Errors in measuring water potentials of small samples resulting from water adsorption by thermocouple psychrometer chambers.

PubMed

Bennett, J M; Cortes, P M

1985-09-01

The adsorption of water by thermocouple psychrometer assemblies is known to cause errors in the determination of water potential. Experiments were conducted to evaluate the effect of sample size and psychrometer chamber volume on measured water potentials of leaf discs, leaf segments, and sodium chloride solutions. Reasonable agreement was found between soybean (Glycine max L. Merr.) leaf water potentials measured on 5-millimeter radius leaf discs and large leaf segments. Results indicated that while errors due to adsorption may be significant when using small volumes of tissue, if sufficient tissue is used the errors are negligible. Because of the relationship between water potential and volume in plant tissue, the errors due to adsorption were larger with turgid tissue. Large psychrometers which were sealed into the sample chamber with latex tubing appeared to adsorb more water than those sealed with flexible plastic tubing. Estimates are provided of the amounts of water adsorbed by two different psychrometer assemblies and the amount of tissue sufficient for accurate measurements of leaf water potential with these assemblies. It is also demonstrated that water adsorption problems may have generated low water potential values which in prior studies have been attributed to large cut surface area to volume ratios.

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.

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.

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.

Hospital-based transfusion error tracking from 2005 to 2010: identifying the key errors threatening patient transfusion safety.

PubMed

Maskens, Carolyn; Downie, Helen; Wendt, Alison; Lima, Ana; Merkley, Lisa; Lin, Yulia; Callum, Jeannie

2014-01-01

This report provides a comprehensive analysis of transfusion errors occurring at a large teaching hospital and aims to determine key errors that are threatening transfusion safety, despite implementation of safety measures. Errors were prospectively identified from 2005 to 2010. Error data were coded on a secure online database called the Transfusion Error Surveillance System. Errors were defined as any deviation from established standard operating procedures. Errors were identified by clinical and laboratory staff. Denominator data for volume of activity were used to calculate rates. A total of 15,134 errors were reported with a median number of 215 errors per month (range, 85-334). Overall, 9083 (60%) errors occurred on the transfusion service and 6051 (40%) on the clinical services. In total, 23 errors resulted in patient harm: 21 of these errors occurred on the clinical services and two in the transfusion service. Of the 23 harm events, 21 involved inappropriate use of blood. Errors with no harm were 657 times more common than events that caused harm. The most common high-severity clinical errors were sample labeling (37.5%) and inappropriate ordering of blood (28.8%). The most common high-severity error in the transfusion service was sample accepted despite not meeting acceptance criteria (18.3%). The cost of product and component loss due to errors was $593,337. Errors occurred at every point in the transfusion process, with the greatest potential risk of patient harm resulting from inappropriate ordering of blood products and errors in sample labeling. © 2013 American Association of Blood Banks (CME).

Measurement variability error for estimates of volume change

Treesearch

James A. Westfall; Paul L. Patterson

2007-01-01

Using quality assurance data, measurement variability distributions were developed for attributes that affect tree volume prediction. Random deviations from the measurement variability distributions were applied to 19381 remeasured sample trees in Maine. The additional error due to measurement variation and measurement bias was estimated via a simulation study for...

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

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).

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.

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.

Elimination of Emergency Department Medication Errors Due To Estimated Weights.

PubMed

Greenwalt, Mary; Griffen, David; Wilkerson, Jim

2017-01-01

From 7/2014 through 6/2015, 10 emergency department (ED) medication dosing errors were reported through the electronic incident reporting system of an urban academic medical center. Analysis of these medication errors identified inaccurate estimated weight on patients as the root cause. The goal of this project was to reduce weight-based dosing medication errors due to inaccurate estimated weights on patients presenting to the ED. Chart review revealed that 13.8% of estimated weights documented on admitted ED patients varied more than 10% from subsequent actual admission weights recorded. A random sample of 100 charts containing estimated weights revealed 2 previously unreported significant medication dosage errors (.02 significant error rate). Key improvements included removing barriers to weighing ED patients, storytelling to engage staff and change culture, and removal of the estimated weight documentation field from the ED electronic health record (EHR) forms. With these improvements estimated weights on ED patients, and the resulting medication errors, were eliminated.

A 2 × 2 taxonomy of multilevel latent contextual models: accuracy-bias trade-offs in full and partial error correction models.

PubMed

Lüdtke, Oliver; Marsh, Herbert W; Robitzsch, Alexander; Trautwein, Ulrich

2011-12-01

In multilevel modeling, group-level variables (L2) for assessing contextual effects are frequently generated by aggregating variables from a lower level (L1). A major problem of contextual analyses in the social sciences is that there is no error-free measurement of constructs. In the present article, 2 types of error occurring in multilevel data when estimating contextual effects are distinguished: unreliability that is due to measurement error and unreliability that is due to sampling error. The fact that studies may or may not correct for these 2 types of error can be translated into a 2 × 2 taxonomy of multilevel latent contextual models comprising 4 approaches: an uncorrected approach, partial correction approaches correcting for either measurement or sampling error (but not both), and a full correction approach that adjusts for both sources of error. It is shown mathematically and with simulated data that the uncorrected and partial correction approaches can result in substantially biased estimates of contextual effects, depending on the number of L1 individuals per group, the number of groups, the intraclass correlation, the number of indicators, and the size of the factor loadings. However, the simulation study also shows that partial correction approaches can outperform full correction approaches when the data provide only limited information in terms of the L2 construct (i.e., small number of groups, low intraclass correlation). A real-data application from educational psychology is used to illustrate the different approaches.

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.

Errors in the estimation of approximate entropy and other recurrence-plot-derived indices due to the finite resolution of RR time series.

PubMed

García-González, Miguel A; Fernández-Chimeno, Mireya; Ramos-Castro, Juan

2009-02-01

An analysis of the errors due to the finite resolution of RR time series in the estimation of the approximate entropy (ApEn) is described. The quantification errors in the discrete RR time series produce considerable errors in the ApEn estimation (bias and variance) when the signal variability or the sampling frequency is low. Similar errors can be found in indices related to the quantification of recurrence plots. An easy way to calculate a figure of merit [the signal to resolution of the neighborhood ratio (SRN)] is proposed in order to predict when the bias in the indices could be high. When SRN is close to an integer value n, the bias is higher than when near n - 1/2 or n + 1/2. Moreover, if SRN is close to an integer value, the lower this value, the greater the bias is.

Effect of sample inhomogeneity in KAr dating

USGS Publications Warehouse

Engels, J.C.; Ingamells, C.O.

1970-01-01

Error in K-Ar ages is often due more to deficiencies in the splitting process, whereby portions of the sample are taken for potassium and for argon determination, than to imprecision in the analytical methods. The effect of the grain size of a sample and of the composition of a contaminating mineral can be evaluated, and this provides a useful guide in attempts to minimize error. Rocks and minerals should be prepared for age determination with the effects of contaminants and grain size in mind. The magnitude of such effects can be much larger than intuitive estimates might indicate. ?? 1970.

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

[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.

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.

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.

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.

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).

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.

Precision and Error of Three-dimensional Phenotypic Measures Acquired from 3dMD Photogrammetric Images

PubMed Central

Aldridge, Kristina; Boyadjiev, Simeon A.; Capone, George T.; DeLeon, Valerie B.; Richtsmeier, Joan T.

2015-01-01

The genetic basis for complex phenotypes is currently of great interest for both clinical investigators and basic scientists. In order to acquire a thorough understanding of the translation from genotype to phenotype, highly precise measures of phenotypic variation are required. New technologies, such as 3D photogrammetry are being implemented in phenotypic studies due to their ability to collect data rapidly and non-invasively. Before these systems can be broadly implemented the error associated with data collected from images acquired using these technologies must be assessed. This study investigates the precision, error, and repeatability associated with anthropometric landmark coordinate data collected from 3D digital photogrammetric images acquired with the 3dMDface System. Precision, error due to the imaging system, error due to digitization of the images, and repeatability are assessed in a sample of children and adults (N=15). Results show that data collected from images with the 3dMDface System are highly repeatable and precise. The average error associated with the placement of landmarks is sub-millimeter; both the error due to digitization and to the imaging system are very low. The few measures showing a higher degree of error include those crossing the labial fissure, which are influenced by even subtle movement of the mandible. These results suggest that 3D anthropometric data collected using the 3dMDface System are highly reliable and therefore useful for evaluation of clinical dysmorphology and surgery, analyses of genotype-phenotype correlations, and inheritance of complex phenotypes. PMID:16158436

Uncertainty in predicting soil hydraulic properties at the hillslope scale with indirect methods

NASA Astrophysics Data System (ADS)

Chirico, G. B.; Medina, H.; Romano, N.

2007-02-01

SummarySeveral hydrological applications require the characterisation of the soil hydraulic properties at large spatial scales. Pedotransfer functions (PTFs) are being developed as simplified methods to estimate soil hydraulic properties as an alternative to direct measurements, which are unfeasible for most practical circumstances. The objective of this study is to quantify the uncertainty in PTFs spatial predictions at the hillslope scale as related to the sampling density, due to: (i) the error in estimated soil physico-chemical properties and (ii) PTF model error. The analysis is carried out on a 2-km-long experimental hillslope in South Italy. The method adopted is based on a stochastic generation of patterns of soil variables using sequential Gaussian simulation, conditioned to the observed sample data. The following PTFs are applied: Vereecken's PTF [Vereecken, H., Diels, J., van Orshoven, J., Feyen, J., Bouma, J., 1992. Functional evaluation of pedotransfer functions for the estimation of soil hydraulic properties. Soil Sci. Soc. Am. J. 56, 1371-1378] and HYPRES PTF [Wösten, J.H.M., Lilly, A., Nemes, A., Le Bas, C., 1999. Development and use of a database of hydraulic properties of European soils. Geoderma 90, 169-185]. The two PTFs estimate reliably the soil water retention characteristic even for a relatively coarse sampling resolution, with prediction uncertainties comparable to the uncertainties in direct laboratory or field measurements. The uncertainty of soil water retention prediction due to the model error is as much as or more significant than the uncertainty associated with the estimated input, even for a relatively coarse sampling resolution. Prediction uncertainties are much more important when PTF are applied to estimate the saturated hydraulic conductivity. In this case model error dominates the overall prediction uncertainties, making negligible the effect of the input error.

A Bayesian Measurment Error Model for Misaligned Radiographic Data

DOE PAGES

Lennox, Kristin P.; Glascoe, Lee G.

2013-09-06

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error inmore » addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.« less

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-10-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. Here, we are applying a consistent approach based on auto- and cross-covariance functions to quantify the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining data sets from several analysers and using simulations, we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time lag eliminates these effects (provided the time lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

Eddy-covariance data with low signal-to-noise ratio: time-lag determination, uncertainties and limit of detection

NASA Astrophysics Data System (ADS)

Langford, B.; Acton, W.; Ammann, C.; Valach, A.; Nemitz, E.

2015-03-01

All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. We are here applying a consistent approach based on auto- and cross-covariance functions to quantifying the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time-lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time-lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining datasets from several analysers and using simulations we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time-lag eliminates these effects (provided the time-lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time-lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.

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.

Skylab water balance error analysis

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1977-01-01

Estimates of the precision of the net water balance were obtained for the entire Skylab preflight and inflight phases as well as for the first two weeks of flight. Quantitative estimates of both total sampling errors and instrumentation errors were obtained. It was shown that measurement error is minimal in comparison to biological variability and little can be gained from improvement in analytical accuracy. In addition, a propagation of error analysis demonstrated that total water balance error could be accounted for almost entirely by the errors associated with body mass changes. Errors due to interaction between terms in the water balance equation (covariances) represented less than 10% of the total error. Overall, the analysis provides evidence that daily measurements of body water changes obtained from the indirect balance technique are reasonable, precise, and relaible. The method is not biased toward net retention or loss.

Improving the accuracy of hyaluronic acid molecular weight estimation by conventional size exclusion chromatography.

PubMed

Shanmuga Doss, Sreeja; Bhatt, Nirav Pravinbhai; Jayaraman, Guhan

2017-08-15

There is an unreasonably high variation in the literature reports on molecular weight of hyaluronic acid (HA) estimated using conventional size exclusion chromatography (SEC). This variation is most likely due to errors in estimation. Working with commercially available HA molecular weight standards, this work examines the extent of error in molecular weight estimation due to two factors: use of non-HA based calibration and concentration of sample injected into the SEC column. We develop a multivariate regression correlation to correct for concentration effect. Our analysis showed that, SEC calibration based on non-HA standards like polyethylene oxide and pullulan led to approximately 2 and 10 times overestimation, respectively, when compared to HA-based calibration. Further, we found that injected sample concentration has an effect on molecular weight estimation. Even at 1g/l injected sample concentration, HA molecular weight standards of 0.7 and 1.64MDa showed appreciable underestimation of 11-24%. The multivariate correlation developed was found to reduce error in estimations at 1g/l to <4%. The correlation was also successfully applied to accurately estimate the molecular weight of HA produced by a recombinant Lactococcus lactis fermentation. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

IQ Gains and the Binet Decrements.

ERIC Educational Resources Information Center

Flynn, James R.

1984-01-01

Thorndike's Stanford-Binet data suggest that from 1932 to 1971-72 preschool children enjoyed greater IQ gains than older children, possibly due to the rise of television. Additional analysis indicated that gains were either due to sampling error or totally antedated 1947. Gains of 12 IQ points were found for Americans. (Author/EGS)

Underestimating the effects of spatial heterogeneity due to individual movement and spatial scale: infectious disease as an example

USGS Publications Warehouse

Cross, Paul C.; Caillaud, Damien; Heisey, Dennis M.

2013-01-01

Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.

On the accuracy and precision of numerical waveforms: effect of waveform extraction methodology

NASA Astrophysics Data System (ADS)

Chu, Tony; Fong, Heather; Kumar, Prayush; Pfeiffer, Harald P.; Boyle, Michael; Hemberger, Daniel A.; Kidder, Lawrence E.; Scheel, Mark A.; Szilagyi, Bela

2016-08-01

We present a new set of 95 numerical relativity simulations of non-precessing binary black holes (BBHs). The simulations sample comprehensively both black-hole spins up to spin magnitude of 0.9, and cover mass ratios 1-3. The simulations cover on average 24 inspiral orbits, plus merger and ringdown, with low initial orbital eccentricities e\\lt {10}-4. A subset of the simulations extends the coverage of non-spinning BBHs up to mass ratio q = 10. Gravitational waveforms at asymptotic infinity are computed with two independent techniques: extrapolation and Cauchy characteristic extraction. An error analysis based on noise-weighted inner products is performed. We find that numerical truncation error, error due to gravitational wave extraction, and errors due to the Fourier transformation of signals with finite length of the numerical waveforms are of similar magnitude, with gravitational wave extraction errors dominating at noise-weighted mismatches of ˜ 3× {10}-4. This set of waveforms will serve to validate and improve aligned-spin waveform models for gravitational wave science.

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

Determining the sample size for co-dominant molecular marker-assisted linkage detection for a monogenic qualitative trait by controlling the type-I and type-II errors in a segregating F2 population.

PubMed

Hühn, M; Piepho, H P

2003-03-01

Tests for linkage are usually performed using the lod score method. A critical question in linkage analyses is the choice of sample size. The appropriate sample size depends on the desired type-I error and power of the test. This paper investigates the exact type-I error and power of the lod score method in a segregating F(2) population with co-dominant markers and a qualitative monogenic dominant-recessive trait. For illustration, a disease-resistance trait is considered, where the susceptible allele is recessive. A procedure is suggested for finding the appropriate sample size. It is shown that recessive plants have about twice the information content of dominant plants, so the former should be preferred for linkage detection. In some cases the exact alpha-values for a given nominal alpha may be rather small due to the discrete nature of the sampling distribution in small samples. We show that a gain in power is possible by using exact methods.

Diagnosing and Correcting Mass Accuracy and Signal Intensity Error Due to Initial Ion Position Variations in a MALDI TOFMS

NASA Astrophysics Data System (ADS)

Malys, Brian J.; Piotrowski, Michelle L.; Owens, Kevin G.

2018-02-01

Frustrated by worse than expected error for both peak area and time-of-flight (TOF) in matrix assisted laser desorption ionization (MALDI) experiments using samples prepared by electrospray deposition, it was finally determined that there was a correlation between sample location on the target plate and the measured TOF/peak area. Variations in both TOF and peak area were found to be due to small differences in the initial position of ions formed in the source region of the TOF mass spectrometer. These differences arise largely from misalignment of the instrument sample stage, with a smaller contribution arising from the non-ideal shape of the target plates used. By physically measuring the target plates used and comparing TOF data collected from three different instruments, an estimate of the magnitude and direction of the sample stage misalignment was determined for each of the instruments. A correction method was developed to correct the TOFs and peak areas obtained for a given combination of target plate and instrument. Two correction factors are determined, one by initially collecting spectra from each sample position used and another by using spectra from a single position for each set of samples on a target plate. For TOF and mass values, use of the correction factor reduced the error by a factor of 4, with the relative standard deviation (RSD) of the corrected masses being reduced to 12-24 ppm. For the peak areas, the RSD was reduced from 28% to 16% for samples deposited twice onto two target plates over two days.

Diagnosing and Correcting Mass Accuracy and Signal Intensity Error Due to Initial Ion Position Variations in a MALDI TOFMS

NASA Astrophysics Data System (ADS)

Malys, Brian J.; Piotrowski, Michelle L.; Owens, Kevin G.

2017-12-01

Frustrated by worse than expected error for both peak area and time-of-flight (TOF) in matrix assisted laser desorption ionization (MALDI) experiments using samples prepared by electrospray deposition, it was finally determined that there was a correlation between sample location on the target plate and the measured TOF/peak area. Variations in both TOF and peak area were found to be due to small differences in the initial position of ions formed in the source region of the TOF mass spectrometer. These differences arise largely from misalignment of the instrument sample stage, with a smaller contribution arising from the non-ideal shape of the target plates used. By physically measuring the target plates used and comparing TOF data collected from three different instruments, an estimate of the magnitude and direction of the sample stage misalignment was determined for each of the instruments. A correction method was developed to correct the TOFs and peak areas obtained for a given combination of target plate and instrument. Two correction factors are determined, one by initially collecting spectra from each sample position used and another by using spectra from a single position for each set of samples on a target plate. For TOF and mass values, use of the correction factor reduced the error by a factor of 4, with the relative standard deviation (RSD) of the corrected masses being reduced to 12-24 ppm. For the peak areas, the RSD was reduced from 28% to 16% for samples deposited twice onto two target plates over two days. [Figure not available: see fulltext.

Quantifying Adventitious Error in a Covariance Structure as a Random Effect

PubMed Central

Wu, Hao; Browne, Michael W.

2017-01-01

We present an approach to quantifying errors in covariance structures in which adventitious error, identified as the process underlying the discrepancy between the population and the structured model, is explicitly modeled as a random effect with a distribution, and the dispersion parameter of this distribution to be estimated gives a measure of misspecification. Analytical properties of the resultant procedure are investigated and the measure of misspecification is found to be related to the RMSEA. An algorithm is developed for numerical implementation of the procedure. The consistency and asymptotic sampling distributions of the estimators are established under a new asymptotic paradigm and an assumption weaker than the standard Pitman drift assumption. Simulations validate the asymptotic sampling distributions and demonstrate the importance of accounting for the variations in the parameter estimates due to adventitious error. Two examples are also given as illustrations. PMID:25813463

Determination of nutritional parameters of yoghurts by FT Raman spectroscopy

NASA Astrophysics Data System (ADS)

Czaja, Tomasz; Baranowska, Maria; Mazurek, Sylwester; Szostak, Roman

2018-05-01

FT-Raman quantitative analysis of nutritional parameters of yoghurts was performed with the help of partial least squares models. The relative standard errors of prediction for fat, lactose and protein determination in the quantified commercial samples equalled to 3.9, 3.2 and 3.6%, respectively. Models based on attenuated total reflectance spectra of the liquid yoghurt samples and of dried yoghurt films collected with the single reflection diamond accessory showed relative standard errors of prediction values of 1.6-5.0% and 2.7-5.2%, respectively, for the analysed components. Despite a relatively low signal-to-noise ratio in the obtained spectra, Raman spectroscopy, combined with chemometrics, constitutes a fast and powerful tool for macronutrients quantification in yoghurts. Errors received for attenuated total reflectance method were found to be relatively higher than those for Raman spectroscopy due to inhomogeneity of the analysed samples.

Pyrometer with tracking balancing

NASA Astrophysics Data System (ADS)

Ponomarev, D. B.; Zakharenko, V. A.; Shkaev, A. G.

2018-04-01

Currently, one of the main metrological noncontact temperature measurement challenges is the emissivity uncertainty. This paper describes a pyrometer with emissivity effect diminishing through the use of a measuring scheme with tracking balancing in which the radiation receiver is a null-indicator. In this paper the results of the prototype pyrometer absolute error study in surfaces temperature measurement of aluminum and nickel samples are presented. There is absolute error calculated values comparison considering the emissivity table values with errors on the results of experimental measurements by the proposed method. The practical implementation of the proposed technical solution has allowed two times to reduce the error due to the emissivity uncertainty.

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

Three-dimensional FLASH Laser Radar Range Estimation via Blind Deconvolution

DTIC Science & Technology

2009-10-01

scene can result in errors due to several factors including the optical spatial impulse response, detector blurring, photon noise , timing jitter, and...estimation error include spatial blur, detector blurring, noise , timing jitter, and inter-sample targets. Unlike previous research, this paper ac- counts...for pixel coupling by defining the range image mathematical model as a 2D convolution between the system spatial impulse response and the object (target

Spatial effects, sampling errors, and task specialization in the honey bee.

PubMed

Johnson, B R

2010-05-01

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists.

Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: organic carbon

NASA Astrophysics Data System (ADS)

Dillner, A. M.; Takahama, S.

2015-03-01

Organic carbon (OC) can constitute 50% or more of the mass of atmospheric particulate matter. Typically, organic carbon is measured from a quartz fiber filter that has been exposed to a volume of ambient air and analyzed using thermal methods such as thermal-optical reflectance (TOR). Here, methods are presented that show the feasibility of using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters to accurately predict TOR OC. This work marks an initial step in proposing a method that can reduce the operating costs of large air quality monitoring networks with an inexpensive, non-destructive analysis technique using routinely collected PTFE filter samples which, in addition to OC concentrations, can concurrently provide information regarding the composition of organic aerosol. This feasibility study suggests that the minimum detection limit and errors (or uncertainty) of FT-IR predictions are on par with TOR OC such that evaluation of long-term trends and epidemiological studies would not be significantly impacted. 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 collected during 2011. Partial least-squares regression is used to calibrate sample FT-IR absorbance spectra to TOR OC. The FTIR spectra are divided into calibration and test sets by sampling site and date. The calibration produces precise and accurate TOR OC predictions of the test set samples by FT-IR as indicated by high coefficient of variation (R2; 0.96), low bias (0.02 μg m-3, the nominal IMPROVE sample volume is 32.8 m3), 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 to collocated TOR measurements. FT-IR spectra are also divided into calibration and test sets by OC mass and by OM / OC ratio, which reflects the organic composition of the particulate matter and is obtained from organic functional group composition; these divisions 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 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).

A new high resolution permafrost map of Iceland from Earth Observation data

NASA Astrophysics Data System (ADS)

Barnie, Talfan; Conway, Susan; Balme, Matt; Graham, Alastair

2017-04-01

High resolution maps of permafrost are required for ongoing monitoring of environmental change and the resulting hazards to ecosystems, people and infrastructure. However, permafrost maps are difficult to construct - direct observations require maintaining networks of sensors and boreholes in harsh environments and are thus limited in extent in space and time, and indirect observations require models or assumptions relating the measurements (e.g. weather station air temperature, basal snow temperature) to ground temperature. Operationally produced Land Surface Temperature maps from Earth Observation data can be used to make spatially contiguous estimates of mean annual skin temperature, which has been used a proxy for the presence of permafrost. However these maps are subject to biases due to (i) selective sampling during the day due to limited satellite overpass times, (ii) selective sampling over the year due to seasonally varying cloud cover, (iii) selective sampling of LST only during clearsky conditions, (iv) errors in cloud masking (v) errors in temperature emissivity separation (vi) smoothing over spatial variability. In this study we attempt to compensate for some of these problems using a bayesian modelling approach and high resolution topography-based downscaling.

Evaluation of monthly rainfall estimates derived from the special sensor microwave/imager (SSM/I) over the tropical Pacific

NASA Technical Reports Server (NTRS)

Berg, Wesley; Avery, Susan K.

1995-01-01

Estimates of monthly rainfall have been computed over the tropical Pacific using passive microwave satellite observations from the special sensor microwave/imager (SSM/I) for the period from July 1987 through December 1990. These monthly estimates are calibrated using data from a network of Pacific atoll rain gauges in order to account for systematic biases and are then compared with several visible and infrared satellite-based rainfall estimation techniques for the purpose of evaluating the performance of the microwave-based estimates. Although several key differences among the various techniques are observed, the general features of the monthly rainfall time series agree very well. Finally, the significant error sources contributing to uncertainties in the monthly estimates are examined and an estimate of the total error is produced. The sampling error characteristics are investigated using data from two SSM/I sensors and a detailed analysis of the characteristics of the diurnal cycle of rainfall over the oceans and its contribution to sampling errors in the monthly SSM/I estimates is made using geosynchronous satellite data. Based on the analysis of the sampling and other error sources the total error was estimated to be of the order of 30 to 50% of the monthly rainfall for estimates averaged over 2.5 deg x 2.5 deg latitude/longitude boxes, with a contribution due to diurnal variability of the order of 10%.

Thermal error analysis and compensation for digital image/volume correlation

NASA Astrophysics Data System (ADS)

Pan, Bing

2018-02-01

Digital image/volume correlation (DIC/DVC) rely on the digital images acquired by digital cameras and x-ray CT scanners to extract the motion and deformation of test samples. Regrettably, these imaging devices are unstable optical systems, whose imaging geometry may undergo unavoidable slight and continual changes due to self-heating effect or ambient temperature variations. Changes in imaging geometry lead to both shift and expansion in the recorded 2D or 3D images, and finally manifest as systematic displacement and strain errors in DIC/DVC measurements. Since measurement accuracy is always the most important requirement in various experimental mechanics applications, these thermal-induced errors (referred to as thermal errors) should be given serious consideration in order to achieve high accuracy, reproducible DIC/DVC measurements. In this work, theoretical analyses are first given to understand the origin of thermal errors. Then real experiments are conducted to quantify thermal errors. Three solutions are suggested to mitigate or correct thermal errors. Among these solutions, a reference sample compensation approach is highly recommended because of its easy implementation, high accuracy and in-situ error correction capability. Most of the work has appeared in our previously published papers, thus its originality is not claimed. Instead, this paper aims to give a comprehensive overview and more insights of our work on thermal error analysis and compensation for DIC/DVC measurements.

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

The efficacy of protoporphyrin as a predictive biomarker for lead exposure in canvasback ducks: effect of sample storage time

USGS Publications Warehouse

Franson, J.C.; Hohman, W.L.; Moore, J.L.; Smith, M.R.

1996-01-01

We used 363 blood samples collected from wild canvasback dueks (Aythya valisineria) at Catahoula Lake, Louisiana, U.S.A. to evaluate the effect of sample storage time on the efficacy of erythrocytic protoporphyrin as an indicator of lead exposure. The protoporphyrin concentration of each sample was determined by hematofluorometry within 5 min of blood collection and after refrigeration at 4 °C for 24 and 48 h. All samples were analyzed for lead by atomic absorption spectrophotometry. Based on a blood lead concentration of ≥0.2 ppm wet weight as positive evidence for lead exposure, the protoporphyrin technique resulted in overall error rates of 29%, 20%, and 19% and false negative error rates of 47%, 29% and 25% when hematofluorometric determinations were made on blood at 5 min, 24 h, and 48 h, respectively. False positive error rates were less than 10% for all three measurement times. The accuracy of the 24-h erythrocytic protoporphyrin classification of blood samples as positive or negative for lead exposure was significantly greater than the 5-min classification, but no improvement in accuracy was gained when samples were tested at 48 h. The false negative errors were probably due, at least in part, to the lag time between lead exposure and the increase of blood protoporphyrin concentrations. False negatives resulted in an underestimation of the true number of canvasbacks exposed to lead, indicating that hematofluorometry provides a conservative estimate of lead exposure.

Increased instrument intelligence--can it reduce laboratory error?

PubMed

Jekelis, Albert W

2005-01-01

Recent literature has focused on the reduction of laboratory errors and the potential impact on patient management. This study assessed the intelligent, automated preanalytical process-control abilities in newer generation analyzers as compared with older analyzers and the impact on error reduction. Three generations of immuno-chemistry analyzers were challenged with pooled human serum samples for a 3-week period. One of the three analyzers had an intelligent process of fluidics checks, including bubble detection. Bubbles can cause erroneous results due to incomplete sample aspiration. This variable was chosen because it is the most easily controlled sample defect that can be introduced. Traditionally, lab technicians have had to visually inspect each sample for the presence of bubbles. This is time consuming and introduces the possibility of human error. Instruments with bubble detection may be able to eliminate the human factor and reduce errors associated with the presence of bubbles. Specific samples were vortexed daily to introduce a visible quantity of bubbles, then immediately placed in the daily run. Errors were defined as a reported result greater than three standard deviations below the mean and associated with incomplete sample aspiration of the analyte of the individual analyzer Three standard deviations represented the target limits of proficiency testing. The results of the assays were examined for accuracy and precision. Efficiency, measured as process throughput, was also measured to associate a cost factor and potential impact of the error detection on the overall process. The analyzer performance stratified according to their level of internal process control The older analyzers without bubble detection reported 23 erred results. The newest analyzer with bubble detection reported one specimen incorrectly. The precision and accuracy of the nonvortexed specimens were excellent and acceptable for all three analyzers. No errors were found in the nonvortexed specimens. There were no significant differences in overall process time for any of the analyzers when tests were arranged in an optimal configuration. The analyzer with advanced fluidic intelligence demostrated the greatest ability to appropriately deal with an incomplete aspiration by not processing and reporting a result for the sample. This study suggests that preanalytical process-control capabilities could reduce errors. By association, it implies that similar intelligent process controls could favorably impact the error rate and, in the case of this instrument, do it without negatively impacting process throughput. Other improvements may be realized as a result of having an intelligent error-detection process including further reduction in misreported results, fewer repeats, less operator intervention, and less reagent waste.

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

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.

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.

Does size matter? Statistical limits of paleomagnetic field reconstruction from small rock specimens

NASA Astrophysics Data System (ADS)

Berndt, Thomas; Muxworthy, Adrian R.; Fabian, Karl

2016-01-01

As samples of ever decreasing sizes are being studied paleomagnetically, care has to be taken that the underlying assumptions of statistical thermodynamics (Maxwell-Boltzmann statistics) are being met. Here we determine how many grains and how large a magnetic moment a sample needs to have to be able to accurately record an ambient field. It is found that for samples with a thermoremanent magnetic moment larger than 10-11Am2 the assumption of a sufficiently large number of grains is usually given. Standard 25 mm diameter paleomagnetic samples usually contain enough magnetic grains such that statistical errors are negligible, but "single silicate crystal" works on, for example, zircon, plagioclase, and olivine crystals are approaching the limits of what is physically possible, leading to statistic errors in both the angular deviation and paleointensity that are comparable to other sources of error. The reliability of nanopaleomagnetic imaging techniques capable of resolving individual grains (used, for example, to study the cloudy zone in meteorites), however, is questionable due to the limited area of the material covered.

Claims, errors, and compensation payments in medical malpractice litigation.

PubMed

Studdert, David M; Mello, Michelle M; Gawande, Atul A; Gandhi, Tejal K; Kachalia, Allen; Yoon, Catherine; Puopolo, Ann Louise; Brennan, Troyen A

2006-05-11

In the current debate over tort reform, critics of the medical malpractice system charge that frivolous litigation--claims that lack evidence of injury, substandard care, or both--is common and costly. Trained physicians reviewed a random sample of 1452 closed malpractice claims from five liability insurers to determine whether a medical injury had occurred and, if so, whether it was due to medical error. We analyzed the prevalence, characteristics, litigation outcomes, and costs of claims that lacked evidence of error. For 3 percent of the claims, there were no verifiable medical injuries, and 37 percent did not involve errors. Most of the claims that were not associated with errors (370 of 515 [72 percent]) or injuries (31 of 37 [84 percent]) did not result in compensation; most that involved injuries due to error did (653 of 889 [73 percent]). Payment of claims not involving errors occurred less frequently than did the converse form of inaccuracy--nonpayment of claims associated with errors. When claims not involving errors were compensated, payments were significantly lower on average than were payments for claims involving errors (313,205 dollars vs. 521,560 dollars, P=0.004). Overall, claims not involving errors accounted for 13 to 16 percent of the system's total monetary costs. For every dollar spent on compensation, 54 cents went to administrative expenses (including those involving lawyers, experts, and courts). Claims involving errors accounted for 78 percent of total administrative costs. Claims that lack evidence of error are not uncommon, but most are denied compensation. The vast majority of expenditures go toward litigation over errors and payment of them. The overhead costs of malpractice litigation are exorbitant. Copyright 2006 Massachusetts Medical Society.

Image stretching on a curved surface to improve satellite gridding

NASA Technical Reports Server (NTRS)

Ormsby, J. P.

1975-01-01

A method for substantially reducing gridding errors due to satellite roll, pitch and yaw is given. A gimbal-mounted curved screen, scaled to 1:7,500,000, is used to stretch the satellite image whereby visible landmarks coincide with a projected map outline. The resulting rms position errors averaged 10.7 km as compared with 25.6 and 34.9 km for two samples of satellite imagery upon which image stretching was not performed.

Treatment of ocean tide aliasing in the context of a next generation gravity field mission

NASA Astrophysics Data System (ADS)

Hauk, Markus; Pail, Roland

2018-04-01

Current temporal gravity field solutions from GRACE suffer from temporal aliasing errors due to under-sampling of signal to be recovered (e.g. hydrology), uncertainties in the de-aliasing models (usually atmosphere and ocean), and imperfect ocean tide models. Especially the latter will be one of the most limiting factors in determining high resolution temporal gravity fields from future gravity missions such as GRACE Follow-on and Next-Generation Gravity Missions (NGGM). In this paper a method to co-parameterize ocean tide parameters of the 8 main tidal constituents over time spans of several years is analysed and assessed. Numerical closed-loop simulations of low-low satellite-to-satellite-tracking missions for a single polar pair and a double pair Bender-type formation are performed, using time variable geophysical background models and noise assumptions for new generation instrument technology. Compared to the single pair mission, results show a reduction of tide model errors up to 70 per cent for dedicated tidal constituents due to an enhanced spatial and temporal sampling and error isotropy for the double pair constellation. Extending the observation period from one to three years leads to a further reduction of tidal errors up to 60 per cent for certain constituents, and considering non-tidal mass changes during the estimation process leads to reductions of tidal errors between 20 per cent and 80 per cent. As part of a two-step approach, the estimated tide model is used for de-aliasing during gravity field retrieval in a second iteration, resulting in more than 50 per cent reduction of ocean tide aliasing errors for a NGGM Bender-type formation.

Estimating genotype error rates from high-coverage next-generation sequence data.

PubMed

Wall, Jeffrey D; Tang, Ling Fung; Zerbe, Brandon; Kvale, Mark N; Kwok, Pui-Yan; Schaefer, Catherine; Risch, Neil

2014-11-01

Exome and whole-genome sequencing studies are becoming increasingly common, but little is known about the accuracy of the genotype calls made by the commonly used platforms. Here we use replicate high-coverage sequencing of blood and saliva DNA samples from four European-American individuals to estimate lower bounds on the error rates of Complete Genomics and Illumina HiSeq whole-genome and whole-exome sequencing. Error rates for nonreference genotype calls range from 0.1% to 0.6%, depending on the platform and the depth of coverage. Additionally, we found (1) no difference in the error profiles or rates between blood and saliva samples; (2) Complete Genomics sequences had substantially higher error rates than Illumina sequences had; (3) error rates were higher (up to 6%) for rare or unique variants; (4) error rates generally declined with genotype quality (GQ) score, but in a nonlinear fashion for the Illumina data, likely due to loss of specificity of GQ scores greater than 60; and (5) error rates increased with increasing depth of coverage for the Illumina data. These findings, especially (3)-(5), suggest that caution should be taken in interpreting the results of next-generation sequencing-based association studies, and even more so in clinical application of this technology in the absence of validation by other more robust sequencing or genotyping methods. © 2014 Wall et al.; Published by Cold Spring Harbor Laboratory Press.

Novel approaches to estimating the turbulent kinetic energy dissipation rate from low- and moderate-resolution velocity fluctuation time series

NASA Astrophysics Data System (ADS)

Wacławczyk, Marta; Ma, Yong-Feng; Kopeć, Jacek M.; Malinowski, Szymon P.

2017-11-01

In this paper we propose two approaches to estimating the turbulent kinetic energy (TKE) dissipation rate, based on the zero-crossing method by Sreenivasan et al. (1983). The original formulation requires a fine resolution of the measured signal, down to the smallest dissipative scales. However, due to finite sampling frequency, as well as measurement errors, velocity time series obtained from airborne experiments are characterized by the presence of effective spectral cutoffs. In contrast to the original formulation the new approaches are suitable for use with signals originating from airborne experiments. The suitability of the new approaches is tested using measurement data obtained during the Physics of Stratocumulus Top (POST) airborne research campaign as well as synthetic turbulence data. They appear useful and complementary to existing methods. We show the number-of-crossings-based approaches respond differently to errors due to finite sampling and finite averaging than the classical power spectral method. Hence, their application for the case of short signals and small sampling frequencies is particularly interesting, as it can increase the robustness of turbulent kinetic energy dissipation rate retrieval.

Acidity measurement of iron ore powders using laser-induced breakdown spectroscopy with partial least squares regression.

PubMed

Hao, Z Q; Li, C M; Shen, M; Yang, X Y; Li, K H; Guo, L B; Li, X Y; Lu, Y F; Zeng, X Y

2015-03-23

Laser-induced breakdown spectroscopy (LIBS) with partial least squares regression (PLSR) has been applied to measuring the acidity of iron ore, which can be defined by the concentrations of oxides: CaO, MgO, Al₂O₃, and SiO₂. With the conventional internal standard calibration, it is difficult to establish the calibration curves of CaO, MgO, Al₂O₃, and SiO₂ in iron ore due to the serious matrix effects. PLSR is effective to address this problem due to its excellent performance in compensating the matrix effects. In this work, fifty samples were used to construct the PLSR calibration models for the above-mentioned oxides. These calibration models were validated by the 10-fold cross-validation method with the minimum root-mean-square errors (RMSE). Another ten samples were used as a test set. The acidities were calculated according to the estimated concentrations of CaO, MgO, Al₂O₃, and SiO₂ using the PLSR models. The average relative error (ARE) and RMSE of the acidity achieved 3.65% and 0.0048, respectively, for the test samples.

The performance of a sampled data delay lock loop implemented with a Kalman loop filter

NASA Astrophysics Data System (ADS)

Eilts, H. S.

1980-01-01

The purpose of this study is to evaluate the steady-state and transient (lock-up) performance of a tracking loop implemented with a Kalman filter. Steady-state performance criteria are errors due to measurement noise (jitter) and Doppler errors due to motion of the tracking loop. Trade-offs exist between the two criteria such that increasing performance with respect to either one will cause performance decrease with respect to the other. It is shown that by carefully selecting filter parameters reasonable performance can be obtained for both criteria simultaneously. It is also shown that lock-up performance for the loop is acceptable when these parameters are used.

Dosage uniformity problems which occur due to technological errors in extemporaneously prepared suppositories in hospitals and pharmacies

PubMed Central

Kalmár, Éva; Lasher, Jason Richard; Tarry, Thomas Dean; Myers, Andrea; Szakonyi, Gerda; Dombi, György; Baki, Gabriella; Alexander, Kenneth S.

2013-01-01

The availability of suppositories in Hungary, especially in clinical pharmacy practice, is usually provided by extemporaneous preparations. Due to the known advantages of rectal drug administration, its benefits are frequently utilized in pediatrics. However, errors during the extemporaneous manufacturing process can lead to non-homogenous drug distribution within the dosage units. To determine the root cause of these errors and provide corrective actions, we studied suppository samples prepared with exactly known errors using both cerimetric titration and HPLC technique. Our results show that the most frequent technological error occurs when the pharmacist fails to use the correct displacement factor in the calculations which could lead to a 4.6% increase/decrease in the assay in individual dosage units. The second most important source of error can occur when the molding excess is calculated solely for the suppository base. This can further dilute the final suppository drug concentration causing the assay to be as low as 80%. As a conclusion we emphasize that the application of predetermined displacement factors in calculations for the formulation of suppositories is highly important, which enables the pharmacist to produce a final product containing exactly the determined dose of an active substance despite the different densities of the components. PMID:25161378

Dosage uniformity problems which occur due to technological errors in extemporaneously prepared suppositories in hospitals and pharmacies.

PubMed

Kalmár, Eva; Lasher, Jason Richard; Tarry, Thomas Dean; Myers, Andrea; Szakonyi, Gerda; Dombi, György; Baki, Gabriella; Alexander, Kenneth S

2014-09-01

The availability of suppositories in Hungary, especially in clinical pharmacy practice, is usually provided by extemporaneous preparations. Due to the known advantages of rectal drug administration, its benefits are frequently utilized in pediatrics. However, errors during the extemporaneous manufacturing process can lead to non-homogenous drug distribution within the dosage units. To determine the root cause of these errors and provide corrective actions, we studied suppository samples prepared with exactly known errors using both cerimetric titration and HPLC technique. Our results show that the most frequent technological error occurs when the pharmacist fails to use the correct displacement factor in the calculations which could lead to a 4.6% increase/decrease in the assay in individual dosage units. The second most important source of error can occur when the molding excess is calculated solely for the suppository base. This can further dilute the final suppository drug concentration causing the assay to be as low as 80%. As a conclusion we emphasize that the application of predetermined displacement factors in calculations for the formulation of suppositories is highly important, which enables the pharmacist to produce a final product containing exactly the determined dose of an active substance despite the different densities of the components.

Flow tilt angle measurements using lidar anemometry

NASA Astrophysics Data System (ADS)

Dellwik, Ebba; Mann, Jakob

2010-05-01

A new way of estimating near-surface mean flow tilt angles from ground based Doppler lidar measurements is presented. The results are compared with traditional mast based in-situ sonic anemometry. The tilt angle assessed with the lidar is based on 10 or 30 minute mean values of the velocity field from a conically scanning lidar. In this mode of measurement, the lidar beam is rotated in a circle by a prism with a fixed angle to the vertical at varying focus distances. By fitting a trigonometric function to the scans, the mean vertical velocity can be estimated. Lidar measurements from (1) a fetch-limited beech forest site taken at 48-175m above ground level, (2) a reference site in flat agricultural terrain and (3) a second reference site in very complex terrain are presented. The method to derive flow tilt angles and mean vertical velocities from lidar has several advantages compared to sonic anemometry; there is no flow distortion caused by the instrument itself, there are no temperature effects and the instrument misalignment can be corrected for by comparing tilt estimates at various heights. Contrary to mast-based instruments, the lidar measures the wind field with the exact same alignment error at a multitude of heights. Disadvantages with estimating vertical velocities from a lidar compared to mast-based measurements are slightly increased levels of statistical errors due to limited sampling time, because the sampling is disjunct and a requirement for homogeneous flow. The estimated mean vertical velocity is biased if the flow over the scanned circle is not homogeneous. However, the error on the mean vertical velocity due to flow inhomogeneity can be approximated by a function of the angle of the lidar beam to the vertical, the measurement height and the vertical gradient of the mean vertical velocity, whereas the error due to flow inhomogeneity on the horizontal mean wind speed is independent of the lidar beam angle. For the presented measurements over forest, it is evaluated that the systematic error due to the inhomogeneity of the flow is less than 0.2 degrees. Other possibilities for utilizing lidars for flow tilt angle and mean vertical velocities are discussed.

Critical older driver errors in a national sample of serious U.S. crashes.

PubMed

Cicchino, Jessica B; McCartt, Anne T

2015-07-01

Older drivers are at increased risk of crash involvement per mile traveled. The purpose of this study was to examine older driver errors in serious crashes to determine which errors are most prevalent. The National Highway Traffic Safety Administration's National Motor Vehicle Crash Causation Survey collected in-depth, on-scene data for a nationally representative sample of 5470 U.S. police-reported passenger vehicle crashes during 2005-2007 for which emergency medical services were dispatched. There were 620 crashes involving 647 drivers aged 70 and older, representing 250,504 crash-involved older drivers. The proportion of various critical errors made by drivers aged 70 and older were compared with those made by drivers aged 35-54. Driver error was the critical reason for 97% of crashes involving older drivers. Among older drivers who made critical errors, the most common were inadequate surveillance (33%) and misjudgment of the length of a gap between vehicles or of another vehicle's speed, illegal maneuvers, medical events, and daydreaming (6% each). Inadequate surveillance (33% vs. 22%) and gap or speed misjudgment errors (6% vs. 3%) were more prevalent among older drivers than middle-aged drivers. Seventy-one percent of older drivers' inadequate surveillance errors were due to looking and not seeing another vehicle or failing to see a traffic control rather than failing to look, compared with 40% of inadequate surveillance errors among middle-aged drivers. About two-thirds (66%) of older drivers' inadequate surveillance errors and 77% of their gap or speed misjudgment errors were made when turning left at intersections. When older drivers traveled off the edge of the road or traveled over the lane line, this was most commonly due to non-performance errors such as medical events (51% and 44%, respectively), whereas middle-aged drivers were involved in these crash types for other reasons. Gap or speed misjudgment errors and inadequate surveillance errors were significantly more prevalent among female older drivers than among female middle-aged drivers, but the prevalence of these errors did not differ significantly between older and middle-aged male drivers. These errors comprised 51% of errors among older female drivers but only 31% among older male drivers. Efforts to reduce older driver crash involvements should focus on diminishing the likelihood of the most common driver errors. Countermeasures that simplify or remove the need to make left turns across traffic such as roundabouts, protected left turn signals, and diverging diamond intersection designs could decrease the frequency of inadequate surveillance and gap or speed misjudgment errors. In the future, vehicle-to-vehicle and vehicle-to-infrastructure communications may also help protect older drivers from these errors. Copyright © 2015 Elsevier Ltd. All rights reserved.

ERRATUM: "Reliability of the Detection of the Baryon Acoustic Peak" (2009, ApJ, 696, L93)

NASA Astrophysics Data System (ADS)

Martínez, Vicent J.; Arnalte-Mur, Pablo; Saar, Enn; de la Cruz, Pablo; Jesús Pons-Bordería, María; Paredes, Silvestre; Fernández-Soto, Alberto; Tempel, Elmo

2009-10-01

Due to an error in applying the passive evolution to transform Mg (z = 0) magnitudes to Mg (z = 0.3), the values of the magnitude limits for the samples DR7-LRG and DR7-LRG-VL quoted in Table 1 were not correct. The corrected Table 1 is appended below. Note that although the redshift limits of the sample DR7-LRG are the same as in Eisenstein et al. (2005), the magnitude limits are therefore slightly shifted (see Table 1). Once this fact is considered, figures and results are completely unaffected. We are very grateful to Eyal Kazin for pointing out the error.

Carbon monoxide measurement in the global atmospheric sampling program

NASA Technical Reports Server (NTRS)

Dudzinski, T. J.

1979-01-01

The carbon monoxide measurement system used in the NASA Global Atmospheric Sampling Program (GASP) is described. The system used a modified version of a commercially available infrared absorption analyzer. The modifications increased the sensitivity of the analyzer to 1 ppmv full scale, with a limit of detectability of 0.02 ppmv. Packaging was modified for automatic, unattended operation in an aircraft environment. The GASP system is described along with analyzer operation, calibration procedures, and measurement errors. Uncertainty of the CO measurement over a 2-year period ranged from + or - 3 to + or - 13 percent of reading, plus an error due to random fluctuation of the output signal + or - 3 to + or - 15 ppbv.

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

Sample-Clock Phase-Control Feedback

NASA Technical Reports Server (NTRS)

Quirk, Kevin J.; Gin, Jonathan W.; Nguyen, Danh H.; Nguyen, Huy

2012-01-01

To demodulate a communication signal, a receiver must recover and synchronize to the symbol timing of a received waveform. In a system that utilizes digital sampling, the fidelity of synchronization is limited by the time between the symbol boundary and closest sample time location. To reduce this error, one typically uses a sample clock in excess of the symbol rate in order to provide multiple samples per symbol, thereby lowering the error limit to a fraction of a symbol time. For systems with a large modulation bandwidth, the required sample clock rate is prohibitive due to current technological barriers and processing complexity. With precise control of the phase of the sample clock, one can sample the received signal at times arbitrarily close to the symbol boundary, thus obviating the need, from a synchronization perspective, for multiple samples per symbol. Sample-clock phase-control feedback was developed for use in the demodulation of an optical communication signal, where multi-GHz modulation bandwidths would require prohibitively large sample clock frequencies for rates in excess of the symbol rate. A custom mixedsignal (RF/digital) offset phase-locked loop circuit was developed to control the phase of the 6.4-GHz clock that samples the photon-counting detector output. The offset phase-locked loop is driven by a feedback mechanism that continuously corrects for variation in the symbol time due to motion between the transmitter and receiver as well as oscillator instability. This innovation will allow significant improvements in receiver throughput; for example, the throughput of a pulse-position modulation (PPM) with 16 slots can increase from 188 Mb/s to 1.5 Gb/s.

Standard Errors and Confidence Intervals of Norm Statistics for Educational and Psychological Tests.

PubMed

Oosterhuis, Hannah E M; van der Ark, L Andries; Sijtsma, Klaas

2016-11-14

Norm statistics allow for the interpretation of scores on psychological and educational tests, by relating the test score of an individual test taker to the test scores of individuals belonging to the same gender, age, or education groups, et cetera. Given the uncertainty due to sampling error, one would expect researchers to report standard errors for norm statistics. In practice, standard errors are seldom reported; they are either unavailable or derived under strong distributional assumptions that may not be realistic for test scores. We derived standard errors for four norm statistics (standard deviation, percentile ranks, stanine boundaries and Z-scores) under the mild assumption that the test scores are multinomially distributed. A simulation study showed that the standard errors were unbiased and that corresponding Wald-based confidence intervals had good coverage. Finally, we discuss the possibilities for applying the standard errors in practical test use in education and psychology. The procedure is provided via the R function check.norms, which is available in the mokken package.

Systematic bias in genomic classification due to contaminating non-neoplastic tissue in breast tumor samples.

PubMed

Elloumi, Fathi; Hu, Zhiyuan; Li, Yan; Parker, Joel S; Gulley, Margaret L; Amos, Keith D; Troester, Melissa A

2011-06-30

Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.

Linguistic pattern analysis of misspellings of typically developing writers in grades 1-9.

PubMed

Bahr, Ruth Huntley; Sillian, Elaine R; Berninger, Virginia W; Dow, Michael

2012-12-01

A mixed-methods approach, evaluating triple word-form theory, was used to describe linguistic patterns of misspellings. Spelling errors were taken from narrative and expository writing samples provided by 888 typically developing students in Grades 1-9. Errors were coded by category (phonological, orthographic, and morphological) and specific linguistic feature affected. Grade-level effects were analyzed with trend analysis. Qualitative analyses determined frequent error types and how use of specific linguistic features varied across grades. Phonological, orthographic, and morphological errors were noted across all grades, but orthographic errors predominated. Linear trends revealed developmental shifts in error proportions for the orthographic and morphological categories between Grades 4 and 5. Similar error types were noted across age groups, but the nature of linguistic feature error changed with age. Triple word-form theory was supported. By Grade 1, orthographic errors predominated, and phonological and morphological error patterns were evident. Morphological errors increased in relative frequency in older students, probably due to a combination of word-formation issues and vocabulary growth. These patterns suggest that normal spelling development reflects nonlinear growth and that it takes a long time to develop a robust orthographic lexicon that coordinates phonology, orthography, and morphology and supports word-specific, conventional spelling.

[Statistical Process Control (SPC) can help prevent treatment errors without increasing costs in radiotherapy].

PubMed

Govindarajan, R; Llueguera, E; Melero, A; Molero, J; Soler, N; Rueda, C; Paradinas, C

2010-01-01

Statistical Process Control (SPC) was applied to monitor patient set-up in radiotherapy and, when the measured set-up error values indicated a loss of process stability, its root cause was identified and eliminated to prevent set-up errors. Set up errors were measured for medial-lateral (ml), cranial-caudal (cc) and anterior-posterior (ap) dimensions and then the upper control limits were calculated. Once the control limits were known and the range variability was acceptable, treatment set-up errors were monitored using sub-groups of 3 patients, three times each shift. These values were plotted on a control chart in real time. Control limit values showed that the existing variation was acceptable. Set-up errors, measured and plotted on a X chart, helped monitor the set-up process stability and, if and when the stability was lost, treatment was interrupted, the particular cause responsible for the non-random pattern was identified and corrective action was taken before proceeding with the treatment. SPC protocol focuses on controlling the variability due to assignable cause instead of focusing on patient-to-patient variability which normally does not exist. Compared to weekly sampling of set-up error in each and every patient, which may only ensure that just those sampled sessions were set-up correctly, the SPC method enables set-up error prevention in all treatment sessions for all patients and, at the same time, reduces the control costs. Copyright © 2009 SECA. Published by Elsevier Espana. All rights reserved.

Qualitative and quantitative assessment of Illumina's forensic STR and SNP kits on MiSeq FGx™.

PubMed

Sharma, Vishakha; Chow, Hoi Yan; Siegel, Donald; Wurmbach, Elisa

2017-01-01

Massively parallel sequencing (MPS) is a powerful tool transforming DNA analysis in multiple fields ranging from medicine, to environmental science, to evolutionary biology. In forensic applications, MPS offers the ability to significantly increase the discriminatory power of human identification as well as aid in mixture deconvolution. However, before the benefits of any new technology can be employed, a thorough evaluation of its quality, consistency, sensitivity, and specificity must be rigorously evaluated in order to gain a detailed understanding of the technique including sources of error, error rates, and other restrictions/limitations. This extensive study assessed the performance of Illumina's MiSeq FGx MPS system and ForenSeq™ kit in nine experimental runs including 314 reaction samples. In-depth data analysis evaluated the consequences of different assay conditions on test results. Variables included: sample numbers per run, targets per run, DNA input per sample, and replications. Results are presented as heat maps revealing patterns for each locus. Data analysis focused on read numbers (allele coverage), drop-outs, drop-ins, and sequence analysis. The study revealed that loci with high read numbers performed better and resulted in fewer drop-outs and well balanced heterozygous alleles. Several loci were prone to drop-outs which led to falsely typed homozygotes and therefore to genotype errors. Sequence analysis of allele drop-in typically revealed a single nucleotide change (deletion, insertion, or substitution). Analyses of sequences, no template controls, and spurious alleles suggest no contamination during library preparation, pooling, and sequencing, but indicate that sequencing or PCR errors may have occurred due to DNA polymerase infidelities. Finally, we found utilizing Illumina's FGx System at recommended conditions does not guarantee 100% outcomes for all samples tested, including the positive control, and required manual editing due to low read numbers and/or allele drop-in. These findings are important for progressing towards implementation of MPS in forensic DNA testing.

Species-area relationships and extinction forecasts.

PubMed

Halley, John M; Sgardeli, Vasiliki; Monokrousos, Nikolaos

2013-05-01

The species-area relationship (SAR) predicts that smaller areas contain fewer species. This is the basis of the SAR method that has been used to forecast large numbers of species committed to extinction every year due to deforestation. The method has a number of issues that must be handled with care to avoid error. These include the functional form of the SAR, the choice of equation parameters, the sampling procedure used, extinction debt, and forest regeneration. Concerns about the accuracy of the SAR technique often cite errors not much larger than the natural scatter of the SAR itself. Such errors do not undermine the credibility of forecasts predicting large numbers of extinctions, although they may be a serious obstacle in other SAR applications. Very large errors can arise from misinterpretation of extinction debt, inappropriate functional form, and ignoring forest regeneration. Major challenges remain to understand better the relationship between sampling protocol and the functional form of SARs and the dynamics of relaxation, especially in continental areas, and to widen the testing of extinction forecasts. © 2013 New York Academy of Sciences.

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

How accurate are lexile text measures?

PubMed

Stenner, A Jackson; Burdick, Hal; Sanford, Eleanor E; Burdick, Donald S

2006-01-01

The Lexile Framework for Reading models comprehension as the difference between a reader measure and a text measure. Uncertainty in comprehension rates results from unreliability in reader measures and inaccuracy in text readability measures. Whole-text processing eliminates sampling error in text measures. However, Lexile text measures are imperfect due to misspecification of the Lexile theory. The standard deviation component associated with theory misspecification is estimated at 64L for a standard-length passage (approximately 125 words). A consequence is that standard errors for longer texts (2,500 to 150,000 words) are measured on the Lexile scale with uncertainties in the single digits. Uncertainties in expected comprehension rates are largely due to imprecision in reader ability and not inaccuracies in text readabilities.

Trans-dimensional matched-field geoacoustic inversion with hierarchical error models and interacting Markov chains.

PubMed

Dettmer, Jan; Dosso, Stan E

2012-10-01

This paper develops a trans-dimensional approach to matched-field geoacoustic inversion, including interacting Markov chains to improve efficiency and an autoregressive model to account for correlated errors. The trans-dimensional approach and hierarchical seabed model allows inversion without assuming any particular parametrization by relaxing model specification to a range of plausible seabed models (e.g., in this case, the number of sediment layers is an unknown parameter). Data errors are addressed by sampling statistical error-distribution parameters, including correlated errors (covariance), by applying a hierarchical autoregressive error model. The well-known difficulty of low acceptance rates for trans-dimensional jumps is addressed with interacting Markov chains, resulting in a substantial increase in efficiency. The trans-dimensional seabed model and the hierarchical error model relax the degree of prior assumptions required in the inversion, resulting in substantially improved (more realistic) uncertainty estimates and a more automated algorithm. In particular, the approach gives seabed parameter uncertainty estimates that account for uncertainty due to prior model choice (layering and data error statistics). The approach is applied to data measured on a vertical array in the Mediterranean Sea.

Incorporating measurement error in n = 1 psychological autoregressive modeling.

PubMed

Schuurman, Noémi K; Houtveen, Jan H; Hamaker, Ellen L

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30-50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters.

DETERMINING SPECIATION OF PB IN PHOSPHATE AMENDED SOILS: METHOD LIMITATIONS

EPA Science Inventory

Determining the effectiveness of in-situ immobilization for P-amended, Pb-contaminated soils has typically relied on non-spectroscopic methods that in recent years have come under scrutiny due to technical and unforeseen error issues. In this study, we analyzed 18 soil samples vi...

SU-E-T-769: T-Test Based Prior Error Estimate and Stopping Criterion for Monte Carlo Dose Calculation in Proton Therapy

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

Hong, X; Gao, H; Schuemann, J

2015-06-15

Purpose: The Monte Carlo (MC) method is a gold standard for dose calculation in radiotherapy. However, it is not a priori clear how many particles need to be simulated to achieve a given dose accuracy. Prior error estimate and stopping criterion are not well established for MC. This work aims to fill this gap. Methods: Due to the statistical nature of MC, our approach is based on one-sample t-test. We design the prior error estimate method based on the t-test, and then use this t-test based error estimate for developing a simulation stopping criterion. The three major components are asmore » follows.First, the source particles are randomized in energy, space and angle, so that the dose deposition from a particle to the voxel is independent and identically distributed (i.i.d.).Second, a sample under consideration in the t-test is the mean value of dose deposition to the voxel by sufficiently large number of source particles. Then according to central limit theorem, the sample as the mean value of i.i.d. variables is normally distributed with the expectation equal to the true deposited dose.Third, the t-test is performed with the null hypothesis that the difference between sample expectation (the same as true deposited dose) and on-the-fly calculated mean sample dose from MC is larger than a given error threshold, in addition to which users have the freedom to specify confidence probability and region of interest in the t-test based stopping criterion. Results: The method is validated for proton dose calculation. The difference between the MC Result based on the t-test prior error estimate and the statistical Result by repeating numerous MC simulations is within 1%. Conclusion: The t-test based prior error estimate and stopping criterion are developed for MC and validated for proton dose calculation. Xiang Hong and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

Evaluation of the pre-posterior distribution of optimized sampling times for the design of pharmacokinetic studies.

PubMed

Duffull, Stephen B; Graham, Gordon; Mengersen, Kerrie; Eccleston, John

2012-01-01

Information theoretic methods are often used to design studies that aim to learn about pharmacokinetic and linked pharmacokinetic-pharmacodynamic systems. These design techniques, such as D-optimality, provide the optimum experimental conditions. The performance of the optimum design will depend on the ability of the investigator to comply with the proposed study conditions. However, in clinical settings it is not possible to comply exactly with the optimum design and hence some degree of unplanned suboptimality occurs due to error in the execution of the study. In addition, due to the nonlinear relationship of the parameters of these models to the data, the designs are also locally dependent on an arbitrary choice of a nominal set of parameter values. A design that is robust to both study conditions and uncertainty in the nominal set of parameter values is likely to be of use clinically. We propose an adaptive design strategy to account for both execution error and uncertainty in the parameter values. In this study we investigate designs for a one-compartment first-order pharmacokinetic model. We do this in a Bayesian framework using Markov-chain Monte Carlo (MCMC) methods. We consider log-normal prior distributions on the parameters and investigate several prior distributions on the sampling times. An adaptive design was used to find the sampling window for the current sampling time conditional on the actual times of all previous samples.

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

Detecting and overcoming systematic errors in genome-scale phylogenies.

PubMed

Rodríguez-Ezpeleta, Naiara; Brinkmann, Henner; Roure, Béatrice; Lartillot, Nicolas; Lang, B Franz; Philippe, Hervé

2007-06-01

Genome-scale data sets result in an enhanced resolution of the phylogenetic inference by reducing stochastic errors. However, there is also an increase of systematic errors due to model violations, which can lead to erroneous phylogenies. Here, we explore the impact of systematic errors on the resolution of the eukaryotic phylogeny using a data set of 143 nuclear-encoded proteins from 37 species. The initial observation was that, despite the impressive amount of data, some branches had no significant statistical support. To demonstrate that this lack of resolution is due to a mutual annihilation of phylogenetic and nonphylogenetic signals, we created a series of data sets with slightly different taxon sampling. As expected, these data sets yielded strongly supported but mutually exclusive trees, thus confirming the presence of conflicting phylogenetic and nonphylogenetic signals in the original data set. To decide on the correct tree, we applied several methods expected to reduce the impact of some kinds of systematic error. Briefly, we show that (i) removing fast-evolving positions, (ii) recoding amino acids into functional categories, and (iii) using a site-heterogeneous mixture model (CAT) are three effective means of increasing the ratio of phylogenetic to nonphylogenetic signal. Finally, our results allow us to formulate guidelines for detecting and overcoming phylogenetic artefacts in genome-scale phylogenetic analyses.

Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements

USGS Publications Warehouse

Tarrab, Leticia; Garcia, Carlos M.; Cantero, Mariano I.; Oberg, Kevin

2012-01-01

This work presents a systematic analysis quantifying the role of the presence of turbulence fluctuations on uncertainties (random errors) of acoustic Doppler current profiler (ADCP) discharge measurements from moving platforms. Data sets of three-dimensional flow velocities with high temporal and spatial resolution were generated from direct numerical simulation (DNS) of turbulent open channel flow. Dimensionless functions relating parameters quantifying the uncertainty in discharge measurements due to flow turbulence (relative variance and relative maximum random error) to sampling configuration were developed from the DNS simulations and then validated with field-scale discharge measurements. The validated functions were used to evaluate the role of the presence of flow turbulence fluctuations on uncertainties in ADCP discharge measurements. The results of this work indicate that random errors due to the flow turbulence are significant when: (a) a low number of transects is used for a discharge measurement, and (b) measurements are made in shallow rivers using high boat velocity (short time for the boat to cross a flow turbulence structure).

Genetic and Environmental Contributions to Educational Attainment in Australia.

ERIC Educational Resources Information Center

Miller, Paul; Mulvey, Charles; Martin, Nick

2001-01-01

Data from a large sample of Australian twins indicate that 50 to 65 percent of variance in educational attainments can be attributed to genetic endowments. Only about 25 to 40 percent may be due to environmental factors, depending on adjustments for measurement error and assortative mating. (Contains 51 references.) (MLH)

Reliable estimation of orbit errors in spaceborne SAR interferometry. The network approach

NASA Astrophysics Data System (ADS)

Bähr, Hermann; Hanssen, Ramon F.

2012-12-01

An approach to improve orbital state vectors by orbit error estimates derived from residual phase patterns in synthetic aperture radar interferograms is presented. For individual interferograms, an error representation by two parameters is motivated: the baseline error in cross-range and the rate of change of the baseline error in range. For their estimation, two alternatives are proposed: a least squares approach that requires prior unwrapping and a less reliable gridsearch method handling the wrapped phase. In both cases, reliability is enhanced by mutual control of error estimates in an overdetermined network of linearly dependent interferometric combinations of images. Thus, systematic biases, e.g., due to unwrapping errors, can be detected and iteratively eliminated. Regularising the solution by a minimum-norm condition results in quasi-absolute orbit errors that refer to particular images. For the 31 images of a sample ENVISAT dataset, orbit corrections with a mutual consistency on the millimetre level have been inferred from 163 interferograms. The method itself qualifies by reliability and rigorous geometric modelling of the orbital error signal but does not consider interfering large scale deformation effects. However, a separation may be feasible in a combined processing with persistent scatterer approaches or by temporal filtering of the estimates.

Sampling errors in the measurement of rain and hail parameters

NASA Technical Reports Server (NTRS)

Gertzman, H. S.; Atlas, D.

1977-01-01

Attention is given to a general derivation of the fractional standard deviation (FSD) of any integrated property X such that X(D) = cD to the n. This work extends that of Joss and Waldvogel (1969). The equation is applicable to measuring integrated properties of cloud, rain or hail populations (such as water content, precipitation rate, kinetic energy, or radar reflectivity) which are subject to statistical sampling errors due to the Poisson distributed fluctuations of particles sampled in each particle size interval and the weighted sum of the associated variances in proportion to their contribution to the integral parameter to be measured. Universal curves are presented which are applicable to the exponential size distribution permitting FSD estimation of any parameters from n = 0 to n = 6. The equations and curves also permit corrections for finite upper limits in the size spectrum and a realistic fall speed law.

Linguistic Pattern Analysis of Misspellings of Typically Developing Writers in Grades 1 to 9

PubMed Central

Bahr, Ruth Huntley; Silliman, Elaine R.; Berninger, Virginia W.; Dow, Michael

2012-01-01

Purpose A mixed methods approach, evaluating triple word form theory, was used to describe linguistic patterns of misspellings. Method Spelling errors were taken from narrative and expository writing samples provided by 888 typically developing students in grades 1–9. Errors were coded by category (phonological, orthographic, and morphological) and specific linguistic feature affected. Grade level effects were analyzed with trend analysis. Qualitative analyses determined frequent error types and how use of specific linguistic features varied across grades. Results Phonological, orthographic, and morphological errors were noted across all grades, but orthographic errors predominated. Linear trends revealed developmental shifts in error proportions for the orthographic and morphological categories between grades 4–5. Similar error types were noted across age groups but the nature of linguistic feature error changed with age. Conclusions Triple word-form theory was supported. By grade 1, orthographic errors predominated and phonological and morphological error patterns were evident. Morphological errors increased in relative frequency in older students, probably due to a combination of word-formation issues and vocabulary growth. These patterns suggest that normal spelling development reflects non-linear growth and that it takes a long time to develop a robust orthographic lexicon that coordinates phonology, orthography, and morphology and supports word-specific, conventional spelling. PMID:22473834

Factors affecting the sticking of insects on modified aircraft wings

NASA Technical Reports Server (NTRS)

Yi, O.; Chitsaz-Z, M. R.; Eiss, N. S.; Wightman, J. P.

1988-01-01

Previous work showed that the total number of insects sticking to an aluminum surface was reduced by coating the aluminum surface with elastomers. Due to a large number of possible experimental errors, no correlation between the modulus of elasticity, the elastomer, and the total number of insects sticking to a given elastomer was obtained. One of the errors assumed to be introduced during the road test is a variable insect flux so the number of insects striking one surface might be different from that striking another sample. To eliminate this source of error, the road test used to collect insects was simulated in a laboratory by development of an insect impacting technique using a pipe and high pressure compressed air. The insects are accelerated by a compressed air gun to high velocities and are then impacted with a stationary target on which the sample is mounted. The velocity of an object exiting from the pipe was determined and further improvement of the technique was achieved to obtain a uniform air velocity distribution.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality.

PubMed

Bishara, Anthony J; Hittner, James B

2015-10-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box-Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples ( n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

PubMed Central

Hittner, James B.

2014-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box–Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples (n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated. PMID:29795841

(Sample) Size Matters: Best Practices for Defining Error in Planktic Foraminiferal Proxy Records

NASA Astrophysics Data System (ADS)

Lowery, C.; Fraass, A. J.

2016-02-01

Paleoceanographic research is a vital tool to extend modern observational datasets and to study the impact of climate events for which there is no modern analog. Foraminifera are one of the most widely used tools for this type of work, both as paleoecological indicators and as carriers for geochemical proxies. However, the use of microfossils as proxies for paleoceanographic conditions brings about a unique set of problems. This is primarily due to the fact that groups of individual foraminifera, which usually live about a month, are used to infer average conditions for time periods ranging from hundreds to tens of thousands of years. Because of this, adequate sample size is very important for generating statistically robust datasets, particularly for stable isotopes. In the early days of stable isotope geochemistry, instrumental limitations required hundreds of individual foraminiferal tests to return a value. This had the fortunate side-effect of smoothing any seasonal to decadal changes within the planktic foram population. With the advent of more sensitive mass spectrometers, smaller sample sizes have now become standard. While this has many advantages, the use of smaller numbers of individuals to generate a data point has lessened the amount of time averaging in the isotopic analysis and decreased precision in paleoceanographic datasets. With fewer individuals per sample, the differences between individual specimens will result in larger variation, and therefore error, and less precise values for each sample. Unfortunately, most (the authors included) do not make a habit of reporting the error associated with their sample size. We have created an open-source model in R to quantify the effect of sample sizes under various realistic and highly modifiable parameters (calcification depth, diagenesis in a subset of the population, improper identification, vital effects, mass, etc.). For example, a sample in which only 1 in 10 specimens is diagenetically altered can be off by >0.3‰ δ18O VPDB, or 1°C. Here, we demonstrate the use of this tool to quantify error in micropaleontological datasets, and suggest best practices for minimizing error when generating stable isotope data with foraminifera.

Flow tilt angles near forest edges - Part 2: Lidar anemometry

NASA Astrophysics Data System (ADS)

Dellwik, E.; Mann, J.; Bingöl, F.

2010-05-01

A novel way of estimating near-surface mean flow tilt angles from ground based Doppler lidar measurements is presented. The results are compared with traditional mast based in-situ sonic anemometry. The tilt angle assessed with the lidar is based on 10 or 30 min mean values of the velocity field from a conically scanning lidar. In this mode of measurement, the lidar beam is rotated in a circle by a prism with a fixed angle to the vertical at varying focus distances. By fitting a trigonometric function to the scans, the mean vertical velocity can be estimated. Lidar measurements from (1) a fetch-limited beech forest site taken at 48-175 m a.g.l. (above ground level), (2) a reference site in flat agricultural terrain and (3) a second reference site in complex terrain are presented. The method to derive flow tilt angles and mean vertical velocities from lidar has several advantages compared to sonic anemometry; there is no flow distortion caused by the instrument itself, there are no temperature effects and the instrument misalignment can be corrected for by assuming zero tilt angle at high altitudes. Contrary to mast-based instruments, the lidar measures the wind field with the exact same alignment error at a multitude of heights. Disadvantages with estimating vertical velocities from a lidar compared to mast-based measurements are potentially slightly increased levels of statistical errors due to limited sampling time, because the sampling is disjunct, and a requirement for homogeneous flow. The estimated mean vertical velocity is biased if the flow over the scanned circle is not homogeneous. It is demonstrated that the error on the mean vertical velocity due to flow inhomogeneity can be approximated by a function of the angle of the lidar beam to the vertical and the vertical gradient of the mean vertical velocity, whereas the error due to flow inhomogeneity on the horizontal mean wind speed is independent of the lidar beam angle. For the presented measurements over forest, it is evaluated that the systematic error due to the inhomogeneity of the flow is less than 0.2°. The results of the vertical conical scans were promising, and yielded positive flow angles for a sector where the forest is fetch-limited. However, more data and analysis are needed for a complete evaluation of the lidar technique.

Impacts of sampling design and estimation methods on nutrient leaching of intensively monitored forest plots in the Netherlands.

PubMed

de Vries, W; Wieggers, H J J; Brus, D J

2010-08-05

Element fluxes through forest ecosystems are generally based on measurements of concentrations in soil solution at regular time intervals at plot locations sampled in a regular grid. Here we present spatially averaged annual element leaching fluxes in three Dutch forest monitoring plots using a new sampling strategy in which both sampling locations and sampling times are selected by probability sampling. Locations were selected by stratified random sampling with compact geographical blocks of equal surface area as strata. In each sampling round, six composite soil solution samples were collected, consisting of five aliquots, one per stratum. The plot-mean concentration was estimated by linear regression, so that the bias due to one or more strata being not represented in the composite samples is eliminated. The sampling times were selected in such a way that the cumulative precipitation surplus of the time interval between two consecutive sampling times was constant, using an estimated precipitation surplus averaged over the past 30 years. The spatially averaged annual leaching flux was estimated by using the modeled daily water flux as an ancillary variable. An important advantage of the new method is that the uncertainty in the estimated annual leaching fluxes due to spatial and temporal variation and resulting sampling errors can be quantified. Results of this new method were compared with the reference approach in which daily leaching fluxes were calculated by multiplying daily interpolated element concentrations with daily water fluxes and then aggregated to a year. Results show that the annual fluxes calculated with the reference method for the period 2003-2005, including all plots, elements and depths, lies only in 53% of the cases within the range of the average +/-2 times the standard error of the new method. Despite the differences in results, both methods indicate comparable N retention and strong Al mobilization in all plots, with Al leaching being nearly equal to the leaching of SO(4) and NO(3) with fluxes expressed in mol(c) ha(-1) yr(-1). This illustrates that Al release, which is the clearest signal of soil acidification, is mainly due to the external input of SO(4) and NO(3).

GNSS software receiver sampling noise and clock jitter performance and impact analysis

NASA Astrophysics Data System (ADS)

Chen, Jian Yun; Feng, XuZhe; Li, XianBin; Wu, GuangYao

2015-02-01

In the design of a multi-frequency multi-constellation GNSS software defined radio receivers is becoming more and more popular due to its simple architecture, flexible configuration and good coherence in multi-frequency signal processing. It plays an important role in navigation signal processing and signal quality monitoring. In particular, GNSS software defined radio receivers driving the sampling clock of analogue-to-digital converter (ADC) by FPGA implies that a more flexible radio transceiver design is possible. According to the concept of software defined radio (SDR), the ideal is to digitize as close to the antenna as possible. Whereas the carrier frequency of GNSS signal is of the frequency of GHz, converting at this frequency is expensive and consumes more power. Band sampling method is a cheaper, more effective alternative. When using band sampling method, it is possible to sample a RF signal at twice the bandwidth of the signal. Unfortunately, as the other side of the coin, the introduction of SDR concept and band sampling method induce negative influence on the performance of the GNSS receivers. ADC's suffer larger sampling clock jitter generated by FPGA; and low sampling frequency introduces more noise to the receiver. Then the influence of sampling noise cannot be neglected. The paper analyzes the sampling noise, presents its influence on the carrier noise ratio, and derives the ranging error by calculating the synchronization error of the delay locked loop. Simulations aiming at each impact factors of sampling-noise-induced ranging error are performed. Simulation and experiment results show that if the target ranging accuracy is at the level of centimeter, the quantization length should be no less than 8 and the sampling clock jitter should not exceed 30ps.

Solutions to decrease a systematic error related to AAPH addition in the fluorescence-based ORAC assay.

PubMed

Mellado-Ortega, Elena; Zabalgogeazcoa, Iñigo; Vázquez de Aldana, Beatriz R; Arellano, Juan B

2017-02-15

Oxygen radical absorbance capacity (ORAC) assay in 96-well multi-detection plate readers is a rapid method to determine total antioxidant capacity (TAC) in biological samples. A disadvantage of this method is that the antioxidant inhibition reaction does not start in all of the 96 wells at the same time due to technical limitations when dispensing the free radical-generating azo initiator 2,2'-azobis (2-methyl-propanimidamide) dihydrochloride (AAPH). The time delay between wells yields a systematic error that causes statistically significant differences in TAC determination of antioxidant solutions depending on their plate position. We propose two alternative solutions to avoid this AAPH-dependent error in ORAC assays. Copyright © 2016 Elsevier Inc. All rights reserved.

Out-of-plane ultrasonic velocity measurement

DOEpatents

Hall, M.S.; Brodeur, P.H.; Jackson, T.G.

1998-07-14

A method for improving the accuracy of measuring the velocity and time of flight of ultrasonic signals through moving web-like materials such as paper, paperboard and the like, includes a pair of ultrasonic transducers disposed on opposing sides of a moving web-like material. In order to provide acoustical coupling between the transducers and the web-like material, the transducers are disposed in fluid-filled wheels. Errors due to variances in the wheel thicknesses about their circumference which can affect time of flight measurements and ultimately the mechanical property being tested are compensated by averaging the ultrasonic signals for a predetermined number of revolutions. The invention further includes a method for compensating for errors resulting from the digitization of the ultrasonic signals. More particularly, the invention includes a method for eliminating errors known as trigger jitter inherent with digitizing oscilloscopes used to digitize the signals for manipulation by a digital computer. In particular, rather than cross-correlate ultrasonic signals taken during different sample periods as is known in the art in order to determine the time of flight of the ultrasonic signal through the moving web, a pulse echo box is provided to enable cross-correlation of predetermined transmitted ultrasonic signals with predetermined reflected ultrasonic or echo signals during the sample period. By cross-correlating ultrasonic signals in the same sample period, the error associated with trigger jitter is eliminated. 20 figs.

Out-of-plane ultrasonic velocity measurement

DOEpatents

Hall, Maclin S.; Brodeur, Pierre H.; Jackson, Theodore G.

1998-01-01

A method for improving the accuracy of measuring the velocity and time of flight of ultrasonic signals through moving web-like materials such as paper, paperboard and the like, includes a pair of ultrasonic transducers disposed on opposing sides of a moving web-like material. In order to provide acoustical coupling between the transducers and the web-like material, the transducers are disposed in fluid-filled wheels. Errors due to variances in the wheel thicknesses about their circumference which can affect time of flight measurements and ultimately the mechanical property being tested are compensated by averaging the ultrasonic signals for a predetermined number of revolutions. The invention further includes a method for compensating for errors resulting from the digitization of the ultrasonic signals. More particularly, the invention includes a method for eliminating errors known as trigger jitter inherent with digitizing oscilloscopes used to digitize the signals for manipulation by a digital computer. In particular, rather than cross-correlate ultrasonic signals taken during different sample periods as is known in the art in order to determine the time of flight of the ultrasonic signal through the moving web, a pulse echo box is provided to enable cross-correlation of predetermined transmitted ultrasonic signals with predetermined reflected ultrasonic or echo signals during the sample period. By cross-correlating ultrasonic signals in the same sample period, the error associated with trigger jitter is eliminated.

Time-gated scintillator imaging for real-time optical surface dosimetry in total skin electron therapy.

PubMed

Bruza, Petr; Gollub, Sarah L; Andreozzi, Jacqueline M; Tendler, Irwin I; Williams, Benjamin B; Jarvis, Lesley A; Gladstone, David J; Pogue, Brian W

2018-05-02

The purpose of this study was to measure surface dose by remote time-gated imaging of plastic scintillators. A novel technique for time-gated, intensified camera imaging of scintillator emission was demonstrated, and key parameters influencing the signal were analyzed, including distance, angle and thickness. A set of scintillator samples was calibrated by using thermo-luminescence detector response as reference. Examples of use in total skin electron therapy are described. The data showed excellent room light rejection (signal-to-noise ratio of scintillation SNR  ≈  470), ideal scintillation dose response linearity, and 2% dose rate error. Individual sample scintillation response varied by 7% due to sample preparation. Inverse square distance dependence correction and lens throughput error (8% per meter) correction were needed. At scintillator-to-source angle and observation angle  <50°, the radiant energy fluence error was smaller than 1%. The achieved standard error of the scintillator cumulative dose measurement compared to the TLD dose was 5%. The results from this proof-of-concept study documented the first use of small scintillator targets for remote surface dosimetry in ambient room lighting. The measured dose accuracy renders our method to be comparable to thermo-luminescent detector dosimetry, with the ultimate realization of accuracy likely to be better than shown here. Once optimized, this approach to remote dosimetry may substantially reduce the time and effort required for surface dosimetry.

Time-gated scintillator imaging for real-time optical surface dosimetry in total skin electron therapy

NASA Astrophysics Data System (ADS)

Bruza, Petr; Gollub, Sarah L.; Andreozzi, Jacqueline M.; Tendler, Irwin I.; Williams, Benjamin B.; Jarvis, Lesley A.; Gladstone, David J.; Pogue, Brian W.

2018-05-01

The purpose of this study was to measure surface dose by remote time-gated imaging of plastic scintillators. A novel technique for time-gated, intensified camera imaging of scintillator emission was demonstrated, and key parameters influencing the signal were analyzed, including distance, angle and thickness. A set of scintillator samples was calibrated by using thermo-luminescence detector response as reference. Examples of use in total skin electron therapy are described. The data showed excellent room light rejection (signal-to-noise ratio of scintillation SNR  ≈  470), ideal scintillation dose response linearity, and 2% dose rate error. Individual sample scintillation response varied by 7% due to sample preparation. Inverse square distance dependence correction and lens throughput error (8% per meter) correction were needed. At scintillator-to-source angle and observation angle  <50°, the radiant energy fluence error was smaller than 1%. The achieved standard error of the scintillator cumulative dose measurement compared to the TLD dose was 5%. The results from this proof-of-concept study documented the first use of small scintillator targets for remote surface dosimetry in ambient room lighting. The measured dose accuracy renders our method to be comparable to thermo-luminescent detector dosimetry, with the ultimate realization of accuracy likely to be better than shown here. Once optimized, this approach to remote dosimetry may substantially reduce the time and effort required for surface dosimetry.

Measurement-based analysis of error latency. [in computer operating system

NASA Technical Reports Server (NTRS)

Chillarege, Ram; Iyer, Ravishankar K.

1987-01-01

This paper demonstrates a practical methodology for the study of error latency under a real workload. The method is illustrated with sampled data on the physical memory activity, gathered by hardware instrumentation on a VAX 11/780 during the normal workload cycle of the installation. These data are used to simulate fault occurrence and to reconstruct the error discovery process in the system. The technique provides a means to study the system under different workloads and for multiple days. An approach to determine the percentage of undiscovered errors is also developed and a verification of the entire methodology is performed. This study finds that the mean error latency, in the memory containing the operating system, varies by a factor of 10 to 1 (in hours) between the low and high workloads. It is found that of all errors occurring within a day, 70 percent are detected in the same day, 82 percent within the following day, and 91 percent within the third day. The increase in failure rate due to latency is not so much a function of remaining errors but is dependent on whether or not there is a latent error.

Incorporating measurement error in n = 1 psychological autoregressive modeling

PubMed Central

Schuurman, Noémi K.; Houtveen, Jan H.; Hamaker, Ellen L.

2015-01-01

Measurement error is omnipresent in psychological data. However, the vast majority of applications of autoregressive time series analyses in psychology do not take measurement error into account. Disregarding measurement error when it is present in the data results in a bias of the autoregressive parameters. We discuss two models that take measurement error into account: An autoregressive model with a white noise term (AR+WN), and an autoregressive moving average (ARMA) model. In a simulation study we compare the parameter recovery performance of these models, and compare this performance for both a Bayesian and frequentist approach. We find that overall, the AR+WN model performs better. Furthermore, we find that for realistic (i.e., small) sample sizes, psychological research would benefit from a Bayesian approach in fitting these models. Finally, we illustrate the effect of disregarding measurement error in an AR(1) model by means of an empirical application on mood data in women. We find that, depending on the person, approximately 30–50% of the total variance was due to measurement error, and that disregarding this measurement error results in a substantial underestimation of the autoregressive parameters. PMID:26283988

A Stepwise Test Characteristic Curve Method to Detect Item Parameter Drift

ERIC Educational Resources Information Center

Guo, Rui; Zheng, Yi; Chang, Hua-Hua

2015-01-01

An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the…

A Strategy to Use Soft Data Effectively in Randomized Controlled Clinical Trials.

ERIC Educational Resources Information Center

Kraemer, Helena Chmura; Thiemann, Sue

1989-01-01

Sees soft data, measures having substantial intrasubject variability due to errors of measurement or response inconsistency, as important measures of response in randomized clinical trials. Shows that using intensive design and slope of response on time as outcome measure maximizes sample retention and decreases within-group variability, thus…

A Simple Approach to Fourier Aliasing

ERIC Educational Resources Information Center

Foadi, James

2007-01-01

In the context of discrete Fourier transforms the idea of aliasing as due to approximation errors in the integral defining Fourier coefficients is introduced and explained. This has the positive pedagogical effect of getting to the heart of sampling and the discrete Fourier transform without having to delve into effective, but otherwise long and…

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.

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.

Analysis on the optical aberration effect on spectral resolution of coded aperture spectroscopy

NASA Astrophysics Data System (ADS)

Hao, Peng; Chi, Mingbo; Wu, Yihui

2017-10-01

The coded aperture spectrometer can achieve high throughput and high spectral resolution by replacing the traditional single slit with two-dimensional array slits manufactured by MEMS technology. However, the sampling accuracy of coding spectrum image will be distorted due to the existence of system aberrations, machining error, fixing errors and so on, resulting in the declined spectral resolution. The influence factor of the spectral resolution come from the decode error, the spectral resolution of each column, and the column spectrum offset correction. For the Czerny-Turner spectrometer, the spectral resolution of each column most depend on the astigmatism, in this coded aperture spectroscopy, the uncorrected astigmatism does result in degraded performance. Some methods must be used to reduce or remove the limiting astigmatism. The curvature of field and the spectral curvature can be result in the spectrum revision errors.

Errors of five-day mean surface wind and temperature conditions due to inadequate sampling

NASA Technical Reports Server (NTRS)

Legler, David M.

1991-01-01

Surface meteorological reports of wind components, wind speed, air temperature, and sea-surface temperature from buoys located in equatorial and midlatitude regions are used in a simulation of random sampling to determine errors of the calculated means due to inadequate sampling. Subsampling the data with several different sample sizes leads to estimates of the accuracy of the subsampled means. The number N of random observations needed to compute mean winds with chosen accuracies of 0.5 (N sub 0.5) and 1.0 (N sub 1,0) m/s and mean air and sea surface temperatures with chosen accuracies of 0.1 (N sub 0.1) and 0.2 (N sub 0.2) C were calculated for each 5-day and 30-day period in the buoy datasets. Mean values of N for the various accuracies and datasets are given. A second-order polynomial relation is established between N and the variability of the data record. This relationship demonstrates that for the same accuracy, N increases as the variability of the data record increases. The relationship is also independent of the data source. Volunteer-observing ship data do not satisfy the recommended minimum number of observations for obtaining 0.5 m/s and 0.2 C accuracy for most locations. The effect of having remotely sensed data is discussed.

A pharmacometric case study regarding the sensitivity of structural model parameter estimation to error in patient reported dosing times.

PubMed

Knights, Jonathan; Rohatagi, Shashank

2015-12-01

Although there is a body of literature focused on minimizing the effect of dosing inaccuracies on pharmacokinetic (PK) parameter estimation, most of the work centers on missing doses. No attempt has been made to specifically characterize the effect of error in reported dosing times. Additionally, existing work has largely dealt with cases in which the compound of interest is dosed at an interval no less than its terminal half-life. This work provides a case study investigating how error in patient reported dosing times might affect the accuracy of structural model parameter estimation under sparse sampling conditions when the dosing interval is less than the terminal half-life of the compound, and the underlying kinetics are monoexponential. Additional effects due to noncompliance with dosing events are not explored and it is assumed that the structural model and reasonable initial estimates of the model parameters are known. Under the conditions of our simulations, with structural model CV % ranging from ~20 to 60 %, parameter estimation inaccuracy derived from error in reported dosing times was largely controlled around 10 % on average. Given that no observed dosing was included in the design and sparse sampling was utilized, we believe these error results represent a practical ceiling given the variability and parameter estimates for the one-compartment model. The findings suggest additional investigations may be of interest and are noteworthy given the inability of current PK software platforms to accommodate error in dosing times.

Modelling vertical error in LiDAR-derived digital elevation models

NASA Astrophysics Data System (ADS)

Aguilar, Fernando J.; Mills, Jon P.; Delgado, Jorge; Aguilar, Manuel A.; Negreiros, J. G.; Pérez, José L.

2010-01-01

A hybrid theoretical-empirical model has been developed for modelling the error in LiDAR-derived digital elevation models (DEMs) of non-open terrain. The theoretical component seeks to model the propagation of the sample data error (SDE), i.e. the error from light detection and ranging (LiDAR) data capture of ground sampled points in open terrain, towards interpolated points. The interpolation methods used for infilling gaps may produce a non-negligible error that is referred to as gridding error. In this case, interpolation is performed using an inverse distance weighting (IDW) method with the local support of the five closest neighbours, although it would be possible to utilize other interpolation methods. The empirical component refers to what is known as "information loss". This is the error purely due to modelling the continuous terrain surface from only a discrete number of points plus the error arising from the interpolation process. The SDE must be previously calculated from a suitable number of check points located in open terrain and assumes that the LiDAR point density was sufficiently high to neglect the gridding error. For model calibration, data for 29 study sites, 200×200 m in size, belonging to different areas around Almeria province, south-east Spain, were acquired by means of stereo photogrammetric methods. The developed methodology was validated against two different LiDAR datasets. The first dataset used was an Ordnance Survey (OS) LiDAR survey carried out over a region of Bristol in the UK. The second dataset was an area located at Gador mountain range, south of Almería province, Spain. Both terrain slope and sampling density were incorporated in the empirical component through the calibration phase, resulting in a very good agreement between predicted and observed data (R2 = 0.9856 ; p < 0.001). In validation, Bristol observed vertical errors, corresponding to different LiDAR point densities, offered a reasonably good fit to the predicted errors. Even better results were achieved in the more rugged morphology of the Gador mountain range dataset. The findings presented in this article could be used as a guide for the selection of appropriate operational parameters (essentially point density in order to optimize survey cost), in projects related to LiDAR survey in non-open terrain, for instance those projects dealing with forestry applications.

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.

Linear models for airborne-laser-scanning-based operational forest inventory with small field sample size and highly correlated LiDAR data

USGS Publications Warehouse

Junttila, Virpi; Kauranne, Tuomo; Finley, Andrew O.; Bradford, John B.

2015-01-01

Modern operational forest inventory often uses remotely sensed data that cover the whole inventory area to produce spatially explicit estimates of forest properties through statistical models. The data obtained by airborne light detection and ranging (LiDAR) correlate well with many forest inventory variables, such as the tree height, the timber volume, and the biomass. To construct an accurate model over thousands of hectares, LiDAR data must be supplemented with several hundred field sample measurements of forest inventory variables. This can be costly and time consuming. Different LiDAR-data-based and spatial-data-based sampling designs can reduce the number of field sample plots needed. However, problems arising from the features of the LiDAR data, such as a large number of predictors compared with the sample size (overfitting) or a strong correlation among predictors (multicollinearity), may decrease the accuracy and precision of the estimates and predictions. To overcome these problems, a Bayesian linear model with the singular value decomposition of predictors, combined with regularization, is proposed. The model performance in predicting different forest inventory variables is verified in ten inventory areas from two continents, where the number of field sample plots is reduced using different sampling designs. The results show that, with an appropriate field plot selection strategy and the proposed linear model, the total relative error of the predicted forest inventory variables is only 5%–15% larger using 50 field sample plots than the error of a linear model estimated with several hundred field sample plots when we sum up the error due to both the model noise variance and the model’s lack of fit.

Relationship auditing of the FMA ontology

PubMed Central

Gu, Huanying (Helen); Wei, Duo; Mejino, Jose L.V.; Elhanan, Gai

2010-01-01

The Foundational Model of Anatomy (FMA) ontology is a domain reference ontology based on a disciplined modeling approach. Due to its large size, semantic complexity and manual data entry process, errors and inconsistencies are unavoidable and might remain within the FMA structure without detection. In this paper, we present computable methods to highlight candidate concepts for various relationship assignment errors. The process starts with locating structures formed by transitive structural relationships (part_of, tributary_of, branch_of) and examine their assignments in the context of the IS-A hierarchy. The algorithms were designed to detect five major categories of possible incorrect relationship assignments: circular, mutually exclusive, redundant, inconsistent, and missed entries. A domain expert reviewed samples of these presumptive errors to confirm the findings. Seven thousand and fifty-two presumptive errors were detected, the largest proportion related to part_of relationship assignments. The results highlight the fact that errors are unavoidable in complex ontologies and that well designed algorithms can help domain experts to focus on concepts with high likelihood of errors and maximize their effort to ensure consistency and reliability. In the future similar methods might be integrated with data entry processes to offer real-time error detection. PMID:19475727

Linguistic Precautions That to Be Considered When Translating the Holy Quran

ERIC Educational Resources Information Center

Siddiek, Ahmed Gumaa

2017-01-01

The present study is an attempt to raise some points that should be considered when translating the Quranic Text into English. We have looked into some samples of translations, selected from well known English translations of the Holy Quran and critically examined them. There were some errors in those translations, due to linguistic factors, owing…

Estimation of true incidence of polio: overcoming misclassification errors due to stool culture insensitivity.

PubMed

Srinivas, V; Puliyel, Jacob M

2007-08-01

The diagnosis of polio dependents on culturing the virus in stool samples of children with AFP. Using data obtained under the "Right to Information Act" of instances where only one of the two samples was positive for polio, it was possible to estimate the sensitivity of the system to detect cases of polio. The calculations suggest that there were 1625 (95% CI 1528 to 1725) cases of polio in India in 2006 rather than the 674 reported widely!

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.

Effects of Heavy Ion Exposure on Nanocrystal Nonvolatile Memory

NASA Technical Reports Server (NTRS)

Oldham, Timothy R.; Suhail, Mohammed; Kuhn, Peter; Prinz, Erwin; Kim, Hak; LaBel, Kenneth A.

2004-01-01

We have irradiated engineering samples of Freescale 4M nonvolatile memories with heavy ions. They use Silicon nanocrystals as the storage element, rather than the more common floating gate. The irradiations were performed using the Texas A&M University cyclotron Single Event Effects Test Facility. The chips were tested in the static mode, and in the dynamic read mode, dynamic write (program) mode, and dynamic erase mode. All the errors observed appeared to be due to single, isolated bits, even in the program and erase modes. These errors appeared to be related to the micro-dose mechanism. All the errors corresponded to the loss of electrons from a programmed cell. The underlying physical mechanisms will be discussed in more detail later. There were no errors, which could be attributed to malfunctions of the control circuits. At the highest LET used in the test (85 MeV/mg/sq cm), however, there appeared to be a failure due to gate rupture. Failure analysis is being conducted to confirm this conclusion. There was no unambiguous evidence of latchup under any test conditions. Generally, the results on the nanocrystal technology compare favorably with results on currently available commercial floating gate technology, indicating that the technology is promising for future space applications, both civilian and military.

The Power of the Spectrum: Combining Numerical Proxy System Models with Analytical Error Spectra to Better Understand Timescale Dependent Proxy Uncertainty

NASA Astrophysics Data System (ADS)

Dolman, A. M.; Laepple, T.; Kunz, T.

2017-12-01

Understanding the uncertainties associated with proxy-based reconstructions of past climate is critical if they are to be used to validate climate models and contribute to a comprehensive understanding of the climate system. Here we present two related and complementary approaches to quantifying proxy uncertainty. The proxy forward model (PFM) "sedproxy" bitbucket.org/ecus/sedproxy numerically simulates the creation, archiving and observation of marine sediment archived proxies such as Mg/Ca in foraminiferal shells and the alkenone unsaturation index UK'37. It includes the effects of bioturbation, bias due to seasonality in the rate of proxy creation, aliasing of the seasonal temperature cycle into lower frequencies, and error due to cleaning, processing and measurement of samples. Numerical PFMs have the advantage of being very flexible, allowing many processes to be modelled and assessed for their importance. However, as more and more proxy-climate data become available, their use in advanced data products necessitates rapid estimates of uncertainties for both the raw reconstructions, and their smoothed/derived products, where individual measurements have been aggregated to coarser time scales or time-slices. To address this, we derive closed-form expressions for power spectral density of the various error sources. The power spectra describe both the magnitude and autocorrelation structure of the error, allowing timescale dependent proxy uncertainty to be estimated from a small number of parameters describing the nature of the proxy, and some simple assumptions about the variance of the true climate signal. We demonstrate and compare both approaches for time-series of the last millennia, Holocene, and the deglaciation. While the numerical forward model can create pseudoproxy records driven by climate model simulations, the analytical model of proxy error allows for a comprehensive exploration of parameter space and mapping of climate signal re-constructability, conditional on the climate and sampling conditions.

Multi-kW coherent combining of fiber lasers seeded with pseudo random phase modulated light

NASA Astrophysics Data System (ADS)

Flores, Angel; Ehrehreich, Thomas; Holten, Roger; Anderson, Brian; Dajani, Iyad

2016-03-01

We report efficient coherent beam combining of five kilowatt-class fiber amplifiers with a diffractive optical element (DOE). Based on a master oscillator power amplifier (MOPA) configuration, the amplifiers were seeded with pseudo random phase modulated light. Each non-polarization maintaining fiber amplifier was optically path length matched and provides approximately 1.2 kW of near diffraction-limited output power (measured M2<1.1). Consequently, a low power sample of each laser was utilized for active linear polarization control. A low power sample of the combined beam after the DOE provided an error signal for active phase locking which was performed via Locking of Optical Coherence by Single-Detector Electronic-Frequency Tagging (LOCSET). After phase stabilization, the beams were coherently combined via the 1x5 DOE. A total combined output power of 4.9 kW was achieved with 82% combining efficiency and excellent beam quality (M2<1.1). The intrinsic DOE splitter loss was 5%. Similarly, losses due in part to non-ideal polarization, ASE content, uncorrelated wavefront errors, and misalignment errors contributed to the efficiency reduction.

Evaluating the Effective Factors for Reporting Medical Errors among Midwives Working at Teaching Hospitals Affiliated to Isfahan University of Medical Sciences.

PubMed

Khorasani, Fahimeh; Beigi, Marjan

2017-01-01

Recently, evaluation and accreditation system of hospitals has had a special emphasis on reporting malpractices and sharing errors or lessons learnt from errors, but still due to lack of promotion of systematic approach for solving problems from the same system, this issue has remained unattended. This study was conducted to determine the effective factors for reporting medical errors among midwives. This project was a descriptive cross-sectional observational study. Data gathering tools were a standard checklist and two researcher-made questionnaires. Sampling for this study was conducted from all the midwives who worked at teaching hospitals affiliated to Isfahan University of Medical Sciences through census method (convenient) and lasted for 3 months. Data were analyzed using descriptive and inferential statistics through SPSS 16. Results showed that 79.1% of the staff reported errors and the highest rate of errors was in the process of patients' tests. In this study, the mean score of midwives' knowledge about the errors was 79.1 and the mean score of their attitude toward reporting errors was 70.4. There was a direct relation between the score of errors' knowledge and attitude in the midwifery staff and reporting errors. Based on the results of this study about the appropriate knowledge and attitude of midwifery staff regarding errors and action toward reporting them, it is recommended to strengthen the system when it comes to errors and hospitals risks.

Evidence of Selection against Complex Mitotic-Origin Aneuploidy during Preimplantation Development

PubMed Central

McCoy, Rajiv C.; Demko, Zachary P.; Ryan, Allison; Banjevic, Milena; Hill, Matthew; Sigurjonsson, Styrmir; Rabinowitz, Matthew; Petrov, Dmitri A.

2015-01-01

Whole-chromosome imbalances affect over half of early human embryos and are the leading cause of pregnancy loss. While these errors frequently arise in oocyte meiosis, many such whole-chromosome abnormalities affecting cleavage-stage embryos are the result of chromosome missegregation occurring during the initial mitotic cell divisions. The first wave of zygotic genome activation at the 4–8 cell stage results in the arrest of a large proportion of embryos, the vast majority of which contain whole-chromosome abnormalities. Thus, the full spectrum of meiotic and mitotic errors can only be detected by sampling after the initial cell divisions, but prior to this selective filter. Here, we apply 24-chromosome preimplantation genetic screening (PGS) to 28,052 single-cell day-3 blastomere biopsies and 18,387 multi-cell day-5 trophectoderm biopsies from 6,366 in vitro fertilization (IVF) cycles. We precisely characterize the rates and patterns of whole-chromosome abnormalities at each developmental stage and distinguish errors of meiotic and mitotic origin without embryo disaggregation, based on informative chromosomal signatures. We show that mitotic errors frequently involve multiple chromosome losses that are not biased toward maternal or paternal homologs. This outcome is characteristic of spindle abnormalities and chaotic cell division detected in previous studies. In contrast to meiotic errors, our data also show that mitotic errors are not significantly associated with maternal age. PGS patients referred due to previous IVF failure had elevated rates of mitotic error, while patients referred due to recurrent pregnancy loss had elevated rates of meiotic error, controlling for maternal age. These results support the conclusion that mitotic error is the predominant mechanism contributing to pregnancy losses occurring prior to blastocyst formation. This high-resolution view of the full spectrum of whole-chromosome abnormalities affecting early embryos provides insight into the cytogenetic mechanisms underlying their formation and the consequences for human fertility. PMID:26491874

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

White blood cell counting system

NASA Technical Reports Server (NTRS)

1972-01-01

The design, fabrication, and tests of a prototype white blood cell counting system for use in the Skylab IMSS are presented. The counting system consists of a sample collection subsystem, sample dilution and fluid containment subsystem, and a cell counter. Preliminary test results show the sample collection and the dilution subsystems are functional and fulfill design goals. Results for the fluid containment subsystem show the handling bags cause counting errors due to: (1) adsorption of cells to the walls of the container, and (2) inadequate cleaning of the plastic bag material before fabrication. It was recommended that another bag material be selected.

The accuracy of estimates of the overturning circulation from basin-wide mooring arrays

NASA Astrophysics Data System (ADS)

Sinha, B.; Smeed, D. A.; McCarthy, G.; Moat, B. I.; Josey, S. A.; Hirschi, J. J.-M.; Frajka-Williams, E.; Blaker, A. T.; Rayner, D.; Madec, G.

2018-01-01

Previous modeling and observational studies have established that it is possible to accurately monitor the Atlantic Meridional Overturning Circulation (AMOC) at 26.5°N using a coast-to-coast array of instrumented moorings supplemented by direct transport measurements in key boundary regions (the RAPID/MOCHA/WBTS Array). The main sources of observational and structural errors have been identified in a variety of individual studies. Here a unified framework for identifying and quantifying structural errors associated with the RAPID array-based AMOC estimates is established using a high-resolution (eddy resolving at low-mid latitudes, eddy permitting elsewhere) ocean general circulation model, which simulates the ocean state between 1978 and 2010. We define a virtual RAPID array in the model in close analogy to the real RAPID array and compare the AMOC estimate from the virtual array with the true model AMOC. The model analysis suggests that the RAPID method underestimates the mean AMOC by ∼1.5 Sv (1 Sv = 106 m3 s-1) at ∼900 m depth, however it captures the variability to high accuracy. We examine three major contributions to the streamfunction bias: (i) due to the assumption of a single fixed reference level for calculation of geostrophic transports, (ii) due to regions not sampled by the array and (iii) due to ageostrophic transport. A key element in (i) and (iii) is use of the model sea surface height to establish the true (or absolute) geostrophic transport. In the upper 2000 m, we find that the reference level bias is strongest and most variable in time, whereas the bias due to unsampled regions is largest below 3000 m. The ageostrophic transport is significant in the upper 1000 m but shows very little variability. The results establish, for the first time, the uncertainty of the AMOC estimate due to the combined structural errors in the measurement design and suggest ways in which the error could be reduced. Our work has applications to basin-wide circulation measurement arrays at other latitudes and in other basins as well as quantifying systematic errors in ocean model estimates of the AMOC at 26.5°N.

Bivariate least squares linear regression: Towards a unified analytic formalism. I. Functional models

NASA Astrophysics Data System (ADS)

Caimmi, R.

2011-08-01

Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both heteroscedastic and homoscedastic data. Conversely, samples related to different methods produce discrepant results, due to the presence of (still undetected) systematic errors, which implies no definitive statement can be made at present. A comparison is also made between different expressions of regression line slope and intercept variance estimators, where fractional discrepancies are found to be not exceeding a few percent, which grows up to about 20% in the presence of large dispersion data. An extension of the formalism to structural models is left to a forthcoming paper.

GNSS Clock Error Impacts on Radio Occultation Retrievals

NASA Astrophysics Data System (ADS)

Weiss, Jan; Sokolovskiy, Sergey; Schreiner, Bill; Yoon, Yoke

2017-04-01

We assess the impacts of GPS and GLONASS clock errors on radio occultation retrieval of bending angle, refractivity, and temperature from low Earth orbit. The major contributing factor is the interpretation of GNSS clock offsets sampled at 30 sec or longer intervals. Using 1 Hz GNSS clock estimates as truth we apply several interpolation and fitting schemes to evaluate how they affect the accuracy of atmospheric retrieval products. The results are organized by GPS and GLONASS space vehicle and the GNSS clock interpolation/fitting scheme. We find that bending angle error is roughly similar for all current GPS transmitters (about 0.7 mcrad) but note some differences related to the type of atomic oscillator onboard the transmitter satellite. GLONASS bending angle errors show more variation over the constellation and are approximately two times larger than GPS. An investigation of the transmitter clock spectra reveals this is due to more power in periods between 2-10 sec. Retrieved refractivity and temperature products show clear differences between GNSS satellite generations, and indicate that GNSS clocks sampled at intervals smaller than 5 sec significantly improve accuracy, particularly for GLONASS. We conclude by summarizing the tested GNSS clock estimation and application strategies in the context of current and future radio occultation missions.

Dealing with AFLP genotyping errors to reveal genetic structure in Plukenetia volubilis (Euphorbiaceae) in the Peruvian Amazon

PubMed Central

Vašek, Jakub; Viehmannová, Iva; Ocelák, Martin; Cachique Huansi, Danter; Vejl, Pavel

2017-01-01

An analysis of the population structure and genetic diversity for any organism often depends on one or more molecular marker techniques. Nonetheless, these techniques are not absolutely reliable because of various sources of errors arising during the genotyping process. Thus, a complex analysis of genotyping error was carried out with the AFLP method in 169 samples of the oil seed plant Plukenetia volubilis L. from small isolated subpopulations in the Peruvian Amazon. Samples were collected in nine localities from the region of San Martin. Analysis was done in eight datasets with a genotyping error from 0 to 5%. Using eleven primer combinations, 102 to 275 markers were obtained according to the dataset. It was found that it is only possible to obtain the most reliable and robust results through a multiple-level filtering process. Genotyping error and software set up influence both the estimation of population structure and genetic diversity, where in our case population number (K) varied between 2–9 depending on the dataset and statistical method used. Surprisingly, discrepancies in K number were caused more by statistical approaches than by genotyping errors themselves. However, for estimation of genetic diversity, the degree of genotyping error was critical because descriptive parameters (He, FST, PLP 5%) varied substantially (by at least 25%). Due to low gene flow, P. volubilis mostly consists of small isolated subpopulations (ΦPT = 0.252–0.323) with some degree of admixture given by socio-economic connectivity among the sites; a direct link between the genetic and geographic distances was not confirmed. The study illustrates the successful application of AFLP to infer genetic structure in non-model plants. PMID:28910307

Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics

DOE PAGES

Lundquist, J. K.; Churchfield, M. J.; Lee, S.; ...

2015-02-23

Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications such as wind energy and air quality. Lidar wind profilers exploit the Doppler shift of laser light backscattered from particulates carried by the wind to measure a line-of-sight (LOS) velocity. The Doppler beam swinging (DBS) technique, used by many commercial systems, considers measurements of this LOS velocity in multiple radial directions in order to estimate horizontal and vertical winds. The method relies on the assumption of homogeneous flow across the region sampled by the beams. Using such a system in inhomogeneous flow, such as wind turbine wakes ormore » complex terrain, will result in errors. To quantify the errors expected from such violation of the assumption of horizontal homogeneity, we simulate inhomogeneous flow in the atmospheric boundary layer, notably stably stratified flow past a wind turbine, with a mean wind speed of 6.5 m s -1 at the turbine hub-height of 80 m. This slightly stable case results in 15° of wind direction change across the turbine rotor disk. The resulting flow field is sampled in the same fashion that a lidar samples the atmosphere with the DBS approach, including the lidar range weighting function, enabling quantification of the error in the DBS observations. The observations from the instruments located upwind have small errors, which are ameliorated with time averaging. However, the downwind observations, particularly within the first two rotor diameters downwind from the wind turbine, suffer from errors due to the heterogeneity of the wind turbine wake. Errors in the stream-wise component of the flow approach 30% of the hub-height inflow wind speed close to the rotor disk. Errors in the cross-stream and vertical velocity components are also significant: cross-stream component errors are on the order of 15% of the hub-height inflow wind speed (1.0 m s −1) and errors in the vertical velocity measurement exceed the actual vertical velocity. By three rotor diameters downwind, DBS-based assessments of wake wind speed deficits based on the stream-wise velocity can be relied on even within the near wake within 1.0 s -1 (or 15% of the hub-height inflow wind speed), and the cross-stream velocity error is reduced to 8% while vertical velocity estimates are compromised. Furthermore, measurements of inhomogeneous flow such as wind turbine wakes are susceptible to these errors, and interpretations of field observations should account for this uncertainty.« less

Quantifying error of lidar and sodar Doppler beam swinging measurements of wind turbine wakes using computational fluid dynamics

NASA Astrophysics Data System (ADS)

Lundquist, J. K.; Churchfield, M. J.; Lee, S.; Clifton, A.

2015-02-01

Wind-profiling lidars are now regularly used in boundary-layer meteorology and in applications such as wind energy and air quality. Lidar wind profilers exploit the Doppler shift of laser light backscattered from particulates carried by the wind to measure a line-of-sight (LOS) velocity. The Doppler beam swinging (DBS) technique, used by many commercial systems, considers measurements of this LOS velocity in multiple radial directions in order to estimate horizontal and vertical winds. The method relies on the assumption of homogeneous flow across the region sampled by the beams. Using such a system in inhomogeneous flow, such as wind turbine wakes or complex terrain, will result in errors. To quantify the errors expected from such violation of the assumption of horizontal homogeneity, we simulate inhomogeneous flow in the atmospheric boundary layer, notably stably stratified flow past a wind turbine, with a mean wind speed of 6.5 m s-1 at the turbine hub-height of 80 m. This slightly stable case results in 15° of wind direction change across the turbine rotor disk. The resulting flow field is sampled in the same fashion that a lidar samples the atmosphere with the DBS approach, including the lidar range weighting function, enabling quantification of the error in the DBS observations. The observations from the instruments located upwind have small errors, which are ameliorated with time averaging. However, the downwind observations, particularly within the first two rotor diameters downwind from the wind turbine, suffer from errors due to the heterogeneity of the wind turbine wake. Errors in the stream-wise component of the flow approach 30% of the hub-height inflow wind speed close to the rotor disk. Errors in the cross-stream and vertical velocity components are also significant: cross-stream component errors are on the order of 15% of the hub-height inflow wind speed (1.0 m s-1) and errors in the vertical velocity measurement exceed the actual vertical velocity. By three rotor diameters downwind, DBS-based assessments of wake wind speed deficits based on the stream-wise velocity can be relied on even within the near wake within 1.0 m s-1 (or 15% of the hub-height inflow wind speed), and the cross-stream velocity error is reduced to 8% while vertical velocity estimates are compromised. Measurements of inhomogeneous flow such as wind turbine wakes are susceptible to these errors, and interpretations of field observations should account for this uncertainty.

Effect of uncertainties on probabilistic-based design capacity of hydrosystems

NASA Astrophysics Data System (ADS)

Tung, Yeou-Koung

2018-02-01

Hydrosystems engineering designs involve analysis of hydrometric data (e.g., rainfall, floods) and use of hydrologic/hydraulic models, all of which contribute various degrees of uncertainty to the design process. Uncertainties in hydrosystem designs can be generally categorized into aleatory and epistemic types. The former arises from the natural randomness of hydrologic processes whereas the latter are due to knowledge deficiency in model formulation and model parameter specification. This study shows that the presence of epistemic uncertainties induces uncertainty in determining the design capacity. Hence, the designer needs to quantify the uncertainty features of design capacity to determine the capacity with a stipulated performance reliability under the design condition. Using detention basin design as an example, the study illustrates a methodological framework by considering aleatory uncertainty from rainfall and epistemic uncertainties from the runoff coefficient, curve number, and sampling error in design rainfall magnitude. The effects of including different items of uncertainty and performance reliability on the design detention capacity are examined. A numerical example shows that the mean value of the design capacity of the detention basin increases with the design return period and this relation is found to be practically the same regardless of the uncertainty types considered. The standard deviation associated with the design capacity, when subject to epistemic uncertainty, increases with both design frequency and items of epistemic uncertainty involved. It is found that the epistemic uncertainty due to sampling error in rainfall quantiles should not be ignored. Even with a sample size of 80 (relatively large for a hydrologic application) the inclusion of sampling error in rainfall quantiles resulted in a standard deviation about 2.5 times higher than that considering only the uncertainty of the runoff coefficient and curve number. Furthermore, the presence of epistemic uncertainties in the design would result in under-estimation of the annual failure probability of the hydrosystem and has a discounting effect on the anticipated design return period.

Magnetic resonance imaging-targeted, 3D transrectal ultrasound-guided fusion biopsy for prostate cancer: Quantifying the impact of needle delivery error on diagnosis

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

Martin, Peter R., E-mail: pmarti46@uwo.ca; Cool, Derek W.; Romagnoli, Cesare

2014-07-15

Purpose: Magnetic resonance imaging (MRI)-targeted, 3D transrectal ultrasound (TRUS)-guided “fusion” prostate biopsy intends to reduce the ∼23% false negative rate of clinical two-dimensional TRUS-guided sextant biopsy. Although it has been reported to double the positive yield, MRI-targeted biopsies continue to yield false negatives. Therefore, the authors propose to investigate how biopsy system needle delivery error affects the probability of sampling each tumor, by accounting for uncertainties due to guidance system error, image registration error, and irregular tumor shapes. Methods: T2-weighted, dynamic contrast-enhanced T1-weighted, and diffusion-weighted prostate MRI and 3D TRUS images were obtained from 49 patients. A radiologist and radiologymore » resident contoured 81 suspicious regions, yielding 3D tumor surfaces that were registered to the 3D TRUS images using an iterative closest point prostate surface-based method to yield 3D binary images of the suspicious regions in the TRUS context. The probabilityP of obtaining a sample of tumor tissue in one biopsy core was calculated by integrating a 3D Gaussian distribution over each suspicious region domain. Next, the authors performed an exhaustive search to determine the maximum root mean squared error (RMSE, in mm) of a biopsy system that gives P ≥ 95% for each tumor sample, and then repeated this procedure for equal-volume spheres corresponding to each tumor sample. Finally, the authors investigated the effect of probe-axis-direction error on measured tumor burden by studying the relationship between the error and estimated percentage of core involvement. Results: Given a 3.5 mm RMSE for contemporary fusion biopsy systems,P ≥ 95% for 21 out of 81 tumors. The authors determined that for a biopsy system with 3.5 mm RMSE, one cannot expect to sample tumors of approximately 1 cm{sup 3} or smaller with 95% probability with only one biopsy core. The predicted maximum RMSE giving P ≥ 95% for each tumor was consistently greater when using spherical tumor shapes as opposed to no shape assumption. However, an assumption of spherical tumor shape for RMSE = 3.5 mm led to a mean overestimation of tumor sampling probabilities of 3%, implying that assuming spherical tumor shape may be reasonable for many prostate tumors. The authors also determined that a biopsy system would need to have a RMS needle delivery error of no more than 1.6 mm in order to sample 95% of tumors with one core. The authors’ experiments also indicated that the effect of axial-direction error on the measured tumor burden was mitigated by the 18 mm core length at 3.5 mm RMSE. Conclusions: For biopsy systems with RMSE ≥ 3.5 mm, more than one biopsy core must be taken from the majority of tumors to achieveP ≥ 95%. These observations support the authors’ perspective that some tumors of clinically significant sizes may require more than one biopsy attempt in order to be sampled during the first biopsy session. This motivates the authors’ ongoing development of an approach to optimize biopsy plans with the aim of achieving a desired probability of obtaining a sample from each tumor, while minimizing the number of biopsies. Optimized planning of within-tumor targets for MRI-3D TRUS fusion biopsy could support earlier diagnosis of prostate cancer while it remains localized to the gland and curable.« less

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.

Comparison of point counts and territory mapping for detecting effects of forest management on songbirds

USGS Publications Warehouse

Newell, Felicity L.; Sheehan, James; Wood, Petra Bohall; Rodewald, Amanda D.; Buehler, David A.; Keyser, Patrick D.; Larkin, Jeffrey L.; Beachy, Tiffany A.; Bakermans, Marja H.; Boves, Than J.; Evans, Andrea; George, Gregory A.; McDermott, Molly E.; Perkins, Kelly A.; White, Matthew; Wigley, T. Bently

2013-01-01

Point counts are commonly used to assess changes in bird abundance, including analytical approaches such as distance sampling that estimate density. Point-count methods have come under increasing scrutiny because effects of detection probability and field error are difficult to quantify. For seven forest songbirds, we compared fixed-radii counts (50 m and 100 m) and density estimates obtained from distance sampling to known numbers of birds determined by territory mapping. We applied point-count analytic approaches to a typical forest management question and compared results to those obtained by territory mapping. We used a before–after control impact (BACI) analysis with a data set collected across seven study areas in the central Appalachians from 2006 to 2010. Using a 50-m fixed radius, variance in error was at least 1.5 times that of the other methods, whereas a 100-m fixed radius underestimated actual density by >3 territories per 10 ha for the most abundant species. Distance sampling improved accuracy and precision compared to fixed-radius counts, although estimates were affected by birds counted outside 10-ha units. In the BACI analysis, territory mapping detected an overall treatment effect for five of the seven species, and effects were generally consistent each year. In contrast, all point-count methods failed to detect two treatment effects due to variance and error in annual estimates. Overall, our results highlight the need for adequate sample sizes to reduce variance, and skilled observers to reduce the level of error in point-count data. Ultimately, the advantages and disadvantages of different survey methods should be considered in the context of overall study design and objectives, allowing for trade-offs among effort, accuracy, and power to detect treatment effects.

Perception of Community Pharmacists towards Dispensing Errors in Community Pharmacy Setting in Gondar Town, Northwest Ethiopia

PubMed Central

2017-01-01

Background Dispensing errors are inevitable occurrences in community pharmacies across the world. Objective This study aimed to identify the community pharmacists' perception towards dispensing errors in the community pharmacies in Gondar town, Northwest Ethiopia. Methods A cross-sectional study was conducted among 47 community pharmacists selected through convenience sampling. Data were analyzed using SPSS version 20. Descriptive statistics, Mann–Whitney U test, and Pearson's Chi-square test of independence were conducted with P ≤ 0.05 considered statistically significant. Result The majority of respondents were in the 23–28-year age group (N = 26, 55.3%) and with at least B.Pharm degree (N = 25, 53.2%). Poor prescription handwriting and similar/confusing names were perceived to be the main contributing factors while all the strategies and types of dispensing errors were highly acknowledged by the respondents. Group differences (P < 0.05) in opinions were largely due to educational level and age. Conclusion Dispensing errors were associated with prescribing quality and design of dispensary as well as dispensing procedures. Opinion differences relate to age and educational status of the respondents. PMID:28612023

Perception of Community Pharmacists towards Dispensing Errors in Community Pharmacy Setting in Gondar Town, Northwest Ethiopia.

PubMed

Asmelashe Gelayee, Dessalegn; Binega Mekonnen, Gashaw

2017-01-01

Dispensing errors are inevitable occurrences in community pharmacies across the world. This study aimed to identify the community pharmacists' perception towards dispensing errors in the community pharmacies in Gondar town, Northwest Ethiopia. A cross-sectional study was conducted among 47 community pharmacists selected through convenience sampling. Data were analyzed using SPSS version 20. Descriptive statistics, Mann-Whitney U test, and Pearson's Chi-square test of independence were conducted with P ≤ 0.05 considered statistically significant. The majority of respondents were in the 23-28-year age group ( N = 26, 55.3%) and with at least B.Pharm degree ( N = 25, 53.2%). Poor prescription handwriting and similar/confusing names were perceived to be the main contributing factors while all the strategies and types of dispensing errors were highly acknowledged by the respondents. Group differences ( P < 0.05) in opinions were largely due to educational level and age. Dispensing errors were associated with prescribing quality and design of dispensary as well as dispensing procedures. Opinion differences relate to age and educational status of the respondents.

Risks and Consequences of Oversimplifying Educational Inequities: A Response to Morgan et al. (2015)

ERIC Educational Resources Information Center

Skiba, Russell J.; Artiles, Alfredo J.; Kozleski, Elizabeth B.; Losen, Daniel J.; Harry, Elizabeth G.

2016-01-01

In this technical comment, we argue that Morgan et al.'s claim that there is no minority overrepresentation in special education is in error due to (a) sampling considerations, (b) inadequate support from previous and current analyses, and (c) their failure to consider the complexities of special education disproportionality. [For Morgan et al.'s…

The relationship between purely stochastic sampling error and the number of technical replicates used to estimate concentration at an extreme dilution

USDA-ARS?s Scientific Manuscript database

For any analytical system the population mean (mu) number of entities (e.g., cells or molecules) per tested volume, surface area, or mass also defines the population standard deviation (sigma = square root of mu ). For a preponderance of analytical methods, sigma is very small relative to mu due to...

The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships

Treesearch

Tabitha A. Graves; Tzeidle N. Wasserman; Milton Cezar Ribeiro; Erin L. Landguth; Stephen F. Spear; Niko Balkenhol; Colleen B. Higgins; Marie-Josee Fortin; Samuel A. Cushman; Lisette P. Waits

2012-01-01

A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range ormeasurement error in plant or animal...

Analysis and Compensation for Lateral Chromatic Aberration in a Color Coding Structured Light 3D Measurement System.

PubMed

Huang, Junhui; Xue, Qi; Wang, Zhao; Gao, Jianmin

2016-09-03

While color-coding methods have improved the measuring efficiency of a structured light three-dimensional (3D) measurement system, they decreased the measuring accuracy significantly due to lateral chromatic aberration (LCA). In this study, the LCA in a structured light measurement system is analyzed, and a method is proposed to compensate the error caused by the LCA. Firstly, based on the projective transformation, a 3D error map of LCA is constructed in the projector images by using a flat board and comparing the image coordinates of red, green and blue circles with the coordinates of white circles at preselected sample points within the measurement volume. The 3D map consists of the errors, which are the equivalent errors caused by LCA of the camera and projector. Then in measurements, error values of LCA are calculated and compensated to correct the projector image coordinates through the 3D error map and a tri-linear interpolation method. Eventually, 3D coordinates with higher accuracy are re-calculated according to the compensated image coordinates. The effectiveness of the proposed method is verified in the following experiments.

Analysis and Compensation for Lateral Chromatic Aberration in a Color Coding Structured Light 3D Measurement System

PubMed Central

Huang, Junhui; Xue, Qi; Wang, Zhao; Gao, Jianmin

2016-01-01

While color-coding methods have improved the measuring efficiency of a structured light three-dimensional (3D) measurement system, they decreased the measuring accuracy significantly due to lateral chromatic aberration (LCA). In this study, the LCA in a structured light measurement system is analyzed, and a method is proposed to compensate the error caused by the LCA. Firstly, based on the projective transformation, a 3D error map of LCA is constructed in the projector images by using a flat board and comparing the image coordinates of red, green and blue circles with the coordinates of white circles at preselected sample points within the measurement volume. The 3D map consists of the errors, which are the equivalent errors caused by LCA of the camera and projector. Then in measurements, error values of LCA are calculated and compensated to correct the projector image coordinates through the 3D error map and a tri-linear interpolation method. Eventually, 3D coordinates with higher accuracy are re-calculated according to the compensated image coordinates. The effectiveness of the proposed method is verified in the following experiments. PMID:27598174

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.

Patterns of technical error among surgical malpractice claims: an analysis of strategies to prevent injury to surgical patients.

PubMed

Regenbogen, Scott E; Greenberg, Caprice C; Studdert, David M; Lipsitz, Stuart R; Zinner, Michael J; Gawande, Atul A

2007-11-01

To identify the most prevalent patterns of technical errors in surgery, and evaluate commonly recommended interventions in light of these patterns. The majority of surgical adverse events involve technical errors, but little is known about the nature and causes of these events. We examined characteristics of technical errors and common contributing factors among closed surgical malpractice claims. Surgeon reviewers analyzed 444 randomly sampled surgical malpractice claims from four liability insurers. Among 258 claims in which injuries due to error were detected, 52% (n = 133) involved technical errors. These technical errors were further analyzed with a structured review instrument designed by qualitative content analysis. Forty-nine percent of the technical errors caused permanent disability; an additional 16% resulted in death. Two-thirds (65%) of the technical errors were linked to manual error, 9% to errors in judgment, and 26% to both manual and judgment error. A minority of technical errors involved advanced procedures requiring special training ("index operations"; 16%), surgeons inexperienced with the task (14%), or poorly supervised residents (9%). The majority involved experienced surgeons (73%), and occurred in routine, rather than index, operations (84%). Patient-related complexities-including emergencies, difficult or unexpected anatomy, and previous surgery-contributed to 61% of technical errors, and technology or systems failures contributed to 21%. Most technical errors occur in routine operations with experienced surgeons, under conditions of increased patient complexity or systems failure. Commonly recommended interventions, including restricting high-complexity operations to experienced surgeons, additional training for inexperienced surgeons, and stricter supervision of trainees, are likely to address only a minority of technical errors. Surgical safety research should instead focus on improving decision-making and performance in routine operations for complex patients and circumstances.

[Monitoring medication errors in personalised dispensing using the Sentinel Surveillance System method].

PubMed

Pérez-Cebrián, M; Font-Noguera, I; Doménech-Moral, L; Bosó-Ribelles, V; Romero-Boyero, P; Poveda-Andrés, J L

2011-01-01

To assess the efficacy of a new quality control strategy based on daily randomised sampling and monitoring a Sentinel Surveillance System (SSS) medication cart, in order to identify medication errors and their origin at different levels of the process. Prospective quality control study with one year follow-up. A SSS medication cart was randomly selected once a week and double-checked before dispensing medication. Medication errors were recorded before it was taken to the relevant hospital ward. Information concerning complaints after receiving medication and 24-hour monitoring were also noted. Type and origin error data were assessed by a Unit Dose Quality Control Group, which proposed relevant improvement measures. Thirty-four SSS carts were assessed, including 5130 medication lines and 9952 dispensed doses, corresponding to 753 patients. Ninety erroneous lines (1.8%) and 142 mistaken doses (1.4%) were identified at the Pharmacy Department. The most frequent error was dose duplication (38%) and its main cause inappropriate management and forgetfulness (69%). Fifty medication complaints (6.6% of patients) were mainly due to new treatment at admission (52%), and 41 (0.8% of all medication lines), did not completely match the prescription (0.6% lines) as recorded by the Pharmacy Department. Thirty-seven (4.9% of patients) medication complaints due to changes at admission and 32 matching errors (0.6% medication lines) were recorded. The main cause also was inappropriate management and forgetfulness (24%). The simultaneous recording of incidences due to complaints and new medication coincided in 33.3%. In addition, 433 (4.3%) of dispensed doses were returned to the Pharmacy Department. After the Unit Dose Quality Control Group conducted their feedback analysis, 64 improvement measures for Pharmacy Department nurses, 37 for pharmacists, and 24 for the hospital ward were introduced. The SSS programme has proven to be useful as a quality control strategy to identify Unit Dose Distribution System errors at initial, intermediate and final stages of the process, improving the involvement of the Pharmacy Department and ward nurses. Copyright © 2009 SEFH. Published by Elsevier Espana. All rights reserved.

Estimating random errors due to shot noise in backscatter lidar observations.

PubMed

Liu, Zhaoyan; Hunt, William; Vaughan, Mark; Hostetler, Chris; McGill, Matthew; Powell, Kathleen; Winker, David; Hu, Yongxiang

2006-06-20

We discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson- distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root mean square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF, uncertainties can be reliably calculated from or for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations lidar and tested using data from the Lidar In-space Technology Experiment.

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

NASA Technical Reports Server (NTRS)

Liu, Zhaoyan; Hunt, William; Vaughan, Mark A.; Hostetler, Chris A.; McGill, Matthew J.; Powell, Kathy; Winker, David M.; Hu, Yongxiang

2006-01-01

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Effective Thermal-Conductivity Measurements on Supporting Structures of the Mercury Probe Bepi Colombo

NASA Astrophysics Data System (ADS)

Vidi, S.; Rausch, S.; Ebert, H. P.; Löhberg, A.; Petry, D.

2013-05-01

Measurements were done on a carbon fiber reinforced composite (CFC) sample tested for the space probe Bepi Colombo by using the guarded hot-plate (GHP) method. The values of interest were the thermal transmittance through the samples, (56.3 ± 3.6) W · m-2 · K-1, and the effective thermal conductivity (1.06 ± 0.07) W · m-1 · K-1. The samples consist of a light honeycomb core attached to thicker surface plates. Due to this construction, the effective thermal conductivity parallel to the face plates is higher than the effective thermal conductivity through the sample. This leads to lateral heat gains or losses during the GHP measurement, which in return can lead to erroneous results. Furthermore, due to the high rigidity of the CFC material, there will be high contact resistances between the samples and the GHP apparatus plates. The separation of these thermal contact resistances from the total measured thermal resistance is essential in order to achieve correct results. Good results were achieved using a special measurement setup and a lateral correction method designed to reduce errors due to lateral heat flows.

Apparent polyploidization after gamma irradiation: pitfalls in the use of quantitative polymerase chain reaction (qPCR) for the estimation of mitochondrial and nuclear DNA gene copy numbers.

PubMed

Kam, Winnie W Y; Lake, Vanessa; Banos, Connie; Davies, Justin; Banati, Richard

2013-05-30

Quantitative polymerase chain reaction (qPCR) has been widely used to quantify changes in gene copy numbers after radiation exposure. Here, we show that gamma irradiation ranging from 10 to 100 Gy of cells and cell-free DNA samples significantly affects the measured qPCR yield, due to radiation-induced fragmentation of the DNA template and, therefore, introduces errors into the estimation of gene copy numbers. The radiation-induced DNA fragmentation and, thus, measured qPCR yield varies with temperature not only in living cells, but also in isolated DNA irradiated under cell-free conditions. In summary, the variability in measured qPCR yield from irradiated samples introduces a significant error into the estimation of both mitochondrial and nuclear gene copy numbers and may give spurious evidence for polyploidization.

Systematic evaluation of NASA precipitation radar estimates using NOAA/NSSL National Mosaic QPE products

NASA Astrophysics Data System (ADS)

Kirstetter, P.; Hong, Y.; Gourley, J. J.; Chen, S.; Flamig, Z.; Zhang, J.; Howard, K.; Petersen, W. A.

2011-12-01

Proper characterization of the error structure of TRMM Precipitation Radar (PR) quantitative precipitation estimation (QPE) is needed for their use in TRMM combined products, water budget studies and hydrological modeling applications. Due to the variety of sources of error in spaceborne radar QPE (attenuation of the radar signal, influence of land surface, impact of off-nadir viewing angle, etc.) and the impact of correction algorithms, the problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements (GV) using NOAA/NSSL's National Mosaic QPE (NMQ) system. An investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) on the basis of a 3-month-long data sample. A significant effort has been carried out to derive a bias-corrected, robust reference rainfall source from NMQ. The GV processing details will be presented along with preliminary results of PR's error characteristics using contingency table statistics, probability distribution comparisons, scatter plots, semi-variograms, and systematic biases and random errors.

Benign phyllodes tumor with tubular adenoma-like epithelial component in FNAC: A diagnostic pitfall.

PubMed

Panda, Kishori M

2016-01-01

Benign phyllodes tumor (BPT) is a biphasic neoplasm composed of bland stromal and epithelial elements. Cytologic diagnostic criteria of BPT, though documented in the literature, diagnostic pitfalls in fine-needle aspiration cytology (FNAC) may occur due to sampling error, high cellularity, ductal hyperplasia, paucity of stromal component, and occasional dissociation of epithelial cells. Here, we describe a case of BPT diagnosed by histology in a 19-year-old female, where FNAC features were inconclusive due to paucity of stromal component, predominance of tubular adenoma-like epithelial component, and due to the presence of other overlapping features with fibroadenoma.

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%.

Phonological and Motor Errors in Individuals with Acquired Sound Production Impairment

ERIC Educational Resources Information Center

Buchwald, Adam; Miozzo, Michele

2012-01-01

Purpose: This study aimed to compare sound production errors arising due to phonological processing impairment with errors arising due to motor speech impairment. Method: Two speakers with similar clinical profiles who produced similar consonant cluster simplification errors were examined using a repetition task. We compared both overall accuracy…

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.

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.

Optical diagnosis of malaria infection in human plasma using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Bilal, Muhammad; Saleem, Muhammad; Amanat, Samina Tufail; Shakoor, Huma Abdul; Rashid, Rashad; Mahmood, Arshad; Ahmed, Mushtaq

2015-01-01

We present the prediction of malaria infection in human plasma using Raman spectroscopy. Raman spectra of malaria-infected samples are compared with those of healthy and dengue virus infected ones for disease recognition. Raman spectra were acquired using a laser at 532 nm as an excitation source and 10 distinct spectral signatures that statistically differentiated malaria from healthy and dengue-infected cases were found. A multivariate regression model has been developed that utilized Raman spectra of 20 malaria-infected, 10 non-malarial with fever, 10 healthy, and 6 dengue-infected samples to optically predict the malaria infection. The model yields the correlation coefficient r2 value of 0.981 between the predicted values and clinically known results of trainee samples, and the root mean square error in cross validation was found to be 0.09; both these parameters validated the model. The model was further blindly tested for 30 unknown suspected samples and found to be 86% accurate compared with the clinical results, with the inaccuracy due to three samples which were predicted in the gray region. Standard deviation and root mean square error in prediction for unknown samples were found to be 0.150 and 0.149, which are accepted for the clinical validation of the model.

An Improved Model Predictive Current Controller of Switched Reluctance Machines Using Time-Multiplexed Current Sensor

PubMed Central

Li, Bingchu; Ling, Xiao; Huang, Yixiang; Gong, Liang; Liu, Chengliang

2017-01-01

This paper presents a fixed-switching-frequency model predictive current controller using multiplexed current sensor for switched reluctance machine (SRM) drives. The converter was modified to distinguish currents from simultaneously excited phases during the sampling period. The only current sensor installed in the converter was time division multiplexing for phase current sampling. During the commutation stage, the control steps of adjacent phases were shifted so that sampling time was staggered. The maximum and minimum duty ratio of pulse width modulation (PWM) was limited to keep enough sampling time for analog-to-digital (A/D) conversion. Current sensor multiplexing was realized without complex adjustment of either driver circuit nor control algorithms, while it helps to reduce the cost and errors introduced in current sampling due to inconsistency between sensors. The proposed controller is validated by both simulation and experimental results with a 1.5 kW three-phase 12/8 SRM. Satisfied current sampling is received with little difference compared with independent phase current sensors for each phase. The proposed controller tracks the reference current profile as accurately as the model predictive current controller with independent phase current sensors, while having minor tracking errors compared with a hysteresis current controller. PMID:28513554

Treatment of ocean tide aliasing in the context of a next generation gravity field mission

NASA Astrophysics Data System (ADS)

Hauk, Markus; Pail, Roland

2018-07-01

Current temporal gravity field solutions from Gravity Recovery and Climate Experiment (GRACE) suffer from temporal aliasing errors due to undersampling of signal to be recovered (e.g. hydrology), uncertainties in the de-aliasing models (usually atmosphere and ocean) and imperfect ocean tide models. Especially the latter will be one of the most limiting factors in determining high-resolution temporal gravity fields from future gravity missions such as GRACE Follow-On and Next-Generation Gravity Missions (NGGM). In this paper a method to co-parametrize ocean tide parameters of the eight main tidal constituents over time spans of several years is analysed and assessed. Numerical closed-loop simulations of low-low satellite-to-satellite-tracking missions for a single polar pair and a double pair Bender-type formation are performed, using time variable geophysical background models and noise assumptions for new generation instrument technology. Compared to the single pair mission, results show a reduction of tide model errors up to 70 per cent for dedicated tidal constituents due to an enhanced spatial and temporal sampling and error isotropy for the double pair constellation. Extending the observation period from 1 to 3 yr leads to a further reduction of tidal errors up to 60 per cent for certain constituents, and considering non-tidal mass changes during the estimation process leads to reductions of tidal errors between 20 and 80 per cent. As part of a two-step approach, the estimated tide model is used for de-aliasing during gravity field retrieval in a second iteration, resulting in more than 50 per cent reduction of ocean tide aliasing errors for a NGGM Bender-type formation.

Cluster-sample surveys and lot quality assurance sampling to evaluate yellow fever immunisation coverage following a national campaign, Bolivia, 2007.

PubMed

Pezzoli, Lorenzo; Pineda, Silvia; Halkyer, Percy; Crespo, Gladys; Andrews, Nick; Ronveaux, Olivier

2009-03-01

To estimate the yellow fever (YF) vaccine coverage for the endemic and non-endemic areas of Bolivia and to determine whether selected districts had acceptable levels of coverage (>70%). We conducted two surveys of 600 individuals (25 x 12 clusters) to estimate coverage in the endemic and non-endemic areas. We assessed 11 districts using lot quality assurance sampling (LQAS). The lot (district) sample was 35 individuals with six as decision value (alpha error 6% if true coverage 70%; beta error 6% if true coverage 90%). To increase feasibility, we divided the lots into five clusters of seven individuals; to investigate the effect of clustering, we calculated alpha and beta by conducting simulations where each cluster's true coverage was sampled from a normal distribution with a mean of 70% or 90% and standard deviations of 5% or 10%. Estimated coverage was 84.3% (95% CI: 78.9-89.7) in endemic areas, 86.8% (82.5-91.0) in non-endemic and 86.0% (82.8-89.1) nationally. LQAS showed that four lots had unacceptable coverage levels. In six lots, results were inconsistent with the estimated administrative coverage. The simulations suggested that the effect of clustering the lots is unlikely to have significantly increased the risk of making incorrect accept/reject decisions. Estimated YF coverage was high. Discrepancies between administrative coverage and LQAS results may be due to incorrect population data. Even allowing for clustering in LQAS, the statistical errors would remain low. Catch-up campaigns are recommended in districts with unacceptable coverage.

Evaluating mixed samples as a source of error in non-invasive genetic studies using microsatellites

USGS Publications Warehouse

Roon, David A.; Thomas, M.E.; Kendall, K.C.; Waits, L.P.

2005-01-01

The use of noninvasive genetic sampling (NGS) for surveying wild populations is increasing rapidly. Currently, only a limited number of studies have evaluated potential biases associated with NGS. This paper evaluates the potential errors associated with analysing mixed samples drawn from multiple animals. Most NGS studies assume that mixed samples will be identified and removed during the genotyping process. We evaluated this assumption by creating 128 mixed samples of extracted DNA from brown bear (Ursus arctos) hair samples. These mixed samples were genotyped and screened for errors at six microsatellite loci according to protocols consistent with those used in other NGS studies. Five mixed samples produced acceptable genotypes after the first screening. However, all mixed samples produced multiple alleles at one or more loci, amplified as only one of the source samples, or yielded inconsistent electropherograms by the final stage of the error-checking process. These processes could potentially reduce the number of individuals observed in NGS studies, but errors should be conservative within demographic estimates. Researchers should be aware of the potential for mixed samples and carefully design gel analysis criteria and error checking protocols to detect mixed samples.

Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias

PubMed Central

Chambers, David A.; Glasgow, Russell E.

2014-01-01

Abstract A number of commentaries have suggested that large studies are more reliable than smaller studies and there is a growing interest in the analysis of “big data” that integrates information from many thousands of persons and/or different data sources. We consider a variety of biases that are likely in the era of big data, including sampling error, measurement error, multiple comparisons errors, aggregation error, and errors associated with the systematic exclusion of information. Using examples from epidemiology, health services research, studies on determinants of health, and clinical trials, we conclude that it is necessary to exercise greater caution to be sure that big sample size does not lead to big inferential errors. Despite the advantages of big studies, large sample size can magnify the bias associated with error resulting from sampling or study design. Clin Trans Sci 2014; Volume #: 1–5 PMID:25043853

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

NASA Astrophysics Data System (ADS)

Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

2016-09-01

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

Quantifying seining detection probability for fishes of Great Plains sand‐bed rivers

USGS Publications Warehouse

Mollenhauer, Robert; Logue, Daniel R.; Brewer, Shannon K.

2018-01-01

Species detection error (i.e., imperfect and variable detection probability) is an essential consideration when investigators map distributions and interpret habitat associations. When fish detection error that is due to highly variable instream environments needs to be addressed, sand‐bed streams of the Great Plains represent a unique challenge. We quantified seining detection probability for diminutive Great Plains fishes across a range of sampling conditions in two sand‐bed rivers in Oklahoma. Imperfect detection resulted in underestimates of species occurrence using naïve estimates, particularly for less common fishes. Seining detection probability also varied among fishes and across sampling conditions. We observed a quadratic relationship between water depth and detection probability, in which the exact nature of the relationship was species‐specific and dependent on water clarity. Similarly, the direction of the relationship between water clarity and detection probability was species‐specific and dependent on differences in water depth. The relationship between water temperature and detection probability was also species dependent, where both the magnitude and direction of the relationship varied among fishes. We showed how ignoring detection error confounded an underlying relationship between species occurrence and water depth. Despite imperfect and heterogeneous detection, our results support that determining species absence can be accomplished with two to six spatially replicated seine hauls per 200‐m reach under average sampling conditions; however, required effort would be higher under certain conditions. Detection probability was low for the Arkansas River Shiner Notropis girardi, which is federally listed as threatened, and more than 10 seine hauls per 200‐m reach would be required to assess presence across sampling conditions. Our model allows scientists to estimate sampling effort to confidently assess species occurrence, which maximizes the use of available resources. Increased implementation of approaches that consider detection error promote ecological advancements and conservation and management decisions that are better informed.

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.

Feedback Augmented Sub-Ranging (FASR) Quantizer

NASA Technical Reports Server (NTRS)

Guilligan, Gerard

2012-01-01

This innovation is intended to reduce the size, power, and complexity of pipeline analog-to-digital converters (ADCs) that require high resolution and speed along with low power. Digitizers are important components in any application where analog signals (such as light, sound, temperature, etc.) need to be digitally processed. The innovation implements amplification of a sampled residual voltage in a switched capacitor amplifier stage that does not depend on charge redistribution. The result is less sensitive to capacitor mismatches that cause gain errors, which are the main limitation of such amplifiers in pipeline ADCs. The residual errors due to mismatch are reduced by at least a factor of 16, which is equivalent to at least 4 bits of improvement. The settling time is also faster because of a higher feedback factor. In traditional switched capacitor residue amplifiers, closed-loop amplification of a sampled and held residue signal is achieved by redistributing sampled charge onto a feedback capacitor around a high-gain transconductance amplifier. The residual charge that was sampled during the acquisition or sampling phase is stored on two or more capacitors, often equal in value or integral multiples of each other. During the hold or amplification phase, all of the charge is redistributed onto one capacitor in the feedback loop of the amplifier to produce an amplified voltage. The key error source is the non-ideal ratios of feedback and input capacitors caused by manufacturing tolerances, called mismatches. The mismatches cause non-ideal closed-loop gain, leading to higher differential non-linearity. Traditional solutions to the mismatch errors are to use larger capacitor values (than dictated by thermal noise requirements) and/or complex calibration schemes, both of which increase the die size and power dissipation. The key features of this innovation are (1) the elimination of the need for charge redistribution to achieve an accurate closed-loop gain of two, (2) a higher feedback factor in the amplifier stage giving a higher closed-loop bandwidth compared to the prior art, and (3) reduced requirement for calibration. The accuracy of the new amplifier is mainly limited by the sampling networks parasitic capacitances, which should be minimized in relation to the sampling capacitors.

Propagation of stage measurement uncertainties to streamflow time series

NASA Astrophysics Data System (ADS)

Horner, Ivan; Le Coz, Jérôme; Renard, Benjamin; Branger, Flora; McMillan, Hilary

2016-04-01

Streamflow uncertainties due to stage measurements errors are generally overlooked in the promising probabilistic approaches that have emerged in the last decade. We introduce an original error model for propagating stage uncertainties through a stage-discharge rating curve within a Bayesian probabilistic framework. The method takes into account both rating curve (parametric errors and structural errors) and stage uncertainty (systematic and non-systematic errors). Practical ways to estimate the different types of stage errors are also presented: (1) non-systematic errors due to instrument resolution and precision and non-stationary waves and (2) systematic errors due to gauge calibration against the staff gauge. The method is illustrated at a site where the rating-curve-derived streamflow can be compared with an accurate streamflow reference. The agreement between the two time series is overall satisfying. Moreover, the quantification of uncertainty is also satisfying since the streamflow reference is compatible with the streamflow uncertainty intervals derived from the rating curve and the stage uncertainties. Illustrations from other sites are also presented. Results are much contrasted depending on the site features. In some cases, streamflow uncertainty is mainly due to stage measurement errors. The results also show the importance of discriminating systematic and non-systematic stage errors, especially for long term flow averages. Perspectives for improving and validating the streamflow uncertainty estimates are eventually discussed.

[Epidemiology of refractive errors].

PubMed

Wolfram, C

2017-07-01

Refractive errors are very common and can lead to severe pathological changes in the eye. This article analyzes the epidemiology of refractive errors in the general population in Germany and worldwide and describes common definitions for refractive errors and clinical characteristics for pathologicaal changes. Refractive errors differ between age groups due to refractive changes during the life time and also due to generation-specific factors. Current research about the etiology of refractive errors has strengthened the influence of environmental factors, which led to new strategies for the prevention of refractive pathologies.

Unforced errors and error reduction in tennis

PubMed Central

Brody, H

2006-01-01

Only at the highest level of tennis is the number of winners comparable to the number of unforced errors. As the average player loses many more points due to unforced errors than due to winners by an opponent, if the rate of unforced errors can be reduced, it should lead to an increase in points won. This article shows how players can improve their game by understanding and applying the laws of physics to reduce the number of unforced errors. PMID:16632568

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.

Sampling of the Diurnal Cycle of Precipitation using TRMM

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Bell, Thomas L.; Xu, Li-Ming; Starr, David OC. (Technical Monitor)

2001-01-01

We examine the temporal sampling of tropical regions using observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR). We conclude that PR estimates at any one hour, even using three years of data, are inadequate to describe the diurnal cycle of precipitation over regions smaller than 12 degrees, due to high spatial variability in sampling. We show that the optimum period of accumulation is four hours. Diurnal signatures display half as much sampling error when averaged over four hours of local time. A similar pattern of sampling variability is found in the TMI data, despite the TMI's wider swath and increased sampling. These results are verified using an orbital model. The sensitivity of the sampling to satellite altitude is presented, as well as sampling patterns at the new TRMM altitude of 402.5 km.

An improved SRC method based on virtual samples for face recognition

NASA Astrophysics Data System (ADS)

Fu, Lijun; Chen, Deyun; Lin, Kezheng; Li, Ao

2018-07-01

The sparse representation classifier (SRC) performs classification by evaluating which class leads to the minimum representation error. However, in real world, the number of available training samples is limited due to noise interference, training samples cannot accurately represent the test sample linearly. Therefore, in this paper, we first produce virtual samples by exploiting original training samples at the aim of increasing the number of training samples. Then, we take the intra-class difference as data representation of partial noise, and utilize the intra-class differences and training samples simultaneously to represent the test sample in a linear way according to the theory of SRC algorithm. Using weighted score level fusion, the respective representation scores of the virtual samples and the original training samples are fused together to obtain the final classification results. The experimental results on multiple face databases show that our proposed method has a very satisfactory classification performance.

"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.

Simultaneous Laser Ranging and Communication from an Earth-Based Satellite Laser Ranging Station to the Lunar Reconnaissance Orbiter in Lunar Orbit

NASA Technical Reports Server (NTRS)

Sun, Xiaoli; Skillman, David R.; Hoffman, Evan D.; Mao, Dandan; McGarry, Jan F.; Neumann, Gregory A.; McIntire, Leva; Zellar, Ronald S.; Davidson, Frederic M.; Fong, Wai H.;

High-frequency signal and noise estimates of CSR GRACE RL04

NASA Astrophysics Data System (ADS)

Bonin, Jennifer A.; Bettadpur, Srinivas; Tapley, Byron D.

2012-12-01

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04's poor ability to accurately and reliably measure hydrological signal above 3-9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.

[Failure mode and effects analysis on computerized drug prescriptions].

PubMed

Paredes-Atenciano, J A; Roldán-Aviña, J P; González-García, Mercedes; Blanco-Sánchez, M C; Pinto-Melero, M A; Pérez-Ramírez, C; Calvo Rubio-Burgos, Miguel; Osuna-Navarro, F J; Jurado-Carmona, A M

2015-01-01

To identify and analyze errors in drug prescriptions of patients treated in a "high resolution" hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in "unspecified route of administration" and "dosage unspecified", with no significant decreases observed in the second phase, although it did detect, "incorrect dosing time", "contraindication due to drug allergy", "wrong patient" or "duplicate prescription", which resulted in the improvement of prescriptions. Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

PubMed

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

2014-08-25

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

Preliminary Evidence for Reduced Post-Error Reaction Time Slowing in Hyperactive/Inattentive Preschool Children

PubMed Central

Berwid, Olga G.; Halperin, Jeffrey M.; Johnson, Ray E.; Marks, David J.

2013-01-01

Background Attention-Deficit/Hyperactivity Disorder has been associated with deficits in self-regulatory cognitive processes, some of which are thought to lie at the heart of the disorder. Slowing of reaction times (RTs) for correct responses following errors made during decision tasks has been interpreted as an indication of intact self-regulatory functioning and has been shown to be attenuated in school-aged children with ADHD. This study attempted to examine whether ADHD symptoms are associated with an early-emerging deficit in post-error slowing. Method A computerized two-choice RT task was administered to an ethnically diverse sample of preschool-aged children classified as either ‘control’ (n = 120) or ‘hyperactive/inattentive’ (HI; n = 148) using parent- and teacher-rated ADHD symptoms. Analyses were conducted to determine whether HI preschoolers exhibit a deficit in this self-regulatory ability. Results HI children exhibited reduced post-error slowing relative to controls on the trials selected for analysis. Supplementary analyses indicated that this may have been due to a reduced proportion of trials following errors on which HI children slowed rather than to a reduction in the absolute magnitude of slowing on all trials following errors. Conclusions High levels of ADHD symptoms in preschoolers may be associated with a deficit in error processing as indicated by post-error slowing. The results of supplementary analyses suggest that this deficit is perhaps more a result of failures to perceive errors than of difficulties with executive control. PMID:23387525

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...

Estimating and comparing microbial diversity in the presence of sequencing errors

PubMed Central

Chiu, Chun-Huo

2016-01-01

Estimating and comparing microbial diversity are statistically challenging due to limited sampling and possible sequencing errors for low-frequency counts, producing spurious singletons. The inflated singleton count seriously affects statistical analysis and inferences about microbial diversity. Previous statistical approaches to tackle the sequencing errors generally require different parametric assumptions about the sampling model or about the functional form of frequency counts. Different parametric assumptions may lead to drastically different diversity estimates. We focus on nonparametric methods which are universally valid for all parametric assumptions and can be used to compare diversity across communities. We develop here a nonparametric estimator of the true singleton count to replace the spurious singleton count in all methods/approaches. Our estimator of the true singleton count is in terms of the frequency counts of doubletons, tripletons and quadrupletons, provided these three frequency counts are reliable. To quantify microbial alpha diversity for an individual community, we adopt the measure of Hill numbers (effective number of taxa) under a nonparametric framework. Hill numbers, parameterized by an order q that determines the measures’ emphasis on rare or common species, include taxa richness (q = 0), Shannon diversity (q = 1, the exponential of Shannon entropy), and Simpson diversity (q = 2, the inverse of Simpson index). A diversity profile which depicts the Hill number as a function of order q conveys all information contained in a taxa abundance distribution. Based on the estimated singleton count and the original non-singleton frequency counts, two statistical approaches (non-asymptotic and asymptotic) are developed to compare microbial diversity for multiple communities. (1) A non-asymptotic approach refers to the comparison of estimated diversities of standardized samples with a common finite sample size or sample completeness. This approach aims to compare diversity estimates for equally-large or equally-complete samples; it is based on the seamless rarefaction and extrapolation sampling curves of Hill numbers, specifically for q = 0, 1 and 2. (2) An asymptotic approach refers to the comparison of the estimated asymptotic diversity profiles. That is, this approach compares the estimated profiles for complete samples or samples whose size tends to be sufficiently large. It is based on statistical estimation of the true Hill number of any order q ≥ 0. In the two approaches, replacing the spurious singleton count by our estimated count, we can greatly remove the positive biases associated with diversity estimates due to spurious singletons and also make fair comparisons across microbial communities, as illustrated in our simulation results and in applying our method to analyze sequencing data from viral metagenomes. PMID:26855872

Compressive sensing of signals generated in plastic scintillators in a novel J-PET instrument

NASA Astrophysics Data System (ADS)

Raczyński, L.; Moskal, P.; Kowalski, P.; Wiślicki, W.; Bednarski, T.; Białas, P.; Czerwiński, E.; Gajos, A.; Kapłon, Ł.; Kochanowski, A.; Korcyl, G.; Kowal, J.; Kozik, T.; Krzemień, W.; Kubicz, E.; Niedźwiecki, Sz.; Pałka, M.; Rudy, Z.; Rundel, O.; Salabura, P.; Sharma, N. G.; Silarski, M.; Słomski, A.; Smyrski, J.; Strzelecki, A.; Wieczorek, A.; Zieliński, M.; Zoń, N.

2015-06-01

The J-PET scanner, which allows for single bed imaging of the whole human body, is currently under development at the Jagiellonian University. The discussed detector offers improvement of the Time of Flight (TOF) resolution due to the use of fast plastic scintillators and dedicated electronics allowing for sampling in the voltage domain of signals with durations of few nanoseconds. In this paper we show that recovery of the whole signal, based on only a few samples, is possible. In order to do that, we incorporate the training signals into the Tikhonov regularization framework and we perform the Principal Component Analysis decomposition, which is well known for its compaction properties. The method yields a simple closed form analytical solution that does not require iterative processing. Moreover, from the Bayes theory the properties of regularized solution, especially its covariance matrix, may be easily derived. This is the key to introduce and prove the formula for calculations of the signal recovery error. In this paper we show that an average recovery error is approximately inversely proportional to the number of acquired samples.

Detecting and preventing error propagation via competitive learning.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2013-05-01

Semisupervised learning is a machine learning approach which is able to employ both labeled and unlabeled samples in the training process. It is an important mechanism for autonomous systems due to the ability of exploiting the already acquired information and for exploring the new knowledge in the learning space at the same time. In these cases, the reliability of the labels is a crucial factor, because mislabeled samples may propagate wrong labels to a portion of or even the entire data set. This paper has the objective of addressing the error propagation problem originated by these mislabeled samples by presenting a mechanism embedded in a network-based (graph-based) semisupervised learning method. Such a procedure is based on a combined random-preferential walk of particles in a network constructed from the input data set. The particles of the same class cooperate among them, while the particles of different classes compete with each other to propagate class labels to the whole network. Computer simulations conducted on synthetic and real-world data sets reveal the effectiveness of the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

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.

Blood transfusion sampling and a greater role for error recovery.

PubMed

Oldham, Jane

Patient identification errors in pre-transfusion blood sampling ('wrong blood in tube') are a persistent area of risk. These errors can potentially result in life-threatening complications. Current measures to address root causes of incidents and near misses have not resolved this problem and there is a need to look afresh at this issue. PROJECT PURPOSE: This narrative review of the literature is part of a wider system-improvement project designed to explore and seek a better understanding of the factors that contribute to transfusion sampling error as a prerequisite to examining current and potential approaches to error reduction. A broad search of the literature was undertaken to identify themes relating to this phenomenon. KEY DISCOVERIES: Two key themes emerged from the literature. Firstly, despite multi-faceted causes of error, the consistent element is the ever-present potential for human error. Secondly, current focus on error prevention could potentially be augmented with greater attention to error recovery. Exploring ways in which clinical staff taking samples might learn how to better identify their own errors is proposed to add to current safety initiatives.

Evaluation of limited sampling models for prediction of oral midazolam AUC for CYP3A phenotyping and drug interaction studies.

PubMed

Mueller, Silke C; Drewelow, Bernd

2013-05-01

The area under the concentration-time curve (AUC) after oral midazolam administration is commonly used for cytochrome P450 (CYP) 3A phenotyping studies. The aim of this investigation was to evaluate a limited sampling strategy for the prediction of AUC with oral midazolam. A total of 288 concentration-time profiles from 123 healthy volunteers who participated in four previously performed drug interaction studies with intense sampling after a single oral dose of 7.5 mg midazolam were available for evaluation. Of these, 45 profiles served for model building, which was performed by stepwise multiple linear regression, and the remaining 243 datasets served for validation. Mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were calculated to determine bias and precision The one- to four-sampling point models with the best coefficient of correlation were the one-sampling point model (8 h; r (2) = 0.84), the two-sampling point model (0.5 and 8 h; r (2) = 0.93), the three-sampling point model (0.5, 2, and 8 h; r (2) = 0.96), and the four-sampling point model (0.5,1, 2, and 8 h; r (2) = 0.97). However, the one- and two-sampling point models were unable to predict the midazolam AUC due to unacceptable bias and precision. Only the four-sampling point model predicted the very low and very high midazolam AUC of the validation dataset with acceptable precision and bias. The four-sampling point model was also able to predict the geometric mean ratio of the treatment phase over the baseline (with 90 % confidence interval) results of three drug interaction studies in the categories of strong, moderate, and mild induction, as well as no interaction. A four-sampling point limited sampling strategy to predict the oral midazolam AUC for CYP3A phenotyping is proposed. The one-, two- and three-sampling point models were not able to predict midazolam AUC accurately.

The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study

PubMed Central

Thorlund, Kristian; Imberger, Georgina; Walsh, Michael; Chu, Rong; Gluud, Christian; Wetterslev, Jørn; Guyatt, Gordon; Devereaux, Philip J.; Thabane, Lehana

2011-01-01

Background Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. Methods We simulated a comprehensive array of meta-analysis scenarios where no intervention effect existed (i.e., relative risk reduction (RRR) = 0%) or where a small but possibly unimportant effect existed (RRR = 10%). We constructed different scenarios by varying the control group risk, the degree of heterogeneity, and the distribution of trial sample sizes. For each scenario, we calculated the probability of observing overestimates of RRR>20% and RRR>30% for each cumulative 500 patients and 50 events. We calculated the cumulative number of patients and events required to reduce the probability of overestimation of intervention effect to 10%, 5%, and 1%. We calculated the optimal information size for each of the simulated scenarios and explored whether meta-analyses that surpassed their optimal information size had sufficient protection against overestimation of intervention effects due to random error. Results The risk of overestimation of intervention effects was usually high when the number of patients and events was small and this risk decreased exponentially over time as the number of patients and events increased. The number of patients and events required to limit the risk of overestimation depended considerably on the underlying simulation settings. Surpassing the optimal information size generally provided sufficient protection against overestimation. Conclusions Random errors are a frequent cause of overestimation of intervention effects in meta-analyses. Surpassing the optimal information size will provide sufficient protection against overestimation. PMID:22028777

Simulating the performance of a distance-3 surface code in a linear ion trap

NASA Astrophysics Data System (ADS)

Trout, Colin J.; Li, Muyuan; Gutiérrez, Mauricio; Wu, Yukai; Wang, Sheng-Tao; Duan, Luming; Brown, Kenneth R.

2018-04-01

We explore the feasibility of implementing a small surface code with 9 data qubits and 8 ancilla qubits, commonly referred to as surface-17, using a linear chain of 171Yb+ ions. Two-qubit gates can be performed between any two ions in the chain with gate time increasing linearly with ion distance. Measurement of the ion state by fluorescence requires that the ancilla qubits be physically separated from the data qubits to avoid errors on the data due to scattered photons. We minimize the time required to measure one round of stabilizers by optimizing the mapping of the two-dimensional surface code to the linear chain of ions. We develop a physically motivated Pauli error model that allows for fast simulation and captures the key sources of noise in an ion trap quantum computer including gate imperfections and ion heating. Our simulations showed a consistent requirement of a two-qubit gate fidelity of ≥99.9% for the logical memory to have a better fidelity than physical two-qubit operations. Finally, we perform an analysis of the error subsets from the importance sampling method used to bound the logical error rates to gain insight into which error sources are particularly detrimental to error correction.

Visual disability, visual function, and myopia among rural chinese secondary school children: the Xichang Pediatric Refractive Error Study (X-PRES)--report 1.

PubMed

Congdon, Nathan; Wang, Yunfei; Song, Yue; Choi, Kai; Zhang, Mingzhi; Zhou, Zhongxia; Xie, Zhenling; Li, Liping; Liu, Xueyu; Sharma, Abhishek; Wu, Bin; Lam, Dennis S C

2008-07-01

To evaluate visual acuity, visual function, and prevalence of refractive error among Chinese secondary-school children in a cross-sectional school-based study. Uncorrected, presenting, and best corrected visual acuity, cycloplegic autorefraction with refinement, and self-reported visual function were assessed in a random, cluster sample of rural secondary school students in Xichang, China. Among the 1892 subjects (97.3% of the consenting children, 84.7% of the total sample), mean age was 14.7 +/- 0.8 years, 51.2% were female, and 26.4% were wearing glasses. The proportion of children with uncorrected, presenting, and corrected visual disability (< or = 6/12 in the better eye) was 41.2%, 19.3%, and 0.5%, respectively. Myopia < -0.5, < -2.0, and < -6.0 D in both eyes was present in 62.3%, 31.1%, and 1.9% of the subjects, respectively. Among the children with visual disability when tested without correction, 98.7% was due to refractive error, while only 53.8% (414/770) of these children had appropriate correction. The girls had significantly (P < 0.001) more presenting visual disability and myopia < -2.0 D than did the boys. More myopic refractive error was associated with worse self-reported visual function (ANOVA trend test, P < 0.001). Visual disability in this population was common, highly correctable, and frequently uncorrected. The impact of refractive error on self-reported visual function was significant. Strategies and studies to understand and remove barriers to spectacle wear are needed.

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…

Adjustment of regional regression models of urban-runoff quality using data for Chattanooga, Knoxville, and Nashville, Tennessee

USGS Publications Warehouse

Hoos, Anne B.; Patel, Anant R.

1996-01-01

Model-adjustment procedures were applied to the combined data bases of storm-runoff quality for Chattanooga, Knoxville, and Nashville, Tennessee, to improve predictive accuracy for storm-runoff quality for urban watersheds in these three cities and throughout Middle and East Tennessee. Data for 45 storms at 15 different sites (five sites in each city) constitute the data base. Comparison of observed values of storm-runoff load and event-mean concentration to the predicted values from the regional regression models for 10 constituents shows prediction errors, as large as 806,000 percent. Model-adjustment procedures, which combine the regional model predictions with local data, are applied to improve predictive accuracy. Standard error of estimate after model adjustment ranges from 67 to 322 percent. Calibration results may be biased due to sampling error in the Tennessee data base. The relatively large values of standard error of estimate for some of the constituent models, although representing significant reduction (at least 50 percent) in prediction error compared to estimation with unadjusted regional models, may be unacceptable for some applications. The user may wish to collect additional local data for these constituents and repeat the analysis, or calibrate an independent local regression model.

Verification of Satellite Rainfall Estimates from the Tropical Rainfall Measuring Mission over Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.; Silberstein, D. S.; Marks, D. M.; Pippitt, J. L.

2007-12-01

The Tropical Rainfall Measuring Mission's (TRMM) Ground Validation (GV) Program was originally established with the principal long-term goal of determining the random errors and systematic biases stemming from the application of the TRMM rainfall algorithms. The GV Program has been structured around two validation strategies: 1) determining the quantitative accuracy of the integrated monthly rainfall products at GV regional sites over large areas of about 500 km2 using integrated ground measurements and 2) evaluating the instantaneous satellite and GV rain rate statistics at spatio-temporal scales compatible with the satellite sensor resolution (Simpson et al. 1988, Thiele 1988). The GV Program has continued to evolve since the launch of the TRMM satellite on November 27, 1997. This presentation will discuss current GV methods of validating TRMM operational rain products in conjunction with ongoing research. The challenge facing TRMM GV has been how to best utilize rain information from the GV system to infer the random and systematic error characteristics of the satellite rain estimates. A fundamental problem of validating space-borne rain estimates is that the true mean areal rainfall is an ideal, scale-dependent parameter that cannot be directly measured. Empirical validation uses ground-based rain estimates to determine the error characteristics of the satellite-inferred rain estimates, but ground estimates also incur measurement errors and contribute to the error covariance. Furthermore, sampling errors, associated with the discrete, discontinuous temporal sampling by the rain sensors aboard the TRMM satellite, become statistically entangled in the monthly estimates. Sampling errors complicate the task of linking biases in the rain retrievals to the physics of the satellite algorithms. The TRMM Satellite Validation Office (TSVO) has made key progress towards effective satellite validation. For disentangling the sampling and retrieval errors, TSVO has developed and applied a methodology that statistically separates the two error sources. Using TRMM monthly estimates and high-resolution radar and gauge data, this method has been used to estimate sampling and retrieval error budgets over GV sites. More recently, a multi- year data set of instantaneous rain rates from the TRMM microwave imager (TMI), the precipitation radar (PR), and the combined algorithm was spatio-temporally matched and inter-compared to GV radar rain rates collected during satellite overpasses of select GV sites at the scale of the TMI footprint. The analysis provided a more direct probe of the satellite rain algorithms using ground data as an empirical reference. TSVO has also made significant advances in radar quality control through the development of the Relative Calibration Adjustment (RCA) technique. The RCA is currently being used to provide a long-term record of radar calibration for the radar at Kwajalein, a strategically important GV site in the tropical Pacific. The RCA technique has revealed previously undetected alterations in the radar sensitivity due to engineering changes (e.g., system modifications, antenna offsets, alterations of the receiver, or the data processor), making possible the correction of the radar rainfall measurements and ensuring the integrity of nearly a decade of TRMM GV observations and resources.

The effect of photometric redshift uncertainties on galaxy clustering and baryonic acoustic oscillations

NASA Astrophysics Data System (ADS)

Chaves-Montero, Jonás; Angulo, Raúl E.; Hernández-Monteagudo, Carlos

2018-07-01

In the upcoming era of high-precision galaxy surveys, it becomes necessary to understand the impact of redshift uncertainties on cosmological observables. In this paper we explore the effect of sub-percent photometric redshift errors (photo-z errors) on galaxy clustering and baryonic acoustic oscillations (BAOs). Using analytic expressions and results from 1000 N-body simulations, we show how photo-z errors modify the amplitude of moments of the 2D power spectrum, their variances, the amplitude of BAOs, and the cosmological information in them. We find that (a) photo-z errors suppress the clustering on small scales, increasing the relative importance of shot noise, and thus reducing the interval of scales available for BAO analyses; (b) photo-z errors decrease the smearing of BAOs due to non-linear redshift-space distortions (RSDs) by giving less weight to line-of-sight modes; and (c) photo-z errors (and small-scale RSD) induce a scale dependence on the information encoded in the BAO scale, and that reduces the constraining power on the Hubble parameter. Using these findings, we propose a template that extracts unbiased cosmological information from samples with photo-z errors with respect to cases without them. Finally, we provide analytic expressions to forecast the precision in measuring the BAO scale, showing that spectro-photometric surveys will measure the expansion history of the Universe with a precision competitive to that of spectroscopic surveys.

Error reporting in transfusion medicine at a tertiary care centre: a patient safety initiative.

PubMed

Elhence, Priti; Shenoy, Veena; Verma, Anupam; Sachan, Deepti

2012-11-01

Errors in the transfusion process can compromise patient safety. A study was undertaken at our center to identify the errors in the transfusion process and their causes in order to reduce their occurrence by corrective and preventive actions. All near miss, no harm events and adverse events reported in the 'transfusion process' during 1 year study period were recorded, classified and analyzed at a tertiary care teaching hospital in North India. In total, 285 transfusion related events were reported during the study period. Of these, there were four adverse (1.5%), 10 no harm (3.5%) and 271 (95%) near miss events. Incorrect blood component transfusion rate was 1 in 6031 component units. ABO incompatible transfusion rate was one in 15,077 component units issued or one in 26,200 PRBC units issued and acute hemolytic transfusion reaction due to ABO incompatible transfusion was 1 in 60,309 component units issued. Fifty-three percent of the antecedent near miss events were bedside events. Patient sample handling errors were the single largest category of errors (n=94, 33%) followed by errors in labeling and blood component handling and storage in user areas. The actual and near miss event data obtained through this initiative provided us with clear evidence about latent defects and critical points in the transfusion process so that corrective and preventive actions could be taken to reduce errors and improve transfusion safety.

The effect of photometric redshift uncertainties on galaxy clustering and baryonic acoustic oscillations

NASA Astrophysics Data System (ADS)

Chaves-Montero, Jonás; Angulo, Raúl E.; Hernández-Monteagudo, Carlos

2018-04-01

In the upcoming era of high-precision galaxy surveys, it becomes necessary to understand the impact of redshift uncertainties on cosmological observables. In this paper we explore the effect of sub-percent photometric redshift errors (photo-z errors) on galaxy clustering and baryonic acoustic oscillations (BAO). Using analytic expressions and results from 1 000 N-body simulations, we show how photo-z errors modify the amplitude of moments of the 2D power spectrum, their variances, the amplitude of BAO, and the cosmological information in them. We find that: a) photo-z errors suppress the clustering on small scales, increasing the relative importance of shot noise, and thus reducing the interval of scales available for BAO analyses; b) photo-z errors decrease the smearing of BAO due to non-linear redshift-space distortions (RSD) by giving less weight to line-of-sight modes; and c) photo-z errors (and small-scale RSD) induce a scale dependence on the information encoded in the BAO scale, and that reduces the constraining power on the Hubble parameter. Using these findings, we propose a template that extracts unbiased cosmological information from samples with photo-z errors with respect to cases without them. Finally, we provide analytic expressions to forecast the precision in measuring the BAO scale, showing that spectro-photometric surveys will measure the expansion history of the Universe with a precision competitive to that of spectroscopic surveys.

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…

On Time/Space Aggregation of Fine-Scale Error Estimates (Invited)

NASA Astrophysics Data System (ADS)

Huffman, G. J.

2013-12-01

Estimating errors inherent in fine time/space-scale satellite precipitation data sets is still an on-going problem and a key area of active research. Complicating features of these data sets include the intrinsic intermittency of the precipitation in space and time and the resulting highly skewed distribution of precipitation rates. Additional issues arise from the subsampling errors that satellites introduce, the errors due to retrieval algorithms, and the correlated error that retrieval and merger algorithms sometimes introduce. Several interesting approaches have been developed recently that appear to make progress on these long-standing issues. At the same time, the monthly averages over 2.5°x2.5° grid boxes in the Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) precipitation data set follow a very simple sampling-based error model (Huffman 1997) with coefficients that are set using coincident surface and GPCP SG data. This presentation outlines the unsolved problem of how to aggregate the fine-scale errors (discussed above) to an arbitrary time/space averaging volume for practical use in applications, reducing in the limit to simple Gaussian expressions at the monthly 2.5°x2.5° scale. Scatter diagrams with different time/space averaging show that the relationship between the satellite and validation data improves due to the reduction in random error. One of the key, and highly non-linear, issues is that fine-scale estimates tend to have large numbers of cases with points near the axes on the scatter diagram (one of the values is exactly or nearly zero, while the other value is higher). Averaging 'pulls' the points away from the axes and towards the 1:1 line, which usually happens for higher precipitation rates before lower rates. Given this qualitative observation of how aggregation affects error, we observe that existing aggregation rules, such as the Steiner et al. (2003) power law, only depend on the aggregated precipitation rate. Is this sufficient, or is it necessary to aggregate the precipitation error estimates across the time/space data cube used for averaging? At least for small time/space data cubes it would seem that the detailed variables that affect each precipitation error estimate in the aggregation, such as sensor type, land/ocean surface type, convective/stratiform type, and so on, drive variations that must be accounted for explicitly.

Effects of system net charge and electrostatic truncation on all-atom constant pH molecular dynamics.

PubMed

Chen, Wei; Shen, Jana K

2014-10-15

Constant pH molecular dynamics offers a means to rigorously study the effects of solution pH on dynamical processes. Here, we address two critical questions arising from the most recent developments of the all-atom continuous constant pH molecular dynamics (CpHMD) method: (1) What is the effect of spatial electrostatic truncation on the sampling of protonation states? (2) Is the enforcement of electrical neutrality necessary for constant pH simulations? We first examined how the generalized reaction field and force-shifting schemes modify the electrostatic forces on the titration coordinates. Free energy simulations of model compounds were then carried out to delineate the errors in the deprotonation free energy and salt-bridge stability due to electrostatic truncation and system net charge. Finally, CpHMD titration of a mini-protein HP36 was used to understand the manifestation of the two types of errors in the calculated pK(a) values. The major finding is that enforcing charge neutrality under all pH conditions and at all time via cotitrating ions significantly improves the accuracy of protonation-state sampling. We suggest that such finding is also relevant for simulations with particle mesh Ewald, considering the known artifacts due to charge-compensating background plasma. Copyright © 2014 Wiley Periodicals, Inc.

Effects of system net charge and electrostatic truncation on all-atom constant pH molecular dynamics †

PubMed Central

Chen, Wei; Shen, Jana K.

2014-01-01

Constant pH molecular dynamics offers a means to rigorously study the effects of solution pH on dynamical processes. Here we address two critical questions arising from the most recent developments of the all-atom continuous constant pH molecular dynamics (CpHMD) method: 1) What is the effect of spatial electrostatic truncation on the sampling of protonation states? 2) Is the enforcement of electrical neutrality necessary for constant pH simulations? We first examined how the generalized reaction field and force shifting schemes modify the electrostatic forces on the titration coordinates. Free energy simulations of model compounds were then carried out to delineate the errors in the deprotonation free energy and salt-bridge stability due to electrostatic truncation and system net charge. Finally, CpHMD titration of a mini-protein HP36 was used to understand the manifestation of the two types of errors in the calculated pK a values. The major finding is that enforcing charge neutrality under all pH conditions and at all time via co-titrating ions significantly improves the accuracy of protonation-state sampling. We suggest that such finding is also relevant for simulations with particle-mesh Ewald, considering the known artifacts due to charge-compensating background plasma. PMID:25142416

Frozen Section Evaluation of Margin Status in Primary Squamous Cell Carcinomas of the Head and Neck: A Correlation Study of Frozen Section and Final Diagnoses.

PubMed

Layfield, Eleanor M; Schmidt, Robert L; Esebua, Magda; Layfield, Lester J

2018-06-01

Frozen section is routinely used for intraoperative margin evaluation in carcinomas of the head and neck. We studied a series of frozen sections performed for margin status of head and neck tumors to determine diagnostic accuracy. All frozen sections for margin control of squamous carcinomas of the head and neck were studied from a 66 month period. Frozen and permanent section diagnoses were classified as negative or malignant. Correlation of diagnoses was performed to determine accuracy. One thousand seven hundred and ninety-six pairs of frozen section and corresponding permanent section diagnoses were obtained. Discordances were found in 55 (3.1%) pairs. In 35 pairs (1.9%), frozen section was reported as benign, but permanent sections disclosed carcinoma. In 21 cases, the discrepancy was due to sampling and in the remaining cases it was an interpretive error. In 20 cases (1.1%), frozen section was malignant, but the permanent section was interpreted as negative. Frozen section is an accurate method for evaluation of operative margins for head and neck carcinomas with concordance between frozen and permanent results of 97%. Most errors are false negative results with the majority of these being due to sampling issues.

A steep peripheral ring in irregular cornea topography, real or an instrument error?

PubMed

Galindo-Ferreiro, Alicia; Galvez-Ruiz, Alberto; Schellini, Silvana A; Galindo-Alonso, Julio

2016-01-01

To demonstrate that the steep peripheral ring (red zone) on corneal topography after myopic laser in situ keratomileusis (LASIK) could possibly due to instrument error and not always to a real increase in corneal curvature. A spherical model for the corneal surface and modifying topography software was used to analyze the cause of an error due to instrument design. This study involved modification of the software of a commercially available topographer. A small modification of the topography image results in a red zone on the corneal topography color map. Corneal modeling indicates that the red zone could be an artifact due to an instrument-induced error. The steep curvature changes after LASIK, signified by the red zone, could be also an error due to the plotting algorithms of the corneal topographer, besides a steep curvature change.

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.

Model Error Estimation for the CPTEC Eta Model

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; daSilva, Arlindo

1999-01-01

Statistical data assimilation systems require the specification of forecast and observation error statistics. Forecast error is due to model imperfections and differences between the initial condition and the actual state of the atmosphere. Practical four-dimensional variational (4D-Var) methods try to fit the forecast state to the observations and assume that the model error is negligible. Here with a number of simplifying assumption, a framework is developed for isolating the model error given the forecast error at two lead-times. Two definitions are proposed for the Talagrand ratio tau, the fraction of the forecast error due to model error rather than initial condition error. Data from the CPTEC Eta Model running operationally over South America are used to calculate forecast error statistics and lower bounds for tau.

On the selection of gantry and collimator angles for isocenter localization using Winston-Lutz tests.

PubMed

Du, Weiliang; Johnson, Jennifer L; Jiang, Wei; Kudchadker, Rajat J

2016-01-08

In Winston-Lutz (WL) tests, the isocenter of a linear accelerator (linac) is determined as the intersection of radiation central axes (CAX) from multiple gantry, collimator, and couch angles. It is well known that the CAX can wobble due to mechanical imperfections of the linac. Previous studies suggested that the wobble varies with gantry and collimator angles. Therefore, the isocenter determined in the WL tests has a profound dependence on the gantry and collimator angles at which CAX are sampled. In this study, we evaluated the systematic and random errors in the iso-centers determined with different CAX sampling schemes. Digital WL tests were performed on six linacs. For each WL test, 63 CAX were sampled at nine gantry angles and seven collimator angles. Subsets of these data were used to simulate the effects of various CAX sampling schemes. An isocenter was calculated from each subset of CAX and compared against the reference isocenter, which was calculated from 48 opposing CAX. The differences between the calculated isocenters and the reference isocenters ranged from 0 to 0.8 mm. The differences diminished to less than 0.2 mm when 24 or more CAX were sampled. Isocenters determined with collimator 0° were vertically lower than those determined with collimator 90° and 270°. Isocenter localization errors in the longitudinal direction (along the axis of gantry rotation) showed a strong dependence on the collimator angle selected. The errors in all directions were significantly reduced when opposing collimator angles and opposing gantry angles were employed. The isocenter localization errors were less than 0.2 mm with the common CAX sampling scheme, which used four cardinal gantry angles and two opposing collimator angles. Reproducibility stud-ies on one linac showed that the mean and maximum variations of CAX during the WL tests were 0.053 mm and 0.30 mm, respectively. The maximal variation in the resulting isocenters was 0.068 mm if 48 CAX were used, or 0.13 mm if four CAX were used. Quantitative results from this study are useful for understanding and minimizing the isocenter uncertainty in WL tests.

A general model for attitude determination error analysis

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Seidewitz, ED; Nicholson, Mark

1988-01-01

An overview is given of a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The models presented include both batch least-squares and sequential attitude estimation processes for both spin-stabilized and three-axis stabilized spacecraft. The discussion includes a brief description of a dynamics model of strapdown gyros, but it does not cover other sensor models. Model parameters can be chosen to be solve-for parameters, which are assumed to be estimated as part of the determination process, or consider parameters, which are assumed to have errors but not to be estimated. The only restriction on this choice is that the time evolution of the consider parameters must not depend on any of the solve-for parameters. The result of an error analysis is an indication of the contributions of the various error sources to the uncertainties in the determination of the spacecraft solve-for parameters. The model presented gives the uncertainty due to errors in the a priori estimates of the solve-for parameters, the uncertainty due to measurement noise, the uncertainty due to dynamic noise (also known as process noise or measurement noise), the uncertainty due to the consider parameters, and the overall uncertainty due to all these sources of error.

Prevalence of refractive errors in the Slovak population calculated using the Gullstrand schematic eye model.

PubMed

Popov, I; Valašková, J; Štefaničková, J; Krásnik, V

2017-01-01

A substantial part of the population suffers from some kind of refractive errors. It is envisaged that their prevalence may change with the development of society. The aim of this study is to determine the prevalence of refractive errors using calculations based on the Gullstrand schematic eye model. We used the Gullstrand schematic eye model to calculate refraction retrospectively. Refraction was presented as the need for glasses correction at a vertex distance of 12 mm. The necessary data was obtained using the optical biometer Lenstar LS900. Data which could not be obtained due to the limitations of the device was substituted by theoretical data from the Gullstrand schematic eye model. Only analyses from the right eyes were presented. The data was interpreted using descriptive statistics, Pearson correlation and t-test. The statistical tests were conducted at a level of significance of 5%. Our sample included 1663 patients (665 male, 998 female) within the age range of 19 to 96 years. Average age was 70.8 ± 9.53 years. Average refraction of the eye was 2.73 ± 2.13D (males 2.49 ± 2.34, females 2.90 ± 2.76). The mean absolute error from emmetropia was 3.01 ± 1.58 (males 2.83 ± 2.95, females 3.25 ± 3.35). 89.06% of the sample was hyperopic, 6.61% was myopic and 4.33% emmetropic. We did not find any correlation between refraction and age. Females were more hyperopic than males. We did not find any statistically significant hypermetopic shift of refraction with age. According to our estimation, the calculations of refractive errors using the Gullstrand schematic eye model showed a significant hypermetropic shift of more than +2D. Our results could be used in future for comparing the prevalence of refractive errors using same methods we used.Key words: refractive errors, refraction, Gullstrand schematic eye model, population, emmetropia.

A broadband variable-temperature test system for complex permittivity measurements of solid and powder materials

NASA Astrophysics Data System (ADS)

Zhang, Yunpeng; Li, En; Zhang, Jing; Yu, Chengyong; Zheng, Hu; Guo, Gaofeng

2018-02-01

A microwave test system to measure the complex permittivity of solid and powder materials as a function of temperature has been developed. The system is based on a TM0n0 multi-mode cylindrical cavity with a slotting structure, which provides purer test modes compared to a traditional cavity. To ensure the safety, effectiveness, and longevity, heating and testing are carried out separately and the sample can move between two functional areas through an Alundum tube. Induction heating and a pneumatic platform are employed to, respectively, shorten the heating and cooling time of the sample. The single trigger function of the vector network analyzer is added to test software to suppress the drift of the resonance peak during testing. Complex permittivity is calculated by the rigorous field theoretical solution considering multilayer media loading. The variation of the cavity equivalent radius caused by the sample insertion holes is discussed in detail, and its influence to the test result is analyzed. The calibration method for the complex permittivity of the Alundum tube and quartz vial (for loading powder sample), which vary with the temperature, is given. The feasibility of the system has been verified by measuring different samples in a wide range of relative permittivity and loss tangent, and variable-temperature test results of fused quartz and SiO2 powder up to 1500 °C are compared with published data. The results indicate that the presented system is reliable and accurate. The stability of the system is verified by repeated and long-term tests, and error analysis is presented to estimate the error incurred due to the uncertainties in different error sources.

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor.

PubMed

Biagi, Lyvia; Ramkissoon, Charrise M; Facchinetti, Andrea; Leal, Yenny; Vehi, Josep

2017-06-12

Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor.

Super-global distortion correction for a rotational C-arm x-ray image intensifier.

PubMed

Liu, R R; Rudin, S; Bednarek, D R

1999-09-01

Image intensifier (II) distortion changes as a function of C-arm rotation angle because of changes in the orientation of the II with the earth's or other stray magnetic fields. For cone-beam computed tomography (CT), distortion correction for all angles is essential. The new super-global distortion correction consists of a model to continuously correct II distortion not only at each location in the image but for every rotational angle of the C arm. Calibration bead images were acquired with a standard C arm in 9 in. II mode. The super-global (SG) model is obtained from the single-plane global correction of the selected calibration images with given sampling angle interval. The fifth-order single-plane global corrections yielded a residual rms error of 0.20 pixels, while the SG model yielded a rms error of 0.21 pixels, a negligibly small difference. We evaluated the accuracy dependence of the SG model on various factors, such as the single-plane global fitting order, SG order, and angular sampling interval. We found that a good SG model can be obtained using a sixth-order SG polynomial fit based on the fifth-order single-plane global correction, and that a 10 degrees sampling interval was sufficient. Thus, the SG model saves processing resources and storage space. The residual errors from the mechanical errors of the x-ray system were also investigated, and found comparable with the SG residual error. Additionally, a single-plane global correction was done in the cylindrical coordinate system, and physical information about pincushion distortion and S distortion were observed and analyzed; however, this method is not recommended due to a lack of calculational efficiency. In conclusion, the SG model provides an accurate, fast, and simple correction for rotational C-arm images, which may be used for cone-beam CT.

Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Radiances

NASA Technical Reports Server (NTRS)

Hoffman, Matthew J.; Eluszkiewicz, Janusz; Weisenstein, Deborah; Uymin, Gennady; Moncet, Jean-Luc

2012-01-01

Motivated by the needs of Mars data assimilation. particularly quantification of measurement errors and generation of averaging kernels. we have evaluated atmospheric temperature retrievals from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) radiances. Multiple sets of retrievals have been considered in this study; (1) retrievals available from the Planetary Data System (PDS), (2) retrievals based on variants of the retrieval algorithm used to generate the PDS retrievals, and (3) retrievals produced using the Mars 1-Dimensional Retrieval (M1R) algorithm based on the Optimal Spectral Sampling (OSS ) forward model. The retrieved temperature profiles are compared to the MGS Radio Science (RS) temperature profiles. For the samples tested, the M1R temperature profiles can be made to agree within 2 K with the RS temperature profiles, but only after tuning the prior and error statistics. Use of a global prior that does not take into account the seasonal dependence leads errors of up 6 K. In polar samples. errors relative to the RS temperature profiles are even larger. In these samples, the PDS temperature profiles also exhibit a poor fit with RS temperatures. This fit is worse than reported in previous studies, indicating that the lack of fit is due to a bias correction to TES radiances implemented after 2004. To explain the differences between the PDS and Ml R temperatures, the algorithms are compared directly, with the OSS forward model inserted into the PDS algorithm. Factors such as the filtering parameter, the use of linear versus nonlinear constrained inversion, and the choice of the forward model, are found to contribute heavily to the differences in the temperature profiles retrieved in the polar regions, resulting in uncertainties of up to 6 K. Even outside the poles, changes in the a priori statistics result in different profile shapes which all fit the radiances within the specified error. The importance of the a priori statistics prevents reliable global retrievals based a single a priori and strongly implies that a robust science analysis must instead rely on retrievals employing localized a priori information, for example from an ensemble based data assimilation system such as the Local Ensemble Transform Kalman Filter (LETKF).

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...

Precision rectifier detectors for ac resistance bridge measurements with application to temperature control systems for irradiation creep experiments

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

Duncan, M. G.

The suitability of several temperature measurement schemes for an irradiation creep experiment is examined. It is found that the specimen resistance can be used to measure and control the sample temperature if compensated for resistance drift due to radiation and annealing effects. A modified Kelvin bridge is presented that allows compensation for resistance drift by periodically checking the sample resistance at a controlled ambient temperature. A new phase-insensitive method for detecting the bridge error signals is presented. The phase-insensitive detector is formed by averaging the magnitude of two bridge voltages. Although this method is substantially less sensitive to stray reactancesmore » in the bridge than conventional phase-sensitive detectors, it is sensitive to gain stability and linearity of the rectifier circuits. Accuracy limitations of rectifier circuits are examined both theoretically and experimentally in great detail. Both hand analyses and computer simulations of rectifier errors are presented. Finally, the design of a temperature control system based on sample resistance measurement is presented. The prototype is shown to control a 316 stainless steel sample to within a 0.15/sup 0/C short term (10 sec) and a 0.03/sup 0/C long term (10 min) standard deviation at temperatures between 150 and 700/sup 0/C. The phase-insensitive detector typically contributes less than 10 ppM peak resistance measurement error (0.04/sup 0/C at 700/sup 0/C for 316 stainless steel or 0.005/sup 0/C at 150/sup 0/C for zirconium).« less

Validation of prostate-specific antigen laboratory values recorded in Surveillance, Epidemiology, and End Results registries.

PubMed

Adamo, Margaret Peggy; Boten, Jessica A; Coyle, Linda M; Cronin, Kathleen A; Lam, Clara J K; Negoita, Serban; Penberthy, Lynne; Stevens, Jennifer L; Ward, Kevin C

2017-02-15

Researchers have used prostate-specific antigen (PSA) values collected by central cancer registries to evaluate tumors for potential aggressive clinical disease. An independent study collecting PSA values suggested a high error rate (18%) related to implied decimal points. To evaluate the error rate in the Surveillance, Epidemiology, and End Results (SEER) program, a comprehensive review of PSA values recorded across all SEER registries was performed. Consolidated PSA values for eligible prostate cancer cases in SEER registries were reviewed and compared with text documentation from abstracted records. Four types of classification errors were identified: implied decimal point errors, abstraction or coding implementation errors, nonsignificant errors, and changes related to "unknown" values. A total of 50,277 prostate cancer cases diagnosed in 2012 were reviewed. Approximately 94.15% of cases did not have meaningful changes (85.85% correct, 5.58% with a nonsignificant change of <1 ng/mL, and 2.80% with no clinical change). Approximately 5.70% of cases had meaningful changes (1.93% due to implied decimal point errors, 1.54% due to abstract or coding errors, and 2.23% due to errors related to unknown categories). Only 419 of the original 50,277 cases (0.83%) resulted in a change in disease stage due to a corrected PSA value. The implied decimal error rate was only 1.93% of all cases in the current validation study, with a meaningful error rate of 5.81%. The reasons for the lower error rate in SEER are likely due to ongoing and rigorous quality control and visual editing processes by the central registries. The SEER program currently is reviewing and correcting PSA values back to 2004 and will re-release these data in the public use research file. Cancer 2017;123:697-703. © 2016 American Cancer Society. © 2016 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

A crowdsourcing workflow for extracting chemical-induced disease relations from free text

PubMed Central

Li, Tong Shu; Bravo, Àlex; Furlong, Laura I.; Good, Benjamin M.; Su, Andrew I.

2016-01-01

Relations between chemicals and diseases are one of the most queried biomedical interactions. Although expert manual curation is the standard method for extracting these relations from the literature, it is expensive and impractical to apply to large numbers of documents, and therefore alternative methods are required. We describe here a crowdsourcing workflow for extracting chemical-induced disease relations from free text as part of the BioCreative V Chemical Disease Relation challenge. Five non-expert workers on the CrowdFlower platform were shown each potential chemical-induced disease relation highlighted in the original source text and asked to make binary judgments about whether the text supported the relation. Worker responses were aggregated through voting, and relations receiving four or more votes were predicted as true. On the official evaluation dataset of 500 PubMed abstracts, the crowd attained a 0.505 F-score (0.475 precision, 0.540 recall), with a maximum theoretical recall of 0.751 due to errors with named entity recognition. The total crowdsourcing cost was $1290.67 ($2.58 per abstract) and took a total of 7 h. A qualitative error analysis revealed that 46.66% of sampled errors were due to task limitations and gold standard errors, indicating that performance can still be improved. All code and results are publicly available at https://github.com/SuLab/crowd_cid_relex Database URL: https://github.com/SuLab/crowd_cid_relex PMID:27087308

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

A device for high-throughput monitoring of degradation in soft tissue samples.

PubMed

Tzeranis, D S; Panagiotopoulos, I; Gkouma, S; Kanakaris, G; Georgiou, N; Vaindirlis, N; Vasileiou, G; Neidlin, M; Gkousioudi, A; Spitas, V; Macheras, G A; Alexopoulos, L G

2018-06-06

This work describes the design and validation of a novel device, the High-Throughput Degradation Monitoring Device (HDD), for monitoring the degradation of 24 soft tissue samples over incubation periods of several days inside a cell culture incubator. The device quantifies sample degradation by monitoring its deformation induced by a static gravity load. Initial instrument design and experimental protocol development focused on quantifying cartilage degeneration. Characterization of measurement errors, caused mainly by thermal transients and by translating the instrument sensor, demonstrated that HDD can quantify sample degradation with <6 μm precision and <10 μm temperature-induced errors. HDD capabilities were evaluated in a pilot study that monitored the degradation of fresh ex vivo human cartilage samples by collagenase solutions over three days. HDD could robustly resolve the effects of collagenase concentration as small as 0.5 mg/ml. Careful sample preparation resulted in measurements that did not suffer from donor-to-donor variation (coefficient of variance <70%). Due to its unique combination of sample throughput, measurement precision, temporal sampling and experimental versality, HDD provides a novel biomechanics-based experimental platform for quantifying the effects of proteins (cytokines, growth factors, enzymes, antibodies) or small molecules on the degradation of soft tissues or tissue engineering constructs. Thereby, HDD can complement established tools and in vitro models in important applications including drug screening and biomaterial development. Copyright © 2018 Elsevier Ltd. All rights reserved.

Performance of concatenated Reed-Solomon/Viterbi channel coding

NASA Technical Reports Server (NTRS)

Divsalar, D.; Yuen, J. H.

1982-01-01

The concatenated Reed-Solomon (RS)/Viterbi coding system is reviewed. The performance of the system is analyzed and results are derived with a new simple approach. A functional model for the input RS symbol error probability is presented. Based on this new functional model, we compute the performance of a concatenated system in terms of RS word error probability, output RS symbol error probability, bit error probability due to decoding failure, and bit error probability due to decoding error. Finally we analyze the effects of the noisy carrier reference and the slow fading on the system performance.

Black hole masses in active galactic nuclei

NASA Astrophysics Data System (ADS)

Denney, Kelly D.

2010-11-01

We present the complete results from two, high sampling-rate, multi-month, spectrophotometric reverberation mapping campaigns undertaken to obtain either new or improved Hbeta reverberation lag measurements for several relatively low-luminosity active galactic nuclei (AGNs). We have reliably measured the time delay between variations in the continuum and Hbeta emission line in seven local Seyfert 1 galaxies. These measurements are used to calculate the mass of the supermassive black hole at the center of each of these AGNs. We place our results in context to the most current calibration of the broad-line region (BLR) RBLR-L relationship, where our results remove many outliers and significantly reduce the scatter at the low-luminosity end of this relationship. A detailed analysis of the data from our high sampling rate, multi-month reverberation mapping campaign in 2007 reveals that the Hbeta emission region within the BLRs of several nearby AGNs exhibit a variety of kinematic behaviors. Through a velocity-resolved reverberation analysis of the broad Hbeta emission-line flux variations in our sample, we reconstruct velocity-resolved kinematic signals for our entire sample and clearly see evidence for outflowing, infalling, and virialized BLR gas motions in NGC 3227, NGC 3516, and NGC 5548, respectively. Finally, we explore the nature of systematic errors that can arise in measurements of black hole masses from single-epoch spectra of AGNs by utilizing the many epochs available for NGC 5548 and PG1229+204 from reverberation mapping databases. In particular, we examine systematics due to AGN variability, contamination due to constant spectral components (i.e., narrow lines and host galaxy flux), data quality (i.e., signal-to-noise ratio, S/N), and blending of spectral features. We investigate the effect that each of these systematics has on the precision and accuracy of single-epoch masses calculated from two commonly-used line-width measures by comparing these results to recent reverberation mapping studies. We then present an error budget which summarizes the minimum observable uncertainties as well as the amount of additional scatter and/or systematic offset that can be expected from the individual sources of error investigated.

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.

Automatic alignment for three-dimensional tomographic reconstruction

NASA Astrophysics Data System (ADS)

van Leeuwen, Tristan; Maretzke, Simon; Joost Batenburg, K.

2018-02-01

In tomographic reconstruction, the goal is to reconstruct an unknown object from a collection of line integrals. Given a complete sampling of such line integrals for various angles and directions, explicit inverse formulas exist to reconstruct the object. Given noisy and incomplete measurements, the inverse problem is typically solved through a regularized least-squares approach. A challenge for both approaches is that in practice the exact directions and offsets of the x-rays are only known approximately due to, e.g. calibration errors. Such errors lead to artifacts in the reconstructed image. In the case of sufficient sampling and geometrically simple misalignment, the measurements can be corrected by exploiting so-called consistency conditions. In other cases, such conditions may not apply and we have to solve an additional inverse problem to retrieve the angles and shifts. In this paper we propose a general algorithmic framework for retrieving these parameters in conjunction with an algebraic reconstruction technique. The proposed approach is illustrated by numerical examples for both simulated data and an electron tomography dataset.

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.

A Bayesian approach to model structural error and input variability in groundwater modeling

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Lin, Y. F. F.; Liang, F.

2015-12-01

Effective water resource management typically relies on numerical models to analyze groundwater flow and solute transport processes. Model structural error (due to simplification and/or misrepresentation of the "true" environmental system) and input forcing variability (which commonly arises since some inputs are uncontrolled or estimated with high uncertainty) are ubiquitous in groundwater models. Calibration that overlooks errors in model structure and input data can lead to biased parameter estimates and compromised predictions. We present a fully Bayesian approach for a complete assessment of uncertainty for spatially distributed groundwater models. The approach explicitly recognizes stochastic input and uses data-driven error models based on nonparametric kernel methods to account for model structural error. We employ exploratory data analysis to assist in specifying informative prior for error models to improve identifiability. The inference is facilitated by an efficient sampling algorithm based on DREAM-ZS and a parameter subspace multiple-try strategy to reduce the required number of forward simulations of the groundwater model. We demonstrate the Bayesian approach through a synthetic case study of surface-ground water interaction under changing pumping conditions. It is found that explicit treatment of errors in model structure and input data (groundwater pumping rate) has substantial impact on the posterior distribution of groundwater model parameters. Using error models reduces predictive bias caused by parameter compensation. In addition, input variability increases parametric and predictive uncertainty. The Bayesian approach allows for a comparison among the contributions from various error sources, which could inform future model improvement and data collection efforts on how to best direct resources towards reducing predictive uncertainty.

Counting OCR errors in typeset text

NASA Astrophysics Data System (ADS)

Sandberg, Jonathan S.

1995-03-01

Frequently object recognition accuracy is a key component in the performance analysis of pattern matching systems. In the past three years, the results of numerous excellent and rigorous studies of OCR system typeset-character accuracy (henceforth OCR accuracy) have been published, encouraging performance comparisons between a variety of OCR products and technologies. These published figures are important; OCR vendor advertisements in the popular trade magazines lead readers to believe that published OCR accuracy figures effect market share in the lucrative OCR market. Curiously, a detailed review of many of these OCR error occurrence counting results reveals that they are not reproducible as published and they are not strictly comparable due to larger variances in the counts than would be expected by the sampling variance. Naturally, since OCR accuracy is based on a ratio of the number of OCR errors over the size of the text searched for errors, imprecise OCR error accounting leads to similar imprecision in OCR accuracy. Some published papers use informal, non-automatic, or intuitively correct OCR error accounting. Still other published results present OCR error accounting methods based on string matching algorithms such as dynamic programming using Levenshtein (edit) distance but omit critical implementation details (such as the existence of suspect markers in the OCR generated output or the weights used in the dynamic programming minimization procedure). The problem with not specifically revealing the accounting method is that the number of errors found by different methods are significantly different. This paper identifies the basic accounting methods used to measure OCR errors in typeset text and offers an evaluation and comparison of the various accounting methods.

[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.

Atmospheric fossil fuel CO2 traced by 14CO2 and air quality index pollutant observations in Beijing and Xiamen, China.

PubMed

Niu, Zhenchuan; Zhou, Weijian; Feng, Xue; Feng, Tian; Wu, Shugang; Cheng, Peng; Lu, Xuefeng; Du, Hua; Xiong, Xiaohu; Fu, Yunchong

2018-06-01

Radiocarbon ( 14 C) is the most accurate tracer available for quantifying atmospheric CO 2 derived from fossil fuel (CO 2ff ), but it is expensive and time-consuming to measure. Here, we used common hourly Air Quality Index (AQI) pollutants (AQI, PM 2.5 , PM 10 , and CO) to indirectly trace diurnal CO 2ff variations during certain days at the urban sites in Beijing and Xiamen, China, based on linear relationships between AQI pollutants and CO 2ff traced by 14 C ([Formula: see text]) for semimonthly samples obtained in 2014. We validated these indirectly traced CO 2ff (CO 2ff-in ) concentrations against [Formula: see text] concentrations traced by simultaneous diurnal 14 CO 2 observations. Significant (p < 0.05) strong correlations were observed between each of the separate AQI pollutants and [Formula: see text] for the semimonthly samples. Diurnal variations in CO 2ff traced by each of the AQI pollutants generally showed similar trends to those of [Formula: see text], with high agreement at the sampling site in Beijing and relatively poor agreement at the sampling site in Xiamen. AQI pollutant tracers showed high normalized root-mean-square (NRMS) errors for the summer diurnal samples due to low [Formula: see text] concentrations. After the removal of these summer samples, the NRMS errors for AQI pollutant tracers were in the range of 31.6-64.2%. CO generally showed a high agreement and low NRMS errors among these indirect tracers. Based on these linear relationships, monthly CO 2ff averages at the sampling sites in Beijing and Xiamen were traced using CO concentration as a tracer. The monthly CO 2ff averages at the Beijing site showed a shallow U-type variation. These results indicate that CO can be used to trace CO 2ff variations in Chinese cities with CO 2ff concentrations above 5 ppm.

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.

Prevalence of vision impairment and refractive error in school children in Ba Ria – Vung Tau province, Vietnam

PubMed Central

Paudel, Prakash; Ramson, Prasidh; Naduvilath, Thomas; Wilson, David; Phuong, Ha Thanh; Ho, Suit M; Giap, Nguyen V

2014-01-01

Background To assess the prevalence of vision impairment and refractive error in school children 12–15 years of age in Ba Ria – Vung Tau province, Vietnam. Design Prospective, cross-sectional study. Participants 2238 secondary school children. Methods Subjects were selected based on stratified multistage cluster sampling of 13 secondary schools from urban, rural and semi-urban areas. The examination included visual acuity measurements, ocular motility evaluation, cycloplegic autorefraction, and examination of the external eye, anterior segment, media and fundus. Main Outcome Measures Visual acuity and principal cause of vision impairment. Results The prevalence of uncorrected and presenting visual acuity ≤6/12 in the better eye were 19.4% (95% confidence interval, 12.5–26.3) and 12.2% (95% confidence interval, 8.8–15.6), respectively. Refractive error was the cause of vision impairment in 92.7%, amblyopia in 2.2%, cataract in 0.7%, retinal disorders in 0.4%, other causes in 1.5% and unexplained causes in the remaining 2.6%. The prevalence of vision impairment due to myopia in either eye (–0.50 diopter or greater) was 20.4% (95% confidence interval, 12.8–28.0), hyperopia (≥2.00 D) was 0.4% (95% confidence interval, 0.0–0.7) and emmetropia with astigmatism (≥0.75 D) was 0.7% (95% confidence interval, 0.2–1.2). Vision impairment due to myopia was associated with higher school grade and increased time spent reading and working on a computer. Conclusions Uncorrected refractive error, particularly myopia, among secondary school children in Vietnam is a major public health problem. School-based eye health initiative such as refractive error screening is warranted to reduce vision impairment. PMID:24299145

Prevalence of vision impairment and refractive error in school children in Ba Ria - Vung Tau province, Vietnam.

PubMed

Paudel, Prakash; Ramson, Prasidh; Naduvilath, Thomas; Wilson, David; Phuong, Ha Thanh; Ho, Suit M; Giap, Nguyen V

2014-04-01

To assess the prevalence of vision impairment and refractive error in school children 12-15 years of age in Ba Ria - Vung Tau province, Vietnam. Prospective, cross-sectional study. 2238 secondary school children. Subjects were selected based on stratified multistage cluster sampling of 13 secondary schools from urban, rural and semi-urban areas. The examination included visual acuity measurements, ocular motility evaluation, cycloplegic autorefraction, and examination of the external eye, anterior segment, media and fundus. Visual acuity and principal cause of vision impairment. The prevalence of uncorrected and presenting visual acuity ≤6/12 in the better eye were 19.4% (95% confidence interval, 12.5-26.3) and 12.2% (95% confidence interval, 8.8-15.6), respectively. Refractive error was the cause of vision impairment in 92.7%, amblyopia in 2.2%, cataract in 0.7%, retinal disorders in 0.4%, other causes in 1.5% and unexplained causes in the remaining 2.6%. The prevalence of vision impairment due to myopia in either eye (-0.50 diopter or greater) was 20.4% (95% confidence interval, 12.8-28.0), hyperopia (≥2.00 D) was 0.4% (95% confidence interval, 0.0-0.7) and emmetropia with astigmatism (≥0.75 D) was 0.7% (95% confidence interval, 0.2-1.2). Vision impairment due to myopia was associated with higher school grade and increased time spent reading and working on a computer. Uncorrected refractive error, particularly myopia, among secondary school children in Vietnam is a major public health problem. School-based eye health initiative such as refractive error screening is warranted to reduce vision impairment. © 2013 The Authors. Clinical & Experimental Ophthalmology published by Wiley Publishing Asia Pty Ltd on behalf of Royal Australian and New Zealand College of Ophthalmologists.

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...

[The German promille law--overview and guideline for legal traffic applications].

PubMed

Grohmann, P

1996-07-01

1. The alcohol level regulation affects everyone who participates in public road, rail, shipping and air traffic. In legal terms a person participating in traffic is anyone who has a direct, physical influence on the traffic flow i.e. as a pedestrian, a vehicle driver, an aircraft captain or a train driver. Participation in any kind of traffic requires a physical, mental and psychological joint effort which is controlled by the central nervous system. The influence of alcohol drastically deteriorates driver performance to the detritment of traffic safety. In cases of traffic law determination of dangerous driving or in cases of the legal limitations of diminished or no responsibility, recognised discoveries in traffic medicine as well as blood alcohol research, psychiatry and statistics have played a significant role. The main medical-scientific used to determine the alcohol level regulation, in particular the borderline cases, essentially rely on on experiments (mainly driving experiments). These experiments are carried out with drivers under the influence of alcohol and who drive road vehicles, particularly motor vehicles. At present, no comparable, scientifically convincing research is available for the other groups of participants in traffic. Therefore, the determination of a universal alcohol level regulation including pedestrians and train drivers for example, can not be justified. Blood alcohol effect has been thoroughly researched, the metabolic reaction is well known, alcohol is easily quantifiable, its effect can be easily reviewed and is reproducible to a large extent. Therefore, due to existence of certain alcohol level values, legal conclusions can be drawn which affect all participants in traffic. The main issue is, that the blood alcohol level taken at the time of the accident is definite, regardless whether it was taken by means by a blood sample or by means of a statement of the amount of alcohol consumed. Whether or not the driving under the influence of alcohol falls under the category of "infringement of the law" or "criminal offence" depends largely on the abstract danger caused to the traffic. According to section 316 StGB a motorized or non-motorized driver under the influence of alcohol is considered to be unsafe if he/she is incapable of driving the vehicle safely for a long span of time or when sudden difficulties arise. It would apply if the alcohol has caused a personality change which would not enable the driver to drive safely despite wilfully trying. This applies respectively to drivers of vehicles that don't circulate on roads. 2. Currently, the following alcohol limit regulation applied in Germany: Criminal offences section 316, section 315 c section 1 no. 1 a StGB 1. Drivers of motor vehicles on the road--0.3 to 1.09/1000 and an additional error to due the consumption of alcohol--1.10/1000 (including the body's alcohol resorption effect) and more, with or without errors due to the consumption of alcohol. 2. Cyclists--0.3 to 1.59/1000 and an additional error due to the consumption of alcohol--1.60/1000 (including the body's resorption effect) and more, with oder without error due to the consumption of alcohol. 3. Carriage drivers, motorized wheelchair users--0.3/1000 and more and an additional error due to the consumption of alcohol. Section 316, Section 315 StGB 4. Train drivers, airplane pilots and persons in charge of ships--0.3/1000 and more and an additional error due to the consumption of alcohol. Author's opinion: airplane pilots, from 0.1/1000 even without an error due to the consumption of alcohol. Infringement of the law section 24 StVG--0.80 (including body's alcohol resorption effect) to 1.09/1000 without error due to the comsumption of alcohol. Sections 2, 69 a section 1 no. 1 StVZO pedestrians with or without special means of transport, animal leaders/animal drovers, pillion rider or passenger on a motor-bike--0.3/1000 and more and an additional error due to the consumption of alc

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.

Fine needle aspiration cytology of oral and oropharyngeal lesions with an emphasis on the diagnostic utility and pitfalls.

PubMed

Gupta, Nalini; Banik, Tarak; Rajwanshi, Arvind; Radotra, Bishan D; Panda, Naresh; Dey, Pranab; Srinivasan, Radhika; Nijhawan, Raje

2012-01-01

This study was undertaken to evaluate the diagnostic utility and pitfalls of fine needle aspiration cytology (FNAC) in oral and oropharyngeal lesions. This was a retrospective audit of oral and oropharyngeal lesions diagnosed with FNAC over a period of six years (2005-2010). Oral/oropharyngeal lesions [n=157] comprised 0.35% of the total FNAC load. The age ranged 1-80 years with the male: female ratio being 1.4:1. Aspirates were inadequate in 7% cases. Histopathology was available in 73/157 (46.5%) cases. Palate was the most common site of involvement [n=66] followed by tongue [n=35], buccal mucosa [n=18], floor of the mouth [n=17], tonsil [n=10], alveolus [n=5], retromolar trigone [n=3], and posterior pharyngeal wall [n=3]. Cytodiagnoses were categorized into infective/inflammatory lesions and benign cysts, and benign and malignant tumours. Uncommon lesions included ectopic lingual thyroid and adult rhabdomyoma of tongue, and solitary fibrous tumor (SFT), and leiomyosarcoma in buccal mucosa. A single false-positive case was dense inflammation with squamous cells misinterpreted as squamous cell carcinoma (SCC) on cytology. There were eight false-negative cases mainly due to sampling error. One false-negative case due to interpretation error was in a salivary gland tumor. The sensitivity of FNAC in diagnosing oral/oropharyngeal lesions was 71.4%; specificity was 97.8% with diagnostic accuracy of 87.7%. Salivary gland tumors and squamous cell carcinoma (SCC) are the most common lesions seen in the oral cavity. FNAC proves to be highly effective in diagnosing the spectrum of different lesions in this region. Sampling error is the main cause of false-negative cases in this region.

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.

Satellite telemetry: performance of animal-tracking systems

USGS Publications Warehouse

Keating, Kim A.; Brewster, Wayne G.; Key, Carl H.

1991-01-01

t: We used 10 Telonics ST-3 platform transmitter terminals (PTT's) configured for wolves and ungulates to examine the performance of the Argos satellite telemetry system. Under near-optimal conditions, 68 percentile errors for location qualities (NQ) 1, 2, and 3 were 1,188, 903, and 361 m, respectively. Errors (rE) exceeded expected values for NQ = 2 and 3, varied greatly among PTT's, increased as the difference (HE) between the estimated and actual PTT elevations increased, and were correlated nonlinearly with maximum satellite pass height (P,). We present a model of the relationships among rE, HE, and PH. Errors were bimodally distributed along the east-west axis and tended to occur away from the satellite when HE was positive. A southeasterly bias increased with HE, probably due to the particular distribution of satellite passes and effects of HE on rE. Under near-optimal conditions, 21 sensor message was received for up to 64% of available (PH, 50) satellite passes, and a location (NQ 2 1) was calculated for up to 63% of such passes. Sampling frequencies of sensor and location data declined 13 and 70%, respectively, for PTT's in a valley bottom and 65 and 86%, respectively, for PTT's on animals that were in valley bottoms. Sampling frequencies were greater for ungulate than for wolf collars.

Triangulation Error Analysis for the Barium Ion Cloud Experiment. M.S. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Long, S. A. T.

1973-01-01

The triangulation method developed specifically for the Barium Ion Cloud Project is discussed. Expression for the four displacement errors, the three slope errors, and the curvature error in the triangulation solution due to a probable error in the lines-of-sight from the observation stations to points on the cloud are derived. The triangulation method is then used to determine the effect of the following on these different errors in the solution: the number and location of the stations, the observation duration, east-west cloud drift, the number of input data points, and the addition of extra cameras to one of the stations. The pointing displacement errors, and the pointing slope errors are compared. The displacement errors in the solution due to a probable error in the position of a moving station plus the weighting factors for the data from the moving station are also determined.

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.

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.

Efficient Solar Scene Wavefront Estimation with Reduced Systematic and RMS Errors: Summary

NASA Astrophysics Data System (ADS)

Anugu, N.; Garcia, P.

2016-04-01

Wave front sensing for solar telescopes is commonly implemented with the Shack-Hartmann sensors. Correlation algorithms are usually used to estimate the extended scene Shack-Hartmann sub-aperture image shifts or slopes. The image shift is computed by correlating a reference sub-aperture image with the target distorted sub-aperture image. The pixel position where the maximum correlation is located gives the image shift in integer pixel coordinates. Sub-pixel precision image shifts are computed by applying a peak-finding algorithm to the correlation peak Poyneer (2003); Löfdahl (2010). However, the peak-finding algorithm results are usually biased towards the integer pixels, these errors are called as systematic bias errors Sjödahl (1994). These errors are caused due to the low pixel sampling of the images. The amplitude of these errors depends on the type of correlation algorithm and the type of peak-finding algorithm being used. To study the systematic errors in detail, solar sub-aperture synthetic images are constructed by using a Swedish Solar Telescope solar granulation image1. The performance of cross-correlation algorithm in combination with different peak-finding algorithms is investigated. The studied peak-finding algorithms are: parabola Poyneer (2003); quadratic polynomial Löfdahl (2010); threshold center of gravity Bailey (2003); Gaussian Nobach & Honkanen (2005) and Pyramid Bailey (2003). The systematic error study reveals that that the pyramid fit is the most robust to pixel locking effects. The RMS error analysis study reveals that the threshold centre of gravity behaves better in low SNR, although the systematic errors in the measurement are large. It is found that no algorithm is best for both the systematic and the RMS error reduction. To overcome the above problem, a new solution is proposed. In this solution, the image sampling is increased prior to the actual correlation matching. The method is realized in two steps to improve its computational efficiency. In the first step, the cross-correlation is implemented at the original image spatial resolution grid (1 pixel). In the second step, the cross-correlation is performed using a sub-pixel level grid by limiting the field of search to 4 × 4 pixels centered at the first step delivered initial position. The generation of these sub-pixel grid based region of interest images is achieved with the bi-cubic interpolation. The correlation matching with sub-pixel grid technique was previously reported in electronic speckle photography Sjö'dahl (1994). This technique is applied here for the solar wavefront sensing. A large dynamic range and a better accuracy in the measurements are achieved with the combination of the original pixel grid based correlation matching in a large field of view and a sub-pixel interpolated image grid based correlation matching within a small field of view. The results revealed that the proposed method outperforms all the different peak-finding algorithms studied in the first approach. It reduces both the systematic error and the RMS error by a factor of 5 (i.e., 75% systematic error reduction), when 5 times improved image sampling was used. This measurement is achieved at the expense of twice the computational cost. With the 5 times improved image sampling, the wave front accuracy is increased by a factor of 5. The proposed solution is strongly recommended for wave front sensing in the solar telescopes, particularly, for measuring large dynamic image shifts involved open loop adaptive optics. Also, by choosing an appropriate increment of image sampling in trade-off between the computational speed limitation and the aimed sub-pixel image shift accuracy, it can be employed in closed loop adaptive optics. The study is extended to three other class of sub-aperture images (a point source; a laser guide star; a Galactic Center extended scene). The results are planned to submit for the Optical Express journal.

Prevalence of refractive errors among school children in gondar town, northwest ethiopia.

PubMed

Yared, Assefa Wolde; Belaynew, Wasie Taye; Destaye, Shiferaw; Ayanaw, Tsegaw; Zelalem, Eshete

2012-10-01

Many children with poor vision due to refractive error remain undiagnosed and perform poorly in school. The situation is worse in the Sub-Saharan Africa, including Ethiopia, and current information is lacking. The objective of this study is to determine the prevalence of refractive error among children enrolled in elementary schools in Gondar town, Ethiopia. This was a cross-sectional study of 1852 students in 8 elementary schools. Subjects were selected by multistage random sampling. The study parameters were visual acuity (VA) evaluation and ocular examination. VA was measured by staff optometrists with the Snellen E-chart while students with subnormal vision were examined using pinhole, retinoscopy evaluation and subjective refraction by ophthalmologists. The study cohort was comprised of 45.8% males and 54.2% females from 8 randomly selected elementary schools with a response rate of 93%. Refractive errors in either eye were present in 174 (9.4%) children. Of these, myopia was diagnosed in 55 (31.6%) children in the right and left eyes followed by hyperopia in 46 (26.4%) and 39 (22.4%) in the right and left eyes respectively. Low myopia was the most common refractive error in 61 (49.2%) and 68 (50%) children for the right and left eyes respectively. Refractive error among children is a common problem in Gondar town and needs to be assessed at every health evaluation of school children for timely treatment.

Comparing errors in ED computer-assisted vs conventional pediatric drug dosing and administration.

PubMed

Yamamoto, Loren; Kanemori, Joan

2010-06-01

Compared to fixed-dose single-vial drug administration in adults, pediatric drug dosing and administration requires a series of calculations, all of which are potentially error prone. The purpose of this study is to compare error rates and task completion times for common pediatric medication scenarios using computer program assistance vs conventional methods. Two versions of a 4-part paper-based test were developed. Each part consisted of a set of medication administration and/or dosing tasks. Emergency department and pediatric intensive care unit nurse volunteers completed these tasks using both methods (sequence assigned to start with a conventional or a computer-assisted approach). Completion times, errors, and the reason for the error were recorded. Thirty-eight nurses completed the study. Summing the completion of all 4 parts, the mean conventional total time was 1243 seconds vs the mean computer program total time of 879 seconds (P < .001). The conventional manual method had a mean of 1.8 errors vs the computer program with a mean of 0.7 errors (P < .001). Of the 97 total errors, 36 were due to misreading the drug concentration on the label, 34 were due to calculation errors, and 8 were due to misplaced decimals. Of the 36 label interpretation errors, 18 (50%) occurred with digoxin or insulin. Computerized assistance reduced errors and the time required for drug administration calculations. A pattern of errors emerged, noting that reading/interpreting certain drug labels were more error prone. Optimizing the layout of drug labels could reduce the error rate for error-prone labels. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Comment on ''Reassessment of space-change and central-cell scattering contributions to GaAs electron mobility''

NASA Astrophysics Data System (ADS)

Stringfellow, G. B.

1982-07-01

Walukiewicz et al.1 have recently stated that previously reported contributions to the electron mobility of GaAs from space-charge and/or central-cell scattering are in fact insignificant, and that reports of a T-1/2 term in the mobility2,3 are artifacts due to the assumption of Mathiessen's rule. This conclusion is an overstatement of their results and in fact demonstrably incorrect. First, an analysis of the data reported by Stringfellow2 and Stringfellow and Kuenzel3 as well as others has already been performed by Chattopadhyay et al.4 without assuming Mathiessen's rule. Their conclusion is that central-cell scattering is indeed significant. Second, the particular data analyzed by Walukiewicz et al. are in fact acknowledged in Ref. 2 to have very little T-1/2 scattering. The magnitude of the scattering cross section for T-1/2 scattering, SCA, for other samples is more than an order of magnitude larger, too large to be ascribed to errors inherent in using Mathiessen's rule. Experimental data convincingly demonstrate this. The mobility versus temperature curves are lower, especially at higher temperatures, for C as opposed to Zn- or Ge-doped samples where all have the same values of ND+NA (see Fig. 2 of Ref. 3). In addition, recently published data5 for MBE GaAs grown with different C doping levels show that for constant ND+NA, SCA is three times larger for the more highly C doped samples. This could not be due to errors inherent in the use of Mathiessen's rule. For these samples C clearly introduces an increase in the T-1/2 scattering which is not observed for other acceptors. ufc15xr 1W. Walukiewicz, J. Lagowski, and H. C. Gatos, J. Appl. Phys. 52, 5853 (1981). 2G. B. Stringfellow, J. Appl. Phys. 50, 4178 (1979). 3G. B. Stringfellow and H. Kuenzel, J. Appl. Phys. 51, 3254 (1980). 4D. Chattopadhyay, H. J. Queisser, and G. B. Stringfellow, J. Phys. Soc. Jpn. 49, Suppl. A, 293 (1980). 5G. B. Stringfellow, R. Stall, and W. Koschel, Appl. Phys. Lett. 38, 156 (1981). UFTELTAL G. B. Stringfellow G. B. Stringfellow G. B. Stringfellow The T-1/2 term in electron mobility for GaAs and AlxGa1-xAs is shown not to be solely due to errors inherent in the use of Mathiessen's rule.

How to Avoid Errors in Error Propagation: Prediction Intervals and Confidence Intervals in Forest Biomass

NASA Astrophysics Data System (ADS)

Lilly, P.; Yanai, R. D.; Buckley, H. L.; Case, B. S.; Woollons, R. C.; Holdaway, R. J.; Johnson, J.

2016-12-01

Calculations of forest biomass and elemental content require many measurements and models, each contributing uncertainty to the final estimates. While sampling error is commonly reported, based on replicate plots, error due to uncertainty in the regression used to estimate biomass from tree diameter is usually not quantified. Some published estimates of uncertainty due to the regression models have used the uncertainty in the prediction of individuals, ignoring uncertainty in the mean, while others have propagated uncertainty in the mean while ignoring individual variation. Using the simple case of the calcium concentration of sugar maple leaves, we compare the variation among individuals (the standard deviation) to the uncertainty in the mean (the standard error) and illustrate the declining importance in the prediction of individual concentrations as the number of individuals increases. For allometric models, the analogous statistics are the prediction interval (or the residual variation in the model fit) and the confidence interval (describing the uncertainty in the best fit model). The effect of propagating these two sources of error is illustrated using the mass of sugar maple foliage. The uncertainty in individual tree predictions was large for plots with few trees; for plots with 30 trees or more, the uncertainty in individuals was less important than the uncertainty in the mean. Authors of previously published analyses have reanalyzed their data to show the magnitude of these two sources of uncertainty in scales ranging from experimental plots to entire countries. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks, as required by the IPCC, can ignore the uncertainty in individuals. Ignoring the uncertainty in the mean will lead to exaggerated estimates of confidence in estimates of forest biomass and carbon and nutrient contents.

Preparatory studies for the WFIRST supernova cosmology measurements

NASA Astrophysics Data System (ADS)

Perlmutter, Saul

In the context of the WFIRST-AFTA Science Definition Team we developed a first version of a supernova program, described in the WFIRST-AFTA SDT report. This program uses the imager to discover supernova candidates and an Integral Field Spectrograph (IFS) to obtain spectrophotometric light curves and higher signal to noise spectra of the supernovae near peak to better characterize the supernovae and thus minimize systematic errors. While this program was judged a robust one, and the estimates of the sensitivity to the cosmological parameters were felt to be reliable, due to limitation of time the analysis was clearly limited in depth on a number of issues. The goal of this proposal is to further develop this program and refine the estimates of the sensitivities to the cosmological parameters using more sophisticated systematic uncertainty models and covariance error matrices that fold in more realistic data concerning observed populations of SNe Ia as well as more realistic instrument models. We propose to develop analysis algorithms and approaches that are needed to build, optimize, and refine the WFIRST instrument and program requirements to accomplish the best supernova cosmology measurements possible. We plan to address the following: a) Use realistic Supernova populations, subclasses and population drift. One bothersome uncertainty with the supernova technique is the possibility of population drift with redshift. We are in a unique position to characterize and mitigate such effects using the spectrophotometric time series of real Type Ia supernovae from the Nearby Supernova Factory (SNfactory). Each supernova in this sample has global galaxy measurements as well as additional local environment information derived from the IFS spectroscopy. We plan to develop methods of coping with this issue, e.g., by selecting similar subsamples of supernovae and allowing additional model flexibility, in order to reduce systematic uncertainties. These studies will allow us to tune details, like the wavelength coverage and S/N requirements, of the WFIRST IFS to capitalize on these systematic error reduction methods. b) Supernova extraction and host galaxy subtractions. The underlying light of the host galaxy must be subtracted from the supernova images making up the lightcurves. Using the IFS to provide the lightcurve points via spectrophotometry requires the subtraction of a reference spectrum of the galaxy taken after the supernova light has faded to a negligible level. We plan to apply the expertise obtained from the SNfactory to develop galaxy background procedures that minimize the systematic errors introduced by this step in the analysis. c) Instrument calibration and ground to space cross calibration. Calibrating the entire supernova sample will be a challenge as no standard stars exist that span the range of magnitudes and wavelengths relevant to the WFIRST survey. Linking the supernova measurements to the relatively brighter standards will require several links. WFIRST will produce the high redshift sample, but the nearby supernova to anchor the Hubble diagram will have to come from ground based observations. Developing algorithms to carry out the cross calibration of these two samples to the required one percent level will be an important goal of our proposal. An integral part of this calibration will be to remove all instrumental signatures and to develop unbiased measurement techniques starting at the pixel level. We then plan to pull the above studies together in a synthesis to produce a correlated error matrix. We plan to develop a Fisher Matrix based model to evaluate the correlated error matrix due to the various systematic errors discussed above. A realistic error model will allow us to carry out a more reliable estimates of the eventual errors on the measurement of the cosmological parameters, as well as serve as a means of optimizing and fine tuning the requirements for the instruments and survey strategies.

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.

Dynamic modelling and estimation of the error due to asynchronism in a redundant asynchronous multiprocessor system

NASA Technical Reports Server (NTRS)

Huynh, Loc C.; Duval, R. W.

1986-01-01

The use of Redundant Asynchronous Multiprocessor System to achieve ultrareliable Fault Tolerant Control Systems shows great promise. The development has been hampered by the inability to determine whether differences in the outputs of redundant CPU's are due to failures or to accrued error built up by slight differences in CPU clock intervals. This study derives an analytical dynamic model of the difference between redundant CPU's due to differences in their clock intervals and uses this model with on-line parameter identification to idenitify the differences in the clock intervals. The ability of this methodology to accurately track errors due to asynchronisity generate an error signal with the effect of asynchronisity removed and this signal may be used to detect and isolate actual system failures.

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.

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.

How to deal with multiple binding poses in alchemical relative protein-ligand binding free energy calculations.

PubMed

Kaus, Joseph W; Harder, Edward; Lin, Teng; Abel, Robert; McCammon, J Andrew; Wang, Lingle

2015-06-09

Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges.

How To Deal with Multiple Binding Poses in Alchemical Relative Protein–Ligand Binding Free Energy Calculations

PubMed Central

2016-01-01

Recent advances in improved force fields and sampling methods have made it possible for the accurate calculation of protein–ligand binding free energies. Alchemical free energy perturbation (FEP) using an explicit solvent model is one of the most rigorous methods to calculate relative binding free energies. However, for cases where there are high energy barriers separating the relevant conformations that are important for ligand binding, the calculated free energy may depend on the initial conformation used in the simulation due to the lack of complete sampling of all the important regions in phase space. This is particularly true for ligands with multiple possible binding modes separated by high energy barriers, making it difficult to sample all relevant binding modes even with modern enhanced sampling methods. In this paper, we apply a previously developed method that provides a corrected binding free energy for ligands with multiple binding modes by combining the free energy results from multiple alchemical FEP calculations starting from all enumerated poses, and the results are compared with Glide docking and MM-GBSA calculations. From these calculations, the dominant ligand binding mode can also be predicted. We apply this method to a series of ligands that bind to c-Jun N-terminal kinase-1 (JNK1) and obtain improved free energy results. The dominant ligand binding modes predicted by this method agree with the available crystallography, while both Glide docking and MM-GBSA calculations incorrectly predict the binding modes for some ligands. The method also helps separate the force field error from the ligand sampling error, such that deviations in the predicted binding free energy from the experimental values likely indicate possible inaccuracies in the force field. An error in the force field for a subset of the ligands studied was identified using this method, and improved free energy results were obtained by correcting the partial charges assigned to the ligands. This improved the root-mean-square error (RMSE) for the predicted binding free energy from 1.9 kcal/mol with the original partial charges to 1.3 kcal/mol with the corrected partial charges. PMID:26085821

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

The role of global cloud climatologies in validating numerical models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1993-01-01

The purpose of this work is to estimate sampling errors of area-time averaged rain rate due to temporal samplings by satellites. In particular, the sampling errors of the proposed low inclination orbit satellite of the Tropical Rainfall Measuring Mission (TRMM) (35 deg inclination and 350 km altitude), one of the sun synchronous polar orbiting satellites of NOAA series (98.89 deg inclination and 833 km altitude), and two simultaneous sun synchronous polar orbiting satellites--assumed to carry a perfect passive microwave sensor for direct rainfall measurements--will be estimated. This estimate is done by performing a study of the satellite orbits and the autocovariance function of the area-averaged rain rate time series. A model based on an exponential fit of the autocovariance function is used for actual calculations. Varying visiting intervals and total coverage of averaging area on each visit by the satellites are taken into account in the model. The data are generated by a General Circulation Model (GCM). The model has a diurnal cycle and parameterized convective processes. A special run of the GCM was made at NASA/GSFC in which the rainfall and precipitable water fields were retained globally for every hour of the run for the whole year.

Quantization of high dimensional Gaussian vector using permutation modulation with application to information reconciliation in continuous variable QKD

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina; Olia, Khashayar

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal-to-Noise Ratio (SNR) exasperating the problem. Quantization over higher dimensions is advantageous since it allows for fractional bit per sample accuracy which may be needed at very low SNR conditions whereby the achievable secret key rate is significantly less than one bit per sample. In this paper, we propose to use Permutation Modulation (PM) for quantization of Gaussian vectors potentially containing thousands of samples. PM is applied to the magnitudes of the Gaussian samples and we explore the dependence of the sign error probability on the magnitude of the samples. At very low SNR, we may transmit the entire label of the PM code from Bob to Alice in Reverse Reconciliation (RR) over public channel. The side information extracted from this label can then be used by Alice to characterize the sign error probability of her individual samples. Forward Error Correction (FEC) coding can be used by Bob on each subset of samples with similar sign error probability to aid Alice in error correction. This can be done for different subsets of samples with similar sign error probabilities leading to an Unequal Error Protection (UEP) coding paradigm.

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.

Radiometric analysis of the longwave infrared channel of the Thematic Mapper on LANDSAT 4 and 5

NASA Technical Reports Server (NTRS)

Schott, John R.; Volchok, William J.; Biegel, Joseph D.

1986-01-01

The first objective was to evaluate the postlaunch radiometric calibration of the LANDSAT Thematic Mapper (TM) band 6 data. The second objective was to determine to what extent surface temperatures could be computed from the TM and 6 data using atmospheric propagation models. To accomplish this, ground truth data were compared to a single TM-4 band 6 data set. This comparison indicated satisfactory agreement over a narrow temperature range. The atmospheric propagation model (modified LOWTRAN 5A) was used to predict surface temperature values based on the radiance at the spacecraft. The aircraft data were calibrated using a multi-altitude profile calibration technique which had been extensively tested in previous studies. This aircraft calibration permitted measurement of surface temperatures based on the radiance reaching the aircraft. When these temperature values are evaluated, an error in the satellite's ability to predict surface temperatures can be estimated. This study indicated that by carefully accounting for various sensor calibration and atmospheric propagation effects, and expected error (1 standard deviation) in surface temperature would be 0.9 K. This assumes no error in surface emissivity and no sampling error due to target location. These results indicate that the satellite calibration is within nominal limits to within this study's ability to measure error.

Identification and Correction of Sample Mix-Ups in Expression Genetic Data: A Case Study

PubMed Central

Broman, Karl W.; Keller, Mark P.; Broman, Aimee Teo; Kendziorski, Christina; Yandell, Brian S.; Sen, Śaunak; Attie, Alan D.

2015-01-01

In a mouse intercross with more than 500 animals and genome-wide gene expression data on six tissues, we identified a high proportion (18%) of sample mix-ups in the genotype data. Local expression quantitative trait loci (eQTL; genetic loci influencing gene expression) with extremely large effect were used to form a classifier to predict an individual’s eQTL genotype based on expression data alone. By considering multiple eQTL and their related transcripts, we identified numerous individuals whose predicted eQTL genotypes (based on their expression data) did not match their observed genotypes, and then went on to identify other individuals whose genotypes did match the predicted eQTL genotypes. The concordance of predictions across six tissues indicated that the problem was due to mix-ups in the genotypes (although we further identified a small number of sample mix-ups in each of the six panels of gene expression microarrays). Consideration of the plate positions of the DNA samples indicated a number of off-by-one and off-by-two errors, likely the result of pipetting errors. Such sample mix-ups can be a problem in any genetic study, but eQTL data allow us to identify, and even correct, such problems. Our methods have been implemented in an R package, R/lineup. PMID:26290572

Identification and Correction of Sample Mix-Ups in Expression Genetic Data: A Case Study.

PubMed

Broman, Karl W; Keller, Mark P; Broman, Aimee Teo; Kendziorski, Christina; Yandell, Brian S; Sen, Śaunak; Attie, Alan D

2015-08-19

In a mouse intercross with more than 500 animals and genome-wide gene expression data on six tissues, we identified a high proportion (18%) of sample mix-ups in the genotype data. Local expression quantitative trait loci (eQTL; genetic loci influencing gene expression) with extremely large effect were used to form a classifier to predict an individual's eQTL genotype based on expression data alone. By considering multiple eQTL and their related transcripts, we identified numerous individuals whose predicted eQTL genotypes (based on their expression data) did not match their observed genotypes, and then went on to identify other individuals whose genotypes did match the predicted eQTL genotypes. The concordance of predictions across six tissues indicated that the problem was due to mix-ups in the genotypes (although we further identified a small number of sample mix-ups in each of the six panels of gene expression microarrays). Consideration of the plate positions of the DNA samples indicated a number of off-by-one and off-by-two errors, likely the result of pipetting errors. Such sample mix-ups can be a problem in any genetic study, but eQTL data allow us to identify, and even correct, such problems. Our methods have been implemented in an R package, R/lineup. Copyright © 2015 Broman et al.

Acquisition of Malay word recognition skills: lessons from low-progress early readers.

PubMed

Lee, Lay Wah; Wheldall, Kevin

2011-02-01

Malay is a consistent alphabetic orthography with complex syllable structures. The focus of this research was to investigate word recognition performance in order to inform reading interventions for low-progress early readers. Forty-six Grade 1 students were sampled and 11 were identified as low-progress readers. The results indicated that both syllable awareness and phoneme blending were significant predictors of word recognition, suggesting that both syllable and phonemic grain-sizes are important in Malay word recognition. Item analysis revealed a hierarchical pattern of difficulty based on the syllable and the phonic structure of the words. Error analysis identified the sources of errors to be errors due to inefficient syllable segmentation, oversimplification of syllables, insufficient grapheme-phoneme knowledge and inefficient phonemic code assembly. Evidence also suggests that direct instruction in syllable segmentation, phonemic awareness and grapheme-phoneme correspondence is necessary for low-progress readers to acquire word recognition skills. Finally, a logical sequence to teach grapheme-phoneme decoding in Malay is suggested. Copyright © 2010 John Wiley & Sons, Ltd.

Hand-Writing Motion Tracking with Vision-Inertial Sensor Fusion: Calibration and Error Correction

PubMed Central

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J.

2014-01-01

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model. PMID:25157546

Multi-canister overpack project -- verification and validation, MCNP 4A

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

Goldmann, L.H.

This supporting document contains the software verification and validation (V and V) package used for Phase 2 design of the Spent Nuclear Fuel Multi-Canister Overpack. V and V packages for both ANSYS and MCNP are included. Description of Verification Run(s): This software requires that it be compiled specifically for the machine it is to be used on. Therefore to facilitate ease in the verification process the software automatically runs 25 sample problems to ensure proper installation and compilation. Once the runs are completed the software checks for verification by performing a file comparison on the new output file and themore » old output file. Any differences between any of the files will cause a verification error. Due to the manner in which the verification is completed a verification error does not necessarily indicate a problem. This indicates that a closer look at the output files is needed to determine the cause of the error.« less

Application of Barcoding to Reduce Error of Patient Identification and to Increase Patient's Information Confidentiality of Test Tube Labelling in a Psychiatric Teaching Hospital.

PubMed

Liu, Hsiu-Chu; Li, Hsing; Chang, Hsin-Fei; Lu, Mei-Rou; Chen, Feng-Chuan

2015-01-01

Learning from the experience of another medical center in Taiwan, Kaohsiung Municipal Kai-Suan Psychiatric Hospital has changed the nursing informatics system step by step in the past year and a half . We considered ethics in the original idea of implementing barcodes on the test tube labels to process the identification of the psychiatric patients. The main aims of this project are to maintain the confidential information and to transport the sample effectively. The primary nurses had been using different work sheets for this project to ensure the acceptance of the new barcode system. In the past two years the errors in the blood testing process were as high as 11,000 in 14,000 events per year, resulting in wastage of resources. The actions taken by the nurses and the new barcode system implementation can improve the clinical nursing care quality, safety of the patients, and efficiency, while decreasing the cost due to the human error.

77 FR 41699 - Transportation of Household Goods in Interstate Commerce; Consumer Protection Regulations...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-16

... due Revision due to agency Collection Old burden to error error (old-- error) IC1: ``Ready to Move... Revisions of Estimates of Annual Costs to Respondents Total cost Collection New cost Old cost reduction (new--old) IC1: ``Ready to Move?'' $288,000 $720,000 -$432,000 ``Rights & Responsibilities'' 3,264,000 8,160...

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.

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.

Determination of fluoride in water - A modified zirconium-alizarin method

USGS Publications Warehouse

Lamar, W.L.

1945-01-01

A convenient, rapid colorimetric procedure using the zirconium-alizarin indicator acidified with sulfuric acid for the determination of fluoride in water is described. Since this acid indicator is stable indefinitely, it is more useful than other zirconium-alizarin reagents previously reported. The use of sulfuric acid alone in acidifying the zirconium-alizarin reagent makes possible the maximum suppression of the interference of sulfate. Control of the pH of the samples eliminates errors due to the alkalinity of the samples. The fluoride content of waters containing less than 500 parts per million of sulfate and less than 1000 p.p.m. of chloride may be determined within a limit of 0.1 p.p.m. when a 100-ml. sample is used.

Medication errors in anesthesia: unacceptable or unavoidable?

PubMed

Dhawan, Ira; Tewari, Anurag; Sehgal, Sankalp; Sinha, Ashish Chandra

Medication errors are the common causes of patient morbidity and mortality. It adds financial burden to the institution as well. Though the impact varies from no harm to serious adverse effects including death, it needs attention on priority basis since medication errors' are preventable. In today's world where people are aware and medical claims are on the hike, it is of utmost priority that we curb this issue. Individual effort to decrease medication error alone might not be successful until a change in the existing protocols and system is incorporated. Often drug errors that occur cannot be reversed. The best way to 'treat' drug errors is to prevent them. Wrong medication (due to syringe swap), overdose (due to misunderstanding or preconception of the dose, pump misuse and dilution error), incorrect administration route, under dosing and omission are common causes of medication error that occur perioperatively. Drug omission and calculation mistakes occur commonly in ICU. Medication errors can occur perioperatively either during preparation, administration or record keeping. Numerous human and system errors can be blamed for occurrence of medication errors. The need of the hour is to stop the blame - game, accept mistakes and develop a safe and 'just' culture in order to prevent medication errors. The newly devised systems like VEINROM, a fluid delivery system is a novel approach in preventing drug errors due to most commonly used medications in anesthesia. Similar developments along with vigilant doctors, safe workplace culture and organizational support all together can help prevent these errors. Copyright © 2016. Published by Elsevier Editora Ltda.

Comparison of Aircraft Models and Integration Schemes for Interval Management in the TRACON

NASA Technical Reports Server (NTRS)

Neogi, Natasha; Hagen, George E.; Herencia-Zapana, Heber

2012-01-01

Reusable models of common elements for communication, computation, decision and control in air traffic management are necessary in order to enable simulation, analysis and assurance of emergent properties, such as safety and stability, for a given operational concept. Uncertainties due to faults, such as dropped messages, along with non-linearities and sensor noise are an integral part of these models, and impact emergent system behavior. Flight control algorithms designed using a linearized version of the flight mechanics will exhibit error due to model uncertainty, and may not be stable outside a neighborhood of the given point of linearization. Moreover, the communication mechanism by which the sensed state of an aircraft is fed back to a flight control system (such as an ADS-B message) impacts the overall system behavior; both due to sensor noise as well as dropped messages (vacant samples). Additionally simulation of the flight controller system can exhibit further numerical instability, due to selection of the integration scheme and approximations made in the flight dynamics. We examine the theoretical and numerical stability of a speed controller under the Euler and Runge-Kutta schemes of integration, for the Maintain phase for a Mid-Term (2035-2045) Interval Management (IM) Operational Concept for descent and landing operations. We model uncertainties in communication due to missed ADS-B messages by vacant samples in the integration schemes, and compare the emergent behavior of the system, in terms of stability, via the boundedness of the final system state. Any bound on the errors incurred by these uncertainties will play an essential part in a composable assurance argument required for real-time, flight-deck guidance and control systems,. Thus, we believe that the creation of reusable models, which possess property guarantees, such as safety and stability, is an innovative and essential requirement to assessing the emergent properties of novel airspace concepts of operation.

Nonuniform fast Fourier transform method for numerical diffraction simulation on tilted planes.

PubMed

Xiao, Yu; Tang, Xiahui; Qin, Yingxiong; Peng, Hao; Wang, Wei; Zhong, Lijing

2016-10-01

The method, based on the rotation of the angular spectrum in the frequency domain, is generally used for the diffraction simulation between the tilted planes. Due to the rotation of the angular spectrum, the interval between the sampling points in the Fourier domain is not even. For the conventional fast Fourier transform (FFT)-based methods, a spectrum interpolation is needed to get the approximate sampling value on the equidistant sampling points. However, due to the numerical error caused by the spectrum interpolation, the calculation accuracy degrades very quickly as the rotation angle increases. Here, the diffraction propagation between the tilted planes is transformed into a problem about the discrete Fourier transform on the uneven sampling points, which can be evaluated effectively and precisely through the nonuniform fast Fourier transform method (NUFFT). The most important advantage of this method is that the conventional spectrum interpolation is avoided and the high calculation accuracy can be guaranteed for different rotation angles, even when the rotation angle is close to π/2. Also, its calculation efficiency is comparable with that of the conventional FFT-based methods. Numerical examples as well as a discussion about the calculation accuracy and the sampling method are presented.

Micro-tensile testing system

DOEpatents

Wenski, Edward G [Lenexa, KS

2007-08-21

A micro-tensile testing system providing a stand-alone test platform for testing and reporting physical or engineering properties of test samples of materials having thicknesses of approximately between 0.002 inch and 0.030 inch, including, for example, LiGA engineered materials. The testing system is able to perform a variety of static, dynamic, and cyclic tests. The testing system includes a rigid frame and adjustable gripping supports to minimize measurement errors due to deflection or bending under load; serrated grips for securing the extremely small test sample; high-speed laser scan micrometers for obtaining accurate results; and test software for controlling the testing procedure and reporting results.

Micro-tensile testing system

DOEpatents

Wenski, Edward G.

2006-01-10

A micro-tensile testing system providing a stand-alone test platform for testing and reporting physical or engineering properties of test samples of materials having thicknesses of approximately between 0.002 inch and 0.030 inch, including, for example, LiGA engineered materials. The testing system is able to perform a variety of static, dynamic, and cyclic tests. The testing system includes a rigid frame and adjustable gripping supports to minimize measurement errors due to deflection or bending under load; serrated grips for securing the extremely small test sample; high-speed laser scan micrometers for obtaining accurate results; and test software for controlling the testing procedure and reporting results.

Micro-tensile testing system

DOEpatents

Wenski, Edward G [Lenexa, KS

2007-07-17

A micro-tensile testing system providing a stand-alone test platform for testing and reporting physical or engineering properties of test samples of materials having thicknesses of approximately between 0.002 inch and 0.030 inch, including, for example, LiGA engineered materials. The testing system is able to perform a variety of static, dynamic, and cyclic tests. The testing system includes a rigid frame and adjustable gripping supports to minimize measurement errors due to deflection or bending under load; serrated grips for securing the extremely small test sample; high-speed laser scan micrometers for obtaining accurate results; and test software for controlling the testing procedure and reporting results.

Determination of beta emitters ( 90Sr, 14C and 3H) in routine measurements using plastic scintillation beads

NASA Astrophysics Data System (ADS)

Tarancón, A.; García, J. F.; Rauret, G.

2004-01-01

Plastic scintillation has recently been shown to be a powerful alternative to liquid scintillation and Cherenkov techniques in radionuclide determination due to the good values obtained for the measurement parameters and the low amount of wastes generated. The present study evaluated the capability of plastic scintillation beads and polyethylene vials for routine measurements of beta emitters ( 90Sr, 14C, 3H). Results show that high- and medium-energetic beta emitters can be quantified with relative errors less than 5% in low-activity aqueous samples, whereas low-energetic beta emitters can only be quantified in medium-activity samples.

Thermal Conductivities of Some Polymers and Composites

DTIC Science & Technology

2018-02-01

volume fraction of glass and fabric style. The experimental results are compared to modeled results for Kt in composites. 15. SUBJECT TERMS...entities in a polymer above TG increases, so Cp will increase at TG. For Kt to remain constant, there would have to be a comparable decrease in α due to...scanning calorimetry (DSC) method, and have error bars as large as the claimed effect. Their Kt values for their carbon fiber samples are comparable to

Model Selection with Strong-lensing Systems

NASA Astrophysics Data System (ADS)

Leaf, Kyle; Melia, Fulvio

2018-05-01

In this paper, we use an unprecedentedly large sample (158) of confirmed strong lens systems for model selection, comparing five well studied Friedmann-Robertson-Walker cosmologies: ΛCDM, wCDM (the standard model with a variable dark-energy equation of state), the Rh = ct universe, the (empty) Milne cosmology, and the classical Einstein-de Sitter (matter dominated) universe. We first use these sources to optimize the parameters in the standard model and show that they are consistent with Planck, though the quality of the best fit is not satisfactory. We demonstrate that this is likely due to under-reported errors, or to errors yet to be included in this kind of analysis. We suggest that the missing dispersion may be due to scatter about a pure single isothermal sphere (SIS) model that is often assumed for the mass distribution in these lenses. We then use the Bayes information criterion, with the inclusion of a suggested SIS dispersion, to calculate the relative likelihoods and ranking of these models, showing that Milne and Einstein-de Sitter are completely ruled out, while Rh = ct is preferred over ΛCDM/wCDM with a relative probability of ˜73% versus ˜24%. The recently reported sample of new strong lens candidates by the Dark Energy Survey, if confirmed, may be able to demonstrate which of these two models is favoured over the other at a level exceeding 3σ.

Remediating Common Math Errors.

ERIC Educational Resources Information Center

Wagner, Rudolph F.

1981-01-01

Explanations and remediation suggestions for five types of mathematics errors due either to perceptual or cognitive difficulties are given. Error types include directionality problems, mirror writing, visually misperceived signs, diagnosed directionality problems, and mixed process errors. (CL)

Intimate Partner Violence, 1993-2010

MedlinePlus

... appendix table 2 for standard errors. *Due to methodological changes, use caution when comparing 2006 NCVS criminal ... appendix table 2 for standard errors. *Due to methodological changes, use caution when comparing 2006 NCVS criminal ...

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.

Intrusion errors in visuospatial working memory performance.

PubMed

Cornoldi, Cesare; Mammarella, Nicola

2006-02-01

This study tested the hypothesis that failure in active visuospatial working memory tasks involves a difficulty in avoiding intrusions due to information that is already activated. Two experiments are described, in which participants were required to process several series of locations on a 4 x 4 matrix and then to produce only the final location of each series. Results revealed a higher number of errors due to already activated locations (intrusions) compared with errors due to new locations (inventions). Moreover, when participants were required to pay extra attention to some irrelevant (non-final) locations by tapping on the table, intrusion errors increased. Results are discussed in terms of current models of working memory functioning.

Confidence Preserving Machine for Facial Action Unit Detection

PubMed Central

Zeng, Jiabei; Chu, Wen-Sheng; De la Torre, Fernando; Cohn, Jeffrey F.; Xiong, Zhang

2016-01-01

Facial action unit (AU) detection from video has been a long-standing problem in automated facial expression analysis. While progress has been made, accurate detection of facial AUs remains challenging due to ubiquitous sources of errors, such as inter-personal variability, pose, and low-intensity AUs. In this paper, we refer to samples causing such errors as hard samples, and the remaining as easy samples. To address learning with the hard samples, we propose the Confidence Preserving Machine (CPM), a novel two-stage learning framework that combines multiple classifiers following an “easy-to-hard” strategy. During the training stage, CPM learns two confident classifiers. Each classifier focuses on separating easy samples of one class from all else, and thus preserves confidence on predicting each class. During the testing stage, the confident classifiers provide “virtual labels” for easy test samples. Given the virtual labels, we propose a quasi-semi-supervised (QSS) learning strategy to learn a person-specific (PS) classifier. The QSS strategy employs a spatio-temporal smoothness that encourages similar predictions for samples within a spatio-temporal neighborhood. In addition, to further improve detection performance, we introduce two CPM extensions: iCPM that iteratively augments training samples to train the confident classifiers, and kCPM that kernelizes the original CPM model to promote nonlinearity. Experiments on four spontaneous datasets GFT [15], BP4D [56], DISFA [42], and RU-FACS [3] illustrate the benefits of the proposed CPM models over baseline methods and state-of-the-art semisupervised learning and transfer learning methods. PMID:27479964

Goldmann tonometer error correcting prism: clinical evaluation.

PubMed

McCafferty, Sean; Lim, Garrett; Duncan, William; Enikov, Eniko T; Schwiegerling, Jim; Levine, Jason; Kew, Corin

2017-01-01

Clinically evaluate a modified applanating surface Goldmann tonometer prism designed to substantially negate errors due to patient variability in biomechanics. A modified Goldmann prism with a correcting applanation tonometry surface (CATS) was mathematically optimized to minimize the intraocular pressure (IOP) measurement error due to patient variability in corneal thickness, stiffness, curvature, and tear film adhesion force. A comparative clinical study of 109 eyes measured IOP with CATS and Goldmann prisms. The IOP measurement differences between the CATS and Goldmann prisms were correlated to corneal thickness, hysteresis, and curvature. The CATS tonometer prism in correcting for Goldmann central corneal thickness (CCT) error demonstrated a reduction to <±2 mmHg in 97% of a standard CCT population. This compares to only 54% with CCT error <±2 mmHg using the Goldmann prism. Equal reductions of ~50% in errors due to corneal rigidity and curvature were also demonstrated. The results validate the CATS prism's improved accuracy and expected reduced sensitivity to Goldmann errors without IOP bias as predicted by mathematical modeling. The CATS replacement for the Goldmann prism does not change Goldmann measurement technique or interpretation.

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2010 CFR

2010-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2014 CFR

2014-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2012 CFR

2012-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2013 CFR

2013-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2011 CFR

2011-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

Characterizing Satellite Rainfall Errors based on Land Use and Land Cover and Tracing Error Source in Hydrologic Model Simulation

NASA Astrophysics Data System (ADS)

Gebregiorgis, A. S.; Peters-Lidard, C. D.; Tian, Y.; Hossain, F.

2011-12-01

Hydrologic modeling has benefited from operational production of high resolution satellite rainfall products. The global coverage, near-real time availability, spatial and temporal sampling resolutions have advanced the application of physically based semi-distributed and distributed hydrologic models for wide range of environmental decision making processes. Despite these successes, the existence of uncertainties due to indirect way of satellite rainfall estimates and hydrologic models themselves remain a challenge in making meaningful and more evocative predictions. This study comprises breaking down of total satellite rainfall error into three independent components (hit bias, missed precipitation and false alarm), characterizing them as function of land use and land cover (LULC), and tracing back the source of simulated soil moisture and runoff error in physically based distributed hydrologic model. Here, we asked "on what way the three independent total bias components, hit bias, missed, and false precipitation, affect the estimation of soil moisture and runoff in physically based hydrologic models?" To understand the clear picture of the outlined question above, we implemented a systematic approach by characterizing and decomposing the total satellite rainfall error as a function of land use and land cover in Mississippi basin. This will help us to understand the major source of soil moisture and runoff errors in hydrologic model simulation and trace back the information to algorithm development and sensor type which ultimately helps to improve algorithms better and will improve application and data assimilation in future for GPM. For forest and woodland and human land use system, the soil moisture was mainly dictated by the total bias for 3B42-RT, CMORPH, and PERSIANN products. On the other side, runoff error was largely dominated by hit bias than the total bias. This difference occurred due to the presence of missed precipitation which is a major contributor to the total bias both during the summer and winter seasons. Missed precipitation, most likely light rain and rain over snow cover, has significant effect on soil moisture and are less capable of producing runoff that results runoff dependency on the hit bias only.

A partial least squares based spectrum normalization method for uncertainty reduction for laser-induced breakdown spectroscopy measurements

NASA Astrophysics Data System (ADS)

Li, Xiongwei; Wang, Zhe; Lui, Siu-Lung; Fu, Yangting; Li, Zheng; Liu, Jianming; Ni, Weidou

2013-10-01

A bottleneck of the wide commercial application of laser-induced breakdown spectroscopy (LIBS) technology is its relatively high measurement uncertainty. A partial least squares (PLS) based normalization method was proposed to improve pulse-to-pulse measurement precision for LIBS based on our previous spectrum standardization method. The proposed model utilized multi-line spectral information of the measured element and characterized the signal fluctuations due to the variation of plasma characteristic parameters (plasma temperature, electron number density, and total number density) for signal uncertainty reduction. The model was validated by the application of copper concentration prediction in 29 brass alloy samples. The results demonstrated an improvement on both measurement precision and accuracy over the generally applied normalization as well as our previously proposed simplified spectrum standardization method. The average relative standard deviation (RSD), average of the standard error (error bar), the coefficient of determination (R2), the root-mean-square error of prediction (RMSEP), and average value of the maximum relative error (MRE) were 1.80%, 0.23%, 0.992, 1.30%, and 5.23%, respectively, while those for the generally applied spectral area normalization were 3.72%, 0.71%, 0.973, 1.98%, and 14.92%, respectively.

Monitoring forest areas from continental to territorial levels using a sample of medium spatial resolution satellite imagery

NASA Astrophysics Data System (ADS)

Eva, Hugh; Carboni, Silvia; Achard, Frédéric; Stach, Nicolas; Durieux, Laurent; Faure, Jean-François; Mollicone, Danilo

A global systematic sampling scheme has been developed by the UN FAO and the EC TREES project to estimate rates of deforestation at global or continental levels at intervals of 5 to 10 years. This global scheme can be intensified to produce results at the national level. In this paper, using surrogate observations, we compare the deforestation estimates derived from these two levels of sampling intensities (one, the global, for the Brazilian Amazon the other, national, for French Guiana) to estimates derived from the official inventories. We also report the precisions that are achieved due to sampling errors and, in the case of French Guiana, compare such precision with the official inventory precision. We extract nine sample data sets from the official wall-to-wall deforestation map derived from satellite interpretations produced for the Brazilian Amazon for the year 2002 to 2003. This global sampling scheme estimate gives 2.81 million ha of deforestation (mean from nine simulated replicates) with a standard error of 0.10 million ha. This compares with the full population estimate from the wall-to-wall interpretations of 2.73 million ha deforested, which is within one standard error of our sampling test estimate. The relative difference between the mean estimate from sampling approach and the full population estimate is 3.1%, and the standard error represents 4.0% of the full population estimate. This global sampling is then intensified to a territorial level with a case study over French Guiana to estimate deforestation between the years 1990 and 2006. For the historical reference period, 1990, Landsat-5 Thematic Mapper data were used. A coverage of SPOT-HRV imagery at 20 m × 20 m resolution acquired at the Cayenne receiving station in French Guiana was used for year 2006. Our estimates from the intensified global sampling scheme over French Guiana are compared with those produced by the national authority to report on deforestation rates under the Kyoto protocol rules for its overseas department. The latter estimates come from a sample of nearly 17,000 plots analyzed from same spatial imagery acquired between year 1990 and year 2006. This sampling scheme is derived from the traditional forest inventory methods carried out by IFN (Inventaire Forestier National). Our intensified global sampling scheme leads to an estimate of 96,650 ha deforested between 1990 and 2006, which is within the 95% confidence interval of the IFN sampling scheme, which gives an estimate of 91,722 ha, representing a relative difference from the IFN of 5.4%. These results demonstrate that the intensification of the global sampling scheme can provide forest area change estimates close to those achieved by official forest inventories (<6%), with precisions of between 4% and 7%, although we only estimate errors from sampling, not from the use of surrogate data. Such methods could be used by developing countries to demonstrate that they are fulfilling requirements for reducing emissions from deforestation in the framework of an REDD (Reducing Emissions from Deforestation in Developing Countries) mechanism under discussion within the United Nations Framework Convention on Climate Change (UNFCCC). Monitoring systems at national levels in tropical countries can also benefit from pan-tropical and regional observations, to ensure consistency between different national monitoring systems.

Effects of tropospheric and ionospheric refraction errors in the utilization of GEOS-C altimeter data

NASA Technical Reports Server (NTRS)

Goad, C. C.

1977-01-01

The effects of tropospheric and ionospheric refraction errors are analyzed for the GEOS-C altimeter project in terms of their resultant effects on C-band orbits and the altimeter measurement itself. Operational procedures using surface meteorological measurements at ground stations and monthly means for ocean surface conditions are assumed, with no corrections made for ionospheric effects. Effects on the orbit height due to tropospheric errors are approximately 15 cm for single pass short arcs (such as for calibration) and 10 cm for global orbits of one revolution. Orbit height errors due to neglect of the ionosphere have an amplitude of approximately 40 cm when the orbits are determined from C-band range data with predominantly daylight tracking. Altimeter measurement errors are approximately 10 cm due to residual tropospheric refraction correction errors. Ionospheric effects on the altimeter range measurement are also on the order of 10 cm during the GEOS-C launch and early operation period.

Geographically correlated orbit error

NASA Technical Reports Server (NTRS)

Rosborough, G. W.

1989-01-01

The dominant error source in estimating the orbital position of a satellite from ground based tracking data is the modeling of the Earth's gravity field. The resulting orbit error due to gravity field model errors are predominantly long wavelength in nature. This results in an orbit error signature that is strongly correlated over distances on the size of ocean basins. Anderle and Hoskin (1977) have shown that the orbit error along a given ground track also is correlated to some degree with the orbit error along adjacent ground tracks. This cross track correlation is verified here and is found to be significant out to nearly 1000 kilometers in the case of TOPEX/POSEIDON when using the GEM-T1 gravity model. Finally, it was determined that even the orbit error at points where ascending and descending ground traces cross is somewhat correlated. The implication of these various correlations is that the orbit error due to gravity error is geographically correlated. Such correlations have direct implications when using altimetry to recover oceanographic signals.

Transperineal prostate biopsy under magnetic resonance image guidance: a needle placement accuracy study.

PubMed

Blumenfeld, Philip; Hata, Nobuhiko; DiMaio, Simon; Zou, Kelly; Haker, Steven; Fichtinger, Gabor; Tempany, Clare M C

2007-09-01

To quantify needle placement accuracy of magnetic resonance image (MRI)-guided core needle biopsy of the prostate. A total of 10 biopsies were performed with 18-gauge (G) core biopsy needle via a percutaneous transperineal approach. Needle placement error was assessed by comparing the coordinates of preplanned targets with the needle tip measured from the intraprocedural coherent gradient echo images. The source of these errors was subsequently investigated by measuring displacement caused by needle deflection and needle susceptibility artifact shift in controlled phantom studies. Needle placement error due to misalignment of the needle template guide was also evaluated. The mean and standard deviation (SD) of errors in targeted biopsies was 6.5 +/- 3.5 mm. Phantom experiments showed significant placement error due to needle deflection with a needle with an asymmetrically beveled tip (3.2-8.7 mm depending on tissue type) but significantly smaller error with a symmetrical bevel (0.6-1.1 mm). Needle susceptibility artifacts observed a shift of 1.6 +/- 0.4 mm from the true needle axis. Misalignment of the needle template guide contributed an error of 1.5 +/- 0.3 mm. Needle placement error was clinically significant in MRI-guided biopsy for diagnosis of prostate cancer. Needle placement error due to needle deflection was the most significant cause of error, especially for needles with an asymmetrical bevel. (c) 2007 Wiley-Liss, Inc.

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.

Circulating tumoral cells lack circadian-rhythm in hospitalized metastasic breast cancer patients.

PubMed

García-Sáenz, José Angel; Martín, Miguel; Maestro, Marisa; Vidaurreta, Marta; Veganzones, Silvia; Villalobos, Laura; Rodríguez-Lajusticia, Laura; Rafael, Sara; Sanz-Casla, María Teresa; Casado, Antonio; Sastre, Javier; Arroyo, Manuel; Díaz-Rubio, Eduardo

2006-11-01

The relationship between breast cancer and circadian rhythm variation has been extensively studied. Increased breast tumorigenesis has been reported in melatonin-suppressed experimental models and in observational studies. Circulating Tumor Cells (CTC) circadian- rhythm may optimize the timing of therapies. This is a prospective experimental study to ascertain the day-time and night-time CTC levels in hospitalized metastasic breast cancer (MBC) patients. CTC are isolated and enumerated from a 08:00 AM and 08:00 PM blood collections. 23 MBC and 23 healthy volunteers entered the study. 69 samples were collected (23 samples at 08:00 AM and 23 samples at 08:00 PM from MBC; 23 samples from healthy volunteers). Results from two patients were rejected due to sample processing errors. No CTC were isolated from healthy-volunteers. No-differences between daytime and night-time CTC were observed. Therefore, we could not ascertain CTC circadian-rhythm in hospitalized metastasic breast cancer patients.

Refractive error and visual impairment in private school children in Ghana.

PubMed

Kumah, Ben D; Ebri, Anne; Abdul-Kabir, Mohammed; Ahmed, Abdul-Sadik; Koomson, Nana Ya; Aikins, Samual; Aikins, Amos; Amedo, Angela; Lartey, Seth; Naidoo, Kovin

2013-12-01

To assess the prevalence of refractive error and visual impairment in private school children in Ghana. A random selection of geographically defined classes in clusters was used to identify a sample of school children aged 12 to 15 years in the Ashanti Region. Children in 60 clusters were enumerated and examined in classrooms. The examination included visual acuity, retinoscopy, autorefraction under cycloplegia, and examination of anterior segment, media, and fundus. For quality assurance, a random sample of children with reduced and normal vision were selected and re-examined independently. A total of 2454 children attending 53 private schools were enumerated, and of these, 2435 (99.2%) were examined. Prevalence of uncorrected, presenting, and best visual acuity of 20/40 or worse in the better eye was 3.7, 3.5, and 0.4%, respectively. Refractive error was the cause of reduced vision in 71.7% of 152 eyes, amblyopia in 9.9%, retinal disorders in 5.9%, and corneal opacity in 4.6%. Exterior and anterior segment abnormalities occurred in 43 (1.8%) children. Myopia (at least -0.50 D) in one or both eyes was present in 3.2% of children when measured with retinoscopy and in 3.4% measured with autorefraction. Myopia was not significantly associated with gender (P = 0.82). Hyperopia (+2.00 D or more) in at least one eye was present in 0.3% of children with retinoscopy and autorefraction. The prevalence of reduced vision in Ghanaian private school children due to uncorrected refractive error was low. However, the prevalence of amblyopia, retinal disorders, and corneal opacities indicate the need for early interventions.

Role of training activities for the reduction of pre-analytical errors in laboratory samples from primary care.

PubMed

Romero, Adolfo; Cobos, Andrés; Gómez, Juan; Muñoz, Manuel

2012-01-18

The presence of pre-analytical errors (PE) is a usual contingency in laboratories. The incidence may increase where it is difficult to control that period, as it is the case with samples sent from primary care (PC) to clinical reference laboratory. Detection of a large number of PE in PC samples in our Institution led to the development and implementation of preventive strategies. The first of these has been the realization of a cycle of educational sessions for PC nurses, followed by the evaluation of their impact on PE number. The incidence of PE was assessed in two periods, before (October-November 2007) and after (October-November, 2009) the implementation of educational sessions. Eleven PC centers in the urban area and 17 in the rural area participated. In the urban area, samples were withdrawn by any PC nurse; in the rural area, samples were obtained by the patient's reference nurse. The types of analyzed PE included missed sample (MS), hemolyzed sample (HS), coagulated sample (CS), incorrect sample (ISV) and others (OPE), such as lipemic or icteric serum or plasma. In the former period, we received 52,669 blood samples and 18,852 urine samples, detecting 3885 (7.5%) and 1567 (8.3%) PEs, respectively. After the educational intervention, there were 52,659 and 19,048 samples with 5057 (9.6%) and 1.256 (6.5%) PEs, respectively (p<0.001). According to the type of PE, the incidents compared before and after compared incidences were: MS, 4.8% vs. 3.8%, p<0.001; HS, 1.97% vs. 3.9%, p<0.001; CS, 0.54% vs. 0.25%, p<0.001; ISV, 0.15% vs. 0.19% p=0.08; and OPE, 0.3% vs. 0.42%, p<0.001. Surprisingly the PE incidence increased after the educational intervention, although it should be noted that it was primarily due to the increase of HS, as the other EP incidence decreased (MS and CS) or remained unchanged (ISV). This seems to indicate the need for a comprehensive approach to reduce the incidence of errors in the pre-analytical period, as one stage interventions do not seem to be effective enough. Copyright © 2011 Elsevier B.V. All rights reserved.

Construction and field test of a programmable and self-cleaning auto-sampler controlled by a low-cost one-board computer

NASA Astrophysics Data System (ADS)

Stadler, Philipp; Farnleitner, Andreas H.; Zessner, Matthias

2016-04-01

This presentation describes in-depth how a low cost micro-computer was used for substantial improvement of established measuring systems due to the construction and implementation of a purposeful complementary device for on-site sample pretreatment. A fully automated on-site device was developed and field-tested, that enables water sampling with simultaneous filtration as well as effective cleaning procedure of the devicés components. The described auto-sampler is controlled by a low-cost one-board computer and designed for sample pre-treatment, with minimal sample alteration, to meet requirements of on-site measurement devices that cannot handle coarse suspended solids within the measurement procedure or -cycle. The automated sample pretreatment was tested for over one year for rapid and on-site enzymatic activity (beta-D-glucuronidase, GLUC) determination in sediment laden stream water. The formerly used proprietary sampling set-up was assumed to lead to a significant damping of the measurement signal due to its susceptibility to clogging, debris- and bio film accumulation. Results show that the installation of the developed apparatus considerably enhanced error-free running time of connected measurement devices and increased the measurement accuracy to an up-to-now unmatched quality.

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

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k -NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k -NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

Effect of porosity, tissue density, and mechanical properties on radial sound speed in human cortical bone

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

Eneh, C. T. M., E-mail: chibuzor.eneh@uef.fi, E-mail: markus.malo@uef.fi, E-mail: janne.karjalainen@boneindex.fi, E-mail: jukka.liukkonen@gmail.com, E-mail: juha.toyras@uef.fi; Töyräs, J., E-mail: chibuzor.eneh@uef.fi, E-mail: markus.malo@uef.fi, E-mail: janne.karjalainen@boneindex.fi, E-mail: jukka.liukkonen@gmail.com, E-mail: juha.toyras@uef.fi; Jurvelin, J. S., E-mail: jukka.jurvelin@uef.fi

Purpose: The purpose of this study was to investigate the effect of simultaneous changes in cortical porosity, tissue mineral density, and elastic properties on radial speed of sound (SOS) in cortical bone. The authors applied quantitative pulse-echo (PE) ultrasound techniques that hold much potential especially for screening of osteoporosis at primary healthcare facilities. Currently, most PE measurements of cortical thickness, a well-known indicator of fracture risk, use a predefined estimate for SOS in bone to calculate thickness. Due to variation of cortical bone porosity, the use of a constant SOS value propagates to an unknown error in cortical thickness assessmentmore » by PE ultrasound. Methods: The authors conducted 2.25 and 5.00 MHz focused PE ultrasound time of flight measurements on femoral diaphyses of 18 cadavers in vitro. Cortical porosities of the samples were determined using microcomputed tomography and related to SOS in the samples. Additionally, the effect of cortical bone porosity and mechanical properties of the calcified matrix on SOS was investigated using numerical finite difference time domain simulations. Results: Both experimental measurements and simulations demonstrated significant negative correlation between radial SOS and cortical porosity (R{sup 2} ≥ 0.493, p < 0.01 and R{sup 2} ≥ 0.989, p < 0.01, respectively). When a constant SOS was assumed for cortical bone, the error due to variation of cortical bone porosity (4.9%–16.4%) was about 6% in the cortical thickness assessment in vitro. Conclusions: Use of a predefined, constant value for radial SOS in cortical bone, i.e., neglecting the effect of measured variation in cortical porosity, propagated to an error of 6% in cortical thickness. This error can be critical as characteristic cortical thinning of 1.10% ± 1.06% per yr decreases bending strength of the distal radius and results in increased fragility in postmenopausal women. Provided that the cortical porosity can be estimated in vivo, the relationship between radial SOS and cortical porosity can be utilized and a porosity based radial SOS estimate could be implemented to determine cortical thickness. This would constitute a step toward individualized quantitative ultrasound diagnostics of osteoporosis.« less

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.

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.

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.

Field comparison of analytical results from discrete-depth ground water samplers

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

Zemo, D.A.; Delfino, T.A.; Gallinatti, J.D.

1995-07-01

Discrete-depth ground water samplers are used during environmental screening investigations to collect ground water samples in lieu of installing and sampling monitoring wells. Two of the most commonly used samplers are the BAT Enviroprobe and the QED HydroPunch I, which rely on differing sample collection mechanics. Although these devices have been on the market for several years, it was unknown what, if any, effect the differences would have on analytical results for ground water samples containing low to moderate concentrations of chlorinated volatile organic compounds (VOCs). This study investigated whether the discrete-depth ground water sampler used introduces statistically significant differencesmore » in analytical results. The goal was to provide a technical basis for allowing the two devices to be used interchangeably during screening investigations. Because this study was based on field samples, it included several sources of potential variability. It was necessary to separate differences due to sampler type from variability due to sampling location, sample handling, and laboratory analytical error. To statistically evaluate these sources of variability, the experiment was arranged in a nested design. Sixteen ground water samples were collected from eight random locations within a 15-foot by 15-foot grid. The grid was located in an area where shallow ground water was believed to be uniformly affected by VOCs. The data were evaluated using analysis of variance.« less

Value Focused Thinking Approach Using Multivariate Validation for Junior Enlisted Performance Reporting in the United States Air Force

DTIC Science & Technology

2014-03-22

consideration for enlisted airmen, has largely become a non factor due to over-inflated scores, with other factors such as specialty knowledge test scores, time...appraisal. Secondly, an Artificial Neural Network (ANN) classifier will be applied to the large sample data to confirm that the values solicited to...jobs, employees make themselves vulnerable to the organization when they expend effort. If extra effort is expended to reduce errors or defects, or

PARTIAL REVISION: ABSORPTION SPECTRUM AND QUANTUM STATES OF THE PRASEODYMIUM ION. I. SINGLE CRYSTALS OF PRASEODYMIUM CHLORIDE

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

Sayre, E.V.; Sancier, K.M.; Freed, S.

1958-07-01

In an analysis of term splitting in the absorption spectrum of 24 samples of praseodymium chloride, Judd (Proc. Roy. Soc. (London) A241, 414(1957)) found all but two of the authors' results to be constant with his. A discussion of reconciliation is presentrd, and the authors point out that the error is due to a mistake in descrimination between electronic transitions and the weak vibrationally coupled lines. (J.R.D.)

Investigating the Causes of Medication Errors and Strategies to Prevention of Them from Nurses and Nursing Student Viewpoint

PubMed Central

Gorgich, Enam Alhagh Charkhat; Barfroshan, Sanam; Ghoreishi, Gholamreza; Yaghoobi, Maryam

2016-01-01

Introduction and Aim: Medication errors as a serious problem in world and one of the most common medical errors that threaten patient safety and may lead to even death of them. The purpose of this study was to investigate the causes of medication errors and strategies to prevention of them from nurses and nursing student viewpoint. Materials & Methods: This cross-sectional descriptive study was conducted on 327 nursing staff of khatam-al-anbia hospital and 62 intern nursing students in nursing and midwifery school of Zahedan, Iran, enrolled through the availability sampling in 2015. The data were collected by the valid and reliable questionnaire. To analyze the data, descriptive statistics, T-test and ANOVA were applied by use of SPSS16 software. Findings: The results showed that the most common causes of medications errors in nursing were tiredness due increased workload (97.8%), and in nursing students were drug calculation, (77.4%). The most important way for prevention in nurses and nursing student opinion, was reducing the work pressure by increasing the personnel, proportional to the number and condition of patients and also creating a unit as medication calculation. Also there was a significant relationship between the type of ward and the mean of medication errors in two groups. Conclusion: Based on the results it is recommended that nurse-managers resolve the human resources problem, provide workshops and in-service education about preparing medications, side-effects of drugs and pharmacological knowledge. Using electronic medications cards is a measure which reduces medications errors. PMID:27045413

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros

2004-01-01

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

Defining And Characterizing Sample Representativeness For DWPF Melter Feed Samples

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

Shine, E. P.; Poirier, M. R.

2013-10-29

Representative sampling is important throughout the Defense Waste Processing Facility (DWPF) process, and the demonstrated success of the DWPF process to achieve glass product quality over the past two decades is a direct result of the quality of information obtained from the process. The objective of this report was to present sampling methods that the Savannah River Site (SRS) used to qualify waste being dispositioned at the DWPF. The goal was to emphasize the methodology, not a list of outcomes from those studies. This methodology includes proven methods for taking representative samples, the use of controlled analytical methods, and datamore » interpretation and reporting that considers the uncertainty of all error sources. Numerous sampling studies were conducted during the development of the DWPF process and still continue to be performed in order to evaluate options for process improvement. Study designs were based on use of statistical tools applicable to the determination of uncertainties associated with the data needs. Successful designs are apt to be repeated, so this report chose only to include prototypic case studies that typify the characteristics of frequently used designs. Case studies have been presented for studying in-tank homogeneity, evaluating the suitability of sampler systems, determining factors that affect mixing and sampling, comparing the final waste glass product chemical composition and durability to that of the glass pour stream sample and other samples from process vessels, and assessing the uniformity of the chemical composition in the waste glass product. Many of these studies efficiently addressed more than one of these areas of concern associated with demonstrating sample representativeness and provide examples of statistical tools in use for DWPF. The time when many of these designs were implemented was in an age when the sampling ideas of Pierre Gy were not as widespread as they are today. Nonetheless, the engineers and statisticians used carefully thought out designs that systematically and economically provided plans for data collection from the DWPF process. Key shared features of the sampling designs used at DWPF and the Gy sampling methodology were the specification of a standard for sample representativeness, an investigation that produced data from the process to study the sampling function, and a decision framework used to assess whether the specification was met based on the data. Without going into detail with regard to the seven errors identified by Pierre Gy, as excellent summaries are readily available such as Pitard [1989] and Smith [2001], SRS engineers understood, for example, that samplers can be biased (Gy's extraction error), and developed plans to mitigate those biases. Experiments that compared installed samplers with more representative samples obtained directly from the tank may not have resulted in systematically partitioning sampling errors into the now well-known error categories of Gy, but did provide overall information on the suitability of sampling systems. Most of the designs in this report are related to the DWPF vessels, not the large SRS Tank Farm tanks. Samples from the DWPF Slurry Mix Evaporator (SME), which contains the feed to the DWPF melter, are characterized using standardized analytical methods with known uncertainty. The analytical error is combined with the established error from sampling and processing in DWPF to determine the melter feed composition. This composition is used with the known uncertainty of the models in the Product Composition Control System (PCCS) to ensure that the wasteform that is produced is comfortably within the acceptable processing and product performance region. Having the advantage of many years of processing that meets the waste glass product acceptance criteria, the DWPF process has provided a considerable amount of data about itself in addition to the data from many special studies. Demonstrating representative sampling directly from the large Tank Farm tanks is a difficult, if not unsolvable enterprise due to limited accessibility. However, the consistency and the adequacy of sampling and mixing at SRS could at least be studied under the controlled process conditions based on samples discussed by Ray and others [2012a] in Waste Form Qualification Report (WQR) Volume 2 and the transfers from Tanks 40H and 51H to the Sludge Receipt and Adjustment Tank (SRAT) within DWPF. It is important to realize that the need for sample representativeness becomes more stringent as the material gets closer to the melter, and the tanks within DWPF have been studied extensively to meet those needs.« less

Wavefront reconstruction algorithm based on Legendre polynomials for radial shearing interferometry over a square area and error analysis.

PubMed

Kewei, E; Zhang, Chen; Li, Mengyang; Xiong, Zhao; Li, Dahai

2015-08-10

Based on the Legendre polynomials expressions and its properties, this article proposes a new approach to reconstruct the distorted wavefront under test of a laser beam over square area from the phase difference data obtained by a RSI system. And the result of simulation and experimental results verifies the reliability of the method proposed in this paper. The formula of the error propagation coefficients is deduced when the phase difference data of overlapping area contain noise randomly. The matrix T which can be used to evaluate the impact of high-orders Legendre polynomial terms on the outcomes of the low-order terms due to mode aliasing is proposed, and the magnitude of impact can be estimated by calculating the F norm of the T. In addition, the relationship between ratio shear, sampling points, terms of polynomials and noise propagation coefficients, and the relationship between ratio shear, sampling points and norms of the T matrix are both analyzed, respectively. Those research results can provide an optimization design way for radial shearing interferometry system with the theoretical reference and instruction.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Prevalence of Refractive Errors Among School Children in Gondar Town, Northwest Ethiopia

PubMed Central

Yared, Assefa Wolde; Belaynew, Wasie Taye; Destaye, Shiferaw; Ayanaw, Tsegaw; Zelalem, Eshete

2012-01-01

Purpose: Many children with poor vision due to refractive error remain undiagnosed and perform poorly in school. The situation is worse in the Sub-Saharan Africa, including Ethiopia, and current information is lacking. The objective of this study is to determine the prevalence of refractive error among children enrolled in elementary schools in Gondar town, Ethiopia. Materials and Methods: This was a cross-sectional study of 1852 students in 8 elementary schools. Subjects were selected by multistage random sampling. The study parameters were visual acuity (VA) evaluation and ocular examination. VA was measured by staff optometrists with the Snellen E-chart while students with subnormal vision were examined using pinhole, retinoscopy evaluation and subjective refraction by ophthalmologists. Results: The study cohort was comprised of 45.8% males and 54.2% females from 8 randomly selected elementary schools with a response rate of 93%. Refractive errors in either eye were present in 174 (9.4%) children. Of these, myopia was diagnosed in 55 (31.6%) children in the right and left eyes followed by hyperopia in 46 (26.4%) and 39 (22.4%) in the right and left eyes respectively. Low myopia was the most common refractive error in 61 (49.2%) and 68 (50%) children for the right and left eyes respectively. Conclusions: Refractive error among children is a common problem in Gondar town and needs to be assessed at every health evaluation of school children for timely treatment. PMID:23248538

Image Reconstruction for Interferometric Imaging of Geosynchronous Satellites

NASA Astrophysics Data System (ADS)

DeSantis, Zachary J.

Imaging distant objects at a high resolution has always presented a challenge due to the diffraction limit. Larger apertures improve the resolution, but at some point the cost of engineering, building, and correcting phase aberrations of large apertures become prohibitive. Interferometric imaging uses the Van Cittert-Zernike theorem to form an image from measurements of spatial coherence. This effectively allows the synthesis of a large aperture from two or more smaller telescopes to improve the resolution. We apply this method to imaging geosynchronous satellites with a ground-based system. Imaging a dim object from the ground presents unique challenges. The atmosphere creates errors in the phase measurements. The measurements are taken simultaneously across a large bandwidth of light. The atmospheric piston error, therefore, manifests as a linear phase error across the spectral measurements. Because the objects are faint, many of the measurements are expected to have a poor signal-to-noise ratio (SNR). This eliminates possibility of use of commonly used techniques like closure phase, which is a standard technique in astronomical interferometric imaging for making partial phase measurements in the presence of atmospheric error. The bulk of our work has been focused on forming an image, using sub-Nyquist sampled data, in the presence of these linear phase errors without relying on closure phase techniques. We present an image reconstruction algorithm that successfully forms an image in the presence of these linear phase errors. We demonstrate our algorithm’s success in both simulation and in laboratory experiments.

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.

Utilization of all Spectral Channels of IASI for the Retrieval of the Atmospheric State

NASA Astrophysics Data System (ADS)

Del Bianco, S.; Cortesi, U.; Carli, B.

2010-12-01

The retrieval of atmospheric state parameters from broadband measurements acquired by high spectral resolution sensors, such as the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Meteorological Operational (MetOp) platform, generally requires to deal with a prohibitively large number of spectral elements available from a single observation (8461 samples in the case of IASI, covering the 645-2760 cm-1 range with a resolution of 0.5 cm-1 and a spectral sampling of 0.25 cm-1). Most inversion algorithms developed for both operational and scientific analysis of IASI spectra perform a reduction of the data - typically based on channel selection, super-channel clustering or Principal Component Analysis (PCA) techniques - in order to handle the high dimensionality of the problem. Accordingly, simultaneous processing of all IASI channels received relatively low attention. Here we prove the feasibility of a retrieval approach exploiting all spectral channels of IASI, to extract information on water vapor, temperature and ozone profiles. This multi-target retrieval removes the systematic errors due to interfering parameters and makes the channel selection no longer necessary. The challenging computation is made possible by the use of a coarse spectral grid for the forward model calculation and by the abatement of the associated modeling errors through the use of a variance-covariance matrix of the residuals that takes into account all the forward model errors.

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)

A Factorial Data Rate and Dwell Time Experiment in the National Transonic Facility

NASA Technical Reports Server (NTRS)

DeLoach, R.

2000-01-01

This report is an introductory tutorial on the application of formal experiment design methods to wind tunnel testing, for the benefit of aeronautical engineers with little formal experiment design training. It also describes the results of a Study to determine whether increases in the sample rate and dwell time of the National Transonic Facility data system Would result in significant changes in force and moment data. Increases in sample rate from 10 samples per second to 50 samples per second were examined, as were changes in dwell time from one second per data point to two seconds. These changes were examined for a representative aircraft model in a range of tunnel operating conditions defined by angles of attack from 0 deg to 3.8 degrees, total pressure from 15.0 psi to 24.1 psi, and Mach numbers from 0.52 to 0.82. No statistically significant effect was associated with the change in sample rate. The change in dwell time from one second to two seconds affected axial force measurements, and to a lesser degree normal force measurements. This dwell effect comprises a "rectification error" caused by incomplete cancellation of the positive and negative elements of certain low frequency dynamic components that are not rejected by the one-Hz low-pass filters of the data system. These low frequency effects may be due to tunnel circuit phenomena and other sources. The magnitude of the dwell effect depends on dynamic pressure, with angle of attack and Mach number influencing the strength of this dependence. An analysis is presented which suggests that the magnitude of the rectification error depends on the ratio of measurement dwell time to the period of the low-frequency dynamics, as well as the amplitude of the dynamics The essential conclusion of this analysis is that extending the dwell time (or, equivalently, replicating short-dwell data points) reduces the rectification error.

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intrinsic errors in transporting a single-spin qubit through a double quantum dot

NASA Astrophysics Data System (ADS)

Li, Xiao; Barnes, Edwin; Kestner, J. P.; Das Sarma, S.

2017-07-01

Coherent spatial transport or shuttling of a single electron spin through semiconductor nanostructures is an important ingredient in many spintronic and quantum computing applications. In this work we analyze the possible errors in solid-state quantum computation due to leakage in transporting a single-spin qubit through a semiconductor double quantum dot. In particular, we consider three possible sources of leakage errors associated with such transport: finite ramping times, spin-dependent tunneling rates between quantum dots induced by finite spin-orbit couplings, and the presence of multiple valley states. In each case we present quantitative estimates of the leakage errors, and discuss how they can be minimized. The emphasis of this work is on how to deal with the errors intrinsic to the ideal semiconductor structure, such as leakage due to spin-orbit couplings, rather than on errors due to defects or noise sources. In particular, we show that in order to minimize leakage errors induced by spin-dependent tunnelings, it is necessary to apply pulses to perform certain carefully designed spin rotations. We further develop a formalism that allows one to systematically derive constraints on the pulse shapes and present a few examples to highlight the advantage of such an approach.

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

NASA Technical Reports Server (NTRS)

Geogdzhayev, Igor V.; Cairns, Brian; Mishchenko, Michael I.; Tsigaridis, Kostas; van Noije, Twan

2014-01-01

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3?: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

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.

The GEDI Performance Tool

NASA Astrophysics Data System (ADS)

Hancock, S.; Armston, J.; Tang, H.; Patterson, P. L.; Healey, S. P.; Marselis, S.; Duncanson, L.; Hofton, M. A.; Kellner, J. R.; Luthcke, S. B.; Sun, X.; Blair, J. B.; Dubayah, R.

2017-12-01

NASA's Global Ecosystem Dynamics Investigation will mount a multi-track, full-waveform lidar on the International Space Station (ISS) that is optimised for the measurement of forest canopy height and structure. GEDI will use ten laser tracks, two 10 mJ "power beams" and eight 5 mJ "coverage beams" to produce global (51.5oS to 51.5oN) maps of above ground biomass (AGB), canopy height, vegetation structure and other biophysical parameters. The mission has a requirement to generate a 1 km AGB map with 80% of pixels with ≤ 20% standard error or 20 Mg·ha-1, whichever is greater. To assess performance and compare to mission requirements, an end-to-end simulator has been developed. The simulator brings together tools to propagate the effects of measurement and sampling error on GEDI data products. The simulator allows us to evaluate the impact of instrument performance, ISS orbits, processing algorithms and losses of data that may occur due to clouds, snow, leaf-off conditions, and areas with an insufficient signal-to-noise ratio (SNR). By evaluating the consequences of operational decisions on GEDI data products, this tool provides a quantitative framework for decision-making and mission planning. Here we demonstrate the performance tool by using it to evaluate the trade-off between measurement and sampling error on the 1 km AGB data product. Results demonstrate that the use of coverage beams during the day (lowest GEDI SNR case) over very dense forests (>95% canopy cover) will result in some measurement bias. Omitting these low SNR cases increased the sampling error. Through this an SNR threshold for a given expected canopy cover can be set. The other applications of the performance tool are also discussed, such as assessing the impact of decisions made in the AGB modelling and signal processing stages on the accuracy of final data products.

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.

Combining wrist age and third molars in forensic age estimation: how to calculate the joint age estimate and its error rate in age diagnostics.

PubMed

Gelbrich, Bianca; Frerking, Carolin; Weiss, Sandra; Schwerdt, Sebastian; Stellzig-Eisenhauer, Angelika; Tausche, Eve; Gelbrich, Götz

2015-01-01

Forensic age estimation in living adolescents is based on several methods, e.g. the assessment of skeletal and dental maturation. Combination of several methods is mandatory, since age estimates from a single method are too imprecise due to biological variability. The correlation of the errors of the methods being combined must be known to calculate the precision of combined age estimates. To examine the correlation of the errors of the hand and the third molar method and to demonstrate how to calculate the combined age estimate. Clinical routine radiographs of the hand and dental panoramic images of 383 patients (aged 7.8-19.1 years, 56% female) were assessed. Lack of correlation (r = -0.024, 95% CI = -0.124 to + 0.076, p = 0.64) allows calculating the combined age estimate as the weighted average of the estimates from hand bones and third molars. Combination improved the standard deviations of errors (hand = 0.97, teeth = 1.35 years) to 0.79 years. Uncorrelated errors of the age estimates obtained from both methods allow straightforward determination of the common estimate and its variance. This is also possible when reference data for the hand and the third molar method are established independently from each other, using different samples.

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.

Peak-locking centroid bias in Shack-Hartmann wavefront sensing

NASA Astrophysics Data System (ADS)

Anugu, Narsireddy; Garcia, Paulo J. V.; Correia, Carlos M.

2018-05-01

Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantization, or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field, and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial, and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the antisymmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of ˜7 to values of ≲ 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.

cual-id: Globally Unique, Correctable, and Human-Friendly Sample Identifiers for Comparative Omics Studies.

PubMed

Chase, John H; Bolyen, Evan; Rideout, Jai Ram; Caporaso, J Gregory

2016-01-01

The number of samples in high-throughput comparative "omics" studies is increasing rapidly due to declining experimental costs. To keep sample data and metadata manageable and to ensure the integrity of scientific results as the scale of these projects continues to increase, it is essential that we transition to better-designed sample identifiers. Ideally, sample identifiers should be globally unique across projects, project teams, and institutions; short (to facilitate manual transcription); correctable with respect to common types of transcription errors; opaque, meaning that they do not contain information about the samples; and compatible with existing standards. We present cual-id, a lightweight command line tool that creates, or mints, sample identifiers that meet these criteria without reliance on centralized infrastructure. cual-id allows users to assign universally unique identifiers, or UUIDs, that are globally unique to their samples. UUIDs are too long to be conveniently written on sampling materials, such as swabs or microcentrifuge tubes, however, so cual-id additionally generates human-friendly 4- to 12-character identifiers that map to their UUIDs and are unique within a project. By convention, we use "cual-id" to refer to the software, "CualID" to refer to the short, human-friendly identifiers, and "UUID" to refer to the globally unique identifiers. CualIDs are used by humans when they manually write or enter identifiers, while the longer UUIDs are used by computers to unambiguously reference a sample. Finally, cual-id optionally generates printable label sticker sheets containing Code 128 bar codes and CualIDs for labeling of sample collection and processing materials. IMPORTANCE The adoption of identifiers that are globally unique, correctable, and easily handwritten or manually entered into a computer will be a major step forward for sample tracking in comparative omics studies. As the fields transition to more-centralized sample management, for example, across labs within an institution, across projects funded under a common program, or in systems designed to facilitate meta- and/or integrated analysis, sample identifiers generated with cual-id will not need to change; thus, costly and error-prone updating of data and metadata identifiers will be avoided. Further, using cual-id will ensure that transcription errors in sample identifiers do not require the discarding of otherwise-useful samples that may have been expensive to obtain. Finally, cual-id is simple to install and use and is free for all use. No centralized infrastructure is required to ensure global uniqueness, so it is feasible for any lab to get started using these identifiers within their existing infrastructure.

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…

Understanding Effective Diameter and Its Application to Terrestrial Radiation in Ice Clouds

NASA Technical Reports Server (NTRS)

Mitchell, D. L.; Lawson, R. P.; Baker, B.

2011-01-01

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, D(sub e), and their cloud water content (CWC), henceforth referred to as the D(sub e)-CWC assumption. This study challenges this assumption, showing that while the D(sub e)-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De less than 60 m, which is where this D(sub e)-CWC assumption appears poorest. Treating optical properties solely in terms of D(sub e) and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the D(sub e)-CWC assumption breaks down, ice cloud optical properties appear to depend on D(sub e), IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al., 2005 database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the D(sub e)-IWC assumption was made possible by using MADA. MADA allows one to approximate the contribution of photon tunneling to absorption relative to other optical processes, which reveals that part of the error regarding the D(sub e)-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (DELTA L) due to absorption, the domain where the D(sub e)-IWC assumption is weakest was described in terms of D(sub e) and DELTA L.

Understanding effective diameter and its application to terrestrial radiation in ice clouds

NASA Astrophysics Data System (ADS)

Mitchell, D. L.; Lawson, R. P.; Baker, B.

2010-12-01

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, De, and their cloud water content (CWC), henceforth referred to as the De-CWC assumption. This study challenges this assumption, showing that while the De-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De<∼60 μm, which is where this De-CWC assumption appears poorest. Treating optical properties solely in terms of De and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the De-CWC assumption breaks down, ice cloud optical properties appear to depend on De, IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al. (2005) database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the De-IWC assumption was made possible by using MADA. MADA allows one to separate the photon tunneling process from the other optical processes, which reveals that much of the error regarding the De-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (ΔL) due to absorption, the domain where the De-IWC assumption is weakest was described in terms of De and ΔL.

Towards an Integrated QR Code Biosensor: Light-Driven Sample Acquisition and Bacterial Cellulose Paper Substrate.

PubMed

Yuan, Mingquan; Jiang, Qisheng; Liu, Keng-Ku; Singamaneni, Srikanth; Chakrabartty, Shantanu

2018-06-01

This paper addresses two key challenges toward an integrated forward error-correcting biosensor based on our previously reported self-assembled quick-response (QR) code. The first challenge involves the choice of the paper substrate for printing and self-assembling the QR code. We have compared four different substrates that includes regular printing paper, Whatman filter paper, nitrocellulose membrane and lab synthesized bacterial cellulose. We report that out of the four substrates bacterial cellulose outperforms the others in terms of probe (gold nanorods) and ink retention capability. The second challenge involves remote activation of the analyte sampling and the QR code self-assembly process. In this paper, we use light as a trigger signal and a graphite layer as a light-absorbing material. The resulting change in temperature due to infrared absorption leads to a temperature gradient that then exerts a diffusive force driving the analyte toward the regions of self-assembly. The working principle has been verified in this paper using assembled biosensor prototypes where we demonstrate higher sample flow rate due to light induced thermal gradients.

Impact of hindcast length on estimates of seasonal climate predictability.

PubMed

Shi, W; Schaller, N; MacLeod, D; Palmer, T N; Weisheimer, A

2015-03-16

It has recently been argued that single-model seasonal forecast ensembles are overdispersive, implying that the real world is more predictable than indicated by estimates of so-called perfect model predictability, particularly over the North Atlantic. However, such estimates are based on relatively short forecast data sets comprising just 20 years of seasonal predictions. Here we study longer 40 year seasonal forecast data sets from multimodel seasonal forecast ensemble projects and show that sampling uncertainty due to the length of the hindcast periods is large. The skill of forecasting the North Atlantic Oscillation during winter varies within the 40 year data sets with high levels of skill found for some subperiods. It is demonstrated that while 20 year estimates of seasonal reliability can show evidence of overdispersive behavior, the 40 year estimates are more stable and show no evidence of overdispersion. Instead, the predominant feature on these longer time scales is underdispersion, particularly in the tropics. Predictions can appear overdispersive due to hindcast length sampling errorLonger hindcasts are more robust and underdispersive, especially in the tropicsTwenty hindcasts are an inadequate sample size to assess seasonal forecast skill.

Matrix effect and correction by standard addition in quantitative liquid chromatographic-mass spectrometric analysis of diarrhetic shellfish poisoning toxins.

PubMed

Ito, Shinya; Tsukada, Katsuo

2002-01-11

An evaluation of the feasibility of liquid chromatography-mass spectrometry (LC-MS) with atmospheric pressure ionization was made for quantitation of four diarrhetic shellfish poisoning toxins, okadaic acid, dinophysistoxin-1, pectenotoxin-6 and yessotoxin in scallops. When LC-MS was applied to the analysis of scallop extracts, large signal suppressions were observed due to coeluting substances from the column. To compensate for these matrix signal suppressions, the standard addition method was applied. First, the sample was analyzed and then the sample involving the addition of calibration standards is analyzed. Although this method requires two LC-MS runs per analysis, effective correction of quantitative errors was found.

Estimate of higher order ionospheric errors in GNSS positioning

NASA Astrophysics Data System (ADS)

Hoque, M. Mainul; Jakowski, N.

2008-10-01

Precise navigation and positioning using GPS/GLONASS/Galileo require the ionospheric propagation errors to be accurately determined and corrected for. Current dual-frequency method of ionospheric correction ignores higher order ionospheric errors such as the second and third order ionospheric terms in the refractive index formula and errors due to bending of the signal. The total electron content (TEC) is assumed to be same at two GPS frequencies. All these assumptions lead to erroneous estimations and corrections of the ionospheric errors. In this paper a rigorous treatment of these problems is presented. Different approximation formulas have been proposed to correct errors due to excess path length in addition to the free space path length, TEC difference at two GNSS frequencies, and third-order ionospheric term. The GPS dual-frequency residual range errors can be corrected within millimeter level accuracy using the proposed correction formulas.

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.

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

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.

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.

A Method for Developing Standard Patient Education Program.

PubMed

Lura, Carolina Bryne; Hauch, Sophie Misser Pallesgaard; Gøeg, Kirstine Rosenbeck; Pape-Haugaard, Louise

2018-01-01

In Denmark, patients being treated on Haematology Outpatients Departments get instructed to self-manage their blood sample collection from Central Venous Catheter (CVC). However, this is a complex and risky procedure, which can jeopardize patient safety. The aim of the study was to suggest a method for developing standard digital patient education programs for patients in self-administration of blood samples drawn from CVC. The Design Science Research Paradigm was used to develop a digital patient education program, called PAVIOSY, to increase patient safety during execution of the blood sample collection procedure by using videos for teaching as well as procedural support. A step-by-step guide was developed and used as basis for making the videos. Quality assurance through evaluation with a nurse was conducted on both the step-by-step guide and the videos. The quality assurance evaluation of the videos showed; 1) Errors due to the order of the procedure can be determined by reviewing the videos despite that the guide was followed. 2) Videos can be used to identify errors - important for patient safety - in the procedure, which are not identifiable in a written script. To ensure correct clinical content of the educational patient system, health professionals must be engaged early in the development of content and design phase.

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.

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.

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.

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)

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.

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.

Airplane wing vibrations due to atmospheric turbulence

NASA Technical Reports Server (NTRS)

Pastel, R. L.; Caruthers, J. E.; Frost, W.

1981-01-01

The magnitude of error introduced due to wing vibration when measuring atmospheric turbulence with a wind probe mounted at the wing tip was studied. It was also determined whether accelerometers mounted on the wing tip are needed to correct this error. A spectrum analysis approach is used to determine the error. Estimates of the B-57 wing characteristics are used to simulate the airplane wing, and von Karman's cross spectrum function is used to simulate atmospheric turbulence. It was found that wing vibration introduces large error in measured spectra of turbulence in the frequency's range close to the natural frequencies of the wing.

Comparison of Interferometric Time-Series Analysis Techniques with Implications for Future Mission Design

NASA Astrophysics Data System (ADS)

Werner, C. L.; Wegmuller, U.; Strozzi, T.; Wiesmann, A.

2006-12-01

Principle contributors to the noise in differential SAR interferograms are temporal phase stability of the surface, geometry relating to baseline and surface slope, and propagation path delay variations due to tropospheric water vapor and the ionosphere. Time series analysis of multiple interferograms generated from a stack of SAR SLC images seeks to determine the deformation history of the surface while reducing errors. Only those scatterers within a resolution element that are stable and coherent for each interferometric pair contribute to the desired deformation signal. Interferograms with baselines exceeding 1/3 the critical baseline have substantial geometrical decorrelation for distributed targets. Short baseline pairs with multiple reference scenes can be combined using least-squares estimation to obtain a global deformation solution. Alternately point-like persistent scatterers can be identified in scenes that do not exhibit geometrical decorrelation associated with large baselines. In this approach interferograms are formed from a stack of SAR complex images using a single reference scene. Stable distributed scatter pixels are excluded however due to the presence of large baselines. We apply both point- based and short-baseline methodologies and compare results for a stack of fine-beam Radarsat data acquired in 2002-2004 over a rapidly subsiding oil field near Lost Hills, CA. We also investigate the density of point-like scatters with respect to image resolution. The primary difficulty encountered when applying time series methods is phase unwrapping errors due to spatial and temporal gaps. Phase unwrapping requires sufficient spatial and temporal sampling. Increasing the SAR range bandwidth increases the range resolution as well as increasing the critical interferometric baseline that defines the required satellite orbital tube diameter. Sufficient spatial sampling also permits unwrapping because of the reduced phase/pixel gradient. Short time intervals further reduce the differential phase due to deformation when the deformation is continuous. Lower frequency systems (L- vs. C-Band) substantially improve the ability to unwrap the phase correctly by directly reducing both interferometric phase amplitude and temporal decorrelation.

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.;

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

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

Chowdhary, Kenny; Najm, Habib N.

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

A simple differential steady-state method to measure the thermal conductivity of solid bulk materials with high accuracy.

PubMed

Kraemer, D; Chen, G

2014-02-01

Accurate measurements of thermal conductivity are of great importance for materials research and development. Steady-state methods determine thermal conductivity directly from the proportionality between heat flow and an applied temperature difference (Fourier Law). Although theoretically simple, in practice, achieving high accuracies with steady-state methods is challenging and requires rather complex experimental setups due to temperature sensor uncertainties and parasitic heat loss. We developed a simple differential steady-state method in which the sample is mounted between an electric heater and a temperature-controlled heat sink. Our method calibrates for parasitic heat losses from the electric heater during the measurement by maintaining a constant heater temperature close to the environmental temperature while varying the heat sink temperature. This enables a large signal-to-noise ratio which permits accurate measurements of samples with small thermal conductance values without an additional heater calibration measurement or sophisticated heater guards to eliminate parasitic heater losses. Additionally, the differential nature of the method largely eliminates the uncertainties of the temperature sensors, permitting measurements with small temperature differences, which is advantageous for samples with high thermal conductance values and/or with strongly temperature-dependent thermal conductivities. In order to accelerate measurements of more than one sample, the proposed method allows for measuring several samples consecutively at each temperature measurement point without adding significant error. We demonstrate the method by performing thermal conductivity measurements on commercial bulk thermoelectric Bi2Te3 samples in the temperature range of 30-150 °C with an error below 3%.

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE PAGES

Chowdhary, Kenny; Najm, Habib N.

2016-04-13

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Deconvolution of continuous paleomagnetic data from pass-through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization

NASA Astrophysics Data System (ADS)

Oda, Hirokuni; Xuan, Chuang

2014-10-01

development of pass-through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long-core samples. The output of pass-through measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor response. Although several studies could restore high-resolution paleomagnetic signal through deconvolution of pass-through measurement, difficulties in accurately measuring the magnetometer sensor response have hindered the application of deconvolution. We acquired reliable sensor response of an SRM at the Oregon State University based on repeated measurements of a precisely fabricated magnetic point source. In addition, we present an improved deconvolution algorithm based on Akaike's Bayesian Information Criterion (ABIC) minimization, incorporating new parameters to account for errors in sample measurement position and length. The new algorithm was tested using synthetic data constructed by convolving "true" paleomagnetic signal containing an "excursion" with the sensor response. Realistic noise was added to the synthetic measurement using Monte Carlo method based on measurement noise distribution acquired from 200 repeated measurements of a u-channel sample. Deconvolution of 1000 synthetic measurements with realistic noise closely resembles the "true" magnetization, and successfully restored fine-scale magnetization variations including the "excursion." Our analyses show that inaccuracy in sample measurement position and length significantly affects deconvolution estimation, and can be resolved using the new deconvolution algorithm. Optimized deconvolution of 20 repeated measurements of a u-channel sample yielded highly consistent deconvolution results and estimates of error in sample measurement position and length, demonstrating the reliability of the new deconvolution algorithm for real pass-through measurements.

Asymmetric Memory Circuit Would Resist Soft Errors

NASA Technical Reports Server (NTRS)

Buehler, Martin G.; Perlman, Marvin

1990-01-01

Some nonlinear error-correcting codes more efficient in presence of asymmetry. Combination of circuit-design and coding concepts expected to make integrated-circuit random-access memories more resistant to "soft" errors (temporary bit errors, also called "single-event upsets" due to ionizing radiation). Integrated circuit of new type made deliberately more susceptible to one kind of bit error than to other, and associated error-correcting code adapted to exploit this asymmetry in error probabilities.

Uncertainties in stormwater runoff data collection from a small urban catchment, Southeast China.

PubMed

Huang, Jinliang; Tu, Zhenshun; Du, Pengfei; Lin, Jie; Li, Qingsheng

2010-01-01

Monitoring data are often used to identify stormwater runoff characteristics and in stormwater runoff modelling without consideration of their inherent uncertainties. Integrated with discrete sample analysis and error propagation analysis, this study attempted to quantify the uncertainties of discrete chemical oxygen demand (COD), total suspended solids (TSS) concentration, stormwater flowrate, stormwater event volumes, COD event mean concentration (EMC), and COD event loads in terms of flow measurement, sample collection, storage and laboratory analysis. The results showed that the uncertainties due to sample collection, storage and laboratory analysis of COD from stormwater runoff are 13.99%, 19.48% and 12.28%. Meanwhile, flow measurement uncertainty was 12.82%, and the sample collection uncertainty of TSS from stormwater runoff was 31.63%. Based on the law of propagation of uncertainties, the uncertainties regarding event flow volume, COD EMC and COD event loads were quantified as 7.03%, 10.26% and 18.47%.

Direct Analysis of Samples of Various Origin and Composition Using Specific Types of Mass Spectrometry.

PubMed

Byliński, Hubert; Gębicki, Jacek; Dymerski, Tomasz; Namieśnik, Jacek

2017-07-04

One of the major sources of error that occur during chemical analysis utilizing the more conventional and established analytical techniques is the possibility of losing part of the analytes during the sample preparation stage. Unfortunately, this sample preparation stage is required to improve analytical sensitivity and precision. Direct techniques have helped to shorten or even bypass the sample preparation stage; and in this review, we comment of some of the new direct techniques that are mass-spectrometry based. The study presents information about the measurement techniques using mass spectrometry, which allow direct sample analysis, without sample preparation or limiting some pre-concentration steps. MALDI - MS, PTR - MS, SIFT - MS, DESI - MS techniques are discussed. These solutions have numerous applications in different fields of human activity due to their interesting properties. The advantages and disadvantages of these techniques are presented. The trends in development of direct analysis using the aforementioned techniques are also presented.

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…

Variability And Uncertainty Analysis Of Contaminant Transport Model Using Fuzzy Latin Hypercube Sampling Technique

NASA Astrophysics Data System (ADS)

Kumar, V.; Nayagum, D.; Thornton, S.; Banwart, S.; Schuhmacher2, M.; Lerner, D.

2006-12-01

Characterization of uncertainty associated with groundwater quality models is often of critical importance, as for example in cases where environmental models are employed in risk assessment. Insufficient data, inherent variability and estimation errors of environmental model parameters introduce uncertainty into model predictions. However, uncertainty analysis using conventional methods such as standard Monte Carlo sampling (MCS) may not be efficient, or even suitable, for complex, computationally demanding models and involving different nature of parametric variability and uncertainty. General MCS or variant of MCS such as Latin Hypercube Sampling (LHS) assumes variability and uncertainty as a single random entity and the generated samples are treated as crisp assuming vagueness as randomness. Also when the models are used as purely predictive tools, uncertainty and variability lead to the need for assessment of the plausible range of model outputs. An improved systematic variability and uncertainty analysis can provide insight into the level of confidence in model estimates, and can aid in assessing how various possible model estimates should be weighed. The present study aims to introduce, Fuzzy Latin Hypercube Sampling (FLHS), a hybrid approach of incorporating cognitive and noncognitive uncertainties. The noncognitive uncertainty such as physical randomness, statistical uncertainty due to limited information, etc can be described by its own probability density function (PDF); whereas the cognitive uncertainty such estimation error etc can be described by the membership function for its fuzziness and confidence interval by ?-cuts. An important property of this theory is its ability to merge inexact generated data of LHS approach to increase the quality of information. The FLHS technique ensures that the entire range of each variable is sampled with proper incorporation of uncertainty and variability. A fuzzified statistical summary of the model results will produce indices of sensitivity and uncertainty that relate the effects of heterogeneity and uncertainty of input variables to model predictions. The feasibility of the method is validated to assess uncertainty propagation of parameter values for estimation of the contamination level of a drinking water supply well due to transport of dissolved phenolics from a contaminated site in the UK.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

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.

Errors in clinical laboratories or errors in laboratory medicine?

PubMed

Plebani, Mario

2006-01-01

Laboratory testing is a highly complex process and, although laboratory services are relatively safe, they are not as safe as they could or should be. Clinical laboratories have long focused their attention on quality control methods and quality assessment programs dealing with analytical aspects of testing. However, a growing body of evidence accumulated in recent decades demonstrates that quality in clinical laboratories cannot be assured by merely focusing on purely analytical aspects. The more recent surveys on errors in laboratory medicine conclude that in the delivery of laboratory testing, mistakes occur more frequently before (pre-analytical) and after (post-analytical) the test has been performed. Most errors are due to pre-analytical factors (46-68.2% of total errors), while a high error rate (18.5-47% of total errors) has also been found in the post-analytical phase. Errors due to analytical problems have been significantly reduced over time, but there is evidence that, particularly for immunoassays, interference may have a serious impact on patients. A description of the most frequent and risky pre-, intra- and post-analytical errors and advice on practical steps for measuring and reducing the risk of errors is therefore given in the present paper. Many mistakes in the Total Testing Process are called "laboratory errors", although these may be due to poor communication, action taken by others involved in the testing process (e.g., physicians, nurses and phlebotomists), or poorly designed processes, all of which are beyond the laboratory's control. Likewise, there is evidence that laboratory information is only partially utilized. A recent document from the International Organization for Standardization (ISO) recommends a new, broader definition of the term "laboratory error" and a classification of errors according to different criteria. In a modern approach to total quality, centered on patients' needs and satisfaction, the risk of errors and mistakes in pre- and post-examination steps must be minimized to guarantee the total quality of laboratory services.

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks

PubMed Central

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-01-01

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C/2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C/2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi’s model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments. PMID:29401668

The Application of Social Characteristic and L1 Optimization in the Error Correction for Network Coding in Wireless Sensor Networks.

PubMed

Zhang, Guangzhi; Cai, Shaobin; Xiong, Naixue

2018-02-03

One of the remarkable challenges about Wireless Sensor Networks (WSN) is how to transfer the collected data efficiently due to energy limitation of sensor nodes. Network coding will increase network throughput of WSN dramatically due to the broadcast nature of WSN. However, the network coding usually propagates a single original error over the whole network. Due to the special property of error propagation in network coding, most of error correction methods cannot correct more than C /2 corrupted errors where C is the max flow min cut of the network. To maximize the effectiveness of network coding applied in WSN, a new error-correcting mechanism to confront the propagated error is urgently needed. Based on the social network characteristic inherent in WSN and L1 optimization, we propose a novel scheme which successfully corrects more than C /2 corrupted errors. What is more, even if the error occurs on all the links of the network, our scheme also can correct errors successfully. With introducing a secret channel and a specially designed matrix which can trap some errors, we improve John and Yi's model so that it can correct the propagated errors in network coding which usually pollute exactly 100% of the received messages. Taking advantage of the social characteristic inherent in WSN, we propose a new distributed approach that establishes reputation-based trust among sensor nodes in order to identify the informative upstream sensor nodes. With referred theory of social networks, the informative relay nodes are selected and marked with high trust value. The two methods of L1 optimization and utilizing social characteristic coordinate with each other, and can correct the propagated error whose fraction is even exactly 100% in WSN where network coding is performed. The effectiveness of the error correction scheme is validated through simulation experiments.

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

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,…

Balancing the books - a statistical theory of prospective budgets in Earth System science

NASA Astrophysics Data System (ADS)

O'Kane, J. Philip

An honest declaration of the error in a mass, momentum or energy balance, ɛ, simply raises the question of its acceptability: "At what value of ɛ is the attempted balance to be rejected?" Answering this question requires a reference quantity against which to compare ɛ. This quantity must be a mathematical function of all the data used in making the balance. To deliver this function, a theory grounded in a workable definition of acceptability is essential. A distinction must be drawn between a retrospective balance and a prospective budget in relation to any natural space-filling body. Balances look to the past; budgets look to the future. The theory is built on the application of classical sampling theory to the measurement and closure of a prospective budget. It satisfies R.A. Fisher's "vital requirement that the actual and physical conduct of experiments should govern the statistical procedure of their interpretation". It provides a test, which rejects, or fails to reject, the hypothesis that the closing error on the budget, when realised, was due to sampling error only. By increasing the number of measurements, the discrimination of the test can be improved, controlling both the precision and accuracy of the budget and its components. The cost-effective design of such measurement campaigns is discussed briefly. This analysis may also show when campaigns to close a budget on a particular space-filling body are not worth the effort for either scientific or economic reasons. Other approaches, such as those based on stochastic processes, lack this finality, because they fail to distinguish between different types of error in the mismatch between a set of realisations of the process and the measured data.

Explanation of Two Anomalous Results in Statistical Mediation Analysis.

PubMed

Fritz, Matthew S; Taylor, Aaron B; Mackinnon, David P

2012-01-01

Previous studies of different methods of testing mediation models have consistently found two anomalous results. The first result is elevated Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap tests not found in nonresampling tests or in resampling tests that did not include a bias correction. This is of special concern as the bias-corrected bootstrap is often recommended and used due to its higher statistical power compared with other tests. The second result is statistical power reaching an asymptote far below 1.0 and in some conditions even declining slightly as the size of the relationship between X and M , a , increased. Two computer simulations were conducted to examine these findings in greater detail. Results from the first simulation found that the increased Type I error rates for the bias-corrected and accelerated bias-corrected bootstrap are a function of an interaction between the size of the individual paths making up the mediated effect and the sample size, such that elevated Type I error rates occur when the sample size is small and the effect size of the nonzero path is medium or larger. Results from the second simulation found that stagnation and decreases in statistical power as a function of the effect size of the a path occurred primarily when the path between M and Y , b , was small. Two empirical mediation examples are provided using data from a steroid prevention and health promotion program aimed at high school football players (Athletes Training and Learning to Avoid Steroids; Goldberg et al., 1996), one to illustrate a possible Type I error for the bias-corrected bootstrap test and a second to illustrate a loss in power related to the size of a . Implications of these findings are discussed.

Topographic analysis of individual activation patterns in medial frontal cortex in schizophrenia

PubMed Central

Stern, Emily R.; Welsh, Robert C.; Fitzgerald, Kate D.; Taylor, Stephan F.

2009-01-01

Individual variability in the location of neural activations poses a unique problem for neuroimaging studies employing group averaging techniques to investigate the neural bases of cognitive and emotional functions. This may be especially challenging for studies examining patient groups, which often have limited sample sizes and increased intersubject variability. In particular, medial frontal cortex (MFC) dysfunction is thought to underlie performance monitoring dysfunction among patients with previous studies using group averaging to have yielded conflicting results. schizophrenia, yet compare schizophrenic patients to controls To examine individual activations in MFC associated with two aspects of performance monitoring, interference and error processing, functional magnetic resonance imaging (fMRI) data were acquired while 17 patients with schizophrenia and 21 healthy controls performed an event-related version of the multi-source interference task. Comparisons of averaged data revealed few differences between the groups. By contrast, topographic analysis of individual activations for errors showed that control subjects exhibited activations spanning across both posterior and anterior regions of MFC while patients primarily activated posterior MFC, possibly reflecting an impaired emotional response to errors in schizophrenia. This discrepancy between topographic and group-averaged results may be due to the significant dispersion among individual activations, particularly among healthy controls, highlighting the importance of considering intersubject variability when interpreting the medial frontal response to error commission. PMID:18819107

Unified Model for the Overall Efficiency of Inlets Sampling from Horizontal Aerosol Flows

NASA Astrophysics Data System (ADS)

Hangal, Sunil Pralhad

When sampling aerosols from ambient or industrial air environments, the sampled aerosol must be representative of the aerosol in the free stream. The changes that occur during sampling must be assessed quantitatively so that sampling errors can be compensated for. In this study, unified models have been developed for the overall efficiency of tubular sharp-edged inlets sampling from horizontal aerosol flows oriented at 0 to 90^circ relative to the wind direction in the vertical (pitch) and horizontal plane(yaw). In the unified model, based on experimental data, the aspiration efficiency is represented by a single equation with different inertial parameters at 0 to 60^ circ and 45 to 90^circ . Tnt transmission efficiency is separated into two components: one due to gravitational settling in the boundary layer and the other due to impaction. The gravitational settling component is determined by extending a previously developed isoaxial sampling model to nonisoaxial sampling. The impaction component is determined by a new model that quantifies the particle losses caused by wall impaction. The model also quantifies the additional particle losses resulting from turbulent motion in the vena contracta which is formed in the inlet when the inlet velocity is higher than the wind velocity. When sampling aerosols in ambient or industrial environments with an inlet, small changes in wind direction or physical constraints in positioning the inlet in the system necessitates the assessment of sampling efficiency in both the vertical and horizontal plane. The overall sampling efficiency of tubular inlets has been experimentally investigated in yaw and pitch orientations at 0 to 20 ^circ from horizontal aerosol flows using a wind tunnel facility. The model for overall sampling efficiency has been extended to include both yaw and pitch sampling based on the new data. In this model, the difference between yaw and pitch is expressed by the effect of gravity on the impaction process inside the inlet described by a newly developed gravity effect angle. At yaw, the gravity effect angle on the wall impaction process does not change with sampling angle. At pitch, the gravity effect on the impaction process results in particle loss increase for upward and decrease for downward sampling. Using the unified model, graphical representations have been developed for sampling at small angles. These can be used in the field to determine the overall sampling efficiency of inlets at several operating conditions and the operating conditions that result in an acceptable sampling error. Pitch and diameter factors have been introduced for relating the efficiency values over a wide range of conditions to those of a reference condition. The pitch factor determines the overall sampling efficiency at pitch from yaw values, and the diameter factor determines the overall sampling efficiency at different inlet diameters.

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.

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.

Errors in Bibliographic Citations: A Continuing Problem.

ERIC Educational Resources Information Center

Sweetland, James H.

1989-01-01

Summarizes studies examining citation errors and illustrates errors resulting from a lack of standardization, misunderstanding of foreign languages, failure to examine the document cited, and general lack of training in citation norms. It is argued that the failure to detect and correct citation errors is due to diffusion of responsibility in the…

Accounting for measurement error: a critical but often overlooked process.

PubMed

Harris, Edward F; Smith, Richard N

2009-12-01

Due to instrument imprecision and human inconsistencies, measurements are not free of error. Technical error of measurement (TEM) is the variability encountered between dimensions when the same specimens are measured at multiple sessions. A goal of a data collection regimen is to minimise TEM. The few studies that actually quantify TEM, regardless of discipline, report that it is substantial and can affect results and inferences. This paper reviews some statistical approaches for identifying and controlling TEM. Statistically, TEM is part of the residual ('unexplained') variance in a statistical test, so accounting for TEM, which requires repeated measurements, enhances the chances of finding a statistically significant difference if one exists. The aim of this paper was to review and discuss common statistical designs relating to types of error and statistical approaches to error accountability. This paper addresses issues of landmark location, validity, technical and systematic error, analysis of variance, scaled measures and correlation coefficients in order to guide the reader towards correct identification of true experimental differences. Researchers commonly infer characteristics about populations from comparatively restricted study samples. Most inferences are statistical and, aside from concerns about adequate accounting for known sources of variation with the research design, an important source of variability is measurement error. Variability in locating landmarks that define variables is obvious in odontometrics, cephalometrics and anthropometry, but the same concerns about measurement accuracy and precision extend to all disciplines. With increasing accessibility to computer-assisted methods of data collection, the ease of incorporating repeated measures into statistical designs has improved. Accounting for this technical source of variation increases the chance of finding biologically true differences when they exist.

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

2004-01-01

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

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,…

To err is human nature. Can transfusion errors due to human factors ever be eliminated?

PubMed

Lau, F Y; Cheng, G

2001-11-01

Fatal hemolytic transfusion reaction due to ABO incompatibility occurs mainly as a result of clerical errors. Blood sample drawn from the wrong patient and labeled as another patient's specimen will not be detected by the blood bank unless there is a previous ABO grouping result. In Hong Kong, we had designed a transfusion wristband system--portable barcode scanner system to detect such clerical errors. The system was well accepted by the house staff and had prevented two BO mismatched transfusion. Other current system of patient's identification may have similar results, but the wristband system has the advantages of being simple, inexpensive and easy to implement. The Hong Kong Government is planning to replace the personal identity card for all citizens with an electronic smart card by 2003. If the new card contains the person's detailed red cell phenotypes in digital code, then the phenotypes of all blood donors and admitted patients will be readily available. It is feasible to issue phenotype-matched blood to patients without any need of pre-transfusion testing, therefore eliminating mismatched transfusions for most patients. Our pilot study of 474 patients showed that the system was safe and up to 98% of admitted patients could be transfused without delays. Patients with rare phenotypes, visitors or illegal immigrants may still need pre-transfusion antibody screen, but if most patients can be issued blood units without testings, the potential savings in health care amount to US$14 million/year.

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.

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.

The effects of sampling frequency on the climate statistics of the European Centre for Medium-Range Weather Forecasts

NASA Astrophysics Data System (ADS)

Phillips, Thomas J.; Gates, W. Lawrence; Arpe, Klaus

1992-12-01

The effects of sampling frequency on the first- and second-moment statistics of selected European Centre for Medium-Range Weather Forecasts (ECMWF) model variables are investigated in a simulation of "perpetual July" with a diurnal cycle included and with surface and atmospheric fields saved at hourly intervals. The shortest characteristic time scales (as determined by the e-folding time of lagged autocorrelation functions) are those of ground heat fluxes and temperatures, precipitation and runoff, convective processes, cloud properties, and atmospheric vertical motion, while the longest time scales are exhibited by soil temperature and moisture, surface pressure, and atmospheric specific humidity, temperature, and wind. The time scales of surface heat and momentum fluxes and of convective processes are substantially shorter over land than over oceans. An appropriate sampling frequency for each model variable is obtained by comparing the estimates of first- and second-moment statistics determined at intervals ranging from 2 to 24 hours with the "best" estimates obtained from hourly sampling. Relatively accurate estimation of first- and second-moment climate statistics (10% errors in means, 20% errors in variances) can be achieved by sampling a model variable at intervals that usually are longer than the bandwidth of its time series but that often are shorter than its characteristic time scale. For the surface variables, sampling at intervals that are nonintegral divisors of a 24-hour day yields relatively more accurate time-mean statistics because of a reduction in errors associated with aliasing of the diurnal cycle and higher-frequency harmonics. The superior estimates of first-moment statistics are accompanied by inferior estimates of the variance of the daily means due to the presence of systematic biases, but these probably can be avoided by defining a different measure of low-frequency variability. Estimates of the intradiurnal variance of accumulated precipitation and surface runoff also are strongly impacted by the length of the storage interval. In light of these results, several alternative strategies for storage of the EMWF model variables are recommended.

Characterization of Full Set Material Constants and Their Temperature Dependence for Piezoelectric Materials Using Resonant Ultrasound Spectroscopy

PubMed Central

Tang, Liguo; Cao, Wenwu

2016-01-01

During the operation of high power electromechanical devices, a temperature rise is unavoidable due to mechanical and electrical losses, causing the degradation of device performance. In order to evaluate such degradations using computer simulations, full matrix material properties at elevated temperatures are needed as inputs. It is extremely difficult to measure such data for ferroelectric materials due to their strong anisotropic nature and property variation among samples of different geometries. Because the degree of depolarization is boundary condition dependent, data obtained by the IEEE (Institute of Electrical and Electronics Engineers) impedance resonance technique, which requires several samples with drastically different geometries, usually lack self-consistency. The resonant ultrasound spectroscopy (RUS) technique allows the full set material constants to be measured using only one sample, which can eliminate errors caused by sample to sample variation. A detailed RUS procedure is demonstrated here using a lead zirconate titanate (PZT-4) piezoceramic sample. In the example, the complete set of material constants was measured from room temperature to 120 °C. Measured free dielectric constants and  were compared with calculated ones based on the measured full set data, and piezoelectric constants d15 and d33 were also calculated using different formulas. Excellent agreement was found in the entire range of temperatures, which confirmed the self-consistency of the data set obtained by the RUS. PMID:27168336

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...

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.

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.

Evaluating the design of an earth radiation budget instrument with system simulations. Part 2: Minimization of instantaneous sampling errors for CERES-I

NASA Technical Reports Server (NTRS)

Stowe, Larry; Hucek, Richard; Ardanuy, Philip; Joyce, Robert

1994-01-01

Much of the new record of broadband earth radiation budget satellite measurements to be obtained during the late 1990s and early twenty-first century will come from the dual-radiometer Clouds and Earth's Radiant Energy System Instrument (CERES-I) flown aboard sun-synchronous polar orbiters. Simulation studies conducted in this work for an early afternoon satellite orbit indicate that spatial root-mean-square (rms) sampling errors of instantaneous CERES-I shortwave flux estimates will range from about 8.5 to 14.0 W/m on a 2.5 deg latitude and longitude grid resolution. Rms errors in longwave flux estimates are only about 20% as large and range from 1.5 to 3.5 W/sq m. These results are based on an optimal cross-track scanner design that includes 50% footprint overlap to eliminate gaps in the top-of-the-atmosphere coverage, and a 'smallest' footprint size to increase the ratio in the number of observations lying within to the number of observations lying on grid area boundaries. Total instantaneous measurement error also depends on the variability of anisotropic reflectance and emission patterns and on retrieval methods used to generate target area fluxes. Three retrieval procedures from both CERES-I scanners (cross-track and rotating azimuth plane) are used. (1) The baseline Earth Radiaton Budget Experiment (ERBE) procedure, which assumes that errors due to the use of mean angular dependence models (ADMs) in the radiance-to-flux inversion process nearly cancel when averaged over grid areas. (2) To estimate N, instantaneous ADMs are estimated from the multiangular, collocated observations of the two scanners. These observed models replace the mean models in computation of satellite flux estimates. (3) The scene flux approach, conducts separate target-area retrievals for each ERBE scene category and combines their results using area weighting by scene type. The ERBE retrieval performs best when the simulated radiance field departs from the ERBE mean models by less than 10%. For larger perturbations, both the scene flux and collocation methods produce less error than the ERBE retrieval. The scene flux technique is preferable, however, because it involves fewer restrictive assumptions.

Accounting for Dependence Induced by Weighted KNN Imputation in Paired Samples, Motivated by a Colorectal Cancer Study

PubMed Central

Suyundikov, Anvar; Stevens, John R.; Corcoran, Christopher; Herrick, Jennifer; Wolff, Roger K.; Slattery, Martha L.

2015-01-01

Missing data can arise in bioinformatics applications for a variety of reasons, and imputation methods are frequently applied to such data. We are motivated by a colorectal cancer study where miRNA expression was measured in paired tumor-normal samples of hundreds of patients, but data for many normal samples were missing due to lack of tissue availability. We compare the precision and power performance of several imputation methods, and draw attention to the statistical dependence induced by K-Nearest Neighbors (KNN) imputation. This imputation-induced dependence has not previously been addressed in the literature. We demonstrate how to account for this dependence, and show through simulation how the choice to ignore or account for this dependence affects both power and type I error rate control. PMID:25849489

Fiber optics frequency comb enabled linear optical sampling with operation wavelength range extension.

PubMed

Liao, Ruolin; Wu, Zhichao; Fu, Songnian; Zhu, Shengnan; Yu, Zhe; Tang, Ming; Liu, Deming

2018-02-01

Although the linear optical sampling (LOS) technique is powerful enough to characterize various advanced modulation formats with high symbol rates, the central wavelength of a pulsed local oscillator (LO) needs to be carefully set according to that of the signal under test, due to the coherent mixing operation. Here, we experimentally demonstrate wideband LOS enabled by a fiber optics frequency comb (FOFC). Meanwhile, when the broadband FOFC acts as the pulsed LO, we propose a scheme to mitigate the enhanced sampling error arising in the non-ideal response of a balanced photodetector. Finally, precise characterizations of arbitrary 128 Gbps PDM-QPSK wavelength channels from 1550 to 1570 nm are successfully achieved, when a 101.3 MHz frequency spaced comb with a 3 dB spectral power ripple of 20 nm is used.

Preanalytical requirements of urinalysis

PubMed Central

Delanghe, Joris; Speeckaert, Marijn

2014-01-01

Urine may be a waste product, but it contains an enormous amount of information. Well-standardized procedures for collection, transport, sample preparation and analysis should become the basis of an effective diagnostic strategy for urinalysis. As reproducibility of urinalysis has been greatly improved due to recent technological progress, preanalytical requirements of urinalysis have gained importance and have become stricter. Since the patients themselves often sample urine specimens, urinalysis is very susceptible to preanalytical issues. Various sampling methods and inappropriate specimen transport can cause important preanalytical errors. The use of preservatives may be helpful for particular analytes. Unfortunately, a universal preservative that allows a complete urinalysis does not (yet) exist. The preanalytical aspects are also of major importance for newer applications (e.g. metabolomics). The present review deals with the current preanalytical problems and requirements for the most common urinary analytes. PMID:24627718

Two-dimensional confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry

NASA Astrophysics Data System (ADS)

Jun, Brian; Giarra, Matthew; Golz, Brian; Main, Russell; Vlachos, Pavlos

2016-11-01

We present a methodology to mitigate the major sources of error associated with two-dimensional confocal laser scanning microscopy (CLSM) images of nanoparticles flowing through a microfluidic channel. The correlation-based velocity measurements from CLSM images are subject to random error due to the Brownian motion of nanometer-sized tracer particles, and a bias error due to the formation of images by raster scanning. Here, we develop a novel ensemble phase correlation with dynamic optimal filter that maximizes the correlation strength, which diminishes the random error. In addition, we introduce an analytical model of CLSM measurement bias error correction due to two-dimensional image scanning of tracer particles. We tested our technique using both synthetic and experimental images of nanoparticles flowing through a microfluidic channel. We observed that our technique reduced the error by up to a factor of ten compared to ensemble standard cross correlation (SCC) for the images tested in the present work. Subsequently, we will assess our framework further, by interrogating nanoscale flow in the cell culture environment (transport within the lacunar-canalicular system) to demonstrate our ability to accurately resolve flow measurements in a biological system.

Color and Vector Flow Imaging in Parallel Ultrasound With Sub-Nyquist Sampling.

PubMed

Madiena, Craig; Faurie, Julia; Poree, Jonathan; Garcia, Damien; Garcia, Damien; Madiena, Craig; Faurie, Julia; Poree, Jonathan

2018-05-01

RF acquisition with a high-performance multichannel ultrasound system generates massive data sets in short periods of time, especially in "ultrafast" ultrasound when digital receive beamforming is required. Sampling at a rate four times the carrier frequency is the standard procedure since this rule complies with the Nyquist-Shannon sampling theorem and simplifies quadrature sampling. Bandpass sampling (or undersampling) outputs a bandpass signal at a rate lower than the maximal frequency without harmful aliasing. Advantages over Nyquist sampling are reduced storage volumes and data workflow, and simplified digital signal processing tasks. We used RF undersampling in color flow imaging (CFI) and vector flow imaging (VFI) to decrease data volume significantly (factor of 3 to 13 in our configurations). CFI and VFI with Nyquist and sub-Nyquist samplings were compared in vitro and in vivo. The estimate errors due to undersampling were small or marginal, which illustrates that Doppler and vector Doppler images can be correctly computed with a drastically reduced amount of RF samples. Undersampling can be a method of choice in CFI and VFI to avoid information overload and reduce data transfer and storage.

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.

The Orthogonally Partitioned EM Algorithm: Extending the EM Algorithm for Algorithmic Stability and Bias Correction Due to Imperfect Data.

PubMed

Regier, Michael D; Moodie, Erica E M

2016-05-01

We propose an extension of the EM algorithm that exploits the common assumption of unique parameterization, corrects for biases due to missing data and measurement error, converges for the specified model when standard implementation of the EM algorithm has a low probability of convergence, and reduces a potentially complex algorithm into a sequence of smaller, simpler, self-contained EM algorithms. We use the theory surrounding the EM algorithm to derive the theoretical results of our proposal, showing that an optimal solution over the parameter space is obtained. A simulation study is used to explore the finite sample properties of the proposed extension when there is missing data and measurement error. We observe that partitioning the EM algorithm into simpler steps may provide better bias reduction in the estimation of model parameters. The ability to breakdown a complicated problem in to a series of simpler, more accessible problems will permit a broader implementation of the EM algorithm, permit the use of software packages that now implement and/or automate the EM algorithm, and make the EM algorithm more accessible to a wider and more general audience.

Reconstructing the calibrated strain signal in the Advanced LIGO detectors

NASA Astrophysics Data System (ADS)

Viets, A. D.; Wade, M.; Urban, A. L.; Kandhasamy, S.; Betzwieser, J.; Brown, Duncan A.; Burguet-Castell, J.; Cahillane, C.; Goetz, E.; Izumi, K.; Karki, S.; Kissel, J. S.; Mendell, G.; Savage, R. L.; Siemens, X.; Tuyenbayev, D.; Weinstein, A. J.

2018-05-01

Advanced LIGO’s raw detector output needs to be calibrated to compute dimensionless strain h(t) . Calibrated strain data is produced in the time domain using both a low-latency, online procedure and a high-latency, offline procedure. The low-latency h(t) data stream is produced in two stages, the first of which is performed on the same computers that operate the detector’s feedback control system. This stage, referred to as the front-end calibration, uses infinite impulse response (IIR) filtering and performs all operations at a 16 384 Hz digital sampling rate. Due to several limitations, this procedure currently introduces certain systematic errors in the calibrated strain data, motivating the second stage of the low-latency procedure, known as the low-latency gstlal calibration pipeline. The gstlal calibration pipeline uses finite impulse response (FIR) filtering to apply corrections to the output of the front-end calibration. It applies time-dependent correction factors to the sensing and actuation components of the calibrated strain to reduce systematic errors. The gstlal calibration pipeline is also used in high latency to recalibrate the data, which is necessary due mainly to online dropouts in the calibrated data and identified improvements to the calibration models or filters.

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…

Measurements of the toroidal torque balance of error field penetration locked modes

DOE PAGES

Shiraki, Daisuke; Paz-Soldan, Carlos; Hanson, Jeremy M.; ...

2015-01-05

Here, detailed measurements from the DIII-D tokamak of the toroidal dynamics of error field penetration locked modes under the influence of slowly evolving external fields, enable study of the toroidal torques on the mode, including interaction with the intrinsic error field. The error field in these low density Ohmic discharges is well known based on the mode penetration threshold, allowing resonant and non-resonant torque effects to be distinguished. These m/n = 2/1 locked modes are found to be well described by a toroidal torque balance between the resonant interaction with n = 1 error fields, and a viscous torque inmore » the electron diamagnetic drift direction which is observed to scale as the square of the perturbed field due to the island. Fitting to this empirical torque balance allows a time-resolved measurement of the intrinsic error field of the device, providing evidence for a time-dependent error field in DIII-D due to ramping of the Ohmic coil current.« less

Chaos in Atomic Force Microscopy

NASA Astrophysics Data System (ADS)

Hu, Shuiqing; Raman, Arvind

2006-01-01

Chaotic oscillations of microcantilever tips in dynamic atomic force microscopy (AFM) are reported and characterized. Systematic experiments performed using a variety of microcantilevers under a wide range of operating conditions indicate that softer AFM microcantilevers bifurcate from periodic to chaotic oscillations near the transition from the noncontact to the tapping regimes. Careful Lyapunov exponent and noise titration calculations of the tip oscillation data confirm their chaotic nature. AFM images taken by scanning the chaotically oscillating tips over the sample show small, but significant metrology errors at the nanoscale due to this “deterministic” uncertainty.

Scribed transparency microplates mounted on a modified standard microplate.

PubMed

Cheong, Brandon Huey-Ping; Chua, Wei Seong; Liew, Oi Wah; Ng, Tuck Wah

2014-08-01

The immense cost effectiveness of using transparencies as analyte handling implements in microplate instrumentation offers the possibility of application even in resource-limited laboratories. In this work, a standard microplate was adapted to serve as the permanent base for disposable scribed transparencies. The approach is shown to ameliorate evaporation, which can affect assay accuracy when analytes need to be incubated for some time. It also offers assurance against fluorescence measurement errors due to the cross-talk of samples from adjacent wells. Copyright © 2014 Elsevier Inc. All rights reserved.

A novel variable baseline visibility detection system and its measurement method

NASA Astrophysics Data System (ADS)

Li, Meng; Jiang, Li-hui; Xiong, Xing-long; Zhang, Guizhong; Yao, JianQuan

2017-10-01

As an important meteorological observation instrument, the visibility meter can ensure the safety of traffic operation. However, due to the optical system contamination as well as sample error, the accuracy and stability of the equipment are difficult to meet the requirement in the low-visibility environment. To settle this matter, a novel measurement equipment was designed based upon multiple baseline, which essentially acts as an atmospheric transmission meter with movable optical receiver, applying weighted least square method to process signal. Theoretical analysis and experiments in real atmosphere environment support this technique.

Automated Mounting Bias Calibration for Airborne LIDAR System

NASA Astrophysics Data System (ADS)

Zhang, J.; Jiang, W.; Jiang, S.

2012-07-01

Mounting bias is the major error source of Airborne LIDAR system. In this paper, an automated calibration method for estimating LIDAR system mounting parameters is introduced. LIDAR direct geo-referencing model is used to calculate systematic errors. Due to LIDAR footprints discretely sampled, the real corresponding laser points are hardly existence among different strips. The traditional corresponding point methodology does not seem to apply to LIDAR strip registration. We proposed a Virtual Corresponding Point Model to resolve the corresponding problem among discrete laser points. Each VCPM contains a corresponding point and three real laser footprints. Two rules are defined to calculate tie point coordinate from real laser footprints. The Scale Invariant Feature Transform (SIFT) is used to extract corresponding points in LIDAR strips, and the automatic flow of LIDAR system calibration based on VCPM is detailed described. The practical examples illustrate the feasibility and effectiveness of the proposed calibration method.

Efficient computation of the Grünwald-Letnikov fractional diffusion derivative using adaptive time step memory

NASA Astrophysics Data System (ADS)

MacDonald, Christopher L.; Bhattacharya, Nirupama; Sprouse, Brian P.; Silva, Gabriel A.

2015-09-01

Computing numerical solutions to fractional differential equations can be computationally intensive due to the effect of non-local derivatives in which all previous time points contribute to the current iteration. In general, numerical approaches that depend on truncating part of the system history while efficient, can suffer from high degrees of error and inaccuracy. Here we present an adaptive time step memory method for smooth functions applied to the Grünwald-Letnikov fractional diffusion derivative. This method is computationally efficient and results in smaller errors during numerical simulations. Sampled points along the system's history at progressively longer intervals are assumed to reflect the values of neighboring time points. By including progressively fewer points backward in time, a temporally 'weighted' history is computed that includes contributions from the entire past of the system, maintaining accuracy, but with fewer points actually calculated, greatly improving computational efficiency.

Functional Mixed Effects Model for Small Area Estimation.

PubMed

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

Error-based Extraction of States and Energy Landscapes from Experimental Single-Molecule Time-Series

NASA Astrophysics Data System (ADS)

Taylor, J. Nicholas; Li, Chun-Biu; Cooper, David R.; Landes, Christy F.; Komatsuzaki, Tamiki

2015-03-01

Characterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements. Here we present a method to extract the underlying state sequences from experimental SM time-series. Taking into account empirical error and the finite sampling of the time-series, the method extracts a steady-state network which provides an approximation of the underlying effective free energy landscape. The core of the method is the application of rate-distortion theory from information theory, allowing the individual data points to be assigned to multiple states simultaneously. We demonstrate the method's proficiency in its application to simulated trajectories as well as to experimental SM fluorescence resonance energy transfer (FRET) trajectories obtained from isolated agonist binding domains of the AMPA receptor, an ionotropic glutamate receptor that is prevalent in the central nervous system.

Dual-phase-shift spherical Fizeau interferometer for reduction of noise due to internally scattered light

NASA Astrophysics Data System (ADS)

Kumagai, Toshiki; Hibino, Kenichi; Nagaike, Yasunari

2017-03-01

Internally scattered light in a Fizeau interferometer is generated from dust, defects, imperfect coating of the optical components, and multiple reflections inside the collimator lens. It produces additional noise fringes in the observed interference image and degrades the repeatability of the phase measurement. A method to reduce the phase measurement error is proposed, in which the test surface is mechanically translated between each phase measurement in addition to an ordinary phase shift of the reference surface. It is shown that a linear combination of several measured phases at different test surface positions can reduce the phase errors caused by the scattered light. The combination can also compensate for the nonuniformity of the phase shift that occurs in spherical tests. A symmetric sampling of the phase measurements can cancel the additional primary spherical aberrations that occur when the test surface is out of the null position of the confocal configuration.

Risk-Based Sampling: I Don't Want to Weight in Vain.

PubMed

Powell, Mark R

2015-12-01

Recently, there has been considerable interest in developing risk-based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk-based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean-variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false "optimal" portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out-of-sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk-based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers. © 2015 Society for Risk Analysis.

Error of semiclassical eigenvalues in the semiclassical limit - an asymptotic analysis of the Sinai billiard

NASA Astrophysics Data System (ADS)

Dahlqvist, Per

1999-10-01

We estimate the error in the semiclassical trace formula for the Sinai billiard under the assumption that the largest source of error is due to penumbra diffraction: namely, diffraction effects for trajectories passing within a distance Ricons/Journals/Common/cdot" ALT="cdot" ALIGN="TOP"/>O((kR)-2/3) to the disc and trajectories being scattered in very forward directions. Here k is the momentum and R the radius of the scatterer. The semiclassical error is estimated by perturbing the Berry-Keating formula. The analysis necessitates an asymptotic analysis of very long periodic orbits. This is obtained within an approximation originally due to Baladi, Eckmann and Ruelle. We find that the average error, for sufficiently large values of kR, will exceed the mean level spacing.

Galaxy–galaxy lensing estimators and their covariance properties

DOE PAGES

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; ...

2017-07-21

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens densitymore » field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.« less

[Spatial interpolation of soil organic matter using regression Kriging and geographically weighted regression Kriging].

PubMed

Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan

2015-06-01

Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations.

Sample size and classification error for Bayesian change-point models with unlabelled sub-groups and incomplete follow-up.

PubMed

White, Simon R; Muniz-Terrera, Graciela; Matthews, Fiona E

2018-05-01

Many medical (and ecological) processes involve the change of shape, whereby one trajectory changes into another trajectory at a specific time point. There has been little investigation into the study design needed to investigate these models. We consider the class of fixed effect change-point models with an underlying shape comprised two joined linear segments, also known as broken-stick models. We extend this model to include two sub-groups with different trajectories at the change-point, a change and no change class, and also include a missingness model to account for individuals with incomplete follow-up. Through a simulation study, we consider the relationship of sample size to the estimates of the underlying shape, the existence of a change-point, and the classification-error of sub-group labels. We use a Bayesian framework to account for the missing labels, and the analysis of each simulation is performed using standard Markov chain Monte Carlo techniques. Our simulation study is inspired by cognitive decline as measured by the Mini-Mental State Examination, where our extended model is appropriate due to the commonly observed mixture of individuals within studies who do or do not exhibit accelerated decline. We find that even for studies of modest size ( n = 500, with 50 individuals observed past the change-point) in the fixed effect setting, a change-point can be detected and reliably estimated across a range of observation-errors.

Galaxy–galaxy lensing estimators and their covariance properties

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

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros

Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens densitymore » field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.« less

Galaxy-galaxy lensing estimators and their covariance properties

NASA Astrophysics Data System (ADS)

Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose

2017-11-01

We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.

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.

Characterizing the SWOT discharge error budget on the Sacramento River, CA

NASA Astrophysics Data System (ADS)

Yoon, Y.; Durand, M. T.; Minear, J. T.; Smith, L.; Merry, C. J.

2013-12-01

The Surface Water and Ocean Topography (SWOT) is an upcoming satellite mission (2020 year) that will provide surface-water elevation and surface-water extent globally. One goal of SWOT is the estimation of river discharge directly from SWOT measurements. SWOT discharge uncertainty is due to two sources. First, SWOT cannot measure channel bathymetry and determine roughness coefficient data necessary for discharge calculations directly; these parameters must be estimated from the measurements or from a priori information. Second, SWOT measurement errors directly impact the discharge estimate accuracy. This study focuses on characterizing parameter and measurement uncertainties for SWOT river discharge estimation. A Bayesian Markov Chain Monte Carlo scheme is used to calculate parameter estimates, given the measurements of river height, slope and width, and mass and momentum constraints. The algorithm is evaluated using simulated both SWOT and AirSWOT (the airborne version of SWOT) observations over seven reaches (about 40 km) of the Sacramento River. The SWOT and AirSWOT observations are simulated by corrupting the ';true' HEC-RAS hydraulic modeling results with the instrument error. This experiment answers how unknown bathymetry and roughness coefficients affect the accuracy of the river discharge algorithm. From the experiment, the discharge error budget is almost completely dominated by unknown bathymetry and roughness; 81% of the variance error is explained by uncertainties in bathymetry and roughness. Second, we show how the errors in water surface, slope, and width observations influence the accuracy of discharge estimates. Indeed, there is a significant sensitivity to water surface, slope, and width errors due to the sensitivity of bathymetry and roughness to measurement errors. Increasing water-surface error above 10 cm leads to a corresponding sharper increase of errors in bathymetry and roughness. Increasing slope error above 1.5 cm/km leads to a significant degradation due to direct error in the discharge estimates. As the width error increases past 20%, the discharge error budget is dominated by the width error. Above two experiments are performed based on AirSWOT scenarios. In addition, we explore the sensitivity of the algorithm to the SWOT scenarios.

An optical/NIR survey of globular clusters in early-type galaxies. III. On the colour bimodality of globular cluster systems

NASA Astrophysics Data System (ADS)

Chies-Santos, A. L.; Larsen, S. S.; Cantiello, M.; Strader, J.; Kuntschner, H.; Wehner, E. M.; Brodie, J. P.

2012-03-01

Context. The interpretation that bimodal colour distributions of globular clusters (GCs) reflect bimodal metallicity distributions has been challenged. Non-linearities in the colour to metallicity conversions caused for example by the horizontal branch (HB) stars may be responsible for transforming a unimodal metallicity distribution into a bimodal (optical) colour distribution. Aims: We study optical/near-infrared (NIR) colour distributions of the GC systems in 14 E/S0 galaxies. Methods: We test whether the bimodal feature, generally present in optical colour distributions, remains in the optical/NIR ones. The latter colour combination is a better metallicity proxy than the former. We use KMM and GMM tests to quantify the probability that different colour distributions are better described by a bimodal, as opposed to a unimodal distribution. Results: We find that double-peaked colour distributions are more commonly seen in optical than in optical/NIR colours. For some of the galaxies where the optical (g - z) distribution is clearly bimodal, a bimodal distribution is not preferred over a unimodal one at a statistically significant level for the (g - K) and (z - K) distributions. The two most cluster-rich galaxies in our sample, NGC 4486 and NGC 4649, show some interesting differences. The (g - K) distribution of NGC 4649 is better described by a bimodal distribution, while this is true for the (g - K) distribution of NGC 4486 GCs only if restricted to a brighter sub-sample with small K-band errors (<0.05 mag). Formally, the K-band photometric errors cannot be responsible for blurring bimodal metallicity distributions to unimodal (g - K) colour distributions. However, simulations including the extra scatter in the colour-colour diagrams (not fully accounted for in the photometric errors) show that such scatter may contribute to the disappearance of bimodality in (g - K) for the full NGC 4486 sample. For the less cluster-rich galaxies results are inconclusive due to poorer statistics. Conclusions: A bimodal optical colour distribution is not necessarily an indication of an underlying bimodal metallicity distribution. Horizontal branch morphology may play an important role in shaping some of the optical GC colour distributions. However, we find tentative evidence that the (g - K) colour distributions remain bimodal in the two cluster-rich galaxies in our sample (NGC 4486 and NGC 4649) when restricted to clusters with small K-band photometric errors. This bimodality becomes less pronounced when including objects with larger errors, or for the (z - K) colour distributions. Deeper observations of large numbers of GCs will be required to reach more secure conclusions.

Quantifying Fugitive Methane Emissions from Natural Gas Production with Mobile Technology

NASA Astrophysics Data System (ADS)

Tsai, T.; Rella, C.; Crosson, E.

2013-12-01

Quantification of fugitive methane (CH4) emissions to determine the environmental impact of natural gas production is challenging with current methods. We present a new mobile method known as the Plume Scanner that can quickly quantify CH4 emissions of point sources. The Plume Scanner is a direct measurement technique which utilizes a mobile Picarro cavity ring-down spectrometer and a gas sampling system based on AirCore technology [1]. As the Plume Scanner vehicle drives through the plume, the air is simultaneously sampled at four different heights, and therefore, the spatial CH4 distribution can be captured (Fig. 1). The flux of the plume is then determined by multiplying the spatial CH4 distribution data with the anemometer measurements. In this way, fugitive emission rates of highly localized sources such as natural gas production pads can be made quickly (~7 min). Verification with controlled CH4 releases demonstrate that under stable atmospheric conditions (Pasquill stability class is C or greater), the Plume Scanner measurements have an error of 2% and a repeatability of 15% [2]. Under unstable atmospheric conditions (Class A or B), the error is 6%, and the repeatability increases to 70% due to the variability of wind conditions. Over two weeks, 275 facilities in the Barnett Shale were surveyed from public roads by sampling the air for elevations in CH4 concentration, and 77% were found leaking. Emissions from 52 sites have been quantified with the Plume Scanner (Fig. 2), and the total emission is 4,900 liters per min (lpm) or 39,000 metric tons/yr CO2e. 1. Karion, A., C. Sweeney, P. Tans, and T. Newberger (2010), AirCore: An innovative atmospheric sampling system, J. Atmos. Oceanic Tech, 27, 1839-1853. 2. F. Pasquill (1961), The estimation of the dispersion of wind borne material, Meterol. Mag., 90(1063), 33-49 Figure 1. Plume Scanner Cartoon Figure 2. Distribution of methane fugitive emissions with error bars associated with the Pasquill stability classes drawn for reference.

Experimental transition probabilities for Mn II spectral lines

NASA Astrophysics Data System (ADS)

Manrique, J.; Aguilera, J. A.; Aragón, C.

2018-06-01

Transition probabilities for 46 spectral lines of Mn II with wavelengths in the range 2000-3500 Å have been measured by CSigma laser-induced breakdown spectroscopy (Cσ-LIBS). For 28 of the lines, experimental data had not been reported previously. The Cσ-LIBS method, based in the construction of generalized curves of growth called Cσ graphs, avoids the error due to self-absorption. The samples used to generate the laser-induced plasmas are fused glass disks prepared from pure MnO. The Mn concentrations in the samples and the lines included in the study are selected to ensure the validity of the model of homogeneous plasma used. The results are compared to experimental and theoretical values available 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.

A new stochastic model considering satellite clock interpolation errors in precise point positioning

NASA Astrophysics Data System (ADS)

Wang, Shengli; Yang, Fanlin; Gao, Wang; Yan, Lizi; Ge, Yulong

2018-03-01

Precise clock products are typically interpolated based on the sampling interval of the observational data when they are used for in precise point positioning. However, due to the occurrence of white noise in atomic clocks, a residual component of such noise will inevitable reside within the observations when clock errors are interpolated, and such noise will affect the resolution of the positioning results. In this paper, which is based on a twenty-one-week analysis of the atomic clock noise characteristics of numerous satellites, a new stochastic observation model that considers satellite clock interpolation errors is proposed. First, the systematic error of each satellite in the IGR clock product was extracted using a wavelet de-noising method to obtain the empirical characteristics of atomic clock noise within each clock product. Then, based on those empirical characteristics, a stochastic observation model was structured that considered the satellite clock interpolation errors. Subsequently, the IGR and IGS clock products at different time intervals were used for experimental validation. A verification using 179 stations worldwide from the IGS showed that, compared with the conventional model, the convergence times using the stochastic model proposed in this study were respectively shortened by 4.8% and 4.0% when the IGR and IGS 300-s-interval clock products were used and by 19.1% and 19.4% when the 900-s-interval clock products were used. Furthermore, the disturbances during the initial phase of the calculation were also effectively improved.

Evaluation of Mycology Laboratory Proficiency Testing

PubMed Central

Reilly, Andrew A.; Salkin, Ira F.; McGinnis, Michael R.; Gromadzki, Sally; Pasarell, Lester; Kemna, Maggi; Higgins, Nancy; Salfinger, Max

1999-01-01

Changes over the last decade in overt proficiency testing (OPT) regulations have been ostensibly directed at improving laboratory performance on patient samples. However, the overt (unblinded) format of the tests and regulatory penalties associated with incorrect values allow and encourage laboratorians to take extra precautions with OPT analytes. As a result OPT may measure optimal laboratory performance instead of the intended target of typical performance attained during routine patient testing. This study addresses this issue by evaluating medical mycology OPT and comparing its fungal specimen identification error rates to those obtained in a covert (blinded) proficiency testing (CPT) program. Identifications from 188 laboratories participating in the New York State mycology OPT from 1982 to 1994 were compared with the identifications of the same fungi recovered from patient specimens in 1989 and 1994 as part of the routine procedures of 88 of these laboratories. The consistency in the identification of OPT specimens was sufficient to make accurate predictions of OPT error rates. However, while the error rates in OPT and CPT were similar for Candida albicans, significantly higher error rates were found in CPT for Candida tropicalis, Candida glabrata, and other common pathogenic fungi. These differences may, in part, be due to OPT’s use of ideal organism representatives cultured under optimum growth conditions. This difference, as well as the organism-dependent error rate differences, reflects the limitations of OPT as a means of assessing the quality of routine laboratory performance in medical mycology. PMID:10364601

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.

Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter. Pt. 2; Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics

NASA Technical Reports Server (NTRS)

Menard, Richard; Chang, Lang-Ping

1998-01-01

A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

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

Questioning the stability of sense of coherence--the impact of socio-economic status and working conditions in the Canadian population.

PubMed

Smith, Peter M; Breslin, F Curtis; Beaton, Dorcas E

2003-09-01

Much debate exists about the stability of the sense of coherence measure. This study examined changes in sense of coherence (SOC), and the variables associated with these changes, over a 4-year period, in a representative sample of the Canadian labour force (n=6,790). Two methods were used to assess change in SOC: (1) Change outside of that which could be considered as indistinguishable from measurement error, and (2) Change of more than 10%, which was originally proposed by Antonovksy, the scales designer. Over the study period, 35.4% of the population reported changes in SOC outside the range we consider possible due to measurement error, with 58% reporting change greater than 10%. Unskilled occupations were associated with declines in SOC, with household income demonstrating a curvilinear relationship with decline in SOC in the female population only. None of the variables used predicted increases in SOC. Given the degree of change in SOC, and the representativeness of the study sample, we suggest that SOC has a large state component. Given this lack of stability, we recommend caution if using the SOC to represent a stable global orientation within a causal context.

Quantifying creatinine and urea in human urine through Raman spectroscopy aiming at diagnosis of kidney disease

NASA Astrophysics Data System (ADS)

Saatkamp, Cassiano Junior; de Almeida, Maurício Liberal; Bispo, Jeyse Aliana Martins; Pinheiro, Antonio Luiz Barbosa; Fernandes, Adriana Barrinha; Silveira, Landulfo, Jr.

2016-03-01

Due to their importance in the regulation of metabolites, the kidneys need continuous monitoring to check for correct functioning, mainly by urea and creatinine urinalysis. This study aimed to develop a model to estimate the concentrations of urea and creatinine in urine by means of Raman spectroscopy (RS) that could be used to diagnose kidney disease. Midstream urine samples were obtained from 54 volunteers with no kidney complaints. Samples were subjected to a standard colorimetric assay of urea and creatinine and submitted to spectroscopic analysis by means of a dispersive Raman spectrometer (830 nm, 350 mW, 30 s). The Raman spectra of urine showed peaks related mainly to urea and creatinine. Partial least squares models were developed using selected Raman bands related to urea and creatinine and the biochemical concentrations in urine measured by the colorimetric method, resulting in r=0.90 and 0.91 for urea and creatinine, respectively, with root mean square error of cross-validation (RMSEcv) of 312 and 25.2 mg/dL, respectively. RS may become a technique for rapid urinalysis, with concentration errors suitable for population screening aimed at the prevention of renal diseases.

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).

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.

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

Three-Dimensional (3D) Nanometrology Based on Scanning Electron Microscope (SEM) Stereophotogrammetry.

PubMed

Tondare, Vipin N; Villarrubia, John S; Vlada R, András E

2017-10-01

Three-dimensional (3D) reconstruction of a sample surface from scanning electron microscope (SEM) images taken at two perspectives has been known for decades. Nowadays, there exist several commercially available stereophotogrammetry software packages. For testing these software packages, in this study we used Monte Carlo simulated SEM images of virtual samples. A virtual sample is a model in a computer, and its true dimensions are known exactly, which is impossible for real SEM samples due to measurement uncertainty. The simulated SEM images can be used for algorithm testing, development, and validation. We tested two stereophotogrammetry software packages and compared their reconstructed 3D models with the known geometry of the virtual samples used to create the simulated SEM images. Both packages performed relatively well with simulated SEM images of a sample with a rough surface. However, in a sample containing nearly uniform and therefore low-contrast zones, the height reconstruction error was ≈46%. The present stereophotogrammetry software packages need further improvement before they can be used reliably with SEM images with uniform zones.

A sequential bioequivalence design with a potential ethical advantage.

PubMed

Fuglsang, Anders

2014-07-01

This paper introduces a two-stage approach for evaluation of bioequivalence, where, in contrast to the designs of Diane Potvin and co-workers, two stages are mandatory regardless of the data obtained at stage 1. The approach is derived from Potvin's method C. It is shown that under circumstances with relatively high variability and relatively low initial sample size, this method has an advantage over Potvin's approaches in terms of sample sizes while controlling type I error rates at or below 5% with a minute occasional trade-off in power. Ethically and economically, the method may thus be an attractive alternative to the Potvin designs. It is also shown that when using the method introduced here, average total sample sizes are rather independent of initial sample size. Finally, it is shown that when a futility rule in terms of sample size for stage 2 is incorporated into this method, i.e., when a second stage can be abolished due to sample size considerations, there is often an advantage in terms of power or sample size as compared to the previously published methods.

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

Ellefson, S; Department of Human Oncology, University of Wisconsin, Madison, WI; Culberson, W

Purpose: Discrepancies in absolute dose values have been detected between the ViewRay treatment planning system and ArcCHECK readings when performing delivery quality assurance on the ViewRay system with the ArcCHECK-MR diode array (SunNuclear Corporation). In this work, we investigate whether these discrepancies are due to errors in the ViewRay planning and/or delivery system or due to errors in the ArcCHECK’s readings. Methods: Gamma analysis was performed on 19 ViewRay patient plans using the ArcCHECK. Frequency analysis on the dose differences was performed. To investigate whether discrepancies were due to measurement or delivery error, 10 diodes in low-gradient dose regions weremore » chosen to compare with ion chamber measurements in a PMMA phantom with the same size and shape as the ArcCHECK, provided by SunNuclear. The diodes chosen all had significant discrepancies in absolute dose values compared to the ViewRay TPS. Absolute doses to PMMA were compared between the ViewRay TPS calculations, ArcCHECK measurements, and measurements in the PMMA phantom. Results: Three of the 19 patient plans had 3%/3mm gamma passing rates less than 95%, and ten of the 19 plans had 2%/2mm passing rates less than 95%. Frequency analysis implied a non-random error process. Out of the 10 diode locations measured, ion chamber measurements were all within 2.2% error relative to the TPS and had a mean error of 1.2%. ArcCHECK measurements ranged from 4.5% to over 15% error relative to the TPS and had a mean error of 8.0%. Conclusion: The ArcCHECK performs well for quality assurance on the ViewRay under most circumstances. However, under certain conditions the absolute dose readings are significantly higher compared to the planned doses. As the ion chamber measurements consistently agree with the TPS, it can be concluded that the discrepancies are due to ArcCHECK measurement error and not TPS or delivery system error. This work was funded by the Bhudatt Paliwal Professorship and the University of Wisconsin Medical Radiation Research Center.« less

The External Quality Assessment Scheme (EQAS): Experiences of a medium sized accredited laboratory.

PubMed

Bhat, Vivek; Chavan, Preeti; Naresh, Chital; Poladia, Pratik

2015-06-15

We put forth our experiences of EQAS, analyzed the result discrepancies, reviewed the corrective actions and also put forth strategies for risk identification and prevention of potential errors in a medical laboratory. For hematology, EQAS samples - blood, peripheral and reticulocyte smears - were received quarterly every year. All the blood samples were processed on HMX hematology analyzer by Beckman-Coulter. For clinical chemistry, lyophilized samples were received and were processed on Siemens Dimension Xpand and RXL analyzers. For microbiology, EQAS samples were received quarterly every year as lyophilized strains along with smears and serological samples. In hematology no outliers were noted for reticulocyte and peripheral smear examination. Only one outlier was noted for CBC. In clinical chemistry outliers (SDI ≥ 2) were noted in 7 samples (23 parameters) out of total 36 samples (756 parameters) processed. Thirteen of these parameters were analyzed as random errors, 3 as transcriptional errors and seven instances of systemic error were noted. In microbiology, one discrepancy was noted in isolate identification and in the grading of smears for AFB by Ziehl Neelsen stain. EQAS along with IQC is a very important tool for maintaining optimal quality of services. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Further development of a robust workup process for solution-phase high-throughput library synthesis to address environmental and sample tracking issues.

PubMed

Kuroda, Noritaka; Hird, Nick; Cork, David G

2006-01-01

During further improvement of a high-throughput, solution-phase synthesis system, new workup tools and apparatus for parallel liquid-liquid extraction and evaporation have been developed. A combination of in-house design and collaboration with external manufacturers has been used to address (1) environmental issues concerning solvent emissions and (2) sample tracking errors arising from manual intervention. A parallel liquid-liquid extraction unit, containing miniature high-speed magnetic stirrers for efficient mixing of organic and aqueous phases, has been developed for use on a multichannel liquid handler. Separation of the phases is achieved by dispensing them into a newly patented filter tube containing a vertical hydrophobic porous membrane, which allows only the organic phase to pass into collection vials positioned below. The vertical positioning of the membrane overcomes the hitherto dependence on the use of heavier-than-water, bottom-phase, organic solvents such as dichloromethane, which are restricted due to environmental concerns. Both small (6-mL) and large (60-mL) filter tubes were developed for parallel phase separation in library and template synthesis, respectively. In addition, an apparatus for parallel solvent evaporation was developed to (1) remove solvent from the above samples with highly efficient recovery and (2) avoid the movement of individual samples between their collection on a liquid handler and registration to prevent sample identification errors. The apparatus uses a diaphragm pump to achieve a dynamic circulating closed system with a heating block for the rack of 96 sample vials and an efficient condenser to trap the solvents. Solvent recovery is typically >98%, and convenient operation and monitoring has made the apparatus the first choice for removal of volatile solvents.

Errors in radiation oncology: A study in pathways and dosimetric impact

PubMed Central

Drzymala, Robert E.; Purdy, James A.; Michalski, Jeff

2005-01-01

As complexity for treating patients increases, so does the risk of error. Some publications have suggested that record and verify (R&V) systems may contribute in propagating errors. Direct data transfer has the potential to eliminate most, but not all, errors. And although the dosimetric consequences may be obvious in some cases, a detailed study does not exist. In this effort, we examined potential errors in terms of scenarios, pathways of occurrence, and dosimetry. Our goal was to prioritize error prevention according to likelihood of event and dosimetric impact. For conventional photon treatments, we investigated errors of incorrect source‐to‐surface distance (SSD), energy, omitted wedge (physical, dynamic, or universal) or compensating filter, incorrect wedge or compensating filter orientation, improper rotational rate for arc therapy, and geometrical misses due to incorrect gantry, collimator or table angle, reversed field settings, and setup errors. For electron beam therapy, errors investigated included incorrect energy, incorrect SSD, along with geometric misses. For special procedures we examined errors for total body irradiation (TBI, incorrect field size, dose rate, treatment distance) and LINAC radiosurgery (incorrect collimation setting, incorrect rotational parameters). Likelihood of error was determined and subsequently rated according to our history of detecting such errors. Dosimetric evaluation was conducted by using dosimetric data, treatment plans, or measurements. We found geometric misses to have the highest error probability. They most often occurred due to improper setup via coordinate shift errors or incorrect field shaping. The dosimetric impact is unique for each case and depends on the proportion of fields in error and volume mistreated. These errors were short‐lived due to rapid detection via port films. The most significant dosimetric error was related to a reversed wedge direction. This may occur due to incorrect collimator angle or wedge orientation. For parallel‐opposed 60° wedge fields, this error could be as high as 80% to a point off‐axis. Other examples of dosimetric impact included the following: SSD, ~2%/cm for photons or electrons; photon energy (6 MV vs. 18 MV), on average 16% depending on depth, electron energy, ~0.5cm of depth coverage per MeV (mega‐electron volt). Of these examples, incorrect distances were most likely but rapidly detected by in vivo dosimetry. Errors were categorized by occurrence rate, methods and timing of detection, longevity, and dosimetric impact. Solutions were devised according to these criteria. To date, no one has studied the dosimetric impact of global errors in radiation oncology. Although there is heightened awareness that with increased use of ancillary devices and automation, there must be a parallel increase in quality check systems and processes, errors do and will continue to occur. This study has helped us identify and prioritize potential errors in our clinic according to frequency and dosimetric impact. For example, to reduce the use of an incorrect wedge direction, our clinic employs off‐axis in vivo dosimetry. To avoid a treatment distance setup error, we use both vertical table settings and optical distance indicator (ODI) values to properly set up fields. As R&V systems become more automated, more accurate and efficient data transfer will occur. This will require further analysis. Finally, we have begun examining potential intensity‐modulated radiation therapy (IMRT) errors according to the same criteria. PACS numbers: 87.53.Xd, 87.53.St PMID:16143793

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.

Picometer Level Modeling of a Shared Vertex Double Corner Cube in the Space Interferometry Mission Kite Testbed

NASA Technical Reports Server (NTRS)

Kuan, Gary M.; Dekens, Frank G.

2006-01-01

The Space Interferometry Mission (SIM) is a microarcsecond interferometric space telescope that requires picometer level precision measurements of its truss and interferometer baselines. Single-gauge metrology errors due to non-ideal physical characteristics of corner cubes reduce the angular measurement capability of the science instrument. Specifically, the non-common vertex error (NCVE) of a shared vertex, double corner cube introduces micrometer level single-gauge errors in addition to errors due to dihedral angles and reflection phase shifts. A modified SIM Kite Testbed containing an articulating double corner cube is modeled and the results are compared to the experimental testbed data. The results confirm modeling capability and viability of calibration techniques.

General linear codes for fault-tolerant matrix operations on processor arrays

NASA Technical Reports Server (NTRS)

Nair, V. S. S.; Abraham, J. A.

1988-01-01

Various checksum codes have been suggested for fault-tolerant matrix computations on processor arrays. Use of these codes is limited due to potential roundoff and overflow errors. Numerical errors may also be misconstrued as errors due to physical faults in the system. In this a set of linear codes is identified which can be used for fault-tolerant matrix operations such as matrix addition, multiplication, transposition, and LU-decomposition, with minimum numerical error. Encoding schemes are given for some of the example codes which fall under the general set of codes. With the help of experiments, a rule of thumb for the selection of a particular code for a given application is derived.

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.

Voice Onset Time in Consonant Cluster Errors: Can Phonetic Accommodation Differentiate Cognitive from Motor Errors?

ERIC Educational Resources Information Center

Pouplier, Marianne; Marin, Stefania; Waltl, Susanne

2014-01-01

Purpose: Phonetic accommodation in speech errors has traditionally been used to identify the processing level at which an error has occurred. Recent studies have challenged the view that noncanonical productions may solely be due to phonetic, not phonological, processing irregularities, as previously assumed. The authors of the present study…

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.

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.

Modulus design multiwavelength polarization microscope for transmission Mueller matrix imaging.

PubMed

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. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

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.

Experimental investigation of strain errors in stereo-digital image correlation due to camera calibration

NASA Astrophysics Data System (ADS)

Shao, Xinxing; Zhu, Feipeng; Su, Zhilong; Dai, Xiangjun; Chen, Zhenning; He, Xiaoyuan

2018-03-01

The strain errors in stereo-digital image correlation (DIC) due to camera calibration were investigated using precisely controlled numerical experiments and real experiments. Three-dimensional rigid body motion tests were conducted to examine the effects of camera calibration on the measured results. For a fully accurate calibration, rigid body motion causes negligible strain errors. However, for inaccurately calibrated camera parameters and a short working distance, rigid body motion will lead to more than 50-μɛ strain errors, which significantly affects the measurement. In practical measurements, it is impossible to obtain a fully accurate calibration; therefore, considerable attention should be focused on attempting to avoid these types of errors, especially for high-accuracy strain measurements. It is necessary to avoid large rigid body motions in both two-dimensional DIC and stereo-DIC.

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

Due Diligence Processes for Public Acquisition of Mining-Impacted Landscapes

NASA Astrophysics Data System (ADS)

Martin, E.; Monohan, C.; Keeble-Toll, A. K.

2016-12-01

The acquisition of public land is critical for achieving conservation and habitat goals in rural regions projected to experience continuously high rates of population growth. To ensure that public funds are utilized responsibly in the purchase of conservation easements appropriate due diligence processes must be established that limit landowner liability post-acquisition. Traditional methods of characterizing contamination in regions where legacy mining activities were prevalent may not utilize current scientific knowledge and understanding of contaminant fate, transport and bioavailability, and therefore are likely to have type two error. Agency prescribed assessment methods utilized under CERLA in many cases fail to detect contamination that presents liability issues by failing to require water quality sampling that would reveal offsite transport potential of contaminants posing human health risks, including mercury. Historical analysis can be used to inform judgmental sampling to identify hotspots and contaminants of concern. Land acquisition projects at two historic mine sites in Nevada County, California, the Champion Mine Complex and the Black Swan Preserve have established the necessity of re-thinking due diligence processes for mining-impacted landscapes. These pilot projects demonstrate that pre-acquisition assessment in the Gold Country must include judgmental sampling and evaluation of contaminant transport. Best practices using the current scientific knowledge must be codified by agencies, consultants, and NGOs in order to ensure responsible use of public funds and to safeguard public health.

Error simulation of paired-comparison-based scaling methods

NASA Astrophysics Data System (ADS)

Cui, Chengwu

2000-12-01

Subjective image quality measurement usually resorts to psycho physical scaling. However, it is difficult to evaluate the inherent precision of these scaling methods. Without knowing the potential errors of the measurement, subsequent use of the data can be misleading. In this paper, the errors on scaled values derived form paired comparison based scaling methods are simulated with randomly introduced proportion of choice errors that follow the binomial distribution. Simulation results are given for various combinations of the number of stimuli and the sampling size. The errors are presented in the form of average standard deviation of the scaled values and can be fitted reasonably well with an empirical equation that can be sued for scaling error estimation and measurement design. The simulation proves paired comparison based scaling methods can have large errors on the derived scaled values when the sampling size and the number of stimuli are small. Examples are also given to show the potential errors on actually scaled values of color image prints as measured by the method of paired comparison.

Quality of nutrient data from streams and ground water sampled during water years 1992-2001

USGS Publications Warehouse

Mueller, David K.; Titus, Cindy J.

2005-01-01

Proper interpretation of water-quality data requires consideration of the effects that bias and variability might have on measured constituent concentrations. In this report, methods are described to estimate the bias due to contamination of samples in the field or laboratory and the variability due to sample collection, processing, shipment, and analysis. Contamination can adversely affect interpretation of measured concentrations in comparison to standards or criteria. Variability can affect interpretation of small differences between individual measurements or mean concentrations. Contamination and variability are determined for nutrient data from quality-control samples (field blanks and replicates) collected as part of the National Water-Quality Assessment (NAWQA) Program during water years 1992-2001. Statistical methods are used to estimate the likelihood of contamination and variability in all samples. Results are presented for five nutrient analytes from stream samples and four nutrient analytes from ground-water samples. Ammonia contamination can add at least 0.04 milligram per liter in up to 5 percent of all samples. This could account for more than 22 percent of measured concentrations at the low range of aquatic-life criteria (0.18 milligram per liter). Orthophosphate contamination, at least 0.019 milligram per liter in up to 5 percent of all samples, could account for more than 38 percent of measured concentrations at the limit to avoid eutrophication (0.05 milligram per liter). Nitrite-plus-nitrate and Kjeldahl nitrogen contamination is less than 0.4 milligram per liter in 99 percent of all samples; thus there is no significant effect on measured concentrations of environmental significance. Sampling variability has little or no effect on reported concentrations of ammonia, nitrite-plus-nitrate, orthophosphate, or total phosphorus sampled after 1998. The potential errors due to sampling variability are greater for the Kjeldahl nitrogen analytes and for total phosphorus sampled before 1999. The uncertainty in a mean of 10 concentrations caused by sampling variability is within a small range (1 to 7 percent) for all nutrients. These results can be applied to interpretation of environmental data collected during water years 1992-2001 in 52 NAWQA study units.

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

Buoyancy-corrected gravimetric analysis of lightly loaded filters.

PubMed

Rasmussen, Pat E; Gardner, H David; Niu, Jianjun

2010-09-01

Numerous sources of uncertainty are associated with the gravimetric analysis of lightly loaded air filter samples (< 100 microg). The purpose of the study presented here is to investigate the effectiveness and limitations of air buoyancy corrections over experimentally adjusted conditions of temperature (21-25 degrees C) and relative humidity (RH) (16-60% RH). Conditioning (24 hr) and weighing were performed inside the Archimedes M3 environmentally controlled chamber. The measurements were performed using 20 size-fractionated samples of resuspended house dust loaded onto Teflo (PTFE) filters using a Micro-Orifice Uniform Deposit Impactor representing a wide range of mass loading (7.2-3130 microg) and cut sizes (0.056-9.9 microm). By maintaining tight controls on humidity (within 0.5% RH of control setting) throughout pre- and postweighing at each stepwise increase in RH, it was possible to quantify error due to water absorption: 45% of the total mass change due to water absorption occurred between 16 and 50% RH, and 55% occurred between 50 and 60% RH. The buoyancy corrections ranged from -3.5 to +5.8 microg in magnitude and improved relative standard deviation (RSD) from 21.3% (uncorrected) to 5.6% (corrected) for a 7.2 microg sample. It is recommended that protocols for weighing low-mass particle samples (e.g., nanoparticle samples) should include buoyancy corrections and tight temperature/humidity controls. In some cases, conditioning times longer than 24 hr may be warranted.

A Rasch Perspective

ERIC Educational Resources Information Center

Schumacker, Randall E.; Smith, Everett V., Jr.

2007-01-01

Measurement error is a common theme in classical measurement models used in testing and assessment. In classical measurement models, the definition of measurement error and the subsequent reliability coefficients differ on the basis of the test administration design. Internal consistency reliability specifies error due primarily to poor item…

Targeted observations to improve tropical cyclone track forecasts in the Atlantic and eastern Pacific basins

NASA Astrophysics Data System (ADS)

Aberson, Sim David

In 1997, the National Hurricane Center and the Hurricane Research Division began conducting operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve operational forecast models. During the first two years, twenty-four missions were conducted around tropical cyclones threatening the continental United States, Puerto Rico, and the Virgin Islands. Global Positioning System dropwindsondes were released from the aircraft at 150--200 km intervals along the flight track in the tropical cyclone environment to obtain wind, temperature, and humidity profiles from flight level (around 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and transmitted to the National Centers for Environmental Prediction (NCEP). There, they were ingested into the Global Data Assimilation System that subsequently provides initial and time-dependent boundary conditions for numerical models that forecast tropical cyclone track and intensity. Three dynamical models were employed in testing the targeting and sampling strategies. With the assimilation into the numerical guidance of all the observations gathered during the surveillance missions, only the 12-h Geophysical Fluid Dynamics Laboratory Hurricane Model forecast showed statistically significant improvement. Neither the forecasts from the Aviation run of the Global Spectral Model nor the shallow-water VICBAR model were improved with the assimilation of the dropwindsonde data. This mediocre result is found to be due mainly to the difficulty in operationally quantifying the storm-motion vector used to create accurate synthetic data to represent the tropical cyclone vortex in the models. A secondary limit on forecast improvements from the surveillance missions is the limited amount of data provided by the one surveillance aircraft in regular missions. The inability of some surveillance missions to surround the tropical cyclone with dropwindsonde observations is a possible third limit, though the results are inconclusive. Due to limited aircraft resources, optimal observing strategies for these missions must be developed. Since observations in areas of decaying error modes are unlikely to have large impact on subsequent forecasts, such strategies should be based on taking observations in those geographic locations corresponding to the most rapidly growing error modes in the numerical models and on known deficiencies in current data assimilation systems. Here, the most rapidly growing modes are represented by areas of large forecast spread in the NCEP bred-mode global ensemble forecasting system. The sampling strategy requires sampling the entire target region at approximately the same resolution as the North American rawinsonde network to limit the possibly spurious spread of information from dropwindsonde observations into data-sparse regions where errors are likely to grow. When only the subset of data in these fully-sampled target regions is assimilated into the numerical models, statistically significant reduction of the track forecast errors of up to 25% within the critical first two days of the forecast are seen. These model improvements are comparable with the cumulative business-as-usual track forecast model improvements expected over eighteen years.

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.

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