlveda, E.; Schneider, M.; Blumenstock, T.

2013-08-01

The Total Carbon Column Observing Network (TCCON) has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF) of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE) is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment). Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y) at both sites show discrepancies of 0.2-0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

A content validated questionnaire for assessment of self reported venous blood sampling practices

PubMed Central

2012-01-01

Background Venous blood sampling is a common procedure in health care. It is strictly regulated by national and international guidelines. Deviations from guidelines due to human mistakes can cause patient harm. Validated questionnaires for health care personnel can be used to assess preventable "near misses"--i.e. potential errors and nonconformities during venous blood sampling practices that could transform into adverse events. However, no validated questionnaire that assesses nonconformities in venous blood sampling has previously been presented. The aim was to test a recently developed questionnaire in self reported venous blood sampling practices for validity and reliability. Findings We developed a questionnaire to assess deviations from best practices during venous blood sampling. The questionnaire contained questions about patient identification, test request management, test tube labeling, test tube handling, information search procedures and frequencies of error reporting. For content validity, the questionnaire was confirmed by experts on questionnaires and venous blood sampling. For reliability, test-retest statistics were used on the questionnaire answered twice. The final venous blood sampling questionnaire included 19 questions out of which 9 had in total 34 underlying items. It was found to have content validity. The test-retest analysis demonstrated that the items were generally stable. In total, 82% of the items fulfilled the reliability acceptance criteria. Conclusions The questionnaire could be used for assessment of "near miss" practices that could jeopardize patient safety and gives several benefits instead of assessing rare adverse events only. The higher frequencies of "near miss" practices allows for quantitative analysis of the effect of corrective interventions and to benchmark preanalytical quality not only at the laboratory/hospital level but also at the health care unit/hospital ward. PMID:22260505

A content validated questionnaire for assessment of self reported venous blood sampling practices.

PubMed

Bölenius, Karin; Brulin, Christine; Grankvist, Kjell; Lindkvist, Marie; Söderberg, Johan

2012-01-19

Venous blood sampling is a common procedure in health care. It is strictly regulated by national and international guidelines. Deviations from guidelines due to human mistakes can cause patient harm. Validated questionnaires for health care personnel can be used to assess preventable "near misses"--i.e. potential errors and nonconformities during venous blood sampling practices that could transform into adverse events. However, no validated questionnaire that assesses nonconformities in venous blood sampling has previously been presented. The aim was to test a recently developed questionnaire in self reported venous blood sampling practices for validity and reliability. We developed a questionnaire to assess deviations from best practices during venous blood sampling. The questionnaire contained questions about patient identification, test request management, test tube labeling, test tube handling, information search procedures and frequencies of error reporting. For content validity, the questionnaire was confirmed by experts on questionnaires and venous blood sampling. For reliability, test-retest statistics were used on the questionnaire answered twice. The final venous blood sampling questionnaire included 19 questions out of which 9 had in total 34 underlying items. It was found to have content validity. The test-retest analysis demonstrated that the items were generally stable. In total, 82% of the items fulfilled the reliability acceptance criteria. The questionnaire could be used for assessment of "near miss" practices that could jeopardize patient safety and gives several benefits instead of assessing rare adverse events only. The higher frequencies of "near miss" practices allows for quantitative analysis of the effect of corrective interventions and to benchmark preanalytical quality not only at the laboratory/hospital level but also at the health care unit/hospital ward.

Masked and unmasked error-related potentials during continuous control and feedback

NASA Astrophysics Data System (ADS)

Lopes Dias, Catarina; Sburlea, Andreea I.; Müller-Putz, Gernot R.

2018-06-01

The detection of error-related potentials (ErrPs) in tasks with discrete feedback is well established in the brain–computer interface (BCI) field. However, the decoding of ErrPs in tasks with continuous feedback is still in its early stages. Objective. We developed a task in which subjects have continuous control of a cursor’s position by means of a joystick. The cursor’s position was shown to the participants in two different modalities of continuous feedback: normal and jittered. The jittered feedback was created to mimic the instability that could exist if participants controlled the trajectory directly with brain signals. Approach. This paper studies the electroencephalographic (EEG)—measurable signatures caused by a loss of control over the cursor’s trajectory, causing a target miss. Main results. In both feedback modalities, time-locked potentials revealed the typical frontal-central components of error-related potentials. Errors occurring during the jittered feedback (masked errors) were delayed in comparison to errors occurring during normal feedback (unmasked errors). Masked errors displayed lower peak amplitudes than unmasked errors. Time-locked classification analysis allowed a good distinction between correct and error classes (average Cohen-, average TPR  =  81.8% and average TNR  =  96.4%). Time-locked classification analysis between masked error and unmasked error classes revealed results at chance level (average Cohen-, average TPR  =  60.9% and average TNR  =  58.3%). Afterwards, we performed asynchronous detection of ErrPs, combining both masked and unmasked trials. The asynchronous detection of ErrPs in a simulated online scenario resulted in an average TNR of 84.0% and in an average TPR of 64.9%. Significance. The time-locked classification results suggest that the masked and unmasked errors were indistinguishable in terms of classification. The asynchronous classification results suggest that the feedback modality did not hinder the asynchronous detection of ErrPs.

A simulation test of the effectiveness of several methods for error-checking non-invasive genetic data

USGS Publications Warehouse

Roon, David A.; Waits, L.P.; Kendall, K.C.

2005-01-01

Non-invasive genetic sampling (NGS) is becoming a popular tool for population estimation. However, multiple NGS studies have demonstrated that polymerase chain reaction (PCR) genotyping errors can bias demographic estimates. These errors can be detected by comprehensive data filters such as the multiple-tubes approach, but this approach is expensive and time consuming as it requires three to eight PCR replicates per locus. Thus, researchers have attempted to correct PCR errors in NGS datasets using non-comprehensive error checking methods, but these approaches have not been evaluated for reliability. We simulated NGS studies with and without PCR error and 'filtered' datasets using non-comprehensive approaches derived from published studies and calculated mark-recapture estimates using CAPTURE. In the absence of data-filtering, simulated error resulted in serious inflations in CAPTURE estimates; some estimates exceeded N by ??? 200%. When data filters were used, CAPTURE estimate reliability varied with per-locus error (E??). At E?? = 0.01, CAPTURE estimates from filtered data displayed < 5% deviance from error-free estimates. When E?? was 0.05 or 0.09, some CAPTURE estimates from filtered data displayed biases in excess of 10%. Biases were positive at high sampling intensities; negative biases were observed at low sampling intensities. We caution researchers against using non-comprehensive data filters in NGS studies, unless they can achieve baseline per-locus error rates below 0.05 and, ideally, near 0.01. However, we suggest that data filters can be combined with careful technique and thoughtful NGS study design to yield accurate demographic information. ?? 2005 The Zoological Society of London.

Describing Phonological Paraphasias in Three Variants of Primary Progressive Aphasia.

PubMed

Dalton, Sarah Grace Hudspeth; Shultz, Christine; Henry, Maya L; Hillis, Argye E; Richardson, Jessica D

2018-03-01

The purpose of this study was to describe the linguistic environment of phonological paraphasias in 3 variants of primary progressive aphasia (semantic, logopenic, and nonfluent) and to describe the profiles of paraphasia production for each of these variants. Discourse samples of 26 individuals diagnosed with primary progressive aphasia were investigated for phonological paraphasias using the criteria established for the Philadelphia Naming Test (Moss Rehabilitation Research Institute, 2013). Phonological paraphasias were coded for paraphasia type, part of speech of the target word, target word frequency, type of segment in error, word position of consonant errors, type of error, and degree of change in consonant errors. Eighteen individuals across the 3 variants produced phonological paraphasias. Most paraphasias were nonword, followed by formal, and then mixed, with errors primarily occurring on nouns and verbs, with relatively few on function words. Most errors were substitutions, followed by addition and deletion errors, and few sequencing errors. Errors were evenly distributed across vowels, consonant singletons, and clusters, with more errors occurring in initial and medial positions of words than in the final position of words. Most consonant errors consisted of only a single-feature change, with few 2- or 3-feature changes. Importantly, paraphasia productions by variant differed from these aggregate results, with unique production patterns for each variant. These results suggest that a system where paraphasias are coded as present versus absent may be insufficient to adequately distinguish between the 3 subtypes of PPA. The 3 variants demonstrate patterns that may be used to improve phenotyping and diagnostic sensitivity. These results should be integrated with recent findings on phonological processing and speech rate. Future research should attempt to replicate these results in a larger sample of participants with longer speech samples and varied elicitation tasks. https://doi.org/10.23641/asha.5558107.

Usage of DNA Fingerprinting Technology for Quality Control in Molecular Lab Bench Work.

PubMed

McIntosh, Linda Y; Lal, Janella E; Qin, Dahui

2018-01-01

One of the major quality assurance (QA) goals in many molecular laboratories is to avoid sample pipetting errors on the lab bench; especially when pipetting into multiwell plates. A pipetting error can cause a switch in patient samples, which can lead to recording the wrong results for the patient samples involved. Such pipetting errors are difficult to identify when it happens in lab bench work. DNA fingerprinting is a powerful tool in determining sample identities. Our laboratory has explored the usage of this technology in our QA process and successfully established that DNA fingerprinting can be used to monitor possible sample switch in gene rearrangement lab bench work. We use florescent light to quench the florescence in the gene rearrangement polymerase chain reaction products. After that, DNA fingerprinting technology is used to identify the sample DNA in the gene rearrangement polymerase chain reaction plate. The result is compared with the corresponding patient's blood sample DNA to determine whether there is a sample switch during the lab bench work.

Correcting intensity loss errors in the absence of texture-free reference samples during pole figure measurement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saleh, Ahmed A., E-mail: asaleh@uow.edu.au

Even with the use of X-ray polycapillary lenses, sample tilting during pole figure measurement results in a decrease in the recorded X-ray intensity. The magnitude of this error is affected by the sample size and/or the finite detector size. These errors can be typically corrected by measuring the intensity loss as a function of the tilt angle using a texture-free reference sample (ideally made of the same alloy as the investigated material). Since texture-free reference samples are not readily available for all alloys, the present study employs an empirical procedure to estimate the correction curve for a particular experimental configuration.more » It involves the use of real texture-free reference samples that pre-exist in any X-ray diffraction laboratory to first establish the empirical correlations between X-ray intensity, sample tilt and their Bragg angles and thereafter generate correction curves for any Bragg angle. It will be shown that the empirically corrected textures are in very good agreement with the experimentally corrected ones. - Highlights: •Sample tilting during X-ray pole figure measurement leads to intensity loss errors. •Texture-free reference samples are typically used to correct the pole figures. •An empirical correction procedure is proposed in the absence of reference samples. •The procedure relies on reference samples that pre-exist in any texture laboratory. •Experimentally and empirically corrected textures are in very good agreement.« less

Risk-Taking and the Feedback Negativity Response to Loss among At-Risk Adolescents

PubMed Central

Crowley, Michael J.; Wu, Jia; Crutcher, Clifford; Bailey, Christopher A.; Lejuez, C.W.; Mayes, Linda C.

2009-01-01

Event-related brain potentials were examined in 32 adolescents (50% female) from a high-risk sample, who were exposed to cocaine and other drugs prenatally. Adolescents were selected for extreme high- or low-risk behavior on the Balloon Analog Risk Task, a measure of real-world risk-taking propensity. The feedback error-related negativity (fERN), an event-related potential (ERP) that occurs when an expected reward does not occur, was examined in a game in which choices lead to monetary gains and losses with feedback delayed 1 or 2 s. The fERN was clearly visible in the fronto-central scalp region in this adolescent sample. Feedback type, feedback delay, risk status, and sex were all associated with fERN variability. Monetary feedback also elicited a P300-like component, moderated by delay and sex. Delaying reward feedback may provide a means for studying complementary functioning of dopamine and norepinephrine systems. PMID:19372694

Sources of uncertainty in the quantification of genetically modified oilseed rape contamination in seed lots.

PubMed

Begg, Graham S; Cullen, Danny W; Iannetta, Pietro P M; Squire, Geoff R

2007-02-01

Testing of seed and grain lots is essential in the enforcement of GM labelling legislation and needs reliable procedures for which associated errors have been identified and minimised. In this paper we consider the testing of oilseed rape seed lots obtained from the harvest of a non-GM crop known to be contaminated by volunteer plants from a GM herbicide tolerant variety. The objective was to identify and quantify the error associated with the testing of these lots from the initial sampling to completion of the real-time PCR assay with which the level of GM contamination was quantified. The results showed that, under the controlled conditions of a single laboratory, the error associated with the real-time PCR assay to be negligible in comparison with sampling error, which was exacerbated by heterogeneity in the distribution of GM seeds, most notably at a small scale, i.e. 25 cm3. Sampling error was reduced by one to two thirds on the application of appropriate homogenisation procedures.

Uncertainties in the cluster-cluster correlation function

NASA Astrophysics Data System (ADS)

Ling, E. N.; Frenk, C. S.; Barrow, J. D.

1986-12-01

The bootstrap resampling technique is applied to estimate sampling errors and significance levels of the two-point correlation functions determined for a subset of the CfA redshift survey of galaxies and a redshift sample of 104 Abell clusters. The angular correlation function for a sample of 1664 Abell clusters is also calculated. The standard errors in xi(r) for the Abell data are found to be considerably larger than quoted 'Poisson errors'. The best estimate for the ratio of the correlation length of Abell clusters (richness class R greater than or equal to 1, distance class D less than or equal to 4) to that of CfA galaxies is 4.2 + 1.4 or - 1.0 (68 percentile error). The enhancement of cluster clustering over galaxy clustering is statistically significant in the presence of resampling errors. The uncertainties found do not include the effects of possible systematic biases in the galaxy and cluster catalogs and could be regarded as lower bounds on the true uncertainty range.

Inventory implications of using sampling variances in estimation of growth model coefficients

Treesearch

Albert R. Stage; William R. Wykoff

2000-01-01

Variables based on stand densities or stocking have sampling errors that depend on the relation of tree size to plot size and on the spatial structure of the population, ignoring the sampling errors of such variables, which include most measures of competition used in both distance-dependent and distance-independent growth models, can bias the predictions obtained from...

Getting the right blood to the right patient: the contribution of near-miss event reporting and barrier analysis.

PubMed

Kaplan, H S

2005-11-01

Safety and reliability in blood transfusion are not static, but are dynamic non-events. Since performance deviations continually occur in complex systems, their detection and correction must be accomplished over and over again. Non-conformance must be detected early enough to allow for recovery or mitigation. Near-miss events afford early detection of possible system weaknesses and provide an early chance at correction. National event reporting systems, both voluntary and involuntary, have begun to include near-miss reporting in their classification schemes, raising awareness for their detection. MERS-TM is a voluntary safety reporting initiative in transfusion. Currently 22 hospitals submit reports anonymously to a central database which supports analysis of a hospital's own data and that of an aggregate database. The system encourages reporting of near-miss events, where the patient is protected from receiving an unsuitable or incorrect blood component due to a planned or unplanned recovery step. MERS-TM data suggest approximately 90% of events are near-misses, with 10% caught after issue but before transfusion. Near-miss reporting may increase total reports ten-fold. The ratio of near-misses to events with harm is 339:1, consistent with other industries' ratio of 300:1, which has been proposed as a measure of reporting in event reporting systems. Use of a risk matrix and an event's relation to protective barriers allow prioritization of these events. Near-misses recovered by planned barriers occur ten times more frequently then unplanned recoveries. A bedside check of the patient's identity with that on the blood component is an essential, final barrier. How the typical two person check is performed, is critical. Even properly done, this check is ineffective against sampling and testing errors. Blood testing at bedside just prior to transfusion minimizes the risk of such upstream events. However, even with simple and well designed devices, training may be a critical issue. Sample errors account for more than half of reported events. The most dangerous miscollection is a blood sample passing acceptance with no previous patient results for comparison. Bar code labels or collection of a second sample may counter this upstream vulnerability. Further upstream barriers have been proposed to counter the precariousness of urgent blood sample collection in a changing unstable situation. One, a linking device, allows safer labeling of tubes away from the bedside, the second, a forcing function, prevents omission of critical patient identification steps. Errors in the blood bank itself account for 15% of errors with a high potential severity. In one such event, a component incorrectly issued, but safely detected prior to transfusion, focused attention on multitasking's contribution to laboratory error. In sum, use of near-miss information, by enhancing barriers supporting error prevention and mitigation, increases our capacity to get the right blood to the right patient.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

PubMed

Fushing, Hsieh; McAssey, Michael P; Beisner, Brianne; McCowan, Brenda

2011-03-15

We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Application of Lamendin's adult dental aging technique to a diverse skeletal sample.

PubMed

Prince, Debra A; Ubelaker, Douglas H

2002-01-01

Lamendin et al. (1) proposed a technique to estimate age at death for adults by analyzing single-rooted teeth. They expressed age as a function of two factors: translucency of the tooth root and periodontosis (gingival regression). In their study, they analyzed 306 singled rooted teeth that were extracted at autopsy from 208 individuals of known age at death, all of whom were considered as having a French ancestry. Their sample consisted of 135 males, 73 females, 198 whites, and 10 blacks. The sample ranged in age from 22 to 90 years of age. By using a simple formulae (A = 0.18 x P + 0.42 x T + 25.53, where A = Age in years, P = Periodontosis height x 100/root height, and T = Transparency height x 100/root height), Lamendin et al. were able to estimate age at death with a mean error of +/- 10 years on their working sample and +/- 8.4 years on a forensic control sample. Lamendin found this technique to work well with a French population, but did not test it outside of that sample area. This study tests the accuracy of this adult aging technique on a more diverse skeletal population, the Terry Collection housed at the Smithsonian's National Museum of Natural History. Our sample consists of 400 teeth from 94 black females, 72 white females, 98 black males, and 95 white males, ranging from 25 to 99 years. Lamendin's technique was applied to this sample to test its applicability to a population not of French origin. Providing results from a diverse skeletal population will aid in establishing the validity of this method to be used in forensic cases, its ideal purpose. Our results suggest that Lamendin's method estimates age fairly accurately outside of the French sample yielding a mean error of 8.2 years, standard deviation 6.9 years, and standard error of the mean 0.34 years. In addition, when ancestry and sex are accounted for, the mean errors are reduced for each group (black females, white females, black males, and white males). Lamendin et al. reported an inter-observer error of 9+/-1.8 and 10+/-2 sears from two independent observers. Forty teeth were randomly remeasured from the Terry Collection in order to assess an intra-observer error. From this retest, an intra-observer error of 6.5 years was detected.

Evaluating concentration estimation errors in ELISA microarray experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daly, Don S.; White, Amanda M.; Varnum, Susan M.

Enzyme-linked immunosorbent assay (ELISA) is a standard immunoassay to predict a protein concentration in a sample. Deploying ELISA in a microarray format permits simultaneous prediction of the concentrations of numerous proteins in a small sample. These predictions, however, are uncertain due to processing error and biological variability. Evaluating prediction error is critical to interpreting biological significance and improving the ELISA microarray process. Evaluating prediction error must be automated to realize a reliable high-throughput ELISA microarray system. Methods: In this paper, we present a statistical method based on propagation of error to evaluate prediction errors in the ELISA microarray process. Althoughmore » propagation of error is central to this method, it is effective only when comparable data are available. Therefore, we briefly discuss the roles of experimental design, data screening, normalization and statistical diagnostics when evaluating ELISA microarray prediction errors. We use an ELISA microarray investigation of breast cancer biomarkers to illustrate the evaluation of prediction errors. The illustration begins with a description of the design and resulting data, followed by a brief discussion of data screening and normalization. In our illustration, we fit a standard curve to the screened and normalized data, review the modeling diagnostics, and apply propagation of error.« less

Sampling errors for satellite-derived tropical rainfall - Monte Carlo study using a space-time stochastic model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Abdullah, A.; Martin, Russell L.; North, Gerald R.

1990-01-01

Estimates of monthly average rainfall based on satellite observations from a low earth orbit will differ from the true monthly average because the satellite observes a given area only intermittently. This sampling error inherent in satellite monitoring of rainfall would occur even if the satellite instruments could measure rainfall perfectly. The size of this error is estimated for a satellite system being studied at NASA, the Tropical Rainfall Measuring Mission (TRMM). First, the statistical description of rainfall on scales from 1 to 1000 km is examined in detail, based on rainfall data from the Global Atmospheric Research Project Atlantic Tropical Experiment (GATE). A TRMM-like satellite is flown over a two-dimensional time-evolving simulation of rainfall using a stochastic model with statistics tuned to agree with GATE statistics. The distribution of sampling errors found from many months of simulated observations is found to be nearly normal, even though the distribution of area-averaged rainfall is far from normal. For a range of orbits likely to be employed in TRMM, sampling error is found to be less than 10 percent of the mean for rainfall averaged over a 500 x 500 sq km area.

TECHNICAL ADVANCES: Effects of genotyping protocols on success and errors in identifying individual river otters (Lontra canadensis) from their faeces.

PubMed

Hansen, Heidi; Ben-David, Merav; McDonald, David B

2008-03-01

In noninvasive genetic sampling, when genotyping error rates are high and recapture rates are low, misidentification of individuals can lead to overestimation of population size. Thus, estimating genotyping errors is imperative. Nonetheless, conducting multiple polymerase chain reactions (PCRs) at multiple loci is time-consuming and costly. To address the controversy regarding the minimum number of PCRs required for obtaining a consensus genotype, we compared consumer-style the performance of two genotyping protocols (multiple-tubes and 'comparative method') in respect to genotyping success and error rates. Our results from 48 faecal samples of river otters (Lontra canadensis) collected in Wyoming in 2003, and from blood samples of five captive river otters amplified with four different primers, suggest that use of the comparative genotyping protocol can minimize the number of PCRs per locus. For all but five samples at one locus, the same consensus genotypes were reached with fewer PCRs and with reduced error rates with this protocol compared to the multiple-tubes method. This finding is reassuring because genotyping errors can occur at relatively high rates even in tissues such as blood and hair. In addition, we found that loci that amplify readily and yield consensus genotypes, may still exhibit high error rates (7-32%) and that amplification with different primers resulted in different types and rates of error. Thus, assigning a genotype based on a single PCR for several loci could result in misidentification of individuals. We recommend that programs designed to statistically assign consensus genotypes should be modified to allow the different treatment of heterozygotes and homozygotes intrinsic to the comparative method. © 2007 The Authors.

Modulus design multiwavelength polarization microscope for transmission Mueller matrix imaging

NASA Astrophysics Data System (ADS)

Zhou, Jialing; He, Honghui; Chen, Zhenhua; Wang, Ye; Ma, Hui

2018-01-01

We have developed a polarization microscope based on a commercial transmission microscope. We replace the halogen light source by a collimated LED light source module of six different colors. We use achromatic polarized optical elements that can cover the six different wavelength ranges in the polarization state generator (PSG) and polarization state analyzer (PSA) modules. The dual-rotating wave plate method is used to measure the Mueller matrix of samples, which requires the simultaneous rotation of the two quarter-wave plates in both PSG and PSA at certain angular steps. A scientific CCD detector is used as the image receiving module. A LabView-based software is developed to control the rotation angels of the wave plates and the exposure time of the detector to allow the system to run fully automatically in preprogrammed schedules. Standard samples, such as air, polarizers, and quarter-wave plates, are used to calibrate the intrinsic Mueller matrix of optical components, such as the objectives, using the eigenvalue calibration method. Errors due to the images walk-off in the PSA are studied. Errors in the Mueller matrices are below 0.01 using air and polarizer as standard samples. Data analysis based on Mueller matrix transformation and Mueller matrix polarization decomposition is used to demonstrate the potential application of this microscope in pathological diagnosis.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

NASA Technical Reports Server (NTRS)

Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

2016-01-01

Model benchmarking allows us to separate uncertainty in model predictions caused 1 by model inputs from uncertainty due to model structural error. We extend this method with a large-sample approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions.

PubMed

Nearing, Grey S; Mocko, David M; Peters-Lidard, Christa D; Kumar, Sujay V; Xia, Youlong

2016-03-01

Model benchmarking allows us to separate uncertainty in model predictions caused by model inputs from uncertainty due to model structural error. We extend this method with a "large-sample" approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

NASA Technical Reports Server (NTRS)

Rafael, Qihang Li; Bras, Rafael L.; Veneziano, Daniele

1996-01-01

Rainfall data collected by radar in the vicinity of Darwin, Australia, have been analyzed in terms of their mean, variance, autocorrelation of area-averaged rain rate, and diurnal variation. It is found that, when compared with the well-studied GATE (Global Atmospheric Research Program Atlantic Tropical Experiment) data, Darwin rainfall has larger coefficient of variation (CV), faster reduction of CV with increasing area size, weaker temporal correlation, and a strong diurnal cycle and intermittence. The coefficient of variation for Darwin rainfall has larger magnitude and exhibits larger spatial variability over the sea portion than over the land portion within the area of radar coverage. Stationary, and nonstationary models have been used to study the sampling errors associated with space-based rainfall measurement. The nonstationary model shows that the sampling error is sensitive to the starting sampling time for some sampling frequencies, due to the diurnal cycle of rain, but not for others. Sampling experiments using data also show such sensitivity. When the errors are averaged over starting time, the results of the experiments and the stationary and nonstationary models match each other very closely. In the small areas for which data are available for I>oth Darwin and GATE, the sampling error is expected to be larger for Darwin due to its larger CV.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

GY SAMPLING THEORY IN ENVIRONMENTAL STUDIES 2: SUBSAMPLING ERROR MEASUREMENTS

EPA Science Inventory

Sampling can be a significant source of error in the measurement process. The characterization and cleanup of hazardous waste sites require data that meet site-specific levels of acceptable quality if scientifically supportable decisions are to be made. In support of this effort,...

Developmental Changes in Error Monitoring: An Event-Related Potential Study

ERIC Educational Resources Information Center

Wiersema, Jan R.; van der Meere, Jacob J.; Roeyers, Herbert

2007-01-01

The aim of the study was to investigate the developmental trajectory of error monitoring. For this purpose, children (age 7-8), young adolescents (age 13-14) and adults (age 23-24) performed a Go/No-Go task and were compared on overt reaction time (RT) performance and on event-related potentials (ERPs), thought to reflect error detection…

Double ErrP Detection for Automatic Error Correction in an ERP-Based BCI Speller.

PubMed

Cruz, Aniana; Pires, Gabriel; Nunes, Urbano J

2018-01-01

Brain-computer interface (BCI) is a useful device for people with severe motor disabilities. However, due to its low speed and low reliability, BCI still has a very limited application in daily real-world tasks. This paper proposes a P300-based BCI speller combined with a double error-related potential (ErrP) detection to automatically correct erroneous decisions. This novel approach introduces a second error detection to infer whether wrong automatic correction also elicits a second ErrP. Thus, two single-trial responses, instead of one, contribute to the final selection, improving the reliability of error detection. Moreover, to increase error detection, the evoked potential detected as target by the P300 classifier is combined with the evoked error potential at a feature-level. Discriminable error and positive potentials (response to correct feedback) were clearly identified. The proposed approach was tested on nine healthy participants and one tetraplegic participant. The online average accuracy for the first and second ErrPs were 88.4% and 84.8%, respectively. With automatic correction, we achieved an improvement around 5% achieving 89.9% in spelling accuracy for an effective 2.92 symbols/min. The proposed approach revealed that double ErrP detection can improve the reliability and speed of BCI systems.

Outlier removal, sum scores, and the inflation of the Type I error rate in independent samples t tests: the power of alternatives and recommendations.

PubMed

Bakker, Marjan; Wicherts, Jelte M

2014-09-01

In psychology, outliers are often excluded before running an independent samples t test, and data are often nonnormal because of the use of sum scores based on tests and questionnaires. This article concerns the handling of outliers in the context of independent samples t tests applied to nonnormal sum scores. After reviewing common practice, we present results of simulations of artificial and actual psychological data, which show that the removal of outliers based on commonly used Z value thresholds severely increases the Type I error rate. We found Type I error rates of above 20% after removing outliers with a threshold value of Z = 2 in a short and difficult test. Inflations of Type I error rates are particularly severe when researchers are given the freedom to alter threshold values of Z after having seen the effects thereof on outcomes. We recommend the use of nonparametric Mann-Whitney-Wilcoxon tests or robust Yuen-Welch tests without removing outliers. These alternatives to independent samples t tests are found to have nominal Type I error rates with a minimal loss of power when no outliers are present in the data and to have nominal Type I error rates and good power when outliers are present. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Judging Statistical Models of Individual Decision Making under Risk Using In- and Out-of-Sample Criteria

PubMed Central

Drichoutis, Andreas C.; Lusk, Jayson L.

2014-01-01

Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample. PMID:25029467

Judging statistical models of individual decision making under risk using in- and out-of-sample criteria.

PubMed

Drichoutis, Andreas C; Lusk, Jayson L

2014-01-01

Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.

Analyzing Hydraulic Conductivity Sampling Schemes in an Idealized Meandering Stream Model

NASA Astrophysics Data System (ADS)

Stonedahl, S. H.; Stonedahl, F.

2017-12-01

Hydraulic conductivity (K) is an important parameter affecting the flow of water through sediments under streams, which can vary by orders of magnitude within a stream reach. Measuring heterogeneous K distributions in the field is limited by time and resources. This study investigates hypothetical sampling practices within a modeling framework on a highly idealized meandering stream. We generated three sets of 100 hydraulic conductivity grids containing two sands with connectivity values of 0.02, 0.08, and 0.32. We investigated systems with twice as much fast (K=0.1 cm/s) sand as slow sand (K=0.01 cm/s) and the reverse ratio on the same grids. The K values did not vary with depth. For these 600 cases, we calculated the homogenous K value, Keq, that would yield the same flux into the sediments as the corresponding heterogeneous grid. We then investigated sampling schemes with six weighted probability distributions derived from the homogenous case: uniform, flow-paths, velocity, in-stream, flux-in, and flux-out. For each grid, we selected locations from these distributions and compared the arithmetic, geometric, and harmonic means of these lists to the corresponding Keq using the root-mean-square deviation. We found that arithmetic averaging of samples outperformed geometric or harmonic means for all sampling schemes. Of the sampling schemes, flux-in (sampling inside the stream in an inward flux-weighted manner) yielded the least error and flux-out yielded the most error. All three sampling schemes outside of the stream yielded very similar results. Grids with lower connectivity values (fewer and larger clusters) showed the most sensitivity to the choice of sampling scheme, and thus improved the most with the flux-insampling. We also explored the relationship between the number of samples taken and the resulting error. Increasing the number of sampling points reduced error for the arithmetic mean with diminishing returns, but did not substantially reduce error associated with geometric and harmonic means.

Evaluation and mitigation of potential errors in radiochromic film dosimetry due to film curvature at scanning

PubMed Central

Bradley, David A.; Nisbet, Andrew

2015-01-01

This work considers a previously overlooked uncertainty present in film dosimetry which results from moderate curvature of films during the scanning process. Small film samples are particularly susceptible to film curling which may be undetected or deemed insignificant. In this study, we consider test cases with controlled induced curvature of film and with film raised horizontally above the scanner plate. We also evaluate the difference in scans of a film irradiated with a typical brachytherapy dose distribution with the film naturally curved and with the film held flat on the scanner. Typical naturally occurring curvature of film at scanning, giving rise to a maximum height 1 to 2 mm above the scan plane, may introduce dose errors of 1% to 4%, and considerably reduce gamma evaluation passing rates when comparing film‐measured doses with treatment planning system‐calculated dose distributions, a common application of film dosimetry in radiotherapy. The use of a triple‐channel dosimetry algorithm appeared to mitigate the error due to film curvature compared to conventional single‐channel film dosimetry. The change in pixel value and calibrated reported dose with film curling or height above the scanner plate may be due to variations in illumination characteristics, optical disturbances, or a Callier‐type effect. There is a clear requirement for physically flat films at scanning to avoid the introduction of a substantial error source in film dosimetry. Particularly for small film samples, a compression glass plate above the film is recommended to ensure flat‐film scanning. This effect has been overlooked to date in the literature. PACS numbers: 87.55.Qr, 87.56.bg, 87.55.km PMID:26103181

An internal pilot design for prospective cancer screening trials with unknown disease prevalence.

PubMed

Brinton, John T; Ringham, Brandy M; Glueck, Deborah H

2015-10-13

For studies that compare the diagnostic accuracy of two screening tests, the sample size depends on the prevalence of disease in the study population, and on the variance of the outcome. Both parameters may be unknown during the design stage, which makes finding an accurate sample size difficult. To solve this problem, we propose adapting an internal pilot design. In this adapted design, researchers will accrue some percentage of the planned sample size, then estimate both the disease prevalence and the variances of the screening tests. The updated estimates of the disease prevalence and variance are used to conduct a more accurate power and sample size calculation. We demonstrate that in large samples, the adapted internal pilot design produces no Type I inflation. For small samples (N less than 50), we introduce a novel adjustment of the critical value to control the Type I error rate. We apply the method to two proposed prospective cancer screening studies: 1) a small oral cancer screening study in individuals with Fanconi anemia and 2) a large oral cancer screening trial. Conducting an internal pilot study without adjusting the critical value can cause Type I error rate inflation in small samples, but not in large samples. An internal pilot approach usually achieves goal power and, for most studies with sample size greater than 50, requires no Type I error correction. Further, we have provided a flexible and accurate approach to bound Type I error below a goal level for studies with small sample size.

Evaluating data mining algorithms using molecular dynamics trajectories.

PubMed

Tatsis, Vasileios A; Tjortjis, Christos; Tzirakis, Panagiotis

2013-01-01

Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.

Demographics of the gay and lesbian population in the United States: evidence from available systematic data sources.

PubMed

Black, D; Gates, G; Sanders, S; Taylor, L

2000-05-01

This work provides an overview of standard social science data sources that now allow some systematic study of the gay and lesbian population in the United States. For each data source, we consider how sexual orientation can be defined, and we note the potential sample sizes. We give special attention to the important problem of measurement error, especially the extent to which individuals recorded as gay and lesbian are indeed recorded correctly. Our concern is that because gays and lesbians constitute a relatively small fraction of the population, modest measurement problems could lead to serious errors in inference. In examining gays and lesbians in multiple data sets we also achieve a second objective: We provide a set of statistics about this population that is relevant to several current policy debates.

Deep sequencing of evolving pathogen populations: applications, errors, and bioinformatic solutions

PubMed Central

2014-01-01

Deep sequencing harnesses the high throughput nature of next generation sequencing technologies to generate population samples, treating information contained in individual reads as meaningful. Here, we review applications of deep sequencing to pathogen evolution. Pioneering deep sequencing studies from the virology literature are discussed, such as whole genome Roche-454 sequencing analyses of the dynamics of the rapidly mutating pathogens hepatitis C virus and HIV. Extension of the deep sequencing approach to bacterial populations is then discussed, including the impacts of emerging sequencing technologies. While it is clear that deep sequencing has unprecedented potential for assessing the genetic structure and evolutionary history of pathogen populations, bioinformatic challenges remain. We summarise current approaches to overcoming these challenges, in particular methods for detecting low frequency variants in the context of sequencing error and reconstructing individual haplotypes from short reads. PMID:24428920

Estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean.

PubMed

Schillaci, Michael A; Schillaci, Mario E

2009-02-01

The use of small sample sizes in human and primate evolutionary research is commonplace. Estimating how well small samples represent the underlying population, however, is not commonplace. Because the accuracy of determinations of taxonomy, phylogeny, and evolutionary process are dependant upon how well the study sample represents the population of interest, characterizing the uncertainty, or potential error, associated with analyses of small sample sizes is essential. We present a method for estimating the probability that the sample mean is within a desired fraction of the standard deviation of the true mean using small (n<10) or very small (n < or = 5) sample sizes. This method can be used by researchers to determine post hoc the probability that their sample is a meaningful approximation of the population parameter. We tested the method using a large craniometric data set commonly used by researchers in the field. Given our results, we suggest that sample estimates of the population mean can be reasonable and meaningful even when based on small, and perhaps even very small, sample sizes.

Medication administration errors in nursing homes using an automated medication dispensing system.

PubMed

van den Bemt, Patricia M L A; Idzinga, Jetske C; Robertz, Hans; Kormelink, Dennis Groot; Pels, Neske

2009-01-01

OBJECTIVE To identify the frequency of medication administration errors as well as their potential risk factors in nursing homes using a distribution robot. DESIGN The study was a prospective, observational study conducted within three nursing homes in the Netherlands caring for 180 individuals. MEASUREMENTS Medication errors were measured using the disguised observation technique. Types of medication errors were described. The correlation between several potential risk factors and the occurrence of medication errors was studied to identify potential causes for the errors. RESULTS In total 2,025 medication administrations to 127 clients were observed. In these administrations 428 errors were observed (21.2%). The most frequently occurring types of errors were use of wrong administration techniques (especially incorrect crushing of medication and not supervising the intake of medication) and wrong time errors (administering the medication at least 1 h early or late).The potential risk factors female gender (odds ratio (OR) 1.39; 95% confidence interval (CI) 1.05-1.83), ATC medication class antibiotics (OR 11.11; 95% CI 2.66-46.50), medication crushed (OR 7.83; 95% CI 5.40-11.36), number of dosages/day/client (OR 1.03; 95% CI 1.01-1.05), nursing home 2 (OR 3.97; 95% CI 2.86-5.50), medication not supplied by distribution robot (OR 2.92; 95% CI 2.04-4.18), time classes "7-10 am" (OR 2.28; 95% CI 1.50-3.47) and "10 am-2 pm" (OR 1.96; 1.18-3.27) and day of the week "Wednesday" (OR 1.46; 95% CI 1.03-2.07) are associated with a higher risk of administration errors. CONCLUSIONS Medication administration in nursing homes is prone to many errors. This study indicates that the handling of the medication after removing it from the robot packaging may contribute to this high error frequency, which may be reduced by training of nurse attendants, by automated clinical decision support and by measures to reduce workload.

Sample sizes needed for specified margins of relative error in the estimates of the repeatability and reproducibility standard deviations.

PubMed

McClure, Foster D; Lee, Jung K

2005-01-01

Sample size formulas are developed to estimate the repeatability and reproducibility standard deviations (Sr and S(R)) such that the actual error in (Sr and S(R)) relative to their respective true values, sigmar and sigmaR, are at predefined levels. The statistical consequences associated with AOAC INTERNATIONAL required sample size to validate an analytical method are discussed. In addition, formulas to estimate the uncertainties of (Sr and S(R)) were derived and are provided as supporting documentation. Formula for the Number of Replicates Required for a Specified Margin of Relative Error in the Estimate of the Repeatability Standard Deviation.

Improving the accuracy of livestock distribution estimates through spatial interpolation.

PubMed

Bryssinckx, Ward; Ducheyne, Els; Muhwezi, Bernard; Godfrey, Sunday; Mintiens, Koen; Leirs, Herwig; Hendrickx, Guy

2012-11-01

Animal distribution maps serve many purposes such as estimating transmission risk of zoonotic pathogens to both animals and humans. The reliability and usability of such maps is highly dependent on the quality of the input data. However, decisions on how to perform livestock surveys are often based on previous work without considering possible consequences. A better understanding of the impact of using different sample designs and processing steps on the accuracy of livestock distribution estimates was acquired through iterative experiments using detailed survey. The importance of sample size, sample design and aggregation is demonstrated and spatial interpolation is presented as a potential way to improve cattle number estimates. As expected, results show that an increasing sample size increased the precision of cattle number estimates but these improvements were mainly seen when the initial sample size was relatively low (e.g. a median relative error decrease of 0.04% per sampled parish for sample sizes below 500 parishes). For higher sample sizes, the added value of further increasing the number of samples declined rapidly (e.g. a median relative error decrease of 0.01% per sampled parish for sample sizes above 500 parishes. When a two-stage stratified sample design was applied to yield more evenly distributed samples, accuracy levels were higher for low sample densities and stabilised at lower sample sizes compared to one-stage stratified sampling. Aggregating the resulting cattle number estimates yielded significantly more accurate results because of averaging under- and over-estimates (e.g. when aggregating cattle number estimates from subcounty to district level, P <0.009 based on a sample of 2,077 parishes using one-stage stratified samples). During aggregation, area-weighted mean values were assigned to higher administrative unit levels. However, when this step is preceded by a spatial interpolation to fill in missing values in non-sampled areas, accuracy is improved remarkably. This counts especially for low sample sizes and spatially even distributed samples (e.g. P <0.001 for a sample of 170 parishes using one-stage stratified sampling and aggregation on district level). Whether the same observations apply on a lower spatial scale should be further investigated.

Sample Size Calculations for Population Size Estimation Studies Using Multiplier Methods With Respondent-Driven Sampling Surveys.

PubMed

Fearon, Elizabeth; Chabata, Sungai T; Thompson, Jennifer A; Cowan, Frances M; Hargreaves, James R

2017-09-14

While guidance exists for obtaining population size estimates using multiplier methods with respondent-driven sampling surveys, we lack specific guidance for making sample size decisions. To guide the design of multiplier method population size estimation studies using respondent-driven sampling surveys to reduce the random error around the estimate obtained. The population size estimate is obtained by dividing the number of individuals receiving a service or the number of unique objects distributed (M) by the proportion of individuals in a representative survey who report receipt of the service or object (P). We have developed an approach to sample size calculation, interpreting methods to estimate the variance around estimates obtained using multiplier methods in conjunction with research into design effects and respondent-driven sampling. We describe an application to estimate the number of female sex workers in Harare, Zimbabwe. There is high variance in estimates. Random error around the size estimate reflects uncertainty from M and P, particularly when the estimate of P in the respondent-driven sampling survey is low. As expected, sample size requirements are higher when the design effect of the survey is assumed to be greater. We suggest a method for investigating the effects of sample size on the precision of a population size estimate obtained using multipler methods and respondent-driven sampling. Uncertainty in the size estimate is high, particularly when P is small, so balancing against other potential sources of bias, we advise researchers to consider longer service attendance reference periods and to distribute more unique objects, which is likely to result in a higher estimate of P in the respondent-driven sampling survey. ©Elizabeth Fearon, Sungai T Chabata, Jennifer A Thompson, Frances M Cowan, James R Hargreaves. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 14.09.2017.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barbee, D; McCarthy, A; Galavis, P

Purpose: Errors found during initial physics plan checks frequently require replanning and reprinting, resulting decreased departmental efficiency. Additionally, errors may be missed during physics checks, resulting in potential treatment errors or interruption. This work presents a process control created using the Eclipse Scripting API (ESAPI) enabling dosimetrists and physicists to detect potential errors in the Eclipse treatment planning system prior to performing any plan approvals or printing. Methods: Potential failure modes for five categories were generated based on available ESAPI (v11) patient object properties: Images, Contours, Plans, Beams, and Dose. An Eclipse script plugin (PlanCheck) was written in C# tomore » check errors most frequently observed clinically in each of the categories. The PlanCheck algorithms were devised to check technical aspects of plans, such as deliverability (e.g. minimum EDW MUs), in addition to ensuring that policy and procedures relating to planning were being followed. The effect on clinical workflow efficiency was measured by tracking the plan document error rate and plan revision/retirement rates in the Aria database over monthly intervals. Results: The number of potential failure modes the PlanCheck script is currently capable of checking for in the following categories: Images (6), Contours (7), Plans (8), Beams (17), and Dose (4). Prior to implementation of the PlanCheck plugin, the observed error rates in errored plan documents and revised/retired plans in the Aria database was 20% and 22%, respectively. Error rates were seen to decrease gradually over time as adoption of the script improved. Conclusion: A process control created using the Eclipse scripting API enabled plan checks to occur within the planning system, resulting in reduction in error rates and improved efficiency. Future work includes: initiating full FMEA for planning workflow, extending categories to include additional checks outside of ESAPI via Aria database queries, and eventual automated plan checks.« less

Parametric Modulation of Error-Related ERP Components by the Magnitude of Visuo-Motor Mismatch

ERIC Educational Resources Information Center

Vocat, Roland; Pourtois, Gilles; Vuilleumier, Patrik

2011-01-01

Errors generate typical brain responses, characterized by two successive event-related potentials (ERP) following incorrect action: the error-related negativity (ERN) and the positivity error (Pe). However, it is unclear whether these error-related responses are sensitive to the magnitude of the error, or instead show all-or-none effects. We…

Reducing Diagnostic Errors through Effective Communication: Harnessing the Power of Information Technology

PubMed Central

Naik, Aanand Dinkar; Rao, Raghuram; Petersen, Laura Ann

2008-01-01

Diagnostic errors are poorly understood despite being a frequent cause of medical errors. Recent efforts have aimed to advance the "basic science" of diagnostic error prevention by tracing errors to their most basic origins. Although a refined theory of diagnostic error prevention will take years to formulate, we focus on communication breakdown, a major contributor to diagnostic errors and an increasingly recognized preventable factor in medical mishaps. We describe a comprehensive framework that integrates the potential sources of communication breakdowns within the diagnostic process and identifies vulnerable steps in the diagnostic process where various types of communication breakdowns can precipitate error. We then discuss potential information technology-based interventions that may have efficacy in preventing one or more forms of these breakdowns. These possible intervention strategies include using new technologies to enhance communication between health providers and health systems, improve patient involvement, and facilitate management of information in the medical record. PMID:18373151

Spatial and temporal variability of the overall error of National Atmospheric Deposition Program measurements determined by the USGS collocated-sampler program, water years 1989-2001

USGS Publications Warehouse

Wetherbee, G.A.; Latysh, N.E.; Gordon, J.D.

2005-01-01

Data from the U.S. Geological Survey (USGS) collocated-sampler program for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) are used to estimate the overall error of NADP/NTN measurements. Absolute errors are estimated by comparison of paired measurements from collocated instruments. Spatial and temporal differences in absolute error were identified and are consistent with longitudinal distributions of NADP/NTN measurements and spatial differences in precipitation characteristics. The magnitude of error for calcium, magnesium, ammonium, nitrate, and sulfate concentrations, specific conductance, and sample volume is of minor environmental significance to data users. Data collected after a 1994 sample-handling protocol change are prone to less absolute error than data collected prior to 1994. Absolute errors are smaller during non-winter months than during winter months for selected constituents at sites where frozen precipitation is common. Minimum resolvable differences are estimated for different regions of the USA to aid spatial and temporal watershed analyses.

Putting Meaning Back Into the Mean: A Comment on the Misuse of Elementary Statistics in a Sample of Manuscripts Submitted to Clinical Therapeutics.

PubMed

Forrester, Janet E

2015-12-01

Errors in the statistical presentation and analyses of data in the medical literature remain common despite efforts to improve the review process, including the creation of guidelines for authors and the use of statistical reviewers. This article discusses common elementary statistical errors seen in manuscripts recently submitted to Clinical Therapeutics and describes some ways in which authors and reviewers can identify errors and thus correct them before publication. A nonsystematic sample of manuscripts submitted to Clinical Therapeutics over the past year was examined for elementary statistical errors. Clinical Therapeutics has many of the same errors that reportedly exist in other journals. Authors require additional guidance to avoid elementary statistical errors and incentives to use the guidance. Implementation of reporting guidelines for authors and reviewers by journals such as Clinical Therapeutics may be a good approach to reduce the rate of statistical errors. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.

Ensemble Data Assimilation Without Ensembles: Methodology and Application to Ocean Data Assimilation

NASA Technical Reports Server (NTRS)

Keppenne, Christian L.; Rienecker, Michele M.; Kovach, Robin M.; Vernieres, Guillaume

2013-01-01

Two methods to estimate background error covariances for data assimilation are introduced. While both share properties with the ensemble Kalman filter (EnKF), they differ from it in that they do not require the integration of multiple model trajectories. Instead, all the necessary covariance information is obtained from a single model integration. The first method is referred-to as SAFE (Space Adaptive Forecast error Estimation) because it estimates error covariances from the spatial distribution of model variables within a single state vector. It can thus be thought of as sampling an ensemble in space. The second method, named FAST (Flow Adaptive error Statistics from a Time series), constructs an ensemble sampled from a moving window along a model trajectory. The underlying assumption in these methods is that forecast errors in data assimilation are primarily phase errors in space and/or time.

Two-sample binary phase 2 trials with low type I error and low sample size.

PubMed

Litwin, Samuel; Basickes, Stanley; Ross, Eric A

2017-04-30

We address design of two-stage clinical trials comparing experimental and control patients. Our end point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p 0 and alternative that it is p 0 among controls and p 1  > p 0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E⩾m, with two-sample rules of the form E - C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Statistical approaches to account for false-positive errors in environmental DNA samples.

PubMed

Lahoz-Monfort, José J; Guillera-Arroita, Gurutzeta; Tingley, Reid

2016-05-01

Environmental DNA (eDNA) sampling is prone to both false-positive and false-negative errors. We review statistical methods to account for such errors in the analysis of eDNA data and use simulations to compare the performance of different modelling approaches. Our simulations illustrate that even low false-positive rates can produce biased estimates of occupancy and detectability. We further show that removing or classifying single PCR detections in an ad hoc manner under the suspicion that such records represent false positives, as sometimes advocated in the eDNA literature, also results in biased estimation of occupancy, detectability and false-positive rates. We advocate alternative approaches to account for false-positive errors that rely on prior information, or the collection of ancillary detection data at a subset of sites using a sampling method that is not prone to false-positive errors. We illustrate the advantages of these approaches over ad hoc classifications of detections and provide practical advice and code for fitting these models in maximum likelihood and Bayesian frameworks. Given the severe bias induced by false-negative and false-positive errors, the methods presented here should be more routinely adopted in eDNA studies. © 2015 John Wiley & Sons Ltd.

Comparison of structural and least-squares lines for estimating geologic relations

USGS Publications Warehouse

Williams, G.P.; Troutman, B.M.

1990-01-01

Two different goals in fitting straight lines to data are to estimate a "true" linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating "true" straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal-predicting the dependent variable-OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples. ?? 1990 International Association for Mathematical Geology.

Cognitive flexibility correlates with gambling severity in young adults.

PubMed

Leppink, Eric W; Redden, Sarah A; Chamberlain, Samuel R; Grant, Jon E

2016-10-01

Although gambling disorder (GD) is often characterized as a problem of impulsivity, compulsivity has recently been proposed as a potentially important feature of addictive disorders. The present analysis assessed the neurocognitive and clinical relationship between compulsivity on gambling behavior. A sample of 552 non-treatment seeking gamblers age 18-29 was recruited from the community for a study on gambling in young adults. Gambling severity levels included both casual and disordered gamblers. All participants completed the Intra/Extra-Dimensional Set Shift (IED) task, from which the total adjusted errors were correlated with gambling severity measures, and linear regression modeling was used to assess three error measures from the task. The present analysis found significant positive correlations between problems with cognitive flexibility and gambling severity (reflected by the number of DSM-5 criteria, gambling frequency, amount of money lost in the past year, and gambling urge/behavior severity). IED errors also showed a positive correlation with self-reported compulsive behavior scores. A significant correlation was also found between IED errors and non-planning impulsivity from the BIS. Linear regression models based on total IED errors, extra-dimensional (ED) shift errors, or pre-ED shift errors indicated that these factors accounted for a significant portion of the variance noted in several variables. These findings suggest that cognitive flexibility may be an important consideration in the assessment of gamblers. Results from correlational and linear regression analyses support this possibility, but the exact contributions of both impulsivity and cognitive flexibility remain entangled. Future studies will ideally be able to assess the longitudinal relationships between gambling, compulsivity, and impulsivity, helping to clarify the relative contributions of both impulsive and compulsive features. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reducing sampling error in faecal egg counts from black rhinoceros (Diceros bicornis).

PubMed

Stringer, Andrew P; Smith, Diane; Kerley, Graham I H; Linklater, Wayne L

2014-04-01

Faecal egg counts (FECs) are commonly used for the non-invasive assessment of parasite load within hosts. Sources of error, however, have been identified in laboratory techniques and sample storage. Here we focus on sampling error. We test whether a delay in sample collection can affect FECs, and estimate the number of samples needed to reliably assess mean parasite abundance within a host population. Two commonly found parasite eggs in black rhinoceros (Diceros bicornis) dung, strongyle-type nematodes and Anoplocephala gigantea, were used. We find that collection of dung from the centre of faecal boluses up to six hours after defecation does not affect FECs. More than nine samples were needed to greatly improve confidence intervals of the estimated mean parasite abundance within a host population. These results should improve the cost-effectiveness and efficiency of sampling regimes, and support the usefulness of FECs when used for the non-invasive assessment of parasite abundance in black rhinoceros populations.

Adventures in Uncertainty: An Empirical Investigation of the Use of a Taylor's Series Approximation for the Assessment of Sampling Errors in Educational Research.

ERIC Educational Resources Information Center

Wilson, Mark

This study investigates the accuracy of the Woodruff-Causey technique for estimating sampling errors for complex statistics. The technique may be applied when data are collected by using multistage clustered samples. The technique was chosen for study because of its relevance to the correct use of multivariate analyses in educational survey…

Decreased Leftward ‘Aiming’ Motor-Intentional Spatial Cuing in Traumatic Brain Injury

PubMed Central

Wagner, Daymond; Eslinger, Paul J.; Barrett, A. M.

2016-01-01

Objective To characterize the mediation of attention and action in space following traumatic brain injury (TBI). Method Two exploratory analyses were performed to determine the influence of spatial ‘Aiming’ motor versus spatial ‘Where’ bias on line bisection in TBI participants. The first experiment compared performance according to severity and location of injury in TBI. The second experiment examined bisection performance in a larger TBI sample against a matched control group. In both experiments, participants bisected lines in near and far space using an apparatus that allowed for the fractionation of spatial Aiming versus Where error components. Results In the first experiment, participants with severe injuries tended to incur rightward error when starting from the right in far space, compared with participants with mild injuries. In the second experiment, when performance was examined at the individual level, more participants with TBI tended to incur rightward motor error compared to controls. Conclusions TBI may cause frontal-subcortical cognitive dysfunction and asymmetric motor perseveration, affecting spatial Aiming bias on line bisection. Potential effects on real-world function need further investigation. PMID:27571220

Performance appraisal of VAS radiometry for GOES-4, -5 and -6

NASA Technical Reports Server (NTRS)

Chesters, D.; Robinson, W. D.

1983-01-01

The first three VISSR Atmospheric Sounders (VAS) were launched on GOES-4, -5, and -6 in 1980, 1981 and 1983. Postlaunch radiometric performance is assessed for noise, biases, registration and reliability, with special attention to calibration and problems in the data processing chain. The postlaunch performance of the VAS radiometer meets its prelaunch design specifications, particularly those related to image formation and noise reduction. The best instrument is carried on GOES-5, currently operational as GOES-EAST. Single sample noise is lower than expected, especially for the small longwave and large shortwave detectors. Detector to detector offsets are correctable to within the resolution limits of the instrument. Truncation, zero point and droop errors are insignificant. Absolute calibration errors, estimated from HIRS and from radiation transfer calculations, indicate moderate, but stable biases. Relative calibration errors from scanline to scanline are noticeable, but meet sounding requirements for temporarily and spatially averaged sounding fields of view. The VAS instrument is a potentially useful radiometer for mesoscale sounding operations. Image quality is very good. Soundings derived from quality controlled data meet prelaunch requirements when calculated with noise and bias resistant algorithms.

Self-reported and observed punitive parenting prospectively predicts increased error-related brain activity in six-year-old children

PubMed Central

Meyer, Alexandria; Proudfit, Greg Hajcak; Bufferd, Sara J.; Kujawa, Autumn J.; Laptook, Rebecca S.; Torpey, Dana C.; Klein, Daniel N.

2017-01-01

The error-related negativity (ERN) is a negative deflection in the event-related potential (ERP) occurring approximately 50 ms after error commission at fronto-central electrode sites and is thought to reflect the activation of a generic error monitoring system. Several studies have reported an increased ERN in clinically anxious children, and suggest that anxious children are more sensitive to error commission—although the mechanisms underlying this association are not clear. We have previously found that punishing errors results in a larger ERN, an effect that persists after punishment ends. It is possible that learning-related experiences that impact sensitivity to errors may lead to an increased ERN. In particular, punitive parenting might sensitize children to errors and increase their ERN. We tested this possibility in the current study by prospectively examining the relationship between parenting style during early childhood and children’s ERN approximately three years later. Initially, 295 parents and children (approximately 3 years old) participated in a structured observational measure of parenting behavior, and parents completed a self-report measure of parenting style. At a follow-up assessment approximately three years later, the ERN was elicited during a Go/No-Go task, and diagnostic interviews were completed with parents to assess child psychopathology. Results suggested that both observational measures of hostile parenting and self-report measures of authoritarian parenting style uniquely predicted a larger ERN in children 3 years later. We previously reported that children in this sample with anxiety disorders were characterized by an increased ERN. A mediation analysis indicated that ERN magnitude mediated the relationship between harsh parenting and child anxiety disorder. Results suggest that parenting may shape children’s error processing through environmental conditioning and thereby risk for anxiety, although future work is needed to confirm this hypothesis. PMID:25092483

Measurement Error and Equating Error in Power Analysis

ERIC Educational Resources Information Center

Phillips, Gary W.; Jiang, Tao

2016-01-01

Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of…

New method for stock-tank oil compositional analysis.

PubMed

McAndrews, Kristine; Nighswander, John; Kotzakoulakis, Konstantin; Ross, Paul; Schroeder, Helmut

2009-01-01

A new method for accurately determining stock-tank oil composition to normal pentatriacontane using gas chromatography is developed and validated. The new method addresses the potential errors associated with the traditional equipment and technique employed for extended hydrocarbon gas chromatography outside a controlled laboratory environment, such as on an offshore oil platform. In particular, the experimental measurement of stock-tank oil molecular weight with the freezing point depression technique and the use of an internal standard to find the unrecovered sample fraction are replaced with correlations for estimating these properties. The use of correlations reduces the number of necessary experimental steps in completing the required sample preparation and analysis, resulting in reduced uncertainty in the analysis.

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis

PubMed Central

Lin, Johnny; Bentler, Peter M.

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne’s asymptotically distribution-free method and Satorra Bentler’s mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler’s statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby’s study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic. PMID:23144511

[Improving blood safety: errors management in transfusion medicine].

PubMed

Bujandrić, Nevenka; Grujić, Jasmina; Krga-Milanović, Mirjana

2014-01-01

The concept of blood safety includes the entire transfusion chain starting with the collection of blood from the blood donor, and ending with blood transfusion to the patient. The concept involves quality management system as the systematic monitoring of adverse reactions and incidents regarding the blood donor or patient. Monitoring of near-miss errors show the critical points in the working process and increase transfusion safety. The aim of the study was to present the analysis results of adverse and unexpected events in transfusion practice with a potential risk to the health of blood donors and patients. One-year retrospective study was based on the collection, analysis and interpretation of written reports on medical errors in the Blood Transfusion Institute of Vojvodina. Errors were distributed according to the type, frequency and part of the working process where they occurred. Possible causes and corrective actions were described for each error. The study showed that there were not errors with potential health consequences for the blood donor/patient. Errors with potentially damaging consequences for patients were detected throughout the entire transfusion chain. Most of the errors were identified in the preanalytical phase. The human factor was responsible for the largest number of errors. Error reporting system has an important role in the error management and the reduction of transfusion-related risk of adverse events and incidents. The ongoing analysis reveals the strengths and weaknesses of the entire process and indicates the necessary changes. Errors in transfusion medicine can be avoided in a large percentage and prevention is cost-effective, systematic and applicable.

Exploring the influence of workplace supports and relationships on safe medication practice: A pilot study of Australian graduate nurses.

PubMed

Sahay, Ashlyn; Hutchinson, Marie; East, Leah

2015-05-01

Despite the growing awareness of the benefits of positive workplace climates, unsupportive and disruptive workplace behaviours are widespread in health care organisations. Recent graduate nurses, who are often new to a workplace, are particularly vulnerable in unsupportive climates, and are also recognised to be at higher risk for medication errors. Investigate the association between workplace supports and relationships and safe medication practice among graduate nurses. Exploratory study using quantitative survey with a convenience sample of 58 nursing graduates in two Australian States. Online survey focused on graduates' self-reported medication errors, safe medication practice and the nature of workplace supports and relationships. Spearman's correlations identified that unsupportive workplace relationships were inversely related to graduate nurse medication errors and erosion of safe medication practices, while supportive Nurse Unit Manager and supportive work team relationships positively influenced safe medication practice among graduates. Workplace supports and relationships are potentially both the cause and solution to graduate nurse medication errors and safe medication practices. The findings develop further understanding about the impact of unsupportive and disruptive behaviours on patient safety and draw attention to the importance of undergraduate and continuing education strategies that promote positive workplace behaviours and graduate resilience. Copyright © 2015 Elsevier Ltd. All rights reserved.

Managing the Pre- and Post-analytical Phases of the Total Testing Process

PubMed Central

2012-01-01

For many years, the clinical laboratory's focus on analytical quality has resulted in an error rate of 4-5 sigma, which surpasses most other areas in healthcare. However, greater appreciation of the prevalence of errors in the pre- and post-analytical phases and their potential for patient harm has led to increasing requirements for laboratories to take greater responsibility for activities outside their immediate control. Accreditation bodies such as the Joint Commission International (JCI) and the College of American Pathologists (CAP) now require clear and effective procedures for patient/sample identification and communication of critical results. There are a variety of free on-line resources available to aid in managing the extra-analytical phase and the recent publication of quality indicators and proposed performance levels by the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) working group on laboratory errors and patient safety provides particularly useful benchmarking data. Managing the extra-laboratory phase of the total testing cycle is the next challenge for laboratory medicine. By building on its existing quality management expertise, quantitative scientific background and familiarity with information technology, the clinical laboratory is well suited to play a greater role in reducing errors and improving patient safety outside the confines of the laboratory. PMID:22259773

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts

PubMed Central

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2018-01-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments. PMID:29375930

Auditing the Assignments of Top-Level Semantic Types in the UMLS Semantic Network to UMLS Concepts.

PubMed

He, Zhe; Perl, Yehoshua; Elhanan, Gai; Chen, Yan; Geller, James; Bian, Jiang

2017-11-01

The Unified Medical Language System (UMLS) is an important terminological system. By the policy of its curators, each concept of the UMLS should be assigned the most specific Semantic Types (STs) in the UMLS Semantic Network (SN). Hence, the Semantic Types of most UMLS concepts are assigned at or near the bottom (leaves) of the UMLS Semantic Network. While most ST assignments are correct, some errors do occur. Therefore, Quality Assurance efforts of UMLS curators for ST assignments should concentrate on automatically detected sets of UMLS concepts with higher error rates than random sets. In this paper, we investigate the assignments of top-level semantic types in the UMLS semantic network to concepts, identify potential erroneous assignments, define four categories of errors, and thus provide assistance to curators of the UMLS to avoid these assignments errors. Human experts analyzed samples of concepts assigned 10 of the top-level semantic types and categorized the erroneous ST assignments into these four logical categories. Two thirds of the concepts assigned these 10 top-level semantic types are erroneous. Our results demonstrate that reviewing top-level semantic type assignments to concepts provides an effective way for UMLS quality assurance, comparing to reviewing a random selection of semantic type assignments.

Scalable effective-temperature reduction for quantum annealers via nested quantum annealing correction

NASA Astrophysics Data System (ADS)

Vinci, Walter; Lidar, Daniel A.

2018-02-01

Nested quantum annealing correction (NQAC) is an error-correcting scheme for quantum annealing that allows for the encoding of a logical qubit into an arbitrarily large number of physical qubits. The encoding replaces each logical qubit by a complete graph of degree C . The nesting level C represents the distance of the error-correcting code and controls the amount of protection against thermal and control errors. Theoretical mean-field analyses and empirical data obtained with a D-Wave Two quantum annealer (supporting up to 512 qubits) showed that NQAC has the potential to achieve a scalable effective-temperature reduction, Teff˜C-η , with 0 <η ≤2 . We confirm that this scaling is preserved when NQAC is tested on a D-Wave 2000Q device (supporting up to 2048 qubits). In addition, we show that NQAC can also be used in sampling problems to lower the effective-temperature of a quantum annealer. Such effective-temperature reduction is relevant for machine-learning applications. Since we demonstrate that NQAC achieves error correction via a reduction of the effective-temperature of the quantum annealing device, our results address the problem of the "temperature scaling law for quantum annealers," which requires the temperature of quantum annealers to be reduced as problems of larger sizes are attempted to be solved.

Magnitude error bounds for sampled-data frequency response obtained from the truncation of an infinite series, and compensator improvement program

NASA Technical Reports Server (NTRS)

Mitchell, J. R.

1972-01-01

The frequency response method of analyzing control system performance is discussed, and the difficulty of obtaining the sampled frequency response of the continuous system is considered. An upper bound magnitude error equation is obtained which yields reasonable estimates of the actual error. Finalization of the compensator improvement program is also reported, and the program was used to design compensators for Saturn 5/S1-C dry workshop and Saturn 5/S1-C Skylab.

The use of error-category mapping in pharmacokinetic model analysis of dynamic contrast-enhanced MRI data.

PubMed

Gill, Andrew B; Anandappa, Gayathri; Patterson, Andrew J; Priest, Andrew N; Graves, Martin J; Janowitz, Tobias; Jodrell, Duncan I; Eisen, Tim; Lomas, David J

2015-02-01

This study introduces the use of 'error-category mapping' in the interpretation of pharmacokinetic (PK) model parameter results derived from dynamic contrast-enhanced (DCE-) MRI data. Eleven patients with metastatic renal cell carcinoma were enrolled in a multiparametric study of the treatment effects of bevacizumab. For the purposes of the present analysis, DCE-MRI data from two identical pre-treatment examinations were analysed by application of the extended Tofts model (eTM), using in turn a model arterial input function (AIF), an individually-measured AIF and a sample-average AIF. PK model parameter maps were calculated. Errors in the signal-to-gadolinium concentration ([Gd]) conversion process and the model-fitting process itself were assigned to category codes on a voxel-by-voxel basis, thereby forming a colour-coded 'error-category map' for each imaged slice. These maps were found to be repeatable between patient visits and showed that the eTM converged adequately in the majority of voxels in all the tumours studied. However, the maps also clearly indicated sub-regions of low Gd uptake and of non-convergence of the model in nearly all tumours. The non-physical condition ve ≥ 1 was the most frequently indicated error category and appeared sensitive to the form of AIF used. This simple method for visualisation of errors in DCE-MRI could be used as a routine quality-control technique and also has the potential to reveal otherwise hidden patterns of failure in PK model applications. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197

PubMed Central

Bedini, José Luis; Wallace, Jane F.; Pardo, Scott; Petruschke, Thorsten

2015-01-01

Background: Blood glucose monitoring is an essential component of diabetes management. Inaccurate blood glucose measurements can severely impact patients’ health. This study evaluated the performance of 3 blood glucose monitoring systems (BGMS), Contour® Next USB, FreeStyle InsuLinx®, and OneTouch® Verio™ IQ, under routine hospital conditions. Methods: Venous blood samples (N = 236) obtained for routine laboratory procedures were collected at a Spanish hospital, and blood glucose (BG) concentrations were measured with each BGMS and with the available reference (hexokinase) method. Accuracy of the 3 BGMS was compared according to ISO 15197:2013 accuracy limit criteria, by mean absolute relative difference (MARD), consensus error grid (CEG) and surveillance error grid (SEG) analyses, and an insulin dosing error model. Results: All BGMS met the accuracy limit criteria defined by ISO 15197:2013. While all measurements of the 3 BGMS were within low-risk zones in both error grid analyses, the Contour Next USB showed significantly smaller MARDs between reference values compared to the other 2 BGMS. Insulin dosing errors were lowest for the Contour Next USB than compared to the other systems. Conclusions: All BGMS fulfilled ISO 15197:2013 accuracy limit criteria and CEG criterion. However, taking together all analyses, differences in performance of potential clinical relevance may be observed. Results showed that Contour Next USB had lowest MARD values across the tested glucose range, as compared with the 2 other BGMS. CEG and SEG analyses as well as calculation of the hypothetical bolus insulin dosing error suggest a high accuracy of the Contour Next USB. PMID:26445813

An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rothenberg, Daniel; Wang, Chien

We describe an emulator of a detailed cloud parcel model which has been trained to assess droplet nucleation from a complex, multimodal aerosol size distribution simulated by a global aerosol–climate model. The emulator is constructed using a sensitivity analysis approach (polynomial chaos expansion) which reproduces the behavior of the targeted parcel model across the full range of aerosol properties and meteorology simulated by the parent climate model. An iterative technique using aerosol fields sampled from a global model is used to identify the critical aerosol size distribution parameters necessary for accurately predicting activation. Across the large parameter space used tomore » train them, the emulators estimate cloud droplet number concentration (CDNC) with a mean relative error of 9.2% for aerosol populations without giant cloud condensation nuclei (CCN) and 6.9% when including them. Versus a parcel model driven by those same aerosol fields, the best-performing emulator has a mean relative error of 4.6%, which is comparable with two commonly used activation schemes also evaluated here (which have mean relative errors of 2.9 and 6.7%, respectively). We identify the potential for regional biases in modeled CDNC, particularly in oceanic regimes, where our best-performing emulator tends to overpredict by 7%, whereas the reference activation schemes range in mean relative error from -3 to 7%. The emulators which include the effects of giant CCN are more accurate in continental regimes (mean relative error of 0.3%) but strongly overestimate CDNC in oceanic regimes by up to 22%, particularly in the Southern Ocean. Finally, the biases in CDNC resulting from the subjective choice of activation scheme could potentially influence the magnitude of the indirect effect diagnosed from the model incorporating it.« less

An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

DOE PAGES

Rothenberg, Daniel; Wang, Chien

2017-04-27

We describe an emulator of a detailed cloud parcel model which has been trained to assess droplet nucleation from a complex, multimodal aerosol size distribution simulated by a global aerosol–climate model. The emulator is constructed using a sensitivity analysis approach (polynomial chaos expansion) which reproduces the behavior of the targeted parcel model across the full range of aerosol properties and meteorology simulated by the parent climate model. An iterative technique using aerosol fields sampled from a global model is used to identify the critical aerosol size distribution parameters necessary for accurately predicting activation. Across the large parameter space used tomore » train them, the emulators estimate cloud droplet number concentration (CDNC) with a mean relative error of 9.2% for aerosol populations without giant cloud condensation nuclei (CCN) and 6.9% when including them. Versus a parcel model driven by those same aerosol fields, the best-performing emulator has a mean relative error of 4.6%, which is comparable with two commonly used activation schemes also evaluated here (which have mean relative errors of 2.9 and 6.7%, respectively). We identify the potential for regional biases in modeled CDNC, particularly in oceanic regimes, where our best-performing emulator tends to overpredict by 7%, whereas the reference activation schemes range in mean relative error from -3 to 7%. The emulators which include the effects of giant CCN are more accurate in continental regimes (mean relative error of 0.3%) but strongly overestimate CDNC in oceanic regimes by up to 22%, particularly in the Southern Ocean. Finally, the biases in CDNC resulting from the subjective choice of activation scheme could potentially influence the magnitude of the indirect effect diagnosed from the model incorporating it.« less

Physician Preferences to Communicate Neuropsychological Results: Comparison of Qualitative Descriptors and a Proposal to Reduce Communication Errors.

PubMed

Schoenberg, Mike R; Osborn, Katie E; Mahone, E Mark; Feigon, Maia; Roth, Robert M; Pliskin, Neil H

2017-11-08

Errors in communication are a leading cause of medical errors. A potential source of error in communicating neuropsychological results is confusion in the qualitative descriptors used to describe standardized neuropsychological data. This study sought to evaluate the extent to which medical consumers of neuropsychological assessments believed that results/findings were not clearly communicated. In addition, preference data for a variety of qualitative descriptors commonly used to communicate normative neuropsychological test scores were obtained. Preference data were obtained for five qualitative descriptor systems as part of a larger 36-item internet-based survey of physician satisfaction with neuropsychological services. A new qualitative descriptor system termed the Simplified Qualitative Classification System (Q-Simple) was proposed to reduce the potential for communication errors using seven terms: very superior, superior, high average, average, low average, borderline, and abnormal/impaired. A non-random convenience sample of 605 clinicians identified from four United States academic medical centers from January 1, 2015 through January 7, 2016 were invited to participate. A total of 182 surveys were completed. A minority of clinicians (12.5%) indicated that neuropsychological study results were not clearly communicated. When communicating neuropsychological standardized scores, the two most preferred qualitative descriptor systems were by Heaton and colleagues (26%) and a newly proposed Q-simple system (22%). Comprehensive norms for an extended Halstead-Reitan battery: Demographic corrections, research findings, and clinical applications. Odessa, TX: Psychological Assessment Resources) (26%) and the newly proposed Q-Simple system (22%). Initial findings highlight the need to improve and standardize communication of neuropsychological results. These data offer initial guidance for preferred terms to communicate test results and form a foundation for more standardized practice among neuropsychologists. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Spectral CT of the extremities with a silicon strip photon counting detector

NASA Astrophysics Data System (ADS)

Sisniega, A.; Zbijewski, W.; Stayman, J. W.; Xu, J.; Taguchi, K.; Siewerdsen, J. H.

2015-03-01

Purpose: Photon counting x-ray detectors (PCXDs) are an important emerging technology for spectral imaging and material differentiation with numerous potential applications in diagnostic imaging. We report development of a Si-strip PCXD system originally developed for mammography with potential application to spectral CT of musculoskeletal extremities, including challenges associated with sparse sampling, spectral calibration, and optimization for higher energy x-ray beams. Methods: A bench-top CT system was developed incorporating a Si-strip PCXD, fixed anode x-ray source, and rotational and translational motions to execute complex acquisition trajectories. Trajectories involving rotation and translation combined with iterative reconstruction were investigated, including single and multiple axial scans and longitudinal helical scans. The system was calibrated to provide accurate spectral separation in dual-energy three-material decomposition of soft-tissue, bone, and iodine. Image quality and decomposition accuracy were assessed in experiments using a phantom with pairs of bone and iodine inserts (3, 5, 15 and 20 mm) and an anthropomorphic wrist. Results: The designed trajectories improved the sampling distribution from 56% minimum sampling of voxels to 75%. Use of iterative reconstruction (viz., penalized likelihood with edge preserving regularization) in combination with such trajectories resulted in a very low level of artifacts in images of the wrist. For large bone or iodine inserts (>5 mm diameter), the error in the estimated material concentration was <16% for (50 mg/mL) bone and <8% for (5 mg/mL) iodine with strong regularization. For smaller inserts, errors of 20-40% were observed and motivate improved methods for spectral calibration and optimization of the edge-preserving regularizer. Conclusion: Use of PCXDs for three-material decomposition in joint imaging proved feasible through a combination of rotation-translation acquisition trajectories and iterative reconstruction with optimized regularization.

Purification of Logic-Qubit Entanglement.

PubMed

Zhou, Lan; Sheng, Yu-Bo

2016-07-05

Recently, the logic-qubit entanglement shows its potential application in future quantum communication and quantum network. However, the entanglement will suffer from the noise and decoherence. In this paper, we will investigate the first entanglement purification protocol for logic-qubit entanglement. We show that both the bit-flip error and phase-flip error in logic-qubit entanglement can be well purified. Moreover, the bit-flip error in physical-qubit entanglement can be completely corrected. The phase-flip in physical-qubit entanglement error equals to the bit-flip error in logic-qubit entanglement, which can also be purified. This entanglement purification protocol may provide some potential applications in future quantum communication and quantum network.

Evaluating morphometric body mass prediction equations with a juvenile human test sample: accuracy and applicability to small-bodied hominins.

PubMed

Walker, Christopher S; Yapuncich, Gabriel S; Sridhar, Shilpa; Cameron, Noël; Churchill, Steven E

2018-02-01

Body mass is an ecologically and biomechanically important variable in the study of hominin biology. Regression equations derived from recent human samples allow for the reasonable prediction of body mass of later, more human-like, and generally larger hominins from hip joint dimensions, but potential differences in hip biomechanics across hominin taxa render their use questionable with some earlier taxa (i.e., Australopithecus spp.). Morphometric prediction equations using stature and bi-iliac breadth avoid this problem, but their applicability to early hominins, some of which differ in both size and proportions from modern adult humans, has not been demonstrated. Here we use mean stature, bi-iliac breadth, and body mass from a global sample of human juveniles ranging in age from 6 to 12 years (n = 530 age- and sex-specific group annual means from 33 countries/regions) to evaluate the accuracy of several published morphometric prediction equations when applied to small humans. Though the body proportions of modern human juveniles likely differ from those of small-bodied early hominins, human juveniles (like fossil hominins) often differ in size and proportions from adult human reference samples and, accordingly, serve as a useful model for assessing the robustness of morphometric prediction equations. Morphometric equations based on adults systematically underpredict body mass in the youngest age groups and moderately overpredict body mass in the older groups, which fall in the body size range of adult Australopithecus (∼26-46 kg). Differences in body proportions, notably the ratio of lower limb length to stature, influence predictive accuracy. Ontogenetic changes in these body proportions likely influence the shift in prediction error (from under- to overprediction). However, because morphometric equations are reasonably accurate when applied to this juvenile test sample, we argue these equations may be used to predict body mass in small-bodied hominins, despite the potential for some error induced by differing body proportions and/or extrapolation beyond the original reference sample range. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-throughput methods for characterizing the mechanical properties of coatings

NASA Astrophysics Data System (ADS)

Siripirom, Chavanin

The characterization of mechanical properties in a combinatorial and high-throughput workflow has been a bottleneck that reduced the speed of the materials development process. High-throughput characterization of the mechanical properties was applied in this research in order to reduce the amount of sample handling and to accelerate the output. A puncture tester was designed and built to evaluate the toughness of materials using an innovative template design coupled with automation. The test is in the form of a circular free-film indentation. A single template contains 12 samples which are tested in a rapid serial approach. Next, the operational principles of a novel parallel dynamic mechanical-thermal analysis instrument were analyzed in detail for potential sources of errors. The test uses a model of a circular bilayer fixed-edge plate deformation. A total of 96 samples can be analyzed simultaneously which provides a tremendous increase in efficiency compared with a conventional dynamic test. The modulus values determined by the system had considerable variation. The errors were observed and improvements to the system were made. A finite element analysis was used to analyze the accuracy given by the closed-form solution with respect to testing geometries, such as thicknesses of the samples. A good control of the thickness of the sample was proven to be crucial to the accuracy and precision of the output. Then, the attempt to correlate the high-throughput experiments and conventional coating testing methods was made. Automated nanoindentation in dynamic mode was found to provide information on the near-surface modulus and could potentially correlate with the pendulum hardness test using the loss tangent component. Lastly, surface characterization of stratified siloxane-polyurethane coatings was carried out with X-ray photoelectron spectroscopy, Rutherford backscattering spectroscopy, transmission electron microscopy, and nanoindentation. The siloxane component segregates to the surface during curing. The distribution of siloxane as a function of thickness into the sample showed differences depending on the formulation parameters. The coatings which had higher siloxane content near the surface were those coatings found to perform well in field tests.

Heterogenic Solid Biofuel Sampling Methodology and Uncertainty Associated with Prompt Analysis

PubMed Central

Pazó, Jose A.; Granada, Enrique; Saavedra, Ángeles; Patiño, David; Collazo, Joaquín

2010-01-01

Accurate determination of the properties of biomass is of particular interest in studies on biomass combustion or cofiring. The aim of this paper is to develop a methodology for prompt analysis of heterogeneous solid fuels with an acceptable degree of accuracy. Special care must be taken with the sampling procedure to achieve an acceptable degree of error and low statistical uncertainty. A sampling and error determination methodology for prompt analysis is presented and validated. Two approaches for the propagation of errors are also given and some comparisons are made in order to determine which may be better in this context. Results show in general low, acceptable levels of uncertainty, demonstrating that the samples obtained in the process are representative of the overall fuel composition. PMID:20559506

Analysis of naturalistic driving videos of fleet services drivers to estimate driver error and potentially distracting behaviors as risk factors for rear-end versus angle crashes.

PubMed

Harland, Karisa K; Carney, Cher; McGehee, Daniel

2016-07-03

The objective of this study was to estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes. Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the 6 s before crash impact. Categorical variables were examined using the Pearson's chi-square test, and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes. Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender, and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (P < .0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior, whereas less than 40% of angle crashes involved these behaviors (P < .01). On average, drivers spent 4.4 s with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% confidence interval [CI], 1.73-5.44) times adjusted higher odds of being potentially distracted than those in angle crashes. Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of drivers' distracting behaviors and errors that may potentially reducing crashes.

Sampling for mercury at subnanogram per litre concentrations for load estimation in rivers

USGS Publications Warehouse

Colman, J.A.; Breault, R.F.

2000-01-01

Estimation of constituent loads in streams requires collection of stream samples that are representative of constituent concentrations, that is, composites of isokinetic multiple verticals collected along a stream transect. An all-Teflon isokinetic sampler (DH-81) cleaned in 75??C, 4 N HCl was tested using blank, split, and replicate samples to assess systematic and random sample contamination by mercury species. Mean mercury concentrations in field-equipment blanks were low: 0.135 ng??L-1 for total mercury (??Hg) and 0.0086 ng??L-1 for monomethyl mercury (MeHg). Mean square errors (MSE) for ??Hg and MeHg duplicate samples collected at eight sampling stations were not statistically different from MSE of samples split in the laboratory, which represent the analytical and splitting error. Low fieldblank concentrations and statistically equal duplicate- and split-sample MSE values indicate that no measurable contamination was occurring during sampling. Standard deviations associated with example mercury load estimations were four to five times larger, on a relative basis, than standard deviations calculated from duplicate samples, indicating that error of the load determination was primarily a function of the loading model used, not of sampling or analytical methods.

Lognormal kriging for the assessment of reliability in groundwater quality control observation networks

USGS Publications Warehouse

Candela, L.; Olea, R.A.; Custodio, E.

1988-01-01

Groundwater quality observation networks are examples of discontinuous sampling on variables presenting spatial continuity and highly skewed frequency distributions. Anywhere in the aquifer, lognormal kriging provides estimates of the variable being sampled and a standard error of the estimate. The average and the maximum standard error within the network can be used to dynamically improve the network sampling efficiency or find a design able to assure a given reliability level. The approach does not require the formulation of any physical model for the aquifer or any actual sampling of hypothetical configurations. A case study is presented using the network monitoring salty water intrusion into the Llobregat delta confined aquifer, Barcelona, Spain. The variable chloride concentration used to trace the intrusion exhibits sudden changes within short distances which make the standard error fairly invariable to changes in sampling pattern and to substantial fluctuations in the number of wells. ?? 1988.

Using beta binomials to estimate classification uncertainty for ensemble models.

PubMed

Clark, Robert D; Liang, Wenkel; Lee, Adam C; Lawless, Michael S; Fraczkiewicz, Robert; Waldman, Marvin

2014-01-01

Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions. Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions. For artificial neural network ensembles (ANNEs) using two different methods for determining ensemble classification - one using vote tallies and the other averaging individual network outputs - we have found that the distribution of predictions across positive vote tallies can be reasonably well-modeled as a beta binomial distribution, as can the distribution of errors. Together, these two distributions can be used to estimate the probability that a given predictive classification will be in error. Large data sets comprised of logP, Ames mutagenicity, and CYP2D6 inhibition data are used to illustrate and validate the method. The distributions of predictions and errors for the training pool accurately predicted the distribution of predictions and errors for large external validation sets, even when the number of positive and negative examples in the training pool were not balanced. Moreover, the likelihood of a given compound being prospectively misclassified as a function of the degree of consensus between networks in the ensemble could in most cases be estimated accurately from the fitted beta binomial distributions for the training pool. Confidence in an individual predictive classification by an ensemble model can be accurately assessed by examining the distributions of predictions and errors as a function of the degree of agreement among the constituent submodels. Further, ensemble uncertainty estimation can often be improved by adjusting the voting or classification threshold based on the parameters of the error distribution. Finally, the profiles for models whose predictive uncertainty estimates are not reliable provide clues to that effect without the need for comparison to an external test set.

#2 - An Empirical Assessment of Exposure Measurement Error and Effect Attenuation in Bi-Pollutant Epidemiologic Models

EPA Science Inventory

Background• Differing degrees of exposure error acrosspollutants• Previous focus on quantifying and accounting forexposure error in single-pollutant models• Examine exposure errors for multiple pollutantsand provide insights on the potential for bias andattenuation...

Forecasting the brittle failure of heterogeneous, porous geomaterials

NASA Astrophysics Data System (ADS)

Vasseur, Jérémie; Wadsworth, Fabian; Heap, Michael; Main, Ian; Lavallée, Yan; Dingwell, Donald

2017-04-01

Heterogeneity develops in magmas during ascent and is dominated by the development of crystal and importantly, bubble populations or pore-network clusters which grow, interact, localize, coalesce, outgas and resorb. Pore-scale heterogeneity is also ubiquitous in sedimentary basin fill during diagenesis. As a first step, we construct numerical simulations in 3D in which randomly generated heterogeneous and polydisperse spheres are placed in volumes and which are permitted to overlap with one another, designed to represent the random growth and interaction of bubbles in a liquid volume. We use these simulated geometries to show that statistical predictions of the inter-bubble lengthscales and evolving bubble surface area or cluster densities can be made based on fundamental percolation theory. As a second step, we take a range of well constrained random heterogeneous rock samples including sandstones, andesites, synthetic partially sintered glass bead samples, and intact glass samples and subject them to a variety of stress loading conditions at a range of temperatures until failure. We record in real time the evolution of the number of acoustic events that precede failure and show that in all scenarios, the acoustic event rate accelerates toward failure, consistent with previous findings. Applying tools designed to forecast the failure time based on these precursory signals, we constrain the absolute error on the forecast time. We find that for all sample types, the error associated with an accurate forecast of failure scales non-linearly with the lengthscale between the pore clusters in the material. Moreover, using a simple micromechanical model for the deformation of porous elastic bodies, we show that the ratio between the equilibrium sub-critical crack length emanating from the pore clusters relative to the inter-pore lengthscale, provides a scaling for the error on forecast accuracy. Thus for the first time we provide a potential quantitative correction for forecasting the failure of porous brittle solids that build the Earth's crust.

Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.

PubMed

Spüler, Martin; Rosenstiel, Wolfgang; Bogdan, Martin

2012-01-01

The goal of a Brain-Computer Interface (BCI) is to control a computer by pure brain activity. Recently, BCIs based on code-modulated visual evoked potentials (c-VEPs) have shown great potential to establish high-performance communication. In this paper we present a c-VEP BCI that uses online adaptation of the classifier to reduce calibration time and increase performance. We compare two different approaches for online adaptation of the system: an unsupervised method and a method that uses the detection of error-related potentials. Both approaches were tested in an online study, in which an average accuracy of 96% was achieved with adaptation based on error-related potentials. This accuracy corresponds to an average information transfer rate of 144 bit/min, which is the highest bitrate reported so far for a non-invasive BCI. In a free-spelling mode, the subjects were able to write with an average of 21.3 error-free letters per minute, which shows the feasibility of the BCI system in a normal-use scenario. In addition we show that a calibration of the BCI system solely based on the detection of error-related potentials is possible, without knowing the true class labels.

A synchronization method for wireless acquisition systems, application to brain computer interfaces.

PubMed

Foerster, M; Bonnet, S; van Langhenhove, A; Porcherot, J; Charvet, G

2013-01-01

A synchronization method for wireless acquisition systems has been developed and implemented on a wireless ECoG recording implant and on a wireless EEG recording helmet. The presented algorithm and hardware implementation allow the precise synchronization of several data streams from several sensor nodes for applications where timing is critical like in event-related potential (ERP) studies. The proposed method has been successfully applied to obtain visual evoked potentials and compared with a reference biosignal amplifier. The control over the exact sampling frequency allows reducing synchronization errors that will otherwise accumulate during a recording. The method is scalable to several sensor nodes communicating with a shared base station.

Review of Pre-Analytical Errors in Oral Glucose Tolerance Testing in a Tertiary Care Hospital.

PubMed

Nanda, Rachita; Patel, Suprava; Sahoo, Sibashish; Mohapatra, Eli

2018-03-13

The pre-pre-analytical and pre-analytical phases form a major chunk of the errors in a laboratory. The process has taken into consideration a very common procedure which is the oral glucose tolerance test to identify the pre-pre-analytical errors. Quality indicators provide evidence of quality, support accountability and help in the decision making of laboratory personnel. The aim of this research is to evaluate pre-analytical performance of the oral glucose tolerance test procedure. An observational study that was conducted overa period of three months, in the phlebotomy and accessioning unit of our laboratory using questionnaire that examined the pre-pre-analytical errors through a scoring system. The pre-analytical phase was analyzed for each sample collected as per seven quality indicators. About 25% of the population gave wrong answer with regard to the question that tested the knowledge of patient preparation. The appropriateness of test result QI-1 had the most error. Although QI-5 for sample collection had a low error rate, it is a very important indicator as any wrongly collected sample can alter the test result. Evaluating the pre-analytical and pre-pre-analytical phase is essential and must be conducted routinely on a yearly basis to identify errors and take corrective action and to facilitate their gradual introduction into routine practice.

Analysis of counting errors in the phase/Doppler particle analyzer

NASA Technical Reports Server (NTRS)

Oldenburg, John R.

1987-01-01

NASA is investigating the application of the Phase Doppler measurement technique to provide improved drop sizing and liquid water content measurements in icing research. The magnitude of counting errors were analyzed because these errors contribute to inaccurate liquid water content measurements. The Phase Doppler Particle Analyzer counting errors due to data transfer losses and coincidence losses were analyzed for data input rates from 10 samples/sec to 70,000 samples/sec. Coincidence losses were calculated by determining the Poisson probability of having more than one event occurring during the droplet signal time. The magnitude of the coincidence loss can be determined, and for less than a 15 percent loss, corrections can be made. The data transfer losses were estimated for representative data transfer rates. With direct memory access enabled, data transfer losses are less than 5 percent for input rates below 2000 samples/sec. With direct memory access disabled losses exceeded 20 percent at a rate of 50 samples/sec preventing accurate number density or mass flux measurements. The data transfer losses of a new signal processor were analyzed and found to be less than 1 percent for rates under 65,000 samples/sec.

An Analysis of Spanish and German Learners' Errors. Working Papers on Bilingualism, No. 7.

ERIC Educational Resources Information Center

LoCoco, Veronica Gonzalez-Mena

This study analyzes Spanish and German errors committed by adult native speakers of English enrolled in elementary and intermediate levels. Four written samples were collected for each target language, over a period of five months. Errors were categorized according to their possible source. Types of errors were ordered according to their…

Modifying Spearman's Attenuation Equation to Yield Partial Corrections for Measurement Error--With Application to Sample Size Calculations

ERIC Educational Resources Information Center

Nicewander, W. Alan

2018-01-01

Spearman's correction for attenuation (measurement error) corrects a correlation coefficient for measurement errors in either-or-both of two variables, and follows from the assumptions of classical test theory. Spearman's equation removes all measurement error from a correlation coefficient which translates into "increasing the reliability of…

SEM Microanalysis of Particles: Concerns and Suggestions

NASA Astrophysics Data System (ADS)

Fournelle, J.

2008-12-01

The scanning electron microscope (SEM) is well suited to examine and characterize small (i.e. <10 micron) particles. Particles can be imaged and sizes and shapes determined. With energy dispersive x-ray spectrometers (EDS), chemical compositions can be determined quickly. Despite the ease in acquiring x-ray spectra and chemical compositions, there are potentially major sources of error to be recognized. Problems with EDS analyses of small particles: Qualitive estimates of composition (e.g. stating that Si>Al>Ca>Fe plus O) are easy. However, to be able to have confidence that a chemical composition is accurate, several issues should be examined. (1) Particle Mass Effect: Is the accelerating voltage appropriate for the specimen size? Are all the incident electrons remaining inside the particle, and not traveling out of the sample side or bottom? (2) Particle Absorption Effect: What is the geometric relationship of the beam impact point to the x-ray detector? The x-ray intensity will vary by significant amounts for the same material if the grains are irregular and the path out of the sample in the direction of the detector is longer or shorter. (3) Particle Fluorescence Effect: This is generally a smaller error, but should be considered: for small particles, using large standards, there will be a few % less x-rays generated in a small particle relative to one of the same composition and 50-100 times larger. Also, if the sample sits on a grid of a particular composition (e.g. Si wafer) potentially several % of Si could appear in the analysis. (4) In a increasing number of laboratories, with environmental or variable pressure SEMs, the Gas Skirt Effect is operating against you: here the incident electron beam scatters in the gas in the chamber, with less electrons impacting the target spot and some others hitting grains 100s of microns away, producing spectra that could be faulty. (5) Inclusion of measured oxygen: if the measured oxygen x-ray counts are utilized, significant errors can be introduced by differential absorption of this low energy x-ray. (6) Standardless Analysis: This typical method of doing EDS analysis has a major pitfall: the printed analysis is normalized to 100 wt%, thereby eliminating an important clue to analytical error. Suggestions: (1) Use lower voltage, e.g. 10 kV, reducing effects 1,2,3 above. (2) Use standards--traditional flat polished ones--and don't initially normalize totals. Discrepancies can be observed and addressed, not ignored. (3) Alway include oxygen by stoichometry, not measured. (4) Experimental simulation. Using material of constant composition (e.g. NIST glass K-411, or other homogeneous multi-element material with the elements of interest), grind into fragments of similar size to your unknowns, and see what is the analytical error for measurements of these known particles. Analyses of your unknown material will be no better, and probably worse than that, particularly if the grains are smaller. The results of this experiment should be reported whenever discussing measurements on the unknown materials. (5) Monte Carlo simulation. Programs such PENEPMA allows creation of complex geometry samples (and samples on substrates) and resulting EDS spectra can be generated. This allows estimation of errors for representative cases. It is slow, however; other simulations such as DTSA-II promise faster simulations with some limitations. (6) EBSD: this is a perfectly suited for some problems with SEM identification of small particles, e.g. distinguishing magnetite (Fe3O4) from hematite (Fe2O3), which is virtually impossible to do by EDS. With the appropriate hardware and software, electron diffraction patterns on particles can be gathered and the crystal type determined.

Design considerations for case series models with exposure onset measurement error.

PubMed

Mohammed, Sandra M; Dalrymple, Lorien S; Sentürk, Damla; Nguyen, Danh V

2013-02-28

The case series model allows for estimation of the relative incidence of events, such as cardiovascular events, within a pre-specified time window after an exposure, such as an infection. The method requires only cases (individuals with events) and controls for all fixed/time-invariant confounders. The measurement error case series model extends the original case series model to handle imperfect data, where the timing of an infection (exposure) is not known precisely. In this work, we propose a method for power/sample size determination for the measurement error case series model. Extensive simulation studies are used to assess the accuracy of the proposed sample size formulas. We also examine the magnitude of the relative loss of power due to exposure onset measurement error, compared with the ideal situation where the time of exposure is measured precisely. To facilitate the design of case series studies, we provide publicly available web-based tools for determining power/sample size for both the measurement error case series model as well as the standard case series model. Copyright © 2012 John Wiley & Sons, Ltd.

Sequential Tests of Multiple Hypotheses Controlling Type I and II Familywise Error Rates

PubMed Central

Bartroff, Jay; Song, Jinlin

2014-01-01

This paper addresses the following general scenario: A scientist wishes to perform a battery of experiments, each generating a sequential stream of data, to investigate some phenomenon. The scientist would like to control the overall error rate in order to draw statistically-valid conclusions from each experiment, while being as efficient as possible. The between-stream data may differ in distribution and dimension but also may be highly correlated, even duplicated exactly in some cases. Treating each experiment as a hypothesis test and adopting the familywise error rate (FWER) metric, we give a procedure that sequentially tests each hypothesis while controlling both the type I and II FWERs regardless of the between-stream correlation, and only requires arbitrary sequential test statistics that control the error rates for a given stream in isolation. The proposed procedure, which we call the sequential Holm procedure because of its inspiration from Holm’s (1979) seminal fixed-sample procedure, shows simultaneous savings in expected sample size and less conservative error control relative to fixed sample, sequential Bonferroni, and other recently proposed sequential procedures in a simulation study. PMID:25092948

Error baseline rates of five sample preparation methods used to characterize RNA virus populations.

PubMed

Kugelman, Jeffrey R; Wiley, Michael R; Nagle, Elyse R; Reyes, Daniel; Pfeffer, Brad P; Kuhn, Jens H; Sanchez-Lockhart, Mariano; Palacios, Gustavo F

2017-01-01

Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic "no amplification" method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a "targeted" amplification method, sequence-independent single-primer amplification (SISPA) as a "random" amplification method, rolling circle reverse transcription sequencing (CirSeq) as an advanced "no amplification" method, and Illumina TruSeq RNA Access as a "targeted" enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4-5) of all compared methods.

Error baseline rates of five sample preparation methods used to characterize RNA virus populations

PubMed Central

Kugelman, Jeffrey R.; Wiley, Michael R.; Nagle, Elyse R.; Reyes, Daniel; Pfeffer, Brad P.; Kuhn, Jens H.; Sanchez-Lockhart, Mariano; Palacios, Gustavo F.

2017-01-01

Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic “no amplification” method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a “targeted” amplification method, sequence-independent single-primer amplification (SISPA) as a “random” amplification method, rolling circle reverse transcription sequencing (CirSeq) as an advanced “no amplification” method, and Illumina TruSeq RNA Access as a “targeted” enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4−5) of all compared methods. PMID:28182717

Type-II generalized family-wise error rate formulas with application to sample size determination.

PubMed

Delorme, Phillipe; de Micheaux, Pierre Lafaye; Liquet, Benoit; Riou, Jérémie

2016-07-20

Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

Two-step estimation in ratio-of-mediator-probability weighted causal mediation analysis.

PubMed

Bein, Edward; Deutsch, Jonah; Hong, Guanglei; Porter, Kristin E; Qin, Xu; Yang, Cheng

2018-04-15

This study investigates appropriate estimation of estimator variability in the context of causal mediation analysis that employs propensity score-based weighting. Such an analysis decomposes the total effect of a treatment on the outcome into an indirect effect transmitted through a focal mediator and a direct effect bypassing the mediator. Ratio-of-mediator-probability weighting estimates these causal effects by adjusting for the confounding impact of a large number of pretreatment covariates through propensity score-based weighting. In step 1, a propensity score model is estimated. In step 2, the causal effects of interest are estimated using weights derived from the prior step's regression coefficient estimates. Statistical inferences obtained from this 2-step estimation procedure are potentially problematic if the estimated standard errors of the causal effect estimates do not reflect the sampling uncertainty in the estimation of the weights. This study extends to ratio-of-mediator-probability weighting analysis a solution to the 2-step estimation problem by stacking the score functions from both steps. We derive the asymptotic variance-covariance matrix for the indirect effect and direct effect 2-step estimators, provide simulation results, and illustrate with an application study. Our simulation results indicate that the sampling uncertainty in the estimated weights should not be ignored. The standard error estimation using the stacking procedure offers a viable alternative to bootstrap standard error estimation. We discuss broad implications of this approach for causal analysis involving propensity score-based weighting. Copyright © 2018 John Wiley & Sons, Ltd.

Resolution-enhancement and sampling error correction based on molecular absorption line in frequency scanning interferometry

NASA Astrophysics Data System (ADS)

Pan, Hao; Qu, Xinghua; Shi, Chunzhao; Zhang, Fumin; Li, Yating

2018-06-01

The non-uniform interval resampling method has been widely used in frequency modulated continuous wave (FMCW) laser ranging. In the large-bandwidth and long-distance measurements, the range peak is deteriorated due to the fiber dispersion mismatch. In this study, we analyze the frequency-sampling error caused by the mismatch and measure it using the spectroscopy of molecular frequency references line. By using the adjacent points' replacement and spline interpolation technique, the sampling errors could be eliminated. The results demonstrated that proposed method is suitable for resolution-enhancement and high-precision measurement. Moreover, using the proposed method, we achieved the precision of absolute distance less than 45 μm within 8 m.

Action-Based Dynamical Modelling For The Milky Way Disk

NASA Astrophysics Data System (ADS)

Trick, Wilma; Rix, Hans-Walter; Bovy, Jo

2016-09-01

We present Road Mapping, a full-likelihood dynamical modelling machinery, that aims to recover the Milky Way's (MW) gravitational potential from large samples of stars in the Galactic disk. Road Mapping models the observed positions and velocities of stars with a parameterized, action-based distribution function (DF) in a parameterized axisymmetric gravitational potential (Binney & McMillan 2011, Binney 2012, Bovy & Rix 2013).In anticipation of the Gaia data release in autumn, we have fully tested Road Mapping and demonstrated its robustness against the breakdown of its assumptions.Using large suites of mock data, we investigated in isolated test cases how the modelling would be affected if the data's true potential or DF was not included in the families of potentials and DFs assumed by Road Mapping, or if we misjudged measurement errors or the spatial selection function (SF) (Trick et al., submitted to ApJ). We found that the potential can be robustly recovered — given the limitations of the assumed potential model—, even for minor misjudgments in DF or SF, or for proper motion errors or distances known to within 10%.We were also able to demonstrate that Road Mapping is still successful if the strong assumption of axisymmetric breaks down (Trick et al., in preparation). Data drawn from a highresolution simulation (D'Onghia et al. 2013) of a MW-like galaxy with pronounced spiral arms does neither follow the assumed simple DF, nor does it come from an axisymmetric potential. We found that as long as the survey volume is large enough, Road Mapping gives good average constraints on the galaxy's potential.We are planning to apply Road Mapping to a real data set — the Tycho-2 catalogue (Hog et al. 2000) —very soon, and might be able to present some preliminary results already at the conference.

Evaluation of an in-practice wet-chemistry analyzer using canine and feline serum samples.

PubMed

Irvine, Katherine L; Burt, Kay; Papasouliotis, Kostas

2016-01-01

A wet-chemistry biochemical analyzer was assessed for in-practice veterinary use. Its small size may mean a cost-effective method for low-throughput in-house biochemical analyses for first-opinion practice. The objectives of our study were to determine imprecision, total observed error, and acceptability of the analyzer for measurement of common canine and feline serum analytes, and to compare clinical sample results to those from a commercial reference analyzer. Imprecision was determined by within- and between-run repeatability for canine and feline pooled samples, and manufacturer-supplied quality control material (QCM). Total observed error (TEobs) was determined for pooled samples and QCM. Performance was assessed for canine and feline pooled samples by sigma metric determination. Agreement and errors between the in-practice and reference analyzers were determined for canine and feline clinical samples by Bland-Altman and Deming regression analyses. Within- and between-run precision was high for most analytes, and TEobs(%) was mostly lower than total allowable error. Performance based on sigma metrics was good (σ > 4) for many analytes and marginal (σ > 3) for most of the remainder. Correlation between the analyzers was very high for most canine analytes and high for most feline analytes. Between-analyzer bias was generally attributed to high constant error. The in-practice analyzer showed good overall performance, with only calcium and phosphate analyses identified as significantly problematic. Agreement for most analytes was insufficient for transposition of reference intervals, and we recommend that in-practice-specific reference intervals be established in the laboratory. © 2015 The Author(s).

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The incidence and severity of errors in pharmacist-written discharge medication orders.

PubMed

Onatade, Raliat; Sawieres, Sara; Veck, Alexandra; Smith, Lindsay; Gore, Shivani; Al-Azeib, Sumiah

2017-08-01

Background Errors in discharge prescriptions are problematic. When hospital pharmacists write discharge prescriptions improvements are seen in the quality and efficiency of discharge. There is limited information on the incidence of errors in pharmacists' medication orders. Objective To investigate the extent and clinical significance of errors in pharmacist-written discharge medication orders. Setting 1000-bed teaching hospital in London, UK. Method Pharmacists in this London hospital routinely write discharge medication orders as part of the clinical pharmacy service. Convenient days, based on researcher availability, between October 2013 and January 2014 were selected. Pre-registration pharmacists reviewed all discharge medication orders written by pharmacists on these days and identified discrepancies between the medication history, inpatient chart, patient records and discharge summary. A senior clinical pharmacist confirmed the presence of an error. Each error was assigned a potential clinical significance rating (based on the NCCMERP scale) by a physician and an independent senior clinical pharmacist, working separately. Main outcome measure Incidence of errors in pharmacist-written discharge medication orders. Results 509 prescriptions, written by 51 pharmacists, containing 4258 discharge medication orders were assessed (8.4 orders per prescription). Ten prescriptions (2%), contained a total of ten erroneous orders (order error rate-0.2%). The pharmacist considered that one error had the potential to cause temporary harm (0.02% of all orders). The physician did not rate any of the errors with the potential to cause harm. Conclusion The incidence of errors in pharmacists' discharge medication orders was low. The quality, safety and policy implications of pharmacists routinely writing discharge medication orders should be further explored.

Replacement Beef Cow Valuation under Data Availability Constraints

PubMed Central

Hagerman, Amy D.; Thompson, Jada M.; Ham, Charlotte; Johnson, Kamina K.

2017-01-01

Economists are often tasked with estimating the benefits or costs associated with livestock production losses; however, lack of available data or absence of consistent reporting can reduce the accuracy of these valuations. This work looks at three potential estimation techniques for determining the value for replacement beef cows with varying types of market data to proxy constrained data availability and discusses the potential margin of error for each technique. Oklahoma bred replacement cows are valued using hedonic pricing based on Oklahoma bred cow data—a best case scenario—vector error correction modeling (VECM) based on national cow sales data and cost of production (COP) based on just a representative enterprise budget and very limited sales data. Each method was then used to perform a within-sample forecast of 2016 January to December, and forecasts are compared with the 2016 monthly observed market prices in Oklahoma using the mean absolute percent error (MAPE). Hedonic pricing methods tend to overvalue for within-sample forecasting but performed best, as measured by MAPE for high quality cows. The VECM tended to undervalue cows but performed best for younger animals. COP performed well, compared with the more data intensive methods. Examining each method individually across eight representative replacement beef female types, the VECM forecast resulted in a MAPE under 10% for 33% of forecasted months, followed by hedonic pricing at 24% of the forecasted months and COP at 14% of the forecasted months for average quality beef females. For high quality females, the hedonic pricing method worked best producing a MAPE under 10% in 36% of the forecasted months followed by the COP method at 21% of months and the VECM at 14% of the forecasted months. These results suggested that livestock valuation method selection was not one-size-fits-all and may need to vary based not only on the data available but also on the characteristics (e.g., quality or age) of the livestock being valued. PMID:29164141

Accounting for nonsampling error in estimates of HIV epidemic trends from antenatal clinic sentinel surveillance

PubMed Central

Eaton, Jeffrey W.; Bao, Le

2017-01-01

Objectives The aim of the study was to propose and demonstrate an approach to allow additional nonsampling uncertainty about HIV prevalence measured at antenatal clinic sentinel surveillance (ANC-SS) in model-based inferences about trends in HIV incidence and prevalence. Design Mathematical model fitted to surveillance data with Bayesian inference. Methods We introduce a variance inflation parameter σinfl2 that accounts for the uncertainty of nonsampling errors in ANC-SS prevalence. It is additive to the sampling error variance. Three approaches are tested for estimating σinfl2 using ANC-SS and household survey data from 40 subnational regions in nine countries in sub-Saharan, as defined in UNAIDS 2016 estimates. Methods were compared using in-sample fit and out-of-sample prediction of ANC-SS data, fit to household survey prevalence data, and the computational implications. Results Introducing the additional variance parameter σinfl2 increased the error variance around ANC-SS prevalence observations by a median of 2.7 times (interquartile range 1.9–3.8). Using only sampling error in ANC-SS prevalence ( σinfl2=0), coverage of 95% prediction intervals was 69% in out-of-sample prediction tests. This increased to 90% after introducing the additional variance parameter σinfl2. The revised probabilistic model improved model fit to household survey prevalence and increased epidemic uncertainty intervals most during the early epidemic period before 2005. Estimating σinfl2 did not increase the computational cost of model fitting. Conclusions: We recommend estimating nonsampling error in ANC-SS as an additional parameter in Bayesian inference using the Estimation and Projection Package model. This approach may prove useful for incorporating other data sources such as routine prevalence from Prevention of mother-to-child transmission testing into future epidemic estimates. PMID:28296801

Outlier Removal and the Relation with Reporting Errors and Quality of Psychological Research

PubMed Central

Bakker, Marjan; Wicherts, Jelte M.

2014-01-01

Background The removal of outliers to acquire a significant result is a questionable research practice that appears to be commonly used in psychology. In this study, we investigated whether the removal of outliers in psychology papers is related to weaker evidence (against the null hypothesis of no effect), a higher prevalence of reporting errors, and smaller sample sizes in these papers compared to papers in the same journals that did not report the exclusion of outliers from the analyses. Methods and Findings We retrieved a total of 2667 statistical results of null hypothesis significance tests from 153 articles in main psychology journals, and compared results from articles in which outliers were removed (N = 92) with results from articles that reported no exclusion of outliers (N = 61). We preregistered our hypotheses and methods and analyzed the data at the level of articles. Results show no significant difference between the two types of articles in median p value, sample sizes, or prevalence of all reporting errors, large reporting errors, and reporting errors that concerned the statistical significance. However, we did find a discrepancy between the reported degrees of freedom of t tests and the reported sample size in 41% of articles that did not report removal of any data values. This suggests common failure to report data exclusions (or missingness) in psychological articles. Conclusions We failed to find that the removal of outliers from the analysis in psychological articles was related to weaker evidence (against the null hypothesis of no effect), sample size, or the prevalence of errors. However, our control sample might be contaminated due to nondisclosure of excluded values in articles that did not report exclusion of outliers. Results therefore highlight the importance of more transparent reporting of statistical analyses. PMID:25072606

LoCuSS: THE MASS DENSITY PROFILE OF MASSIVE GALAXY CLUSTERS AT z = 0.2 {sup ,}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Okabe, Nobuhiro; Umetsu, Keiichi; Smith, Graham P.

We present a stacked weak-lensing analysis of an approximately mass-selected sample of 50 galaxy clusters at 0.15 < z < 0.3, based on observations with Suprime-Cam on the Subaru Telescope. We develop a new method for selecting lensed background galaxies from which we estimate that our sample of red background galaxies suffers just 1% contamination. We detect the stacked tangential shear signal from the full sample of 50 clusters, based on this red sample of background galaxies, at a total signal-to-noise ratio of 32.7. The Navarro-Frenk-White model is an excellent fit to the data, yielding sub-10% statistical precision on massmore » and concentration: M{sub vir}=7.19{sup +0.53}{sub -0.50} Multiplication-Sign 10{sup 14} h{sup -1} M{sub sun}, c{sub vir}=5.41{sup +0.49}{sub -0.45} (c{sub 200}=4.22{sup +0.40}{sub -0.36}). Tests of a range of possible systematic errors, including shear calibration and stacking-related issues, indicate that they are subdominant to the statistical errors. The concentration parameter obtained from stacking our approximately mass-selected cluster sample is broadly in line with theoretical predictions. Moreover, the uncertainty on our measurement is comparable with the differences between the different predictions in the literature. Overall, our results highlight the potential for stacked weak-lensing methods to probe the mean mass density profile of cluster-scale dark matter halos with upcoming surveys, including Hyper-Suprime-Cam, Dark Energy Survey, and KIDS.« less

Multiple Category-Lot Quality Assurance Sampling: A New Classification System with Application to Schistosomiasis Control

PubMed Central

Olives, Casey; Valadez, Joseph J.; Brooker, Simon J.; Pagano, Marcello

2012-01-01

Background Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa. Methodology We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n = 15 and n = 25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa. Principle Findings Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n = 15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error. Conclusion/Significance This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools. PMID:22970333

Evaluation of Laser-Induced Breakdown Spectroscopy (LIBS) for Measurement of Silica on Filter Samples of Coal Dust

PubMed Central

Stipe, Christopher B.; Miller, Arthur L.; Brown, Jonathan; Guevara, Edward; Cauda, Emanuele

2015-01-01

Airborne silica dust (quartz) is common in coal mines and represents a respiratory hazard that can lead to silicosis, a potentially fatal lung disease. With an eye toward developing a portable monitoring device for rapid analysis of silica dust, laser-induced breakdown spectroscopy (LIBS) was used to quantify quartz in coal dust samples collected on filter media. Pure silica (Min-U-Sil™ 5), Georgia kaolin, and Pittsburgh-4 and Illinois-6 coal dusts were deposited separately and at multiple mass loadings onto 37-mm polyvinylchloride (PVC) filters. LIBS-generated silicon emission was monitored at 288.16 nm, and non-silica contributions to that signal from kaolinite were removed by simultaneously detecting aluminum. Measurements of the four samples were used to calculate limits of detection (LOD) for silicon and aluminum of approximately 0.08 µg/cm2 and 0.05 µg/cm2, respectively (corresponding to 0.16 µg/cm2 and 0.20 µg/cm2 for silica and kaolinite, respectively). Relative errors of prediction are around 10%. Results demonstrate that LIBS can dependably quantify silica on filter samples of coal dust and confirm that accurate quantification can be achieved for very lightly loaded samples, which supports the potential application of LIBS for rapid, in-field monitoring. PMID:23146184

Evaluation of laser-induced breakdown spectroscopy (LIBS) for measurement of silica on filter samples of coal dust.

PubMed

Stipe, Christopher B; Miller, Arthur L; Brown, Jonathan; Guevara, Edward; Cauda, Emanuele

2012-11-01

Airborne silica dust (quartz) is common in coal mines and represents a respiratory hazard that can lead to silicosis, a potentially fatal lung disease. With an eye toward developing a portable monitoring device for rapid analysis of silica dust, laser-induced breakdown spectroscopy (LIBS) was used to quantify quartz in coal dust samples collected on filter media. Pure silica (Min-U-Sil™ 5), Georgia kaolin, and Pittsburgh-4 and Illinois-6 coal dusts were deposited separately and at multiple mass loadings onto 37-mm polyvinylchloride (PVC) filters. LIBS-generated silicon emission was monitored at 288.16 nm, and non-silica contributions to that signal from kaolinite were removed by simultaneously detecting aluminum. Measurements of the four samples were used to calculate limits of detection (LOD) for silicon and aluminum of approximately 0.08 μg/cm(2) and 0.05 μg/cm(2), respectively (corresponding to 0.16 μg/cm(2) and 0.20 μg/cm(2) for silica and kaolinite, respectively). Relative errors of prediction are around 10%. Results demonstrate that LIBS can dependably quantify silica on filter samples of coal dust and confirm that accurate quantification can be achieved for very lightly loaded samples, which supports the potential application of LIBS for rapid, in-field monitoring.

Efficient design and inference for multistage randomized trials of individualized treatment policies.

PubMed

Dawson, Ree; Lavori, Philip W

2012-01-01

Clinical demand for individualized "adaptive" treatment policies in diverse fields has spawned development of clinical trial methodology for their experimental evaluation via multistage designs, building upon methods intended for the analysis of naturalistically observed strategies. Because often there is no need to parametrically smooth multistage trial data (in contrast to observational data for adaptive strategies), it is possible to establish direct connections among different methodological approaches. We show by algebraic proof that the maximum likelihood (ML) and optimal semiparametric (SP) estimators of the population mean of the outcome of a treatment policy and its standard error are equal under certain experimental conditions. This result is used to develop a unified and efficient approach to design and inference for multistage trials of policies that adapt treatment according to discrete responses. We derive a sample size formula expressed in terms of a parametric version of the optimal SP population variance. Nonparametric (sample-based) ML estimation performed well in simulation studies, in terms of achieved power, for scenarios most likely to occur in real studies, even though sample sizes were based on the parametric formula. ML outperformed the SP estimator; differences in achieved power predominately reflected differences in their estimates of the population mean (rather than estimated standard errors). Neither methodology could mitigate the potential for overestimated sample sizes when strong nonlinearity was purposely simulated for certain discrete outcomes; however, such departures from linearity may not be an issue for many clinical contexts that make evaluation of competitive treatment policies meaningful.

Limited Sampling Strategy for Accurate Prediction of Pharmacokinetics of Saroglitazar: A 3-point Linear Regression Model Development and Successful Prediction of Human Exposure.

PubMed

Joshi, Shuchi N; Srinivas, Nuggehally R; Parmar, Deven V

2018-03-01

Our aim was to develop and validate the extrapolative performance of a regression model using a limited sampling strategy for accurate estimation of the area under the plasma concentration versus time curve for saroglitazar. Healthy subject pharmacokinetic data from a well-powered food-effect study (fasted vs fed treatments; n = 50) was used in this work. The first 25 subjects' serial plasma concentration data up to 72 hours and corresponding AUC 0-t (ie, 72 hours) from the fasting group comprised a training dataset to develop the limited sampling model. The internal datasets for prediction included the remaining 25 subjects from the fasting group and all 50 subjects from the fed condition of the same study. The external datasets included pharmacokinetic data for saroglitazar from previous single-dose clinical studies. Limited sampling models were composed of 1-, 2-, and 3-concentration-time points' correlation with AUC 0-t of saroglitazar. Only models with regression coefficients (R 2 ) >0.90 were screened for further evaluation. The best R 2 model was validated for its utility based on mean prediction error, mean absolute prediction error, and root mean square error. Both correlations between predicted and observed AUC 0-t of saroglitazar and verification of precision and bias using Bland-Altman plot were carried out. None of the evaluated 1- and 2-concentration-time points models achieved R 2 > 0.90. Among the various 3-concentration-time points models, only 4 equations passed the predefined criterion of R 2 > 0.90. Limited sampling models with time points 0.5, 2, and 8 hours (R 2 = 0.9323) and 0.75, 2, and 8 hours (R 2 = 0.9375) were validated. Mean prediction error, mean absolute prediction error, and root mean square error were <30% (predefined criterion) and correlation (r) was at least 0.7950 for the consolidated internal and external datasets of 102 healthy subjects for the AUC 0-t prediction of saroglitazar. The same models, when applied to the AUC 0-t prediction of saroglitazar sulfoxide, showed mean prediction error, mean absolute prediction error, and root mean square error <30% and correlation (r) was at least 0.9339 in the same pool of healthy subjects. A 3-concentration-time points limited sampling model predicts the exposure of saroglitazar (ie, AUC 0-t ) within predefined acceptable bias and imprecision limit. Same model was also used to predict AUC 0-∞ . The same limited sampling model was found to predict the exposure of saroglitazar sulfoxide within predefined criteria. This model can find utility during late-phase clinical development of saroglitazar in the patient population. Copyright © 2018 Elsevier HS Journals, Inc. All rights reserved.

TH-B-BRC-00: How to Identify and Resolve Potential Clinical Errors Before They Impact Patients Treatment: Lessons Learned

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2016-06-15

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews ofmore » some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.« less

TH-B-BRC-01: How to Identify and Resolve Potential Clinical Errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Das, I.

2016-06-15

Radiation treatment consists of a chain of events influenced by the quality of machine operation, beam data commissioning, machine calibration, patient specific data, simulation, treatment planning, imaging and treatment delivery. There is always a chance that the clinical medical physicist may make or fail to detect an error in one of the events that may impact on the patient’s treatment. In the clinical scenario, errors may be systematic and, without peer review, may have a low detectability because they are not part of routine QA procedures. During treatment, there might be errors on machine that needs attention. External reviews ofmore » some of the treatment delivery components by independent reviewers, like IROC, can detect errors, but may not be timely. The goal of this session is to help junior clinical physicists identify potential errors as well as the approach of quality assurance to perform a root cause analysis to find and eliminate an error and to continually monitor for errors. A compilation of potential errors will be presented by examples of the thought process required to spot the error and determine the root cause. Examples may include unusual machine operation, erratic electrometer reading, consistent lower electron output, variation in photon output, body parts inadvertently left in beam, unusual treatment plan, poor normalization, hot spots etc. Awareness of the possibility and detection of error in any link of the treatment process chain will help improve the safe and accurate delivery of radiation to patients. Four experts will discuss how to identify errors in four areas of clinical treatment. D. Followill, NIH grant CA 180803.« less

Accuracy of measurement in electrically evoked compound action potentials.

PubMed

Hey, Matthias; Müller-Deile, Joachim

2015-01-15

Electrically evoked compound action potentials (ECAP) in cochlear implant (CI) patients are characterized by the amplitude of the N1P1 complex. The measurement of evoked potentials yields a combination of the measured signal with various noise components but for ECAP procedures performed in the clinical routine, only the averaged curve is accessible. To date no detailed analysis of error dimension has been published. The aim of this study was to determine the error of the N1P1 amplitude and to determine the factors that impact the outcome. Measurements were performed on 32 CI patients with either CI24RE (CA) or CI512 implants using the Software Custom Sound EP (Cochlear). N1P1 error approximation of non-averaged raw data consisting of recorded single-sweeps was compared to methods of error approximation based on mean curves. The error approximation of the N1P1 amplitude using averaged data showed comparable results to single-point error estimation. The error of the N1P1 amplitude depends on the number of averaging steps and amplification; in contrast, the error of the N1P1 amplitude is not dependent on the stimulus intensity. Single-point error showed smaller N1P1 error and better coincidence with 1/√(N) function (N is the number of measured sweeps) compared to the known maximum-minimum criterion. Evaluation of N1P1 amplitude should be accompanied by indication of its error. The retrospective approximation of this measurement error from the averaged data available in clinically used software is possible and best done utilizing the D-trace in forward masking artefact reduction mode (no stimulation applied and recording contains only the switch-on-artefact). Copyright © 2014 Elsevier B.V. All rights reserved.

Previous Estimates of Mitochondrial DNA Mutation Level Variance Did Not Account for Sampling Error: Comparing the mtDNA Genetic Bottleneck in Mice and Humans

PubMed Central

Wonnapinij, Passorn; Chinnery, Patrick F.; Samuels, David C.

2010-01-01

In cases of inherited pathogenic mitochondrial DNA (mtDNA) mutations, a mother and her offspring generally have large and seemingly random differences in the amount of mutated mtDNA that they carry. Comparisons of measured mtDNA mutation level variance values have become an important issue in determining the mechanisms that cause these large random shifts in mutation level. These variance measurements have been made with samples of quite modest size, which should be a source of concern because higher-order statistics, such as variance, are poorly estimated from small sample sizes. We have developed an analysis of the standard error of variance from a sample of size n, and we have defined error bars for variance measurements based on this standard error. We calculate variance error bars for several published sets of measurements of mtDNA mutation level variance and show how the addition of the error bars alters the interpretation of these experimental results. We compare variance measurements from human clinical data and from mouse models and show that the mutation level variance is clearly higher in the human data than it is in the mouse models at both the primary oocyte and offspring stages of inheritance. We discuss how the standard error of variance can be used in the design of experiments measuring mtDNA mutation level variance. Our results show that variance measurements based on fewer than 20 measurements are generally unreliable and ideally more than 50 measurements are required to reliably compare variances with less than a 2-fold difference. PMID:20362273

Reducing medication errors in critical care: a multimodal approach

PubMed Central

Kruer, Rachel M; Jarrell, Andrew S; Latif, Asad

2014-01-01

The Institute of Medicine has reported that medication errors are the single most common type of error in health care, representing 19% of all adverse events, while accounting for over 7,000 deaths annually. The frequency of medication errors in adult intensive care units can be as high as 947 per 1,000 patient-days, with a median of 105.9 per 1,000 patient-days. The formulation of drugs is a potential contributor to medication errors. Challenges related to drug formulation are specific to the various routes of medication administration, though errors associated with medication appearance and labeling occur among all drug formulations and routes of administration. Addressing these multifaceted challenges requires a multimodal approach. Changes in technology, training, systems, and safety culture are all strategies to potentially reduce medication errors related to drug formulation in the intensive care unit. PMID:25210478

A system dynamics approach to analyze laboratory test errors.

PubMed

Guo, Shijing; Roudsari, Abdul; Garcez, Artur d'Avila

2015-01-01

Although many researches have been carried out to analyze laboratory test errors during the last decade, it still lacks a systemic view of study, especially to trace errors during test process and evaluate potential interventions. This study implements system dynamics modeling into laboratory errors to trace the laboratory error flows and to simulate the system behaviors while changing internal variable values. The change of the variables may reflect a change in demand or a proposed intervention. A review of literature on laboratory test errors was given and provided as the main data source for the system dynamics model. Three "what if" scenarios were selected for testing the model. System behaviors were observed and compared under different scenarios over a period of time. The results suggest system dynamics modeling has potential effectiveness of helping to understand laboratory errors, observe model behaviours, and provide a risk-free simulation experiments for possible strategies.

Transient fault behavior in a microprocessor: A case study

NASA Technical Reports Server (NTRS)

Duba, Patrick

1989-01-01

An experimental analysis is described which studies the susceptibility of a microprocessor based jet engine controller to upsets caused by current and voltage transients. A design automation environment which allows the run time injection of transients and the tracing from their impact device to the pin level is described. The resulting error data are categorized by the charge levels of the injected transients by location and by their potential to cause logic upsets, latched errors, and pin errors. The results show a 3 picoCouloumb threshold, below which the transients have little impact. An Arithmetic and Logic Unit transient is most likely to result in logic upsets and pin errors (i.e., impact the external environment). The transients in the countdown unit are potentially serious since they can result in latched errors, thus causing latent faults. Suggestions to protect the processor against these errors, by incorporating internal error detection and transient suppression techniques, are also made.

Measurement Error Calibration in Mixed-Mode Sample Surveys

ERIC Educational Resources Information Center

Buelens, Bart; van den Brakel, Jan A.

2015-01-01

Mixed-mode surveys are known to be susceptible to mode-dependent selection and measurement effects, collectively referred to as mode effects. The use of different data collection modes within the same survey may reduce selectivity of the overall response but is characterized by measurement errors differing across modes. Inference in sample surveys…

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

PubMed Central

Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J

2009-01-01

Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590

Decision Making In A High-Tech World: Automation Bias and Countermeasures

NASA Technical Reports Server (NTRS)

Mosier, Kathleen L.; Skitka, Linda J.; Burdick, Mark R.; Heers, Susan T.; Rosekind, Mark R. (Technical Monitor)

1996-01-01

Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.

Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179

Purification of Logic-Qubit Entanglement

PubMed Central

Zhou, Lan; Sheng, Yu-Bo

2016-01-01

Recently, the logic-qubit entanglement shows its potential application in future quantum communication and quantum network. However, the entanglement will suffer from the noise and decoherence. In this paper, we will investigate the first entanglement purification protocol for logic-qubit entanglement. We show that both the bit-flip error and phase-flip error in logic-qubit entanglement can be well purified. Moreover, the bit-flip error in physical-qubit entanglement can be completely corrected. The phase-flip in physical-qubit entanglement error equals to the bit-flip error in logic-qubit entanglement, which can also be purified. This entanglement purification protocol may provide some potential applications in future quantum communication and quantum network. PMID:27377165

A semiempirical error estimation technique for PWV derived from atmospheric radiosonde data

NASA Astrophysics Data System (ADS)

Castro-Almazán, Julio A.; Pérez-Jordán, Gabriel; Muñoz-Tuñón, Casiana

2016-09-01

A semiempirical method for estimating the error and optimum number of sampled levels in precipitable water vapour (PWV) determinations from atmospheric radiosoundings is proposed. Two terms have been considered: the uncertainties in the measurements and the sampling error. Also, the uncertainty has been separated in the variance and covariance components. The sampling and covariance components have been modelled from an empirical dataset of 205 high-vertical-resolution radiosounding profiles, equipped with Vaisala RS80 and RS92 sondes at four different locations: Güímar (GUI) in Tenerife, at sea level, and the astronomical observatory at Roque de los Muchachos (ORM, 2300 m a.s.l.) on La Palma (both on the Canary Islands, Spain), Lindenberg (LIN) in continental Germany, and Ny-Ålesund (NYA) in the Svalbard Islands, within the Arctic Circle. The balloons at the ORM were launched during intensive and unique site-testing runs carried out in 1990 and 1995, while the data for the other sites were obtained from radiosounding stations operating for a period of 1 year (2013-2014). The PWV values ranged between ˜ 0.9 and ˜ 41 mm. The method sub-samples the profile for error minimization. The result is the minimum error and the optimum number of levels. The results obtained in the four sites studied showed that the ORM is the driest of the four locations and the one with the fastest vertical decay of PWV. The exponential autocorrelation pressure lags ranged from 175 hPa (ORM) to 500 hPa (LIN). The results show a coherent behaviour with no biases as a function of the profile. The final error is roughly proportional to PWV whereas the optimum number of levels (N0) is the reverse. The value of N0 is less than 400 for 77 % of the profiles and the absolute errors are always < 0.6 mm. The median relative error is 2.0 ± 0.7 % and the 90th percentile P90 = 4.6 %. Therefore, whereas a radiosounding samples at least N0 uniform vertical levels, depending on the water vapour content and distribution of the atmosphere, the error in the PWV estimate is likely to stay below ≈ 3 %, even for dry conditions.

Alterations in Error-Related Brain Activity and Post-Error Behavior over Time

ERIC Educational Resources Information Center

Themanson, Jason R.; Rosen, Peter J.; Pontifex, Matthew B.; Hillman, Charles H.; McAuley, Edward

2012-01-01

This study examines the relation between the error-related negativity (ERN) and post-error behavior over time in healthy young adults (N = 61). Event-related brain potentials were collected during two sessions of an identical flanker task. Results indicated changes in ERN and post-error accuracy were related across task sessions, with more…

Toward polarizable AMOEBA thermodynamics at fixed charge efficiency using a dual force field approach: application to organic crystals.

PubMed

Nessler, Ian J; Litman, Jacob M; Schnieders, Michael J

2016-11-09

First principles prediction of the structure, thermodynamics and solubility of organic molecular crystals, which play a central role in chemical, material, pharmaceutical and engineering sciences, challenges both potential energy functions and sampling methodologies. Here we calculate absolute crystal deposition thermodynamics using a novel dual force field approach whose goal is to maintain the accuracy of advanced multipole force fields (e.g. the polarizable AMOEBA model) while performing more than 95% of the sampling in an inexpensive fixed charge (FC) force field (e.g. OPLS-AA). Absolute crystal sublimation/deposition phase transition free energies were determined using an alchemical path that grows the crystalline state from a vapor reference state based on sampling with the OPLS-AA force field, followed by dual force field thermodynamic corrections to change between FC and AMOEBA resolutions at both end states (we denote the three step path as AMOEBA/FC). Importantly, whereas the phase transition requires on the order of 200 ns of sampling per compound, only 5 ns of sampling was needed for the dual force field thermodynamic corrections to reach a mean statistical uncertainty of 0.05 kcal mol -1 . For five organic compounds, the mean unsigned error between direct use of AMOEBA and the AMOEBA/FC dual force field path was only 0.2 kcal mol -1 and not statistically significant. Compared to experimental deposition thermodynamics, the mean unsigned error for AMOEBA/FC (1.4 kcal mol -1 ) was more than a factor of two smaller than uncorrected OPLS-AA (3.2 kcal mol -1 ). Overall, the dual force field thermodynamic corrections reduced condensed phase sampling in the expensive force field by a factor of 40, and may prove useful for protein stability or binding thermodynamics in the future.

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Hsin-Chen; Tan, Jun; Dolly, Steven

2015-02-15

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy basedmore » on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.« less

GUM Analysis for SIMS Isotopic Ratios in BEP0 Graphite Qualification Samples, Round 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerlach, David C.; Heasler, Patrick G.; Reid, Bruce D.

2009-01-01

This report describes GUM calculations for TIMS and SIMS isotopic ratio measurements of reactor graphite samples. These isotopic ratios are used to estimate reactor burn-up, and currently consist of various ratios of U, Pu, and Boron impurities in the graphite samples. The GUM calculation is a propagation of error methodology that assigns uncertainties (in the form of standard error and confidence bound) to the final estimates.

Predicting ambient aerosol Thermal Optical Reflectance (TOR) measurements from infrared spectra: organic carbon

NASA Astrophysics Data System (ADS)

Dillner, A. M.; Takahama, S.

2014-11-01

Organic carbon (OC) can constitute 50% or more of the mass of atmospheric particulate matter. Typically, the organic carbon concentration is measured using thermal methods such as Thermal-Optical Reflectance (TOR) from quartz fiber filters. Here, methods are presented whereby Fourier Transform Infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters are used to accurately predict TOR OC. Transmittance FT-IR analysis is rapid, inexpensive, and non-destructive to the PTFE filters. To develop and test the method, FT-IR absorbance spectra are obtained from 794 samples from seven Interagency Monitoring of PROtected Visual Environment (IMPROVE) sites sampled during 2011. Partial least squares regression is used to calibrate sample FT-IR absorbance spectra to artifact-corrected TOR OC. The FTIR spectra are divided into calibration and test sets by sampling site and date which leads to precise and accurate OC predictions by FT-IR as indicated by high coefficient of determination (R2; 0.96), low bias (0.02 μg m-3, all μg m-3 values based on the nominal IMPROVE sample volume of 32.8 m-3), low error (0.08 μg m-3) and low normalized error (11%). These performance metrics can be achieved with various degrees of spectral pretreatment (e.g., including or excluding substrate contributions to the absorbances) and are comparable in precision and accuracy to collocated TOR measurements. FT-IR spectra are also divided into calibration and test sets by OC mass and by OM / OC which reflects the organic composition of the particulate matter and is obtained from organic functional group composition; this division also leads to precise and accurate OC predictions. Low OC concentrations have higher bias and normalized error due to TOR analytical errors and artifact correction errors, not due to the range of OC mass of the samples in the calibration set. However, samples with low OC mass can be used to predict samples with high OC mass indicating that the calibration is linear. Using samples in the calibration set that have a different OM / OC or ammonium / OC distributions than the test set leads to only a modest increase in bias and normalized error in the predicted samples. We conclude that FT-IR analysis with partial least squares regression is a robust method for accurately predicting TOR OC in IMPROVE network samples; providing complementary information to the organic functional group composition and organic aerosol mass estimated previously from the same set of sample spectra (Ruthenburg et al., 2014).

Biomass Thermogravimetric Analysis: Uncertainty Determination Methodology and Sampling Maps Generation

PubMed Central

Pazó, Jose A.; Granada, Enrique; Saavedra, Ángeles; Eguía, Pablo; Collazo, Joaquín

2010-01-01

The objective of this study was to develop a methodology for the determination of the maximum sampling error and confidence intervals of thermal properties obtained from thermogravimetric analysis (TG), including moisture, volatile matter, fixed carbon and ash content. The sampling procedure of the TG analysis was of particular interest and was conducted with care. The results of the present study were compared to those of a prompt analysis, and a correlation between the mean values and maximum sampling errors of the methods were not observed. In general, low and acceptable levels of uncertainty and error were obtained, demonstrating that the properties evaluated by TG analysis were representative of the overall fuel composition. The accurate determination of the thermal properties of biomass with precise confidence intervals is of particular interest in energetic biomass applications. PMID:20717532

Sample size re-assessment leading to a raised sample size does not inflate type I error rate under mild conditions.

PubMed

Broberg, Per

2013-07-19

One major concern with adaptive designs, such as the sample size adjustable designs, has been the fear of inflating the type I error rate. In (Stat Med 23:1023-1038, 2004) it is however proven that when observations follow a normal distribution and the interim result show promise, meaning that the conditional power exceeds 50%, type I error rate is protected. This bound and the distributional assumptions may seem to impose undesirable restrictions on the use of these designs. In (Stat Med 30:3267-3284, 2011) the possibility of going below 50% is explored and a region that permits an increased sample size without inflation is defined in terms of the conditional power at the interim. A criterion which is implicit in (Stat Med 30:3267-3284, 2011) is derived by elementary methods and expressed in terms of the test statistic at the interim to simplify practical use. Mathematical and computational details concerning this criterion are exhibited. Under very general conditions the type I error rate is preserved under sample size adjustable schemes that permit a raise. The main result states that for normally distributed observations raising the sample size when the result looks promising, where the definition of promising depends on the amount of knowledge gathered so far, guarantees the protection of the type I error rate. Also, in the many situations where the test statistic approximately follows a normal law, the deviation from the main result remains negligible. This article provides details regarding the Weibull and binomial distributions and indicates how one may approach these distributions within the current setting. There is thus reason to consider such designs more often, since they offer a means of adjusting an important design feature at little or no cost in terms of error rate.

Two-Photon Laser-Induced Fluorescence O and N Atoms for the Study of Heterogeneous Catalysis in a Diffusion Reactor

NASA Technical Reports Server (NTRS)

Pallix, Joan B.; Copeland, Richard A.; Arnold, James O. (Technical Monitor)

1995-01-01

Advanced laser-based diagnostics have been developed to examine catalytic effects and atom/surface interactions on thermal protection materials. This study establishes the feasibility of using laser-induced fluorescence for detection of O and N atom loss in a diffusion tube to measure surface catalytic activity. The experimental apparatus is versatile in that it allows fluorescence detection to be used for measuring species selective recombination coefficients as well as diffusion tube and microwave discharge diagnostics. Many of the potential sources of error in measuring atom recombination coefficients by this method have been identified and taken into account. These include scattered light, detector saturation, sample surface cleanliness, reactor design, gas pressure and composition, and selectivity of the laser probe. Recombination coefficients and their associated errors are reported for N and O atoms on a quartz surface at room temperature.

Polarized Raman spectroscopy of bone tissue: watch the scattering

NASA Astrophysics Data System (ADS)

Raghavan, Mekhala; Sahar, Nadder D.; Wilson, Robert H.; Mycek, Mary-Ann; Pleshko, Nancy; Kohn, David H.; Morris, Michael D.

2010-02-01

Polarized Raman spectroscopy is widely used in the study of molecular composition and orientation in synthetic and natural polymer systems. Here, we describe the use of Raman spectroscopy to extract quantitative orientation information from bone tissue. Bone tissue poses special challenges to the use of polarized Raman spectroscopy for measurement of orientation distribution functions because the tissue is turbid and birefringent. Multiple scattering in turbid media depolarizes light and is potentially a source of error. Using a Raman microprobe, we show that repeating the measurements with a series of objectives of differing numerical apertures can be used to assess the contributions of sample turbidity and depth of field to the calculated orientation distribution functions. With this test, an optic can be chosen to minimize the systematic errors introduced by multiple scattering events. With adequate knowledge of the optical properties of these bone tissues, we can determine if elastic light scattering affects the polarized Raman measurements.

A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

PubMed

Tridandapani, Srini; Ramamurthy, Senthil; Provenzale, James; Obuchowski, Nancy A; Evanoff, Michael G; Bhatti, Pamela

2014-08-01

To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors. In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded. Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77). In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Trauma center maturity measured by an analysis of preventable and potentially preventable deaths: there is always something to be learned….

PubMed

Matsumoto, Shokei; Jung, Kyoungwon; Smith, Alan; Coimbra, Raul

2018-06-23

To establish the preventable and potentially preventable death rates in a mature trauma center and to identify the causes of death and highlight the lessons learned from these cases. We analyzed data from a Level-1 Trauma Center Registry, collected over a 15-year period. Data on demographics, timing of death, and potential errors were collected. Deaths were judged as preventable (PD), potentially preventable (PPD), or non-preventable (NPD), following a strict external peer-review process. During the 15-year period, there were 874 deaths, 15 (1.7%) and 6 (0.7%) of which were considered PPDs and PDs, respectively. Patients in the PD and PPD groups were not sicker and had less severe head injury than those in the NPD group. The time-death distribution differed according to preventability. We identified 21 errors in the PD and PPD groups, but only 61 (7.3%) errors in the NPD group (n = 853). Errors in judgement accounted for the majority and for 90.5% of the PD and PPD group errors. Although the numbers of PDs and PPDs were low, denoting maturity of our trauma center, there are important lessons to be learned about how errors in judgment led to deaths that could have been prevented.

Medication Administration Errors in Nursing Homes Using an Automated Medication Dispensing System

PubMed Central

van den Bemt, Patricia M.L.A.; Idzinga, Jetske C.; Robertz, Hans; Kormelink, Dennis Groot; Pels, Neske

2009-01-01

Objective To identify the frequency of medication administration errors as well as their potential risk factors in nursing homes using a distribution robot. Design The study was a prospective, observational study conducted within three nursing homes in the Netherlands caring for 180 individuals. Measurements Medication errors were measured using the disguised observation technique. Types of medication errors were described. The correlation between several potential risk factors and the occurrence of medication errors was studied to identify potential causes for the errors. Results In total 2,025 medication administrations to 127 clients were observed. In these administrations 428 errors were observed (21.2%). The most frequently occurring types of errors were use of wrong administration techniques (especially incorrect crushing of medication and not supervising the intake of medication) and wrong time errors (administering the medication at least 1 h early or late).The potential risk factors female gender (odds ratio (OR) 1.39; 95% confidence interval (CI) 1.05–1.83), ATC medication class antibiotics (OR 11.11; 95% CI 2.66–46.50), medication crushed (OR 7.83; 95% CI 5.40–11.36), number of dosages/day/client (OR 1.03; 95% CI 1.01–1.05), nursing home 2 (OR 3.97; 95% CI 2.86–5.50), medication not supplied by distribution robot (OR 2.92; 95% CI 2.04–4.18), time classes “7–10 am” (OR 2.28; 95% CI 1.50–3.47) and “10 am-2 pm” (OR 1.96; 1.18–3.27) and day of the week “Wednesday” (OR 1.46; 95% CI 1.03–2.07) are associated with a higher risk of administration errors. Conclusions Medication administration in nursing homes is prone to many errors. This study indicates that the handling of the medication after removing it from the robot packaging may contribute to this high error frequency, which may be reduced by training of nurse attendants, by automated clinical decision support and by measures to reduce workload. PMID:19390109

Estimating instream constituent loads using replicate synoptic sampling, Peru Creek, Colorado

NASA Astrophysics Data System (ADS)

Runkel, Robert L.; Walton-Day, Katherine; Kimball, Briant A.; Verplanck, Philip L.; Nimick, David A.

2013-05-01

SummaryThe synoptic mass balance approach is often used to evaluate constituent mass loading in streams affected by mine drainage. Spatial profiles of constituent mass load are used to identify sources of contamination and prioritize sites for remedial action. This paper presents a field scale study in which replicate synoptic sampling campaigns are used to quantify the aggregate uncertainty in constituent load that arises from (1) laboratory analyses of constituent and tracer concentrations, (2) field sampling error, and (3) temporal variation in concentration from diel constituent cycles and/or source variation. Consideration of these factors represents an advance in the application of the synoptic mass balance approach by placing error bars on estimates of constituent load and by allowing all sources of uncertainty to be quantified in aggregate; previous applications of the approach have provided only point estimates of constituent load and considered only a subset of the possible errors. Given estimates of aggregate uncertainty, site specific data and expert judgement may be used to qualitatively assess the contributions of individual factors to uncertainty. This assessment can be used to guide the collection of additional data to reduce uncertainty. Further, error bars provided by the replicate approach can aid the investigator in the interpretation of spatial loading profiles and the subsequent identification of constituent source areas within the watershed. The replicate sampling approach is applied to Peru Creek, a stream receiving acidic, metal-rich effluent from the Pennsylvania Mine. Other sources of acidity and metals within the study reach include a wetland area adjacent to the mine and tributary inflow from Cinnamon Gulch. Analysis of data collected under low-flow conditions indicates that concentrations of Al, Cd, Cu, Fe, Mn, Pb, and Zn in Peru Creek exceed aquatic life standards. Constituent loading within the study reach is dominated by effluent from the Pennsylvania Mine, with over 50% of the Cd, Cu, Fe, Mn, and Zn loads attributable to a collapsed adit near the top of the study reach. These estimates of mass load may underestimate the effect of the Pennsylvania Mine as leakage from underground mine workings may contribute to metal loads that are currently attributed to the wetland area. This potential leakage confounds the evaluation of remedial options and additional research is needed to determine the magnitude and location of the leakage.

Estimating instream constituent loads using replicate synoptic sampling, Peru Creek, Colorado

USGS Publications Warehouse

Runkel, Robert L.; Walton-Day, Katherine; Kimball, Briant A.; Verplanck, Philip L.; Nimick, David A.

2013-01-01

The synoptic mass balance approach is often used to evaluate constituent mass loading in streams affected by mine drainage. Spatial profiles of constituent mass load are used to identify sources of contamination and prioritize sites for remedial action. This paper presents a field scale study in which replicate synoptic sampling campaigns are used to quantify the aggregate uncertainty in constituent load that arises from (1) laboratory analyses of constituent and tracer concentrations, (2) field sampling error, and (3) temporal variation in concentration from diel constituent cycles and/or source variation. Consideration of these factors represents an advance in the application of the synoptic mass balance approach by placing error bars on estimates of constituent load and by allowing all sources of uncertainty to be quantified in aggregate; previous applications of the approach have provided only point estimates of constituent load and considered only a subset of the possible errors. Given estimates of aggregate uncertainty, site specific data and expert judgement may be used to qualitatively assess the contributions of individual factors to uncertainty. This assessment can be used to guide the collection of additional data to reduce uncertainty. Further, error bars provided by the replicate approach can aid the investigator in the interpretation of spatial loading profiles and the subsequent identification of constituent source areas within the watershed.The replicate sampling approach is applied to Peru Creek, a stream receiving acidic, metal-rich effluent from the Pennsylvania Mine. Other sources of acidity and metals within the study reach include a wetland area adjacent to the mine and tributary inflow from Cinnamon Gulch. Analysis of data collected under low-flow conditions indicates that concentrations of Al, Cd, Cu, Fe, Mn, Pb, and Zn in Peru Creek exceed aquatic life standards. Constituent loading within the study reach is dominated by effluent from the Pennsylvania Mine, with over 50% of the Cd, Cu, Fe, Mn, and Zn loads attributable to a collapsed adit near the top of the study reach. These estimates of mass load may underestimate the effect of the Pennsylvania Mine as leakage from underground mine workings may contribute to metal loads that are currently attributed to the wetland area. This potential leakage confounds the evaluation of remedial options and additional research is needed to determine the magnitude and location of the leakage.

Effectiveness of the New Hampshire stream-gaging network in providing regional streamflow information

USGS Publications Warehouse

Olson, Scott A.

2003-01-01

The stream-gaging network in New Hampshire was analyzed for its effectiveness in providing regional information on peak-flood flow, mean-flow, and low-flow frequency. The data available for analysis were from stream-gaging stations in New Hampshire and selected stations in adjacent States. The principles of generalized-least-squares regression analysis were applied to develop regional regression equations that relate streamflow-frequency characteristics to watershed characteristics. Regression equations were developed for (1) the instantaneous peak flow with a 100-year recurrence interval, (2) the mean-annual flow, and (3) the 7-day, 10-year low flow. Active and discontinued stream-gaging stations with 10 or more years of flow data were used to develop the regression equations. Each stream-gaging station in the network was evaluated and ranked on the basis of how much the data from that station contributed to the cost-weighted sampling-error component of the regression equation. The potential effect of data from proposed and new stream-gaging stations on the sampling error also was evaluated. The stream-gaging network was evaluated for conditions in water year 2000 and for estimated conditions under various network strategies if an additional 5 years and 20 years of streamflow data were collected. The effectiveness of the stream-gaging network in providing regional streamflow information could be improved for all three flow characteristics with the collection of additional flow data, both temporally and spatially. With additional years of data collection, the greatest reduction in the average sampling error of the regional regression equations was found for the peak- and low-flow characteristics. In general, additional data collection at stream-gaging stations with unregulated flow, relatively short-term record (less than 20 years), and drainage areas smaller than 45 square miles contributed the largest cost-weighted reduction to the average sampling error of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active stations, the reactivation of discontinued stations, or the activation of new stations to maximize the regional information content provided by the stream-gaging network. Final decisions regarding altering the New Hampshire stream-gaging network would require the consideration of the many uses of the streamflow data serving local, State, and Federal interests.