The evolution of Crew Resource Management training in commercial aviation

NASA Technical Reports Server (NTRS)

Helmreich, R. L.; Merritt, A. C.; Wilhelm, J. A.

1999-01-01

In this study, we describe changes in the nature of Crew Resource Management (CRM) training in commercial aviation, including its shift from cockpit to crew resource management. Validation of the impact of CRM is discussed. Limitations of CRM, including lack of cross-cultural generality are considered. An overarching framework that stresses error management to increase acceptance of CRM concepts is presented. The error management approach defines behavioral strategies taught in CRM as error countermeasures that are employed to avoid error, to trap errors committed, and to mitigate the consequences of error.

[Practical aspects for minimizing errors in the cross-cultural adaptation and validation of quality of life questionnaires].

PubMed

Lauffer, A; Solé, L; Bernstein, S; Lopes, M H; Francisconi, C F

2013-01-01

The development and validation of questionnaires for evaluating quality of life (QoL) has become an important area of research. However, there is a proliferation of non-validated measuring instruments in the health setting that do not contribute to advances in scientific knowledge. To present, through the analysis of available validated questionnaires, a checklist of the practical aspects of how to carry out the cross-cultural adaptation of QoL questionnaires (generic, or disease-specific) so that no step is overlooked in the evaluation process, and thus help prevent the elaboration of insufficient or incomplete validations. We have consulted basic textbooks and Pubmed databases using the following keywords quality of life, questionnaires, and gastroenterology, confined to «validation studies» in English, Spanish, and Portuguese, and with no time limit, for the purpose of analyzing the translation and validation of the questionnaires available through the Mapi Institute and PROQOLID websites. A checklist is presented to aid in the planning and carrying out of the cross-cultural adaptation of QoL questionnaires, in conjunction with a glossary of key terms in the area of knowledge. The acronym DSTAC was used, which refers to each of the 5 stages involved in the recommended procedure. In addition, we provide a table of the QoL instruments that have been validated into Spanish. This article provides information on how to adapt QoL questionnaires from a cross-cultural perspective, as well as to minimize common errors. Copyright © 2012 Asociación Mexicana de Gastroenterología. Published by Masson Doyma México S.A. All rights reserved.

Fast scattering simulation tool for multi-energy x-ray imaging

NASA Astrophysics Data System (ADS)

Sossin, A.; Tabary, J.; Rebuffel, V.; Létang, J. M.; Freud, N.; Verger, L.

2015-12-01

A combination of Monte Carlo (MC) and deterministic approaches was employed as a means of creating a simulation tool capable of providing energy resolved x-ray primary and scatter images within a reasonable time interval. Libraries of Sindbad, a previously developed x-ray simulation software, were used in the development. The scatter simulation capabilities of the tool were validated through simulation with the aid of GATE and through experimentation by using a spectrometric CdTe detector. A simple cylindrical phantom with cavities and an aluminum insert was used. Cross-validation with GATE showed good agreement with a global spatial error of 1.5% and a maximum scatter spectrum error of around 6%. Experimental validation also supported the accuracy of the simulations obtained from the developed software with a global spatial error of 1.8% and a maximum error of around 8.5% in the scatter spectra.

The challenge of estimating the SWOT signal and error spectra over the Ocean and its applications to CalVal and state estimation problems

NASA Astrophysics Data System (ADS)

Ubelmann, C.; Gerald, D.

2016-12-01

The SWOT data validation will be a first challenge after launch, as the nature of the measurement, in particular the two-dimensionality at short spatial scales, is new in altimetry. If the comparison with independent observations may be locally possible, a validation of the full signal and error spectrum will be challenging. However, some recent analyses in simulations have shown the possibility to separate the geophysical signals from the spatially coherent instrumental errors in the spectral space, through cross-spectral analysis. These results suggest that rapidly after launch, the instrument error canl be spectrally separated providing some validations and insights on the Ocean energy spectrum, as well as optimal calibrations. Beyond CalVal, such spectral computations will be also essential for producing high-level Ocean estimates (two and three dimensional Ocean state reconstructions).

Classification of echolocation clicks from odontocetes in the Southern California Bight.

PubMed

Roch, Marie A; Klinck, Holger; Baumann-Pickering, Simone; Mellinger, David K; Qui, Simon; Soldevilla, Melissa S; Hildebrand, John A

2011-01-01

This study presents a system for classifying echolocation clicks of six species of odontocetes in the Southern California Bight: Visually confirmed bottlenose dolphins, short- and long-beaked common dolphins, Pacific white-sided dolphins, Risso's dolphins, and presumed Cuvier's beaked whales. Echolocation clicks are represented by cepstral feature vectors that are classified by Gaussian mixture models. A randomized cross-validation experiment is designed to provide conditions similar to those found in a field-deployed system. To prevent matched conditions from inappropriately lowering the error rate, echolocation clicks associated with a single sighting are never split across the training and test data. Sightings are randomly permuted before assignment to folds in the experiment. This allows different combinations of the training and test data to be used while keeping data from each sighting entirely in the training or test set. The system achieves a mean error rate of 22% across 100 randomized three-fold cross-validation experiments. Four of the six species had mean error rates lower than the overall mean, with the presumed Cuvier's beaked whale clicks showing the best performance (<2% error rate). Long-beaked common and bottlenose dolphins proved the most difficult to classify, with mean error rates of 53% and 68%, respectively.

Portable visible and near-infrared spectrophotometer for triglyceride measurements.

PubMed

Kobayashi, Takanori; Kato, Yukiko Hakariya; Tsukamoto, Megumi; Ikuta, Kazuyoshi; Sakudo, Akikazu

2009-01-01

An affordable and portable machine is required for the practical use of visible and near-infrared (Vis-NIR) spectroscopy. A portable fruit tester comprising a Vis-NIR spectrophotometer was modified for use in the transmittance mode and employed to quantify triglyceride levels in serum in combination with a chemometric analysis. Transmittance spectra collected in the 600- to 1100-nm region were subjected to a partial least-squares regression analysis and leave-out cross-validation to develop a chemometrics model for predicting triglyceride concentrations in serum. The model yielded a coefficient of determination in cross-validation (R2VAL) of 0.7831 with a standard error of cross-validation (SECV) of 43.68 mg/dl. The detection limit of the model was 148.79 mg/dl. Furthermore, masked samples predicted by the model yielded a coefficient of determination in prediction (R2PRED) of 0.6856 with a standard error of prediction (SEP) and detection limit of 61.54 and 159.38 mg/dl, respectively. The portable Vis-NIR spectrophotometer may prove convenient for the measurement of triglyceride concentrations in serum, although before practical use there remain obstacles, which are discussed.

Tuning support vector machines for minimax and Neyman-Pearson classification.

PubMed

Davenport, Mark A; Baraniuk, Richard G; Scott, Clayton D

2010-10-01

This paper studies the training of support vector machine (SVM) classifiers with respect to the minimax and Neyman-Pearson criteria. In principle, these criteria can be optimized in a straightforward way using a cost-sensitive SVM. In practice, however, because these criteria require especially accurate error estimation, standard techniques for tuning SVM parameters, such as cross-validation, can lead to poor classifier performance. To address this issue, we first prove that the usual cost-sensitive SVM, here called the 2C-SVM, is equivalent to another formulation called the 2nu-SVM. We then exploit a characterization of the 2nu-SVM parameter space to develop a simple yet powerful approach to error estimation based on smoothing. In an extensive experimental study, we demonstrate that smoothing significantly improves the accuracy of cross-validation error estimates, leading to dramatic performance gains. Furthermore, we propose coordinate descent strategies that offer significant gains in computational efficiency, with little to no loss in performance.

A systematic review of the measurement properties of the European Organisation for Research and Treatment of Cancer In-patient Satisfaction with Care Questionnaire, the EORTC IN-PATSAT32.

PubMed

Neijenhuijs, Koen I; Jansen, Femke; Aaronson, Neil K; Brédart, Anne; Groenvold, Mogens; Holzner, Bernhard; Terwee, Caroline B; Cuijpers, Pim; Verdonck-de Leeuw, Irma M

2018-05-07

The EORTC IN-PATSAT32 is a patient-reported outcome measure (PROM) to assess cancer patients' satisfaction with in-patient health care. The aim of this study was to investigate whether the initial good measurement properties of the IN-PATSAT32 are confirmed in new studies. Within the scope of a larger systematic review study (Prospero ID 42017057237), a systematic search was performed of Embase, Medline, PsycINFO, and Web of Science for studies that investigated measurement properties of the IN-PATSAT32 up to July 2017. Study quality was assessed, data were extracted, and synthesized according to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. Nine studies were included in this review. The evidence on reliability and construct validity were rated as sufficient and of the quality of the evidence as moderate. The evidence on structural validity was rated as insufficient and of low quality. The evidence on internal consistency was indeterminate. Measurement error, responsiveness, criterion validity, and cross-cultural validity were not reported in the included studies. Measurement error could be calculated for two studies and was judged indeterminate. In summary, the IN-PATSAT32 performs as expected with respect to reliability and construct validity. No firm conclusions can be made yet whether the IN-PATSAT32 also performs as well with respect to structural validity and internal consistency. Further research on these measurement properties of the PROM is therefore needed as well as on measurement error, responsiveness, criterion validity, and cross-cultural validity. For future studies, it is recommended to take the COSMIN methodology into account.

Environmental fate model for ultra-low-volume insecticide applications used for adult mosquito management

USGS Publications Warehouse

Schleier, Jerome J.; Peterson, Robert K.D.; Irvine, Kathryn M.; Marshall, Lucy M.; Weaver, David K.; Preftakes, Collin J.

2012-01-01

One of the more effective ways of managing high densities of adult mosquitoes that vector human and animal pathogens is ultra-low-volume (ULV) aerosol applications of insecticides. The U.S. Environmental Protection Agency uses models that are not validated for ULV insecticide applications and exposure assumptions to perform their human and ecological risk assessments. Currently, there is no validated model that can accurately predict deposition of insecticides applied using ULV technology for adult mosquito management. In addition, little is known about the deposition and drift of small droplets like those used under conditions encountered during ULV applications. The objective of this study was to perform field studies to measure environmental concentrations of insecticides and to develop a validated model to predict the deposition of ULV insecticides. The final regression model was selected by minimizing the Bayesian Information Criterion and its prediction performance was evaluated using k-fold cross validation. Density of the formulation and the density and CMD interaction coefficients were the largest in the model. The results showed that as density of the formulation decreases, deposition increases. The interaction of density and CMD showed that higher density formulations and larger droplets resulted in greater deposition. These results are supported by the aerosol physics literature. A k-fold cross validation demonstrated that the mean square error of the selected regression model is not biased, and the mean square error and mean square prediction error indicated good predictive ability.

Synchronous front-face fluorescence spectroscopy for authentication of the adulteration of edible vegetable oil with refined used frying oil.

PubMed

Tan, Jin; Li, Rong; Jiang, Zi-Tao; Tang, Shu-Hua; Wang, Ying; Shi, Meng; Xiao, Yi-Qian; Jia, Bin; Lu, Tian-Xiang; Wang, Hao

2017-02-15

Synchronous front-face fluorescence spectroscopy has been developed for the discrimination of used frying oil (UFO) from edible vegetable oil (EVO), the estimation of the using time of UFO, and the determination of the adulteration of EVO with UFO. Both the heating time of laboratory prepared UFO and the adulteration of EVO with UFO could be determined by partial least squares regression (PLSR). To simulate the EVO adulteration with UFO, for each kind of oil, fifty adulterated samples at the adulterant amounts range of 1-50% were prepared. PLSR was then adopted to build the model and both full (leave-one-out) cross-validation and external validation were performed to evaluate the predictive ability. Under the optimum condition, the plots of observed versus predicted values exhibited high linearity (R(2)>0.96). The root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) were both lower than 3%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Functional Inference of Complex Anatomical Tendinous Networks at a Macroscopic Scale via Sparse Experimentation

PubMed Central

Saxena, Anupam; Lipson, Hod; Valero-Cuevas, Francisco J.

2012-01-01

In systems and computational biology, much effort is devoted to functional identification of systems and networks at the molecular-or cellular scale. However, similarly important networks exist at anatomical scales such as the tendon network of human fingers: the complex array of collagen fibers that transmits and distributes muscle forces to finger joints. This network is critical to the versatility of the human hand, and its function has been debated since at least the 16th century. Here, we experimentally infer the structure (both topology and parameter values) of this network through sparse interrogation with force inputs. A population of models representing this structure co-evolves in simulation with a population of informative future force inputs via the predator-prey estimation-exploration algorithm. Model fitness depends on their ability to explain experimental data, while the fitness of future force inputs depends on causing maximal functional discrepancy among current models. We validate our approach by inferring two known synthetic Latex networks, and one anatomical tendon network harvested from a cadaver's middle finger. We find that functionally similar but structurally diverse models can exist within a narrow range of the training set and cross-validation errors. For the Latex networks, models with low training set error [<4%] and resembling the known network have the smallest cross-validation errors [∼5%]. The low training set [<4%] and cross validation [<7.2%] errors for models for the cadaveric specimen demonstrate what, to our knowledge, is the first experimental inference of the functional structure of complex anatomical networks. This work expands current bioinformatics inference approaches by demonstrating that sparse, yet informative interrogation of biological specimens holds significant computational advantages in accurate and efficient inference over random testing, or assuming model topology and only inferring parameters values. These findings also hold clues to both our evolutionary history and the development of versatile machines. PMID:23144601

Functional inference of complex anatomical tendinous networks at a macroscopic scale via sparse experimentation.

PubMed

Saxena, Anupam; Lipson, Hod; Valero-Cuevas, Francisco J

2012-01-01

In systems and computational biology, much effort is devoted to functional identification of systems and networks at the molecular-or cellular scale. However, similarly important networks exist at anatomical scales such as the tendon network of human fingers: the complex array of collagen fibers that transmits and distributes muscle forces to finger joints. This network is critical to the versatility of the human hand, and its function has been debated since at least the 16(th) century. Here, we experimentally infer the structure (both topology and parameter values) of this network through sparse interrogation with force inputs. A population of models representing this structure co-evolves in simulation with a population of informative future force inputs via the predator-prey estimation-exploration algorithm. Model fitness depends on their ability to explain experimental data, while the fitness of future force inputs depends on causing maximal functional discrepancy among current models. We validate our approach by inferring two known synthetic Latex networks, and one anatomical tendon network harvested from a cadaver's middle finger. We find that functionally similar but structurally diverse models can exist within a narrow range of the training set and cross-validation errors. For the Latex networks, models with low training set error [<4%] and resembling the known network have the smallest cross-validation errors [∼5%]. The low training set [<4%] and cross validation [<7.2%] errors for models for the cadaveric specimen demonstrate what, to our knowledge, is the first experimental inference of the functional structure of complex anatomical networks. This work expands current bioinformatics inference approaches by demonstrating that sparse, yet informative interrogation of biological specimens holds significant computational advantages in accurate and efficient inference over random testing, or assuming model topology and only inferring parameters values. These findings also hold clues to both our evolutionary history and the development of versatile machines.

Quick method (FT-NIR) for the determination of oil and major fatty acids content in whole achenes of milk thistle (Silybum marianum (L.) Gaertn.).

PubMed

Koláčková, Pavla; Růžičková, Gabriela; Gregor, Tomáš; Šišperová, Eliška

2015-08-30

Calibration models for the Fourier transform-near infrared (FT-NIR) instrument were developed for quick and non-destructive determination of oil and fatty acids in whole achenes of milk thistle. Samples with a range of oil and fatty acid levels were collected and their transmittance spectra were obtained by the FT-NIR instrument. Based on these spectra and data gained by the means of the reference method - Soxhlet extraction and gas chromatography (GC) - calibration models were created by means of partial least square (PLS) regression analysis. Precision and accuracy of the calibration models was verified via the cross-validation of validation samples whose spectra were not part of the calibration model and also according to the root mean square error of prediction (RMSEP), root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV) and the validation coefficient of determination (R(2) ). R(2) for whole seeds were 0.96, 0.96, 0.83 and 0.67 and the RMSEP values were 0.76, 1.68, 1.24, 0.54 for oil, linoleic (C18:2), oleic (C18:1) and palmitic (C16:0) acids, respectively. The calibration models are appropriate for the non-destructive determination of oil and fatty acids levels in whole seeds of milk thistle. © 2014 Society of Chemical Industry.

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

NASA Astrophysics Data System (ADS)

Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad

2018-02-01

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.

Error Consistency Analysis Scheme for Infrared Ultraspectral Sounding Retrieval Error Budget Estimation

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, Larry, L.

2013-01-01

Great effort has been devoted towards validating geophysical parameters retrieved from ultraspectral infrared radiances obtained from satellite remote sensors. An error consistency analysis scheme (ECAS), utilizing fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of mean difference and standard deviation of error in both spectral radiance and retrieval domains. The retrieval error is assessed through ECAS without relying on other independent measurements such as radiosonde data. ECAS establishes a link between the accuracies of radiances and retrieved geophysical parameters. ECAS can be applied to measurements from any ultraspectral instrument and any retrieval scheme with its associated RTM. In this manuscript, ECAS is described and demonstrated with measurements from the MetOp-A satellite Infrared Atmospheric Sounding Interferometer (IASI). This scheme can be used together with other validation methodologies to give a more definitive characterization of the error and/or uncertainty of geophysical parameters retrieved from ultraspectral radiances observed from current and future satellite remote sensors such as IASI, the Atmospheric Infrared Sounder (AIRS), and the Cross-track Infrared Sounder (CrIS).

Quantitative determination of additive Chlorantraniliprole in Abamectin preparation: Investigation of bootstrapping soft shrinkage approach by mid-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Yan, Hong; Song, Xiangzhong; Tian, Kuangda; Chen, Yilin; Xiong, Yanmei; Min, Shungeng

2018-02-01

A novel method, mid-infrared (MIR) spectroscopy, which enables the determination of Chlorantraniliprole in Abamectin within minutes, is proposed. We further evaluate the prediction ability of four wavelength selection methods, including bootstrapping soft shrinkage approach (BOSS), Monte Carlo uninformative variable elimination (MCUVE), genetic algorithm partial least squares (GA-PLS) and competitive adaptive reweighted sampling (CARS) respectively. The results showed that BOSS method obtained the lowest root mean squared error of cross validation (RMSECV) (0.0245) and root mean squared error of prediction (RMSEP) (0.0271), as well as the highest coefficient of determination of cross-validation (Qcv2) (0.9998) and the coefficient of determination of test set (Q2test) (0.9989), which demonstrated that the mid infrared spectroscopy can be used to detect Chlorantraniliprole in Abamectin conveniently. Meanwhile, a suitable wavelength selection method (BOSS) is essential to conducting a component spectral analysis.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules.

PubMed

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-12-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules

NASA Astrophysics Data System (ADS)

Schroeter, Timon Sebastian; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Müller, Klaus-Robert

2007-09-01

We investigate the use of different Machine Learning methods to construct models for aqueous solubility. Models are based on about 4000 compounds, including an in-house set of 632 drug discovery molecules of Bayer Schering Pharma. For each method, we also consider an appropriate method to obtain error bars, in order to estimate the domain of applicability (DOA) for each model. Here, we investigate error bars from a Bayesian model (Gaussian Process (GP)), an ensemble based approach (Random Forest), and approaches based on the Mahalanobis distance to training data (for Support Vector Machine and Ridge Regression models). We evaluate all approaches in terms of their prediction accuracy (in cross-validation, and on an external validation set of 536 molecules) and in how far the individual error bars can faithfully represent the actual prediction error.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

Bias in error estimation when using cross-validation for model selection.

PubMed

Varma, Sudhir; Simon, Richard

2006-02-23

Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data. We used CV to optimize the classification parameters for two kinds of classifiers; Shrunken Centroids and Support Vector Machines (SVM). Random training datasets were created, with no difference in the distribution of the features between the two classes. Using these "null" datasets, we selected classifier parameter values that minimized the CV error estimate. 10-fold CV was used for Shrunken Centroids while Leave-One-Out-CV (LOOCV) was used for the SVM. Independent test data was created to estimate the true error. With "null" and "non null" (with differential expression between the classes) data, we also tested a nested CV procedure, where an inner CV loop is used to perform the tuning of the parameters while an outer CV is used to compute an estimate of the error. The CV error estimate for the classifier with the optimal parameters was found to be a substantially biased estimate of the true error that the classifier would incur on independent data. Even though there is no real difference between the two classes for the "null" datasets, the CV error estimate for the Shrunken Centroid with the optimal parameters was less than 30% on 18.5% of simulated training data-sets. For SVM with optimal parameters the estimated error rate was less than 30% on 38% of "null" data-sets. Performance of the optimized classifiers on the independent test set was no better than chance. The nested CV procedure reduces the bias considerably and gives an estimate of the error that is very close to that obtained on the independent testing set for both Shrunken Centroids and SVM classifiers for "null" and "non-null" data distributions. We show that using CV to compute an error estimate for a classifier that has itself been tuned using CV gives a significantly biased estimate of the true error. Proper use of CV for estimating true error of a classifier developed using a well defined algorithm requires that all steps of the algorithm, including classifier parameter tuning, be repeated in each CV loop. A nested CV procedure provides an almost unbiased estimate of the true error.

The early maximum likelihood estimation model of audiovisual integration in speech perception.

PubMed

Andersen, Tobias S

2015-05-01

Speech perception is facilitated by seeing the articulatory mouth movements of the talker. This is due to perceptual audiovisual integration, which also causes the McGurk-MacDonald illusion, and for which a comprehensive computational account is still lacking. Decades of research have largely focused on the fuzzy logical model of perception (FLMP), which provides excellent fits to experimental observations but also has been criticized for being too flexible, post hoc and difficult to interpret. The current study introduces the early maximum likelihood estimation (MLE) model of audiovisual integration to speech perception along with three model variations. In early MLE, integration is based on a continuous internal representation before categorization, which can make the model more parsimonious by imposing constraints that reflect experimental designs. The study also shows that cross-validation can evaluate models of audiovisual integration based on typical data sets taking both goodness-of-fit and model flexibility into account. All models were tested on a published data set previously used for testing the FLMP. Cross-validation favored the early MLE while more conventional error measures favored more complex models. This difference between conventional error measures and cross-validation was found to be indicative of over-fitting in more complex models such as the FLMP.

Near infrared spectroscopy for prediction of antioxidant compounds in the honey.

PubMed

Escuredo, Olga; Seijo, M Carmen; Salvador, Javier; González-Martín, M Inmaculada

2013-12-15

The selection of antioxidant variables in honey is first time considered applying the near infrared (NIR) spectroscopic technique. A total of 60 honey samples were used to develop the calibration models using the modified partial least squares (MPLS) regression method and 15 samples were used for external validation. Calibration models on honey matrix for the estimation of phenols, flavonoids, vitamin C, antioxidant capacity (DPPH), oxidation index and copper using near infrared (NIR) spectroscopy has been satisfactorily obtained. These models were optimised by cross-validation, and the best model was evaluated according to multiple correlation coefficient (RSQ), standard error of cross-validation (SECV), ratio performance deviation (RPD) and root mean standard error (RMSE) in the prediction set. The result of these statistics suggested that the equations developed could be used for rapid determination of antioxidant compounds in honey. This work shows that near infrared spectroscopy can be considered as rapid tool for the nondestructive measurement of antioxidant constitutes as phenols, flavonoids, vitamin C and copper and also the antioxidant capacity in the honey. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding seasonal variability of uncertainty in hydrological prediction

NASA Astrophysics Data System (ADS)

Li, M.; Wang, Q. J.

2012-04-01

Understanding uncertainty in hydrological prediction can be highly valuable for improving the reliability of streamflow prediction. In this study, a monthly water balance model, WAPABA, in a Bayesian joint probability with error models are presented to investigate the seasonal dependency of prediction error structure. A seasonal invariant error model, analogous to traditional time series analysis, uses constant parameters for model error and account for no seasonal variations. In contrast, a seasonal variant error model uses a different set of parameters for bias, variance and autocorrelation for each individual calendar month. Potential connection amongst model parameters from similar months is not considered within the seasonal variant model and could result in over-fitting and over-parameterization. A hierarchical error model further applies some distributional restrictions on model parameters within a Bayesian hierarchical framework. An iterative algorithm is implemented to expedite the maximum a posterior (MAP) estimation of a hierarchical error model. Three error models are applied to forecasting streamflow at a catchment in southeast Australia in a cross-validation analysis. This study also presents a number of statistical measures and graphical tools to compare the predictive skills of different error models. From probability integral transform histograms and other diagnostic graphs, the hierarchical error model conforms better to reliability when compared to the seasonal invariant error model. The hierarchical error model also generally provides the most accurate mean prediction in terms of the Nash-Sutcliffe model efficiency coefficient and the best probabilistic prediction in terms of the continuous ranked probability score (CRPS). The model parameters of the seasonal variant error model are very sensitive to each cross validation, while the hierarchical error model produces much more robust and reliable model parameters. Furthermore, the result of the hierarchical error model shows that most of model parameters are not seasonal variant except for error bias. The seasonal variant error model is likely to use more parameters than necessary to maximize the posterior likelihood. The model flexibility and robustness indicates that the hierarchical error model has great potential for future streamflow predictions.

The propagation of inventory-based positional errors into statistical landslide susceptibility models

NASA Astrophysics Data System (ADS)

Steger, Stefan; Brenning, Alexander; Bell, Rainer; Glade, Thomas

2016-12-01

There is unanimous agreement that a precise spatial representation of past landslide occurrences is a prerequisite to produce high quality statistical landslide susceptibility models. Even though perfectly accurate landslide inventories rarely exist, investigations of how landslide inventory-based errors propagate into subsequent statistical landslide susceptibility models are scarce. The main objective of this research was to systematically examine whether and how inventory-based positional inaccuracies of different magnitudes influence modelled relationships, validation results, variable importance and the visual appearance of landslide susceptibility maps. The study was conducted for a landslide-prone site located in the districts of Amstetten and Waidhofen an der Ybbs, eastern Austria, where an earth-slide point inventory was available. The methodological approach comprised an artificial introduction of inventory-based positional errors into the present landslide data set and an in-depth evaluation of subsequent modelling results. Positional errors were introduced by artificially changing the original landslide position by a mean distance of 5, 10, 20, 50 and 120 m. The resulting differently precise response variables were separately used to train logistic regression models. Odds ratios of predictor variables provided insights into modelled relationships. Cross-validation and spatial cross-validation enabled an assessment of predictive performances and permutation-based variable importance. All analyses were additionally carried out with synthetically generated data sets to further verify the findings under rather controlled conditions. The results revealed that an increasing positional inventory-based error was generally related to increasing distortions of modelling and validation results. However, the findings also highlighted that interdependencies between inventory-based spatial inaccuracies and statistical landslide susceptibility models are complex. The systematic comparisons of 12 models provided valuable evidence that the respective error-propagation was not only determined by the degree of positional inaccuracy inherent in the landslide data, but also by the spatial representation of landslides and the environment, landslide magnitude, the characteristics of the study area, the selected classification method and an interplay of predictors within multiple variable models. Based on the results, we deduced that a direct propagation of minor to moderate inventory-based positional errors into modelling results can be partly counteracted by adapting the modelling design (e.g. generalization of input data, opting for strongly generalizing classifiers). Since positional errors within landslide inventories are common and subsequent modelling and validation results are likely to be distorted, the potential existence of inventory-based positional inaccuracies should always be considered when assessing landslide susceptibility by means of empirical models.

Comparison of machine-learning algorithms to build a predictive model for detecting undiagnosed diabetes - ELSA-Brasil: accuracy study.

PubMed

Olivera, André Rodrigues; Roesler, Valter; Iochpe, Cirano; Schmidt, Maria Inês; Vigo, Álvaro; Barreto, Sandhi Maria; Duncan, Bruce Bartholow

2017-01-01

Type 2 diabetes is a chronic disease associated with a wide range of serious health complications that have a major impact on overall health. The aims here were to develop and validate predictive models for detecting undiagnosed diabetes using data from the Longitudinal Study of Adult Health (ELSA-Brasil) and to compare the performance of different machine-learning algorithms in this task. Comparison of machine-learning algorithms to develop predictive models using data from ELSA-Brasil. After selecting a subset of 27 candidate variables from the literature, models were built and validated in four sequential steps: (i) parameter tuning with tenfold cross-validation, repeated three times; (ii) automatic variable selection using forward selection, a wrapper strategy with four different machine-learning algorithms and tenfold cross-validation (repeated three times), to evaluate each subset of variables; (iii) error estimation of model parameters with tenfold cross-validation, repeated ten times; and (iv) generalization testing on an independent dataset. The models were created with the following machine-learning algorithms: logistic regression, artificial neural network, naïve Bayes, K-nearest neighbor and random forest. The best models were created using artificial neural networks and logistic regression. -These achieved mean areas under the curve of, respectively, 75.24% and 74.98% in the error estimation step and 74.17% and 74.41% in the generalization testing step. Most of the predictive models produced similar results, and demonstrated the feasibility of identifying individuals with highest probability of having undiagnosed diabetes, through easily-obtained clinical data.

Inflammatory bowel disease-specific health-related quality of life instruments: a systematic review of measurement properties.

PubMed

Chen, Xin-Lin; Zhong, Liang-Huan; Wen, Yi; Liu, Tian-Wen; Li, Xiao-Ying; Hou, Zheng-Kun; Hu, Yue; Mo, Chuan-Wei; Liu, Feng-Bin

2017-09-15

This review aims to critically appraise and compare the measurement properties of inflammatory bowel disease (IBD)-specific health-related quality of life instruments. Medline, EMBASE and ISI Web of Knowledge were searched from their inception to May 2016. IBD-specific instruments for patients with Crohn's disease, ulcerative colitis or IBD were enrolled. The basic characteristics and domains of the instruments were collected. The methodological quality of measurement properties and measurement properties of the instruments were assessed. Fifteen IBD-specific instruments were included, which included twelve instruments for adult IBD patients and three for paediatric IBD patients. All of the instruments were developed in North American and European countries. The following common domains were identified: IBD-related symptoms, physical, emotional and social domain. The methodological quality was satisfactory for content validity; fair in internal consistency, reliability, structural validity, hypotheses testing and criterion validity; and poor in measurement error, cross-cultural validity and responsiveness. For adult IBD patients, the IBDQ-32 and its short version (SIBDQ) had good measurement properties and were the most widely used worldwide. For paediatric IBD patients, the IMPACT-III had good measurement properties and had more translated versions. Most methodological quality should be promoted, especially measurement error, cross-cultural validity and responsiveness. The IBDQ-32 was the most widely used instrument with good reliability and validity, followed by the SIBDQ and IMPACT-III. Further validation studies are necessary to support the use of other instruments.

Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA.

PubMed

Gueto, Carlos; Ruiz, José L; Torres, Juan E; Méndez, Jefferson; Vivas-Reyes, Ricardo

2008-03-01

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.

Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error

NASA Astrophysics Data System (ADS)

Jarabo-Amores, María-Pilar; la Mata-Moya, David de; Gil-Pita, Roberto; Rosa-Zurera, Manuel

2013-12-01

The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the validity of the study.

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

NASA Astrophysics Data System (ADS)

Ali, Mumtaz; Deo, Ravinesh C.; Downs, Nathan J.; Maraseni, Tek

2018-07-01

Forecasting drought by means of the World Meteorological Organization-approved Standardized Precipitation Index (SPI) is considered to be a fundamental task to support socio-economic initiatives and effectively mitigating the climate-risk. This study aims to develop a robust drought modelling strategy to forecast multi-scalar SPI in drought-rich regions of Pakistan where statistically significant lagged combinations of antecedent SPI are used to forecast future SPI. With ensemble-Adaptive Neuro Fuzzy Inference System ('ensemble-ANFIS') executed via a 10-fold cross-validation procedure, a model is constructed by randomly partitioned input-target data. Resulting in 10-member ensemble-ANFIS outputs, judged by mean square error and correlation coefficient in the training period, the optimal forecasts are attained by the averaged simulations, and the model is benchmarked with M5 Model Tree and Minimax Probability Machine Regression (MPMR). The results show the proposed ensemble-ANFIS model's preciseness was notably better (in terms of the root mean square and mean absolute error including the Willmott's, Nash-Sutcliffe and Legates McCabe's index) for the 6- and 12- month compared to the 3-month forecasts as verified by the largest error proportions that registered in smallest error band. Applying 10-member simulations, ensemble-ANFIS model was validated for its ability to forecast severity (S), duration (D) and intensity (I) of drought (including the error bound). This enabled uncertainty between multi-models to be rationalized more efficiently, leading to a reduction in forecast error caused by stochasticity in drought behaviours. Through cross-validations at diverse sites, a geographic signature in modelled uncertainties was also calculated. Considering the superiority of ensemble-ANFIS approach and its ability to generate uncertainty-based information, the study advocates the versatility of a multi-model approach for drought-risk forecasting and its prime importance for estimating drought properties over confidence intervals to generate better information for strategic decision-making.

[Gaussian process regression and its application in near-infrared spectroscopy analysis].

PubMed

Feng, Ai-Ming; Fang, Li-Min; Lin, Min

2011-06-01

Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.

Validity of segmental bioelectrical impedance analysis for estimating fat-free mass in children including overweight individuals.

PubMed

Ohta, Megumi; Midorikawa, Taishi; Hikihara, Yuki; Masuo, Yoshihisa; Sakamoto, Shizuo; Torii, Suguru; Kawakami, Yasuo; Fukunaga, Tetsuo; Kanehisa, Hiroaki

2017-02-01

This study examined the validity of segmental bioelectrical impedance (BI) analysis for predicting the fat-free masses (FFMs) of whole-body and body segments in children including overweight individuals. The FFM and impedance (Z) values of arms, trunk, legs, and whole body were determined using a dual-energy X-ray absorptiometry and segmental BI analyses, respectively, in 149 boys and girls aged 6 to 12 years, who were divided into model-development (n = 74), cross-validation (n = 35), and overweight (n = 40) groups. Simple regression analysis was applied to (length) 2 /Z (BI index) for each of the whole-body and 3 segments to develop the prediction equations of the measured FFM of the related body part. In the model-development group, the BI index of each of the 3 segments and whole body was significantly correlated to the measured FFM (R 2 = 0.867-0.932, standard error of estimation = 0.18-1.44 kg (5.9%-8.7%)). There was no significant difference between the measured and predicted FFM values without systematic error. The application of each equation derived in the model-development group to the cross-validation and overweight groups did not produce significant differences between the measured and predicted FFM values and systematic errors, with an exception that the arm FFM in the overweight group was overestimated. Segmental bioelectrical impedance analysis is useful for predicting the FFM of each of whole-body and body segments in children including overweight individuals, although the application for estimating arm FFM in overweight individuals requires a certain modification.

Proton-nucleus total inelastic cross sections - An empirical formula for E greater than 10 MeV

NASA Technical Reports Server (NTRS)

Letaw, J. R.; Silberberg, R.; Tsao, C. H.

1983-01-01

An empirical formula for the total inelastic cross section of protons on nuclei with charge greater than 1 is presented. The formula is valid with a varying degree of accuracy down to proton energies of 10 MeV. At high energies (equal to or greater than 2 GeV) the formula reproduces experimental data to within reported errors (about 2%).

The Vocal Cord Dysfunction Questionnaire: Validity and Reliability of the Persian Version.

PubMed

Ghaemi, Hamide; Khoddami, Seyyedeh Maryam; Soleymani, Zahra; Zandieh, Fariborz; Jalaie, Shohreh; Ahanchian, Hamid; Khadivi, Ehsan

2017-12-25

The aim of this study was to develop, validate, and assess the reliability of the Persian version of Vocal Cord Dysfunction Questionnaire (VCDQ P ). The study design was cross-sectional or cultural survey. Forty-four patients with vocal fold dysfunction (VFD) and 40 healthy volunteers were recruited for the study. To assess the content validity, the prefinal questions were given to 15 experts to comment on its essential. Ten patients with VFD rated the importance of VCDQ P in detecting face validity. Eighteen of the patients with VFD completed the VCDQ 1 week later for test-retest reliability. To detect absolute reliability, standard error of measurement and smallest detected change were calculated. Concurrent validity was assessed by completing the Persian Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT) by 34 patients with VFD. Discriminant validity was measured from 34 participants. The VCDQ was further validated by administering the questionnaire to 40 healthy volunteers. Validation of the VCDQ as a treatment outcome tool was conducted in 18 patients with VFD using pre- and posttreatment scores. The internal consistency was confirmed (Cronbach α = 0.78). The test-retest reliability was excellent (intraclass correlation coefficient = 0.97). The standard error of measurement and smallest detected change values were acceptable (0.39 and 1.08, respectively). There was a significant correlation between the VCDQ P and the CAT total scores (P < 0.05). Discriminative validity was significantly different. The VCDQ scores in patients with VFD before and after treatment was significantly different (P < 0.001). The VCDQ was cross-culturally adapted to Persian and demonstrated to be a valid and reliable self-administered questionnaire in Persian-speaking population. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Dynamic Time Warping compared to established methods for validation of musculoskeletal models.

PubMed

Gaspar, Martin; Welke, Bastian; Seehaus, Frank; Hurschler, Christof; Schwarze, Michael

2017-04-11

By means of Multi-Body musculoskeletal simulation, important variables such as internal joint forces and moments can be estimated which cannot be measured directly. Validation can ensued by qualitative or by quantitative methods. Especially when comparing time-dependent signals, many methods do not perform well and validation is often limited to qualitative approaches. The aim of the present study was to investigate the capabilities of the Dynamic Time Warping (DTW) algorithm for comparing time series, which can quantify phase as well as amplitude errors. We contrast the sensitivity of DTW with other established metrics: the Pearson correlation coefficient, cross-correlation, the metric according to Geers, RMSE and normalized RMSE. This study is based on two data sets, where one data set represents direct validation and the other represents indirect validation. Direct validation was performed in the context of clinical gait-analysis on trans-femoral amputees fitted with a 6 component force-moment sensor. Measured forces and moments from amputees' socket-prosthesis are compared to simulated forces and moments. Indirect validation was performed in the context of surface EMG measurements on a cohort of healthy subjects with measurements taken of seven muscles of the leg, which were compared to simulated muscle activations. Regarding direct validation, a positive linear relation between results of RMSE and nRMSE to DTW can be seen. For indirect validation, a negative linear relation exists between Pearson correlation and cross-correlation. We propose the DTW algorithm for use in both direct and indirect quantitative validation as it correlates well with methods that are most suitable for one of the tasks. However, in DV it should be used together with methods resulting in a dimensional error value, in order to be able to interpret results more comprehensible. Copyright © 2017 Elsevier Ltd. All rights reserved.

[The Use of FTIR Coupled with Partial Least Square for Quantitative Analysis of the Main Composition of Bamboo/Polypropylene Composites].

PubMed

Lao, Wan-li; He, Yu-chan; Li, Gai-yun; Zhou, Qun

2016-01-01

The biomass to plastic ratio in wood plastic composites (WPCs) greatly affects the physical and mechanical properties and price. Fast and accurate evaluation of the biomass to plastic ratio is important for the further development of WPCs. Quantitative analysis of the WPC main composition currently relies primarily on thermo-analytical methods. However, these methods have some inherent disadvantages, including time-consuming, high analytical errors and sophisticated, which severely limits the applications of these techniques. Therefore, in this study, Fourier Transform Infrared (FTIR) spectroscopy in combination with partial least square (PLS) has been used for rapid prediction of bamboo and polypropylene (PP) content in bamboo/PP composites. The bamboo powders were used as filler after being dried at 105 degrees C for 24 h. PP was used as matrix materials, and some chemical regents were used as additives. Then 42 WPC samples with different ratios of bamboo and PP were prepared by the methods of extrusion. FTIR spectral data of 42 WPC samples were collected by means of KBr pellets technique. The model for bamboo and PP content prediction was developed by PLS-2 and full cross validation. Results of internal cross validation showed that the first derivative spectra in the range of 1 800-800 cm(-1) corrected by standard normal variate (SNV) yielded the optimal model. For both bamboo and PP calibration, the coefficients of determination (R2) were 0.955. The standard errors of calibration (SEC) were 1.872 for bamboo content and 1.848 for PP content, respectively. For both bamboo and PP validation, the R2 values were 0.950. The standard errors of cross validation (SECV) were 1.927 for bamboo content and 1.950 for PP content, respectively. And the ratios of performance to deviation (RPD) were 4.45 for both biomass and PP examinations. The results of external validation showed that the relative prediction deviations for both biomass and PP contents were lower than ± 6%. FTIR combined with PLS can be used for rapid and accurate determination of bamboo and PP content in bamboo/PP composites.

Proportion of medication error reporting and associated factors among nurses: a cross sectional study.

PubMed

Jember, Abebaw; Hailu, Mignote; Messele, Anteneh; Demeke, Tesfaye; Hassen, Mohammed

2018-01-01

A medication error (ME) is any preventable event that may cause or lead to inappropriate medication use or patient harm. Voluntary reporting has a principal role in appreciating the extent and impact of medication errors. Thus, exploration of the proportion of medication error reporting and associated factors among nurses is important to inform service providers and program implementers so as to improve the quality of the healthcare services. Institution based quantitative cross-sectional study was conducted among 397 nurses from March 6 to May 10, 2015. Stratified sampling followed by simple random sampling technique was used to select the study participants. The data were collected using structured self-administered questionnaire which was adopted from studies conducted in Australia and Jordan. A pilot study was carried out to validate the questionnaire before data collection for this study. Bivariate and multivariate logistic regression models were fitted to identify factors associated with the proportion of medication error reporting among nurses. An adjusted odds ratio with 95% confidence interval was computed to determine the level of significance. The proportion of medication error reporting among nurses was found to be 57.4%. Regression analysis showed that sex, marital status, having made a medication error and medication error experience were significantly associated with medication error reporting. The proportion of medication error reporting among nurses in this study was found to be higher than other studies.

Cross-cultural adaptation and validation of the osteoporosis assessment questionnaire short version (OPAQ-SV) for Chinese osteoporotic fracture females.

PubMed

Zhang, Yin-Ping; Wei, Huan-Huan; Wang, Wen; Xia, Ru-Yi; Zhou, Xiao-Ling; Porr, Caroline; Lammi, Mikko

2016-04-01

The Osteoporosis Assessment Questionnaire Short Version (OPAQ-SV) was cross-culturally adapted to measure health-related quality of life in Chinese osteoporotic fracture females and then validated in China for its psychometric properties. Cross-cultural adaptation, including translation of the original OPAQ-SV into Mandarin Chinese language, was performed according to published guidelines. Validation of the newly cross-culturally adapted OPAQ-SV was conducted by sampling 234 Chinese osteoporotic fracture females and also a control group of 235 Chinese osteoporotic females without fractures, producing robust content, construct, and discriminant validation results. Major categories of reliability were also met: the Cronbach alpha coefficient was 0.975, indicating good internal consistency; the test-retest reliability was 0.80; and principal component analysis resulted in a 6-factor structure explaining 75.847 % of the total variance. Further, the Comparative Fit Index result was 0.922 following the modified model confirmatory factor analysis, and the chi-squared test was 1.98. The root mean squared error of approximation was 0.078. Moreover, significant differences were revealed between females with fractures and those without fractures across all domains (p < 0.001). Overall, the newly cross-culturally adapted OPAQ-SV appears to possess adequate validity and reliability and may be utilized in clinical trials to assess the health-related quality of life in Chinese osteoporotic fracture females.

Cross-cultural adaptation and validation of Persian Achilles tendon Total Rupture Score.

PubMed

Ansari, Noureddin Nakhostin; Naghdi, Soofia; Hasanvand, Sahar; Fakhari, Zahra; Kordi, Ramin; Nilsson-Helander, Katarina

2016-04-01

To cross-culturally adapt the Achilles tendon Total Rupture Score (ATRS) to Persian language and to preliminary evaluate the reliability and validity of a Persian ATRS. A cross-sectional and prospective cohort study was conducted to translate and cross-culturally adapt the ATRS to Persian language (ATRS-Persian) following steps described in guidelines. Thirty patients with total Achilles tendon rupture and 30 healthy subjects participated in this study. Psychometric properties of floor/ceiling effects (responsiveness), internal consistency reliability, test-retest reliability, standard error of measurement (SEM), smallest detectable change (SDC), construct validity, and discriminant validity were tested. Factor analysis was performed to determine the ATRS-Persian structure. There were no floor or ceiling effects that indicate the content and responsiveness of ATRS-Persian. Internal consistency was high (Cronbach's α 0.95). Item-total correlations exceeded acceptable standard of 0.3 for the all items (0.58-0.95). The test-retest reliability was excellent [(ICC)agreement 0.98]. SEM and SDC were 3.57 and 9.9, respectively. Construct validity was supported by a significant correlation between the ATRS-Persian total score and the Persian Foot and Ankle Outcome Score (PFAOS) total score and PFAOS subscales (r = 0.55-0.83). The ATRS-Persian significantly discriminated between patients and healthy subjects. Explanatory factor analysis revealed 1 component. The ATRS was cross-culturally adapted to Persian and demonstrated to be a reliable and valid instrument to measure functional outcomes in Persian patients with Achilles tendon rupture. II.

Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

We introduce a framework to build a survival/risk bump hunting model with a censored time-to-event response. Our Survival Bump Hunting (SBH) method is based on a recursive peeling procedure that uses a specific survival peeling criterion derived from non/semi-parametric statistics such as the hazards-ratio, the log-rank test or the Nelson--Aalen estimator. To optimize the tuning parameter of the model and validate it, we introduce an objective function based on survival or prediction-error statistics, such as the log-rank test and the concordance error rate. We also describe two alternative cross-validation techniques adapted to the joint task of decision-rule making by recursive peeling and survival estimation. Numerical analyses show the importance of replicated cross-validation and the differences between criteria and techniques in both low and high-dimensional settings. Although several non-parametric survival models exist, none addresses the problem of directly identifying local extrema. We show how SBH efficiently estimates extreme survival/risk subgroups unlike other models. This provides an insight into the behavior of commonly used models and suggests alternatives to be adopted in practice. Finally, our SBH framework was applied to a clinical dataset. In it, we identified subsets of patients characterized by clinical and demographic covariates with a distinct extreme survival outcome, for which tailored medical interventions could be made. An R package PRIMsrc (Patient Rule Induction Method in Survival, Regression and Classification settings) is available on CRAN (Comprehensive R Archive Network) and GitHub. PMID:27034730

Cross-validating a bidimensional mathematics anxiety scale.

PubMed

Haiyan Bai

2011-03-01

The psychometric properties of a 14-item bidimensional Mathematics Anxiety Scale-Revised (MAS-R) were empirically cross-validated with two independent samples consisting of 647 secondary school students. An exploratory factor analysis on the scale yielded strong construct validity with a clear two-factor structure. The results from a confirmatory factor analysis indicated an excellent model-fit (χ(2) = 98.32, df = 62; normed fit index = .92, comparative fit index = .97; root mean square error of approximation = .04). The internal consistency (.85), test-retest reliability (.71), interfactor correlation (.26, p < .001), and positive discrimination power indicated that MAS-R is a psychometrically reliable and valid instrument for measuring mathematics anxiety. Math anxiety, as measured by MAS-R, correlated negatively with student achievement scores (r = -.38), suggesting that MAS-R may be a useful tool for classroom teachers and other educational personnel tasked with identifying students at risk of reduced math achievement because of anxiety.

Cross-Cultural Adaptation and Measurement Properties of the Brazilian Portuguese Version of the Victorian Institute of Sport Assessment-Achilles (VISA-A) Questionnaire.

PubMed

de Mesquita, Gabriel Nunes; de Oliveira, Marcela Nicácio Medeiros; Matoso, Amanda Ellen Rodrigues; Filho, Alberto Galvão de Moura; de Oliveira, Rodrigo Ribeiro

2018-04-24

Study Design Clinical measurement study. Background Achilles tendon disorders are very common among athletes and it is important to objectively measure symptoms and functional limitations related to Achilles tendinopathy using outcome measures that have been validated in the language of the target population. Objectives To perform a cross-cultural adaptation and to evaluate the measurement properties of the Brazilian version of the Victorian Institute of Sport Assessment-Achilles (VISA-A) questionnaire. Methods We adapted the VISA-A questionnaire to Brazilian Portuguese (VISA-A-Br). The questionnaire was applied on 2 occasions with an interval of 5 to 14 days. We evaluated the following measurement properties: internal consistency, test-retest reliability, measurement error, construct validity, and ceiling and floor effects. Results The VISA-A-Br showed good internal consistency (Cronbach's alpha = 0.79; after excluding 1 item at a time, Cronbach's α = 0.73 to 0.84), good test-retest reliability (ICC agreement2,1 = 0.84, 95% confidence interval = 0.71-0.91), an acceptable measurement error (standard error of measurement = 3.25 points and Smallest Detectable Change= 9.02 points), good construct validity (Spearman's coefficient with LEFS= 0.73 and FAOS in its 5 subscales; Pain= 0.66, other Symptoms=0.48, Function in daily living (ADL)= 0.59, Function in sport and recreation=0.67, and foot and ankle-related Quality of Life = 0.7), and no ceiling and floor effects. Conclusion The VISA-A-Br is equivalent to the original version; it has been validated and confirmed as reliable to measure pain and function among the Brazilian population with Achilles tendinopathy, and it can be used in clinical and scientific settings. J Orthop Sports Phys Ther, Epub 24 Apr 2018. doi:10.2519/jospt.2018.7897.

R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326

Digital floodplain mapping and an analysis of errors involved

USGS Publications Warehouse

Hamblen, C.S.; Soong, D.T.; Cai, X.

2007-01-01

Mapping floodplain boundaries using geographical information system (GIS) and digital elevation models (DEMs) was completed in a recent study. However convenient this method may appear at first, the resulting maps potentially can have unaccounted errors. Mapping the floodplain using GIS is faster than mapping manually, and digital mapping is expected to be more common in the future. When mapping is done manually, the experience and judgment of the engineer or geographer completing the mapping and the contour resolution of the surface topography are critical in determining the flood-plain and floodway boundaries between cross sections. When mapping is done digitally, discrepancies can result from the use of the computing algorithm and digital topographic datasets. Understanding the possible sources of error and how the error accumulates through these processes is necessary for the validation of automated digital mapping. This study will evaluate the procedure of floodplain mapping using GIS and a 3 m by 3 m resolution DEM with a focus on the accumulated errors involved in the process. Within the GIS environment of this mapping method, the procedural steps of most interest, initially, include: (1) the accurate spatial representation of the stream centerline and cross sections, (2) properly using a triangulated irregular network (TIN) model for the flood elevations of the studied cross sections, the interpolated elevations between them and the extrapolated flood elevations beyond the cross sections, and (3) the comparison of the flood elevation TIN with the ground elevation DEM, from which the appropriate inundation boundaries are delineated. The study area involved is of relatively low topographic relief; thereby, making it representative of common suburban development and a prime setting for the need of accurately mapped floodplains. This paper emphasizes the impacts of integrating supplemental digital terrain data between cross sections on floodplain delineation. ?? 2007 ASCE.

Empirical performance of interpolation techniques in risk-neutral density (RND) estimation

NASA Astrophysics Data System (ADS)

Bahaludin, H.; Abdullah, M. H.

2017-03-01

The objective of this study is to evaluate the empirical performance of interpolation techniques in risk-neutral density (RND) estimation. Firstly, the empirical performance is evaluated by using statistical analysis based on the implied mean and the implied variance of RND. Secondly, the interpolation performance is measured based on pricing error. We propose using the leave-one-out cross-validation (LOOCV) pricing error for interpolation selection purposes. The statistical analyses indicate that there are statistical differences between the interpolation techniques:second-order polynomial, fourth-order polynomial and smoothing spline. The results of LOOCV pricing error shows that interpolation by using fourth-order polynomial provides the best fitting to option prices in which it has the lowest value error.

Correcting evaluation bias of relational classifiers with network cross validation

DOE PAGES

Neville, Jennifer; Gallagher, Brian; Eliassi-Rad, Tina; ...

2011-01-04

Recently, a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.). These methods specifically exploit the statistical dependencies among instances in order to improve classification accuracy. However, there has been little focus on how these same dependencies affect our ability to draw accurate conclusions about the performance of the models. More specifically, the complex link structure and attribute dependencies in relational data violate the assumptions of many conventional statistical tests and make it difficult to use these tests to assess themore » models in an unbiased manner. In this work, we examine the task of within-network classification and the question of whether two algorithms will learn models that will result in significantly different levels of performance. We show that the commonly used form of evaluation (paired t-test on overlapping network samples) can result in an unacceptable level of Type I error. Furthermore, we show that Type I error increases as (1) the correlation among instances increases and (2) the size of the evaluation set increases (i.e., the proportion of labeled nodes in the network decreases). Lastly, we propose a method for network cross-validation that combined with paired t-tests produces more acceptable levels of Type I error while still providing reasonable levels of statistical power (i.e., 1–Type II error).« less

A cross-sectional observational study to assess inhaler technique in Saudi hospitalized patients with asthma and chronic obstructive pulmonary disease

PubMed Central

Ammari, Maha Al; Sultana, Khizra; Yunus, Faisal; Ghobain, Mohammed Al; Halwan, Shatha M. Al

2016-01-01

Objectives: To assess the proportion of critical errors committed while demonstrating the inhaler technique in hospitalized patients diagnosed with asthma and chronic obstructive pulmonary disease (COPD). Methods: This cross-sectional observational study was conducted in 47 asthmatic and COPD patients using inhaler devices. The study took place at King Abdulaziz Medical City, Riyadh, Saudi Arabia between September and December 2013. Two pharmacists independently assessed inhaler technique with a validated checklist. Results: Seventy percent of patients made at least one critical error while demonstrating their inhaler technique, and the mean number of critical errors per patient was 1.6. Most patients used metered dose inhaler (MDI), and 73% of MDI users and 92% of dry powder inhaler users committed at least one critical error. Conclusion: Inhaler technique in hospitalized Saudi patients was inadequate. Health care professionals should understand the importance of reassessing and educating patients on a regular basis for inhaler technique, recommend the use of a spacer when needed, and regularly assess and update their own inhaler technique skills. PMID:27146622

Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

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

Niemeyer, Kyle E.; Sung, Chih-Jen

Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, suchmore » as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.« less

Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

DOE PAGES

Niemeyer, Kyle E.; Sung, Chih-Jen

2014-11-01

Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, suchmore » as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.« less

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

PubMed

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

2005-06-01

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

Cross-coupled control for all-terrain rovers.

PubMed

Reina, Giulio

2013-01-08

Mobile robots are increasingly being used in challenging outdoor environments for applications that include construction, mining, agriculture, military and planetary exploration. In order to accomplish the planned task, it is critical that the motion control system ensure accuracy and robustness. The achievement of high performance on rough terrain is tightly connected with the minimization of vehicle-terrain dynamics effects such as slipping and skidding. This paper presents a cross-coupled controller for a 4-wheel-drive/4-wheel-steer robot, which optimizes the wheel motors' control algorithm to reduce synchronization errors that would otherwise result in wheel slip with conventional controllers. Experimental results, obtained with an all-terrain rover operating on agricultural terrain, are presented to validate the system. It is shown that the proposed approach is effective in reducing slippage and vehicle posture errors.

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).

SEU System Analysis: Not Just the Sum of All Parts

NASA Technical Reports Server (NTRS)

Berg, Melanie D.; Label, Kenneth

2014-01-01

Single event upset (SEU) analysis of complex systems is challenging. Currently, system SEU analysis is performed by component level partitioning and then either: the most dominant SEU cross-sections (SEUs) are used in system error rate calculations; or the partition SEUs are summed to eventually obtain a system error rate. In many cases, system error rates are overestimated because these methods generally overlook system level derating factors. The problem with overestimating is that it can cause overdesign and consequently negatively affect the following: cost, schedule, functionality, and validation/verification. The scope of this presentation is to discuss the risks involved with our current scheme of SEU analysis for complex systems; and to provide alternative methods for improvement.

Nurses' systems thinking competency, medical error reporting, and the occurrence of adverse events: a cross-sectional study.

PubMed

Hwang, Jee-In; Park, Hyeoun-Ae

2017-12-01

Healthcare professionals' systems thinking is emphasized for patient safety. To report nurses' systems thinking competency, and its relationship with medical error reporting and the occurrence of adverse events. A cross-sectional survey using a previously validated Systems Thinking Scale (STS), was conducted. Nurses from two teaching hospitals were invited to participate in the survey. There were 407 (60.3%) completed surveys. The mean STS score was 54.5 (SD 7.3) out of 80. Nurses with higher STS scores were more likely to report medical errors (odds ratio (OR) = 1.05; 95% confidence interval (CI) = 1.02-1.08) and were less likely to be involved in the occurrence of adverse events (OR = 0.96; 95% CI = 0.93-0.98). Nurses showed moderate systems thinking competency. Systems thinking was a significant factor associated with patient safety. Impact Statement: The findings of this study highlight the importance of enhancing nurses' systems thinking capacity to promote patient safety.

Prediction of ethanol in bottled Chinese rice wine by NIR spectroscopy

NASA Astrophysics Data System (ADS)

Ying, Yibin; Yu, Haiyan; Pan, Xingxiang; Lin, Tao

2006-10-01

To evaluate the applicability of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining ethanol concentration of Chinese rice wine in square brown glass bottle, transmission spectra of 100 bottled Chinese rice wine samples were collected in the spectral range of 350-1200 nm. Statistical equations were established between the reference data and VIS-NIR spectra by partial least squares (PLS) regression method. Performance of three kinds of mathematical treatment of spectra (original spectra, first derivative spectra and second derivative spectra) were also discussed. The PLS models of original spectra turned out better results, with higher correlation coefficient in calibration (R cal) of 0.89, lower root mean standard error of calibration (RMSEC) of 0.165, and lower root mean standard error of cross validation (RMSECV) of 0.179. Using original spectra, PLS models for ethanol concentration prediction were developed. The R cal and the correlation coefficient in validation (R val) were 0.928 and 0.875, respectively; and the RMSEC and the root mean standard error of validation (RMSEP) were 0.135 (%, v v -1) and 0.177 (%, v v -1), respectively. The results demonstrated that VIS-NIR spectroscopy could be used to predict ethanol concentration in bottled Chinese rice wine.

Lessons Learned from a Cross-Model Validation between a Discrete Event Simulation Model and a Cohort State-Transition Model for Personalized Breast Cancer Treatment.

PubMed

Jahn, Beate; Rochau, Ursula; Kurzthaler, Christina; Paulden, Mike; Kluibenschädl, Martina; Arvandi, Marjan; Kühne, Felicitas; Goehler, Alexander; Krahn, Murray D; Siebert, Uwe

2016-04-01

Breast cancer is the most common malignancy among women in developed countries. We developed a model (the Oncotyrol breast cancer outcomes model) to evaluate the cost-effectiveness of a 21-gene assay when used in combination with Adjuvant! Online to support personalized decisions about the use of adjuvant chemotherapy. The goal of this study was to perform a cross-model validation. The Oncotyrol model evaluates the 21-gene assay by simulating a hypothetical cohort of 50-year-old women over a lifetime horizon using discrete event simulation. Primary model outcomes were life-years, quality-adjusted life-years (QALYs), costs, and incremental cost-effectiveness ratios (ICERs). We followed the International Society for Pharmacoeconomics and Outcomes Research-Society for Medical Decision Making (ISPOR-SMDM) best practice recommendations for validation and compared modeling results of the Oncotyrol model with the state-transition model developed by the Toronto Health Economics and Technology Assessment (THETA) Collaborative. Both models were populated with Canadian THETA model parameters, and outputs were compared. The differences between the models varied among the different validation end points. The smallest relative differences were in costs, and the greatest were in QALYs. All relative differences were less than 1.2%. The cost-effectiveness plane showed that small differences in the model structure can lead to different sets of nondominated test-treatment strategies with different efficiency frontiers. We faced several challenges: distinguishing between differences in outcomes due to different modeling techniques and initial coding errors, defining meaningful differences, and selecting measures and statistics for comparison (means, distributions, multivariate outcomes). Cross-model validation was crucial to identify and correct coding errors and to explain differences in model outcomes. In our comparison, small differences in either QALYs or costs led to changes in ICERs because of changes in the set of dominated and nondominated strategies. © The Author(s) 2015.

Cross-cultural adaptation, reliability, and validation of the Korean version of the identification functional ankle instability (IdFAI).

PubMed

Ko, Jupil; Rosen, Adam B; Brown, Cathleen N

2017-09-12

To cross-culturally adapt the Identification Functional Ankle Instability for use with Korean-speaking participants. The English version of the IdFAI was cross-culturally adapted into Korean based on the guidelines. The psychometric properties in the Korean version of the IdFAI were measured for test-retest reliability, internal consistency, criterion-related validity, discriminative validity, and measurement error 181 native Korean-speakers. Intra-class correlation coefficients (ICC 2,1 ) between the English and Korean versions of the IdFAI for test-retest reliability was 0.98 (standard error of measurement = 1.41). The Cronbach's alpha coefficient was 0.89 for the Korean versions of IdFAI. The Korean versions of the IdFAI had a strong correlation with the SF-36 (r s  = -0.69, p < .001) and the Korean version of the Cumberland Ankle Instability Tool (r s  = -0.65, p < .001). The cutoff score of >10 was the optimal cutoff score to distinguish between the group memberships. The minimally detectable change of the Korean versions of the IdFAI score was 3.91. The Korean versions of the IdFAI have shown to be an excellent, reliable, and valid instrument. The Korean versions of the IdFAI can be utilized to assess the presence of Chronic Ankle Instability by researchers and clinicians working among Korean-speaking populations. Implications for rehabilitation The high recurrence rate of sprains may result into Chronic Ankle Instability (CAI). The Identification of Functional Ankle Instability Tool (IdFAI) has been validated and recommended to identify patients with Chronic Ankle Instability (CAI). The Korean version of the Identification of Functional Ankle Instability Tool (IdFAI) may be also recommend to researchers and clinicians for assessing the presence of Chronic Ankle Instability (CAI) in Korean-speaking population.

Identification and assessment of common errors in the admission process of patients in Isfahan Fertility and Infertility Center based on "failure modes and effects analysis".

PubMed

Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila

2016-01-01

Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of "failure modes and effects analysis" (FMEA). In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members' decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors.

Identification and assessment of common errors in the admission process of patients in Isfahan Fertility and Infertility Center based on “failure modes and effects analysis”

PubMed Central

Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila

2016-01-01

Background: Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of “failure modes and effects analysis” (FMEA). Materials and Methods: In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members’ decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Results: Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. Conclusions: The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors. PMID:28194208

Estimating monthly streamflow values by cokriging

USGS Publications Warehouse

Solow, A.R.; Gorelick, S.M.

1986-01-01

Cokriging is applied to estimation of missing monthly streamflow values in three records from gaging stations in west central Virginia. Missing values are estimated from optimal consideration of the pattern of auto- and cross-correlation among standardized residual log-flow records. Investigation of the sensitivity of estimation to data configuration showed that when observations are available within two months of a missing value, estimation is improved by accounting for correlation. Concurrent and lag-one observations tend to screen the influence of other available observations. Three models of covariance structure in residual log-flow records are compared using cross-validation. Models differ in how much monthly variation they allow in covariance. Precision of estimation, reflected in mean squared error (MSE), proved to be insensitive to this choice. Cross-validation is suggested as a tool for choosing an inverse transformation when an initial nonlinear transformation is applied to flow values. ?? 1986 Plenum Publishing Corporation.

Cross-cultural adaptation and validation of the Italian Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ).

PubMed

Bucci, Rosaria; Rongo, Roberto; Zito, Eugenio; Galeotti, Angela; Valletta, Rosa; D'Antò, Vincenzo

2015-03-01

To validate and cross-culturally adapt the Italian version of the Psychological Impact of Dental Aesthetics Questionnaire (PIDAQ) among Italian young adults. After translation, back translation, and cross-cultural adaptation of the English PIDAQ, a first version of the Italian questionnaire was pretested. The final Italian PIDAQ was administered to 598 subjects aged 18-30 years, along with two other instruments: the aesthetic component of the index of orthodontic treatment need (IOTN-AC) and the perception of occlusion scale (POS), which identified the self-reporting grade of malocclusion. Structural validity was assessed by means of factorial analysis, internal consistency was measured with Cronbach's alpha coefficient (α), convergent validity was assessed by means of Spearman correlation, and test-retest reliability was calculated with intra-class correlation coefficient (ICC) and standard measurement error. Criterion validity was evaluated by multivariate and univariate analysis of variance with Bonferroni post hoc tests. The α of the Italian PIDAQ domains ranged between 0.79 and 0.92. The ICC was between 0.81 and 0.90. The mean scores of each PIDAQ domain showed a statistically significant difference when analysed according to the IOTN-AC and POS scores. The satisfactory psychometric properties make PIDAQ a usable tool for future studies on oral health-related quality of life among Italian young adults.

Measuring activities and participation in persons with haemophilia: A systematic review of commonly used instruments.

PubMed

Timmer, M A; Gouw, S C; Feldman, B M; Zwagemaker, A; de Kleijn, P; Pisters, M F; Schutgens, R E G; Blanchette, V; Srivastava, A; David, J A; Fischer, K; van der Net, J

2018-03-01

Monitoring clinical outcome in persons with haemophilia (PWH) is essential in order to provide optimal treatment for individual patients and compare effectiveness of treatment strategies. Experience with measurement of activities and participation in haemophilia is limited and consensus on preferred tools is lacking. The aim of this study was to give a comprehensive overview of the measurement properties of a selection of commonly used tools developed to assess activities and participation in PWH. Electronic databases were searched for articles that reported on reliability, validity or responsiveness of predetermined measurement tools (5 self-reported and 4 performance based measurement tools). Methodological quality of the studies was assessed according to the COSMIN checklist. Best evidence synthesis was used to summarize evidence on the measurement properties. The search resulted in 3453 unique hits. Forty-two articles were included. The self-reported Haemophilia Acitivity List (HAL), Pediatric HAL (PedHAL) and the performance based Functional Independence Score in Haemophilia (FISH) were studied most extensively. Methodological quality of the studies was limited. Measurement error, cross-cultural validity and responsiveness have been insufficiently evaluated. Albeit based on limited evidence, the measurement properties of the PedHAL, HAL and FISH are currently considered most satisfactory. Further research needs to focus on measurement error, responsiveness, interpretability and cross-cultural validity of the self-reported tools and validity of performance based tools which are able to assess limitations in sports and leisure activities. © 2018 The Authors. Haemophilia Published by John Wiley & Sons Ltd.

Concussion classification via deep learning using whole-brain white matter fiber strains

PubMed Central

Cai, Yunliang; Wu, Shaoju; Zhao, Wei; Li, Zhigang; Wu, Zheyang

2018-01-01

Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses explicitly pre-defined in a specific brain region of interest. They could suffer from loss of information. A single training dataset has also been used to evaluate performance but without cross-validation. In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains. Using reconstructed American National Football League (NFL) injury cases, leave-one-out cross-validation was employed to objectively compare injury prediction performances against two baseline machine learning classifiers (support vector machine (SVM) and random forest (RF)) and four scalar metrics via univariate logistic regression (Brain Injury Criterion (BrIC), cumulative strain damage measure of the whole brain (CSDM-WB) and the corpus callosum (CSDM-CC), and peak fiber strain in the CC). Feature-based machine learning classifiers including deep learning, SVM, and RF consistently outperformed all scalar injury metrics across all performance categories (e.g., leave-one-out accuracy of 0.828–0.862 vs. 0.690–0.776, and .632+ error of 0.148–0.176 vs. 0.207–0.292). Further, deep learning achieved the best cross-validation accuracy, sensitivity, AUC, and .632+ error. These findings demonstrate the superior performances of deep learning in concussion prediction and suggest its promise for future applications in biomechanical investigations of traumatic brain injury. PMID:29795640

Concussion classification via deep learning using whole-brain white matter fiber strains.

PubMed

Cai, Yunliang; Wu, Shaoju; Zhao, Wei; Li, Zhigang; Wu, Zheyang; Ji, Songbai

2018-01-01

Developing an accurate and reliable injury predictor is central to the biomechanical studies of traumatic brain injury. State-of-the-art efforts continue to rely on empirical, scalar metrics based on kinematics or model-estimated tissue responses explicitly pre-defined in a specific brain region of interest. They could suffer from loss of information. A single training dataset has also been used to evaluate performance but without cross-validation. In this study, we developed a deep learning approach for concussion classification using implicit features of the entire voxel-wise white matter fiber strains. Using reconstructed American National Football League (NFL) injury cases, leave-one-out cross-validation was employed to objectively compare injury prediction performances against two baseline machine learning classifiers (support vector machine (SVM) and random forest (RF)) and four scalar metrics via univariate logistic regression (Brain Injury Criterion (BrIC), cumulative strain damage measure of the whole brain (CSDM-WB) and the corpus callosum (CSDM-CC), and peak fiber strain in the CC). Feature-based machine learning classifiers including deep learning, SVM, and RF consistently outperformed all scalar injury metrics across all performance categories (e.g., leave-one-out accuracy of 0.828-0.862 vs. 0.690-0.776, and .632+ error of 0.148-0.176 vs. 0.207-0.292). Further, deep learning achieved the best cross-validation accuracy, sensitivity, AUC, and .632+ error. These findings demonstrate the superior performances of deep learning in concussion prediction and suggest its promise for future applications in biomechanical investigations of traumatic brain injury.

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

PubMed

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

2012-12-01

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

New equations improve NIR prediction of body fat among high school wrestlers.

PubMed

Oppliger, R A; Clark, R R; Nielsen, D H

2000-09-01

Methodologic study to derive prediction equations for percent body fat (%BF). To develop valid regression equations using NIR to assess body composition among high school wrestlers. Clinicians need a portable, fast, and simple field method for assessing body composition among wrestlers. Near-infrared photospectrometry (NIR) meets these criteria, but its efficacy has been challenged. Subjects were 150 high school wrestlers from 2 Midwestern states with mean +/- SD age of 16.3 +/- 1.1 yrs, weight of 69.5 +/- 11.7 kg, and height of 174.4 +/- 7.0 cm. Relative body fatness (%BF) determined from hydrostatic weighing was the criterion measure, and NIR optical density (OD) measurements at multiple sites, plus height, weight, and body mass index (BMI) were the predictor variables. Four equations were developed with multiple R2s that varied from .530 to .693, root mean squared errors varied from 2.8% BF to 3.4% BF, and prediction errors varied from 2.9% BF to 3.1% BF. The best equation used OD measurements at the biceps, triceps, and thigh sites, BMI, and age. The root mean squared error and prediction error for all 4 equations were equal to or smaller than for a skinfold equation commonly used with wrestlers. The results substantiate the validity of NIR for predicting % BF among high school wrestlers. Cross-validation of these equations is warranted.

Three-dimensional quantitative structure-activity relationship CoMSIA/CoMFA and LeapFrog studies on novel series of bicyclo [4.1.0] heptanes derivatives as melanin-concentrating hormone receptor R1 antagonists.

PubMed

Morales-Bayuelo, Alejandro; Ayazo, Hernan; Vivas-Reyes, Ricardo

2010-10-01

Comparative molecular similarity indices analysis (CoMSIA) and comparative molecular field analysis (CoMFA) were performed on a series of bicyclo [4.1.0] heptanes derivatives as melanin-concentrating hormone receptor R1 antagonists (MCHR1 antagonists). Molecular superimposition of antagonists on the template structure was performed by database alignment method. The statistically significant model was established on sixty five molecules, which were validated by a test set of ten molecules. The CoMSIA model yielded the best predictive model with a q(2) = 0.639, non cross-validated R(2) of 0.953, F value of 92.802, bootstrapped R(2) of 0.971, standard error of prediction = 0.402, and standard error of estimate = 0.146 while the CoMFA model yielded a q(2) = 0.680, non cross-validated R(2) of 0.922, F value of 114.351, bootstrapped R(2) of 0.925, standard error of prediction = 0.364, and standard error of estimate = 0.180. CoMFA analysis maps were employed for generating a pseudo cavity for LeapFrog calculation. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. The results show the variability of steric and electrostatic contributions that determine the activity of the MCHR1 antagonist, with these results we proposed new antagonists that may be more potent than previously reported, these novel antagonists were designed from the addition of highly electronegative groups in the substituent di(i-C(3)H(7))N- of the bicycle [4.1.0] heptanes, using the model CoMFA which also was used for the molecular design using the technique LeapFrog. The data generated from the present study will further help to design novel, potent, and selective MCHR1 antagonists. Copyright (c) 2010 Elsevier Masson SAS. All rights reserved.

2D-QSAR and 3D-QSAR Analyses for EGFR Inhibitors

PubMed Central

Zhao, Manman; Zheng, Linfeng; Qiu, Chun

2017-01-01

Epidermal growth factor receptor (EGFR) is an important target for cancer therapy. In this study, EGFR inhibitors were investigated to build a two-dimensional quantitative structure-activity relationship (2D-QSAR) model and a three-dimensional quantitative structure-activity relationship (3D-QSAR) model. In the 2D-QSAR model, the support vector machine (SVM) classifier combined with the feature selection method was applied to predict whether a compound was an EGFR inhibitor. As a result, the prediction accuracy of the 2D-QSAR model was 98.99% by using tenfold cross-validation test and 97.67% by using independent set test. Then, in the 3D-QSAR model, the model with q2 = 0.565 (cross-validated correlation coefficient) and r2 = 0.888 (non-cross-validated correlation coefficient) was built to predict the activity of EGFR inhibitors. The mean absolute error (MAE) of the training set and test set was 0.308 log units and 0.526 log units, respectively. In addition, molecular docking was also employed to investigate the interaction between EGFR inhibitors and EGFR. PMID:28630865

Cross-Coupled Control for All-Terrain Rovers

PubMed Central

Reina, Giulio

2013-01-01

Mobile robots are increasingly being used in challenging outdoor environments for applications that include construction, mining, agriculture, military and planetary exploration. In order to accomplish the planned task, it is critical that the motion control system ensure accuracy and robustness. The achievement of high performance on rough terrain is tightly connected with the minimization of vehicle-terrain dynamics effects such as slipping and skidding. This paper presents a cross-coupled controller for a 4-wheel-drive/4-wheel-steer robot, which optimizes the wheel motors' control algorithm to reduce synchronization errors that would otherwise result in wheel slip with conventional controllers. Experimental results, obtained with an all-terrain rover operating on agricultural terrain, are presented to validate the system. It is shown that the proposed approach is effective in reducing slippage and vehicle posture errors. PMID:23299625

Land surveys show regional variability of historical fire regimes and dry forest structure of the western United States.

PubMed

Baker, William L; Williams, Mark A

2018-03-01

An understanding of how historical fire and structure in dry forests (ponderosa pine, dry mixed conifer) varied across the western United States remains incomplete. Yet, fire strongly affects ecosystem services, and forest restoration programs are underway. We used General Land Office survey reconstructions from the late 1800s across 11 landscapes covering ~1.9 million ha in four states to analyze spatial variation in fire regimes and forest structure. We first synthesized the state of validation of our methods using 20 modern validations, 53 historical cross-validations, and corroborating evidence. These show our method creates accurate reconstructions with low errors. One independent modern test reported high error, but did not replicate our method and made many calculation errors. Using reconstructed parameters of historical fire regimes and forest structure from our validated methods, forests were found to be non-uniform across the 11 landscapes, but grouped together in three geographical areas. Each had a mixture of fire severities, but dominated by low-severity fire and low median tree density in Arizona, mixed-severity fire and intermediate to high median tree density in Oregon-California, and high-severity fire and intermediate median tree density in Colorado. Programs to restore fire and forest structure could benefit from regional frameworks, rather than one size fits all. © 2018 by the Ecological Society of America.

Validation and upgrading of physically based mathematical models

NASA Technical Reports Server (NTRS)

Duval, Ronald

1992-01-01

The validation of the results of physically-based mathematical models against experimental results was discussed. Systematic techniques are used for: (1) isolating subsets of the simulator mathematical model and comparing the response of each subset to its experimental response for the same input conditions; (2) evaluating the response error to determine whether it is the result of incorrect parameter values, incorrect structure of the model subset, or unmodeled external effects of cross coupling; and (3) modifying and upgrading the model and its parameter values to determine the most physically appropriate combination of changes.

Reply to remarks of R Cross on ‘A comparative study of two types of ball-on-ball collision’

NASA Astrophysics Data System (ADS)

White, Colin

2018-01-01

In this letter, I explain an error which was identified to me in my use of the equation v_n=e^nv0 in the first method of measuring the coefficient of restitution of two colliding Newton’s cradle balls. In fact, for this particular scenario, the correct equation is shown to be v_n=≤ft(\\frac{1+e}{2}\\right)n v0 . However, it is further shown that, in this case, the resulting error is small and the thesis of the paper remains valid.

Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

NASA Astrophysics Data System (ADS)

Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

2017-06-01

Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

Determination of total phenolic compounds in compost by infrared spectroscopy.

PubMed

Cascant, M M; Sisouane, M; Tahiri, S; Krati, M El; Cervera, M L; Garrigues, S; de la Guardia, M

2016-06-01

Middle and near infrared (MIR and NIR) were applied to determine the total phenolic compounds (TPC) content in compost samples based on models built by using partial least squares (PLS) regression. The multiplicative scatter correction, standard normal variate and first derivative were employed as spectra pretreatment, and the number of latent variable were optimized by leave-one-out cross-validation. The performance of PLS-ATR-MIR and PLS-DR-NIR models was evaluated according to root mean square error of cross validation and prediction (RMSECV and RMSEP), the coefficient of determination for prediction (Rpred(2)) and residual predictive deviation (RPD) being obtained for this latter values of 5.83 and 8.26 for MIR and NIR, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

Large-scale collision cross-section profiling on a travelling wave ion mobility mass spectrometer

PubMed Central

Lietz, Christopher B.; Yu, Qing; Li, Lingjun

2014-01-01

Ion mobility (IM) is a gas-phase electrophoretic method that separates ions according to charge and ion-neutral collision cross-section (CCS). Herein, we attempt to apply a travelling wave (TW) IM polyalanine calibration method to shotgun proteomics and create a large peptide CCS database. Mass spectrometry methods that utilize IM, such as HDMSE, often use high transmission voltages for sensitive analysis. However, polyalanine calibration has only been demonstrated with low voltage transmission used to prevent gas-phase activation. If polyalanine ions change conformation under higher transmission voltages used for HDMSE, the calibration may no longer be valid. Thus, we aimed to characterize the accuracy of calibration and CCS measurement under high transmission voltages on a TW IM instrument using the polyalanine calibration method and found that the additional error was not significant. We also evaluated the potential error introduced by liquid chromatography (LC)-HDMSE analysis, and found it to be insignificant as well, validating the calibration method. Finally, we demonstrated the utility of building a large-population peptide CCS database by investigating the effects of terminal lysine position, via LysC or LysN digestion, on the formation of two structural sub-families formed by triply charged ions. PMID:24845359

Evaluation and comparison of predictive individual-level general surrogates.

PubMed

Gabriel, Erin E; Sachs, Michael C; Halloran, M Elizabeth

2018-07-01

An intermediate response measure that accurately predicts efficacy in a new setting at the individual level could be used both for prediction and personalized medical decisions. In this article, we define a predictive individual-level general surrogate (PIGS), which is an individual-level intermediate response that can be used to accurately predict individual efficacy in a new setting. While methods for evaluating trial-level general surrogates, which are predictors of trial-level efficacy, have been developed previously, few, if any, methods have been developed to evaluate individual-level general surrogates, and no methods have formalized the use of cross-validation to quantify the expected prediction error. Our proposed method uses existing methods of individual-level surrogate evaluation within a given clinical trial setting in combination with cross-validation over a set of clinical trials to evaluate surrogate quality and to estimate the absolute prediction error that is expected in a new trial setting when using a PIGS. Simulations show that our method performs well across a variety of scenarios. We use our method to evaluate and to compare candidate individual-level general surrogates over a set of multi-national trials of a pentavalent rotavirus vaccine.

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

Translation, Cross-Cultural Adaptation, and Validation of the Activity Rating Scale for Disorders of the Knee.

PubMed

Flosadottir, Vala; Roos, Ewa M; Ageberg, Eva

2017-09-01

The Activity Rating Scale (ARS) for disorders of the knee evaluates the level of activity by the frequency of participation in 4 separate activities with high demands on knee function, with a score ranging from 0 (none) to 16 (pivoting activities 4 times/wk). To translate and cross-culturally adapt the ARS into Swedish and to assess measurement properties of the Swedish version of the ARS. Cohort study (diagnosis); Level of evidence, 2. The COSMIN guidelines were followed. Participants (N = 100 [55 women]; mean age, 27 years) who were undergoing rehabilitation for a knee injury completed the ARS twice for test-retest reliability. The Knee injury and Osteoarthritis Outcome Score (KOOS), Tegner Activity Scale (TAS), and modernized Saltin-Grimby Physical Activity Level Scale (SGPALS) were administered at baseline to validate the ARS. Construct validity and responsiveness of the ARS were evaluated by testing predefined hypotheses regarding correlations between the ARS, KOOS, TAS, and SGPALS. The Cronbach alpha, intraclass correlation coefficients, absolute reliability, standard error of measurement, smallest detectable change, and Spearman rank-order correlation coefficients were calculated. The ARS showed good internal consistency (α ≈ 0.96), good test-retest reliability (intraclass correlation coefficient >0.9), and no systematic bias between measurements. The standard error of measurement was less than 2 points, and the smallest detectable change was less than 1 point at the group level and less than 5 points at the individual level. More than 75% of the hypotheses were confirmed, indicating good construct validity and good responsiveness of the ARS. The Swedish version of the ARS is valid, reliable, and responsive for evaluating the level of activity based on the frequency of participation in high-demand knee sports activities in young adults with a knee injury.

Geolocation error tracking of ZY-3 three line cameras

NASA Astrophysics Data System (ADS)

Pan, Hongbo

2017-01-01

The high-accuracy geolocation of high-resolution satellite images (HRSIs) is a key issue for mapping and integrating multi-temporal, multi-sensor images. In this manuscript, we propose a new geometric frame for analysing the geometric error of a stereo HRSI, in which the geolocation error can be divided into three parts: the epipolar direction, cross base direction, and height direction. With this frame, we proved that the height error of three line cameras (TLCs) is independent of nadir images, and that the terrain effect has a limited impact on the geolocation errors. For ZY-3 error sources, the drift error in both the pitch and roll angle and its influence on the geolocation accuracy are analysed. Epipolar and common tie-point constraints are proposed to study the bundle adjustment of HRSIs. Epipolar constraints explain that the relative orientation can reduce the number of compensation parameters in the cross base direction and have a limited impact on the height accuracy. The common tie points adjust the pitch-angle errors to be consistent with each other for TLCs. Therefore, free-net bundle adjustment of a single strip cannot significantly improve the geolocation accuracy. Furthermore, the epipolar and common tie-point constraints cause the error to propagate into the adjacent strip when multiple strips are involved in the bundle adjustment, which results in the same attitude uncertainty throughout the whole block. Two adjacent strips-Orbit 305 and Orbit 381, covering 7 and 12 standard scenes separately-and 308 ground control points (GCPs) were used for the experiments. The experiments validate the aforementioned theory. The planimetric and height root mean square errors were 2.09 and 1.28 m, respectively, when two GCPs were settled at the beginning and end of the block.

[Alfalfa quality evaluation in the field by near-infrared reflectance spectroscopy].

PubMed

Xu, Rui-Xuan; Li, Dong-Ning; Yang, Dong-Hai; Lin, Jian-Hai; Xiang, Min; Zhang, Ying-Jun

2013-11-01

To explore the feasibility of using near-infrared reflectance spectroscopy (NIRS) to evaluate alfalfa quality rapidly in the field and try to find the appropriate machine and sample preparation method, the representative population of 170 fresh alfalfa samples collected from different regions with different stages and different cuts were scanned by a portable NIRS spectrometer (1 100 - 1 800 nm). This is the first time to build models of fresh alfalfa to rapidly estimate quality in the field for harvesting in time. The calibrations of dry matter (DM), crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF) were developed through the partial least squares regression (PLS). The determination coefficients of cross-validation (R2((CV)) were 0.831 4, 0.597 9, 0.803 6, 0.786 1 for DM, CP, NDF, ADF, respectively; the root mean standard error of cross-validation (RMSECV) were 1.241 1, 0.261 4, 0.990 3, 0.830 6; The determination coefficients of validation (R2(V)) were 0.815 0, 0.401 1, 0.784 9, 0.752 1 and the root mean standard errors of validation(RMSEP)were 1.06, 0.31, 0.95, 0.80 for DM, CP, NDF, ADF, respectively. For fresh alfalfa ,the calibration of DM, NDF, ADF can do rough quantitative analysis but the CP's calibration is failed. however, as CP in alfalfa hay is enough for animal and the DM, NDF and ADF is the crucial indicator for evaluating havest time, the model of DM, NDF and ADF can be used for evaluating the alfalfa quality rapidly in the field.

Quantitative Determination of Fluorine Content in Blends of Polylactide (PLA)–Talc Using Near Infrared Spectroscopy

PubMed Central

Tamburini, Elena; Tagliati, Chiara; Bonato, Tiziano; Costa, Stefania; Scapoli, Chiara; Pedrini, Paola

2016-01-01

Near-infrared spectroscopy (NIRS) has been widely used for quantitative and/or qualitative determination of a wide range of matrices. The objective of this study was to develop a NIRS method for the quantitative determination of fluorine content in polylactide (PLA)-talc blends. A blending profile was obtained by mixing different amounts of PLA granules and talc powder. The calibration model was built correlating wet chemical data (alkali digestion method) and NIR spectra. Using FT (Fourier Transform)-NIR technique, a Partial Least Squares (PLS) regression model was set-up, in a concentration interval of 0 ppm of pure PLA to 800 ppm of pure talc. Fluorine content prediction (R2cal = 0.9498; standard error of calibration, SEC = 34.77; standard error of cross-validation, SECV = 46.94) was then externally validated by means of a further 15 independent samples (R2EX.V = 0.8955; root mean standard error of prediction, RMSEP = 61.08). A positive relationship between an inorganic component as fluorine and NIR signal has been evidenced, and used to obtain quantitative analytical information from the spectra. PMID:27490548

Body fat measurement by bioelectrical impedance and air displacement plethysmography: a cross-validation study to design bioelectrical impedance equations in Mexican adults

PubMed Central

Macias, Nayeli; Alemán-Mateo, Heliodoro; Esparza-Romero, Julián; Valencia, Mauro E

2007-01-01

Background The study of body composition in specific populations by techniques such as bio-impedance analysis (BIA) requires validation based on standard reference methods. The aim of this study was to develop and cross-validate a predictive equation for bioelectrical impedance using air displacement plethysmography (ADP) as standard method to measure body composition in Mexican adult men and women. Methods This study included 155 male and female subjects from northern Mexico, 20–50 years of age, from low, middle, and upper income levels. Body composition was measured by ADP. Body weight (BW, kg) and height (Ht, cm) were obtained by standard anthropometric techniques. Resistance, R (ohms) and reactance, Xc (ohms) were also measured. A random-split method was used to obtain two samples: one was used to derive the equation by the "all possible regressions" procedure and was cross-validated in the other sample to test predicted versus measured values of fat-free mass (FFM). Results and Discussion The final model was: FFM (kg) = 0.7374 * (Ht2 /R) + 0.1763 * (BW) - 0.1773 * (Age) + 0.1198 * (Xc) - 2.4658. R2 was 0.97; the square root of the mean square error (SRMSE) was 1.99 kg, and the pure error (PE) was 2.96. There was no difference between FFM predicted by the new equation (48.57 ± 10.9 kg) and that measured by ADP (48.43 ± 11.3 kg). The new equation did not differ from the line of identity, had a high R2 and a low SRMSE, and showed no significant bias (0.87 ± 2.84 kg). Conclusion The new bioelectrical impedance equation based on the two-compartment model (2C) was accurate, precise, and free of bias. This equation can be used to assess body composition and nutritional status in populations similar in anthropometric and physical characteristics to this sample. PMID:17697388

Estimating Ground-Level PM(sub 2.5) Concentrations in the Southeastern United States Using MAIAC AOD Retrievals and a Two-Stage Model

NASA Technical Reports Server (NTRS)

Hu, Xuefei; Waller, Lance A.; Lyapustin, Alexei; Wang, Yujie; Al-Hamdan, Mohammad Z.; Crosson, William L.; Estes, Maurice G., Jr.; Estes, Sue M.; Quattrochi, Dale A.; Puttaswamy, Sweta Jinnagara;

QSPR for predicting chloroform formation in drinking water disinfection.

PubMed

Luilo, G B; Cabaniss, S E

2011-01-01

Chlorination is the most widely used technique for water disinfection, but may lead to the formation of chloroform (trichloromethane; TCM) and other by-products. This article reports the first quantitative structure-property relationship (QSPR) for predicting the formation of TCM in chlorinated drinking water. Model compounds (n = 117) drawn from 10 literature sources were divided into training data (n = 90, analysed by five-way leave-many-out internal cross-validation) and external validation data (n = 27). QSPR internal cross-validation had Q² = 0.94 and root mean square error (RMSE) of 0.09 moles TCM per mole compound, consistent with external validation Q2 of 0.94 and RMSE of 0.08 moles TCM per mole compound, and met criteria for high predictive power and robustness. In contrast, log TCM QSPR performed poorly and did not meet the criteria for predictive power. The QSPR predictions were consistent with experimental values for TCM formation from tannic acid and for model fulvic acid structures. The descriptors used are consistent with a relatively small number of important TCM precursor structures based upon 1,3-dicarbonyls or 1,3-diphenols.

Validation of tool mark analysis of cut costal cartilage.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Peters, Charles

2012-03-01

This study was designed to establish the potential error rate associated with the generally accepted method of tool mark analysis of cut marks in costal cartilage. Three knives with different blade types were used to make experimental cut marks in costal cartilage of pigs. Each cut surface was cast, and each cast was examined by three analysts working independently. The presence of striations, regularity of striations, and presence of a primary and secondary striation pattern were recorded for each cast. The distance between each striation was measured. The results showed that striations were not consistently impressed on the cut surface by the blade's cutting edge. Also, blade type classification by the presence or absence of striations led to a 65% misclassification rate. Use of the classification tree and cross-validation methods and inclusion of the mean interstriation distance decreased the error rate to c. 50%. © 2011 American Academy of Forensic Sciences.

Blind system identification of two-thermocouple sensor based on cross-relation method.

PubMed

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

Blind system identification of two-thermocouple sensor based on cross-relation method

NASA Astrophysics Data System (ADS)

Li, Yanfeng; Zhang, Zhijie; Hao, Xiaojian

2018-03-01

In dynamic temperature measurement, the dynamic characteristics of the sensor affect the accuracy of the measurement results. Thermocouples are widely used for temperature measurement in harsh conditions due to their low cost, robustness, and reliability, but because of the presence of the thermal inertia, there is a dynamic error in the dynamic temperature measurement. In order to eliminate the dynamic error, two-thermocouple sensor was used to measure dynamic gas temperature in constant velocity flow environments in this paper. Blind system identification of two-thermocouple sensor based on a cross-relation method was carried out. Particle swarm optimization algorithm was used to estimate time constants of two thermocouples and compared with the grid based search method. The method was validated on the experimental equipment built by using high temperature furnace, and the input dynamic temperature was reconstructed by using the output data of the thermocouple with small time constant.

The orthopaedic error index: development and application of a novel national indicator for assessing the relative safety of hospital care using a cross-sectional approach.

PubMed

Panesar, Sukhmeet S; Netuveli, Gopalakrishnan; Carson-Stevens, Andrew; Javad, Sundas; Patel, Bhavesh; Parry, Gareth; Donaldson, Liam J; Sheikh, Aziz

2013-11-21

The Orthopaedic Error Index for hospitals aims to provide the first national assessment of the relative safety of provision of orthopaedic surgery. Cross-sectional study (retrospective analysis of records in a database). The National Reporting and Learning System is the largest national repository of patient-safety incidents in the world with over eight million error reports. It offers a unique opportunity to develop novel approaches to enhancing patient safety, including investigating the relative safety of different healthcare providers and specialties. We extracted all orthopaedic error reports from the system over 1 year (2009-2010). The Orthopaedic Error Index was calculated as a sum of the error propensity and severity. All relevant hospitals offering orthopaedic surgery in England were then ranked by this metric to identify possible outliers that warrant further attention. 155 hospitals reported 48 971 orthopaedic-related patient-safety incidents. The mean Orthopaedic Error Index was 7.09/year (SD 2.72); five hospitals were identified as outliers. Three of these units were specialist tertiary hospitals carrying out complex surgery; the remaining two outlier hospitals had unusually high Orthopaedic Error Indexes: mean 14.46 (SD 0.29) and 15.29 (SD 0.51), respectively. The Orthopaedic Error Index has enabled identification of hospitals that may be putting patients at disproportionate risk of orthopaedic-related iatrogenic harm and which therefore warrant further investigation. It provides the prototype of a summary index of harm to enable surveillance of unsafe care over time across institutions. Further validation and scrutiny of the method will be required to assess its potential to be extended to other hospital specialties in the UK and also internationally to other health systems that have comparable national databases of patient-safety incidents.

Cognitive tests predict real-world errors: the relationship between drug name confusion rates in laboratory-based memory and perception tests and corresponding error rates in large pharmacy chains

PubMed Central

Schroeder, Scott R; Salomon, Meghan M; Galanter, William L; Schiff, Gordon D; Vaida, Allen J; Gaunt, Michael J; Bryson, Michelle L; Rash, Christine; Falck, Suzanne; Lambert, Bruce L

2017-01-01

Background Drug name confusion is a common type of medication error and a persistent threat to patient safety. In the USA, roughly one per thousand prescriptions results in the wrong drug being filled, and most of these errors involve drug names that look or sound alike. Prior to approval, drug names undergo a variety of tests to assess their potential for confusability, but none of these preapproval tests has been shown to predict real-world error rates. Objectives We conducted a study to assess the association between error rates in laboratory-based tests of drug name memory and perception and real-world drug name confusion error rates. Methods Eighty participants, comprising doctors, nurses, pharmacists, technicians and lay people, completed a battery of laboratory tests assessing visual perception, auditory perception and short-term memory of look-alike and sound-alike drug name pairs (eg, hydroxyzine/hydralazine). Results Laboratory test error rates (and other metrics) significantly predicted real-world error rates obtained from a large, outpatient pharmacy chain, with the best-fitting model accounting for 37% of the variance in real-world error rates. Cross-validation analyses confirmed these results, showing that the laboratory tests also predicted errors from a second pharmacy chain, with 45% of the variance being explained by the laboratory test data. Conclusions Across two distinct pharmacy chains, there is a strong and significant association between drug name confusion error rates observed in the real world and those observed in laboratory-based tests of memory and perception. Regulators and drug companies seeking a validated preapproval method for identifying confusing drug names ought to consider using these simple tests. By using a standard battery of memory and perception tests, it should be possible to reduce the number of confusing look-alike and sound-alike drug name pairs that reach the market, which will help protect patients from potentially harmful medication errors. PMID:27193033

[Research on Resistant Starch Content of Rice Grain Based on NIR Spectroscopy Model].

PubMed

Luo, Xi; Wu, Fang-xi; Xie, Hong-guang; Zhu, Yong-sheng; Zhang, Jian-fu; Xie, Hua-an

2016-03-01

A new method based on near-infrared reflectance spectroscopy (NIRS) analysis was explored to determine the content of rice-resistant starch instead of common chemical method which took long time was high-cost. First of all, we collected 62 spectral data which have big differences in terms of resistant starch content of rice, and then the spectral data and detected chemical values are imported chemometrics software. After that a near-infrared spectroscopy calibration model for rice-resistant starch content was constructed with partial least squares (PLS) method. Results are as follows: In respect of internal cross validation, the coefficient of determination (R2) of untreated, pretreatment with MSC+1thD, pretreatment with 1thD+SNV were 0.920 2, 0.967 0 and 0.976 7 respectively. Root mean square error of prediction (RMSEP) were 1.533 7, 1.011 2 and 0.837 1 respectively. In respect of external validation, the coefficient of determination (R2) of untreated, pretreatment with MSC+ 1thD, pretreatment with 1thD+SNV were 0.805, 0.976 and 0.992 respectively. The average absolute error was 1.456, 0.818, 0.515 respectively. There was no significant difference between chemical and predicted values (Turkey multiple comparison), so we think near infrared spectrum analysis is more feasible than chemical measurement. Among the different pretreatment, the first derivation and standard normal variate (1thD+SNV) have higher coefficient of determination (R2) and lower error value whether in internal validation and external validation. In other words, the calibration model has higher precision and less error by pretreatment with 1thD+SNV.

Validity and test-retest reliability of the six-spot step test in persons after stroke.

PubMed

Arvidsson Lindvall, Mialinn; Anderzén-Carlsson, Agneta; Appelros, Peter; Forsberg, Anette

2018-06-06

After stroke, asymmetric weight distribution is common with decreased balance control in standing and walking. The six-spot step test (SSST) includes a 5-m walk during which one leg shoves wooden blocks out of circles marked on the floor, thus assessing the ability to take load on each leg. The aim of the present study was to investigate the convergent and discriminant validity and test-retest reliability of the SSST in persons with stroke. Eighty-one participants were included. A cross-sectional study was performed, in which the SSST was conducted twice, 3-7 days apart. Validity was investigated using measures of dynamic balance and walking. Reliability was assessed using intraclass correlation coefficient, standard error of the measurement (SEM), and smallest real difference (SRD). The convergent validity was strong to moderate, and the test-retest reliability was good. The SEM% was 14.7%, and the SRD% was 40.8% based on the mean of four walks shoving twice with the paretic and twice with the non-paretic leg. Values on random measurement error were high affecting the use of the SSST for follow-up evaluations but the SSST can be a complementary measure of gait and balance.

An experimental study of interstitial lung tissue classification in HRCT images using ANN and role of cost functions

NASA Astrophysics Data System (ADS)

Dash, Jatindra K.; Kale, Mandar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan; Prabhakar, Nidhi; Garg, Mandeep; Kalra, Naveen

2017-03-01

In this paper, we investigate the effect of the error criteria used during a training phase of the artificial neural network (ANN) on the accuracy of the classifier for classification of lung tissues affected with Interstitial Lung Diseases (ILD). Mean square error (MSE) and the cross-entropy (CE) criteria are chosen being most popular choice in state-of-the-art implementations. The classification experiment performed on the six interstitial lung disease (ILD) patterns viz. Consolidation, Emphysema, Ground Glass Opacity, Micronodules, Fibrosis and Healthy from MedGIFT database. The texture features from an arbitrary region of interest (AROI) are extracted using Gabor filter. Two different neural networks are trained with the scaled conjugate gradient back propagation algorithm with MSE and CE error criteria function respectively for weight updation. Performance is evaluated in terms of average accuracy of these classifiers using 4 fold cross-validation. Each network is trained for five times for each fold with randomly initialized weight vectors and accuracies are computed. Significant improvement in classification accuracy is observed when ANN is trained by using CE (67.27%) as error function compared to MSE (63.60%). Moreover, standard deviation of the classification accuracy for the network trained with CE (6.69) error criteria is found less as compared to network trained with MSE (10.32) criteria.

Joint multifractal analysis based on wavelet leaders

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing

2017-12-01

Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

Quality appraisal of generic self-reported instruments measuring health-related productivity changes: a systematic review

PubMed Central

2014-01-01

Background Health impairments can result in disability and changed work productivity imposing considerable costs for the employee, employer and society as a whole. A large number of instruments exist to measure health-related productivity changes; however their methodological quality remains unclear. This systematic review critically appraised the measurement properties in generic self-reported instruments that measure health-related productivity changes to recommend appropriate instruments for use in occupational and economic health practice. Methods PubMed, PsycINFO, Econlit and Embase were systematically searched for studies whereof: (i) instruments measured health-related productivity changes; (ii) the aim was to evaluate instrument measurement properties; (iii) instruments were generic; (iv) ratings were self-reported; (v) full-texts were available. Next, methodological quality appraisal was based on COSMIN elements: (i) internal consistency; (ii) reliability; (iii) measurement error; (iv) content validity; (v) structural validity; (vi) hypotheses testing; (vii) cross-cultural validity; (viii) criterion validity; and (ix) responsiveness. Recommendations are based on evidence syntheses. Results This review included 25 articles assessing the reliability, validity and responsiveness of 15 different generic self-reported instruments measuring health-related productivity changes. Most studies evaluated criterion validity, none evaluated cross-cultural validity and information on measurement error is lacking. The Work Limitation Questionnaire (WLQ) was most frequently evaluated with moderate respectively strong positive evidence for content and structural validity and negative evidence for reliability, hypothesis testing and responsiveness. Less frequently evaluated, the Stanford Presenteeism Scale (SPS) showed strong positive evidence for internal consistency and structural validity, and moderate positive evidence for hypotheses testing and criterion validity. The Productivity and Disease Questionnaire (PRODISQ) yielded strong positive evidence for content validity, evidence for other properties is lacking. The other instruments resulted in mostly fair-to-poor quality ratings with limited evidence. Conclusions Decisions based on the content of the instrument, usage purpose, target country and population, and available evidence are recommended. Until high-quality studies are in place to accurately assess the measurement properties of the currently available instruments, the WLQ and, in a Dutch context, the PRODISQ are cautiously preferred based on its strong positive evidence for content validity. Based on its strong positive evidence for internal consistency and structural validity, the SPS is cautiously recommended. PMID:24495301

System Error Compensation Methodology Based on a Neural Network for a Micromachined Inertial Measurement Unit

PubMed Central

Liu, Shi Qiang; Zhu, Rong

2016-01-01

Errors compensation of micromachined-inertial-measurement-units (MIMU) is essential in practical applications. This paper presents a new compensation method using a neural-network-based identification for MIMU, which capably solves the universal problems of cross-coupling, misalignment, eccentricity, and other deterministic errors existing in a three-dimensional integrated system. Using a neural network to model a complex multivariate and nonlinear coupling system, the errors could be readily compensated through a comprehensive calibration. In this paper, we also present a thermal-gas MIMU based on thermal expansion, which measures three-axis angular rates and three-axis accelerations using only three thermal-gas inertial sensors, each of which capably measures one-axis angular rate and one-axis acceleration simultaneously in one chip. The developed MIMU (100 × 100 × 100 mm3) possesses the advantages of simple structure, high shock resistance, and large measuring ranges (three-axes angular rates of ±4000°/s and three-axes accelerations of ±10 g) compared with conventional MIMU, due to using gas medium instead of mechanical proof mass as the key moving and sensing elements. However, the gas MIMU suffers from cross-coupling effects, which corrupt the system accuracy. The proposed compensation method is, therefore, applied to compensate the system errors of the MIMU. Experiments validate the effectiveness of the compensation, and the measurement errors of three-axis angular rates and three-axis accelerations are reduced to less than 1% and 3% of uncompensated errors in the rotation range of ±600°/s and the acceleration range of ±1 g, respectively. PMID:26840314

Cross-cultural adaptation and validation of the Patient-Rated Tennis Elbow Evaluation Questionnaire on lateral elbow tendinopathy for French-speaking patients.

PubMed

Kaux, Jean-François; Delvaux, François; Schaus, Jean; Demoulin, Christophe; Locquet, Médéa; Buckinx, Fanny; Beaudart, Charlotte; Dardenne, Nadia; Van Beveren, Julien; Croisier, Jean-Louis; Forthomme, Bénédicte; Bruyère, Olivier

Translation and validation of algo-functional questionnaire. The lateral elbow tendinopathy is a common injury in tennis players and physical workers. The Patient-Rated Tennis Elbow Evaluation (PRTEE) Questionnaire was specifically designed to measure pain and functional limitations in patients with lateral epicondylitis (tennis elbow). First developed in English, this questionnaire has since been translated into several languages. The aims of the study were to translate and cross-culturally adapt the PRTEE questionnaire into French and to evaluate the reliability and validity of this translated version of the questionnaire (PRTEE-F). The PRTEE was translated and cross-culturally adapted into French according to international guidelines. To assess the reliability and validity of the PRTEE-F, 115 participants were asked twice to fill in the PRTEE-F, and once the Disabilities of Arm, Shoulder and Hand Questionnaire (DASH) and the Short Form Health Survey (SF-36). Internal consistency (using Cronbach's alpha), test-retest reliability (using intraclass correlation coefficient (ICC), standard error of measurement and minimal detectable change), and convergent and divergent validity (using the Spearman's correlation coefficients respectively with the DASH and with some subscales of the SF-36) were assessed. The PRTEE was translated into French without any problems. PRTEE-F showed a good test-retest reliability for the overall score (ICC 0.86) and for each item (ICC 0.8-0.96) and a high internal consistency (Cronbach's alpha = 0.98). The correlation analyses revealed high correlation coefficients between PRTEE-F and DASH (convergent validity) and, as expected, a low or moderate correlation with the divergent subscales of the SF-36 (discriminant validity). There was no floor or ceiling effect. The PRTEE questionnaire was successfully cross-culturally adapted into French. The PRTEE-F is reliable and valid for evaluating French-speaking patients with lateral elbow tendinopathy. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

North Atlantic observations sharpen meridional overturning projections

NASA Astrophysics Data System (ADS)

Olson, R.; An, S.-I.; Fan, Y.; Evans, J. P.; Caesar, L.

2018-06-01

Atlantic Meridional Overturning Circulation (AMOC) projections are uncertain due to both model errors, as well as internal climate variability. An AMOC slowdown projected by many climate models is likely to have considerable effects on many aspects of global and North Atlantic climate. Previous studies to make probabilistic AMOC projections have broken new ground. However, they do not drift-correct or cross-validate the projections, and do not fully account for internal variability. Furthermore, they consider a limited subset of models, and ignore the skill of models at representing the temporal North Atlantic dynamics. We improve on previous work by applying Bayesian Model Averaging to weight 13 Coupled Model Intercomparison Project phase 5 models by their skill at modeling the AMOC strength, and its temporal dynamics, as approximated by the northern North-Atlantic temperature-based AMOC Index. We make drift-corrected projections accounting for structural model errors, and for the internal variability. Cross-validation experiments give approximately correct empirical coverage probabilities, which validates our method. Our results present more evidence that AMOC likely already started slowing down. While weighting considerably moderates and sharpens our projections, our results are at low end of previously published estimates. We project mean AMOC changes between periods 1960-1999 and 2060-2099 of -4.0 Sv and -6.8 Sv for RCP4.5 and RCP8.5 emissions scenarios respectively. The corresponding average 90% credible intervals for our weighted experiments are [-7.2, -1.2] and [-10.5, -3.7] Sv respectively for the two scenarios.

Cross-cultural adaptation, reliability and validity of the Turkish version of the Lower Limb Functional Index.

PubMed

Duruturk, Neslihan; Tonga, Eda; Gabel, Charles Philip; Acar, Manolya; Tekindal, Agah

2015-07-26

This study aims to adapt culturally a Turkish version of the Lower Limb Functional Index (LLFI) and to determine its validity, reliability, internal consistency, measurement sensitivity and factor structure in lower limb problems. The LLFI was translated into Turkish and cross-culturally adapted with a double forward-backward protocol that determined face and content validity. Individuals (n = 120) with lower limb musculoskeletal disorders completed the LLFI and Short Form-36 questionnaires and the Timed Up and Go physical test. The psychometric properties were evaluated for the all participants from patient-reported outcome measures made at baseline and repeated at day 3 to determine criterion between scores (Pearson's r), internal consistency (Cronbachs α) and test-retest reliability (intraclass correlation coefficient - ICC 2.1 ). Error was determined using standard error of the measurement (SEM) and minimal detectable change at the 90% level (MDC 90 ), while factor structure was determined using exploratory factor analysis with maximum likelihood extraction and Varimax rotation. The psychometric characteristics showed strong criterion validity (r = 0.74-0.76), high internal consistency (α = 0.82) and high test-retest reability (ICC 2.1  = 0.97). The SEM of 3.2% gave an MDC 90  = 5.8%. The factor structure was uni-dimensional. Turkish version of LLFI was found to be valid and reliable for the measurement of lower limb function in a Turkish population. Implications for Rehabilitation Lower extremity musculoskeletal disorders are common and greatly impact activities among the affected individuals pertaining to daily living, work, leisure and quality of life. Patient-reported outcome (PRO) measures have advantages as they are practical, cost-effective and clinically convenient for use in patient-centered care. The Lower Limb Functional Index is a recently validated PRO measure shown to have strong clinimetric properties.

A Data Mining Approach for Acoustic Diagnosis of Cardiopulmonary Disease

DTIC Science & Technology

2008-06-01

chocolate chip cookies are amazing! This thesis was prepared at The Charles Stark Draper Laboratory, Inc., under Internal Company Research Project 21796...very expensive to perform. New medical technology has been the primary cause for the rising health care costs and insurance premiums. There are two...empirical risk minimization ( ERM ) principle. Generalization error can be minimized by using cross validation to select the best parameters for the

Detection and quantification of adulteration in sandalwood oil through near infrared spectroscopy.

PubMed

Kuriakose, Saji; Thankappan, Xavier; Joe, Hubert; Venkataraman, Venkateswaran

2010-10-01

The confirmation of authenticity of essential oils and the detection of adulteration are problems of increasing importance in the perfumes, pharmaceutical, flavor and fragrance industries. This is especially true for 'value added' products like sandalwood oil. A methodical study is conducted here to demonstrate the potential use of Near Infrared (NIR) spectroscopy along with multivariate calibration models like principal component regression (PCR) and partial least square regression (PLSR) as rapid analytical techniques for the qualitative and quantitative determination of adulterants in sandalwood oil. After suitable pre-processing of the NIR raw spectral data, the models are built-up by cross-validation. The lowest Root Mean Square Error of Cross-Validation and Calibration (RMSECV and RMSEC % v/v) are used as a decision supporting system to fix the optimal number of factors. The coefficient of determination (R(2)) and the Root Mean Square Error of Prediction (RMSEP % v/v) in the prediction sets are used as the evaluation parameters (R(2) = 0.9999 and RMSEP = 0.01355). The overall result leads to the conclusion that NIR spectroscopy with chemometric techniques could be successfully used as a rapid, simple, instant and non-destructive method for the detection of adulterants, even 1% of the low-grade oils, in the high quality form of sandalwood oil.

Quantitative Determination of Fusarium proliferatum Concentration in Intact Garlic Cloves Using Near-Infrared Spectroscopy.

PubMed

Tamburini, Elena; Mamolini, Elisabetta; De Bastiani, Morena; Marchetti, Maria Gabriella

2016-07-15

Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional assays. Preventive detection of infection before seeding is of great interest for farmers, because it could avoid serious losses of yield during harvesting and storage. Spectra were collected on 95 garlic cloves, divided in five classes of infection (from 1-healthy to 5-very highly infected) in the range of fungal concentration 0.34-7231.15 ppb. Calibration and cross validation models were developed with partial least squares regression (PLSR) on pretreated spectra (standard normal variate, SNV, and derivatives), providing good accuracy in prediction, with a coefficient of determination (R²) of 0.829 and 0.774, respectively, a standard error of calibration (SEC) of 615.17 ppb, and a standard error of cross validation (SECV) of 717.41 ppb. The calibration model was then used to predict fungal concentration in unknown samples, peeled and unpeeled. The results showed that NIRS could be used as a reliable tool to directly detect and quantify F. proliferatum infection in peeled intact garlic cloves, but the presence of the external peel strongly affected the prediction reliability.

Mortality risk score prediction in an elderly population using machine learning.

PubMed

Rose, Sherri

2013-03-01

Standard practice for prediction often relies on parametric regression methods. Interesting new methods from the machine learning literature have been introduced in epidemiologic studies, such as random forest and neural networks. However, a priori, an investigator will not know which algorithm to select and may wish to try several. Here I apply the super learner, an ensembling machine learning approach that combines multiple algorithms into a single algorithm and returns a prediction function with the best cross-validated mean squared error. Super learning is a generalization of stacking methods. I used super learning in the Study of Physical Performance and Age-Related Changes in Sonomans (SPPARCS) to predict death among 2,066 residents of Sonoma, California, aged 54 years or more during the period 1993-1999. The super learner for predicting death (risk score) improved upon all single algorithms in the collection of algorithms, although its performance was similar to that of several algorithms. Super learner outperformed the worst algorithm (neural networks) by 44% with respect to estimated cross-validated mean squared error and had an R2 value of 0.201. The improvement of super learner over random forest with respect to R2 was approximately 2-fold. Alternatives for risk score prediction include the super learner, which can provide improved performance.

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm

NASA Astrophysics Data System (ADS)

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV = 0.0776, Rc = 0.9777, RMSEP = 0.0963, and Rp = 0.9686 for pH model; RMSECV = 1.3544% w/w, Rc = 0.8871, RMSEP = 1.4946% w/w, and Rp = 0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry.

Mapping health outcome measures from a stroke registry to EQ-5D weights.

PubMed

Ghatnekar, Ola; Eriksson, Marie; Glader, Eva-Lotta

2013-03-07

To map health outcome related variables from a national register, not part of any validated instrument, with EQ-5D weights among stroke patients. We used two cross-sectional data sets including patient characteristics, outcome variables and EQ-5D weights from the national Swedish stroke register. Three regression techniques were used on the estimation set (n=272): ordinary least squares (OLS), Tobit, and censored least absolute deviation (CLAD). The regression coefficients for "dressing", "toileting", "mobility", "mood", "general health" and "proxy-responders" were applied to the validation set (n=272), and the performance was analysed with mean absolute error (MAE) and mean square error (MSE). The number of statistically significant coefficients varied by model, but all models generated consistent coefficients in terms of sign. Mean utility was underestimated in all models (least in OLS) and with lower variation (least in OLS) compared to the observed. The maximum attainable EQ-5D weight ranged from 0.90 (OLS) to 1.00 (Tobit and CLAD). Health states with utility weights <0.5 had greater errors than those with weights ≥ 0.5 (P<0.01). This study indicates that it is possible to map non-validated health outcome measures from a stroke register into preference-based utilities to study the development of stroke care over time, and to compare with other conditions in terms of utility.

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

PubMed

Parastar, Hadi; Mostafapour, Sara; Azimi, Gholamhasan

2016-01-01

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

A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

PubMed

Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

2016-08-01

A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.

Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

NASA Astrophysics Data System (ADS)

Ward, Logan; Liu, Ruoqian; Krishna, Amar; Hegde, Vinay I.; Agrawal, Ankit; Choudhary, Alok; Wolverton, Chris

2017-07-01

While high-throughput density functional theory (DFT) has become a prevalent tool for materials discovery, it is limited by the relatively large computational cost. In this paper, we explore using DFT data from high-throughput calculations to create faster, surrogate models with machine learning (ML) that can be used to guide new searches. Our method works by using decision tree models to map DFT-calculated formation enthalpies to a set of attributes consisting of two distinct types: (i) composition-dependent attributes of elemental properties (as have been used in previous ML models of DFT formation energies), combined with (ii) attributes derived from the Voronoi tessellation of the compound's crystal structure. The ML models created using this method have half the cross-validation error and similar training and evaluation speeds to models created with the Coulomb matrix and partial radial distribution function methods. For a dataset of 435 000 formation energies taken from the Open Quantum Materials Database (OQMD), our model achieves a mean absolute error of 80 meV/atom in cross validation, which is lower than the approximate error between DFT-computed and experimentally measured formation enthalpies and below 15% of the mean absolute deviation of the training set. We also demonstrate that our method can accurately estimate the formation energy of materials outside of the training set and be used to identify materials with especially large formation enthalpies. We propose that our models can be used to accelerate the discovery of new materials by identifying the most promising materials to study with DFT at little additional computational cost.

Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach

NASA Astrophysics Data System (ADS)

Petersen, D.; Naveed, P.; Ragheb, A.; Niedieker, D.; El-Mashtoly, S. F.; Brechmann, T.; Kötting, C.; Schmiegel, W. H.; Freier, E.; Pox, C.; Gerwert, K.

2017-06-01

Endoscopy plays a major role in early recognition of cancer which is not externally accessible and therewith in increasing the survival rate. Raman spectroscopic fiber-optical approaches can help to decrease the impact on the patient, increase objectivity in tissue characterization, reduce expenses and provide a significant time advantage in endoscopy. In gastroenterology an early recognition of malign and precursor lesions is relevant. Instantaneous and precise differentiation between adenomas as precursor lesions for cancer and hyperplastic polyps on the one hand and between high and low-risk alterations on the other hand is important. Raman fiber-optical measurements of colon biopsy samples taken during colonoscopy were carried out during a clinical study, and samples of adenocarcinoma (22), tubular adenomas (141), hyperplastic polyps (79) and normal tissue (101) from 151 patients were analyzed. This allows us to focus on the bioinformatic analysis and to set stage for Raman endoscopic measurements. Since spectral differences between normal and cancerous biopsy samples are small, special care has to be taken in data analysis. Using a leave-one-patient-out cross-validation scheme, three different outlier identification methods were investigated to decrease the influence of systematic errors, like a residual risk in misplacement of the sample and spectral dilution of marker bands (esp. cancerous tissue) and therewith optimize the experimental design. Furthermore other validations methods like leave-one-sample-out and leave-one-spectrum-out cross-validation schemes were compared with leave-one-patient-out cross-validation. High-risk lesions were differentiated from low-risk lesions with a sensitivity of 79%, specificity of 74% and an accuracy of 77%, cancer and normal tissue with a sensitivity of 79%, specificity of 83% and an accuracy of 81%. Additionally applied outlier identification enabled us to improve the recognition of neoplastic biopsy samples.

Estimation of uncertainty bounds for individual particle image velocimetry measurements from cross-correlation peak ratio

NASA Astrophysics Data System (ADS)

Charonko, John J.; Vlachos, Pavlos P.

2013-06-01

Numerous studies have established firmly that particle image velocimetry (PIV) is a robust method for non-invasive, quantitative measurements of fluid velocity, and that when carefully conducted, typical measurements can accurately detect displacements in digital images with a resolution well below a single pixel (in some cases well below a hundredth of a pixel). However, to date, these estimates have only been able to provide guidance on the expected error for an average measurement under specific image quality and flow conditions. This paper demonstrates a new method for estimating the uncertainty bounds to within a given confidence interval for a specific, individual measurement. Here, cross-correlation peak ratio, the ratio of primary to secondary peak height, is shown to correlate strongly with the range of observed error values for a given measurement, regardless of flow condition or image quality. This relationship is significantly stronger for phase-only generalized cross-correlation PIV processing, while the standard correlation approach showed weaker performance. Using an analytical model of the relationship derived from synthetic data sets, the uncertainty bounds at a 95% confidence interval are then computed for several artificial and experimental flow fields, and the resulting errors are shown to match closely to the predicted uncertainties. While this method stops short of being able to predict the true error for a given measurement, knowledge of the uncertainty level for a PIV experiment should provide great benefits when applying the results of PIV analysis to engineering design studies and computational fluid dynamics validation efforts. Moreover, this approach is exceptionally simple to implement and requires negligible additional computational cost.

Calibration and Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients with Chronic Pain

PubMed Central

Crins, Martine H. P.; Roorda, Leo D.; Smits, Niels; de Vet, Henrica C. W.; Westhovens, Rene; Cella, David; Cook, Karon F.; Revicki, Dennis; van Leeuwen, Jaap; Boers, Maarten; Dekker, Joost; Terwee, Caroline B.

2015-01-01

The Dutch-Flemish PROMIS Group translated the adult PROMIS Pain Interference item bank into Dutch-Flemish. The aims of the current study were to calibrate the parameters of these items using an item response theory (IRT) model, to evaluate the cross-cultural validity of the Dutch-Flemish translations compared to the original English items, and to evaluate their reliability and construct validity. The 40 items in the bank were completed by 1085 Dutch chronic pain patients. Before calibrating the items, IRT model assumptions were evaluated using confirmatory factor analysis (CFA). Items were calibrated using the graded response model (GRM), an IRT model appropriate for items with more than two response options. To evaluate cross-cultural validity, differential item functioning (DIF) for language (Dutch vs. English) was examined. Reliability was evaluated based on standard errors and Cronbach’s alpha. To evaluate construct validity correlations with scores on legacy instruments (e.g., the Disabilities of the Arm, Shoulder and Hand Questionnaire) were calculated. Unidimensionality of the Dutch-Flemish PROMIS Pain Interference item bank was supported by CFA tests of model fit (CFI = 0.986, TLI = 0.986). Furthermore, the data fit the GRM and showed good coverage across the pain interference continuum (threshold-parameters range: -3.04 to 3.44). The Dutch-Flemish PROMIS Pain Interference item bank has good cross-cultural validity (only two out of 40 items showing DIF), good reliability (Cronbach’s alpha = 0.98), and good construct validity (Pearson correlations between 0.62 and 0.75). A computer adaptive test (CAT) and Dutch-Flemish PROMIS short forms of the Dutch-Flemish PROMIS Pain Interference item bank can now be developed. PMID:26214178

Calibration and Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients with Chronic Pain.

PubMed

Crins, Martine H P; Roorda, Leo D; Smits, Niels; de Vet, Henrica C W; Westhovens, Rene; Cella, David; Cook, Karon F; Revicki, Dennis; van Leeuwen, Jaap; Boers, Maarten; Dekker, Joost; Terwee, Caroline B

2015-01-01

The Dutch-Flemish PROMIS Group translated the adult PROMIS Pain Interference item bank into Dutch-Flemish. The aims of the current study were to calibrate the parameters of these items using an item response theory (IRT) model, to evaluate the cross-cultural validity of the Dutch-Flemish translations compared to the original English items, and to evaluate their reliability and construct validity. The 40 items in the bank were completed by 1085 Dutch chronic pain patients. Before calibrating the items, IRT model assumptions were evaluated using confirmatory factor analysis (CFA). Items were calibrated using the graded response model (GRM), an IRT model appropriate for items with more than two response options. To evaluate cross-cultural validity, differential item functioning (DIF) for language (Dutch vs. English) was examined. Reliability was evaluated based on standard errors and Cronbach's alpha. To evaluate construct validity correlations with scores on legacy instruments (e.g., the Disabilities of the Arm, Shoulder and Hand Questionnaire) were calculated. Unidimensionality of the Dutch-Flemish PROMIS Pain Interference item bank was supported by CFA tests of model fit (CFI = 0.986, TLI = 0.986). Furthermore, the data fit the GRM and showed good coverage across the pain interference continuum (threshold-parameters range: -3.04 to 3.44). The Dutch-Flemish PROMIS Pain Interference item bank has good cross-cultural validity (only two out of 40 items showing DIF), good reliability (Cronbach's alpha = 0.98), and good construct validity (Pearson correlations between 0.62 and 0.75). A computer adaptive test (CAT) and Dutch-Flemish PROMIS short forms of the Dutch-Flemish PROMIS Pain Interference item bank can now be developed.

Measuring and Validating Neutron Capture Cross Sections Using a Lead Slowing-Down Spectrometer

NASA Astrophysics Data System (ADS)

Thompson, Nicholas

Accurate nuclear data is essential for the modeling, design, and operation of nuclear systems. In this work, the Rensselaer Polytechnic Institute (RPI) Lead Slowing-Down Spectrometer (LSDS) at the Gaerttner Linear Accelerator Center (LINAC) was used to measure neutron capture cross sections and validate capture cross sections in cross section libraries. The RPI LINAC was used to create a fast burst of neutrons in the center of the LSDS, a large cube of high purity lead. A sample and YAP:Ce scintillator were placed in the LSDS, and as neutrons lost energy through scattering interactions with the lead, the scintillator detected capture gammas resulting from neutron capture events in the sample. Samples of silver, gold, cobalt, iron, indium, molybdenum, niobium, nickel, tin, tantalum, and zirconium were measured. Data was collected as a function of time after neutron pulse, or slowing-down time, which is correlated to average neutron energy. An analog and a digital data acquisition system collected data simultaneously, allowing for collection of pulse shape information as well as timing. Collection of digital data allowed for pulse shape analysis after the experiment. This data was then analyzed and compared to Monte Carlo simulations to validate the accuracy of neutron capture cross section libraries. These measurements represent the first time that neutron capture cross sections have been measured using an LSDS in the United States, and the first time tools such as coincidence measurements and pulse height weighting have been applied to measurements of neutron capture cross sections using an LSDS. Significant differences between measurement results and simulation results were found in multiple materials, and some errors in nuclear data libraries have already been identified due to these measurements.

Model assessment using a multi-metric ranking technique

NASA Astrophysics Data System (ADS)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

Cross-cultural adaptation and measurement properties testing of the Iconographical Falls Efficacy Scale (Icon-FES).

PubMed

Franco, Marcia Rodrigues; Pinto, Rafael Zambelli; Delbaere, Kim; Eto, Bianca Yumie; Faria, Maíra Sgobbi; Aoyagi, Giovana Ayumi; Steffens, Daniel; Pastre, Carlos Marcelo

2018-02-14

The Iconographical Falls Efficacy Scale (Icon-FES) is an innovative tool to assess concern of falling that uses pictures as visual cues to provide more complete environmental contexts. Advantages of Icon-FES over previous scales include the addition of more demanding balance-related activities, ability to assess concern about falling in highly functioning older people, and its normal distribution. To perform a cross-cultural adaptation and to assess the measurement properties of the 30-item and 10-item Icon-FES in a community-dwelling Brazilian older population. The cross-cultural adaptation followed the recommendations of international guidelines. We evaluated the measurement properties (i.e. internal consistency, test-retest reproducibility, standard error of the measurement, minimal detectable change, construct validity, ceiling/floor effect, data distribution and discriminative validity), in 100 community-dwelling people aged ≥60 years. The 30-item and 10-item Icon-FES-Brazil showed good internal consistency (alpha and omega >0.70) and excellent intra-rater reproducibility (ICC 2,1 =0.96 and 0.93, respectively). According to the standard error of the measurement and minimal detectable change, the magnitude of change needed to exceed the measurement error and variability were 7.2 and 3.4 points for the 30-item and 10-item Icon-FES, respectively. We observed an excellent correlation between both versions of the Icon-FES and Falls Efficacy Scale - International (rho=0.83, p<0.001 [30-item version]; 0.76, p<0.001 [10-item version]). Icon-FES versions showed normal distribution, no floor/ceiling effects and were able to discriminate between groups relating to fall risk factors. Icon-FES-Brazil is a semantically and linguistically appropriate tool with acceptable measurement properties to evaluate concern about falling among the community-dwelling older population. Copyright © 2018 Associação Brasileira de Pesquisa e Pós-Graduação em Fisioterapia. Publicado por Elsevier Editora Ltda. All rights reserved.

Real-time sensor data validation

NASA Technical Reports Server (NTRS)

Bickmore, Timothy W.

1994-01-01

This report describes the status of an on-going effort to develop software capable of detecting sensor failures on rocket engines in real time. This software could be used in a rocket engine controller to prevent the erroneous shutdown of an engine due to sensor failures which would otherwise be interpreted as engine failures by the control software. The approach taken combines analytical redundancy with Bayesian belief networks to provide a solution which has well defined real-time characteristics and well-defined error rates. Analytical redundancy is a technique in which a sensor's value is predicted by using values from other sensors and known or empirically derived mathematical relations. A set of sensors and a set of relations among them form a network of cross-checks which can be used to periodically validate all of the sensors in the network. Bayesian belief networks provide a method of determining if each of the sensors in the network is valid, given the results of the cross-checks. This approach has been successfully demonstrated on the Technology Test Bed Engine at the NASA Marshall Space Flight Center. Current efforts are focused on extending the system to provide a validation capability for 100 sensors on the Space Shuttle Main Engine.

Cross-validation of the Beunen-Malina method to predict adult height.

PubMed

Beunen, Gaston P; Malina, Robert M; Freitas, Duarte I; Maia, José A; Claessens, Albrecht L; Gouveia, Elvio R; Lefevre, Johan

2010-08-01

The purpose of this study was to cross-validate the Beunen-Malina method for non-invasive prediction of adult height. Three hundred and eight boys aged 13, 14, 15 and 16 years from the Madeira Growth Study were observed at annual intervals in 1996, 1997 and 1998 and re-measured 7-8 years later. Height, sitting height and the triceps and subscapular skinfolds were measured; skeletal age was assessed using the Tanner-Whitehouse 2 method. Adult height was measured and predicted using the Beunen-Malina method. Maturity groups were classified using relative skeletal age (skeletal age minus chronological age). Pearson correlations, mean differences and standard errors of estimate (SEE) were calculated. Age-specific correlations between predicted and measured adult height vary between 0.70 and 0.85, while age-specific SEE varies between 3.3 and 4.7 cm. The correlations and SEE are similar to those obtained in the development of the original Beunen-Malina method. The Beunen-Malina method is a valid method to predict adult height in adolescent boys and can be used in European populations or populations from European ancestry. Percentage of predicted adult height is a non-invasive valid method to assess biological maturity.

Predictability of Bristol Bay, Alaska, sockeye salmon returns one to four years in the future

USGS Publications Warehouse

Adkison, Milo D.; Peterson, R.M.

2000-01-01

Historically, forecast error for returns of sockeye salmon Oncorhynchus nerka to Bristol Bay, Alaska, has been large. Using cross-validation forecast error as our criterion, we selected forecast models for each of the nine principal Bristol Bay drainages. Competing forecast models included stock-recruitment relationships, environmental variables, prior returns of siblings, or combinations of these predictors. For most stocks, we found prior returns of siblings to be the best single predictor of returns; however, forecast accuracy was low even when multiple predictors were considered. For a typical drainage, an 80% confidence interval ranged from one half to double the point forecast. These confidence intervals appeared to be appropriately wide.

Validity and reliability of rectus femoris ultrasound measurements: Comparison of curved-array and linear-array transducers.

PubMed

Hammond, Kendra; Mampilly, Jobby; Laghi, Franco A; Goyal, Amit; Collins, Eileen G; McBurney, Conor; Jubran, Amal; Tobin, Martin J

2014-01-01

Muscle-mass loss augers increased morbidity and mortality in critically ill patients. Muscle-mass loss can be assessed by wide linear-array ultrasound transducers connected to cumbersome, expensive console units. Whether cheaper, hand-carried units equipped with curved-array transducers can be used as alternatives is unknown. Accordingly, our primary aim was to investigate in 15 nondisabled subjects the validity of measurements of rectus femoris cross-sectional area by using a curved-array transducer against a linear-array transducer-the reference-standard technique. In these subjects, we also determined the reliability of measurements obtained by a novice operator versus measurements obtained by an experienced operator. Lastly, the relationship between quadriceps strength and rectus area recorded by two experienced operators with a curved-array transducer was assessed in 17 patients with chronic obstructive pulmonary disease (COPD). In nondisabled subjects, the rectus cross-sectional area measured with the curved-array transducer by the novice and experienced operators was valid (intraclass correlation coefficient [ICC]: 0.98, typical percentage error [%TE]: 3.7%) and reliable (ICC: 0.79, %TE: 9.7%). In the subjects with COPD, both reliability (ICC: 0.99) and repeatability (%TE: 7.6% and 9.8%) were high. Rectus area was related to quadriceps strength in COPD for both experienced operators (coefficient of determination: 0.67 and 0.70). In conclusion, measurements of rectus femoris cross-sectional area recorded with a curved-array transducer connected to a hand-carried unit are valid, reliable, and reproducible, leading us to contend that this technique is suitable for cross-sectional and longitudinal studies.

Ionospheric Signatures in Radio Occultation Data

NASA Technical Reports Server (NTRS)

Mannucci, Anthony J.; Ao, Chi; Iijima, Byron A.; Kursinkski, E. Robert

2012-01-01

We can extend robustly the radio occultation data record by 6 years (+60%) by developing a singlefrequency processing method for GPS/MET data. We will produce a calibrated data set with profile-byprofile data characterization to determine robust upper bounds on ionospheric bias. Part of an effort to produce a calibrated RO data set addressing other key error sources such as upper boundary initialization. Planned: AIRS-GPS water vapor cross validation (water vapor climatology and trends).

A calibration method immune to the projector errors in fringe projection profilometry

NASA Astrophysics Data System (ADS)

Zhang, Ruihua; Guo, Hongwei

2017-08-01

In fringe projection technique, system calibration is a tedious task to establish the mapping relationship between the object depths and the fringe phases. Especially, it is not easy to accurately determine the parameters of the projector in this system, which may induce errors in the measurement results. To solve this problem, this paper proposes a new calibration by using the cross-ratio invariance in the system geometry for determining the phase-to-depth relations. In it, we analyze the epipolar eometry of the fringe projection system. On each epipolar plane, the depth variation along an incident ray induces the pixel movement along the epipolar line on the image plane of the camera. These depth variations and pixel movements can be connected by use of the projective transformations, under which condition the cross-ratio for each of them keeps invariant. Based on this fact, we suggest measuring the depth map by use of this cross-ratio invariance. Firstly, we shift the reference board in its perpendicular direction to three positions with known depths, and measure their phase maps as the reference phase maps; and secondly, when measuring an object, we calculate the object depth at each pixel by equating the cross-ratio of the depths to that of the corresponding pixels having the same phase on the image plane of the camera. This method is immune to the errors sourced from the projector, including the distortions both in the geometric shapes and in the intensity profiles of the projected fringe patterns.The experimental results demonstrate the proposed method to be feasible and valid.

Translation, Cross-Cultural Adaptation, and Validation of the Activity Rating Scale for Disorders of the Knee

PubMed Central

Flosadottir, Vala; Roos, Ewa M.; Ageberg, Eva

2017-01-01

Background: The Activity Rating Scale (ARS) for disorders of the knee evaluates the level of activity by the frequency of participation in 4 separate activities with high demands on knee function, with a score ranging from 0 (none) to 16 (pivoting activities 4 times/wk). Purpose: To translate and cross-culturally adapt the ARS into Swedish and to assess measurement properties of the Swedish version of the ARS. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: The COSMIN guidelines were followed. Participants (N = 100 [55 women]; mean age, 27 years) who were undergoing rehabilitation for a knee injury completed the ARS twice for test-retest reliability. The Knee injury and Osteoarthritis Outcome Score (KOOS), Tegner Activity Scale (TAS), and modernized Saltin-Grimby Physical Activity Level Scale (SGPALS) were administered at baseline to validate the ARS. Construct validity and responsiveness of the ARS were evaluated by testing predefined hypotheses regarding correlations between the ARS, KOOS, TAS, and SGPALS. The Cronbach alpha, intraclass correlation coefficients, absolute reliability, standard error of measurement, smallest detectable change, and Spearman rank-order correlation coefficients were calculated. Results: The ARS showed good internal consistency (α ≈ 0.96), good test-retest reliability (intraclass correlation coefficient >0.9), and no systematic bias between measurements. The standard error of measurement was less than 2 points, and the smallest detectable change was less than 1 point at the group level and less than 5 points at the individual level. More than 75% of the hypotheses were confirmed, indicating good construct validity and good responsiveness of the ARS. Conclusion: The Swedish version of the ARS is valid, reliable, and responsive for evaluating the level of activity based on the frequency of participation in high-demand knee sports activities in young adults with a knee injury. PMID:28979920

Testing for carryover effects after cessation of treatments: a design approach.

PubMed

Sturdevant, S Gwynn; Lumley, Thomas

2016-08-02

Recently, trials addressing noisy measurements with diagnosis occurring by exceeding thresholds (such as diabetes and hypertension) have been published which attempt to measure carryover - the impact that treatment has on an outcome after cessation. The design of these trials has been criticised and simulations have been conducted which suggest that the parallel-designs used are not adequate to test this hypothesis; two solutions are that either a differing parallel-design or a cross-over design could allow for diagnosis of carryover. We undertook a systematic simulation study to determine the ability of a cross-over or a parallel-group trial design to detect carryover effects on incident hypertension in a population with prehypertension. We simulated blood pressure and focused on varying criteria to diagnose systolic hypertension. Using the difference in cumulative incidence hypertension to analyse parallel-group or cross-over trials resulted in none of the designs having acceptable Type I error rate. Under the null hypothesis of no carryover the difference is well above the nominal 5 % error rate. When a treatment is effective during the intervention period, reliable testing for a carryover effect is difficult. Neither parallel-group nor cross-over designs using the difference in cumulative incidence appear to be a feasible approach. Future trials should ensure their design and analysis is validated by simulation.

Prediction of resource volumes at untested locations using simple local prediction models

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

[Maslach Burnout Inventory - Student Survey: Portugal-Brazil cross-cultural adaptation].

PubMed

Campos, Juliana Alvares Duarte Bonini; Maroco, João

2012-10-01

To perform a cross-cultural adaptation of the Portuguese version of the Maslach Burnout Inventory for students (MBI-SS), and investigate its reliability, validity and cross-cultural invariance. The face validity involved the participation of a multidisciplinary team. Content validity was performed. The Portuguese version was completed in 2009, on the internet, by 958 Brazilian and 556 Portuguese university students from the urban area. Confirmatory factor analysis was carried out using as fit indices: the χ²/df, the Comparative Fit Index (CFI), the Goodness of Fit Index (GFI) and the Root Mean Square Error of Approximation (RMSEA). To verify the stability of the factor solution according to the original English version, cross-validation was performed in 2/3 of the total sample and replicated in the remaining 1/3. Convergent validity was estimated by the average variance extracted and composite reliability. The discriminant validity was assessed, and the internal consistency was estimated by the Cronbach's alpha coefficient. Concurrent validity was estimated by the correlational analysis of the mean scores of the Portuguese version and the Copenhagen Burnout Inventory, and the divergent validity was compared to the Beck Depression Inventory. The invariance of the model between the Brazilian and the Portuguese samples was assessed. The three-factor model of Exhaustion, Disengagement and Efficacy showed good fit (c 2/df = 8.498, CFI = 0.916, GFI = 0.902, RMSEA = 0.086). The factor structure was stable (λ:χ²dif = 11.383, p = 0.50; Cov: χ²dif = 6.479, p = 0.372; Residues: χ²dif = 21.514, p = 0.121). Adequate convergent validity (VEM = 0.45;0.64, CC = 0.82;0.88), discriminant (ρ² = 0.06;0.33) and internal consistency (α = 0.83;0.88) were observed. The concurrent validity of the Portuguese version with the Copenhagen Inventory was adequate (r = 0.21, 0.74). The assessment of the divergent validity was impaired by the approach of the theoretical concept of the dimensions Exhaustion and Disengagement of the Portuguese version with the Beck Depression Inventory. Invariance of the instrument between the Brazilian and Portuguese samples was not observed (λ:χ²dif = 84.768, p<0.001; Cov: χ²dif = 129.206, p < 0.001; Residues: χ²dif = 518.760, p < 0.001). The Portuguese version of the Maslach Burnout Inventory for students showed adequate reliability and validity, but its factor structure was not invariant between the countries, indicating the absence of cross-cultural stability.

Cognitive tests predict real-world errors: the relationship between drug name confusion rates in laboratory-based memory and perception tests and corresponding error rates in large pharmacy chains.

PubMed

Schroeder, Scott R; Salomon, Meghan M; Galanter, William L; Schiff, Gordon D; Vaida, Allen J; Gaunt, Michael J; Bryson, Michelle L; Rash, Christine; Falck, Suzanne; Lambert, Bruce L

2017-05-01

Drug name confusion is a common type of medication error and a persistent threat to patient safety. In the USA, roughly one per thousand prescriptions results in the wrong drug being filled, and most of these errors involve drug names that look or sound alike. Prior to approval, drug names undergo a variety of tests to assess their potential for confusability, but none of these preapproval tests has been shown to predict real-world error rates. We conducted a study to assess the association between error rates in laboratory-based tests of drug name memory and perception and real-world drug name confusion error rates. Eighty participants, comprising doctors, nurses, pharmacists, technicians and lay people, completed a battery of laboratory tests assessing visual perception, auditory perception and short-term memory of look-alike and sound-alike drug name pairs (eg, hydroxyzine/hydralazine). Laboratory test error rates (and other metrics) significantly predicted real-world error rates obtained from a large, outpatient pharmacy chain, with the best-fitting model accounting for 37% of the variance in real-world error rates. Cross-validation analyses confirmed these results, showing that the laboratory tests also predicted errors from a second pharmacy chain, with 45% of the variance being explained by the laboratory test data. Across two distinct pharmacy chains, there is a strong and significant association between drug name confusion error rates observed in the real world and those observed in laboratory-based tests of memory and perception. Regulators and drug companies seeking a validated preapproval method for identifying confusing drug names ought to consider using these simple tests. By using a standard battery of memory and perception tests, it should be possible to reduce the number of confusing look-alike and sound-alike drug name pairs that reach the market, which will help protect patients from potentially harmful medication errors. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions

DOE PAGES

Pattarino, Franco; Piepel, Greg; Rinaldi, Maurizio

2018-03-03

A paper by Foglio Bonda et al. published previously in this journal (2016, Vol. 83, pp. 175–183) discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (Z ave). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). This commentary addresses some errors and other issues in the previous paper, and also discusses an improved model relating proportions of ITZ, TW20, and E5 to Z ave. The improved model contains six of the 10 terms inmore » the full-cubic mixture model, which were selected using a different cross-validation procedure than used in the previous paper. In conclusion, compared to the four-term model presented in the previous paper, the improved model fit the data better, had excellent cross-validation performance, and the predicted Z ave of a validation point was within model uncertainty of the measured value.« less

Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions.

PubMed

Pattarino, Franco; Piepel, Greg; Rinaldi, Maurizio

2018-05-30

A paper by Foglio Bonda et al. published previously in this journal (2016, Vol. 83, pp. 175-183) discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (Z ave ). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). This commentary addresses some errors and other issues in the previous paper, and also discusses an improved model relating proportions of ITZ, TW20, and E5 to Z ave . The improved model contains six of the 10 terms in the full-cubic mixture model, which were selected using a different cross-validation procedure than used in the previous paper. Compared to the four-term model presented in the previous paper, the improved model fit the data better, had excellent cross-validation performance, and the predicted Z ave of a validation point was within model uncertainty of the measured value. Copyright © 2018 Elsevier B.V. All rights reserved.

Improvement of a mixture experiment model relating the component proportions to the size of nanonized itraconazole particles in extemporary suspensions

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

Pattarino, Franco; Piepel, Greg; Rinaldi, Maurizio

A paper by Foglio Bonda et al. published previously in this journal (2016, Vol. 83, pp. 175–183) discussed the use of mixture experiment design and modeling methods to study how the proportions of three components in an extemporaneous oral suspension affected the mean diameter of drug particles (Z ave). The three components were itraconazole (ITZ), Tween 20 (TW20), and Methocel® E5 (E5). This commentary addresses some errors and other issues in the previous paper, and also discusses an improved model relating proportions of ITZ, TW20, and E5 to Z ave. The improved model contains six of the 10 terms inmore » the full-cubic mixture model, which were selected using a different cross-validation procedure than used in the previous paper. In conclusion, compared to the four-term model presented in the previous paper, the improved model fit the data better, had excellent cross-validation performance, and the predicted Z ave of a validation point was within model uncertainty of the measured value.« less

Application of Rapid Visco Analyser (RVA) viscograms and chemometrics for maize hardness characterisation.

PubMed

Guelpa, Anina; Bevilacqua, Marta; Marini, Federico; O'Kennedy, Kim; Geladi, Paul; Manley, Marena

2015-04-15

It has been established in this study that the Rapid Visco Analyser (RVA) can describe maize hardness, irrespective of the RVA profile, when used in association with appropriate multivariate data analysis techniques. Therefore, the RVA can complement or replace current and/or conventional methods as a hardness descriptor. Hardness modelling based on RVA viscograms was carried out using seven conventional hardness methods (hectoliter mass (HLM), hundred kernel mass (HKM), particle size index (PSI), percentage vitreous endosperm (%VE), protein content, percentage chop (%chop) and near infrared (NIR) spectroscopy) as references and three different RVA profiles (hard, soft and standard) as predictors. An approach using locally weighted partial least squares (LW-PLS) was followed to build the regression models. The resulted prediction errors (root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP)) for the quantification of hardness values were always lower or in the same order of the laboratory error of the reference method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

Validity and reliability of the 1/4 mile run-walk test in physically active children and adolescents.

PubMed

Ruiz, Jonatan R; Ortega, Francisco B; Castro-Piñero, Jose

2014-11-30

We investigated the criterion-related validity and the reliability of the 1/4 mile run-walk test (MRWT) in children and adolescents. A total of 86 children (n=42 girls) completed a maximal graded treadmill test using a gas analyzer and the 1/4MRW test. We investigated the test-retest reliability of the 1/4MRWT in a different group of children and adolescents (n=995, n=418 girls). The 1/4MRWT time, sex, and BMI significantly contributed to predict measured VO2peak (R2= 0.32). There was no systematic bias in the cross-validation group (P>0.1). The root mean sum of squared errors (RMSE) and the percentage error were 6.9 ml/kg/min and 17.7%, respectively, and the accurate prediction (i.e. the percentage of estimations within ±4.5 ml/kg/min of VO2peak) was 48.8%. The reliability analysis showed that the mean inter-trial difference ranged from 0.6 seconds in children aged 6-11 years to 1.3 seconds in adolescents aged 12-17 years (all P. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Predicting cognitive function from clinical measures of physical function and health status in older adults.

PubMed

Bolandzadeh, Niousha; Kording, Konrad; Salowitz, Nicole; Davis, Jennifer C; Hsu, Liang; Chan, Alison; Sharma, Devika; Blohm, Gunnar; Liu-Ambrose, Teresa

2015-01-01

Current research suggests that the neuropathology of dementia-including brain changes leading to memory impairment and cognitive decline-is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies. We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1-L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation. Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year. We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.

Chinese cross-cultural adaptation and validation of the Foot Function Index as tool to measure patients with foot and ankle functional limitations.

PubMed

González-Sánchez, Manuel; Ruiz-Muñoz, Maria; Li, Guang Zhi; Cuesta-Vargas, Antonio I

2018-08-01

To perform a cross-cultural adaptation and validation of the Foot Function Index (FFI) questionnaire to develop the Chinese version. Three hundred and six patients with foot and ankle neuromusculoskeletal diseases participated in this observational study. Construct validity, internal consistency and criterion validity were calculated for the FFI Chinese version after the translation and transcultural adaptation process. Internal consistency ranged from 0.996 to 0.998. Test-retest analysis ranged from 0.985 to 0.994; minimal detectable change 90: 2.270; standard error of measurement: 0.973. Load distribution of the three factors had an eigenvalue greater than 1. Chi-square value was 9738.14 (p < 0.001). Correlations with the three factors were significant between Factor 1 and the other two: r = -0.634 (Factor 2) and r = -0.191 (Factor 1). Foot Function Index (Taiwan Version), Short-Form 12 (Version 2) and EuroQol-5D were used for criterion validity. Factors 1 and 2 showed significant correlation with 15/16 and 14/16 scales and subscales, respectively. Foot Function Index Chinese version psychometric characteristics were good to excellent. Chinese researchers and clinicians may use this tool for foot and ankle assessment and monitoring. Implications for rehabilitation A cross-cultural adaptation of the FFI has been done from original version to Chinese. Consistent results and satisfactory psychometric properties of the Foot Function Index Chinese version have been reported. For Chinese speaking researcher and clinician FFI-Ch could be used as a tool to assess patients with foot disease.

Validation of bioelectrical impedance analysis for total body water assessment against the deuterium dilution technique in Asian children.

PubMed

Liu, A; Byrne, N M; Ma, G; Nasreddine, L; Trinidad, T P; Kijboonchoo, K; Ismail, M N; Kagawa, M; Poh, B K; Hills, A P

2011-12-01

To develop and cross-validate bioelectrical impedance analysis (BIA) prediction equations of total body water (TBW) and fat-free mass (FFM) for Asian pre-pubertal children from China, Lebanon, Malaysia, Philippines and Thailand. Height, weight, age, gender, resistance and reactance measured by BIA were collected from 948 Asian children (492 boys and 456 girls) aged 8-10 years from the five countries. The deuterium dilution technique was used as the criterion method for the estimation of TBW and FFM. The BIA equations were developed using stepwise multiple regression analysis and cross-validated using the Bland-Altman approach. The BIA prediction equation for the estimation of TBW was as follows: TBW=0.231 × height(2)/resistance+0.066 × height+0.188 × weight+0.128 × age+0.500 × sex-0.316 × Thais-4.574 (R (2)=88.0%, root mean square error (RMSE)=1.3 kg), and for the estimation of FFM was as follows: FFM=0.299 × height(2)/resistance+0.086 × height+0.245 × weight+0.260 × age+0.901 × sex-0.415 × ethnicity (Thai ethnicity =1, others = 0)-6.952 (R (2)=88.3%, RMSE=1.7 kg). No significant difference between measured and predicted values for the whole cross-validation sample was found. However, the prediction equation for estimation of TBW/FFM tended to overestimate TBW/FFM at lower levels whereas underestimate at higher levels of TBW/FFM. Accuracy of the general equation for TBW and FFM was also valid at each body mass index category. Ethnicity influences the relationship between BIA and body composition in Asian pre-pubertal children. The newly developed BIA prediction equations are valid for use in Asian pre-pubertal children.

Improving the prediction of going concern of Taiwanese listed companies using a hybrid of LASSO with data mining techniques.

PubMed

Goo, Yeung-Ja James; Chi, Der-Jang; Shen, Zong-De

2016-01-01

The purpose of this study is to establish rigorous and reliable going concern doubt (GCD) prediction models. This study first uses the least absolute shrinkage and selection operator (LASSO) to select variables and then applies data mining techniques to establish prediction models, such as neural network (NN), classification and regression tree (CART), and support vector machine (SVM). The samples of this study include 48 GCD listed companies and 124 NGCD (non-GCD) listed companies from 2002 to 2013 in the TEJ database. We conduct fivefold cross validation in order to identify the prediction accuracy. According to the empirical results, the prediction accuracy of the LASSO-NN model is 88.96 % (Type I error rate is 12.22 %; Type II error rate is 7.50 %), the prediction accuracy of the LASSO-CART model is 88.75 % (Type I error rate is 13.61 %; Type II error rate is 14.17 %), and the prediction accuracy of the LASSO-SVM model is 89.79 % (Type I error rate is 10.00 %; Type II error rate is 15.83 %).

Using Healthcare Failure Mode and Effect Analysis to reduce medication errors in the process of drug prescription, validation and dispensing in hospitalised patients.

PubMed

Vélez-Díaz-Pallarés, Manuel; Delgado-Silveira, Eva; Carretero-Accame, María Emilia; Bermejo-Vicedo, Teresa

2013-01-01

To identify actions to reduce medication errors in the process of drug prescription, validation and dispensing, and to evaluate the impact of their implementation. A Health Care Failure Mode and Effect Analysis (HFMEA) was supported by a before-and-after medication error study to measure the actual impact on error rate after the implementation of corrective actions in the process of drug prescription, validation and dispensing in wards equipped with computerised physician order entry (CPOE) and unit-dose distribution system (788 beds out of 1080) in a Spanish university hospital. The error study was carried out by two observers who reviewed medication orders on a daily basis to register prescription errors by physicians and validation errors by pharmacists. Drugs dispensed in the unit-dose trolleys were reviewed for dispensing errors. Error rates were expressed as the number of errors for each process divided by the total opportunities for error in that process times 100. A reduction in prescription errors was achieved by providing training for prescribers on CPOE, updating prescription procedures, improving clinical decision support and automating the software connection to the hospital census (relative risk reduction (RRR), 22.0%; 95% CI 12.1% to 31.8%). Validation errors were reduced after optimising time spent in educating pharmacy residents on patient safety, developing standardised validation procedures and improving aspects of the software's database (RRR, 19.4%; 95% CI 2.3% to 36.5%). Two actions reduced dispensing errors: reorganising the process of filling trolleys and drawing up a protocol for drug pharmacy checking before delivery (RRR, 38.5%; 95% CI 14.1% to 62.9%). HFMEA facilitated the identification of actions aimed at reducing medication errors in a healthcare setting, as the implementation of several of these led to a reduction in errors in the process of drug prescription, validation and dispensing.

Simple shoulder test and Oxford Shoulder Score: Persian translation and cross-cultural validation.

PubMed

Naghdi, Soofia; Nakhostin Ansari, Noureddin; Rustaie, Nilufar; Akbari, Mohammad; Ebadi, Safoora; Senobari, Maryam; Hasson, Scott

2015-12-01

To translate, culturally adapt, and validate the simple shoulder test (SST) and Oxford Shoulder Score (OSS) into Persian language using a cross-sectional and prospective cohort design. A standard forward and backward translation was followed to culturally adapt the SST and the OSS into Persian language. Psychometric properties of floor and ceiling effects, construct convergent validity, discriminant validity, internal consistency reliability, test-retest reliability, standard error of the measurement (SEM), smallest detectable change (SDC), and factor structure were determined. One hundred patients with shoulder disorders and 50 healthy subjects participated in the study. The PSST and the POSS showed no missing responses. No floor or ceiling effects were observed. Both the PSST and POSS detected differences between patients and healthy subjects supporting their discriminant validity. Construct convergent validity was confirmed by a very good correlation between the PSST and POSS (r = 0.68). There was high internal consistency for both the PSST (α = 0.73) and the POSS (α = 0.91 and 0.92). Test-retest reliability with 1-week interval was excellent (ICCagreement = 0.94 for PSST and 0.90 for POSS). Factor analyses demonstrated a three-factor solution for the PSST (49.7 % of variance) and a two-factor solution for the POSS (61.6 % of variance). The SEM/SDC was satisfactory for PSST (5.5/15.3) and POSS (6.8/18.8). The PSST and POSS are valid and reliable outcome measures for assessing functional limitations in Persian-speaking patients with shoulder disorders.

Error estimates for ice discharge calculated using the flux gate approach

NASA Astrophysics Data System (ADS)

Navarro, F. J.; Sánchez Gámez, P.

2017-12-01

Ice discharge to the ocean is usually estimated using the flux gate approach, in which ice flux is calculated through predefined flux gates close to the marine glacier front. However, published results usually lack a proper error estimate. In the flux calculation, both errors in cross-sectional area and errors in velocity are relevant. While for estimating the errors in velocity there are well-established procedures, the calculation of the error in the cross-sectional area requires the availability of ground penetrating radar (GPR) profiles transverse to the ice-flow direction. In this contribution, we use IceBridge operation GPR profiles collected in Ellesmere and Devon Islands, Nunavut, Canada, to compare the cross-sectional areas estimated using various approaches with the cross-sections estimated from GPR ice-thickness data. These error estimates are combined with those for ice-velocities calculated from Sentinel-1 SAR data, to get the error in ice discharge. Our preliminary results suggest, regarding area, that the parabolic cross-section approaches perform better than the quartic ones, which tend to overestimate the cross-sectional area for flight lines close to the central flowline. Furthermore, the results show that regional ice-discharge estimates made using parabolic approaches provide reasonable results, but estimates for individual glaciers can have large errors, up to 20% in cross-sectional area.

Quantitative Determination of Fusarium proliferatum Concentration in Intact Garlic Cloves Using Near-Infrared Spectroscopy

PubMed Central

Tamburini, Elena; Mamolini, Elisabetta; De Bastiani, Morena; Marchetti, Maria Gabriella

2016-01-01

Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional assays. Preventive detection of infection before seeding is of great interest for farmers, because it could avoid serious losses of yield during harvesting and storage. Spectra were collected on 95 garlic cloves, divided in five classes of infection (from 1-healthy to 5-very highly infected) in the range of fungal concentration 0.34–7231.15 ppb. Calibration and cross validation models were developed with partial least squares regression (PLSR) on pretreated spectra (standard normal variate, SNV, and derivatives), providing good accuracy in prediction, with a coefficient of determination (R2) of 0.829 and 0.774, respectively, a standard error of calibration (SEC) of 615.17 ppb, and a standard error of cross validation (SECV) of 717.41 ppb. The calibration model was then used to predict fungal concentration in unknown samples, peeled and unpeeled. The results showed that NIRS could be used as a reliable tool to directly detect and quantify F. proliferatum infection in peeled intact garlic cloves, but the presence of the external peel strongly affected the prediction reliability. PMID:27428978

Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm.

PubMed

Jiang, Hui; Liu, Guohai; Mei, Congli; Yu, Shuang; Xiao, Xiahong; Ding, Yuhan

2012-11-01

The feasibility of rapid determination of the process variables (i.e. pH and moisture content) in solid-state fermentation (SSF) of wheat straw using Fourier transform near infrared (FT-NIR) spectroscopy was studied. Synergy interval partial least squares (siPLS) algorithm was implemented to calibrate regression model. The number of PLS factors and the number of subintervals were optimized simultaneously by cross-validation. The performance of the prediction model was evaluated according to the root mean square error of cross-validation (RMSECV), the root mean square error of prediction (RMSEP) and the correlation coefficient (R). The measurement results of the optimal model were obtained as follows: RMSECV=0.0776, R(c)=0.9777, RMSEP=0.0963, and R(p)=0.9686 for pH model; RMSECV=1.3544% w/w, R(c)=0.8871, RMSEP=1.4946% w/w, and R(p)=0.8684 for moisture content model. Finally, compared with classic PLS and iPLS models, the siPLS model revealed its superior performance. The overall results demonstrate that FT-NIR spectroscopy combined with siPLS algorithm can be used to measure process variables in solid-state fermentation of wheat straw, and NIR spectroscopy technique has a potential to be utilized in SSF industry. Copyright © 2012 Elsevier B.V. All rights reserved.

Improving Arterial Spin Labeling by Using Deep Learning.

PubMed

Kim, Ki Hwan; Choi, Seung Hong; Park, Sung-Hong

2018-05-01

Purpose To develop a deep learning algorithm that generates arterial spin labeling (ASL) perfusion images with higher accuracy and robustness by using a smaller number of subtraction images. Materials and Methods For ASL image generation from pair-wise subtraction, we used a convolutional neural network (CNN) as a deep learning algorithm. The ground truth perfusion images were generated by averaging six or seven pairwise subtraction images acquired with (a) conventional pseudocontinuous arterial spin labeling from seven healthy subjects or (b) Hadamard-encoded pseudocontinuous ASL from 114 patients with various diseases. CNNs were trained to generate perfusion images from a smaller number (two or three) of subtraction images and evaluated by means of cross-validation. CNNs from the patient data sets were also tested on 26 separate stroke data sets. CNNs were compared with the conventional averaging method in terms of mean square error and radiologic score by using a paired t test and/or Wilcoxon signed-rank test. Results Mean square errors were approximately 40% lower than those of the conventional averaging method for the cross-validation with the healthy subjects and patients and the separate test with the patients who had experienced a stroke (P < .001). Region-of-interest analysis in stroke regions showed that cerebral blood flow maps from CNN (mean ± standard deviation, 19.7 mL per 100 g/min ± 9.7) had smaller mean square errors than those determined with the conventional averaging method (43.2 ± 29.8) (P < .001). Radiologic scoring demonstrated that CNNs suppressed noise and motion and/or segmentation artifacts better than the conventional averaging method did (P < .001). Conclusion CNNs provided superior perfusion image quality and more accurate perfusion measurement compared with those of the conventional averaging method for generation of ASL images from pair-wise subtraction images. © RSNA, 2017.

Utilization of advanced calibration techniques in stochastic rock fall analysis of quarry slopes

NASA Astrophysics Data System (ADS)

Preh, Alexander; Ahmadabadi, Morteza; Kolenprat, Bernd

2016-04-01

In order to study rock fall dynamics, a research project was conducted by the Vienna University of Technology and the Austrian Central Labour Inspectorate (Federal Ministry of Labour, Social Affairs and Consumer Protection). A part of this project included 277 full-scale drop tests at three different quarries in Austria and recording key parameters of the rock fall trajectories. The tests involved a total of 277 boulders ranging from 0.18 to 1.8 m in diameter and from 0.009 to 8.1 Mg in mass. The geology of these sites included strong rock belonging to igneous, metamorphic and volcanic types. In this paper the results of the tests are used for calibration and validation a new stochastic computer model. It is demonstrated that the error of the model (i.e. the difference between observed and simulated results) has a lognormal distribution. Selecting two parameters, advanced calibration techniques including Markov Chain Monte Carlo Technique, Maximum Likelihood and Root Mean Square Error (RMSE) are utilized to minimize the error. Validation of the model based on the cross validation technique reveals that in general, reasonable stochastic approximations of the rock fall trajectories are obtained in all dimensions, including runout, bounce heights and velocities. The approximations are compared to the measured data in terms of median, 95% and maximum values. The results of the comparisons indicate that approximate first-order predictions, using a single set of input parameters, are possible and can be used to aid practical hazard and risk assessment.

Mapping health outcome measures from a stroke registry to EQ-5D weights

PubMed Central

2013-01-01

Purpose To map health outcome related variables from a national register, not part of any validated instrument, with EQ-5D weights among stroke patients. Methods We used two cross-sectional data sets including patient characteristics, outcome variables and EQ-5D weights from the national Swedish stroke register. Three regression techniques were used on the estimation set (n = 272): ordinary least squares (OLS), Tobit, and censored least absolute deviation (CLAD). The regression coefficients for “dressing“, “toileting“, “mobility”, “mood”, “general health” and “proxy-responders” were applied to the validation set (n = 272), and the performance was analysed with mean absolute error (MAE) and mean square error (MSE). Results The number of statistically significant coefficients varied by model, but all models generated consistent coefficients in terms of sign. Mean utility was underestimated in all models (least in OLS) and with lower variation (least in OLS) compared to the observed. The maximum attainable EQ-5D weight ranged from 0.90 (OLS) to 1.00 (Tobit and CLAD). Health states with utility weights <0.5 had greater errors than those with weights ≥0.5 (P < 0.01). Conclusion This study indicates that it is possible to map non-validated health outcome measures from a stroke register into preference-based utilities to study the development of stroke care over time, and to compare with other conditions in terms of utility. PMID:23496957

Ranking and validation of spallation models for isotopic production cross sections of heavy residua

NASA Astrophysics Data System (ADS)

Sharma, Sushil K.; Kamys, Bogusław; Goldenbaum, Frank; Filges, Detlef

2017-07-01

The production cross sections of isotopically identified residual nuclei of spallation reactions induced by 136Xe projectiles at 500AMeV on hydrogen target were analyzed in a two-step model. The first stage of the reaction was described by the INCL4.6 model of an intranuclear cascade of nucleon-nucleon and pion-nucleon collisions whereas the second stage was analyzed by means of four different models; ABLA07, GEM2, GEMINI++ and SMM. The quality of the data description was judged quantitatively using two statistical deviation factors; the H-factor and the M-factor. It was found that the present analysis leads to a different ranking of models as compared to that obtained from the qualitative inspection of the data reproduction. The disagreement was caused by sensitivity of the deviation factors to large statistical errors present in some of the data. A new deviation factor, the A factor, was proposed, that is not sensitive to the statistical errors of the cross sections. The quantitative ranking of models performed using the A-factor agreed well with the qualitative analysis of the data. It was concluded that using the deviation factors weighted by statistical errors may lead to erroneous conclusions in the case when the data cover a large range of values. The quality of data reproduction by the theoretical models is discussed. Some systematic deviations of the theoretical predictions from the experimental results are observed.

Predicting the digestible energy of corn determined with growing swine from nutrient composition and cross-species measurements.

PubMed

Smith, B; Hassen, A; Hinds, M; Rice, D; Jones, D; Sauber, T; Iiams, C; Sevenich, D; Allen, R; Owens, F; McNaughton, J; Parsons, C

2015-03-01

The DE values of corn grain for pigs will differ among corn sources. More accurate prediction of DE may improve diet formulation and reduce diet cost. Corn grain sources ( = 83) were assayed with growing swine (20 kg) in DE experiments with total collection of feces, with 3-wk-old broiler chick in nitrogen-corrected apparent ME (AME) trials and with cecectomized adult roosters in nitrogen-corrected true ME (TME) studies. Additional AME data for the corn grain source set was generated based on an existing near-infrared transmittance prediction model (near-infrared transmittance-predicted AME [NIT-AME]). Corn source nutrient composition was determined by wet chemistry methods. These data were then used to 1) test the accuracy of predicting swine DE of individual corn sources based on available literature equations and nutrient composition and 2) develop models for predicting DE of sources from nutrient composition and the cross-species information gathered above (AME, NIT-AME, and TME). The overall measured DE, AME, NIT-AME, and TME values were 4,105 ± 11, 4,006 ± 10, 4,004 ± 10, and 4,086 ± 12 kcal/kg DM, respectively. Prediction models were developed using 80% of the corn grain sources; the remaining 20% was reserved for validation of the developed prediction equation. Literature equations based on nutrient composition proved imprecise for predicting corn DE; the root mean square error of prediction ranged from 105 to 331 kcal/kg, an equivalent of 2.6 to 8.8% error. Yet among the corn composition traits, 4-variable models developed in the current study provided adequate prediction of DE (model ranging from 0.76 to 0.79 and root mean square error [RMSE] of 50 kcal/kg). When prediction equations were tested using the validation set, these models had a 1 to 1.2% error of prediction. Simple linear equations from AME, NIT-AME, or TME provided an accurate prediction of DE for individual sources ( ranged from 0.65 to 0.73 and RMSE ranged from 50 to 61 kcal/kg). Percentage error of prediction based on the validation data set was greater (1.4%) for the TME model than for the NIT-AME or AME models (1 and 1.2%, respectively), indicating that swine DE values could be accurately predicted by using AME or NIT-AME. In conclusion, regression equations developed from broiler measurements or from analyzed nutrient composition proved adequate to reliably predict the DE of commercially available corn hybrids for growing pigs.

Measuring the statistical validity of summary meta-analysis and meta-regression results for use in clinical practice.

PubMed

Willis, Brian H; Riley, Richard D

2017-09-20

An important question for clinicians appraising a meta-analysis is: are the findings likely to be valid in their own practice-does the reported effect accurately represent the effect that would occur in their own clinical population? To this end we advance the concept of statistical validity-where the parameter being estimated equals the corresponding parameter for a new independent study. Using a simple ('leave-one-out') cross-validation technique, we demonstrate how we may test meta-analysis estimates for statistical validity using a new validation statistic, Vn, and derive its distribution. We compare this with the usual approach of investigating heterogeneity in meta-analyses and demonstrate the link between statistical validity and homogeneity. Using a simulation study, the properties of Vn and the Q statistic are compared for univariate random effects meta-analysis and a tailored meta-regression model, where information from the setting (included as model covariates) is used to calibrate the summary estimate to the setting of application. Their properties are found to be similar when there are 50 studies or more, but for fewer studies Vn has greater power but a higher type 1 error rate than Q. The power and type 1 error rate of Vn are also shown to depend on the within-study variance, between-study variance, study sample size, and the number of studies in the meta-analysis. Finally, we apply Vn to two published meta-analyses and conclude that it usefully augments standard methods when deciding upon the likely validity of summary meta-analysis estimates in clinical practice. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Rapid and non-invasive analysis of deoxynivalenol in durum and common wheat by Fourier-Transform Near Infrared (FT-NIR) spectroscopy.

PubMed

De Girolamo, A; Lippolis, V; Nordkvist, E; Visconti, A

2009-06-01

Fourier transform near-infrared spectroscopy (FT-NIR) was used for rapid and non-invasive analysis of deoxynivalenol (DON) in durum and common wheat. The relevance of using ground wheat samples with a homogeneous particle size distribution to minimize measurement variations and avoid DON segregation among particles of different sizes was established. Calibration models for durum wheat, common wheat and durum + common wheat samples, with particle size <500 microm, were obtained by using partial least squares (PLS) regression with an external validation technique. Values of root mean square error of prediction (RMSEP, 306-379 microg kg(-1)) were comparable and not too far from values of root mean square error of cross-validation (RMSECV, 470-555 microg kg(-1)). Coefficients of determination (r(2)) indicated an "approximate to good" level of prediction of the DON content by FT-NIR spectroscopy in the PLS calibration models (r(2) = 0.71-0.83), and a "good" discrimination between low and high DON contents in the PLS validation models (r(2) = 0.58-0.63). A "limited to good" practical utility of the models was ascertained by range error ratio (RER) values higher than 6. A qualitative model, based on 197 calibration samples, was developed to discriminate between blank and naturally contaminated wheat samples by setting a cut-off at 300 microg kg(-1) DON to separate the two classes. The model correctly classified 69% of the 65 validation samples with most misclassified samples (16 of 20) showing DON contamination levels quite close to the cut-off level. These findings suggest that FT-NIR analysis is suitable for the determination of DON in unprocessed wheat at levels far below the maximum permitted limits set by the European Commission.

Magnetically confined electron beam system for high resolution electron transmission-beam experiments

NASA Astrophysics Data System (ADS)

Lozano, A. I.; Oller, J. C.; Krupa, K.; Ferreira da Silva, F.; Limão-Vieira, P.; Blanco, F.; Muñoz, A.; Colmenares, R.; García, G.

2018-06-01

A novel experimental setup has been implemented to provide accurate electron scattering cross sections from molecules at low and intermediate impact energies (1-300 eV) by measuring the attenuation of a magnetically confined linear electron beam from a molecular target. High-resolution electron energy is achieved through confinement in a magnetic gas trap where electrons are cooled by successive collisions with N2. Additionally, we developed and present a method to correct systematic errors arising from energy and angular resolution limitations. The accuracy of the entire measurement procedure is validated by comparing the N2 total scattering cross section in the considered energy range with benchmark values available in the literature.

In-Flight Validation of Mid and Thermal Infrared Remotely Sensed Data Using the Lake Tahoe and Salton Sea Automated Validation Sites

NASA Technical Reports Server (NTRS)

Hook, Simon J.

2008-01-01

The presentation includes an introduction, Lake Tahoe site layout and measurements, Salton Sea site layout and measurements, field instrument calibration and cross-calculations, data reduction methodology and error budgets, and example results for MODIS. Summary and conclusions are: 1) Lake Tahoe CA/NV automated validation site was established in 1999 to assess radiometric accuracy of satellite and airborne mid and thermal infrared data and products. Water surface temperatures range from 4-25C.2) Salton Sea CA automated validation site was established in 2008 to broaden range of available water surface temperatures and atmospheric water vapor test cases. Water surface temperatures range from 15-35C. 3) Sites provide all information necessary for validation every 2 mins (bulk temperature, skin temperature, air temperature, wind speed, wind direction, net radiation, relative humidity). 4) Sites have been used to validate mid and thermal infrared data and products from: ASTER, AATSR, ATSR2, MODIS-Terra, MODIS-Aqua, Landsat 5, Landsat 7, MTI, TES, MASTER, MAS. 5) Approximately 10 years of data available to help validate AVHRR.

Assessing the short-term clock drift of early broadband stations with burst events of the 26 s persistent and localized microseism

NASA Astrophysics Data System (ADS)

Xie, Jun; Ni, Sidao; Chu, Risheng; Xia, Yingjie

2018-01-01

Accurate seismometer clock plays an important role in seismological studies including earthquake location and tomography. However, some seismic stations may have clock drift larger than 1 s (e.g. GSC in 1992), especially in early days of global seismic networks. The 26 s Persistent Localized (PL) microseism event in the Gulf of Guinea sometime excites strong and coherent signals, and can be used as repeating source for assessing stability of seismometer clocks. Taking station GSC, PAS and PFO in the TERRAscope network as an example, the 26 s PL signal can be easily observed in the ambient noise cross-correlation function between these stations and a remote station OBN with interstation distance about 9700 km. The travel-time variation of this 26 s signal in the ambient noise cross-correlation function is used to infer clock error. A drastic clock error is detected during June 1992 for station GSC, but not found for station PAS and PFO. This short-term clock error is confirmed by both teleseismic and local earthquake records with a magnitude of 25 s. Averaged over the three stations, the accuracy of the ambient noise cross-correlation function method with the 26 s source is about 0.3-0.5 s. Using this PL source, the clock can be validated for historical records of sparsely distributed stations, where the usual ambient noise cross-correlation function of short-period (<20 s) ambient noise might be less effective due to its attenuation over long interstation distances. However, this method suffers from cycling problem, and should be verified by teleseismic/local P waves. Further studies are also needed to investigate whether the 26 s source moves spatially and its effects on clock drift detection.

Validity and reliability of the Tibetan version of s-EMBU for measuring parenting styles.

PubMed

Yangzong, Ciren; Lerkiatbundit, Sanguan; Luobu, Ouzhu; Cui, Chaoying; Liabsuetrakul, Tippawan; Kangzhuo, Baima; Quzong, Deji; Zhandui, Luobu; Zhen, Pu; Chongsuvivatwong, Virasakdi

2017-01-01

Parenting style experienced during childhood has profound effects on children's futures. Scales developed in other countries have never been validated in the Tibetan context. The present study aimed to examine the construct validity and reliability of a Tibetan translation of the 23-item short form of the Egna Minnen Beträffande Uppfostran [One's Memories of Upbringing] (s-EMBU) and to test the correlation between the parenting styles of fathers and mothers. A cross-sectional study was conducted in a sample of 847 students aged 12-21 years from Lhasa, Tibet, during September and October 2015 with a participation rate of 97.7%. The Tibetan translation of self-completed s-EMBU was administered. Confirmatory factor analysis was employed to test the scale's validity on the first half of the sample and was then cross-validated with the second half of the sample. The final model consisted of six factors: three (rejection, emotional warmth, and overprotection) for each parent, equality constrained on factor loadings, factor correlations, and error variance between father and mother. Father-mother correlation coefficients ranged from 0.81 to 0.86, and the level of consistency ranged from 0.62 to 0.82. Thus, the slightly modified s-EMBU is suitable for use in the Tibetan culture where both the father and the mother have consistent parenting styles.

Validity and reliability of the Tibetan version of s-EMBU for measuring parenting styles

PubMed Central

Yangzong, Ciren; Lerkiatbundit, Sanguan; Luobu, Ouzhu; Cui, Chaoying; Liabsuetrakul, Tippawan; Kangzhuo, Baima; Quzong, Deji; Zhandui, Luobu; Zhen, Pu; Chongsuvivatwong, Virasakdi

2017-01-01

Parenting style experienced during childhood has profound effects on children’s futures. Scales developed in other countries have never been validated in the Tibetan context. The present study aimed to examine the construct validity and reliability of a Tibetan translation of the 23-item short form of the Egna Minnen Beträffande Uppfostran [One’s Memories of Upbringing] (s-EMBU) and to test the correlation between the parenting styles of fathers and mothers. A cross-sectional study was conducted in a sample of 847 students aged 12–21 years from Lhasa, Tibet, during September and October 2015 with a participation rate of 97.7%. The Tibetan translation of self-completed s-EMBU was administered. Confirmatory factor analysis was employed to test the scale’s validity on the first half of the sample and was then cross-validated with the second half of the sample. The final model consisted of six factors: three (rejection, emotional warmth, and overprotection) for each parent, equality constrained on factor loadings, factor correlations, and error variance between father and mother. Father–mother correlation coefficients ranged from 0.81 to 0.86, and the level of consistency ranged from 0.62 to 0.82. Thus, the slightly modified s-EMBU is suitable for use in the Tibetan culture where both the father and the mother have consistent parenting styles. PMID:28053560

A new automated method for the determination of cross-section limits in ephemeral gullies

NASA Astrophysics Data System (ADS)

Castillo, Carlos; Ángel Campo-Bescós, Miguel; Casalí, Javier; Giménez, Rafael

2017-04-01

The assessment of gully erosion relies on the estimation of the soil volume enclosed by cross sections limits. Both 3D and 2D methods require the application of a methodology for the determination of the cross-section limits what has been traditionally carried out in two ways: a) by visual inspection of the cross-section by a certain expert operator; b) by the automated identification of thresholds for different geometrical variables such as elevation, slope or plan curvature obtained from the cross-section profile. However, for these last methods, typically, the thresholds are not of general application because they depend on absolute values valid only for the local gully conditions where they were derived. In this communication we evaluate an automated method for cross-section delimitation of ephemeral gullies and compare its performance with the visual assessment provided by five scientists experienced in gully erosion assessment, defining gully width, depth and area for a total of 60 ephemeral gullies cross-sections obtained from field surveys conducted on agricultural plots in Navarra (Spain). The automated method only depends on the calculation of a simple geometrical measurement, which is the bank trapezoid area for every point of each gully bank. This rectangle trapezoid (right-angled trapezoid) is defined by the elevation of a given point, the minimum elevation and the extremes of the cross-section. The gully limit for each bank is determined by the point in the bank with the maximum trapezoid area. The comparison of the estimates among the different expert operators showed large variation coefficients (up to 70%) in a number of cross-sections, larger for cross sections width and area and smaller for cross sections depth. The automated method produced comparable results to those obtained by the experts and was the procedure with the highest average correlation with the rest of the methods for the three dimensional parameters. The errors of the automated method when compared with the average estimate of the experts were occasionally high (up to 40%), in line with the variability found among experts. The automated method showed no apparent systematic errors which approximately followed a normal distribution, although these errors were slightly biased towards overestimation for the depth and area parameters. In conclusion, this study shows that there is not a single definition of gully limits even among gully experts where a large variability was found. The bank trapezoid method was found to be an automated, easy-to-use (readily implementable in a basic excel spread-sheet or programming scripts), threshold-independent procedure to determine consistently gully limits similar to expert-derived estimates. Gully width and area calculations were more prone to errors than gully depth, which was the least sensitive parameter.

On the prompt identification of traces of explosives

NASA Astrophysics Data System (ADS)

Trobajo, M. T.; López-Cabeceira, M. M.; Carriegos, M. V.; Díez-Machío, H.

2014-12-01

Some recent results in the use of Raman spectroscopy for recognition of explosives are reviewed. Experimental study using spectra data base has been developed. In order to simulate a more real situation, both blank substances and explosives substances have been considered in this research. Statistic classification techniques have been performed. Estimations of prediction errors were obtained by cross-validation methods. These results can be applied in airport security systems in order to prevent terror acts (by the detection of explosive/flammable substances).

Adaptive local linear regression with application to printer color management.

PubMed

Gupta, Maya R; Garcia, Eric K; Chin, Erika

2008-06-01

Local learning methods, such as local linear regression and nearest neighbor classifiers, base estimates on nearby training samples, neighbors. Usually, the number of neighbors used in estimation is fixed to be a global "optimal" value, chosen by cross validation. This paper proposes adapting the number of neighbors used for estimation to the local geometry of the data, without need for cross validation. The term enclosing neighborhood is introduced to describe a set of neighbors whose convex hull contains the test point when possible. It is proven that enclosing neighborhoods yield bounded estimation variance under some assumptions. Three such enclosing neighborhood definitions are presented: natural neighbors, natural neighbors inclusive, and enclosing k-NN. The effectiveness of these neighborhood definitions with local linear regression is tested for estimating lookup tables for color management. Significant improvements in error metrics are shown, indicating that enclosing neighborhoods may be a promising adaptive neighborhood definition for other local learning tasks as well, depending on the density of training samples.

Can we predict 4-year graduation in podiatric medical school using admission data?

PubMed

Sesodia, Sanjay; Molnar, David; Shaw, Graham P

2012-01-01

This study examined the predictive ability of educational background and demographic variables, available at the admission stage, to identify applicants who will graduate in 4 years from podiatric medical school. A logistic regression model was used to identify two predictors of 4-year graduation: age at matriculation and total Medical College Admission Test score. The model was cross-validated using a second independent sample from the same population. Cross-validation gives greater confidence that the results could be more generally applied. Total Medical College Admission Test score was the strongest predictor of 4-year graduation, with age at matriculation being a statistically significant but weaker predictor. Despite the model's capacity to predict 4-year graduation better than random assignment, a sufficient amount of error in prediction remained, suggesting that important predictors are missing from the model. Furthermore, the high rate of false-positives makes it inappropriate to use age and Medical College Admission Test score as admission screens in an attempt to eliminate attrition by not accepting at-risk students.

Dutch population specific sex estimation formulae using the proximal femur.

PubMed

Colman, K L; Janssen, M C L; Stull, K E; van Rijn, R R; Oostra, R J; de Boer, H H; van der Merwe, A E

2018-05-01

Sex estimation techniques are frequently applied in forensic anthropological analyses of unidentified human skeletal remains. While morphological sex estimation methods are able to endure population differences, the classification accuracy of metric sex estimation methods are population-specific. No metric sex estimation method currently exists for the Dutch population. The purpose of this study is to create Dutch population specific sex estimation formulae by means of osteometric analyses of the proximal femur. Since the Netherlands lacks a representative contemporary skeletal reference population, 2D plane reconstructions, derived from clinical computed tomography (CT) data, were used as an alternative source for a representative reference sample. The first part of this study assesses the intra- and inter-observer error, or reliability, of twelve measurements of the proximal femur. The technical error of measurement (TEM) and relative TEM (%TEM) were calculated using 26 dry adult femora. In addition, the agreement, or accuracy, between the dry bone and CT-based measurements was determined by percent agreement. Only reliable and accurate measurements were retained for the logistic regression sex estimation formulae; a training set (n=86) was used to create the models while an independent testing set (n=28) was used to validate the models. Due to high levels of multicollinearity, only single variable models were created. Cross-validated classification accuracies ranged from 86% to 92%. The high cross-validated classification accuracies indicate that the developed formulae can contribute to the biological profile and specifically in sex estimation of unidentified human skeletal remains in the Netherlands. Furthermore, the results indicate that clinical CT data can be a valuable alternative source of data when representative skeletal collections are unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

Methodology for Computational Fluid Dynamic Validation for Medical Use: Application to Intracranial Aneurysm.

PubMed

Paliwal, Nikhil; Damiano, Robert J; Varble, Nicole A; Tutino, Vincent M; Dou, Zhongwang; Siddiqui, Adnan H; Meng, Hui

2017-12-01

Computational fluid dynamics (CFD) is a promising tool to aid in clinical diagnoses of cardiovascular diseases. However, it uses assumptions that simplify the complexities of the real cardiovascular flow. Due to high-stakes in the clinical setting, it is critical to calculate the effect of these assumptions in the CFD simulation results. However, existing CFD validation approaches do not quantify error in the simulation results due to the CFD solver's modeling assumptions. Instead, they directly compare CFD simulation results against validation data. Thus, to quantify the accuracy of a CFD solver, we developed a validation methodology that calculates the CFD model error (arising from modeling assumptions). Our methodology identifies independent error sources in CFD and validation experiments, and calculates the model error by parsing out other sources of error inherent in simulation and experiments. To demonstrate the method, we simulated the flow field of a patient-specific intracranial aneurysm (IA) in the commercial CFD software star-ccm+. Particle image velocimetry (PIV) provided validation datasets for the flow field on two orthogonal planes. The average model error in the star-ccm+ solver was 5.63 ± 5.49% along the intersecting validation line of the orthogonal planes. Furthermore, we demonstrated that our validation method is superior to existing validation approaches by applying three representative existing validation techniques to our CFD and experimental dataset, and comparing the validation results. Our validation methodology offers a streamlined workflow to extract the "true" accuracy of a CFD solver.

Application of the Safety Attitudes Questionnaire (SAQ) in Albanian hospitals: a cross-sectional study

PubMed Central

Gabrani, Adriatik; Hoxha, Adrian; Simaku, Artan; Gabrani, Jonila (Cyco)

2015-01-01

Objective To establish the reliability and validity of the translated version of the Safety Attitudes Questionnaire (SAQ) by evaluating its psychometric properties and to determine possible differences among nurses and physicians regarding safety attitudes. Design A cross-sectional study utilising the Albanian version of the SAQ and a demographic questionnaire. Setting Four regional hospitals in Albania. Participants 341 healthcare providers, including 132 nurses and 209 doctors. Main outcome measure(s) The translation, construct validity and internal validity of the SAQ. The SAQ includes six scales and 30 items. Results A total of 341 valid questionnaires were returned, for a response rate of 70%. The confirmatory factor analysis and its goodness-of-fit indices (standardised root mean square residual 0.075, root mean square error of approximation 0.044 and comparative fit index 0.97) showed good model fit. The Cronbach's α values for each of the scales of the SAQ ranged from 0.64 to 0.82. The percentage of hospital healthcare workers who had a positive attitude was 60.3% for the teamwork climate, 57.2% for the safety climate, 58.4% for job satisfaction, 37.4% for stress recognition, 59.3% for the perception of management and 49.5% for working conditions. Intercorrelations showed that the subscales had moderate-to-high correlations with one another. Nurses were more hesitant to admit and report errors; only 55% of physicians and 44% of nurses endorsed this statement (χ2=4.9, p=0.02). Moreover, nurses received lower scores on team work compared with doctors (N 45.7 vs D 52.3, p=0.01). Doctors denied the effects of stress and fatigue on their performance (N 46.7 vs D 39.5, p<0.01), neglecting the workload. Conclusions The SAQ is a useful tool for evaluating safety attitudes in Albanian hospitals. In light of the health workforce's poor recognition of stress, establishing patient safety programmes should be a priority among policymakers in Albania. PMID:25877270

Reliability and construct validity of the Spanish version of the 6-item CTS symptoms scale for outcomes assessment in carpal tunnel syndrome.

PubMed

Rosales, Roberto S; Martin-Hidalgo, Yolanda; Reboso-Morales, Luis; Atroshi, Isam

2016-03-03

The purpose of this study was to assess the reliability and construct validity of the Spanish version of the 6-item carpal tunnel syndrome (CTS) symptoms scale (CTS-6). In this cross-sectional study 40 patients diagnosed with CTS based on clinical and neurophysiologic criteria, completed the standard Spanish versions of the CTS-6 and the disabilities of the arm, shoulder and hand (QuickDASH) scales on two occasions with a 1-week interval. Internal-consistency reliability was assessed with the Cronbach alpha coefficient and test-retest reliability with the intraclass correlation coefficient, two way random effect model and absolute agreement definition (ICC2,1). Cross-sectional precision was analyzed with the Standard Error of the Measurement (SEM). Longitudinal precision for test-retest reliability coefficient was assessed with the Standard Error of the Measurement difference (SEMdiff) and the Minimal Detectable Change at 95 % confidence level (MDC95). For assessing construct validity it was hypothesized that the CTS-6 would have a strong positive correlation with the QuickDASH, analyzed with the Pearson correlation coefficient (r). The standard Spanish version of the CTS-6 presented a Cronbach alpha of 0.81 with a SEM of 0.3. Test-retest reliability showed an ICC of 0.85 with a SRMdiff of 0.36 and a MDC95 of 0.7. The correlation between CTS-6 and the QuickDASH was concordant with the a priori formulated construct hypothesis (r 0.69) CONCLUSIONS: The standard Spanish version of the 6-item CTS symptoms scale showed good internal consistency, test-retest reliability and construct validity for outcomes assessment in CTS. The CTS-6 will be useful to clinicians and researchers in Spanish speaking parts of the world. The use of standardized outcome measures across countries also will facilitate comparison of research results in carpal tunnel syndrome.

Patient-reported outcome instruments that evaluate adherence behaviours in adults with asthma: A systematic review of measurement properties.

PubMed

Gagné, Myriam; Boulet, Louis-Philippe; Pérez, Norma; Moisan, Jocelyne

2018-04-30

To systematically identify the measurement properties of patient-reported outcome instruments (PROs) that evaluate adherence to inhaled maintenance medication in adults with asthma. We conducted a systematic review of six databases. Two reviewers independently included studies on the measurement properties of PROs that evaluated adherence in asthmatic participants aged ≥18 years. Based on the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN), the reviewers (1) extracted data on internal consistency, reliability, measurement error, content validity, structural validity, hypotheses testing, cross-cultural validity, criterion validity, and responsiveness; (2) assessed the methodological quality of the included studies; (3) assessed the quality of the measurement properties (positive or negative); and (4) summarised the level of evidence (limited, moderate, or strong). We screened 6,068 records and included 15 studies (14 PROs). No studies evaluated measurement error or responsiveness. Based on methodological and measurement property quality assessments, we found limited positive evidence of: (a) internal consistency of the Adherence Questionnaire, Refined Medication Adherence Reason Scale (MAR-Scale), Medication Adherence Report Scale for Asthma (MARS-A), and Test of the Adherence to Inhalers (TAI); (b) reliability of the TAI; and (c) structural validity of the Adherence Questionnaire, MAR-Scale, MARS-A, and TAI. We also found limited negative evidence of: (d) hypotheses testing of Adherence Questionnaire; (e) reliability of the MARS-A; and (f) criterion validity of the MARS-A and TAI. Our results highlighted the need to conduct further high-quality studies that will positively evaluate the reliability, validity, and responsiveness of the available PROs. This article is protected by copyright. All rights reserved.

Knee Injury and Osteoarthritis Outcome Score (KOOS): systematic review and meta-analysis of measurement properties.

PubMed

Collins, N J; Prinsen, C A C; Christensen, R; Bartels, E M; Terwee, C B; Roos, E M

2016-08-01

To conduct a systematic review and meta-analysis to synthesize evidence regarding measurement properties of the Knee injury and Osteoarthritis Outcome Score (KOOS). A comprehensive literature search identified 37 eligible papers evaluating KOOS measurement properties in participants with knee injuries and/or osteoarthritis (OA). Methodological quality was evaluated using the COSMIN checklist. Where possible, meta-analysis of extracted data was conducted for all studies and stratified by age and knee condition; otherwise narrative synthesis was performed. KOOS has adequate internal consistency, test-retest reliability and construct validity in young and old adults with knee injuries and/or OA. The ADL subscale has better content validity for older patients and Sport/Rec for younger patients with knee injuries, while the Pain subscale is more relevant for painful knee conditions. The five-factor structure of the original KOOS is unclear. There is some evidence that the KOOS subscales demonstrate sufficient unidimensionality, but this requires confirmation. Although measurement error requires further evaluation, the minimal detectable change for KOOS subscales ranges from 14.3 to 19.6 for younger individuals, and ≥20 for older individuals. Evidence of responsiveness comes from larger effect sizes following surgical (especially total knee replacement) than non-surgical interventions. KOOS demonstrates adequate content validity, internal consistency, test-retest reliability, construct validity and responsiveness for age- and condition-relevant subscales. Structural validity, cross-cultural validity and measurement error require further evaluation, as well as construct validity of KOOS Physical function Short form. Suggested order of subscales for different knee conditions can be applied in hierarchical testing of endpoints in clinical trials. PROSPERO (CRD42011001603). Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Shape Optimization by Bayesian-Validated Computer-Simulation Surrogates

NASA Technical Reports Server (NTRS)

Patera, Anthony T.

1997-01-01

A nonparametric-validated, surrogate approach to optimization has been applied to the computational optimization of eddy-promoter heat exchangers and to the experimental optimization of a multielement airfoil. In addition to the baseline surrogate framework, a surrogate-Pareto framework has been applied to the two-criteria, eddy-promoter design problem. The Pareto analysis improves the predictability of the surrogate results, preserves generality, and provides a means to rapidly determine design trade-offs. Significant contributions have been made in the geometric description used for the eddy-promoter inclusions as well as to the surrogate framework itself. A level-set based, geometric description has been developed to define the shape of the eddy-promoter inclusions. The level-set technique allows for topology changes (from single-body,eddy-promoter configurations to two-body configurations) without requiring any additional logic. The continuity of the output responses for input variations that cross the boundary between topologies has been demonstrated. Input-output continuity is required for the straightforward application of surrogate techniques in which simplified, interpolative models are fitted through a construction set of data. The surrogate framework developed previously has been extended in a number of ways. First, the formulation for a general, two-output, two-performance metric problem is presented. Surrogates are constructed and validated for the outputs. The performance metrics can be functions of both outputs, as well as explicitly of the inputs, and serve to characterize the design preferences. By segregating the outputs and the performance metrics, an additional level of flexibility is provided to the designer. The validated outputs can be used in future design studies and the error estimates provided by the output validation step still apply, and require no additional appeals to the expensive analysis. Second, a candidate-based a posteriori error analysis capability has been developed which provides probabilistic error estimates on the true performance for a design randomly selected near the surrogate-predicted optimal design.

Cross-Cultural Adaptation, Reliability and Validity of the Danish Version of the Readiness for Return to Work Instrument.

PubMed

Stapelfeldt, Christina Malmose; Momsen, Anne-Mette Hedeager; Lund, Thomas; Grønborg, Therese Koops; Hogg-Johnson, Sheilah; Jensen, Chris; Skakon, Janne; Labriola, Merete

2018-06-06

The objective of the present study was to translate and validate the Canadian Readiness for Return To Work instrument (RRTW-CA) into a Danish version (RRTWDK) by testing its test-retest and internal consistency reliability and its structural and construct validity. Cross-cultural adaptation of the six-staged RRTW-CA instrument was performed in a standardised, systematic five-step-procedure; forward translation, panel synthesis of the translation, back translation, consolidation and revision by researchers, and finally pre-testing. This RRTW-DK beta-version was tested for its psychometric properties by intra-class correlation coefficient and standard error of measurement (n = 114), Cronbach's alpha (n = 471), confirmatory factor analyses (n = 373), and Spearman's rank correlation coefficient (n = 436) in sickness beneficiaries from a municipal employment agency and hospital wards. The original RRTW-CA stage structure could not be confirmed in the RRTWDK. The psychometric properties were thus inconclusive. The RRTW-DK cannot be recommended for use in the current version as the RRTW construct is questionable. The RRTW construct needs further exploration, preferably in a population that is homogeneous with regard to cause of sickness, disability duration and age.

Carbon dioxide emission prediction using support vector machine

NASA Astrophysics Data System (ADS)

Saleh, Chairul; Rachman Dzakiyullah, Nur; Bayu Nugroho, Jonathan

2016-02-01

In this paper, the SVM model was proposed for predict expenditure of carbon (CO2) emission. The energy consumption such as electrical energy and burning coal is input variable that affect directly increasing of CO2 emissions were conducted to built the model. Our objective is to monitor the CO2 emission based on the electrical energy and burning coal used from the production process. The data electrical energy and burning coal used were obtained from Alcohol Industry in order to training and testing the models. It divided by cross-validation technique into 90% of training data and 10% of testing data. To find the optimal parameters of SVM model was used the trial and error approach on the experiment by adjusting C parameters and Epsilon. The result shows that the SVM model has an optimal parameter on C parameters 0.1 and 0 Epsilon. To measure the error of the model by using Root Mean Square Error (RMSE) with error value as 0.004. The smallest error of the model represents more accurately prediction. As a practice, this paper was contributing for an executive manager in making the effective decision for the business operation were monitoring expenditure of CO2 emission.

Validation Relaxation: A Quality Assurance Strategy for Electronic Data Collection

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-08-18

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

Medication errors of nurses and factors in refusal to report medication errors among nurses in a teaching medical center of iran in 2012.

PubMed

Mostafaei, Davoud; Barati Marnani, Ahmad; Mosavi Esfahani, Haleh; Estebsari, Fatemeh; Shahzaidi, Shiva; Jamshidi, Ensiyeh; Aghamiri, Seyed Samad

2014-10-01

About one third of unwanted reported medication consequences are due to medication errors, resulting in one-fifth of hospital injuries. The aim of this study was determined formal and informal medication errors of nurses and the level of importance of factors in refusal to report medication errors among nurses. The cross-sectional study was done on the nursing staff of Shohada Tajrish Hospital, Tehran, Iran in 2012. The data was gathered through a questionnaire, made by the researchers. The questionnaires' face and content validity was confirmed by experts and for measuring its reliability test-retest was used. The data was analyzed by descriptive statistics. We used SPSS for related statistical analyses. The most important factors in refusal to report medication errors respectively were: lack of medication error recording and reporting system in the hospital (3.3%), non-significant error reporting to hospital authorities and lack of appropriate feedback (3.1%), and lack of a clear definition for a medication error (3%). There were both formal and informal reporting of medication errors in this study. Factors pertaining to management in hospitals as well as the fear of the consequences of reporting are two broad fields among the factors that make nurses not report their medication errors. In this regard, providing enough education to nurses, boosting the job security for nurses, management support and revising related processes and definitions are some factors that can help decreasing medication errors and increasing their report in case of occurrence.

Comparison of a Virtual Older Driver Assessment with an On-Road Driving Test.

PubMed

Eramudugolla, Ranmalee; Price, Jasmine; Chopra, Sidhant; Li, Xiaolan; Anstey, Kaarin J

2016-12-01

To design a low-cost simulator-based driving assessment for older adults and to compare its validity with that of an on-road driving assessment and other measures of older driver risk. Cross-sectional observational study. Canberra, Australia. Older adult drivers (N = 47; aged 65-88, mean age 75.2). Error rate on a simulated drive with environment and scoring procedure matched to those of an on-road test. Other measures included participant age, simulator sickness severity, neuropsychological measures, and driver screening measures. Outcome variables included occupational therapist (OT)-rated on-road errors, on-road safety rating, and safety category. Participants' error rate on the simulated drive was significantly correlated with their OT-rated driving safety (correlation coefficient (r) = -0.398, P = .006), even after adjustment for age and simulator sickness (P = .009). The simulator error rate was a significant predictor of categorization as unsafe on the road (P = .02, sensitivity 69.2%, specificity 100%), with 13 (27%) drivers assessed as unsafe. Simulator error was also associated with other older driver safety screening measures such as useful field of view (r = 0.341, P = .02), DriveSafe (r = -0.455, P < .01), and visual motion sensitivity (r = 0.368, P = .01) but was not associated with memory (delayed word recall) or global cognition (Mini-Mental State Examination). Drivers made twice as many errors on the simulated assessment as during the on-road assessment (P < .001), with significant differences in the rate and type of errors between the two mediums. A low-cost simulator-based assessment is valid as a screening instrument for identifying at-risk older drivers but not as an alternative to on-road evaluation when accurate data on competence or pattern of impairment is required for licensing decisions and training programs. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

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.

Reflectance infrared spectroscopy for in-line monitoring of nicotine during a coating process for an oral thin film.

PubMed

Hammes, Florian; Hille, Thomas; Kissel, Thomas

2014-02-01

A process analytical method using reflectance infrared spectrometry was developed for the in-line monitoring of the amount of the active pharmaceutical ingredient (API) nicotine during a coating process for an oral thin film (OTF). In-line measurements were made using a reflectance infrared (RI) sensor positioned after the last drying zone of the coating line. Real-time spectra from the coating process were used for modelling the nicotine content. Partial least squares (PLS1) calibration models with different data pre-treatments were generated. The calibration model with the most comparable standard error of calibration (SEC) and the standard error of cross validation (SECV) was selected for an external validation run on the production coating line with an independent laminate. Good correlations could be obtained between values estimated from the reflectance infrared data and the reference HPLC test method, respectively. With in-line measurements it was possible to allow real-time adjustments during the production process to keep product specifications within predefined limits hence avoiding loss of material and batch. Copyright © 2013 Elsevier B.V. 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.

A validation study of the psychometric properties of the Groningen Reflection Ability Scale.

PubMed

Andersen, Nina Bjerre; O'Neill, Lotte; Gormsen, Lise Kirstine; Hvidberg, Line; Morcke, Anne Mette

2014-10-10

Reflection, the ability to examine critically one's own learning and functioning, is considered important for 'the good doctor'. The Groningen Reflection Ability Scale (GRAS) is an instrument measuring student reflection, which has not yet been validated beyond the original Dutch study. The aim of this study was to adapt GRAS for use in a Danish setting and to investigate the psychometric properties of GRAS-DK. We performed a cross-cultural adaptation of GRAS from Dutch to Danish. Next, we collected primary data online, performed a retest, analysed data descriptively, estimated measurement error, performed an exploratory and a confirmatory factor analysis to test the proposed three-factor structure. 361 (69%) of 523 invited students completed GRAS-DK. Their mean score was 88 (SD = 11.42; scale maximum 115). Scores were approximately normally distributed. Measurement error and test-retest score differences were acceptable, apart from a few extreme outliers. However, the confirmatory factor analysis did not replicate the original three-factor model and neither could a one-dimensional structure be confirmed. GRAS is already in use, however we advise that use of GRAS-DK for effect measurements and group comparison awaits further review and validation studies. Our negative finding might be explained by a weak conceptualisation of personal reflection.

The R package "sperrorest" : Parallelized spatial error estimation and variable importance assessment for geospatial machine learning

NASA Astrophysics Data System (ADS)

Schratz, Patrick; Herrmann, Tobias; Brenning, Alexander

2017-04-01

Computational and statistical prediction methods such as the support vector machine have gained popularity in remote-sensing applications in recent years and are often compared to more traditional approaches like maximum-likelihood classification. However, the accuracy assessment of such predictive models in a spatial context needs to account for the presence of spatial autocorrelation in geospatial data by using spatial cross-validation and bootstrap strategies instead of their now more widely used non-spatial equivalent. The R package sperrorest by A. Brenning [IEEE International Geoscience and Remote Sensing Symposium, 1, 374 (2012)] provides a generic interface for performing (spatial) cross-validation of any statistical or machine-learning technique available in R. Since spatial statistical models as well as flexible machine-learning algorithms can be computationally expensive, parallel computing strategies are required to perform cross-validation efficiently. The most recent major release of sperrorest therefore comes with two new features (aside from improved documentation): The first one is the parallelized version of sperrorest(), parsperrorest(). This function features two parallel modes to greatly speed up cross-validation runs. Both parallel modes are platform independent and provide progress information. par.mode = 1 relies on the pbapply package and calls interactively (depending on the platform) parallel::mclapply() or parallel::parApply() in the background. While forking is used on Unix-Systems, Windows systems use a cluster approach for parallel execution. par.mode = 2 uses the foreach package to perform parallelization. This method uses a different way of cluster parallelization than the parallel package does. In summary, the robustness of parsperrorest() is increased with the implementation of two independent parallel modes. A new way of partitioning the data in sperrorest is provided by partition.factor.cv(). This function gives the user the possibility to perform cross-validation at the level of some grouping structure. As an example, in remote sensing of agricultural land uses, pixels from the same field contain nearly identical information and will thus be jointly placed in either the test set or the training set. Other spatial sampling resampling strategies are already available and can be extended by the user.

Measuring cross-cultural patient safety: identifying barriers and developing performance indicators.

PubMed

Walker, Roger; St Pierre-Hansen, Natalie; Cromarty, Helen; Kelly, Len; Minty, Bryanne

2010-01-01

Medical errors and cultural errors threaten patient safety. We know that access to care, quality of care and clinical safety are all impacted by cultural issues. Numerous approaches to describing cultural barriers to patient safety have been developed, but these taxonomies do not provide a useful set of tools for defining the nature of the problem and consequently do not establish a sound base for problem solving. The Sioux Lookout Meno Ya Win Health Centre has implemented a cross-cultural patient safety (CCPS) model (Walker 2009). We developed an analytical CCPS framework within the organization, and in this article, we detail the validation process for our framework by way of a literature review and surveys of local and international healthcare professionals. We reinforce the position that while cultural competency may be defined by the service provider, cultural safety is defined by the client. In addition, we document the difficulties surrounding the measurement of cultural competence in terms of patient outcomes, which is an underdeveloped dimension of the field of patient safety. We continue to explore the correlation between organizational performance and measurable patient outcomes.

Preparations for Global Precipitation Measurement(GPM)Ground Validation

NASA Technical Reports Server (NTRS)

Bidwell, S. W.; Bibyk, I. K.; Duming, J. F.; Everett, D. F.; Smith, E. A.; Wolff, D. B.

2004-01-01

The Global Precipitation Measurement (GPM) program is an international partnership led by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM will improve climate, weather, and hydro-meterorological forecasts through more frequent and more accurate measurement of precipitation across the globe. This paper describes the concept and the preparations for Ground Validation within the GPM program. Ground Validation (GV) plays a critical role in the program by investigating and quantitatively assessing the errors within the satellite retrievals. These quantitative estimates of retrieval errors will assist the scientific community by bounding the errors within their research products. The two fundamental requirements of the GPM Ground Validation program are: (1) error characterization of the precipitation retrievals and (2) continual improvement of the satellite retrieval algorithms. These two driving requirements determine the measurements, instrumentation, and location for ground observations. This paper describes GV plans for estimating the systematic and random components of retrieval error and for characterizing the spatial and temporal structure of the error. This paper describes the GPM program for algorithm improvement in which error models are developed and experimentally explored to uncover the physical causes of errors within the retrievals. GPM will ensure that information gained through Ground Validation is applied to future improvements in the spaceborne retrieval algorithms. This paper discusses the potential locations for validation measurement and research, the anticipated contributions of GPM's international partners, and the interaction of Ground Validation with other GPM program elements.

Regression models to predict hip joint centers in pathological hip population.

PubMed

Mantovani, Giulia; Ng, K C Geoffrey; Lamontagne, Mario

2016-02-01

The purpose was to investigate the validity of Harrington's and Davis's hip joint center (HJC) regression equations on a population affected by a hip deformity, (i.e., femoroacetabular impingement). Sixty-seven participants (21 healthy controls, 46 with a cam-type deformity) underwent pelvic CT imaging. Relevant bony landmarks and geometric HJCs were digitized from the images, and skin thickness was measured for the anterior and posterior superior iliac spines. Non-parametric statistical and Bland-Altman tests analyzed differences between the predicted HJC (from regression equations) and the actual HJC (from CT images). The error from Davis's model (25.0 ± 6.7 mm) was larger than Harrington's (12.3 ± 5.9 mm, p<0.001). There were no differences between groups, thus, studies on femoroacetabular impingement can implement conventional regression models. Measured skin thickness was 9.7 ± 7.0mm and 19.6 ± 10.9 mm for the anterior and posterior bony landmarks, respectively, and correlated with body mass index. Skin thickness estimates can be considered to reduce the systematic error introduced by surface markers. New adult-specific regression equations were developed from the CT dataset, with the hypothesis that they could provide better estimates when tuned to a larger adult-specific dataset. The linear models were validated on external datasets and using leave-one-out cross-validation techniques; Prediction errors were comparable to those of Harrington's model, despite the adult-specific population and the larger sample size, thus, prediction accuracy obtained from these parameters could not be improved. Copyright © 2015 Elsevier B.V. All rights reserved.

Small Scale Mass Flow Plug Calibration

NASA Technical Reports Server (NTRS)

Sasson, Jonathan

2015-01-01

A simple control volume model has been developed to calculate the discharge coefficient through a mass flow plug (MFP) and validated with a calibration experiment. The maximum error of the model in the operating region of the MFP is 0.54%. The model uses the MFP geometry and operating pressure and temperature to couple continuity, momentum, energy, an equation of state, and wall shear. Effects of boundary layer growth and the reduction in cross-sectional flow area are calculated using an in- integral method. A CFD calibration is shown to be of lower accuracy with a maximum error of 1.35%, and slower by a factor of 100. Effects of total pressure distortion are taken into account in the experiment. Distortion creates a loss in flow rate and can be characterized by two different distortion descriptors.

Toward On-line Parameter Estimation of Concentric Tube Robots Using a Mechanics-based Kinematic Model

PubMed Central

Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo

2017-01-01

Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554

Estimating Dense Cardiac 3D Motion Using Sparse 2D Tagged MRI Cross-sections*

PubMed Central

Ardekani, Siamak; Gunter, Geoffrey; Jain, Saurabh; Weiss, Robert G.; Miller, Michael I.; Younes, Laurent

2015-01-01

In this work, we describe a new method, an extension of the Large Deformation Diffeomorphic Metric Mapping to estimate three-dimensional deformation of tagged Magnetic Resonance Imaging Data. Our approach relies on performing non-rigid registration of tag planes that were constructed from set of initial reference short axis tag grids to a set of deformed tag curves. We validated our algorithm using in-vivo tagged images of normal mice. The mapping allows us to compute root mean square distance error between simulated tag curves in a set of long axis image planes and the acquired tag curves in the same plane. Average RMS error was 0.31±0.36(SD) mm, which is approximately 2.5 voxels, indicating good matching accuracy. PMID:25571140

Uncertainties in Coastal Ocean Color Products: Impacts of Spatial Sampling

NASA Technical Reports Server (NTRS)

Pahlevan, Nima; Sarkar, Sudipta; Franz, Bryan A.

2016-01-01

With increasing demands for ocean color (OC) products with improved accuracy and well characterized, per-retrieval uncertainty budgets, it is vital to decompose overall estimated errors into their primary components. Amongst various contributing elements (e.g., instrument calibration, atmospheric correction, inversion algorithms) in the uncertainty of an OC observation, less attention has been paid to uncertainties associated with spatial sampling. In this paper, we simulate MODIS (aboard both Aqua and Terra) and VIIRS OC products using 30 m resolution OC products derived from the Operational Land Imager (OLI) aboard Landsat-8, to examine impacts of spatial sampling on both cross-sensor product intercomparisons and in-situ validations of R(sub rs) products in coastal waters. Various OLI OC products representing different productivity levels and in-water spatial features were scanned for one full orbital-repeat cycle of each ocean color satellite. While some view-angle dependent differences in simulated Aqua-MODIS and VIIRS were observed, the average uncertainties (absolute) in product intercomparisons (due to differences in spatial sampling) at regional scales are found to be 1.8%, 1.9%, 2.4%, 4.3%, 2.7%, 1.8%, and 4% for the R(sub rs)(443), R(sub rs)(482), R(sub rs)(561), R(sub rs)(655), Chla, K(sub d)(482), and b(sub bp)(655) products, respectively. It is also found that, depending on in-water spatial variability and the sensor's footprint size, the errors for an in-situ validation station in coastal areas can reach as high as +/- 18%. We conclude that a) expected biases induced by the spatial sampling in product intercomparisons are mitigated when products are averaged over at least 7 km × 7 km areas, b) VIIRS observations, with improved consistency in cross-track spatial sampling, yield more precise calibration/validation statistics than that of MODIS, and c) use of a single pixel centered on in-situ coastal stations provides an optimal sampling size for validation efforts. These findings will have implications for enhancing our understanding of uncertainties in ocean color retrievals and for planning of future ocean color missions and the associated calibration/validation exercises.

The intention to disclose medical errors among doctors in a referral hospital in North Malaysia.

PubMed

Hs, Arvinder-Singh; Rashid, Abdul

2017-01-23

In this study, medical errors are defined as unintentional patient harm caused by a doctor's mistake. This topic, due to limited research, is poorly understood in Malaysia. The objective of this study was to determine the proportion of doctors intending to disclose medical errors, and their attitudes/perception pertaining to medical errors. This cross-sectional study was conducted at a tertiary public hospital from July- December 2015 among 276 randomly selected doctors. Data was collected using a standardized and validated self-administered questionnaire intending to measure disclosure and attitudes/perceptions. The scale had four vignettes in total two medical and two surgical. Each vignette consisted of five questions and each question measured the disclosure. Disclosure was categorised as "No Disclosure", "Partial Disclosure" or "Full Disclosure". Data was keyed in and analysed using STATA v 13.0. Only 10.1% (n = 28) intended to disclose medical errors. Most respondents felt that they possessed an attitude/perception of adequately disclosing errors to patients. There was a statistically significant difference (p < 0.001) when comparing the intention of disclosure with perceived disclosures. Most respondents were in common agreement that disclosing an error would make them less likely to get sued, that minor errors should be reported and that they experienced relief from disclosing errors. Most doctors in this study would not disclose medical errors although they perceived that the errors were serious and felt responsible for it. Poor disclosure could be due the fear of litigations and improper mechanisms/procedures available for disclosure.

A method for sensitivity analysis to assess the effects of measurement error in multiple exposure variables using external validation data.

PubMed

Agogo, George O; van der Voet, Hilko; van 't Veer, Pieter; Ferrari, Pietro; Muller, David C; Sánchez-Cantalejo, Emilio; Bamia, Christina; Braaten, Tonje; Knüppel, Sven; Johansson, Ingegerd; van Eeuwijk, Fred A; Boshuizen, Hendriek C

2016-10-13

Measurement error in self-reported dietary intakes is known to bias the association between dietary intake and a health outcome of interest such as risk of a disease. The association can be distorted further by mismeasured confounders, leading to invalid results and conclusions. It is, however, difficult to adjust for the bias in the association when there is no internal validation data. We proposed a method to adjust for the bias in the diet-disease association (hereafter, association), due to measurement error in dietary intake and a mismeasured confounder, when there is no internal validation data. The method combines prior information on the validity of the self-report instrument with the observed data to adjust for the bias in the association. We compared the proposed method with the method that ignores the confounder effect, and with the method that ignores measurement errors completely. We assessed the sensitivity of the estimates to various magnitudes of measurement error, error correlations and uncertainty in the literature-reported validation data. We applied the methods to fruits and vegetables (FV) intakes, cigarette smoking (confounder) and all-cause mortality data from the European Prospective Investigation into Cancer and Nutrition study. Using the proposed method resulted in about four times increase in the strength of association between FV intake and mortality. For weakly correlated errors, measurement error in the confounder minimally affected the hazard ratio estimate for FV intake. The effect was more pronounced for strong error correlations. The proposed method permits sensitivity analysis on measurement error structures and accounts for uncertainties in the reported validity coefficients. The method is useful in assessing the direction and quantifying the magnitude of bias in the association due to measurement errors in the confounders.

On the accuracy of aerosol photoacoustic spectrometer calibrations using absorption by ozone

NASA Astrophysics Data System (ADS)

Davies, Nicholas W.; Cotterell, Michael I.; Fox, Cathryn; Szpek, Kate; Haywood, Jim M.; Langridge, Justin M.

2018-04-01

In recent years, photoacoustic spectroscopy has emerged as an invaluable tool for the accurate measurement of light absorption by atmospheric aerosol. Photoacoustic instruments require calibration, which can be achieved by measuring the photoacoustic signal generated by known quantities of gaseous ozone. Recent work has questioned the validity of this approach at short visible wavelengths (404 nm), indicating systematic calibration errors of the order of a factor of 2. We revisit this result and test the validity of the ozone calibration method using a suite of multipass photoacoustic cells operating at wavelengths 405, 514 and 658 nm. Using aerosolised nigrosin with mobility-selected diameters in the range 250-425 nm, we demonstrate excellent agreement between measured and modelled ensemble absorption cross sections at all wavelengths, thus demonstrating the validity of the ozone-based calibration method for aerosol photoacoustic spectroscopy at visible wavelengths.

Validation of simultaneous reverse optimization reconstruction algorithm in a practical circular subaperture stitching interferometer

NASA Astrophysics Data System (ADS)

Zhang, Lei; Li, Dong; Liu, Yu; Liu, Jingxiao; Li, Jingsong; Yu, Benli

2017-11-01

We demonstrate the validity of the simultaneous reverse optimization reconstruction (SROR) algorithm in circular subaperture stitching interferometry (CSSI), which is previously proposed for non-null aspheric annular subaperture stitching interferometry (ASSI). The merits of the modified SROR algorithm in CSSI, such as auto retrace error correction, no need of overlap and even permission of missed coverage, are analyzed in detail in simulations and experiments. Meanwhile, a practical CSSI system is proposed for this demonstration. An optical wedge is employed to deflect the incident beam for subaperture scanning by its rotation and shift instead of the six-axis motion-control system. Also the reference path can provide variable Zernike defocus for each subaperture test, which would decrease the fringe density. Experiments validating the SROR algorithm in this CSSI is implemented with cross validation by testing of paraboloidal mirror, flat mirror and astigmatism mirror. It is an indispensable supplement in SROR application in general subaperture stitching interferometry.

A systematic review of the measurement properties of the Body Image Scale (BIS) in cancer patients.

PubMed

Melissant, Heleen C; Neijenhuijs, Koen I; Jansen, Femke; Aaronson, Neil K; Groenvold, Mogens; Holzner, Bernhard; Terwee, Caroline B; van Uden-Kraan, Cornelia F; Cuijpers, Pim; Verdonck-de Leeuw, Irma M

2018-06-01

Body image is acknowledged as an important aspect of health-related quality of life in cancer patients. The Body Image Scale (BIS) is a patient-reported outcome measure (PROM) to evaluate body image in cancer patients. The aim of this study was to systematically review measurement properties of the BIS among cancer patients. A search in Embase, MEDLINE, PsycINFO, and Web of Science was performed to identify studies that investigated measurement properties of the BIS (Prospero ID 42017057237). Study quality was assessed (excellent, good, fair, poor), and data were extracted and analyzed according to the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology on structural validity, internal consistency, reliability, measurement error, hypothesis testing for construct validity, and responsiveness. Evidence was categorized into sufficient, insufficient, inconsistent, or indeterminate. Nine studies were included. Evidence was sufficient for structural validity (one factor solution), internal consistency (α = 0.86-0.96), and reliability (r > 0.70); indeterminate for measurement error (information on minimal important change lacked) and responsiveness (increasing body image disturbance in only one study); and inconsistent for hypothesis testing (conflicting results). Quality of the evidence was moderate to low. No studies reported on cross-cultural validity. The BIS is a PROM with good structural validity, internal consistency, and test-retest reliability, but good quality studies on the other measurement properties are needed to optimize evidence. It is recommended to include a wider variety of cancer diagnoses and treatment modalities in these future studies.

Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA).

PubMed

Thatcher, R W; North, D; Biver, C

2005-01-01

This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% false positives at the P < .005 level. EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) from 43 normal adult subjects were imported into the Key Institute's LORETA program. We then used the Key Institute's cross-spectrum and the Key Institute's LORETA output files (*.lor) as the 2,394 gray matter pixel representation of 3-dimensional currents at different frequencies. The mean and standard deviation *.lor files were computed for each of the 2,394 gray matter pixels for each of the 43 subjects. Tests of Gaussianity and different transforms were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of parametric vs. non-parametric statistics were compared using a "leave-one-out" cross validation method in which individual normal subjects were withdrawn and then statistically classified as being either normal or abnormal based on the remaining subjects. Log10 transforms approximated Gaussian distribution in the range of 95% to 99% accuracy. Parametric Z score tests at P < .05 cross-validation demonstrated an average misclassification rate of approximately 4.25%, and range over the 2,394 gray matter pixels was 27.66% to 0.11%. At P < .01 parametric Z score cross-validation false positives were 0.26% and ranged from 6.65% to 0% false positives. The non-parametric Key Institute's t-max statistic at P < .05 had an average misclassification error rate of 7.64% and ranged from 43.37% to 0.04% false positives. The nonparametric t-max at P < .01 had an average misclassification rate of 6.67% and ranged from 41.34% to 0% false positives of the 2,394 gray matter pixels for any cross-validated normal subject. In conclusion, adequate approximation to Gaussian distribution and high cross-validation can be achieved by the Key Institute's LORETA programs by using a log10 transform and parametric statistics, and parametric normative comparisons had lower false positive rates than the non-parametric tests.

The development and validation of the clinicians' awareness towards cognitive errors (CATChES) in clinical decision making questionnaire tool.

PubMed

Chew, Keng Sheng; Kueh, Yee Cheng; Abdul Aziz, Adlihafizi

2017-03-21

Despite their importance on diagnostic accuracy, there is a paucity of literature on questionnaire tools to assess clinicians' awareness toward cognitive errors. A validation study was conducted to develop a questionnaire tool to evaluate the Clinician's Awareness Towards Cognitive Errors (CATChES) in clinical decision making. This questionnaire is divided into two parts. Part A is to evaluate the clinicians' awareness towards cognitive errors in clinical decision making while Part B is to evaluate their perception towards specific cognitive errors. Content validation for both parts was first determined followed by construct validation for Part A. Construct validation for Part B was not determined as the responses were set in a dichotomous format. For content validation, all items in both Part A and Part B were rated as "excellent" in terms of their relevance in clinical settings. For construct validation using exploratory factor analysis (EFA) for Part A, a two-factor model with total variance extraction of 60% was determined. Two items were deleted. Then, the EFA was repeated showing that all factor loadings are above the cut-off value of >0.5. The Cronbach's alpha for both factors are above 0.6. The CATChES questionnaire tool is a valid questionnaire tool aimed to evaluate the awareness among clinicians toward cognitive errors in clinical decision making.

Brazilian cross-cultural adaptation and validation of the List of Threatening Events Questionnaire (LTE-Q).

PubMed

Abreu, Patrícia B de; Cogo-Moreira, Hugo; Pose, Regina A; Laranjeira, Ronaldo; Caetano, Raul; Gaya, Carolina M; Madruga, Clarice S

2017-01-01

To perform a construct validation of the List of Threatening Events Questionnaire (LTE-Q), as well as convergence validation by identifying its association with drug use in a sample of the Brazilian population. This is a secondary analysis of the Second Brazilian National Alcohol and Drugs Survey (II BNADS), which used a cross-cultural adaptation of the LTE-Q in a probabilistic sample of 4,607 participants aged 14 years and older. Latent class analysis was used to validate the latent trait adversity (which considered the number of events from the list of 12 item in the LTE experienced by the respondent in the previous year) and logistic regression was performed to find its association with binge drinking and cocaine use. The confirmatory factor analysis returned a chi-square of 108.341, weighted root mean square residual (WRMR) of 1.240, confirmatory fit indices (CFI) of 0.970, Tucker-Lewis index (TLI) of 0.962, and root mean square error approximation (RMSEA) score of 1.000. LTE-Q convergence validation showed that the adversity latent trait increased the chances of binge drinking by 1.31 time and doubled the chances of previous year cocaine use (adjusted by sociodemographic variables). The use of the LTE-Q in Brazil should be encouraged in different research fields, including large epidemiological surveys, as it is also appropriate when time and budget are limited. The LTE-Q can be a useful tool in the development of targeted and more efficient prevention strategies.

Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

USGS Publications Warehouse

Then, Amy Y.; Hoenig, John M; Hall, Norman G.; Hewitt, David A.

2015-01-01

Many methods have been developed in the last 70 years to predict the natural mortality rate, M, of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M, (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age (tmax), growth parameters, and water temperature by seeing how well they reproduce >200 independent, direct estimates of M. We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a tmax-based estimator performs the best among all estimators evaluated. The tmax-based estimators in turn perform better than the Alverson–Carney method based on tmax and the von Bertalanffy K coefficient, Pauly’s method based on growth parameters and water temperature and methods based just on K. It is possible to combine two independent methods by computing a weighted mean but the improvement over the tmax-based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a tmax-based estimator (M=4.899tmax−0.916">M=4.899t−0.916maxM=4.899tmax−0.916, prediction error = 0.32) when possible and a growth-based method (M=4.118K0.73L∞−0.33">M=4.118K0.73L−0.33∞M=4.118K0.73L∞−0.33 , prediction error = 0.6, length in cm) otherwise.

Estimating variance components and breeding values for number of oocytes and number of embryos in dairy cattle using a single-step genomic evaluation.

PubMed

Cornelissen, M A M C; Mullaart, E; Van der Linde, C; Mulder, H A

2017-06-01

Reproductive technologies such as multiple ovulation and embryo transfer (MOET) and ovum pick-up (OPU) accelerate genetic improvement in dairy breeding schemes. To enhance the efficiency of embryo production, breeding values for traits such as number of oocytes (NoO) and number of MOET embryos (NoM) can help in selection of donors with high MOET or OPU efficiency. The aim of this study was therefore to estimate variance components and (genomic) breeding values for NoO and NoM based on Dutch Holstein data. Furthermore, a 10-fold cross-validation was carried out to assess the accuracy of pedigree and genomic breeding values for NoO and NoM. For NoO, 40,734 OPU sessions between 1993 and 2015 were analyzed. These OPU sessions originated from 2,543 donors, from which 1,144 were genotyped. For NoM, 35,695 sessions between 1994 and 2015 were analyzed. These MOET sessions originated from 13,868 donors, from which 3,716 were genotyped. Analyses were done using only pedigree information and using a single-step genomic BLUP (ssGBLUP) approach combining genomic information and pedigree information. Heritabilities were very similar based on pedigree information or based on ssGBLUP [i.e., 0.32 (standard error = 0.03) for NoO and 0.21 (standard error = 0.01) for NoM with pedigree, 0.31 (standard error = 0.03) for NoO, and 0.22 (standard error = 0.01) for NoM with ssGBLUP]. For animals without their own information as mimicked in the cross-validation, the accuracy of pedigree-based breeding values was 0.46 for NoO and NoM. The accuracies of genomic breeding values from ssGBLUP were 0.54 for NoO and 0.52 for NoM. These results show that including genomic information increases the accuracies. These moderate accuracies in combination with a large genetic variance show good opportunities for selection of potential bull dams. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography-based milk fatty acid profiles.

PubMed

van Gastelen, S; Mollenhorst, H; Antunes-Fernandes, E C; Hettinga, K A; van Burgsteden, G G; Dijkstra, J; Rademaker, J L W

2018-06-01

The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH 4 emissions of dairy cows with that of gas chromatography (GC)-based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH 4 production was 366 ± 53.9 g/d, CH 4 yield was 22.5 ± 2.10 g/kg of DMI, and CH 4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA-based and FTIR-based CH 4 prediction models were developed, and subsequently, the final CH 4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA-based prediction models described a greater part of the observed variation in CH 4 emission than did the FTIR-based models. The cross validation results indicate that all CH 4 prediction models (both GC-determined MFA-based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH 4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH 4 emission of dairy cows in practice. Additional CH 4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH 4 prediction. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Vocal Tract Discomfort Scale: Validity and Reliability of the Persian Version in the Assessment of Patients With Muscle Tension Dysphonia.

PubMed

Torabi, Hadi; Khoddami, Seyyedeh Maryam; Ansari, Noureddin Nakhostin; Dabirmoghaddam, Payman

2016-11-01

To cross-culturally adapt of Persian Vocal Tract Discomfort (VTDp) scale and evaluate its validity and reliability in the assessment of patients with muscle tension dysphonia (MTD). A cross-sectional and prospective cohort design was used to psychometrically test the VTDp. The VTD scale was cross-culturally adapted into Persian language following standard forward-backward translations. The VTDp scale was administrated to 100 patients with MTD (54 men and 46 women; mean age: 38.05 ± 10.02 years) and 50 healthy volunteers (26 men and 24 women; mean age: 36.50 ± 12.27 years). Forty-five patients with MTD completed the VTDp 7 days later for test-retest reliability. Patients also completed the Persian Voice Handicap Index (VHIp) to assess construct validity. The results of discriminative validity demonstrated that the VTDp was able to discriminate between patients with MTD and healthy participants. The internal consistency was confirmed with Cronbach α .77 and 0.73 for VTDp frequency and severity subscales, respectively. The test-retest reliability was excellent with an intraclass correlation coefficient (ICC agreement ) of 0.93 for the frequency subscale and 0.91 for the severity subscale. Construct validity of the VTDp was shown with significant correlations between the VTDp frequency and severity subscales and the VHIp total scores (0.36 and 0.37, respectively). The standard error of measurement and smallest detectable change values for VTDp frequency (2.11 and 5.85, respectively) and severity (2.25 and 6.23, respectively) were acceptable. The Bland-Altman analysis for assessing the agreement between test and retest measurements showed no systematic bias. The VTDp is a valid and reliable self-administered scale to measure patient's vocal tract sensations in Persian-speaking population. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

[Psychometric properties of the third version of family adaptability and cohesion evaluation scales (FACES-III): a study of peruvian adolescents].

PubMed

Bazo-Alvarez, Juan Carlos; Bazo-Alvarez, Oscar Alfredo; Aguila, Jeins; Peralta, Frank; Mormontoy, Wilfredo; Bennett, Ian M

2016-01-01

Our aim was to evaluate the psychometric properties of the FACES-III among Peruvian high school students. This is a psychometric cross-sectional study. A probabilistic sampling was applied, defined by three stages: stratum one (school), stratum two (grade) and cluster (section). The participants were 910 adolescent students of both sexes, between 11 and 18 years of age. The instrument was also the object of study: the Olson's FACES-III. The analysis included a review of the structure / construct validity of the measure by factor analysis and assessment of internal consistency (reliability). The real-cohesion scale had moderately high reliability (Ω=.85) while the real-flexibility scale had moderate reliability (Ω=.74). The reliability found for the ideal-cohesion was moderately high (Ω=.89) like for the scale of ideal-flexibility (Ω=.86). Construct validity was confirmed by the goodness of fit of a two factor model (cohesion and flexibility) with 10 items each [Adjusted goodness of fit index (AGFI) = 0.96; Expected Cross Validation Index (ECVI) = 0.87; Normed fit index (NFI) = 0.93; Goodness of fit index (GFI) = 0.97; Root mean square error of approximation (RMSEA) = 0.06]. FACES-III has sufficient reliability and validity to be used in Peruvian adolescents for the purpose of group or individual assessment.

Concurrent validity of single-item measures of emotional exhaustion and depersonalization in burnout assessment.

PubMed

West, Colin P; Dyrbye, Liselotte N; Satele, Daniel V; Sloan, Jeff A; Shanafelt, Tait D

2012-11-01

Burnout is a common problem among physicians and physicians-in-training. The Maslach Burnout Inventory (MBI) is the gold standard for burnout assessment, but the length of this well-validated 22-item instrument can limit its feasibility for survey research. To evaluate the concurrent validity of two questions relative to the full MBI for measuring the association of burnout with published outcomes. DESIGN, PARTICIPANTS, AND MAIN MEASURES: The single questions "I feel burned out from my work" and "I have become more callous toward people since I took this job," representing the emotional exhaustion and depersonalization domains of burnout, respectively, were evaluated in published studies of medical students, internal medicine residents, and practicing surgeons. We compared predictive models for the association of each question, versus the full MBI, using longitudinal data on burnout and suicidality from 2006 and 2007 for 858 medical students at five United States medical schools, cross-sectional data on burnout and serious thoughts of dropping out of medical school from 2007 for 2222 medical students at seven United States medical schools, and cross-sectional data on burnout and unprofessional attitudes and behaviors from 2009 for 2566 medical students at seven United States medical schools. We also assessed results for longitudinal data on burnout and perceived major medical errors from 2003 to 2009 for 321 Mayo Clinic Rochester internal medicine residents and cross-sectional data on burnout and both perceived major medical errors and suicidality from 2008 for 7,905 respondents to a national survey of members of the American College of Surgeons. Point estimates of effect for models based on the single-item measures were uniformly consistent with those reported for models based on the full MBI. The single-item measures of emotional exhaustion and depersonalization exhibited strong associations with each published outcome (all p ≤ 0.008). No conclusion regarding the relationship between burnout and any outcome variable was altered by the use of the single-item measures rather than the full MBI. Relative to the full MBI, single-item measures of emotional exhaustion and depersonalization exhibit strong and consistent associations with key outcomes in medical students, internal medicine residents, and practicing surgeons.

Application of Fourier transform infrared spectroscopy for monitoring short-chain free fatty acids in Swiss cheese.

PubMed

Koca, N; Rodriguez-Saona, L E; Harper, W J; Alvarez, V B

2007-08-01

Short-chain free fatty acids (FFA) are important sources of cheese flavor and have been reported to be indicators for assessing quality. The objective of this research was to develop a simple and rapid screening tool for monitoring the short-chain FFA contents in Swiss cheese by using Fourier transform infrared spectroscopy (FTIR). Forty-four Swiss cheese samples were evaluated by using a MIRacle three-reflection diamond attenuated total reflectance (ATR) accessory. Two different sampling techniques were used for FTIR/ATR measurement: direct measurement of Swiss cheese slices (approximately 0.5 g) and measurement of a water-soluble fraction of cheese. The amounts of FFA (propionic, acetic, and butyric acids) in the water-soluble fraction of samples were analyzed by gas chromatography-flame ion-ization detection as a reference method. Calibration models for both direct measurement and the water-soluble fraction of cheese were developed based on a cross-validated (leave-one-out approach) partial least squares regression by using the regions of 3,000 to 2,800, 1,775 to 1,680, and 1,500 to 900 cm(-1) for short-chain FFA in cheese. Promising performance statistics were obtained for the calibration models of both direct measurement and the water-soluble fraction, with improved performance statistics obtained from the water-soluble extract, particularly for propionic acid. Partial least squares models generated from FTIR/ATR spectra by direct measurement of cheeses gave standard errors of cross-validation of 9.7 mg/100 g of cheese for propionic acid, 9.3 mg/100 g of cheese for acetic acid, and 5.5 mg/100 g of cheese for butyric acid, and correlation coefficients >0.9. Standard error of cross-validation values for the water-soluble fraction were 4.4 mg/100 g of cheese for propionic acid, 9.2 mg/100 g of cheese for acetic acid, and 5.2 mg/100 g of cheese for butyric acid with correlation coefficients of 0.98, 0.95, and 0.92, respectively. Infrared spectroscopy and chemometrics accurately and precisely predicted the short-chain FFA content in Swiss cheeses and in the water-soluble fraction of the cheese.

[Measurement properties of self-report questionnaires published in Korean nursing journals].

PubMed

Lee, Eun-Hyun; Kim, Chun-Ja; Kim, Eun Jung; Chae, Hyun-Ju; Cho, Soo-Yeon

2013-02-01

The purpose of this study was to evaluate measurement properties of self-report questionnaires for studies published in Korean nursing journals. Of 424 Korean nursing articles initially identified, 168 articles met the inclusion criteria. The methodological quality of the measurements used in the studies and interpretability were assessed using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. It consists of items on internal consistency, reliability, measurement error, content validity, construct validity including structural validity, hypothesis testing, cross-cultural validity, and criterion validity, and responsiveness. For each item of the COSMIN checklist, measurement properties are rated on a four-point scale: excellent, good, fair, and poor. Each measurement property is scored with worst score counts. All articles used the classical test theory for measurement properties. Internal consistency (72.6%), construct validity (56.5%), and content validity (38.2%) were most frequently reported properties being rated as 'excellent' by COSMIN checklist, whereas other measurement properties were rarely reported. A systematic review of measurement properties including interpretability of most instruments warrants further research and nursing-focused checklists assessing measurement properties should be developed to facilitate intervention outcomes across Korean studies.

Creating a Test Validated Structural Dynamic Finite Element Model of the X-56A Aircraft

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truong, Samson

2014-01-01

Small modeling errors in the finite element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of the Multi Utility Technology Test-bed, X-56A aircraft, is the flight demonstration of active flutter suppression, and therefore in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of the X-56A aircraft. The ground vibration test-validated structural dynamic finite element model of the X-56A aircraft is created in this study. The structural dynamic finite element model of the X-56A aircraft is improved using a model tuning tool. In this study, two different weight configurations of the X-56A aircraft have been improved in a single optimization run. Frequency and the cross-orthogonality (mode shape) matrix were the primary focus for improvement, while other properties such as center of gravity location, total weight, and offdiagonal terms of the mass orthogonality matrix were used as constraints. The end result was a more improved and desirable structural dynamic finite element model configuration for the X-56A aircraft. Improved frequencies and mode shapes in this study increased average flutter speeds of the X-56A aircraft by 7.6% compared to the baseline model.

Creating a Test-Validated Finite-Element Model of the X-56A Aircraft Structure

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Truong, Samson

2014-01-01

Small modeling errors in a finite-element model will eventually induce errors in the structural flexibility and mass, thus propagating into unpredictable errors in the unsteady aerodynamics and the control law design. One of the primary objectives of the X-56A Multi-Utility Technology Testbed aircraft is the flight demonstration of active flutter suppression and, therefore, in this study, the identification of the primary and secondary modes for the structural model tuning based on the flutter analysis of the X-56A aircraft. The ground-vibration test-validated structural dynamic finite-element model of the X-56A aircraft is created in this study. The structural dynamic finite-element model of the X-56A aircraft is improved using a model-tuning tool. In this study, two different weight configurations of the X-56A aircraft have been improved in a single optimization run. Frequency and the cross-orthogonality (mode shape) matrix were the primary focus for improvement, whereas other properties such as c.g. location, total weight, and off-diagonal terms of the mass orthogonality matrix were used as constraints. The end result was an improved structural dynamic finite-element model configuration for the X-56A aircraft. Improved frequencies and mode shapes in this study increased average flutter speeds of the X-56A aircraft by 7.6% compared to the baseline model.

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

The developmental clock of dental enamel: a test for the periodicity of prism cross-striations in modern humans and an evaluation of the most likely sources of error in histological studies of this kind

PubMed Central

Antoine, Daniel; Hillson, Simon; Dean, M Christopher

2009-01-01

Dental tissues contain regular microscopic structures believed to result from periodic variations in the secretion of matrix by enamel- and dentine-forming cells. Counts of these structures are an important tool for reconstructing the chronology of dental development in both modern and fossil hominids. Most studies rely on the periodicity of the regular cross-banding that occurs along the long axis of enamel prisms. These prism cross-striations are widely thought to reflect a circadian rhythm of enamel matrix secretion and are generally regarded as representing daily increments of tissue. Previously, some researchers have argued against the circadian periodicity of these structures and questioned their use in reconstructing dental development. Here we tested the periodicity of enamel cross-striations – and the accuracy to which they can be used – in the developing permanent dentition of five children, excavated from a 19th century crypt in London, whose age-at-death was independently known. The interruption of crown formation by death was used to calibrate cross-striation counts. All five individuals produced counts that were strongly consistent with those expected from the independently known ages, taking into account the position of the neonatal line and factors of preservation. These results confirm that cross-striations do indeed reflect a circadian rhythm in enamel matrix secretion. They further validate their use in reconstructing dental development and in determining the age-at-death of the remains of children whose dentitions are still forming at the time of death. Significantly they identify the most likely source of error and the common difficulties encountered in histological studies of this kind. PMID:19166472

Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

NASA Astrophysics Data System (ADS)

Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

2012-12-01

The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some validation experiments demonstrated that the models yield accurate estimates at flux measurement sites, the question remains whether they are performing well over the broader landscape. Moreover, a large number of RS_ET products have been released in recent years. Thus, we also pay attention to the cross-validation method of RS_ET derived from multi-source models. "The Multi-scale Observation Experiment on Evapotranspiration over Heterogeneous Land Surfaces: Flux Observation Matrix" campaign is carried out at the middle reaches of the Heihe River Basin, China in 2012. Flux measurements from an observation matrix composed of 22 EC and 4 LAS are acquired to investigate the cross-validation of multi-source models over different landscapes. In this case, six remote sensing models, including the empirical statistical model, the one-source and two-source models, the Penman-Monteith equation based model, the Priestley-Taylor equation based model, and the complementary relationship based model, are used to perform an intercomparison. All the results from the two cases of RS_ET validation showed that the proposed validation methods are reasonable and feasible.

Evaluation of Collision Cross Section Calibrants for Structural Analysis of Lipids by Traveling Wave Ion Mobility-Mass Spectrometry

PubMed Central

2016-01-01

Collision cross section (CCS) measurement of lipids using traveling wave ion mobility-mass spectrometry (TWIM-MS) is of high interest to the lipidomics field. However, currently available calibrants for CCS measurement using TWIM are predominantly peptides that display quite different physical properties and gas-phase conformations from lipids, which could lead to large CCS calibration errors for lipids. Here we report the direct CCS measurement of a series of phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs) in nitrogen using a drift tube ion mobility (DTIM) instrument and an evaluation of the accuracy and reproducibility of PCs and PEs as CCS calibrants for phospholipids against different classes of calibrants, including polyalanine (PolyAla), tetraalkylammonium salts (TAA), and hexakis(fluoroalkoxy)phosphazines (HFAP), in both positive and negative modes in TWIM-MS analysis. We demonstrate that structurally mismatched calibrants lead to larger errors in calibrated CCS values while the structurally matched calibrants, PCs and PEs, gave highly accurate and reproducible CCS values at different traveling wave parameters. Using the lipid calibrants, the majority of the CCS values of several classes of phospholipids measured by TWIM are within 2% error of the CCS values measured by DTIM. The development of phospholipid CCS calibrants will enable high-accuracy structural studies of lipids and add an additional level of validation in the assignment of identifications in untargeted lipidomics experiments. PMID:27321977

Identifying model error in metabolic flux analysis - a generalized least squares approach.

PubMed

Sokolenko, Stanislav; Quattrociocchi, Marco; Aucoin, Marc G

2016-09-13

The estimation of intracellular flux through traditional metabolic flux analysis (MFA) using an overdetermined system of equations is a well established practice in metabolic engineering. Despite the continued evolution of the methodology since its introduction, there has been little focus on validation and identification of poor model fit outside of identifying "gross measurement error". The growing complexity of metabolic models, which are increasingly generated from genome-level data, has necessitated robust validation that can directly assess model fit. In this work, MFA calculation is framed as a generalized least squares (GLS) problem, highlighting the applicability of the common t-test for model validation. To differentiate between measurement and model error, we simulate ideal flux profiles directly from the model, perturb them with estimated measurement error, and compare their validation to real data. Application of this strategy to an established Chinese Hamster Ovary (CHO) cell model shows how fluxes validated by traditional means may be largely non-significant due to a lack of model fit. With further simulation, we explore how t-test significance relates to calculation error and show that fluxes found to be non-significant have 2-4 fold larger error (if measurement uncertainty is in the 5-10 % range). The proposed validation method goes beyond traditional detection of "gross measurement error" to identify lack of fit between model and data. Although the focus of this work is on t-test validation and traditional MFA, the presented framework is readily applicable to other regression analysis methods and MFA formulations.

Nurses' attitude and intention of medication administration error reporting.

PubMed

Hung, Chang-Chiao; Chu, Tsui-Ping; Lee, Bih-O; Hsiao, Chia-Chi

2016-02-01

The Aims of this study were to explore the effects of nurses' attitudes and intentions regarding medication administration error reporting on actual reporting behaviours. Underreporting of medication errors is still a common occurrence. Whether attitude and intention towards medication administration error reporting connect to actual reporting behaviours remain unclear. This study used a cross-sectional design with self-administered questionnaires, and the theory of planned behaviour was used as the framework for this study. A total of 596 staff nurses who worked in general wards and intensive care units in a hospital were invited to participate in this study. The researchers used the instruments measuring nurses' attitude, nurse managers' and co-workers' attitude, report control, and nurses' intention to predict nurses' actual reporting behaviours. Data were collected from September-November 2013. Path analyses were used to examine the hypothesized model. Of the 596 nurses invited to participate, 548 (92%) completed and returned a valid questionnaire. The findings indicated that nurse managers' and co-workers' attitudes are predictors for nurses' attitudes towards medication administration error reporting. Nurses' attitudes also influenced their intention to report medication administration errors; however, no connection was found between intention and actual reporting behaviour. The findings reflected links among colleague perspectives, nurses' attitudes, and intention to report medication administration errors. The researchers suggest that hospitals should increase nurses' awareness and recognition of error occurrence. Regardless of nurse managers' and co-workers' attitudes towards medication administration error reporting, nurses are likely to report medication administration errors if they detect them. Management of medication administration errors should focus on increasing nurses' awareness and recognition of error occurrence. © 2015 John Wiley & Sons Ltd.

An assessment of air pollutant exposure methods in Mexico City, Mexico.

PubMed

Rivera-González, Luis O; Zhang, Zhenzhen; Sánchez, Brisa N; Zhang, Kai; Brown, Daniel G; Rojas-Bracho, Leonora; Osornio-Vargas, Alvaro; Vadillo-Ortega, Felipe; O'Neill, Marie S

2015-05-01

Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or pregnancy-long exposures. Many studies evaluating associations between outdoor air pollution and adverse pregnancy outcomes rely on outdoor air pollution monitoring data linked to information gathered from large birth registries, and often lack residence location information needed to estimate individual exposure. This study simulated 1,000 residential locations to evaluate four air pollution exposure assessment methods, and describes possible exposure misclassification from using spatial averaging versus geostatistical interpolation models. An implication of this work is that policies to reduce air pollution and exposure among pregnant women based on epidemiologic literature should take into account possible error in estimates of effect when spatial averages alone are evaluated.

Evaluation of bone formation in calcium phosphate scaffolds with μCT-method validation using SEM.

PubMed

Lewin, S; Barba, A; Persson, C; Franch, J; Ginebra, M-P; Öhman-Mägi, C

2017-10-05

There is a plethora of calcium phosphate (CaP) scaffolds used as synthetic substitutes to bone grafts. The scaffold performance is often evaluated from the quantity of bone formed within or in direct contact with the scaffold. Micro-computed tomography (μCT) allows three-dimensional evaluation of bone formation inside scaffolds. However, the almost identical x-ray attenuation of CaP and bone obtrude the separation of these phases in μCT images. Commonly, segmentation of bone in μCT images is based on gray scale intensity, with manually determined global thresholds. However, image analysis methods, and methods for manual thresholding in particular, lack standardization and may consequently suffer from subjectivity. The aim of the present study was to provide a methodological framework for addressing these issues. Bone formation in two types of CaP scaffold architectures (foamed and robocast), obtained from a larger animal study (a 12 week canine animal model) was evaluated by μCT. In addition, cross-sectional scanning electron microscopy (SEM) images were acquired as references to determine thresholds and to validate the result. μCT datasets were registered to the corresponding SEM reference. Global thresholds were then determined by quantitatively correlating the different area fractions in the μCT image, towards the area fractions in the corresponding SEM image. For comparison, area fractions were also quantified using global thresholds determined manually by two different approaches. In the validation the manually determined thresholds resulted in large average errors in area fraction (up to 17%), whereas for the evaluation using SEM references, the errors were estimated to be less than 3%. Furthermore, it was found that basing the thresholds on one single SEM reference gave lower errors than determining them manually. This study provides an objective, robust and less error prone method to determine global thresholds for the evaluation of bone formation in CaP scaffolds.

Mapping from disease-specific measures to health-state utility values in individuals with migraine.

PubMed

Gillard, Patrick J; Devine, Beth; Varon, Sepideh F; Liu, Lei; Sullivan, Sean D

2012-05-01

The objective of this study was to develop empirical algorithms that estimate health-state utility values from disease-specific quality-of-life scores in individuals with migraine. Data from a cross-sectional, multicountry study were used. Individuals with episodic and chronic migraine were randomly assigned to training or validation samples. Spearman's correlation coefficients between paired EuroQol five-dimensional (EQ-5D) questionnaire utility values and both Headache Impact Test (HIT-6) scores and Migraine-Specific Quality-of-Life Questionnaire version 2.1 (MSQ) domain scores (role restrictive, role preventive, and emotional function) were examined. Regression models were constructed to estimate EQ-5D questionnaire utility values from the HIT-6 score or the MSQ domain scores. Preferred algorithms were confirmed in the validation samples. In episodic migraine, the preferred HIT-6 and MSQ algorithms explained 22% and 25% of the variance (R(2)) in the training samples, respectively, and had similar prediction errors (root mean square errors of 0.30). In chronic migraine, the preferred HIT-6 and MSQ algorithms explained 36% and 45% of the variance in the training samples, respectively, and had similar prediction errors (root mean square errors 0.31 and 0.29). In episodic and chronic migraine, no statistically significant differences were observed between the mean observed and the mean estimated EQ-5D questionnaire utility values for the preferred HIT-6 and MSQ algorithms in the validation samples. The relationship between the EQ-5D questionnaire and the HIT-6 or the MSQ is adequate to use regression equations to estimate EQ-5D questionnaire utility values. The preferred HIT-6 and MSQ algorithms will be useful in estimating health-state utilities in migraine trials in which no preference-based measure is present. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Temporal regularization of ultrasound-based liver motion estimation for image-guided radiation therapy

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

O’Shea, Tuathan P., E-mail: tuathan.oshea@icr.ac.uk; Bamber, Jeffrey C.; Harris, Emma J.

Purpose: Ultrasound-based motion estimation is an expanding subfield of image-guided radiation therapy. Although ultrasound can detect tissue motion that is a fraction of a millimeter, its accuracy is variable. For controlling linear accelerator tracking and gating, ultrasound motion estimates must remain highly accurate throughout the imaging sequence. This study presents a temporal regularization method for correlation-based template matching which aims to improve the accuracy of motion estimates. Methods: Liver ultrasound sequences (15–23 Hz imaging rate, 2.5–5.5 min length) from ten healthy volunteers under free breathing were used. Anatomical features (blood vessels) in each sequence were manually annotated for comparison withmore » normalized cross-correlation based template matching. Five sequences from a Siemens Acuson™ scanner were used for algorithm development (training set). Results from incremental tracking (IT) were compared with a temporal regularization method, which included a highly specific similarity metric and state observer, known as the α–β filter/similarity threshold (ABST). A further five sequences from an Elekta Clarity™ system were used for validation, without alteration of the tracking algorithm (validation set). Results: Overall, the ABST method produced marked improvements in vessel tracking accuracy. For the training set, the mean and 95th percentile (95%) errors (defined as the difference from manual annotations) were 1.6 and 1.4 mm, respectively (compared to 6.2 and 9.1 mm, respectively, for IT). For each sequence, the use of the state observer leads to improvement in the 95% error. For the validation set, the mean and 95% errors for the ABST method were 0.8 and 1.5 mm, respectively. Conclusions: Ultrasound-based motion estimation has potential to monitor liver translation over long time periods with high accuracy. Nonrigid motion (strain) and the quality of the ultrasound data are likely to have an impact on tracking performance. A future study will investigate spatial uniformity of motion and its effect on the motion estimation errors.« less

Comparing ordinary kriging and inverse distance weighting for soil as pollution in Beijing.

PubMed

Qiao, Pengwei; Lei, Mei; Yang, Sucai; Yang, Jun; Guo, Guanghui; Zhou, Xiaoyong

2018-06-01

Spatial interpolation method is the basis of soil heavy metal pollution assessment and remediation. The existing evaluation index for interpolation accuracy did not combine with actual situation. The selection of interpolation methods needs to be based on specific research purposes and research object characteristics. In this paper, As pollution in soils of Beijing was taken as an example. The prediction accuracy of ordinary kriging (OK) and inverse distance weighted (IDW) were evaluated based on the cross validation results and spatial distribution characteristics of influencing factors. The results showed that, under the condition of specific spatial correlation, the cross validation results of OK and IDW for every soil point and the prediction accuracy of spatial distribution trend are similar. But the prediction accuracy of OK for the maximum and minimum is less than IDW, while the number of high pollution areas identified by OK are less than IDW. It is difficult to identify the high pollution areas fully by OK, which shows that the smoothing effect of OK is obvious. In addition, with increasing of the spatial correlation of As concentration, the cross validation error of OK and IDW decreases, and the high pollution area identified by OK is approaching the result of IDW, which can identify the high pollution areas more comprehensively. However, because the semivariogram constructed by OK interpolation method is more subjective and requires larger number of soil samples, IDW is more suitable for spatial prediction of heavy metal pollution in soils.

Radioactive Quality Evaluation and Cross Validation of Data from the HJ-1A/B Satellites' CCD Sensors

PubMed Central

Zhang, Xin; Zhao, Xiang; Liu, Guodong; Kang, Qian; Wu, Donghai

2013-01-01

Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency. PMID:23881127

Radioactive quality evaluation and cross validation of data from the HJ-1A/B satellites' CCD sensors.

PubMed

Zhang, Xin; Zhao, Xiang; Liu, Guodong; Kang, Qian; Wu, Donghai

2013-07-05

Data from multiple sensors are frequently used in Earth science to gain a more complete understanding of spatial information changes. Higher quality and mutual consistency are prerequisites when multiple sensors are jointly used. The HJ-1A/B satellites successfully launched on 6 September 2008. There are four charge-coupled device (CCD) sensors with uniform spatial resolutions and spectral range onboard the HJ-A/B satellites. Whether these data are keeping consistency is a major issue before they are used. This research aims to evaluate the data consistency and radioactive quality from the four CCDs. First, images of urban, desert, lake and ocean are chosen as the objects of evaluation. Second, objective evaluation variables, such as mean, variance and angular second moment, are used to identify image performance. Finally, a cross validation method are used to ensure the correlation of the data from the four HJ-1A/B CCDs and that which is gathered from the moderate resolution imaging spectro-radiometer (MODIS). The results show that the image quality of HJ-1A/B CCDs is stable, and the digital number distribution of CCD data is relatively low. In cross validation with MODIS, the root mean square errors of bands 1, 2 and 3 range from 0.055 to 0.065, and for band 4 it is 0.101. The data from HJ-1A/B CCD have better consistency.

The associations of insomnia with costly workplace accidents and errors: results from the America Insomnia Survey.

PubMed

Shahly, Victoria; Berglund, Patricia A; Coulouvrat, Catherine; Fitzgerald, Timothy; Hajak, Goeran; Roth, Thomas; Shillington, Alicia C; Stephenson, Judith J; Walsh, James K; Kessler, Ronald C

2012-10-01

Insomnia is a common and seriously impairing condition that often goes unrecognized. To examine associations of broadly defined insomnia (ie, meeting inclusion criteria for a diagnosis from International Statistical Classification of Diseases, 10th Revision, DSM-IV, or Research Diagnostic Criteria/International Classification of Sleep Disorders, Second Edition) with costly workplace accidents and errors after excluding other chronic conditions among workers in the America Insomnia Survey (AIS). A national cross-sectional telephone survey (65.0% cooperation rate) of commercially insured health plan members selected from the more than 34 million in the HealthCore Integrated Research Database. Four thousand nine hundred ninety-one employed AIS respondents. Costly workplace accidents or errors in the 12 months before the AIS interview were assessed with one question about workplace accidents "that either caused damage or work disruption with a value of $500 or more" and another about other mistakes "that cost your company $500 or more." Current insomnia with duration of at least 12 months was assessed with the Brief Insomnia Questionnaire, a validated (area under the receiver operating characteristic curve, 0.86 compared with diagnoses based on blinded clinical reappraisal interviews), fully structured diagnostic interview. Eighteen other chronic conditions were assessed with medical/pharmacy claims records and validated self-report scales. Insomnia had a significant odds ratio with workplace accidents and/or errors controlled for other chronic conditions (1.4). The odds ratio did not vary significantly with respondent age, sex, educational level, or comorbidity. The average costs of insomnia-related accidents and errors ($32 062) were significantly higher than those of other accidents and errors ($21 914). Simulations estimated that insomnia was associated with 7.2% of all costly workplace accidents and errors and 23.7% of all the costs of these incidents. These proportions are higher than for any other chronic condition, with annualized US population projections of 274 000 costly insomnia-related workplace accidents and errors having a combined value of US $31.1 billion. Effectiveness trials are needed to determine whether expanded screening, outreach, and treatment of workers with insomnia would yield a positive return on investment for employers.

Automated body weight prediction of dairy cows using 3-dimensional vision.

PubMed

Song, X; Bokkers, E A M; van der Tol, P P J; Groot Koerkamp, P W G; van Mourik, S

2018-05-01

The objectives of this study were to quantify the error of body weight prediction using automatically measured morphological traits in a 3-dimensional (3-D) vision system and to assess the influence of various sources of uncertainty on body weight prediction. In this case study, an image acquisition setup was created in a cow selection box equipped with a top-view 3-D camera. Morphological traits of hip height, hip width, and rump length were automatically extracted from the raw 3-D images taken of the rump area of dairy cows (n = 30). These traits combined with days in milk, age, and parity were used in multiple linear regression models to predict body weight. To find the best prediction model, an exhaustive feature selection algorithm was used to build intermediate models (n = 63). Each model was validated by leave-one-out cross-validation, giving the root mean square error and mean absolute percentage error. The model consisting of hip width (measurement variability of 0.006 m), days in milk, and parity was the best model, with the lowest errors of 41.2 kg of root mean square error and 5.2% mean absolute percentage error. Our integrated system, including the image acquisition setup, image analysis, and the best prediction model, predicted the body weights with a performance similar to that achieved using semi-automated or manual methods. Moreover, the variability of our simplified morphological trait measurement showed a negligible contribution to the uncertainty of body weight prediction. We suggest that dairy cow body weight prediction can be improved by incorporating more predictive morphological traits and by improving the prediction model structure. The Authors. Published by FASS Inc. and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

Concurrent validity and interrater reliability of a new smartphone application to assess 3D active cervical range of motion in patients with neck pain.

PubMed

Stenneberg, Martijn S; Busstra, Harm; Eskes, Michel; van Trijffel, Emiel; Cattrysse, Erik; Scholten-Peeters, Gwendolijne G M; de Bie, Rob A

2018-04-01

There is a lack of valid, reliable, and feasible instruments for measuring planar active cervical range of motion (aCROM) and associated 3D coupling motions in patients with neck pain. Smartphones have advanced sensors and appear to be suitable for these measurements. To estimate the concurrent validity and interrater reliability of a new iPhone application for assessing planar aCROM and associated 3D coupling motions in patients with neck pain, using an electromagnetic tracking device as a reference test. Cross-sectional study. Two samples of neck pain patients were recruited; 30 patients for the validity study and 26 patients for the reliability study. Validity was estimated using intraclass correlation coefficients (ICCs), and by calculating 95% limits of agreement (LoA). To estimate interrater reliability, ICCs were calculated. Cervical 3D coupling motions were analyzed by calculating the cross-correlation coefficients and ratio between the main motions and coupled motions for both instruments. ICCs for concurrent validity and interrater reliability ranged from 0.90 to 0.99. The width of the 95% LoA ranged from about 5° for right lateral bending to 11° for total rotation. No significant differences were found between both devices for associated coupling motion analysis. The iPhone application appears to be a useful discriminative tool for the measurement of planar aCROM and associated coupling motions in patients with neck pain. It fulfills the need for a valid, reliable, and feasible instrument in clinical practice and research. Therapists and researchers should consider measurement error when interpreting scores. Copyright © 2017 Elsevier Ltd. All rights reserved.

POD-based constrained sensor placement and field reconstruction from noisy wind measurements: A perturbation study

DOE PAGES

Zhang, Zhongqiang; Yang, Xiu; Lin, Guang

2016-04-14

Sensor placement at the extrema of Proper Orthogonal Decomposition (POD) is efficient and leads to accurate reconstruction of the wind field from a limited number of measure- ments. In this paper we extend this approach of sensor placement and take into account measurement errors and detect possible malfunctioning sensors. We use the 48 hourly spa- tial wind field simulation data sets simulated using the Weather Research an Forecasting (WRF) model applied to the Maine Bay to evaluate the performances of our methods. Specifically, we use an exclusion disk strategy to distribute sensors when the extrema of POD modes are close.more » It turns out that this strategy can also reduce the error of recon- struction from noise measurements. Also, by a cross-validation technique, we successfully locate the malfunctioning sensors.« less

A novel method for the simultaneous measurement of temperature and strain using a three-wire connection

NASA Astrophysics Data System (ADS)

Cappa, Paolo; Marinozzi, Franco; Sciuto, Salvatore Andrea

2001-04-01

A novel methodology to simultaneously measure strain and temperature by means of an electrical resistance strain gauge powered by an ac signal and connected to a strain indicator by means of thermocouple wires is proposed. The experimental validation of the viability of this method is conducted by means of a purely electrical simulation of both strain and temperature signals, respectively from -2000 to 2000 µm m-1 and -250 to 230 °C. The results obtained showed that strain measurement is affected by an error always less than ±2 µm m-1 for the whole range of simulated strains, while the error in temperature evaluation is always less than 0.6 °C. The effect of cross-talk between the two signals was determined to be insignificant.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

NASA Astrophysics Data System (ADS)

Brokamp, Cole; Jandarov, Roman; Rao, M. B.; LeMasters, Grace; Ryan, Patrick

2017-02-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches.

PubMed

Brokamp, Cole; Jandarov, Roman; Rao, M B; LeMasters, Grace; Ryan, Patrick

2017-02-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

PubMed Central

Brokamp, Cole; Jandarov, Roman; Rao, M.B.; LeMasters, Grace; Ryan, Patrick

2017-01-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment. PMID:28959135

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

Estimation of Particulate Mass and Manganese Exposure Levels among Welders

PubMed Central

Hobson, Angela; Seixas, Noah; Sterling, David; Racette, Brad A.

2011-01-01

Background: Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations reported in the published literature. Methods: Articles that described welding particulate and Mn exposures during field welding activities were identified through a comprehensive literature search. Summary measures of exposure and related determinants such as year of sampling, welding process performed, type of ventilation used, degree of enclosure, base metal, and location of sampling filter were extracted from each article. The natural log of the reported arithmetic mean exposure level was used as the dependent variable in model building, while the independent variables included the exposure determinants. Cross-validation was performed to aid in model selection and to evaluate the generalizability of the models. Results: A total of 33 particulate and 27 Mn means were included in the regression analysis. The final model explained 76% of the variability in the mean exposures and included welding process and degree of enclosure as predictors. There was very little change in the explained variability and root mean squared error between the final model and its cross-validation model indicating the final model is robust given the available data. Conclusions: This model may be improved with more detailed exposure determinants; however, the relatively large amount of variance explained by the final model along with the positive generalizability results of the cross-validation increases the confidence that the estimates derived from this model can be used for estimating welder exposures in absence of individual measurement data. PMID:20870928

Association between split selection instability and predictive error in survival trees.

PubMed

Radespiel-Tröger, M; Gefeller, O; Rabenstein, T; Hothorn, T

2006-01-01

To evaluate split selection instability in six survival tree algorithms and its relationship with predictive error by means of a bootstrap study. We study the following algorithms: logrank statistic with multivariate p-value adjustment without pruning (LR), Kaplan-Meier distance of survival curves (KM), martingale residuals (MR), Poisson regression for censored data (PR), within-node impurity (WI), and exponential log-likelihood loss (XL). With the exception of LR, initial trees are pruned by using split-complexity, and final trees are selected by means of cross-validation. We employ a real dataset from a clinical study of patients with gallbladder stones. The predictive error is evaluated using the integrated Brier score for censored data. The relationship between split selection instability and predictive error is evaluated by means of box-percentile plots, covariate and cutpoint selection entropy, and cutpoint selection coefficients of variation, respectively, in the root node. We found a positive association between covariate selection instability and predictive error in the root node. LR yields the lowest predictive error, while KM and MR yield the highest predictive error. The predictive error of survival trees is related to split selection instability. Based on the low predictive error of LR, we recommend the use of this algorithm for the construction of survival trees. Unpruned survival trees with multivariate p-value adjustment can perform equally well compared to pruned trees. The analysis of split selection instability can be used to communicate the results of tree-based analyses to clinicians and to support the application of survival trees.

Neural Correlates of User-initiated Motor Success and Failure - A Brain-Computer Interface Perspective.

PubMed

Yazmir, Boris; Reiner, Miriam

2018-05-15

Any motor action is, by nature, potentially accompanied by human errors. In order to facilitate development of error-tailored Brain-Computer Interface (BCI) correction systems, we focused on internal, human-initiated errors, and investigated EEG correlates of user outcome successes and errors during a continuous 3D virtual tennis game against a computer player. We used a multisensory, 3D, highly immersive environment. Missing and repelling the tennis ball were considered, as 'error' (miss) and 'success' (repel). Unlike most previous studies, where the environment "encouraged" the participant to perform a mistake, here errors happened naturally, resulting from motor-perceptual-cognitive processes of incorrect estimation of the ball kinematics, and can be regarded as user internal, self-initiated errors. Results show distinct and well-defined Event-Related Potentials (ERPs), embedded in the ongoing EEG, that differ across conditions by waveforms, scalp signal distribution maps, source estimation results (sLORETA) and time-frequency patterns, establishing a series of typical features that allow valid discrimination between user internal outcome success and error. The significant delay in latency between positive peaks of error- and success-related ERPs, suggests a cross-talk between top-down and bottom-up processing, represented by an outcome recognition process, in the context of the game world. Success-related ERPs had a central scalp distribution, while error-related ERPs were centro-parietal. The unique characteristics and sharp differences between EEG correlates of error/success provide the crucial components for an improved BCI system. The features of the EEG waveform can be used to detect user action outcome, to be fed into the BCI correction system. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

SERS quantitative urine creatinine measurement of human subject

NASA Astrophysics Data System (ADS)

Wang, Tsuei Lian; Chiang, Hui-hua K.; Lu, Hui-hsin; Hung, Yung-da

2005-03-01

SERS method for biomolecular analysis has several potentials and advantages over traditional biochemical approaches, including less specimen contact, non-destructive to specimen, and multiple components analysis. Urine is an easily available body fluid for monitoring the metabolites and renal function of human body. We developed surface-enhanced Raman scattering (SERS) technique using 50nm size gold colloidal particles for quantitative human urine creatinine measurements. This paper shows that SERS shifts of creatinine (104mg/dl) in artificial urine is from 1400cm-1 to 1500cm-1 which was analyzed for quantitative creatinine measurement. Ten human urine samples were obtained from ten healthy persons and analyzed by the SERS technique. Partial least square cross-validation (PLSCV) method was utilized to obtain the estimated creatinine concentration in clinically relevant (55.9mg/dl to 208mg/dl) concentration range. The root-mean square error of cross validation (RMSECV) is 26.1mg/dl. This research demonstrates the feasibility of using SERS for human subject urine creatinine detection, and establishes the SERS platform technique for bodily fluids measurement.

DEApp: an interactive web interface for differential expression analysis of next generation sequence data.

PubMed

Li, Yan; Andrade, Jorge

2017-01-01

A growing trend in the biomedical community is the use of Next Generation Sequencing (NGS) technologies in genomics research. The complexity of downstream differential expression (DE) analysis is however still challenging, as it requires sufficient computer programing and command-line knowledge. Furthermore, researchers often need to evaluate and visualize interactively the effect of using differential statistical and error models, assess the impact of selecting different parameters and cutoffs, and finally explore the overlapping consensus of cross-validated results obtained with different methods. This represents a bottleneck that slows down or impedes the adoption of NGS technologies in many labs. We developed DEApp, an interactive and dynamic web application for differential expression analysis of count based NGS data. This application enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface. DEApp enables labs with no access to full time bioinformaticians to exploit the advantages of NGS applications in biomedical research. This application is freely available at https://yanli.shinyapps.io/DEAppand https://gallery.shinyapps.io/DEApp.

Multivariate methods on the excitation emission matrix fluorescence spectroscopic data of diesel-kerosene mixtures: a comparative study.

PubMed

Divya, O; Mishra, Ashok K

2007-05-29

Quantitative determination of kerosene fraction present in diesel has been carried out based on excitation emission matrix fluorescence (EEMF) along with parallel factor analysis (PARAFAC) and N-way partial least squares regression (N-PLS). EEMF is a simple, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. Calibration models consisting of varying compositions of diesel and kerosene were constructed and their validation was carried out using leave-one-out cross validation method. The accuracy of the model was evaluated through the root mean square error of prediction (RMSEP) for the PARAFAC, N-PLS and unfold PLS methods. N-PLS was found to be a better method compared to PARAFAC and unfold PLS method because of its low RMSEP values.

Cross-validation of a Shortened Battery for the Assessment of Dysexecutive Disorders in Alzheimer Disease.

PubMed

Godefroy, Olivier; Martinaud, Olivier; Verny, Marc; Mosca, Chrystèle; Lenoir, Hermine; Bretault, Eric; Devendeville, Agnès; Diouf, Momar; Pere, Jean-Jacques; Bakchine, Serge; Delabrousse-Mayoux, Jean-Philippe; Roussel, Martine

2016-01-01

The frequency of executive disorders in mild-to-moderate Alzheimer disease (AD) has been demonstrated by the application of a comprehensive battery. The present study analyzed data from 2 recent multicenter studies based on the same executive battery. The objective was to derive a shortened battery by using the GREFEX population as a training dataset and by cross-validating the results in the REFLEX population. A total of 102 AD patients of the GREFEX study (MMSE=23.2±2.9) and 72 patients of the REFLEX study (MMSE=20.8±3.5) were included. Tests were selected and receiver operating characteristic curves were generated relative to the performance of 780 controls from the GREFEX study. Stepwise logistic regression identified 3 cognitive tests (Six Elements Task, categorical fluency and Trail Making Test B error) and behavioral disorders globally referred as global hypoactivity (P=0.0001, all). This shortened battery was as accurate as the entire GREFEX battery in diagnosing dysexecutive disorders in both training group and the validation group. Bootstrap procedure confirmed the stability of AUC. A shortened battery based on 3 cognitive tests and 3 behavioral domains provides a high diagnosis accuracy of executive disorders in mild-to-moderate AD.

Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions

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

Huan, Xun; Safta, Cosmin; Sargsyan, Khachik

Compressive sensing is a powerful technique for recovering sparse solutions of underdetermined linear systems, which is often encountered in uncertainty quanti cation analysis of expensive and high-dimensional physical models. We perform numerical investigations employing several com- pressive sensing solvers that target the unconstrained LASSO formulation, with a focus on linear systems that arise in the construction of polynomial chaos expansions. With core solvers of l1 ls, SpaRSA, CGIST, FPC AS, and ADMM, we develop techniques to mitigate over tting through an automated selection of regularization constant based on cross-validation, and a heuristic strategy to guide the stop-sampling decision. Practical recommendationsmore » on parameter settings for these tech- niques are provided and discussed. The overall method is applied to a series of numerical examples of increasing complexity, including large eddy simulations of supersonic turbulent jet-in-cross flow involving a 24-dimensional input. Through empirical phase-transition diagrams and convergence plots, we illustrate sparse recovery performance under structures induced by polynomial chaos, accuracy and computational tradeoffs between polynomial bases of different degrees, and practi- cability of conducting compressive sensing for a realistic, high-dimensional physical application. Across test cases studied in this paper, we find ADMM to have demonstrated empirical advantages through consistent lower errors and faster computational times.« less

Lymphoedema Functioning, Disability and Health Questionnaire for Lower Limb Lymphoedema (Lymph-ICF-LL): reliability and validity.

PubMed

Devoogdt, Nele; De Groef, An; Hendrickx, Ad; Damstra, Robert; Christiaansen, Anke; Geraerts, Inge; Vervloesem, Nele; Vergote, Ignace; Van Kampen, Marijke

2014-05-01

Patients may develop primary (congenital) or secondary (acquired) lymphedema, causing significant physical and psychosocial problems. To plan treatment for lymphedema and monitor a patient's progress, swelling, and problems in functioning associated with lymphedema development should be assessed at baseline and follow-up. The purpose of this study was to investigate the reliability (test-retest, internal consistency, and measurement variability) and validity (content and construct) of data obtained with the Lymphoedema Functioning, Disability and Health Questionnaire for Lower Limb Lymphoedema (Lymph-ICF-LL). This was a multicenter, cross-sectional study. The Lymph-ICF-LL is a descriptive, evaluative tool containing 28 questions about impairments in function, activity limitations, and participation restrictions in patients with lower limb lymphedema. The questionnaire has 5 domains: physical function, mental function, general tasks/household activities, mobility activities, and life domains/social life. The reliability and validity of the Lymph-ICF-LL were examined in 30 participants with objective lower limb lymphedema. Intraclass correlation coefficients for test-retest reliability ranged from .69 to .94, and Cronbach alpha coefficients for internal consistency ranged from .82 to .97. Measurement variability was acceptable (standard error of measurement=5.9-12.6). Content validity was good because all questions were understandable for 93% of participants, the scoring system (visual analog scale) was clear, and the questionnaire was comprehensive for 90% of participants. Construct validity was good. All hypotheses for assessing convergent validity and divergent validity were accepted. The known-groups validity and responsiveness of the Dutch Lymph-ICF-LL and the cross-cultural validity of the English version of the Lymph-ICF-LL were not investigated. The Lymph-ICF-LL is a Dutch questionnaire with evidence of reliability and validity for assessing impairments in function, activity limitations, and participation restrictions in people with primary or secondary lower limb lymphedema.

High validity and reliability of the PedsQL™ Multidimensional Fatigue Scale for Brazilian children with cancer.

PubMed

Nascimento, Lucila Castanheira; Nunes, Michelle Darezzo Rodrigues; Rocha, Ester Leonardo; Bomfim, Emiliana Omena; Floria-Santos, Milena; Dos Santos, Claudia Benedita; Dos Santos, Danielle Maria de Souza Serio; de Lima, Regina Aparecida Garcia

2015-01-01

Among the main factors that affect patients' quality of life, fatigue is a significant symptom experienced by children during treatment. Despite the high incidence, there has been no validated scale to evaluate fatigue in children with cancer in Brazil. The purpose of this study was to examine the psychometric properties of the PedsQL™ Multidimensional Fatigue Scale, using self-reports of Brazilian children, 8 to 18 years of age, and proxy reports. A cross-sectional method was used to collect data from 216 subjects over an 18-month period. Reliability ranged from .70 to .90 except for sleep/rest fatigue, self-report (α = .55). No floor or ceiling effects were found in any dimension. Convergent validity was higher than .40 and divergent validity had 100% adjustment. The root mean square error of approximation was acceptable. The comparative fit index was lower than expected. The agreement between self and proxy responses was weak and moderate. The results demonstrate the reliability and validity of the Brazilian version in children with cancer. This is the first validated scale that assesses fatigue in Brazilian children and adolescents with cancer. © 2014 by Association of Pediatric Hematology/Oncology Nurses.

[Validity and reliability of the Culture of Quality Health Services questionnaire in Mexico].

PubMed

Herrera-Kiengelher, L; Zepeda-Zaragoza, J; Austria-Corrales, F; Vázquez-Zarate, V M

2013-01-01

Patient Safety is a major public health problem worldwide and is responsibility of all those involved in health care. Establishing a Safety Culture has proved to be a factor that favors the integration of work teams, communication and construction of clear procedures in various organizations. Promote a culture of safety depends on several factors, such as organization, work unit and staff. Objective assessment of these factors will help to identify areas for improvement and establish strategic lines of action. [corrected] To adapt, validate and calibrate the questionnaire Culture of Quality in Health Services (CQHS) in Mexican population. A cross with a stratified representative sample of 522 health workers. The questionnaire was translated and adapted from Singer's. Content was validated by experts, internal consistency, confirmatory factorial validity and item calibration with Samejima's Graded Response Model. Convergent and divergent construct validity was confirmed from the CQHS, item calibration showed that the questionnaire is able to discriminate between patients and represent different levels of the hypothesized dimensions with greater accuracy and lower standard error. The CQHS is a valid and reliable instrument to assess patient safety culture in hospitals in Mexico. Copyright © 2013 SECA. Published by Elsevier Espana. All rights reserved.

[Validation of a method for notifying and monitoring medication errors in pediatrics].

PubMed

Guerrero-Aznar, M D; Jiménez-Mesa, E; Cotrina-Luque, J; Villalba-Moreno, A; Cumplido-Corbacho, R; Fernández-Fernández, L

2014-12-01

To analyze the impact of a multidisciplinary and decentralized safety committee in the pediatric management unit, and the joint implementation of a computing network application for reporting medication errors, monitoring the follow-up of the errors, and an analysis of the improvements introduced. An observational, descriptive, cross-sectional, pre-post intervention study was performed. An analysis was made of medication errors reported to the central safety committee in the twelve months prior to introduction, and those reported to the decentralized safety committee in the management unit in the nine months after implementation, using the computer application, and the strategies generated by the analysis of reported errors. Number of reported errors/10,000 days of stay, number of reported errors with harm per 10,000 days of stay, types of error, categories based on severity, stage of the process, and groups involved in the notification of medication errors. Reported medication errors increased 4.6 -fold, from 7.6 notifications of medication errors per 10,000 days of stay in the pre-intervention period to 36 in the post-intervention, rate ratio 0.21 (95% CI; 0.11-0.39) (P<.001). The medication errors with harm or requiring monitoring reported per 10,000 days of stay, was virtually unchanged from one period to the other ratio rate 0,77 (95% IC; 0,31-1,91) (P>.05). The notification of potential errors or errors without harm per 10,000 days of stay increased 17.4-fold (rate ratio 0.005., 95% CI; 0.001-0.026, P<.001). The increase in medication errors notified in the post-intervention period is a reflection of an increase in the motivation of health professionals to report errors through this new method. Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data.

PubMed

Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios

2014-01-01

To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Atom-type-based AI topological descriptors: application in structure-boiling point correlations of oxo organic compounds.

PubMed

Ren, Biye

2003-01-01

Structure-boiling point relationships are studied for a series of oxo organic compounds by means of multiple linear regression (MLR) analysis. Excellent MLR models based on the recently introduced Xu index and the atom-type-based AI indices are obtained for the two subsets containing respectively 77 ethers and 107 carbonyl compounds and a combined set of 184 oxo compounds. The best models are tested using the leave-one-out cross-validation and an external test set, respectively. The MLR model produces a correlation coefficient of r = 0.9977 and a standard error of s = 3.99 degrees C for the training set of 184 compounds, and r(cv) = 0.9974 and s(cv) = 4.16 degrees C for the cross-validation set, and r(pred) = 0.9949 and s(pred) = 4.38 degrees C for the prediction set of 21 compounds. For the two subsets containing respectively 77 ethers and 107 carbonyl compounds, the quality of the models is further improved. The standard errors are reduced to 3.30 and 3.02 degrees C, respectively. Furthermore, the results obtained from this study indicate that the boiling points of the studied oxo compound dominantly depend on molecular size and also depend on individual atom types, especially oxygen heteroatoms in molecules due to strong polar interactions between molecules. These excellent structure-boiling point models not only provide profound insights into the role of structural features in a molecule but also illustrate the usefulness of these indices in QSPR/QSAR modeling of complex compounds.

Automatic segmentation and co-registration of gated CT angiography datasets: measuring abdominal aortic pulsatility

NASA Astrophysics Data System (ADS)

Wentz, Robert; Manduca, Armando; Fletcher, J. G.; Siddiki, Hassan; Shields, Raymond C.; Vrtiska, Terri; Spencer, Garrett; Primak, Andrew N.; Zhang, Jie; Nielson, Theresa; McCollough, Cynthia; Yu, Lifeng

2007-03-01

Purpose: To develop robust, novel segmentation and co-registration software to analyze temporally overlapping CT angiography datasets, with an aim to permit automated measurement of regional aortic pulsatility in patients with abdominal aortic aneurysms. Methods: We perform retrospective gated CT angiography in patients with abdominal aortic aneurysms. Multiple, temporally overlapping, time-resolved CT angiography datasets are reconstructed over the cardiac cycle, with aortic segmentation performed using a priori anatomic assumptions for the aorta and heart. Visual quality assessment is performed following automatic segmentation with manual editing. Following subsequent centerline generation, centerlines are cross-registered across phases, with internal validation of co-registration performed by examining registration at the regions of greatest diameter change (i.e. when the second derivative is maximal). Results: We have performed gated CT angiography in 60 patients. Automatic seed placement is successful in 79% of datasets, requiring either no editing (70%) or minimal editing (less than 1 minute; 12%). Causes of error include segmentation into adjacent, high-attenuating, nonvascular tissues; small segmentation errors associated with calcified plaque; and segmentation of non-renal, small paralumbar arteries. Internal validation of cross-registration demonstrates appropriate registration in our patient population. In general, we observed that aortic pulsatility can vary along the course of the abdominal aorta. Pulsation can also vary within an aneurysm as well as between aneurysms, but the clinical significance of these findings remain unknown. Conclusions: Visualization of large vessel pulsatility is possible using ECG-gated CT angiography, partial scan reconstruction, automatic segmentation, centerline generation, and coregistration of temporally resolved datasets.

Characterization Approaches to Place Invariant Sites on SI-Traceable Scales

NASA Technical Reports Server (NTRS)

Thome, Kurtis

2012-01-01

The effort to understand the Earth's climate system requires a complete integration of remote sensing imager data across time and multiple countries. Such an integration necessarily requires ensuring inter-consistency between multiple sensors to create the data sets needed to understand the climate system. Past efforts at inter-consistency have forced agreement between two sensors using sources that are viewed by both sensors at nearly the same time, and thus tend to be near polar regions over snow and ice. The current work describes a method that would provide an absolute radiometric calibration of a sensor rather than an inter-consistency of a sensor relative to another. The approach also relies on defensible error budgets that eventually provides a cross comparison of sensors without systematic errors. The basis of the technique is a model-based, SI-traceable prediction of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The effort effectively works to characterize the sites as sources with known top-of-atmosphere radiance allowing accurate intercomparison of sensor data that without the need for coincident views. Data from the Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), and Moderate Resolution Imaging Spectroradiometer (MODIS) are used to demonstrate the difficulties of cross calibration as applied to current sensors. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The radiance comparisons lead to significant differences created by the specific solar model used for each sensor. The paper also proposes methods to mitigate the largest error sources in future systems. The results from these historical intercomparisons provide the basis for a set of recommendations to ensure future SI-traceable cross calibration using future missions such as CLARREO and TRUTHS. The paper describes a proposed approach that relies on model-based, SI-traceable predictions of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The basis of the method is highly accurate measurements of at-sensor radiance of sufficient quality to understand the spectral and BRDF characteristics of the site and sufficient historical data to develop an understanding of temporal effects from changing surface and atmospheric conditions.

PLS-LS-SVM based modeling of ATR-IR as a robust method in detection and qualification of alprazolam

NASA Astrophysics Data System (ADS)

Parhizkar, Elahehnaz; Ghazali, Mohammad; Ahmadi, Fatemeh; Sakhteman, Amirhossein

2017-02-01

According to the United States pharmacopeia (USP), Gold standard technique for Alprazolam determination in dosage forms is HPLC, an expensive and time-consuming method that is not easy to approach. In this study chemometrics assisted ATR-IR was introduced as an alternative method that produce similar results in fewer time and energy consumed manner. Fifty-eight samples containing different concentrations of commercial alprazolam were evaluated by HPLC and ATR-IR method. A preprocessing approach was applied to convert raw data obtained from ATR-IR spectra to normal matrix. Finally, a relationship between alprazolam concentrations achieved by HPLC and ATR-IR data was established using PLS-LS-SVM (partial least squares least squares support vector machines). Consequently, validity of the method was verified to yield a model with low error values (root mean square error of cross validation equal to 0.98). The model was able to predict about 99% of the samples according to R2 of prediction set. Response permutation test was also applied to affirm that the model was not assessed by chance correlations. At conclusion, ATR-IR can be a reliable method in manufacturing process in detection and qualification of alprazolam content.

Cross-layer Design for MIMO Systems with Transmit Antenna Selection and Imperfect CSI

NASA Astrophysics Data System (ADS)

Yu, Xiangbin; Liu, Yan; Rui, Yun; Zhou, Tingting; Yin, Xin

2013-04-01

In this paper, by combining adaptive modulation and automatic repeat request (ARQ), a cross-layer design (CLD) scheme for multiple-input and multiple-output (MIMO) system with transmit antenna selection (TAS) and imperfect channel state information (CSI) is presented. Based on the imperfect CSI, the probability density function of the effective signal to noise ratio (SNR) is derived, and the fading gain switching thresholds are also derived subject to a target packet loss rate and fixed power constraint. According to these results, we further derive the average spectrum efficiency (SE) and packet error rate (PER) of the system. As a result, closed-form expressions of the average SE and PER are obtained, respectively. The derived expressions include the expressions under perfect CSI as special cases, and can provide good performance evaluation for the CLD system with imperfect CSI. Simulation results verify the validity of the theoretical analysis. The results show that the CLD system with TAS provides better SE than that with space-time block coding, but the SE and PER performance of the system with imperfect CSI are worse than those with perfect CSI due to the estimation error.

Evolution of Altimetry Calibration and Future Challenges

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng; Haines, Bruce J.

2012-01-01

Over the past 20 years, altimetry calibration has evolved from an engineering-oriented exercise to a multidisciplinary endeavor driving the state of the art. This evolution has been spurred by the developing promise of altimetry to capture the large-scale, but small-amplitude, changes of the ocean surface containing the expression of climate change. The scope of altimeter calibration/validation programs has expanded commensurately. Early efforts focused on determining a constant range bias and verifying basic compliance of the data products with mission requirements. Contemporary investigations capture, with increasing accuracies, the spatial and temporal characteristics of errors in all elements of the measurement system. Dedicated calibration sites still provide the fundamental service of estimating absolute bias, but also enable long-term monitoring of the sea-surface height and constituent measurements. The use of a network of island and coastal tide gauges has provided the best perspective on the measurement stability, and revealed temporal variations of altimeter measurement system drift. The cross-calibration between successive missions provided fundamentally new information on the performance of altimetry systems. Spatially and temporally correlated errors pose challenges for future missions, underscoring the importance of cross-calibration of new measurements against the established record.

Equations based on anthropometry to predict body fat measured by absorptiometry in schoolchildren and adolescents.

PubMed

Ortiz-Hernández, Luis; Vega López, A Valeria; Ramos-Ibáñez, Norma; Cázares Lara, L Joana; Medina Gómez, R Joab; Pérez-Salgado, Diana

To develop and validate equations to estimate the percentage of body fat of children and adolescents from Mexico using anthropometric measurements. A cross-sectional study was carried out with 601 children and adolescents from Mexico aged 5-19 years. The participants were randomly divided into the following two groups: the development sample (n=398) and the validation sample (n=203). The validity of previously published equations (e.g., Slaughter) was also assessed. The percentage of body fat was estimated by dual-energy X-ray absorptiometry. The anthropometric measurements included height, sitting height, weight, waist and arm circumferences, skinfolds (triceps, biceps, subscapular, supra-iliac, and calf), and elbow and bitrochanteric breadth. Linear regression models were estimated with the percentage of body fat as the dependent variable and the anthropometric measurements as the independent variables. Equations were created based on combinations of six to nine anthropometric variables and had coefficients of determination (r 2 ) equal to or higher than 92.4% for boys and 85.8% for girls. In the validation sample, the developed equations had high r 2 values (≥85.6% in boys and ≥78.1% in girls) in all age groups, low standard errors (SE≤3.05% in boys and ≤3.52% in girls), and the intercepts were not different from the origin (p>0.050). Using the previously published equations, the coefficients of determination were lower, and/or the intercepts were different from the origin. The equations developed in this study can be used to assess the percentage of body fat of Mexican schoolchildren and adolescents, as they demonstrate greater validity and lower error compared with previously published equations. Copyright © 2017 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Quantitative determination and classification of energy drinks using near-infrared spectroscopy.

PubMed

Rácz, Anita; Héberger, Károly; Fodor, Marietta

2016-09-01

Almost a hundred commercially available energy drink samples from Hungary, Slovakia, and Greece were collected for the quantitative determination of their caffeine and sugar content with FT-NIR spectroscopy and high-performance liquid chromatography (HPLC). Calibration models were built with partial least-squares regression (PLSR). An HPLC-UV method was used to measure the reference values for caffeine content, while sugar contents were measured with the Schoorl method. Both the nominal sugar content (as indicated on the cans) and the measured sugar concentration were used as references. Although the Schoorl method has larger error and bias, appropriate models could be developed using both references. The validation of the models was based on sevenfold cross-validation and external validation. FT-NIR analysis is a good candidate to replace the HPLC-UV method, because it is much cheaper than any chromatographic method, while it is also more time-efficient. The combination of FT-NIR with multidimensional chemometric techniques like PLSR can be a good option for the detection of low caffeine concentrations in energy drinks. Moreover, three types of energy drinks that contain (i) taurine, (ii) arginine, and (iii) none of these two components were classified correctly using principal component analysis and linear discriminant analysis. Such classifications are important for the detection of adulterated samples and for quality control, as well. In this case, more than a hundred samples were used for the evaluation. The classification was validated with cross-validation and several randomization tests (X-scrambling). Graphical Abstract The way of energy drinks from cans to appropriate chemometric models.

Translation, cross-cultural adaptation and validation of the Brazilian version of the Nonarthritic Hip Score.

PubMed

Del Castillo, Letícia Nunes Carreras; Leporace, Gustavo; Cardinot, Themis Moura; Levy, Roger Abramino; Oliveira, Liszt Palmeira de

2013-01-01

CONTEXT AND OBJECTIVE The Nonarthritic Hip Score (NAHS) is a clinical evaluation questionnaire that was developed in the English language to evaluate hip function in young and physically active patients. The aims of this study were to translate this questionnaire into the Brazilian Portuguese language, to adapt it to Brazilian culture and to validate it. DESIGN AND SETTING Cohort study conducted between 2008 and 2010, at Universidade do Estado do Rio de Janeiro (UERJ). METHODS Questions about physical activities and household chores were modified to better fit Brazilian culture. Reproducibility, internal consistency and validity (correlations with the Algofunctional Lequesne Index and the Western Ontario and McMaster Universities Arthritis Index [WOMAC]) were tested. The NAHS-Brazil, Lequesne and WOMAC questionnaires were applied to 64 young and physically active patients (mean age, 40.9 years; 31 women). RESULTS The intraclass correlation coefficient (which measures reproducibility) was 0.837 (P < 0.001). Bland-Altman plots revealed a mean error in the difference between the two measurements of 0.42. The internal consistency was confirmed through a Cronbach alpha of 0.944. The validity between NAHS-Brazil and Lequesne and between NAHS-Brazil and WOMAC showed high correlations, r = 0.7340 and r = 0.9073, respectively. NAHS-Brazil showed good validity with no floor or ceiling effects. CONCLUSION The NAHS was translated into the Brazilian Portuguese language and was cross-culturally adapted to Brazilian culture. It was shown to be a useful tool in clinical practice for assessing the quality of life of young and physically active patients with hip pain.

Application of the Safety Attitudes Questionnaire (SAQ) in Albanian hospitals: a cross-sectional study.

PubMed

Gabrani, Adriatik; Hoxha, Adrian; Simaku, Artan; Gabrani, Jonila Cyco

2015-04-15

To establish the reliability and validity of the translated version of the Safety Attitudes Questionnaire (SAQ) by evaluating its psychometric properties and to determine possible differences among nurses and physicians regarding safety attitudes. A cross-sectional study utilising the Albanian version of the SAQ and a demographic questionnaire. Four regional hospitals in Albania. 341 healthcare providers, including 132 nurses and 209 doctors. The translation, construct validity and internal validity of the SAQ. The SAQ includes six scales and 30 items. A total of 341 valid questionnaires were returned, for a response rate of 70%. The confirmatory factor analysis and its goodness-of-fit indices (standardised root mean square residual 0.075, root mean square error of approximation 0.044 and comparative fit index 0.97) showed good model fit. The Cronbach's α values for each of the scales of the SAQ ranged from 0.64 to 0.82. The percentage of hospital healthcare workers who had a positive attitude was 60.3% for the teamwork climate, 57.2% for the safety climate, 58.4% for job satisfaction, 37.4% for stress recognition, 59.3% for the perception of management and 49.5% for working conditions. Intercorrelations showed that the subscales had moderate-to-high correlations with one another. Nurses were more hesitant to admit and report errors; only 55% of physicians and 44% of nurses endorsed this statement (χ(2)=4.9, p=0.02). Moreover, nurses received lower scores on team work compared with doctors (N 45.7 vs D 52.3, p=0.01). Doctors denied the effects of stress and fatigue on their performance (N 46.7 vs D 39.5, p<0.01), neglecting the workload. The SAQ is a useful tool for evaluating safety attitudes in Albanian hospitals. In light of the health workforce's poor recognition of stress, establishing patient safety programmes should be a priority among policymakers in Albania. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Ozone Profile Retrievals from the OMPS on Suomi NPP

NASA Astrophysics Data System (ADS)

Bak, J.; Liu, X.; Kim, J. H.; Haffner, D. P.; Chance, K.; Yang, K.; Sun, K.; Gonzalez Abad, G.

2017-12-01

We verify and correct the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) L1B v2.0 data with the aim of producing accurate ozone profile retrievals using an optimal estimation based inversion method in the 302.5-340 nm fitting. The evaluation of available slit functions demonstrates that preflight-measured slit functions well represent OMPS measurements compared to derived Gaussian slit functions. Our OMPS fitting residuals contain significant wavelength and cross-track dependent biases, and thereby serious cross-track striping errors are found in preliminary retrievals, especially in the troposphere. To eliminate the systematic component of the fitting residuals, we apply "soft calibration" to OMPS radiances. With the soft calibration the amplitude of fitting residuals decreases from 1 % to 0.2 % over low/mid latitudes, and thereby the consistency of tropospheric ozone retrievals between OMPS and Ozone Monitoring Instrument (OMI) are substantially improved. A common mode correction is implemented for additional radiometric calibration, which improves retrievals especially at high latitudes where the amplitude of fitting residuals decreases by a factor of 2. We estimate the floor noise error of OMPS measurements from standard deviations of the fitting residuals. The derived error in the Huggins band ( 0.1 %) is 2 times smaller than OMI floor noise error and 2 times larger than OMPS L1B measurement error. The OMPS floor noise errors better constrain our retrievals for maximizing measurement information and stabilizing our fitting residuals. The final precision of the fitting residuals is less than 0.1 % in the low/mid latitude, with 1 degrees of freedom for signal for the tropospheric ozone, so that we meet the general requirements for successful tropospheric ozone retrievals. To assess if the quality of OMPS ozone retrievals could be acceptable for scientific use, we will characterize OMPS ozone profile retrievals, present error analysis, and validate retrievals using a reference dataset. The useful information on the vertical distribution of ozone is limited below 40 km only from OMPS NM measurements due to the absence of Hartley ozone wavelength. This shortcoming will be improved with the joint ozone profile retrieval using Nadir Profiler (NP) measurements covering the 250 to 310 nm range.

Content Validity of a Tool Measuring Medication Errors.

PubMed

Tabassum, Nishat; Allana, Saleema; Saeed, Tanveer; Dias, Jacqueline Maria

2015-08-01

The objective of this study was to determine content and face validity of a tool measuring medication errors among nursing students in baccalaureate nursing education. Data was collected from the Aga Khan University School of Nursing and Midwifery (AKUSoNaM), Karachi, from March to August 2014. The tool was developed utilizing literature and the expertise of the team members, expert in different areas. The developed tool was then sent to five experts from all over Karachi for ensuring the content validity of the tool, which was measured on relevance and clarity of the questions. The Scale Content Validity Index (S-CVI) for clarity and relevance of the questions was found to be 0.94 and 0.98, respectively. The tool measuring medication errors has an excellent content validity. This tool should be used for future studies on medication errors, with different study populations such as medical students, doctors, and nurses.

Construct Validity of the Societal Outreach Scale (SOS).

PubMed

Fike, David S; Denton, Jason; Walk, Matt; Kish, Jennifer; Gorman, Ira

2018-04-01

The American Physical Therapy Association (APTA) has been working toward a vision of increasing professional focus on societal-level health. However, performance of social responsibility and related behaviors by physical therapists remain relatively poorly integrated into practice. Promoting a focus on societal outreach is necessary for all health care professionals to impact the health of their communities. The objective was to document the validity of the 14-item Societal Outreach Scale (SOS) for use with practicing physical therapists. This study used a cross-sectional survey. The SOS was transmitted via email to all therapists who were licensed and practicing in 10 states in the United States that were purposefully selected to assure a broad representation. A sample of 2612 usable responses was received. Factor analysis was applied to assess construct validity of the instrument. Of alternate models, a 3-factor model best demonstrated goodness of fit with the sample data according to conventional indices (standardized root mean squared residual = .03, comparative fit index .96, root mean square error of approximation = .06). The 3 factors measured by the SOS were labeled Societal-Level Health Advocacy, Community Engagement/Social Integration, and Political Engagement. Internal consistency reliability was 0.7 for all factors. The 3-factor SOS demonstrated acceptable validity and reliability. Though the sample included a broad representation of physical therapists, this was a single cross-sectional study. Additional confirmatory factor analysis, reliability testing, and word refinement of the tool are warranted. Given the construct validity and reliability of the 3-factor SOS, it is recommended for use as a validated instrument to measure physical therapists' performance of social responsibility and related behaviors.

Global Precipitation Measurement (GPM) Ground Validation: Plans and Preparations

NASA Technical Reports Server (NTRS)

Schwaller, M.; Bidwell, S.; Durning, F. J.; Smith, E.

2004-01-01

The Global Precipitation Measurement (GPM) program is an international partnership led by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM will improve climate, weather, and hydro-meteorological forecasts through more frequent and more accurate measurement of precipitation across the globe. This paper describes the concept, the planning, and the preparations for Ground Validation within the GPM program. Ground Validation (GV) plays an important role in the program by investigating and quantitatively assessing the errors within the satellite retrievals. These quantitative estimates of retrieval errors will assist the scientific community by bounding the errors within their research products. The two fundamental requirements of the GPM Ground Validation program are: (1) error characterization of the precipitation retrievals and (2) continual improvement of the satellite retrieval algorithms. These two driving requirements determine the measurements, instrumentation, and location for ground observations. This paper outlines GV plans for estimating the systematic and random components of retrieval error and for characterizing the spatial p d temporal structure of the error and plans for algorithm improvement in which error models are developed and experimentally explored to uncover the physical causes of errors within the retrievals. This paper discusses NASA locations for GV measurements as well as anticipated locations from international GPM partners. NASA's primary locations for validation measurements are an oceanic site at Kwajalein Atoll in the Republic of the Marshall Islands and a continental site in north-central Oklahoma at the U.S. Department of Energy's Atmospheric Radiation Measurement Program site.

Assessing the Online Social Environment for Surveillance of Obesity Prevalence

PubMed Central

Chunara, Rumi; Bouton, Lindsay; Ayers, John W.; Brownstein, John S.

2013-01-01

Background Understanding the social environmental around obesity has been limited by available data. One promising approach used to bridge similar gaps elsewhere is to use passively generated digital data. Purpose This article explores the relationship between online social environment via web-based social networks and population obesity prevalence. Methods We performed a cross-sectional study using linear regression and cross validation to measure the relationship and predictive performance of user interests on the online social network Facebook to obesity prevalence in metros across the United States of America (USA) and neighborhoods within New York City (NYC). The outcomes, proportion of obese and/or overweight population in USA metros and NYC neighborhoods, were obtained via the Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance and NYC EpiQuery systems. Predictors were geographically specific proportion of users with activity-related and sedentary-related interests on Facebook. Results Higher proportion of the population with activity-related interests on Facebook was associated with a significant 12.0% (95% Confidence Interval (CI) 11.9 to 12.1) lower predicted prevalence of obese and/or overweight people across USA metros and 7.2% (95% CI: 6.8 to 7.7) across NYC neighborhoods. Conversely, greater proportion of the population with interest in television was associated with higher prevalence of obese and/or overweight people of 3.9% (95% CI: 3.7 to 4.0) (USA) and 27.5% (95% CI: 27.1 to 27.9, significant) (NYC). For activity-interests and national obesity outcomes, the average root mean square prediction error from 10-fold cross validation was comparable to the average root mean square error of a model developed using the entire data set. Conclusions Activity-related interests across the USA and sedentary-related interests across NYC were significantly associated with obesity prevalence. Further research is needed to understand how the online social environment relates to health outcomes and how it can be used to identify or target interventions. PMID:23637820

Heterogeneous sharpness for cross-spectral face recognition

NASA Astrophysics Data System (ADS)

Cao, Zhicheng; Schmid, Natalia A.

2017-05-01

Matching images acquired in different electromagnetic bands remains a challenging problem. An example of this type of comparison is matching active or passive infrared (IR) against a gallery of visible face images, known as cross-spectral face recognition. Among many unsolved issues is the one of quality disparity of the heterogeneous images. Images acquired in different spectral bands are of unequal image quality due to distinct imaging mechanism, standoff distances, or imaging environment, etc. To reduce the effect of quality disparity on the recognition performance, one can manipulate images to either improve the quality of poor-quality images or to degrade the high-quality images to the level of the quality of their heterogeneous counterparts. To estimate the level of discrepancy in quality of two heterogeneous images a quality metric such as image sharpness is needed. It provides a guidance in how much quality improvement or degradation is appropriate. In this work we consider sharpness as a relative measure of heterogeneous image quality. We propose a generalized definition of sharpness by first achieving image quality parity and then finding and building a relationship between the image quality of two heterogeneous images. Therefore, the new sharpness metric is named heterogeneous sharpness. Image quality parity is achieved by experimentally finding the optimal cross-spectral face recognition performance where quality of the heterogeneous images is varied using a Gaussian smoothing function with different standard deviation. This relationship is established using two models; one of them involves a regression model and the other involves a neural network. To train, test and validate the model, we use composite operators developed in our lab to extract features from heterogeneous face images and use the sharpness metric to evaluate the face image quality within each band. Images from three different spectral bands visible light, near infrared, and short-wave infrared are considered in this work. Both error of a regression model and validation error of a neural network are analyzed.

Extensive validation of the pain disability index in 3 groups of patients with musculoskeletal pain.

PubMed

Soer, Remko; Köke, Albère J A; Vroomen, Patrick C A J; Stegeman, Patrick; Smeets, Rob J E M; Coppes, Maarten H; Reneman, Michiel F

2013-04-20

A cross-sectional study design was performed. To validate the pain disability index (PDI) extensively in 3 groups of patients with musculoskeletal pain. The PDI is a widely used and studied instrument for disability related to various pain syndromes, although there is conflicting evidence concerning factor structure, test-retest reliability, and missing items. Additionally, an official translation of the Dutch language version has never been performed. For reliability, internal consistency, factor structure, test-retest reliability and measurement error were calculated. Validity was tested with hypothesized correlations with pain intensity, kinesiophobia, Rand-36 subscales, Depression, Roland-Morris Disability Questionnaire, Quality of Life, and Work Status. Structural validity was tested with independent backward translation and approval from the original authors. One hundred seventy-eight patients with acute back pain, 425 patients with chronic low back pain and 365 with widespread pain were included. Internal consistency of the PDI was good. One factor was identified with factor analyses. Test-retest reliability was good for the PDI (intraclass correlation coefficient, 0.76). Standard error of measurement was 6.5 points and smallest detectable change was 17.9 points. Little correlations between the PDI were observed with kinesiophobia and depression, fair correlations with pain intensity, work status, and vitality and moderate correlations with the Rand-36 subscales and the Roland-Morris Disability Questionnaire. The PDI-Dutch language version is internally consistent as a 1-factor structure, and test-retest reliable. Missing items seem high in sexual and professional items. Using the PDI as a 2-factor questionnaire has no additional value and is unreliable.

Total absorption cross sections of several gases of aeronomic interest at 584 A.

NASA Technical Reports Server (NTRS)

Starr, W. L.; Loewenstein, M.

1972-01-01

Total photoabsorption cross sections have been measured at 584.3 A for N2, O2, Ar, CO2, CO, NO, N2O, NH3, CH4, H2, and H2S. A monochromator was used to isolate the He I 584 line produced in a helium resonance lamp, and thin aluminum filters were used as absorption cell windows, thereby eliminating possible errors associated with the use of undispersed radiation or windowless cells. Sources of error are examined, and limits of uncertainty are given. Previous relevant cross-sectional measurements and possible error sources are reviewed. Wall adsorption as a source of error in cross-sectional measurements has not previously been considered and is discussed briefly.

Psychometric properties of KIDSCREEN health-related quality of life questionnaire in Iranian adolescents.

PubMed

Parizi, Ahmad Shahabeddin; Garmaroudi, Gholamreza; Fazel, Mojtaba; Omidvari, Sepideh; Azin, Seyed Ali; Montazeri, Ali; Jafarpour, Saba

2014-09-01

Health-related quality of life (HRQOL), which is receiving increasing attention, is a multidimensional concept that encompasses different areas including the physiological, psychological, social, and spiritual aspects of life. The KIDSCREEN-52 questionnaire is designed to measure the HRQOL of 8-18-year-old children and adolescents. The aim of this study was to develop a Persian version of KIDSCREEN-52 and analyze the validity and reliability of the translated version. The KIDSCREEN-52 was translated into Persian in keeping with the international cross-cultural translation guidelines. A cross-sectional study was performed in the city of Tehran during 2012-2013. 328 students ranging in age from 8 to 18 years were enrolled in the study. The reliability for each dimension was estimated using Cronbach's alpha coefficient. To examine the validity of the questionnaire, a confirmatory factor analysis (CFA) was conducted. The Cronbach's alpha coefficient was higher than 0.7 in all ten dimensions except self-perception. Validity of this questionnaire was confirmed by CFA. (Relative chi square (χ (2)/df) = 1.73; root-mean-square error of approximation = 0.047; normed fit index = 0.93; Tucker-Lewis index = 0.97; comparative fit index = 0.97; and relative fit index = 0.92.) The Persian version of KIDSCREEN-52 is reliable and valid and can be used as a self-administered instrument for measuring HRQOL in children and adolescents in Iran.

A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

Reliability and Construct Validity of Limits of Stability Test in Adolescents Using a Portable Forceplate System.

PubMed

Alsalaheen, Bara; Haines, Jamie; Yorke, Amy; Broglio, Steven P

2015-12-01

To examine the reliability, convergent, and discriminant validity of the limits of stability (LOS) test to assess dynamic postural stability in adolescents using a portable forceplate system. Cross-sectional reliability observational study. School setting. Adolescents (N=36) completed all measures during the first session. To examine the reliability of the LOS test, a subset of 15 participants repeated the LOS test after 1 week. Not applicable. Outcome measurements included the LOS test, Balance Error Scoring System, Instrumented Balance Error Scoring System, and Modified Clinical Test for Sensory Interaction on Balance. A significant relation was observed among LOS composite scores (r=.36-.87, P<.05). However, no relation was observed between LOS and static balance outcome measurements. The reliability of the LOS composite scores ranged from moderate to good (intraclass correlation coefficient model 2,1=.73-.96). The results suggest that the LOS composite scores provide unique information about dynamic postural stability, and the LOS test completed at 100% of the theoretical limit appeared to be a reliable test of dynamic postural stability in adolescents. Clinicians should use dynamic balance measurement as part of their balance assessment and should not use static balance testing (eg, Balance Error Scoring System) to make inferences about dynamic balance, especially when balance assessment is used to determine rehabilitation outcomes, or when making return to play decisions after injury. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Evaluation of speech errors in Putonghua speakers with cleft palate: a critical review of methodology issues.

PubMed

Jiang, Chenghui; Whitehill, Tara L

2014-04-01

Speech errors associated with cleft palate are well established for English and several other Indo-European languages. Few articles describing the speech of Putonghua (standard Mandarin Chinese) speakers with cleft palate have been published in English language journals. Although methodological guidelines have been published for the perceptual speech evaluation of individuals with cleft palate, there has been no critical review of methodological issues in studies of Putonghua speakers with cleft palate. A literature search was conducted to identify relevant studies published over the past 30 years in Chinese language journals. Only studies incorporating perceptual analysis of speech were included. Thirty-seven articles which met inclusion criteria were analyzed and coded on a number of methodological variables. Reliability was established by having all variables recoded for all studies. This critical review identified many methodological issues. These design flaws make it difficult to draw reliable conclusions about characteristic speech errors in this group of speakers. Specific recommendations are made to improve the reliability and validity of future studies, as well to facilitate cross-center comparisons.

A comparison of bootstrap methods and an adjusted bootstrap approach for estimating the prediction error in microarray classification.

PubMed

Jiang, Wenyu; Simon, Richard

2007-12-20

This paper first provides a critical review on some existing methods for estimating the prediction error in classifying microarray data where the number of genes greatly exceeds the number of specimens. Special attention is given to the bootstrap-related methods. When the sample size n is small, we find that all the reviewed methods suffer from either substantial bias or variability. We introduce a repeated leave-one-out bootstrap (RLOOB) method that predicts for each specimen in the sample using bootstrap learning sets of size ln. We then propose an adjusted bootstrap (ABS) method that fits a learning curve to the RLOOB estimates calculated with different bootstrap learning set sizes. The ABS method is robust across the situations we investigate and provides a slightly conservative estimate for the prediction error. Even with small samples, it does not suffer from large upward bias as the leave-one-out bootstrap and the 0.632+ bootstrap, and it does not suffer from large variability as the leave-one-out cross-validation in microarray applications. Copyright (c) 2007 John Wiley & Sons, Ltd.

Pricing and hedging derivative securities with neural networks: Bayesian regularization, early stopping, and bagging.

PubMed

Gençay, R; Qi, M

2001-01-01

We study the effectiveness of cross validation, Bayesian regularization, early stopping, and bagging to mitigate overfitting and improving generalization for pricing and hedging derivative securities with daily S&P 500 index daily call options from January 1988 to December 1993. Our results indicate that Bayesian regularization can generate significantly smaller pricing and delta-hedging errors than the baseline neural-network (NN) model and the Black-Scholes model for some years. While early stopping does not affect the pricing errors, it significantly reduces the hedging error (HE) in four of the six years we investigated. Although computationally most demanding, bagging seems to provide the most accurate pricing and delta hedging. Furthermore, the standard deviation of the MSPE of bagging is far less than that of the baseline model in all six years, and the standard deviation of the average HE of bagging is far less than that of the baseline model in five out of six years. We conclude that they be used at least in cases when no appropriate hints are available.

pKa prediction of monoprotic small molecules the SMARTS way.

PubMed

Lee, Adam C; Yu, Jing-Yu; Crippen, Gordon M

2008-10-01

Realizing favorable absorption, distribution, metabolism, elimination, and toxicity profiles is a necessity due to the high attrition rate of lead compounds in drug development today. The ability to accurately predict bioavailability can help save time and money during the screening and optimization processes. As several robust programs already exist for predicting logP, we have turned our attention to the fast and robust prediction of pK(a) for small molecules. Using curated data from the Beilstein Database and Lange's Handbook of Chemistry, we have created a decision tree based on a novel set of SMARTS strings that can accurately predict the pK(a) for monoprotic compounds with R(2) of 0.94 and root mean squared error of 0.68. Leave-some-out (10%) cross-validation achieved Q(2) of 0.91 and root mean squared error of 0.80.

Determining blood and plasma volumes using bioelectrical response spectroscopy

NASA Technical Reports Server (NTRS)

Siconolfi, S. F.; Nusynowitz, M. L.; Suire, S. S.; Moore, A. D. Jr; Leig, J.

1996-01-01

We hypothesized that an electric field (inductance) produced by charged blood components passing through the many branches of arteries and veins could assess total blood volume (TBV) or plasma volume (PV). Individual (N = 29) electrical circuits (inductors, two resistors, and a capacitor) were determined from bioelectrical response spectroscopy (BERS) using a Hewlett Packard 4284A Precision LCR Meter. Inductance, capacitance, and resistance from the circuits of 19 subjects modeled TBV (sum of PV and computed red cell volume) and PV (based on 125I-albumin). Each model (N = 10, cross validation group) had good validity based on 1) mean differences (-2.3 to 1.5%) between the methods that were not significant and less than the propagated errors (+/- 5.2% for TBV and PV), 2) high correlations (r > 0.92) with low SEE (< 7.7%) between dilution and BERS assessments, and 3) Bland-Altman pairwise comparisons that indicated "clinical equivalency" between the methods. Given the limitation of this study (10 validity subjects), we concluded that BERS models accurately assessed TBV and PV. Further evaluations of the models' validities are needed before they are used in clinical or research settings.

Rapid determination of Swiss cheese composition by Fourier transform infrared/attenuated total reflectance spectroscopy.

PubMed

Rodriguez-Saona, L E; Koca, N; Harper, W J; Alvarez, V B

2006-05-01

There is a need for rapid and simple techniques that can be used to predict the quality of cheese. The aim of this research was to develop a simple and rapid screening tool for monitoring Swiss cheese composition by using Fourier transform infrared spectroscopy. Twenty Swiss cheese samples from different manufacturers and degree of maturity were evaluated. Direct measurements of Swiss cheese slices (approximately 0.5 g) were made using a MIRacle 3-reflection diamond attenuated total reflectance (ATR) accessory. Reference methods for moisture (vacuum oven), protein content (Kjeldahl), and fat (Babcock) were used. Calibration models were developed based on a cross-validated (leave-one-out approach) partial least squares regression. The information-rich infrared spectral range for Swiss cheese samples was from 3,000 to 2,800 cm(-1) and 1,800 to 900 cm(-1). The performance statistics for cross-validated models gave estimates for standard error of cross-validation of 0.45, 0.25, and 0.21% for moisture, protein, and fat respectively, and correlation coefficients r > 0.96. Furthermore, the ATR infrared protocol allowed for the classification of cheeses according to manufacturer and aging based on unique spectral information, especially of carbonyl groups, probably due to their distinctive lipid composition. Attenuated total reflectance infrared spectroscopy allowed for the rapid (approximately 3-min analysis time) and accurate analysis of the composition of Swiss cheese. This technique could contribute to the development of simple and rapid protocols for monitoring complex biochemical changes, and predicting the final quality of the cheese.

Reliability and validity of the cross-culturally adapted Turkish version of the Core Outcome Measures Index for low back pain.

PubMed

Çetin, Engin; Çelik, Evrim Coşkun; Acaroğlu, Emre; Berk, Haluk

2018-01-01

To produce a cross-culturally adapted and validated Turkish version of The Core Outcome Measure Index (COMI) Back questionnaire. Ninety-six Turkish-speaking patients with non-specific low back pain (LBP) were recruited from orthopedic and physical therapy outpatient clinics in a public hospital. They completed a booklet of questionnaires containing Turkish version of COMI, adjectival pain scale, Roland Morris disability questionnaire, European 5 Dimension Questionnaire and brief version of World Health Organization Quality of Life Questionnaire. Within following 7-14 days, 67 patients, reported no or minimal changes in their back pain status, completed the Turkish COMI again to assess reproducibility. Data quality was good with very few missing answers. COMI summary index score displayed 3% floor effects and no ceiling effects. The correlations between the COMI summary index score and each of the full instrument whole scores were found to be excellent to very good (ρ = - 0.81 to 0.74). Reliability expressed as intraclass correlation coefficient (ICC) was 0.95 (95% CI 0.91-0.97). Standard error of measurement (SEM agreement ) was acceptable at 0.41 and the minimum detectable change (MDC 95% ) was 1.14. Turkish version of the COMI has acceptable psychometric properties. It is a valid and reliable instrument and cross-culturally adapted, in accordance with established guidelines, for the use by Turkish-speaking patients. It can be recommended for use in evaluation of patients with chronic LBP in daily practice, in international multicenter studies and in spine registry systems.

Nutritional evaluation of commercial dry dog foods by near infrared reflectance spectroscopy.

PubMed

Alomar, D; Hodgkinson, S; Abarzúa, D; Fuchslocher, R; Alvarado, C; Rosales, E

2006-06-01

Near infrared reflectance spectroscopy (NIRS) was used to predict the nutritional value of dog foods sold in Chile. Fifty-nine dry foods for adult and growing dogs were collected, ground and scanned across the visible/NIR range and subsequently analysed for dry matter (DM), crude protein (CP), crude fibre (CF), total fat, linoleic acid, gross energy (GE), estimated metabolizable energy (ME) and several amino acids and minerals. Calibration equations were developed by modified partial least squares regression, and tested by cross-validation. Standard error of cross validation (SE(CV)) and coefficient of determination of cross validation (SE(CV)) were used to select best equations. Equations with good predicting accuracy were obtained for DM, CF, CP, GE and fat. Corresponding values for and SE(CV) were 0.96 and 1.7 g/kg, 0.91 and 3.1 g/kg, 0.99 and 5.0 g/kg, 0.93 and 0.26 MJ/kg, 0.89 and 12.4 g/kg. Several amino acids were also well predicted, such as arginine, leucine, isoleucine, phenylalanine-tyrosine (combined), threonine and valine, with values for and SE(CV) (g/kg) of 0.89 and 0.9, 0.94 and 1.3, 0.91 and 0.5, 0.95 and 0.9, 0.91 and 0.5, 0.93 and 0.5. Intermediate values, appropriate for ranking purposes, were obtained for ME, histidine, lysine and methionine-cysteine. Tryptophan, minerals or linoleic acid were not acceptably predicted, irrespective of the mathematical treatment applied. It is concluded that NIR can be successfully used to predict important nutritional characteristics of commercial dog foods.

Cross-Cultural Adaptation of the Male Genital Self-Image Scale in Iranian Men.

PubMed

Saffari, Mohsen; Pakpour, Amir H; Burri, Andrea

2016-03-01

Certain sexual health problems in men can be attributed to genital self-image. Therefore, a culturally adapted version of a Male Genital Self-Image Scale (MGSIS) could help health professionals understand this concept and its associated correlates. To translate the original English version of the MGSIS into Persian and to assess the psychometric properties of this culturally adapted version (MGSIS-I) for use in Iranian men. In total, 1,784 men were recruited for this cross-sectional study. Backward and forward translations of the MGSIS were used to produce the culturally adapted version. Reliability of the MGSIS-I was assessed using Cronbach α and intra-class correlation coefficients. Divergent and convergent validities were examined using Pearson correlation and known-group validity was assessed in subgroups of participants with different sociodemographic statuses. Factor validity of the scale was investigated using exploratory and confirmatory factor analyses. Demographic information, the International Index of Erectile Function, the Body Appreciation Scale, the Rosenberg Self-Esteem Scale, and the MGSIS. Mean age of participants was 38.13 years (SD = 11.45) and all men were married. Cronbach α of the MGSIS-I was 0.89 and interclass correlation coefficients ranged from 0.70 to 0.94. Significant correlations were found between the MGSIS-I and the International Index of Erectile Function (P < .01), whereas correlation of the scale with non-similar scales was lower than with similar scale (confirming convergent and divergent validity). The scale could differentiate between subgroups in age, smoking status, and income (known-group validity). A single-factor solution that explained 70% variance of the scale was explored using exploratory factor analysis (confirming uni-dimensionality); confirmatory factor analysis indicated better fitness for the five-item version than the seven-item version of the MGSIS-I (root mean square error of approximation = 0.05, comparative fit index > 1.00 vs root mean square error of approximation = 0.10, comparative fit index > 0.97, respectively). The MGSIS-I is a useful instrument to assess genital self-image in Iranian men, a concept that has been associated with sexual function. Further investigation is needed to identify the applicability of the scale in other cultures or populations. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Cross-cultural adaptation and validation of the Norwegian pain catastrophizing scale in patients with low back pain.

PubMed

Fernandes, Linda; Storheim, Kjersti; Lochting, Ida; Grotle, Margreth

2012-06-22

Pain catastrophizing has been found to be an important predictor of disability and days lost from work in patients with low back pain. The most commonly used outcome measure to identify pain catastrophizing is the Pain Catastrophizing Scale (PCS). To enable the use of the PCS in clinical settings and research in Norwegian speaking patients, the PCS had to be translated. The purpose of this study was therefore to translate and cross-culturally adapt the PCS into Norwegian and to test internal consistency, construct validity and reproducibility of the PCS. The PCS was translated before it was tested for psychometric properties. Patients with subacute or chronic non-specific low back pain aged 18 years or more were recruited from primary and secondary care. Validity of the PCS was assessed by evaluating data quality (missing, floor and ceiling effects), principal components analysis, internal consistency (Cronbach's alpha), and construct validity (Spearman's rho). Reproducibility analyses included standard error of measurement, minimum detectable change, limits of agreement, and intraclass correlation coefficients. A total of 38 men and 52 women (n = 90), with a mean (SD) age of 47.6 (11.7) years, were included for baseline testing. A subgroup of 61 patients was included for test-retest assessments. The Norwegian PCS was easy-to-comprehend. The principal components analysis supported a three-factor structure, internal consistency was satisfactory for the PCS total score (α 0.90) and the subscales rumination (α 0.83) and helplessness (α 0.86), but not for the subscale magnification (α 0.53). In total, 86% of the correlation analyses were in accordance with predefined hypothesis. The reliability analyses showed intraclass correlation coefficients of 0.74 - 0.87 for the PCS total score and subscales. The PCS total score (range 0-52 points) showed a standard error of measurement of 4.6 points and a 95% minimum detectable change estimate of 12.8 points. The Norwegian PCS total score showed acceptable psychometric properties in terms of comprehensibility, consistency, construct validity, and reproducibility when applied to patients with subacute or chronic LBP from different clinical settings. Our study support the use of the PCS total score for clinical or research purposes identifying or evaluating pain catastrophizing.

Exposure Measurement Error in PM2.5 Health Effects Studies: A Pooled Analysis of Eight Personal Exposure Validation Studies

EPA Science Inventory

Background: Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typ...

Factor structure and psychometric properties of the Fertility Problem Inventory–Short Form

PubMed Central

Zurlo, Maria Clelia; Cattaneo Della Volta, Maria Franscesca; Vallone, Federica

2017-01-01

The study analyses factor structure and psychometric properties of the Italian version of the Fertility Problem Inventory–Short Form. A sample of 206 infertile couples completed the Italian version of Fertility Problem Inventory (46 items) with demographics, State Anxiety Scale of State-Trait Anxiety Inventory (Form Y), Edinburgh Depression Scale and Dyadic Adjustment Scale, used to assess convergent and discriminant validity. Confirmatory factor analysis was unsatisfactory (comparative fit index = 0.87; Tucker-Lewis Index = 0.83; root mean square error of approximation = 0.17), and Cronbach’s α (0.95) revealed a redundancy of items. Exploratory factor analysis was carried out deleting cross-loading items, and Mokken scale analysis was applied to verify the items homogeneity within the reduced subscales of the questionnaire. The Fertility Problem Inventory–Short Form consists of 27 items, tapping four meaningful and reliable factors. Convergent and discriminant validity were confirmed. Findings indicated that the Fertility Problem Inventory–Short Form is a valid and reliable measure to assess infertility-related stress dimensions. PMID:29379625

Source Attribution of Cyanides Using Anionic Impurity Profiling, Stable Isotope Ratios, Trace Elemental Analysis and Chemometrics.

PubMed

Mirjankar, Nikhil S; Fraga, Carlos G; Carman, April J; Moran, James J

2016-02-02

Chemical attribution signatures (CAS) for chemical threat agents (CTAs), such as cyanides, are being investigated to provide an evidentiary link between CTAs and specific sources to support criminal investigations and prosecutions. Herein, stocks of KCN and NaCN were analyzed for trace anions by high performance ion chromatography (HPIC), carbon stable isotope ratio (δ(13)C) by isotope ratio mass spectrometry (IRMS), and trace elements by inductively coupled plasma optical emission spectroscopy (ICP-OES). The collected analytical data were evaluated using hierarchical cluster analysis (HCA), Fisher-ratio (F-ratio), interval partial least-squares (iPLS), genetic algorithm-based partial least-squares (GAPLS), partial least-squares discriminant analysis (PLSDA), K nearest neighbors (KNN), and support vector machines discriminant analysis (SVMDA). HCA of anion impurity profiles from multiple cyanide stocks from six reported countries of origin resulted in cyanide samples clustering into three groups, independent of the associated alkali metal (K or Na). The three groups were independently corroborated by HCA of cyanide elemental profiles and corresponded to countries each having one known solid cyanide factory: Czech Republic, Germany, and United States. Carbon stable isotope measurements resulted in two clusters: Germany and United States (the single Czech stock grouped with United States stocks). Classification errors for two validation studies using anion impurity profiles collected over five years on different instruments were as low as zero for KNN and SVMDA, demonstrating the excellent reliability associated with using anion impurities for matching a cyanide sample to its factory using our current cyanide stocks. Variable selection methods reduced errors for those classification methods having errors greater than zero; iPLS-forward selection and F-ratio typically provided the lowest errors. Finally, using anion profiles to classify cyanides to a specific stock or stock group for a subset of United States stocks resulted in cross-validation errors ranging from 0 to 5.3%.

Validation of the Malay version of the Inventory of Functional Status after Childbirth questionnaire.

PubMed

Noor, Norhayati Mohd; Aziz, Aniza Abd; Mostapa, Mohd Rosmizaki; Awang, Zainudin

2015-01-01

This study was designed to examine the psychometric properties of Malay version of the Inventory of Functional Status after Childbirth (IFSAC). A cross-sectional study. A total of 108 postpartum mothers attending Obstetrics and Gynaecology Clinic, in a tertiary teaching hospital in Malaysia, were involved. Construct validity and internal consistency were performed after the translation, content validity, and face validity process. The data were analyzed using Analysis of Moment Structure version 18 and Statistical Packages for the Social Sciences version 20. The final model consists of four constructs, namely, infant care, personal care, household activities, and social and community activities, with 18 items demonstrating acceptable factor loadings, domain to domain correlation, and best fit (Chi-squared/degree of freedom = 1.678; Tucker-Lewis index = 0.923; comparative fit index = 0.936; and root mean square error of approximation = 0.080). Composite reliability and average variance extracted of the domains ranged from 0.659 to 0.921 and from 0.499 to 0.628, respectively. The study suggested that the four-factor model with 18 items of the Malay version of IFSAC was acceptable to be used to measure functional status after childbirth because it is valid, reliable, and simple.

Parametric bicubic spline and CAD tools for complex targets shape modelling in physical optics radar cross section prediction

NASA Astrophysics Data System (ADS)

Delogu, A.; Furini, F.

1991-09-01

Increasing interest in radar cross section (RCS) reduction is placing new demands on theoretical, computation, and graphic techniques for calculating scattering properties of complex targets. In particular, computer codes capable of predicting the RCS of an entire aircraft at high frequency and of achieving RCS control with modest structural changes, are becoming of paramount importance in stealth design. A computer code, evaluating the RCS of arbitrary shaped metallic objects that are computer aided design (CAD) generated, and its validation with measurements carried out using ALENIA RCS test facilities are presented. The code, based on the physical optics method, is characterized by an efficient integration algorithm with error control, in order to contain the computer time within acceptable limits, and by an accurate parametric representation of the target surface in terms of bicubic splines.

Quadrant photodetector sensitivity.

PubMed

Manojlović, Lazo M

2011-07-10

A quantitative theoretical analysis of the quadrant photodetector (QPD) sensitivity in position measurement is presented. The Gaussian light spot irradiance distribution on the QPD surface was assumed to meet most of the real-life applications of this sensor. As the result of the mathematical treatment of the problem, we obtained, in a closed form, the sensitivity function versus the ratio of the light spot 1/e radius and the QPD radius. The obtained result is valid for the full range of the ratios. To check the influence of the finite light spot radius on the interaxis cross talk and linearity, we also performed a mathematical analysis to quantitatively measure these types of errors. An optimal range of the ratio of light spot radius and QPD radius has been found to simultaneously achieve low interaxis cross talk and high linearity of the sensor. © 2011 Optical Society of America

Criterion and Concurrent Validity of the activPAL™ Professional Physical Activity Monitor in Adolescent Females

PubMed Central

Dowd, Kieran P.; Harrington, Deirdre M.; Donnelly, Alan E.

2012-01-01

Background The activPAL has been identified as an accurate and reliable measure of sedentary behaviour. However, only limited information is available on the accuracy of the activPAL activity count function as a measure of physical activity, while no unit calibration of the activPAL has been completed to date. This study aimed to investigate the criterion validity of the activPAL, examine the concurrent validity of the activPAL, and perform and validate a value calibration of the activPAL in an adolescent female population. The performance of the activPAL in estimating posture was also compared with sedentary thresholds used with the ActiGraph accelerometer. Methodologies Thirty adolescent females (15 developmental; 15 cross-validation) aged 15–18 years performed 5 activities while wearing the activPAL, ActiGraph GT3X, and the Cosmed K4B2. A random coefficient statistics model examined the relationship between metabolic equivalent (MET) values and activPAL counts. Receiver operating characteristic analysis was used to determine activity thresholds and for cross-validation. The random coefficient statistics model showed a concordance correlation coefficient of 0.93 (standard error of the estimate = 1.13). An optimal moderate threshold of 2997 was determined using mixed regression, while an optimal vigorous threshold of 8229 was determined using receiver operating statistics. The activPAL count function demonstrated very high concurrent validity (r = 0.96, p<0.01) with the ActiGraph count function. Levels of agreement for sitting, standing, and stepping between direct observation and the activPAL and ActiGraph were 100%, 98.1%, 99.2% and 100%, 0%, 100%, respectively. Conclusions These findings suggest that the activPAL is a valid, objective measurement tool that can be used for both the measurement of physical activity and sedentary behaviours in an adolescent female population. PMID:23094069

Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle.

PubMed

Ruuska, Salla; Hämäläinen, Wilhelmiina; Kajava, Sari; Mughal, Mikaela; Matilainen, Pekka; Mononen, Jaakko

2018-03-01

The aim of the present study was to evaluate empirically confusion matrices in device validation. We compared the confusion matrix method to linear regression and error indices in the validation of a device measuring feeding behaviour of dairy cattle. In addition, we studied how to extract additional information on classification errors with confusion probabilities. The data consisted of 12 h behaviour measurements from five dairy cows; feeding and other behaviour were detected simultaneously with a device and from video recordings. The resulting 216 000 pairs of classifications were used to construct confusion matrices and calculate performance measures. In addition, hourly durations of each behaviour were calculated and the accuracy of measurements was evaluated with linear regression and error indices. All three validation methods agreed when the behaviour was detected very accurately or inaccurately. Otherwise, in the intermediate cases, the confusion matrix method and error indices produced relatively concordant results, but the linear regression method often disagreed with them. Our study supports the use of confusion matrix analysis in validation since it is robust to any data distribution and type of relationship, it makes a stringent evaluation of validity, and it offers extra information on the type and sources of errors. Copyright © 2018 Elsevier B.V. All rights reserved.

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

Factors That Affect Large Subunit Ribosomal DNA Amplicon Sequencing Studies of Fungal Communities: Classification Method, Primer Choice, and Error

PubMed Central

Porter, Teresita M.; Golding, G. Brian

2012-01-01

Nuclear large subunit ribosomal DNA is widely used in fungal phylogenetics and to an increasing extent also amplicon-based environmental sequencing. The relatively short reads produced by next-generation sequencing, however, makes primer choice and sequence error important variables for obtaining accurate taxonomic classifications. In this simulation study we tested the performance of three classification methods: 1) a similarity-based method (BLAST + Metagenomic Analyzer, MEGAN); 2) a composition-based method (Ribosomal Database Project naïve Bayesian classifier, NBC); and, 3) a phylogeny-based method (Statistical Assignment Package, SAP). We also tested the effects of sequence length, primer choice, and sequence error on classification accuracy and perceived community composition. Using a leave-one-out cross validation approach, results for classifications to the genus rank were as follows: BLAST + MEGAN had the lowest error rate and was particularly robust to sequence error; SAP accuracy was highest when long LSU query sequences were classified; and, NBC runs significantly faster than the other tested methods. All methods performed poorly with the shortest 50–100 bp sequences. Increasing simulated sequence error reduced classification accuracy. Community shifts were detected due to sequence error and primer selection even though there was no change in the underlying community composition. Short read datasets from individual primers, as well as pooled datasets, appear to only approximate the true community composition. We hope this work informs investigators of some of the factors that affect the quality and interpretation of their environmental gene surveys. PMID:22558215

Quantitative studies on structure-DPPH• scavenging activity relationships of food phenolic acids.

PubMed

Jing, Pu; Zhao, Shu-Juan; Jian, Wen-Jie; Qian, Bing-Jun; Dong, Ying; Pang, Jie

2012-11-01

Phenolic acids are potent antioxidants, yet the quantitative structure-activity relationships of phenolic acids remain unclear. The purpose of this study was to establish 3D-QSAR models able to predict phenolic acids with high DPPH• scavenging activity and understand their structure-activity relationships. The model has been established by using a training set of compounds with cross-validated q2 = 0.638/0.855, non-cross-validated r2 = 0.984/0.986, standard error of estimate = 0.236/0.216, and F = 139.126/208.320 for the best CoMFA/CoMSIA models. The predictive ability of the models was validated with the correlation coefficient r2(pred) = 0.971/0.996 (>0.6) for each model. Additionally, the contour map results suggested that structural characteristics of phenolics acids favorable for the high DPPH• scavenging activity might include: (1) bulky and/or electron-donating substituent groups on the phenol ring; (2) electron-donating groups at the meta-position and/or hydrophobic groups at the meta-/ortho-position; (3) hydrogen-bond donor/electron-donating groups at the ortho-position. The results have been confirmed based on structural analyses of phenolic acids and their DPPH• scavenging data from eight recent publications. The findings may provide deeper insight into the antioxidant mechanisms and provide useful information for selecting phenolic acids for free radical scavenging properties.

Determination of zinc oxide content of mineral medicine calamine using near-infrared spectroscopy based on MIV and BP-ANN algorithm

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Chen, Long; Sun, Yangbo; Bai, Yu; Huang, Bisheng; Chen, Keli

2018-03-01

Near-infrared (NIR) spectroscopy has been widely used in the analysis fields of traditional Chinese medicine. It has the advantages of fast analysis, no damage to samples and no pollution. In this research, a fast quantitative model for zinc oxide (ZnO) content in mineral medicine calamine was explored based on NIR spectroscopy. NIR spectra of 57 batches of calamine samples were collected and the first derivative (FD) method was adopted for conducting spectral pretreatment. The content of ZnO in calamine sample was determined using ethylenediaminetetraacetic acid (EDTA) titration and taken as reference value of NIR spectroscopy. 57 batches of calamine samples were categorized into calibration and prediction set using the Kennard-Stone (K-S) algorithm. Firstly, in the calibration set, to calculate the correlation coefficient (r) between the absorbance value and the ZnO content of corresponding samples at each wave number. Next, according to the square correlation coefficient (r2) value to obtain the top 50 wave numbers to compose the characteristic spectral bands (4081.8-4096.3, 4188.9-4274.7, 4335.4, 4763.6,4794.4-4802.1, 4809.9, 4817.6-4875.4 cm- 1), which were used to establish the quantitative model of ZnO content using back propagation artificial neural network (BP-ANN) algorithm. Then, the 50 wave numbers were operated by the mean impact value (MIV) algorithm to choose wave numbers whose absolute value of MIV greater than or equal to 25, to obtain the optimal characteristic spectral bands (4875.4-4836.9, 4223.6-4080.9 cm- 1). And then, both internal cross and external validation were used to screen the number of hidden layer nodes of BP-ANN. Finally, the number 4 of hidden layer nodes was chosen as the best. At last, the BP-ANN model was found to enjoy a high accuracy and strong forecasting capacity for analyzing ZnO content in calamine samples ranging within 42.05-69.98%, with relative mean square error of cross validation (RMSECV) of 1.66% and coefficient of determination (R2) of 95.75% in internal cross and relative mean square error of prediction (RMSEP) of 1.98%, R2 of 97.94% and ratio of performance to deviation (RPD) of 6.11 in external validation.

Acoustic evidence for phonologically mismatched speech errors.

PubMed

Gormley, Andrea

2015-04-01

Speech errors are generally said to accommodate to their new phonological context. This accommodation has been validated by several transcription studies. The transcription methodology is not the best choice for detecting errors at this level, however, as this type of error can be difficult to perceive. This paper presents an acoustic analysis of speech errors that uncovers non-accommodated or mismatch errors. A mismatch error is a sub-phonemic error that results in an incorrect surface phonology. This type of error could arise during the processing of phonological rules or they could be made at the motor level of implementation. The results of this work have important implications for both experimental and theoretical research. For experimentalists, it validates the tools used for error induction and the acoustic determination of errors free of the perceptual bias. For theorists, this methodology can be used to test the nature of the processes proposed in language production.

Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements

NASA Technical Reports Server (NTRS)

Wang, Jianxin; Wolff, David B.

2009-01-01

Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) spaced-based rain estimates, and hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar-gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar-gauge differences into the gauge area-point error variance and radar rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar rain estimates at various times scales, and are helpful to better understand the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar rain products to validate versatile spaced-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement, and other satellites.

Genomic Prediction Accounting for Residual Heteroskedasticity

PubMed Central

Ou, Zhining; Tempelman, Robert J.; Steibel, Juan P.; Ernst, Catherine W.; Bates, Ronald O.; Bello, Nora M.

2015-01-01

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. PMID:26564950

Classification of burn wounds using support vector machines

NASA Astrophysics Data System (ADS)

Acha, Begona; Serrano, Carmen; Palencia, Sergio; Murillo, Juan Jose

2004-05-01

The purpose of this work is to improve a previous method developed by the authors for the classification of burn wounds into their depths. The inputs of the system are color and texture information, as these are the characteristics observed by physicians in order to give a diagnosis. Our previous work consisted in segmenting the burn wound from the rest of the image and classifying the burn into its depth. In this paper we focus on the classification problem only. We already proposed to use a Fuzzy-ARTMAP neural network (NN). However, we may take advantage of new powerful classification tools such as Support Vector Machines (SVM). We apply the five-folded cross validation scheme to divide the database into training and validating sets. Then, we apply a feature selection method for each classifier, which will give us the set of features that yields the smallest classification error for each classifier. Features used to classify are first-order statistical parameters extracted from the L*, u* and v* color components of the image. The feature selection algorithms used are the Sequential Forward Selection (SFS) and the Sequential Backward Selection (SBS) methods. As data of the problem faced here are not linearly separable, the SVM was trained using some different kernels. The validating process shows that the SVM method, when using a Gaussian kernel of variance 1, outperforms classification results obtained with the rest of the classifiers, yielding an error classification rate of 0.7% whereas the Fuzzy-ARTMAP NN attained 1.6 %.

The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study.

PubMed

Mokkink, Lidwine B; Terwee, Caroline B; Patrick, Donald L; Alonso, Jordi; Stratford, Paul W; Knol, Dirk L; Bouter, Lex M; de Vet, Henrica C W

2010-05-01

Aim of the COSMIN study (COnsensus-based Standards for the selection of health status Measurement INstruments) was to develop a consensus-based checklist to evaluate the methodological quality of studies on measurement properties. We present the COSMIN checklist and the agreement of the panel on the items of the checklist. A four-round Delphi study was performed with international experts (psychologists, epidemiologists, statisticians and clinicians). Of the 91 invited experts, 57 agreed to participate (63%). Panel members were asked to rate their (dis)agreement with each proposal on a five-point scale. Consensus was considered to be reached when at least 67% of the panel members indicated 'agree' or 'strongly agree'. Consensus was reached on the inclusion of the following measurement properties: internal consistency, reliability, measurement error, content validity (including face validity), construct validity (including structural validity, hypotheses testing and cross-cultural validity), criterion validity, responsiveness, and interpretability. The latter was not considered a measurement property. The panel also reached consensus on how these properties should be assessed. The resulting COSMIN checklist could be useful when selecting a measurement instrument, peer-reviewing a manuscript, designing or reporting a study on measurement properties, or for educational purposes.

Recent bathymetric variability of sandbars at Duck, NC

NASA Astrophysics Data System (ADS)

Ladner, H.; Palmsten, M. L.

2016-02-01

Sediment transport and sandbar migration are unresolved research topics due to the complex interaction between waves, currents, and sediments in the nearshore region. Previous studies have led to better fundamental understanding of sediment transport, but the capability to make precise short term estimates is still limited. One challenge in predicting sediment transport is the sparse bathymetric data available to ground-truth predictions. A recently developed algorithm, cBathy, uses video images to estimate the nearshore bathymetry from wave celerity. This new method can provide an extensive time series of bathymetric change in order to further study the physics of short term sediment transport. The cBathy code is still under development and needs further testing for accuracy. The objective of this work is to validate cBathy estimates of bathymetry and quantify sandbar behavior over a two month period by analyzing the position of the sandbar crest. The bias between the cBathy estimate and survey on 04/02/15 was 0.24 m and root mean square error (RMSE) was 0.50 m. The bias for the cBathy estimate and survey on 05/19/15 was -0.02 m and RMSE was 0.39 m. The bias and RMSE we observed were comparable previous estimates. As expected, errors were largest in shallower water depths where assumptions made by the cBathy algorithm were not valid. Over the two month period, the mean cross-shore location of the primary sandbar at the alongshore location of 200 m was approximately 216 m, with a standard deviation of 16 m. The mean cross-shore location of the primary sandbar at the alongshore location of 850 m was approximately 205 m, with a standard deviation of 17 m.

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

Rueegsegger, Michael B.; Bach Cuadra, Meritxell; Pica, Alessia

Purpose: Ocular anatomy and radiation-associated toxicities provide unique challenges for external beam radiation therapy. For treatment planning, precise modeling of organs at risk and tumor volume are crucial. Development of a precise eye model and automatic adaptation of this model to patients' anatomy remain problematic because of organ shape variability. This work introduces the application of a 3-dimensional (3D) statistical shape model as a novel method for precise eye modeling for external beam radiation therapy of intraocular tumors. Methods and Materials: Manual and automatic segmentations were compared for 17 patients, based on head computed tomography (CT) volume scans. A 3Dmore » statistical shape model of the cornea, lens, and sclera as well as of the optic disc position was developed. Furthermore, an active shape model was built to enable automatic fitting of the eye model to CT slice stacks. Cross-validation was performed based on leave-one-out tests for all training shapes by measuring dice coefficients and mean segmentation errors between automatic segmentation and manual segmentation by an expert. Results: Cross-validation revealed a dice similarity of 95% {+-} 2% for the sclera and cornea and 91% {+-} 2% for the lens. Overall, mean segmentation error was found to be 0.3 {+-} 0.1 mm. Average segmentation time was 14 {+-} 2 s on a standard personal computer. Conclusions: Our results show that the solution presented outperforms state-of-the-art methods in terms of accuracy, reliability, and robustness. Moreover, the eye model shape as well as its variability is learned from a training set rather than by making shape assumptions (eg, as with the spherical or elliptical model). Therefore, the model appears to be capable of modeling nonspherically and nonelliptically shaped eyes.« less

Can quantile mapping improve precipitation extremes from regional climate models?

NASA Astrophysics Data System (ADS)

Tani, Satyanarayana; Gobiet, Andreas

2015-04-01

The ability of quantile mapping to accurately bias correct regard to precipitation extremes is investigated in this study. We developed new methods by extending standard quantile mapping (QMα) to improve the quality of bias corrected extreme precipitation events as simulated by regional climate model (RCM) output. The new QM version (QMβ) was developed by combining parametric and nonparametric bias correction methods. The new nonparametric method is tested with and without a controlling shape parameter (Qmβ1 and Qmβ0, respectively). Bias corrections are applied on hindcast simulations for a small ensemble of RCMs at six different locations over Europe. We examined the quality of the extremes through split sample and cross validation approaches of these three bias correction methods. This split-sample approach mimics the application to future climate scenarios. A cross validation framework with particular focus on new extremes was developed. Error characteristics, q-q plots and Mean Absolute Error (MAEx) skill scores are used for evaluation. We demonstrate the unstable behaviour of correction function at higher quantiles with QMα, whereas the correction functions with for QMβ0 and QMβ1 are smoother, with QMβ1 providing the most reasonable correction values. The result from q-q plots demonstrates that, all bias correction methods are capable of producing new extremes but QMβ1 reproduces new extremes with low biases in all seasons compared to QMα, QMβ0. Our results clearly demonstrate the inherent limitations of empirical bias correction methods employed for extremes, particularly new extremes, and our findings reveals that the new bias correction method (Qmß1) produces more reliable climate scenarios for new extremes. These findings present a methodology that can better capture future extreme precipitation events, which is necessary to improve regional climate change impact studies.

Methodology for cork plank characterization (Quercus suber L.) by near-infrared spectroscopy and image analysis

NASA Astrophysics Data System (ADS)

Prades, Cristina; García-Olmo, Juan; Romero-Prieto, Tomás; García de Ceca, José L.; López-Luque, Rafael

2010-06-01

The procedures used today to characterize cork plank for the manufacture of cork bottle stoppers continue to be based on a traditional, manual method that is highly subjective. Furthermore, there is no specific legislation regarding cork classification. The objective of this viability study is to assess the potential of near-infrared spectroscopy (NIRS) technology for characterizing cork plank according to the following variables: aspect or visual quality, porosity, moisture and geographical origin. In order to calculate the porosity coefficient, an image analysis program was specifically developed in Visual Basic language for a desktop scanner. A set comprising 170 samples from two geographical areas of Andalusia (Spain) was classified into eight quality classes by visual inspection. Spectra were obtained in the transverse and tangential sections of the cork planks using an NIRSystems 6500 SY II reflectance spectrophotometer. The quantitative calibrations showed cross-validation coefficients of determination of 0.47 for visual quality, 0.69 for porosity and 0.66 for moisture. The results obtained using NIRS technology are promising considering the heterogeneity and variability of a natural product such as cork in spite of the fact that the standard error of cross validation (SECV) in the quantitative analysis is greater than the standard error of laboratory (SEL) for the three variables. The qualitative analysis regarding geographical origin achieved very satisfactory results. Applying these methods in industry will permit quality control procedures to be automated, as well as establishing correlations between the different classification systems currently used in the sector. These methods can be implemented in the cork chain of custody certification and will also provide a certainly more objective tool for assessing the economic value of the product.

The statistical validity of nursing home survey findings.

PubMed

Woolley, Douglas C

2011-11-01

The Medicare nursing home survey is a high-stakes process whose findings greatly affect nursing homes, their current and potential residents, and the communities they serve. Therefore, survey findings must achieve high validity. This study looked at the validity of one key assessment made during a nursing home survey: the observation of the rate of errors in administration of medications to residents (med-pass). Statistical analysis of the case under study and of alternative hypothetical cases. A skilled nursing home affiliated with a local medical school. The nursing home administrators and the medical director. Observational study. The probability that state nursing home surveyors make a Type I or Type II error in observing med-pass error rates, based on the current case and on a series of postulated med-pass error rates. In the common situation such as our case, where med-pass errors occur at slightly above a 5% rate after 50 observations, and therefore trigger a citation, the chance that the true rate remains above 5% after a large number of observations is just above 50%. If the true med-pass error rate were as high as 10%, and the survey team wished to achieve 75% accuracy in determining that a citation was appropriate, they would have to make more than 200 med-pass observations. In the more common situation where med pass errors are closer to 5%, the team would have to observe more than 2000 med-passes to achieve even a modest 75% accuracy in their determinations. In settings where error rates are low, large numbers of observations of an activity must be made to reach acceptable validity of estimates for the true rates of errors. In observing key nursing home functions with current methodology, the State Medicare nursing home survey process does not adhere to well-known principles of valid error determination. Alternate approaches in survey methodology are discussed. Copyright © 2011 American Medical Directors Association. Published by Elsevier Inc. All rights reserved.

Combined High Spectral Resolution Lidar and Millimeter Wavelength Radar Measurement of Ice Crystal Precipitation

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

Eloranta, Edwin

The goal of this research has been to improve measurements of snowfall using a combination of millimeter-wavelength radar and High Spectral Resolution Lidar (HSRL) Observations. Snowflakes are large compared to the 532nm HSRL wavelength and small compared to the 3.2 and 8.6 mm wavelength radars used in this study. This places the particles in the optical scattering regime of the HSRL, where extinction cross-section is proportional to the projected area of the particles, and in the Rayleigh regime for the radar, where the backscatter cross-section is proportional to the mass-squared of the particles. Forming a ratio of the radar measuredmore » cross-section to the HSRL measured cross section eliminates any dependence on the number of scattering particles, yielding a quantity proportional to the average mass-squared of the snowflakes over the average area of the flakes. Using simultaneous radar measurements of particle fall velocities, which are dependent particle mass and cross-sectional area it is possible to derive the average mass of the snow flakes, and with the radar measured fall velocities compute the snowfall rate. Since this retrieval requires the optical extinction cross-section we began by considering errors this quantity. The HSRL is particularly good at measuring the backscatter cross-section. In previous studies of snowfall in the high Arctic were able to estimate the extinction cross-section directly as a fixed ratio to the backscatter cross-section. Measurements acquired in the STORMVEX experiment in Colorado showed that this approach was not valid in mid-latitude snowfalls and that direct measurement of the extinction cross-section is required. Attempts to measure the extinction directly uncovered shortcomings in thermal regulation and mechanical stability of the newly deployed DOE HSRL systems. These problems were largely mitigated by modifications installed in both of the DOE systems. We also investigated other sources of error in the HSRL direct measurement of extinction (see appendix II of this report). We also developed improved algorithms to extract extinction from the HSRL data. These have been installed in the standard HSRL data processing software and are now available to all users of HSRL data. Validation of snowfall measurements has proven difficult due to the unreliability of conventional snowfall measurements coupled with the complexity of considering the vast variety of snowflake geometries. It was difficult to tell how well the algorithm’s approach to accommodating differences in snowflakes was working without good measurements for comparison. As a result, we decided to apply this approach to the somewhat simpler, but scientifically important, problem of drizzle measurement. Here the particle shape is known and the conventional measurement are more reliable. These algorithms where successfully applied to drizzle data acquired during the ARM MAGIC study of marine stratus clouds between California and Hawaii (see Appendix I). This technique is likely to become a powerful tool for studying lifetime of the climatically important marine stratus clouds.« less

Near infrared spectroscopy (NIRS) for on-line determination of quality parameters in intact olives.

PubMed

Salguero-Chaparro, Lourdes; Baeten, Vincent; Fernández-Pierna, Juan A; Peña-Rodríguez, Francisco

2013-08-15

The acidity, moisture and fat content in intact olive fruits were determined on-line using a NIR diode array instrument, operating on a conveyor belt. Four sets of calibrations models were obtained by means of different combinations from samples collected during 2009-2010 and 2010-2011, using full-cross and external validation. Several preprocessing treatments such as derivatives and scatter correction were investigated by using the root mean square error of cross-validation (RMSECV) and prediction (RMSEP), as control parameters. The results obtained showed RMSECV values of 2.54-3.26 for moisture, 2.35-2.71 for fat content and 2.50-3.26 for acidity parameters, depending on the calibration model developed. Calibrations for moisture, fat content and acidity gave residual predictive deviation (RPD) values of 2.76, 2.37 and 1.60, respectively. Although, it is concluded that the on-line NIRS prediction results were acceptable for the three parameters measured in intact olive samples in movement, the models developed must be improved in order to increase their accuracy before final NIRS implementation at mills. Copyright © 2013 Elsevier Ltd. All rights reserved.

An augmented classical least squares method for quantitative Raman spectral analysis against component information loss.

PubMed

Zhou, Yan; Cao, Hui

2013-01-01

We propose an augmented classical least squares (ACLS) calibration method for quantitative Raman spectral analysis against component information loss. The Raman spectral signals with low analyte concentration correlations were selected and used as the substitutes for unknown quantitative component information during the CLS calibration procedure. The number of selected signals was determined by using the leave-one-out root-mean-square error of cross-validation (RMSECV) curve. An ACLS model was built based on the augmented concentration matrix and the reference spectral signal matrix. The proposed method was compared with partial least squares (PLS) and principal component regression (PCR) using one example: a data set recorded from an experiment of analyte concentration determination using Raman spectroscopy. A 2-fold cross-validation with Venetian blinds strategy was exploited to evaluate the predictive power of the proposed method. The one-way variance analysis (ANOVA) was used to access the predictive power difference between the proposed method and existing methods. Results indicated that the proposed method is effective at increasing the robust predictive power of traditional CLS model against component information loss and its predictive power is comparable to that of PLS or PCR.

Artificial intelligence techniques: An efficient new approach to challenge the assessment of complex clinical fields such as airway clearance techniques in patients with cystic fibrosis?

PubMed

Slavici, Titus; Almajan, Bogdan

2013-04-01

To construct an artificial intelligence application to assist untrained physiotherapists in determining the appropriate physiotherapy exercises to improve the quality of life of patients with cystic fibrosis. A total of 42 children (21 boys and 21 girls), age range 6-18 years, participated in a clinical survey between 2001 and 2005. Data collected during the clinical survey were entered into a neural network in order to correlate the health state indicators of the patients and the type of physiotherapy exercise to be followed. Cross-validation of the network was carried out by comparing the health state indicators achieved after following a certain physiotherapy exercise and the health state indicators predicted by the network. The lifestyle and health state indicators of the survey participants improved. The network predicted the health state indicators of the participants with an accuracy of 93%. The results of the cross-validation test were within the error margins of the real-life indicators. Using data on the clinical state of individuals with cystic fibrosis, it is possible to determine the most effective type of physiotherapy exercise for improving overall health state indicators.

Towards a Next-Generation Catalogue Cross-Match Service

NASA Astrophysics Data System (ADS)

Pineau, F.; Boch, T.; Derriere, S.; Arches Consortium

2015-09-01

We have been developing in the past several catalogue cross-match tools. On one hand the CDS XMatch service (Pineau et al. 2011), able to perform basic but very efficient cross-matches, scalable to the largest catalogues on a single regular server. On the other hand, as part of the European project ARCHES1, we have been developing a generic and flexible tool which performs potentially complex multi-catalogue cross-matches and which computes probabilities of association based on a novel statistical framework. Although the two approaches have been managed so far as different tracks, the need for next generation cross-match services dealing with both efficiency and complexity is becoming pressing with forthcoming projects which will produce huge high quality catalogues. We are addressing this challenge which is both theoretical and technical. In ARCHES we generalize to N catalogues the candidate selection criteria - based on the chi-square distribution - described in Pineau et al. (2011). We formulate and test a number of Bayesian hypothesis which necessarily increases dramatically with the number of catalogues. To assign a probability to each hypotheses, we rely on estimated priors which account for local densities of sources. We validated our developments by comparing the theoretical curves we derived with the results of Monte-Carlo simulations. The current prototype is able to take into account heterogeneous positional errors, object extension and proper motion. The technical complexity is managed by OO programming design patterns and SQL-like functionalities. Large tasks are split into smaller independent pieces for scalability. Performances are achieved resorting to multi-threading, sequential reads and several tree data-structures. In addition to kd-trees, we account for heterogeneous positional errors and object's extension using M-trees. Proper-motions are supported using a modified M-tree we developed, inspired from Time Parametrized R-trees (TPR-tree). Quantitative tests in comparison with the basic cross-match will be presented.

Merging gauge and satellite rainfall with specification of associated uncertainty across Australia

NASA Astrophysics Data System (ADS)

Woldemeskel, Fitsum M.; Sivakumar, Bellie; Sharma, Ashish

2013-08-01

Accurate estimation of spatial rainfall is crucial for modelling hydrological systems and planning and management of water resources. While spatial rainfall can be estimated either using rain gauge-based measurements or using satellite-based measurements, such estimates are subject to uncertainties due to various sources of errors in either case, including interpolation and retrieval errors. The purpose of the present study is twofold: (1) to investigate the benefit of merging rain gauge measurements and satellite rainfall data for Australian conditions and (2) to produce a database of retrospective rainfall along with a new uncertainty metric for each grid location at any timestep. The analysis involves four steps: First, a comparison of rain gauge measurements and the Tropical Rainfall Measuring Mission (TRMM) 3B42 data at such rain gauge locations is carried out. Second, gridded monthly rain gauge rainfall is determined using thin plate smoothing splines (TPSS) and modified inverse distance weight (MIDW) method. Third, the gridded rain gauge rainfall is merged with the monthly accumulated TRMM 3B42 using a linearised weighting procedure, the weights at each grid being calculated based on the error variances of each dataset. Finally, cross validation (CV) errors at rain gauge locations and standard errors at gridded locations for each timestep are estimated. The CV error statistics indicate that merging of the two datasets improves the estimation of spatial rainfall, and more so where the rain gauge network is sparse. The provision of spatio-temporal standard errors with the retrospective dataset is particularly useful for subsequent modelling applications where input error knowledge can help reduce the uncertainty associated with modelling outcomes.

Position Error Covariance Matrix Validation and Correction

NASA Technical Reports Server (NTRS)

Frisbee, Joe, Jr.

2016-01-01

In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.

An intercomparison of a large ensemble of statistical downscaling methods for Europe: Overall results from the VALUE perfect predictor cross-validation experiment

NASA Astrophysics Data System (ADS)

Gutiérrez, Jose Manuel; Maraun, Douglas; Widmann, Martin; Huth, Radan; Hertig, Elke; Benestad, Rasmus; Roessler, Ole; Wibig, Joanna; Wilcke, Renate; Kotlarski, Sven

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research (http://www.value-cost.eu). A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. This framework is based on a user-focused validation tree, guiding the selection of relevant validation indices and performance measures for different aspects of the validation (marginal, temporal, spatial, multi-variable). Moreover, several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur (assessment of intrinsic performance, effect of errors inherited from the global models, effect of non-stationarity, etc.). The list of downscaling experiments includes 1) cross-validation with perfect predictors, 2) GCM predictors -aligned with EURO-CORDEX experiment- and 3) pseudo reality predictors (see Maraun et al. 2015, Earth's Future, 3, doi:10.1002/2014EF000259, for more details). The results of these experiments are gathered, validated and publicly distributed through the VALUE validation portal, allowing for a comprehensive community-open downscaling intercomparison study. In this contribution we describe the overall results from Experiment 1), consisting of a European wide 5-fold cross-validation (with consecutive 6-year periods from 1979 to 2008) using predictors from ERA-Interim to downscale precipitation and temperatures (minimum and maximum) over a set of 86 ECA&D stations representative of the main geographical and climatic regions in Europe. As a result of the open call for contribution to this experiment (closed in Dec. 2015), over 40 methods representative of the main approaches (MOS and Perfect Prognosis, PP) and techniques (linear scaling, quantile mapping, analogs, weather typing, linear and generalized regression, weather generators, etc.) were submitted, including information both data (downscaled values) and metadata (characterizing different aspects of the downscaling methods). This constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods. Here, we present an overall validation, analyzing marginal and temporal aspects to assess the intrinsic performance and added value of statistical downscaling methods at both annual and seasonal levels. This validation takes into account the different properties/limitations of different approaches and techniques (as reported in the provided metadata) in order to perform a fair comparison. It is pointed out that this experiment alone is not sufficient to evaluate the limitations of (MOS) bias correction techniques. Moreover, it also does not fully validate PP since we don't learn whether we have the right predictors and whether the PP assumption is valid. These problems will be analyzed in the subsequent community-open VALUE experiments 2) and 3), which will be open for participation along the present year.

Cross sections for H(-) and Cl(-) production from HCl by dissociative electron attachment

NASA Technical Reports Server (NTRS)

Orient, O. J.; Srivastava, S. K.

1985-01-01

A crossed target beam-electron beam collision geometry and a quadrupole mass spectrometer have been used to conduct dissociative electron attachment cross section measurements for the case of H(-) and Cl(-) production from HCl. The relative flow technique is used to determine the absolute values of cross sections. A tabulation is given of the attachment energies corresponding to various cross section maxima. Error sources contributing to total errors are also estimated.

Measurement Properties of the NIH-Minimal Dataset Dutch Language Version in Patients With Chronic Low Back Pain.

PubMed

Boer, Annemarie; Dutmer, Alisa L; Schiphorst Preuper, Henrica R; van der Woude, Lucas H V; Stewart, Roy E; Deyo, Richard A; Reneman, Michiel F; Soer, Remko

2017-10-01

Validation study with cross-sectional and longitudinal measurements. To translate the US National Institutes of Health (NIH)-minimal dataset for clinical research on chronic low back pain into the Dutch language and to test its validity and reliability among people with chronic low back pain. The NIH developed a minimal dataset to encourage more complete and consistent reporting of clinical research and to be able to compare studies across countries in patients with low back pain. In the Netherlands, the NIH-minimal dataset has not been translated before and measurement properties are unknown. Cross-cultural validity was tested by a formal forward-backward translation. Structural validity was tested with exploratory factor analyses (comparative fit index, Tucker-Lewis index, and root mean square error of approximation). Hypothesis testing was performed to compare subscales of the NIH dataset with the Pain Disability Index and the EurQol-5D (Pearson correlation coefficients). Internal consistency was tested with Cronbach α and test-retest reliability at 2 weeks was calculated in a subsample of patients with Intraclass Correlation Coefficients and weighted Kappa (κω). In total, 452 patients were included of which 52 were included for the test-retest study. factor analysis for structural validity pointed into the direction of a seven-factor model (Cronbach α = 0.78). Factors and total score of the NIH-minimal dataset showed fair to good correlations with Pain Disability Index (r = 0.43-0.70) and EuroQol-5D (r = -0.41 to -0.64). Reliability: test-retest reliability per item showed substantial agreement (κω=0.65). Test-retest reliability per factor was moderate to good (Intraclass Correlation Coefficient = 0.71). The Dutch language version measurement properties of the NIH-minimal were satisfactory. N/A.

Ultrasound is a reproducible and valid tool for measuring scar height in children with burn scars: A cross-sectional study of the psychometric properties and utility of the ultrasound and 3D camera.

PubMed

Simons, M; Kee, E Gee; Kimble, R; Tyack, Z

2017-08-01

The aim of this study was to investigate the reproducibility and validity of measuring scar height in children using ultrasound and 3D camera. Using a cross-sectional design, children with discrete burn scars were included. Reproducibility was tested using Intraclass Correlation Coefficient (ICC) for reliability, and percentage agreement within 1mm between test and re-test, standard error of measurement (SEM), smallest detectable change (SDC) and Bland Altman limits of agreement for agreement. Concurrent validity was tested using Spearman's rho for support of pre-specified hypotheses. Forty-nine participants (55 scars) were included. For ultrasound, test-retest and inter-rater reproducibility of scar thickness was acceptable for scarred skin (ICC=0.95, SDC=0.06cm and ICC=0.82, SDC=0.14cm). The ultrasound picked up changes of <1mm. Inter-rater reproducibility of maximal scar height using the 3D camera was acceptable (ICC=0.73, SDC=0.55cm). Construct validity of the ultrasound was supported with a strong correlation between the measure of scar thickness and observer ratings of thickness using the POSAS (ρ=0.61). Construct validity of the 3D camera was also supported with a moderate correlation (ρ=0.37) with the same measure using maximal scar height. The ultrasound is capable of detecting smaller changes or differences in scar thickness than the 3D camera, in children with burn scars. However agreement as part of reproducibility was lower than expected between raters for the ultrasound. Improving the accuracy of scar relocation may go some way to address agreement. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

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

Reliability and Validity Study of the Finnish Adaptation of Scoliosis Research Society Questionnaire Version SRS-30.

PubMed

Kyrölä, Kati; Järvenpää, Salme; Ylinen, Jari; Mecklin, Jukka-Pekka; Repo, Jussi Petteri; Häkkinen, Arja

2017-06-15

A prospective clinical study to test and adapt a Finnish version of the Scoliosis Research Society 30 (SRS-30) questionnaire. The aim of this study was to perform cross-cultural adaptation and evaluate the validity of the adapted Finnish version of the SRS-30 questionnaire. The SRS-30 questionnaire has proved to be a valid instrument in evaluating health-related quality of life (HRQoL) in adolescent and adult population with spine deformities in the United States. Multinational availability requires cross-cultural and linguistic adaptation and validation of the instrument. The SRS-30 was translated into Finnish using accepted methods for translation of quality-of-life questionnaires. A total of 274 adult patients with degenerative radiographic sagittal spinal disorder answered the questionnaire with sociodemographic data, RAND 36-item health survey questionnaire (RAND Corp. Health, Santa Monica, CA, US), Oswestry disability index, DEPS depression scale, and Visual Analog Scale (VAS) back and leg pain scales within 2 weeks' interval. The cohort included patients with and without previous spine surgery. Internal consistency and validity were tested with Cronbach α, intraclass correlation (ICC), standard error of measurement, and Spearman correlation coefficient with 95% confidence intervals (CIs). The internal consistency of SRS-30 was good in both surgery and nonsurgery groups, with Cronbach α 0.853 (95% CI, 0.670 to 0.960) and 0.885 (95% CI, 0.854 to 0.911), respectively. The test-retest reproducibility ICC of the SRS-30 total and subscore domains of patients with stable symptoms was 0.905 (95% CI, 0.870-0.930) and 0.904 (95% CI, 0.871-0.929), respectively. The questionnaire had discriminative validity in the pain, self-image, and satisfaction with management domains compared with other questionnaires. The SRS-30 questionnaire proved to be valid and applicable in evaluating HRQoL in Finnish adult spinal deformity patients. It has two domains related to deformity that are not covered by other generally used questionnaires. 3.

Executive functioning of complicated-mild to moderate traumatic brain injury patients with frontal contusions.

PubMed

Ghawami, Heshmatollah; Sadeghi, Sadegh; Raghibi, Mahvash; Rahimi-Movaghar, Vafa

2017-01-01

Executive dysfunctions are among the most prevalent neurobehavioral sequelae of traumatic brain injuries (TBIs). Using culturally validated tests from the Delis-Kaplan Executive Function System (D-KEFS: Trail Making, Verbal Fluency, Design Fluency, Sorting, Twenty Questions, and Tower) and the Behavioural Assessment of the Dysexecutive Syndrome (BADS: Rule Shift Cards, Key Search, and Modified Six Elements), the current study was the first to examine executive functioning in a group of Iranian TBI patients with focal frontal contusions. Compared with a demographically matched normative sample, the frontal contusion patients showed substantial impairments, with very large effect sizes (p ≤ .003, 1.56 < d < 3.12), on all the executive measures. Controlling for respective lower-level/fundamental conditions, the differences on the highest-level executive (cognitive switching) conditions were still significant. The frontal patients also committed more errors. Patients with lateral prefrontal (LPFC) contusions were qualitatively worst. For example, only the LPFC patients committed perseverative repetition errors. Altogether, our results support the notion that the frontal lobes, specifically the lateral prefrontal regions, play a critical role in cognitive executive functioning, over and above the contributions of respective lower-level cognitive abilities. The results provide clinical evidence for validity of the cross-culturally adapted versions of the tests.

Quantitative assessment of copper proteinates used as animal feed additives using ATR-FTIR spectroscopy and powder X-ray diffraction (PXRD) analysis.

PubMed

Cantwell, Caoimhe A; Byrne, Laurann A; Connolly, Cathal D; Hynes, Michael J; McArdle, Patrick; Murphy, Richard A

2017-08-01

The aim of the present work was to establish a reliable analytical method to determine the degree of complexation in commercial metal proteinates used as feed additives in the solid state. Two complementary techniques were developed. Firstly, a quantitative attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopic method investigated modifications in vibrational absorption bands of the ligand on complex formation. Secondly, a powder X-ray diffraction (PXRD) method to quantify the amount of crystalline material in the proteinate product was developed. These methods were developed in tandem and cross-validated with each other. Multivariate analysis (MVA) was used to develop validated calibration and prediction models. The FTIR and PXRD calibrations showed excellent linearity (R 2  > 0.99). The diagnostic model parameters showed that the FTIR and PXRD methods were robust with a root mean square error of calibration RMSEC ≤3.39% and a root mean square error of prediction RMSEP ≤7.17% respectively. Comparative statistics show excellent agreement between the MVA packages assessed and between the FTIR and PXRD methods. The methods can be used to determine the degree of complexation in complexes of both protein hydrolysates and pure amino acids.

Estimating aboveground biomass in interior Alaska with Landsat data and field measurements

USGS Publications Warehouse

Ji, Lei; Wylie, Bruce K.; Nossov, Dana R.; Peterson, Birgit E.; Waldrop, Mark P.; McFarland, Jack W.; Rover, Jennifer R.; Hollingsworth, Teresa N.

2012-01-01

Terrestrial plant biomass is a key biophysical parameter required for understanding ecological systems in Alaska. An accurate estimation of biomass at a regional scale provides an important data input for ecological modeling in this region. In this study, we created an aboveground biomass (AGB) map at 30-m resolution for the Yukon Flats ecoregion of interior Alaska using Landsat data and field measurements. Tree, shrub, and herbaceous AGB data in both live and dead forms were collected in summers and autumns of 2009 and 2010. Using the Landsat-derived spectral variables and the field AGB data, we generated a regression model and applied this model to map AGB for the ecoregion. A 3-fold cross-validation indicated that the AGB estimates had a mean absolute error of 21.8 Mg/ha and a mean bias error of 5.2 Mg/ha. Additionally, we validated the mapping results using an airborne lidar dataset acquired for a portion of the ecoregion. We found a significant relationship between the lidar-derived canopy height and the Landsat-derived AGB (R2 = 0.40). The AGB map showed that 90% of the ecoregion had AGB values ranging from 10 Mg/ha to 134 Mg/ha. Vegetation types and fires were the primary factors controlling the spatial AGB patterns in this ecoregion.

Remote estimation of colored dissolved organic matter and chlorophyll-a in Lake Huron using Sentinel-2 measurements

NASA Astrophysics Data System (ADS)

Chen, Jiang; Zhu, Weining; Tian, Yong Q.; Yu, Qian; Zheng, Yuhan; Huang, Litong

2017-07-01

Colored dissolved organic matter (CDOM) and chlorophyll-a (Chla) are important water quality parameters and play crucial roles in aquatic environment. Remote sensing of CDOM and Chla concentrations for inland lakes is often limited by low spatial resolution. The newly launched Sentinel-2 satellite is equipped with high spatial resolution (10, 20, and 60 m). Empirical band ratio models were developed to derive CDOM and Chla concentrations in Lake Huron. The leave-one-out cross-validation method was used for model calibration and validation. The best CDOM retrieval algorithm is a B3/B5 model with accuracy coefficient of determination (R2)=0.884, root-mean-squared error (RMSE)=0.731 m-1, relative root-mean-squared error (RRMSE)=28.02%, and bias=-0.1 m-1. The best Chla retrieval algorithm is a B5/B4 model with accuracy R2=0.49, RMSE=9.972 mg/m3, RRMSE=48.47%, and bias=-0.116 mg/m3. Neural network models were further implemented to improve inversion accuracy. The applications of the two best band ratio models to Sentinel-2 imagery with 10 m×10 m pixel size presented the high potential of the sensor for monitoring water quality of inland lakes.

Weighted divergence correction scheme and its fast implementation

NASA Astrophysics Data System (ADS)

Wang, ChengYue; Gao, Qi; Wei, RunJie; Li, Tian; Wang, JinJun

2017-05-01

Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.

Phase extraction based on iterative algorithm using five-frame crossed fringes in phase measuring deflectometry

NASA Astrophysics Data System (ADS)

Jin, Chengying; Li, Dahai; Kewei, E.; Li, Mengyang; Chen, Pengyu; Wang, Ruiyang; Xiong, Zhao

2018-06-01

In phase measuring deflectometry, two orthogonal sinusoidal fringe patterns are separately projected on the test surface and the distorted fringes reflected by the surface are recorded, each with a sequential phase shift. Then the two components of the local surface gradients are obtained by triangulation. It usually involves some complicated and time-consuming procedures (fringe projection in the orthogonal directions). In addition, the digital light devices (e.g. LCD screen and CCD camera) are not error free. There are quantization errors for each pixel of both LCD and CCD. Therefore, to avoid the complex process and improve the reliability of the phase distribution, a phase extraction algorithm with five-frame crossed fringes is presented in this paper. It is based on a least-squares iterative process. Using the proposed algorithm, phase distributions and phase shift amounts in two orthogonal directions can be simultaneously and successfully determined through an iterative procedure. Both a numerical simulation and a preliminary experiment are conducted to verify the validity and performance of this algorithm. Experimental results obtained by our method are shown, and comparisons between our experimental results and those obtained by the traditional 16-step phase-shifting algorithm and between our experimental results and those measured by the Fizeau interferometer are made.

Validity of mail survey data on bagged waterfowl

USGS Publications Warehouse

Atwood, E.L.

1956-01-01

Knowledge of the pattern of occurrence and characteristics of response errors obtained during an investigation of the validity of post-season surveys of hunters was used to advantage to devise a two-step method for removing the response-bias errors from the raw survey data. The method was tested on data with known errors and found to have a high efficiency in reducing the effect of response-bias errors. The development of this method for removing the effect of the response-bias errors, and its application to post-season hunter-take survey data, increased the reliability of the data from below the point of practical management significance up to the approximate reliability limits corresponding to the sampling errors.

Early detection of lung cancer recurrence after stereotactic ablative radiation therapy: radiomics system design

NASA Astrophysics Data System (ADS)

Dammak, Salma; Palma, David; Mattonen, Sarah; Senan, Suresh; Ward, Aaron D.

2018-02-01

Stereotactic ablative radiotherapy (SABR) is the standard treatment recommendation for Stage I non-small cell lung cancer (NSCLC) patients who are inoperable or who refuse surgery. This option is well tolerated by even unfit patients and has a low recurrence risk post-treatment. However, SABR induces changes in the lung parenchyma that can appear similar to those of recurrence, and the difference between the two at an early follow-up time point is not easily distinguishable for an expert physician. We hypothesized that a radiomics signature derived from standard-of-care computed tomography (CT) imaging can detect cancer recurrence within six months of SABR treatment. This study reports on the design phase of our work, with external validation planned in future work. In this study, we performed cross-validation experiments with four feature selection approaches and seven classifiers on an 81-patient data set. We extracted 104 radiomics features from the consolidative and the peri-consolidative regions on the follow-up CT scans. The best results were achieved using the sum of estimated Mahalanobis distances (Maha) for supervised forward feature selection and a trainable automatic radial basis support vector classifier (RBSVC). This system produced an area under the receiver operating characteristic curve (AUC) of 0.84, an error rate of 16.4%, a false negative rate of 12.7%, and a false positive rate of 20.0% for leaveone patient out cross-validation. This suggests that once validated on an external data set, radiomics could reliably detect post-SABR recurrence and form the basis of a tool assisting physicians in making salvage treatment decisions.

Estimating energy expenditure from heart rate in older adults: a case for calibration.

PubMed

Schrack, Jennifer A; Zipunnikov, Vadim; Goldsmith, Jeff; Bandeen-Roche, Karen; Crainiceanu, Ciprian M; Ferrucci, Luigi

2014-01-01

Accurate measurement of free-living energy expenditure is vital to understanding changes in energy metabolism with aging. The efficacy of heart rate as a surrogate for energy expenditure is rooted in the assumption of a linear function between heart rate and energy expenditure, but its validity and reliability in older adults remains unclear. To assess the validity and reliability of the linear function between heart rate and energy expenditure in older adults using different levels of calibration. Heart rate and energy expenditure were assessed across five levels of exertion in 290 adults participating in the Baltimore Longitudinal Study of Aging. Correlation and random effects regression analyses assessed the linearity of the relationship between heart rate and energy expenditure and cross-validation models assessed predictive performance. Heart rate and energy expenditure were highly correlated (r=0.98) and linear regardless of age or sex. Intra-person variability was low but inter-person variability was high, with substantial heterogeneity of the random intercept (s.d. =0.372) despite similar slopes. Cross-validation models indicated individual calibration data substantially improves accuracy predictions of energy expenditure from heart rate, reducing the potential for considerable measurement bias. Although using five calibration measures provided the greatest reduction in the standard deviation of prediction errors (1.08 kcals/min), substantial improvement was also noted with two (0.75 kcals/min). These findings indicate standard regression equations may be used to make population-level inferences when estimating energy expenditure from heart rate in older adults but caution should be exercised when making inferences at the individual level without proper calibration.

An improved procedure for the validation of satellite-based precipitation estimates

NASA Astrophysics Data System (ADS)

Tang, Ling; Tian, Yudong; Yan, Fang; Habib, Emad

2015-09-01

The objective of this study is to propose and test a new procedure to improve the validation of remote-sensing, high-resolution precipitation estimates. Our recent studies show that many conventional validation measures do not accurately capture the unique error characteristics in precipitation estimates to better inform both data producers and users. The proposed new validation procedure has two steps: 1) an error decomposition approach to separate the total retrieval error into three independent components: hit error, false precipitation and missed precipitation; and 2) the hit error is further analyzed based on a multiplicative error model. In the multiplicative error model, the error features are captured by three model parameters. In this way, the multiplicative error model separates systematic and random errors, leading to more accurate quantification of the uncertainties. The proposed procedure is used to quantitatively evaluate the recent two versions (Version 6 and 7) of TRMM's Multi-sensor Precipitation Analysis (TMPA) real-time and research product suite (3B42 and 3B42RT) for seven years (2005-2011) over the continental United States (CONUS). The gauge-based National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) near-real-time daily precipitation analysis is used as the reference. In addition, the radar-based NCEP Stage IV precipitation data are also model-fitted to verify the effectiveness of the multiplicative error model. The results show that winter total bias is dominated by the missed precipitation over the west coastal areas and the Rocky Mountains, and the false precipitation over large areas in Midwest. The summer total bias is largely coming from the hit bias in Central US. Meanwhile, the new version (V7) tends to produce more rainfall in the higher rain rates, which moderates the significant underestimation exhibited in the previous V6 products. Moreover, the error analysis from the multiplicative error model provides a clear and concise picture of the systematic and random errors, with both versions of 3B42RT have higher errors in varying degrees than their research (post-real-time) counterparts. The new V7 algorithm shows obvious improvements in reducing random errors in both winter and summer seasons, compared to its predecessors V6. Stage IV, as expected, surpasses the satellite-based datasets in all the metrics over CONUS. Based on the results, we recommend the new procedure be adopted for routine validation of satellite-based precipitation datasets, and we expect the procedure will work effectively for higher resolution data to be produced in the Global Precipitation Measurement (GPM) era.

Ozone Observations by the Gas and Aerosol Measurement Sensor during SOLVE II

NASA Technical Reports Server (NTRS)

Pitts, M. C.; Thomason, L. W.; Zawodny, J. M.; Wenny, B. N.; Livingston, J. M.; Russell, P. B.; Yee, J.-H.; Swartz, W. H.; Shetter, R. E.

2006-01-01

The Gas and Aerosol Measurement Sensor (GAMS) was deployed aboard the NASA DC-8 aircraft during the second SAGE III Ozone Loss and Validation Experiment (SOLVE II). GAMS acquired line-of-sight (LOS) direct solar irradiance spectra during the sunlit portions of ten science flights of the DC-8 between 12 January and 4 February 2003. Differential line-of-sight (DLOS) optical depth spectra are produced from the GAMS raw solar irradiance spectra. Then, DLOS ozone number densities are retrieved from the GAMS spectra using a multiple linear regression spectral fitting technique. Both the DLOS optical depth spectra and retrieved ozone data are compared with coincident measurements from two other solar instruments aboard the DC-8 platform to demonstrate the robustness and stability of the GAMS data. The GAMS ozone measurements are then utilized to evaluate the quality of the Wulf band ozone cross sections, a critical component of the SAGE III aerosol, water vapor, and temperature/pressure retrievals. Results suggest the ozone cross section compilation of Shettle and Anderson currently used operationally in SAGE III data processing may be in error by as much as 10-20% in theWulf bands, and their lack of reported temperature dependence is a significant deficiency. A second, more recent, cross section database compiled for the SCIAMACHY satellite mission appears to be of much better quality in the Wulf bands, but still may have errors as large as 5% near the Wulf band absorption peaks, which is slightly larger than their stated uncertainty. Additional laboratory measurements of the Wulf band cross sections should be pursued to further reduce their uncertainty and better quantify their temperature dependence.

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.

Automated smartphone audiometry: Validation of a word recognition test app.

PubMed

Dewyer, Nicholas A; Jiradejvong, Patpong; Henderson Sabes, Jennifer; Limb, Charles J

2018-03-01

Develop and validate an automated smartphone word recognition test. Cross-sectional case-control diagnostic test comparison. An automated word recognition test was developed as an app for a smartphone with earphones. English-speaking adults with recent audiograms and various levels of hearing loss were recruited from an audiology clinic and were administered the smartphone word recognition test. Word recognition scores determined by the smartphone app and the gold standard speech audiometry test performed by an audiologist were compared. Test scores for 37 ears were analyzed. Word recognition scores determined by the smartphone app and audiologist testing were in agreement, with 86% of the data points within a clinically acceptable margin of error and a linear correlation value between test scores of 0.89. The WordRec automated smartphone app accurately determines word recognition scores. 3b. Laryngoscope, 128:707-712, 2018. © 2017 The American Laryngological, Rhinological and Otological Society, Inc.

Modeling brook trout presence and absence from landscape variables using four different analytical methods

USGS Publications Warehouse

Steen, Paul J.; Passino-Reader, Dora R.; Wiley, Michael J.

2006-01-01

As a part of the Great Lakes Regional Aquatic Gap Analysis Project, we evaluated methodologies for modeling associations between fish species and habitat characteristics at a landscape scale. To do this, we created brook trout Salvelinus fontinalis presence and absence models based on four different techniques: multiple linear regression, logistic regression, neural networks, and classification trees. The models were tested in two ways: by application to an independent validation database and cross-validation using the training data, and by visual comparison of statewide distribution maps with historically recorded occurrences from the Michigan Fish Atlas. Although differences in the accuracy of our models were slight, the logistic regression model predicted with the least error, followed by multiple regression, then classification trees, then the neural networks. These models will provide natural resource managers a way to identify habitats requiring protection for the conservation of fish species.

PREVAIL: Predicting Recovery through Estimation and Visualization of Active and Incident Lesions.

PubMed

Dworkin, Jordan D; Sweeney, Elizabeth M; Schindler, Matthew K; Chahin, Salim; Reich, Daniel S; Shinohara, Russell T

2016-01-01

The goal of this study was to develop a model that integrates imaging and clinical information observed at lesion incidence for predicting the recovery of white matter lesions in multiple sclerosis (MS) patients. Demographic, clinical, and magnetic resonance imaging (MRI) data were obtained from 60 subjects with MS as part of a natural history study at the National Institute of Neurological Disorders and Stroke. A total of 401 lesions met the inclusion criteria and were used in the study. Imaging features were extracted from the intensity-normalized T1-weighted (T1w) and T2-weighted sequences as well as magnetization transfer ratio (MTR) sequence acquired at lesion incidence. T1w and MTR signatures were also extracted from images acquired one-year post-incidence. Imaging features were integrated with clinical and demographic data observed at lesion incidence to create statistical prediction models for long-term damage within the lesion. The performance of the T1w and MTR predictions was assessed in two ways: first, the predictive accuracy was measured quantitatively using leave-one-lesion-out cross-validated (CV) mean-squared predictive error. Then, to assess the prediction performance from the perspective of expert clinicians, three board-certified MS clinicians were asked to individually score how similar the CV model-predicted one-year appearance was to the true one-year appearance for a random sample of 100 lesions. The cross-validated root-mean-square predictive error was 0.95 for normalized T1w and 0.064 for MTR, compared to the estimated measurement errors of 0.48 and 0.078 respectively. The three expert raters agreed that T1w and MTR predictions closely resembled the true one-year follow-up appearance of the lesions in both degree and pattern of recovery within lesions. This study demonstrates that by using only information from a single visit at incidence, we can predict how a new lesion will recover using relatively simple statistical techniques. The potential to visualize the likely course of recovery has implications for clinical decision-making, as well as trial enrichment.

Sentinel node status prediction by four statistical models: results from a large bi-institutional series (n = 1132).

PubMed

Mocellin, Simone; Thompson, John F; Pasquali, Sandro; Montesco, Maria C; Pilati, Pierluigi; Nitti, Donato; Saw, Robyn P; Scolyer, Richard A; Stretch, Jonathan R; Rossi, Carlo R

2009-12-01

To improve selection for sentinel node (SN) biopsy (SNB) in patients with cutaneous melanoma using statistical models predicting SN status. About 80% of patients currently undergoing SNB are node negative. In the absence of conclusive evidence of a SNBassociated survival benefit, these patients may be over-treated. Here, we tested the efficiency of 4 different models in predicting SN status. The clinicopathologic data (age, gender, tumor thickness, Clark level, regression, ulceration, histologic subtype, and mitotic index) of 1132 melanoma patients who had undergone SNB at institutions in Italy and Australia were analyzed. Logistic regression, classification tree, random forest, and support vector machine models were fitted to the data. The predictive models were built with the aim of maximizing the negative predictive value (NPV) and reducing the rate of SNB procedures though minimizing the error rate. After cross-validation logistic regression, classification tree, random forest, and support vector machine predictive models obtained clinically relevant NPV (93.6%, 94.0%, 97.1%, and 93.0%, respectively), SNB reduction (27.5%, 29.8%, 18.2%, and 30.1%, respectively), and error rates (1.8%, 1.8%, 0.5%, and 2.1%, respectively). Using commonly available clinicopathologic variables, predictive models can preoperatively identify a proportion of patients ( approximately 25%) who might be spared SNB, with an acceptable (1%-2%) error. If validated in large prospective series, these models might be implemented in the clinical setting for improved patient selection, which ultimately would lead to better quality of life for patients and optimization of resource allocation for the health care system.

A model of prediction and cross-validation of fat-free mass in men with motor complete spinal cord injury.

PubMed

Gorgey, Ashraf S; Dolbow, David R; Gater, David R

2012-07-01

To establish and validate prediction equations by using body weight to predict legs, trunk, and whole-body fat-free mass (FFM) in men with chronic complete spinal cord injury (SCI). Cross-sectional design. Research setting in a large medical center. Individuals with SCI (N=63) divided into prediction (n=42) and cross-validation (n=21) groups. Not applicable. Whole-body FFM and regional FFM were determined by using dual-energy x-ray absorptiometry. Body weight was measured by using a wheelchair weighing scale after subtracting the weight of the chair. Body weight predicted legs FFM (legs FFM=.09×body weight+6.1; R(2)=.25, standard error of the estimate [SEE]=3.1kg, P<.01), trunk FFM (trunk FFM=.21×body weight+8.6; R(2)=.56, SEE=3.6kg, P<.0001), and whole-body FFM (whole-body FFM=.288×body weight+26.3; R(2)=.53, SEE=5.3kg, P<.0001). The whole-body FFM(predicted) (FFM predicted from the derived equations) shared 86% of the variance in whole-body FFM(measured) (FFM measured using dual-energy x-ray absorptiometry scan) (R(2)=.86, SEE=1.8kg, P<.0001), 69% of trunk FFM(measured), and 66% of legs FFM(measured). The trunk FFM(predicted) shared 69% of the variance in trunk FFM(measured) (R(2)=.69, SEE=2.7kg, P<.0001), and legs FFM(predicted) shared 67% of the variance in legs FFM(measured) (R(2)=.67, SEE=2.8kg, P<.0001). Values of FFM did not differ between the prediction and validation groups. Body weight can be used to predict whole-body FFM and regional FFM. The predicted whole-body FFM improved the prediction of trunk FFM and legs FFM. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Cross-Layer Design for Space-Time coded MIMO Systems over Rice Fading Channel

NASA Astrophysics Data System (ADS)

Yu, Xiangbin; Zhou, Tingting; Liu, Xiaoshuai; Yin, Xin

A cross-layer design (CLD) scheme for space-time coded MIMO systems over Rice fading channel is presented by combining adaptive modulation and automatic repeat request, and the corresponding system performance is investigated well. The fading gain switching thresholds subject to a target packet error rate (PER) and fixed power constraint are derived. According to these results, and using the generalized Marcum Q-function, the calculation formulae of the average spectrum efficiency (SE) and PER of the system with CLD are derived. As a result, closed-form expressions for average SE and PER are obtained. These expressions include some existing expressions in Rayleigh channel as special cases. With these expressions, the system performance in Rice fading channel is evaluated effectively. Numerical results verify the validity of the theoretical analysis. The results show that the system performance in Rice channel is effectively improved as Rice factor increases, and outperforms that in Rayleigh channel.

Cross-stream diffusion under pressure-driven flow in microchannels with arbitrary aspect ratios: a phase diagram study using a three-dimensional analytical model

PubMed Central

Song, Hongjun; Wang, Yi; Pant, Kapil

2011-01-01

This article presents a three-dimensional analytical model to investigate cross-stream diffusion transport in rectangular microchannels with arbitrary aspect ratios under pressure-driven flow. The Fourier series solution to the three-dimensional convection–diffusion equation is obtained using a double integral transformation method and associated eigensystem calculation. A phase diagram derived from the dimensional analysis is presented to thoroughly interrogate the characteristics in various transport regimes and examine the validity of the model. The analytical model is verified against both experimental and numerical models in terms of the concentration profile, diffusion scaling law, and mixing efficiency with excellent agreement (with <0.5% relative error). Quantitative comparison against other prior analytical models in extensive parameter space is also performed, which demonstrates that the present model accommodates much broader transport regimes with significantly enhanced applicability. PMID:22247719

Cross-stream diffusion under pressure-driven flow in microchannels with arbitrary aspect ratios: a phase diagram study using a three-dimensional analytical model.

PubMed

Song, Hongjun; Wang, Yi; Pant, Kapil

2012-01-01

This article presents a three-dimensional analytical model to investigate cross-stream diffusion transport in rectangular microchannels with arbitrary aspect ratios under pressure-driven flow. The Fourier series solution to the three-dimensional convection-diffusion equation is obtained using a double integral transformation method and associated eigensystem calculation. A phase diagram derived from the dimensional analysis is presented to thoroughly interrogate the characteristics in various transport regimes and examine the validity of the model. The analytical model is verified against both experimental and numerical models in terms of the concentration profile, diffusion scaling law, and mixing efficiency with excellent agreement (with <0.5% relative error). Quantitative comparison against other prior analytical models in extensive parameter space is also performed, which demonstrates that the present model accommodates much broader transport regimes with significantly enhanced applicability.

All-optical simultaneous multichannel quadrature phase shift keying signal regeneration based on phase-sensitive amplification

NASA Astrophysics Data System (ADS)

Wang, Hongxiang; Wang, Qi; Bai, Lin; Ji, Yuefeng

2018-01-01

A scheme is proposed to realize the all-optical phase regeneration of four-channel quadrature phase shift keying (QPSK) signal based on phase-sensitive amplification. By utilizing conjugate pump and common pump in a highly nonlinear optical fiber, degenerate four-wave mixing process is observed, and QPSK signals are regenerated. The number of waves is reduced to decrease the cross talk caused by undesired nonlinear interaction during the coherent superposition process. In addition, to avoid the effect of overlapping frequency, frequency spans between pumps and signals are set to be nonintegral multiples. Optical signal-to-noise ratio improvement is validated by bit error rate measurements. Compared with single-channel regeneration, multichannel regeneration brings 0.4-dB OSNR penalty when the value of BER is 10-3, which shows the cross talk in regeneration process is negligible.

Monitoring by forward scatter radar techniques: an improved second-order analytical model

NASA Astrophysics Data System (ADS)

Falconi, Marta Tecla; Comite, Davide; Galli, Alessandro; Marzano, Frank S.; Pastina, Debora; Lombardo, Pierfrancesco

2017-10-01

In this work, a second-order phase approximation is introduced to provide an improved analytical model of the signal received in forward scatter radar systems. A typical configuration with a rectangular metallic object illuminated while crossing the baseline, in far- or near-field conditions, is considered. An improved second-order model is compared with a simplified one already proposed by the authors and based on a paraxial approximation. A phase error analysis is carried out to investigate benefits and limitations of the second-order modeling. The results are validated by developing full-wave numerical simulations implementing the relevant scattering problem on a commercial tool.

Quantitative research.

PubMed

Watson, Roger

2015-04-01

This article describes the basic tenets of quantitative research. The concepts of dependent and independent variables are addressed and the concept of measurement and its associated issues, such as error, reliability and validity, are explored. Experiments and surveys – the principal research designs in quantitative research – are described and key features explained. The importance of the double-blind randomised controlled trial is emphasised, alongside the importance of longitudinal surveys, as opposed to cross-sectional surveys. Essential features of data storage are covered, with an emphasis on safe, anonymous storage. Finally, the article explores the analysis of quantitative data, considering what may be analysed and the main uses of statistics in analysis.

Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model

NASA Technical Reports Server (NTRS)

Morris, A. Terry

1999-01-01

This paper examines various sources of error in MIT's improved top oil temperature rise over ambient temperature model and estimation process. The sources of error are the current parameter estimation technique, quantization noise, and post-processing of the transformer data. Results from this paper will show that an output error parameter estimation technique should be selected to replace the current least squares estimation technique. The output error technique obtained accurate predictions of transformer behavior, revealed the best error covariance, obtained consistent parameter estimates, and provided for valid and sensible parameters. This paper will also show that the output error technique should be used to minimize errors attributed to post-processing (decimation) of the transformer data. Models used in this paper are validated using data from a large transformer in service.

A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

NASA Astrophysics Data System (ADS)

Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

2015-12-01

The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

Baseline Error Analysis and Experimental Validation for Height Measurement of Formation Insar Satellite

NASA Astrophysics Data System (ADS)

Gao, X.; Li, T.; Zhang, X.; Geng, X.

2018-04-01

In this paper, we proposed the stochastic model of InSAR height measurement by considering the interferometric geometry of InSAR height measurement. The model directly described the relationship between baseline error and height measurement error. Then the simulation analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of baseline error to height measurement. Furthermore, the whole emulation validation of InSAR stochastic model was performed on the basis of SRTM DEM and TanDEM-X parameters. The spatial distribution characteristics and error propagation rule of InSAR height measurement were fully evaluated.

Supervised local error estimation for nonlinear image registration using convolutional neural networks

NASA Astrophysics Data System (ADS)

Eppenhof, Koen A. J.; Pluim, Josien P. W.

2017-02-01

Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

[Validation of an instrument to measure health-related quality of life in Chilean children and adolescents].

PubMed

Sepúlveda P, Rodrigo; Molina G, Temístocles; Molina C, Ramiro; Martínez N, Vania; González A, Electra; L, Myriam George; Montaño E, Rosa; Hidalgo-Rasmussen, Carlos

2013-10-01

KIDSCREEN-52 is an instrument to assess health related quality of life in children and adolescents. To culturally adapt and validate the KIDSCREEN-52 questionnaire in Chileans. Two independent translations from the English Spanish language were conciliated and retranslated to English. The conciliated version was tested during a cognitive interview to adolescents of different socioeconomic levels. The final version was validated in 7,910 school attending adolescents. In the cross-cultural adaptation, 50 of the 52 items presented low or medium levels of difficulty and a high semantic equivalence. Distribution according to gender, grades and types of schools was similar to the sample. Single ages were not affected by sex distribution. The Confirmatory Factor Analyses were: X² (1229) = 20996.7, Root Mean Square Error of Approximation = .045 and Comparative Fit Index = .96. The instrument had a Cronbach's alpha of .93. The domains had scores over 0.70 points, with the exception of the "Selfperception" domain, with a score of 0.62. The Chilean version of KIDSCREEN-52 is culturally appropriate and semantically equivalent in its English and Spanish versions (from Spain). Its reliability and validity were adequate.

An Approach to a Comprehensive Test Framework for Analysis and Evaluation of Text Line Segmentation Algorithms

PubMed Central

Brodic, Darko; Milivojevic, Dragan R.; Milivojevic, Zoran N.

2011-01-01

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures. PMID:22164106

An approach to a comprehensive test framework for analysis and evaluation of text line segmentation algorithms.

PubMed

Brodic, Darko; Milivojevic, Dragan R; Milivojevic, Zoran N

2011-01-01

The paper introduces a testing framework for the evaluation and validation of text line segmentation algorithms. Text line segmentation represents the key action for correct optical character recognition. Many of the tests for the evaluation of text line segmentation algorithms deal with text databases as reference templates. Because of the mismatch, the reliable testing framework is required. Hence, a new approach to a comprehensive experimental framework for the evaluation of text line segmentation algorithms is proposed. It consists of synthetic multi-like text samples and real handwritten text as well. Although the tests are mutually independent, the results are cross-linked. The proposed method can be used for different types of scripts and languages. Furthermore, two different procedures for the evaluation of algorithm efficiency based on the obtained error type classification are proposed. The first is based on the segmentation line error description, while the second one incorporates well-known signal detection theory. Each of them has different capabilities and convenience, but they can be used as supplements to make the evaluation process efficient. Overall the proposed procedure based on the segmentation line error description has some advantages, characterized by five measures that describe measurement procedures.

Accuracy and uncertainty analysis of soil Bbf spatial distribution estimation at a coking plant-contaminated site based on normalization geostatistical technologies.

PubMed

Liu, Geng; Niu, Junjie; Zhang, Chao; Guo, Guanlin

2015-12-01

Data distribution is usually skewed severely by the presence of hot spots in contaminated sites. This causes difficulties for accurate geostatistical data transformation. Three types of typical normal distribution transformation methods termed the normal score, Johnson, and Box-Cox transformations were applied to compare the effects of spatial interpolation with normal distribution transformation data of benzo(b)fluoranthene in a large-scale coking plant-contaminated site in north China. Three normal transformation methods decreased the skewness and kurtosis of the benzo(b)fluoranthene, and all the transformed data passed the Kolmogorov-Smirnov test threshold. Cross validation showed that Johnson ordinary kriging has a minimum root-mean-square error of 1.17 and a mean error of 0.19, which was more accurate than the other two models. The area with fewer sampling points and that with high levels of contamination showed the largest prediction standard errors based on the Johnson ordinary kriging prediction map. We introduce an ideal normal transformation method prior to geostatistical estimation for severely skewed data, which enhances the reliability of risk estimation and improves the accuracy for determination of remediation boundaries.

Highly Efficient Compression Algorithms for Multichannel EEG.

PubMed

Shaw, Laxmi; Rahman, Daleef; Routray, Aurobinda

2018-05-01

The difficulty associated with processing and understanding the high dimensionality of electroencephalogram (EEG) data requires developing efficient and robust compression algorithms. In this paper, different lossless compression techniques of single and multichannel EEG data, including Huffman coding, arithmetic coding, Markov predictor, linear predictor, context-based error modeling, multivariate autoregression (MVAR), and a low complexity bivariate model have been examined and their performances have been compared. Furthermore, a high compression algorithm named general MVAR and a modified context-based error modeling for multichannel EEG have been proposed. The resulting compression algorithm produces a higher relative compression ratio of 70.64% on average compared with the existing methods, and in some cases, it goes up to 83.06%. The proposed methods are designed to compress a large amount of multichannel EEG data efficiently so that the data storage and transmission bandwidth can be effectively used. These methods have been validated using several experimental multichannel EEG recordings of different subjects and publicly available standard databases. The satisfactory parametric measures of these methods, namely percent-root-mean square distortion, peak signal-to-noise ratio, root-mean-square error, and cross correlation, show their superiority over the state-of-the-art compression methods.

Psychometric characteristics of the Functional Assessment of Cancer Therapy-General when applied to Brazilian cancer patients: a cross-cultural adaptation and validation.

PubMed

Campos, Juliana Alvares Duarte Bonini; Spexoto, Maria Cláudia Bernardes; Serrano, Sergio Vicente; Maroco, João

2016-01-13

The psychometric properties of an instrument should be evaluated routinely when using different samples. This study evaluated the psychometric properties of the Functional Assessment of Cancer Therapy-General (FACT-G) when applied to a sample of Brazilian cancer patients. The face, content, and construct (factorial, convergent, and discriminant) validities of the FACT-G were estimated. Confirmatory factor analysis (CFA) was conducted the ratio chi-square by degrees of freedom (χ (2)/df), the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA) as indices. The invariance of the best model was assessed with multi-group analysis using the difference of chi-squares method (Δχ(2)). Convergent validity was assessed using Average Variance Extracted (AVE) and discriminant validity was determined via correlational analysis. Internal consistency was assessed using the Cronbach's alpha (α) coefficient, and the Composite Reliability (CR) was estimated. A total of 975 cancer patients participated in the study, with a mean age of 53.3 (SD = 13.0) years. Of these participants, 61.5 % were women. In CFA, five correlations between errors were included to fit the FACT-G to the sample (χ (2)/df = 8.611, CFI = .913, TLI = .902, RMSEA = .088). The model did not indicate invariant independent samples (Δχ(2): μ: p < .001, i: p < .958, Cov: p < .001, Res: p < .001). While there was adequate convergent validity for the physical well-being (AVE = .54) and social and family Well-being factors (AVE = .55), there was low convergent validity for the other factors. Reliability was adequate (CR = .76-.89 and α = .71-.82). Functional well-being, emotional well-being, and physical well-being were the factors that demonstrated a strong contribution to patients' health-related quality of life (β = -.99, .88, and .64, respectively). The FACT-G was found to be a valid and reliable assessment of health-related quality of life in a Brazilian sample of patients with cancer.

Validation of the Malay Version of the Inventory of Functional Status after Childbirth Questionnaire

PubMed Central

Noor, Norhayati Mohd; Aziz, Aniza Abd.; Mostapa, Mohd Rosmizaki; Awang, Zainudin

2015-01-01

Objective. This study was designed to examine the psychometric properties of Malay version of the Inventory of Functional Status after Childbirth (IFSAC). Design. A cross-sectional study. Materials and Methods. A total of 108 postpartum mothers attending Obstetrics and Gynaecology Clinic, in a tertiary teaching hospital in Malaysia, were involved. Construct validity and internal consistency were performed after the translation, content validity, and face validity process. The data were analyzed using Analysis of Moment Structure version 18 and Statistical Packages for the Social Sciences version 20. Results. The final model consists of four constructs, namely, infant care, personal care, household activities, and social and community activities, with 18 items demonstrating acceptable factor loadings, domain to domain correlation, and best fit (Chi-squared/degree of freedom = 1.678; Tucker-Lewis index = 0.923; comparative fit index = 0.936; and root mean square error of approximation = 0.080). Composite reliability and average variance extracted of the domains ranged from 0.659 to 0.921 and from 0.499 to 0.628, respectively. Conclusion. The study suggested that the four-factor model with 18 items of the Malay version of IFSAC was acceptable to be used to measure functional status after childbirth because it is valid, reliable, and simple. PMID:25667932

Instruments to assess patients with rotator cuff pathology: a systematic review of measurement properties.

PubMed

Longo, Umile Giuseppe; Saris, Daniël; Poolman, Rudolf W; Berton, Alessandra; Denaro, Vincenzo

2012-10-01

The aims of this study were to obtain an overview of the methodological quality of studies on the measurement properties of rotator cuff questionnaires and to describe how well various aspects of the design and statistical analyses of studies on measurement properties are performed. A systematic review of published studies on the measurement properties of rotator cuff questionnaires was performed. Two investigators independently rated the quality of the studies using the Consensus-based Standards for the selection of health Measurement Instruments checklist. This checklist was developed in an international Delphi consensus study. Sixteen studies were included, in which two measurement instruments were evaluated, namely the Western Ontario Rotator Cuff Index and the Rotator Cuff Quality-of-Life Measure. The methodological quality of the included studies was adequate on some properties (construct validity, reliability, responsiveness, internal consistency, and translation) but need to be improved on other aspects. The most important methodological aspects that need to be developed are as follows: measurement error, content validity, structural validity, cross-cultural validity, criterion validity, and interpretability. Considering the importance of adequate measurement properties, it is concluded that, in the field of rotator cuff pathology, there is room for improvement in the methodological quality of studies measurement properties. II.

Cross-cultural adaptation and validation of the Turkish version of the pain catastrophizing scale among patients with ankylosing spondylitis

PubMed Central

İlçin, Nursen; Gürpınar, Barış; Bayraktar, Deniz; Savcı, Sema; Çetin, Pınar; Sarı, İsmail; Akkoç, Nurullah

2016-01-01

[Purpose] This study describes the cultural adaptation, validation, and reliability of the Turkish version of the Pain Catastrophizing Scale in patients with ankylosing spondylitis. [Methods] The validity of the Turkish version of the Pain Catastrophizing Scale was assessed by evaluating data quality (missing data and floor and ceiling effects), principal components analysis, internal consistency (Cronbach’s alpha), and construct validity (Spearman’s rho). Reproducibility analyses included standard measurement error, minimum detectable change, limits of agreement, and intraclass correlation coefficients. [Results] Sixty-four adult patients with ankylosing spondylitis with a mean age of 42.2 years completed the study. Factor analysis revealed that all questionnaire items could be grouped into two factors. Excellent internal consistency was found, with a Chronbach’s alpha value of 0.95. Reliability analyses showed an intraclass correlation coefficient (95% confidence interval) of 0.96 for the total score. There was a low correlation coefficient between the Turkish version of the Pain Catastrophizing Scale and body mass index, pain levels at rest and during activity, health-related quality of life, and fear and avoidance behaviors. [Conclusion] The results of this study indicate that the Turkish version of the Pain Catastrophizing Scale is a valid and reliable clinical and research tool for patients with ankylosing spondylitis. PMID:26957778

Cross-cultural validation and psychometric testing of the Norwegian version of the TeamSTEPPS® teamwork perceptions questionnaire.

PubMed

Ballangrud, Randi; Husebø, Sissel Eikeland; Hall-Lord, Marie Louise

2017-12-02

Teamwork is an integrated part of today's specialized and complex healthcare and essential to patient safety, and is considered as a core competency to improve twenty-first century healthcare. Teamwork measurements and evaluations show promising results to promote good team performance, and are recommended for identifying areas for improvement. The validated TeamSTEPPS® Teamwork Perception Questionnaire (T-TPQ) was found suitable for cross-cultural validation and testing in a Norwegian context. T-TPQ is a self-report survey that examines five dimensions of perception of teamwork within healthcare settings. The aim of the study was to translate and cross-validate the T-TPQ into Norwegian, and test the questionnaire for psychometric properties among healthcare personnel. The T-TPQ was translated and adapted to a Norwegian context according to a model of a back-translation process. A total of 247 healthcare personnel representing different professionals and hospital settings responded to the questionnaire. A confirmatory factor analysis was carried out to test the factor structure. Cronbach's alpha was used to establish internal consistency, and an Intraclass Correlation Coefficient was used to assess the test - retest reliability. A confirmatory factor analysis showed an acceptable fitting model (χ 2 (df) 969.46 (546), p < 0.001, Root Mean Square Error of Approximation (RMSEA) = 0.056, Tucker-Lewis Index (TLI) = 0.88, Comparative fit index (CFI) = 0.89, which indicates that each set of the items that was supposed to accompany each teamwork dimension clearly represents that specific construct. The Cronbach's alpha demonstrated acceptable values on the five subscales (0.786-0.844), and test-retest showed a reliability parameter, with Intraclass Correlation Coefficient scores from 0.672 to 0.852. The Norwegian version of T-TPQ was considered to be acceptable regarding the validity and reliability for measuring Norwegian individual healthcare personnel's perception of group level teamwork within their unit. However, it needs to be further tested, preferably in a larger sample and in different clinical settings.

Optical dosimetry probes to validate Monte Carlo and empirical-method-based NIR dose planning in the brain.

PubMed

Verleker, Akshay Prabhu; Shaffer, Michael; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M

2016-12-01

A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R²0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.

Building a geological reference platform using sequence stratigraphy combined with geostatistical tools

NASA Astrophysics Data System (ADS)

Bourgine, Bernard; Lasseur, Éric; Leynet, Aurélien; Badinier, Guillaume; Ortega, Carole; Issautier, Benoit; Bouchet, Valentin

2015-04-01

In 2012 BRGM launched an extensive program to build the new French Geological Reference platform (RGF). Among the objectives of this program is to provide the public with validated, reliable and 3D-consistent geological data, with estimation of uncertainty. Approx. 100,000 boreholes over the whole French national territory provide a preliminary interpretation in terms of depths of main geological interfaces, but with an unchecked, unknown and often low reliability. The aim of this paper is to present the procedure that has been tested on two areas in France, in order to validate (or not) these boreholes, with the aim of being generalized as much as possible to the nearly 100,000 boreholes waiting for validation. The approach is based on the following steps, and includes the management of uncertainty at different steps: (a) Selection of a loose network of boreholes owning a logging or coring information enabling a reliable interpretation. This first interpretation is based on the correlation of well log data and allows defining 3D sequence stratigraphic framework identifying isochronous surfaces. A litho-stratigraphic interpretation is also performed. Be "A" the collection of all boreholes used for this step (typically 3 % of the total number of holes to be validated) and "B" the other boreholes to validate, (b) Geostatistical analysis of characteristic geological interfaces. The analysis is carried out firstly on the "A" type data (to validate the variogram model), then on the "B" type data and at last on "B" knowing "A". It is based on cross-validation tests and evaluation of the uncertainty associated to each geological interface. In this step, we take into account inequality constraints provided by boreholes that do not intersect all interfaces, as well as the "litho-stratigraphic pile" defining the formations and their relationships (depositing surfaces or erosion). The goal is to identify quickly and semi-automatically potential errors among the data, up to the geologist to check and correct the anomalies, (c) Consistency tests are also used to verify the appropriateness of interpretations towards other constraints (geological map, maximal formation extension limits, digital terrain model ...), (d) Construction of a 3D geological model from "A"+ "B" boreholes: continuous surfaces representation makes it possible to assess the overall consistency and to validate or invalidate interpretations. Standard-deviation maps allow visualizing areas where data from available but not yet validated boreholes could be added to reduce uncertainty. Maps of absolute or relative errors help to quantify and visualize model uncertainty. This procedure helps to quickly identify the main errors in the data. It guarantees rationalization, reproducibility and traceability of the various stages of validation. Automation aspect is obviously important when it comes to dealing with datasets that can contain tens of thousands of surveys. For this, specific tools have been developed by BRGM (GDM/ MultiLayer software, R scripts, GIS tools).

Cross-mode bioelectrical impedance analysis in a standing position for estimating fat-free mass validated against dual-energy x-ray absorptiometry.

PubMed

Huang, Ai-Chun; Chen, Yu-Yawn; Chuang, Chih-Lin; Chiang, Li-Ming; Lu, Hsueh-Kuan; Lin, Hung-Chi; Chen, Kuen-Tsann; Hsiao, An-Chi; Hsieh, Kuen-Chang

2015-11-01

Bioelectrical impedance analysis (BIA) is commonly used to assess body composition. Cross-mode (left hand to right foot, Z(CR)) BIA presumably uses the longest current path in the human body, which may generate better results when estimating fat-free mass (FFM). We compared the cross-mode with the hand-to-foot mode (right hand to right foot, Z(HF)) using dual-energy x-ray absorptiometry (DXA) as the reference. We hypothesized that when comparing anthropometric parameters using stepwise regression analysis, the impedance value from the cross-mode analysis would have better prediction accuracy than that from the hand-to-foot mode analysis. We studied 264 men and 232 women (mean ages, 32.19 ± 14.95 and 34.51 ± 14.96 years, respectively; mean body mass indexes, 24.54 ± 3.74 and 23.44 ± 4.61 kg/m2, respectively). The DXA-measured FFMs in men and women were 58.85 ± 8.15 and 40.48 ± 5.64 kg, respectively. Multiple stepwise linear regression analyses were performed to construct sex-specific FFM equations. The correlations of FFM measured by DXA vs. FFM from hand-to-foot mode and estimated FFM by cross-mode were 0.85 and 0.86 in women, with standard errors of estimate of 2.96 and 2.92 kg, respectively. In men, they were 0.91 and 0.91, with standard errors of the estimates of 3.34 and 3.48 kg, respectively. Bland-Altman plots showed limits of agreement of -6.78 to 6.78 kg for FFM from hand-to-foot mode and -7.06 to 7.06 kg for estimated FFM by cross-mode for men, and -5.91 to 5.91 and -5.84 to 5.84 kg, respectively, for women. Paired t tests showed no significant differences between the 2 modes (P > .05). Hence, cross-mode BIA appears to represent a reasonable and practical application for assessing FFM in Chinese populations. Copyright © 2015 Elsevier Inc. All rights reserved.

Cross-calibration of A.M. constellation sensors for long term monitoring of land surface processes

USGS Publications Warehouse

Meyer, D.; Chander, G.

2006-01-01

Data from multiple sensors must be used together to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products derived from different sensors (e.g., vegetation cover, albedo, surface temperature) can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectro-radiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Cross-calibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study extends on a previous study of Terra/MODIS and Landsat/ETM+ cross calibration by including the Terra/ASTER and EO-1/ALI sensors, exploring the impacts of cross-calibrating sensors when conditions described above are met to some degree but not perfectly. Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. Due to problems with direct calibration of ASTER data, linear fits were developed between ASTER and ETM+ to assess the impacts of spectral bandpass differences between the two systems. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

Increasing reliability of Gauss-Kronrod quadrature by Eratosthenes' sieve method

NASA Astrophysics Data System (ADS)

Adam, Gh.; Adam, S.

2001-04-01

The reliability of the local error estimates returned by the Gauss-Kronrod quadrature rules can be raised up to the theoretical 100% rate of success, under error estimate sharpening, provided a number of natural validating conditions are required. The self-validating scheme of the local error estimates, which is easy to implement and adds little supplementary computing effort, strengthens considerably the correctness of the decisions within the automatic adaptive quadrature.

Quantitative determination of amorphous cyclosporine in crystalline cyclosporine samples by Fourier transform infrared spectroscopy.

PubMed

Bertacche, Vittorio; Pini, Elena; Stradi, Riccardo; Stratta, Fabio

2006-01-01

The purpose of this study is the development of a quantification method to detect the amount of amorphous cyclosporine using Fourier transform infrared (FTIR) spectroscopy. The mixing of different percentages of crystalline cyclosporine with amorphous cyclosporine was used to obtain a set of standards, composed of cyclosporine samples characterized by different percentages of amorphous cyclosporine. Using a wavelength range of 450-4,000 cm(-1), FTIR spectra were obtained from samples in potassium bromide pellets and then a partial least squares (PLS) model was exploited to correlate the features of the FTIR spectra with the percentage of amorphous cyclosporine in the samples. This model gave a standard error of estimate (SEE) of 0.3562, with an r value of 0.9971 and a standard error of prediction (SEP) of 0.4168, which derives from the cross validation function used to check the precision of the model. Statistical values reveal the applicability of the method to the quantitative determination of amorphous cyclosporine in crystalline cyclosporine samples.

Use of Single-Cysteine Variants for Trapping Transient States in DNA Mismatch Repair.

PubMed

Friedhoff, Peter; Manelyte, Laura; Giron-Monzon, Luis; Winkler, Ines; Groothuizen, Flora S; Sixma, Titia K

2017-01-01

DNA mismatch repair (MMR) is necessary to prevent incorporation of polymerase errors into the newly synthesized DNA strand, as they would be mutagenic. In humans, errors in MMR cause a predisposition to cancer, called Lynch syndrome. The MMR process is performed by a set of ATPases that transmit, validate, and couple information to identify which DNA strand requires repair. To understand the individual steps in the repair process, it is useful to be able to study these large molecular machines structurally and functionally. However, the steps and states are highly transient; therefore, the methods to capture and enrich them are essential. Here, we describe how single-cysteine variants can be used for specific cross-linking and labeling approaches that allow trapping of relevant transient states. Analysis of these defined states in functional and structural studies is instrumental to elucidate the molecular mechanism of this important DNA MMR process. © 2017 Elsevier Inc. All rights reserved.

Desert Test Site Uniformity Analysis

NASA Technical Reports Server (NTRS)

Kerola, Dana X.; Bruegge, Carol J.

2009-01-01

Desert test sites such as Railroad Valley (RRV) Nevada, Egypt-1, and Libya-4 are commonly targeted to assess the on-orbit radiometric performance of sensors. Railroad Valley is used for vicarious calibration experiments, where a field-team makes ground measurements to produce accurate estimates of top-of-atmosphere (TOA) radiances. The Sahara desert test sites are not instrumented, but provide a stable target that can be used for sensor cross-comparisons, or for stability monitoring of a single sensor. These sites are of interest to NASA's Atmospheric Carbon Observation from Space (ACOS) and JAXA's Greenhouse Gas Observation SATellite (GOSAT) programs. This study assesses the utility of these three test sites to the ACOS and GOSAT calibration teams. To simulate errors in sensor-measured radiance with pointing errors, simulated data have been created using MODIS Aqua data. MODIS data are further utilized to validate the campaign data acquired from June 22 through July 5, 2009. The first GOSAT vicarious calibration experiment was conducted during this timeframe.

Prediction of fat-free body mass from bioelectrical impedance and anthropometry among 3-year-old children using DXA

PubMed Central

Ejlerskov, Katrine T.; Jensen, Signe M.; Christensen, Line B.; Ritz, Christian; Michaelsen, Kim F.; Mølgaard, Christian

2014-01-01

For 3-year-old children suitable methods to estimate body composition are sparse. We aimed to develop predictive equations for estimating fat-free mass (FFM) from bioelectrical impedance (BIA) and anthropometry using dual-energy X-ray absorptiometry (DXA) as reference method using data from 99 healthy 3-year-old Danish children. Predictive equations were derived from two multiple linear regression models, a comprehensive model (height2/resistance (RI), six anthropometric measurements) and a simple model (RI, height, weight). Their uncertainty was quantified by means of 10-fold cross-validation approach. Prediction error of FFM was 3.0% for both equations (root mean square error: 360 and 356 g, respectively). The derived equations produced BIA-based prediction of FFM and FM near DXA scan results. We suggest that the predictive equations can be applied in similar population samples aged 2–4 years. The derived equations may prove useful for studies linking body composition to early risk factors and early onset of obesity. PMID:24463487

Prediction of fat-free body mass from bioelectrical impedance and anthropometry among 3-year-old children using DXA.

PubMed

Ejlerskov, Katrine T; Jensen, Signe M; Christensen, Line B; Ritz, Christian; Michaelsen, Kim F; Mølgaard, Christian

2014-01-27

For 3-year-old children suitable methods to estimate body composition are sparse. We aimed to develop predictive equations for estimating fat-free mass (FFM) from bioelectrical impedance (BIA) and anthropometry using dual-energy X-ray absorptiometry (DXA) as reference method using data from 99 healthy 3-year-old Danish children. Predictive equations were derived from two multiple linear regression models, a comprehensive model (height(2)/resistance (RI), six anthropometric measurements) and a simple model (RI, height, weight). Their uncertainty was quantified by means of 10-fold cross-validation approach. Prediction error of FFM was 3.0% for both equations (root mean square error: 360 and 356 g, respectively). The derived equations produced BIA-based prediction of FFM and FM near DXA scan results. We suggest that the predictive equations can be applied in similar population samples aged 2-4 years. The derived equations may prove useful for studies linking body composition to early risk factors and early onset of obesity.

Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

NASA Astrophysics Data System (ADS)

Dasgupta, Hirak

2016-12-01

The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

Body composition by hydrometry (deuterium oxide dilution) and bioelectrical impedance in subjects aged >60 y from rural regions of Cuba, Chile and Mexico.

PubMed

Valencia, M E; Alemán-Mateo, H; Salazar, G; Hernández Triana, M

2003-07-01

In Latin American and Caribbean countries such as Chile, Mexico and Cuba, the population over 60 y has increased steadily. In this age group, there is scarce information about body composition, particularly for those living in rural areas. The purpose of this study was to determine body composition in free-living and healthy elderly subjects >60 y from rural areas of Chile, Cuba and Mexico using deuterium oxide dilution and bioelectrical impedance (BIA) and to develop and cross-validate a predictive equation for this group of subjects by BIA for future use as a field technique. The study included 133 healthy subjects (73 males and 60 females) >60 y from rural regions of Cuba, Chile and Mexico. Total body water, body weight, height and other anthropometric and BIA variables (resistance and reactance) were measured. Total body water was determined by deuterium oxide dilution, and fat-free mass (FFM)/fat mass were derived from this measurement. The total sample was used in a split-sample internal cross-validation. BIA and other anthropometric variables were integrated to multiple regression model to design the best predictive equation, which was validated in the other sample. ANOVA, multiple regression and Bland and Altman's procedure were used to analyze the data. Body weight, percentage of fat and fat-free mass were lower in the Cuban men and women compared with Chilean and Mexican men and women. The best predictive equation of the FFM was: FFM kg=(-7.71+(H(2)/R x 0.49)+(country or ethnicity x 1.12)+(body weight x 0.27)+(sex x 3.49)+(Xc x 0.13)), where H(2) is height(2) (cm); R is resistance (Omega); country: Chile=1, Mexico=2 and Cuba=3; sex: women=0 and men=1; body weight (kg) and Xc is reactance (Omega). R(2) was 0.944 and the root mean square error (RMSE) was 2.08 kg. The mean+/-s.d. of FFM prediction was 44.2+/-9.2 vs 44.6+/-10.1. The results of cross-validation showed no significant difference with the line of identity, showing that the predicted equation was accurate. The intercept (=-0.32) was not significantly different from zero (P=0.89) and the slope (=1.02) not significantly different from 1.0 (P>0.9). The R(2) was 0.86, RMSE=3.86 kg of FFM and the pure error was 3.83. The new BIA equation is accurate, precise and showed good agreement. The use of this equation could improve the estimates of body composition for the elderly population for these regions, as well as enhancing the opportunity to conduct studies in the elderly population from Latin America.

Validity and Reliability of a Digital Inclinometer to Assess Knee Joint Position Sense in an Open Kinetic Chain.

PubMed

Romero-Franco, Natalia; Montaño-Munuera, Juan Antonio; Fernández-Domínguez, Juan Carlos; Jiménez-Reyes, Pedro

2017-12-18

New methods are being validated to easily evaluate the knee joint position sense (JPS) due to its role in sports movement and the risk of injury. However, no studies to date have considered the open kinetic chain (OKC) technique, despite the biomechanical differences compared to closed kinetic chain movements. To analyze the validity and reliability of a digital inclinometer to measure the knee JPS in the OKC movement. The validity, inter-tester and intra-tester reliability of a digital inclinometer for measuring knee JPS were evaluated. Sports research laboratory. Eighteen athletes (11 males and 7 females; 28.4 ± 6.6 years; 71.9 ± 14.0 kg; 1.77 ± 0.09 m; 22.8 ± 3.2 kg/m 2 ) voluntary participated in this study. Absolute angular error (AAE), relative angular error (RAE) and variable angular error (VAE) of knee JPS in an OKC. Intraclass correlation coefficient (ICC) and standard error of the mean (SEM) were calculated to determine the validity and reliability of the inclinometer. Data showed excellent validity of the inclinometer to obtain proprioceptive errors compared to the video analysis in JPS tasks (AAE: ICC = 0.981, SEM = 0.08; RAE: ICC = 0.974, SEM = 0.12; VAE: ICC = 0.973, SEM = 0.07). Inter-tester reliability was also excellent for all the proprioceptive errors (AAE: ICC = 0.967, SEM = 0.04; RAE: ICC = 0.974, SEM = 0.03; VAE: ICC = 0.939, SEM = 0.08). Similar results were obtained for intra-tester reliability (AAE: ICC = 0.861, SEM = 0.1; RAE: ICC = 0.894, SEM = 0.1; VAE: ICC = 0.700, SEM = 0.2). The digital inclinometer is a valid and reliable method to assess the knee JPS in OKC. Sport professionals may evaluate the knee JPS to monitor its deterioration during training or improvements throughout the rehabilitation process.

Causal inference with measurement error in outcomes: Bias analysis and estimation methods.

PubMed

Shu, Di; Yi, Grace Y

2017-01-01

Inverse probability weighting estimation has been popularly used to consistently estimate the average treatment effect. Its validity, however, is challenged by the presence of error-prone variables. In this paper, we explore the inverse probability weighting estimation with mismeasured outcome variables. We study the impact of measurement error for both continuous and discrete outcome variables and reveal interesting consequences of the naive analysis which ignores measurement error. When a continuous outcome variable is mismeasured under an additive measurement error model, the naive analysis may still yield a consistent estimator; when the outcome is binary, we derive the asymptotic bias in a closed-form. Furthermore, we develop consistent estimation procedures for practical scenarios where either validation data or replicates are available. With validation data, we propose an efficient method for estimation of average treatment effect; the efficiency gain is substantial relative to usual methods of using validation data. To provide protection against model misspecification, we further propose a doubly robust estimator which is consistent even when either the treatment model or the outcome model is misspecified. Simulation studies are reported to assess the performance of the proposed methods. An application to a smoking cessation dataset is presented.

Genomic Prediction Accounting for Residual Heteroskedasticity.

PubMed

Ou, Zhining; Tempelman, Robert J; Steibel, Juan P; Ernst, Catherine W; Bates, Ronald O; Bello, Nora M

2015-11-12

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. Copyright © 2016 Ou et al.

Cross-validation of the Student Perceptions of Team-Based Learning Scale in the United States.

PubMed

Lein, Donald H; Lowman, John D; Eidson, Christopher A; Yuen, Hon K

2017-01-01

The purpose of this study was to cross-validate the factor structure of the previously developed Student Perceptions of Team-Based Learning (TBL) Scale among students in an entry-level doctor of physical therapy (DPT) program in the United States. Toward the end of the semester in 2 patient/client management courses taught using TBL, 115 DPT students completed the Student Perceptions of TBL Scale, with a response rate of 87%. Principal component analysis (PCA) and confirmatory factor analysis (CFA) were conducted to replicate and confirm the underlying factor structure of the scale. Based on the PCA for the validation sample, the original 2-factor structure (preference for TBL and preference for teamwork) of the Student Perceptions of TBL Scale was replicated. The overall goodness-of-fit indices from the CFA suggested that the original 2-factor structure for the 15 items of the scale demonstrated a good model fit (comparative fit index, 0.95; non-normed fit index/Tucker-Lewis index, 0.93; root mean square error of approximation, 0.06; and standardized root mean square residual, 0.07). The 2 factors demonstrated high internal consistency (alpha= 0.83 and 0.88, respectively). DPT students taught using TBL viewed the factor of preference for teamwork more favorably than preference for TBL. Our findings provide evidence supporting the replicability of the internal structure of the Student Perceptions of TBL Scale when assessing perceptions of TBL among DPT students in patient/client management courses.

Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2006-10-01

Gene selection algorithms for cancer classification, based on the expression of a small number of biomarker genes, have been the subject of considerable research in recent years. Shevade and Keerthi propose a gene selection algorithm based on sparse logistic regression (SLogReg) incorporating a Laplace prior to promote sparsity in the model parameters, and provide a simple but efficient training procedure. The degree of sparsity obtained is determined by the value of a regularization parameter, which must be carefully tuned in order to optimize performance. This normally involves a model selection stage, based on a computationally intensive search for the minimizer of the cross-validation error. In this paper, we demonstrate that a simple Bayesian approach can be taken to eliminate this regularization parameter entirely, by integrating it out analytically using an uninformative Jeffrey's prior. The improved algorithm (BLogReg) is then typically two or three orders of magnitude faster than the original algorithm, as there is no longer a need for a model selection step. The BLogReg algorithm is also free from selection bias in performance estimation, a common pitfall in the application of machine learning algorithms in cancer classification. The SLogReg, BLogReg and Relevance Vector Machine (RVM) gene selection algorithms are evaluated over the well-studied colon cancer and leukaemia benchmark datasets. The leave-one-out estimates of the probability of test error and cross-entropy of the BLogReg and SLogReg algorithms are very similar, however the BlogReg algorithm is found to be considerably faster than the original SLogReg algorithm. Using nested cross-validation to avoid selection bias, performance estimation for SLogReg on the leukaemia dataset takes almost 48 h, whereas the corresponding result for BLogReg is obtained in only 1 min 24 s, making BLogReg by far the more practical algorithm. BLogReg also demonstrates better estimates of conditional probability than the RVM, which are of great importance in medical applications, with similar computational expense. A MATLAB implementation of the sparse logistic regression algorithm with Bayesian regularization (BLogReg) is available from http://theoval.cmp.uea.ac.uk/~gcc/cbl/blogreg/

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.

Avoiding and identifying errors in health technology assessment models: qualitative study and methodological review.

PubMed

Chilcott, J; Tappenden, P; Rawdin, A; Johnson, M; Kaltenthaler, E; Paisley, S; Papaioannou, D; Shippam, A

2010-05-01

Health policy decisions must be relevant, evidence-based and transparent. Decision-analytic modelling supports this process but its role is reliant on its credibility. Errors in mathematical decision models or simulation exercises are unavoidable but little attention has been paid to processes in model development. Numerous error avoidance/identification strategies could be adopted but it is difficult to evaluate the merits of strategies for improving the credibility of models without first developing an understanding of error types and causes. The study aims to describe the current comprehension of errors in the HTA modelling community and generate a taxonomy of model errors. Four primary objectives are to: (1) describe the current understanding of errors in HTA modelling; (2) understand current processes applied by the technology assessment community for avoiding errors in development, debugging and critically appraising models for errors; (3) use HTA modellers' perceptions of model errors with the wider non-HTA literature to develop a taxonomy of model errors; and (4) explore potential methods and procedures to reduce the occurrence of errors in models. It also describes the model development process as perceived by practitioners working within the HTA community. A methodological review was undertaken using an iterative search methodology. Exploratory searches informed the scope of interviews; later searches focused on issues arising from the interviews. Searches were undertaken in February 2008 and January 2009. In-depth qualitative interviews were performed with 12 HTA modellers from academic and commercial modelling sectors. All qualitative data were analysed using the Framework approach. Descriptive and explanatory accounts were used to interrogate the data within and across themes and subthemes: organisation, roles and communication; the model development process; definition of error; types of model error; strategies for avoiding errors; strategies for identifying errors; and barriers and facilitators. There was no common language in the discussion of modelling errors and there was inconsistency in the perceived boundaries of what constitutes an error. Asked about the definition of model error, there was a tendency for interviewees to exclude matters of judgement from being errors and focus on 'slips' and 'lapses', but discussion of slips and lapses comprised less than 20% of the discussion on types of errors. Interviewees devoted 70% of the discussion to softer elements of the process of defining the decision question and conceptual modelling, mostly the realms of judgement, skills, experience and training. The original focus concerned model errors, but it may be more useful to refer to modelling risks. Several interviewees discussed concepts of validation and verification, with notable consistency in interpretation: verification meaning the process of ensuring that the computer model correctly implemented the intended model, whereas validation means the process of ensuring that a model is fit for purpose. Methodological literature on verification and validation of models makes reference to the Hermeneutic philosophical position, highlighting that the concept of model validation should not be externalized from the decision-makers and the decision-making process. Interviewees demonstrated examples of all major error types identified in the literature: errors in the description of the decision problem, in model structure, in use of evidence, in implementation of the model, in operation of the model, and in presentation and understanding of results. The HTA error classifications were compared against existing classifications of model errors in the literature. A range of techniques and processes are currently used to avoid errors in HTA models: engaging with clinical experts, clients and decision-makers to ensure mutual understanding, producing written documentation of the proposed model, explicit conceptual modelling, stepping through skeleton models with experts, ensuring transparency in reporting, adopting standard housekeeping techniques, and ensuring that those parties involved in the model development process have sufficient and relevant training. Clarity and mutual understanding were identified as key issues. However, their current implementation is not framed within an overall strategy for structuring complex problems. Some of the questioning may have biased interviewees responses but as all interviewees were represented in the analysis no rebalancing of the report was deemed necessary. A potential weakness of the literature review was its focus on spreadsheet and program development rather than specifically on model development. It should also be noted that the identified literature concerning programming errors was very narrow despite broad searches being undertaken. Published definitions of overall model validity comprising conceptual model validation, verification of the computer model, and operational validity of the use of the model in addressing the real-world problem are consistent with the views expressed by the HTA community and are therefore recommended as the basis for further discussions of model credibility. Such discussions should focus on risks, including errors of implementation, errors in matters of judgement and violations. Discussions of modelling risks should reflect the potentially complex network of cognitive breakdowns that lead to errors in models and existing research on the cognitive basis of human error should be included in an examination of modelling errors. There is a need to develop a better understanding of the skills requirements for the development, operation and use of HTA models. Interaction between modeller and client in developing mutual understanding of a model establishes that model's significance and its warranty. This highlights that model credibility is the central concern of decision-makers using models so it is crucial that the concept of model validation should not be externalized from the decision-makers and the decision-making process. Recommendations for future research would be studies of verification and validation; the model development process; and identification of modifications to the modelling process with the aim of preventing the occurrence of errors and improving the identification of errors in models.

Robust colour calibration of an imaging system using a colour space transform and advanced regression modelling.

PubMed

Jackman, Patrick; Sun, Da-Wen; Elmasry, Gamal

2012-08-01

A new algorithm for the conversion of device dependent RGB colour data into device independent L*a*b* colour data without introducing noticeable error has been developed. By combining a linear colour space transform and advanced multiple regression methodologies it was possible to predict L*a*b* colour data with less than 2.2 colour units of error (CIE 1976). By transforming the red, green and blue colour components into new variables that better reflect the structure of the L*a*b* colour space, a low colour calibration error was immediately achieved (ΔE(CAL) = 14.1). Application of a range of regression models on the data further reduced the colour calibration error substantially (multilinear regression ΔE(CAL) = 5.4; response surface ΔE(CAL) = 2.9; PLSR ΔE(CAL) = 2.6; LASSO regression ΔE(CAL) = 2.1). Only the PLSR models deteriorated substantially under cross validation. The algorithm is adaptable and can be easily recalibrated to any working computer vision system. The algorithm was tested on a typical working laboratory computer vision system and delivered only a very marginal loss of colour information ΔE(CAL) = 2.35. Colour features derived on this system were able to safely discriminate between three classes of ham with 100% correct classification whereas colour features measured on a conventional colourimeter were not. Copyright © 2012 Elsevier Ltd. All rights reserved.

Models for H₃ receptor antagonist activity of sulfonylurea derivatives.

PubMed

Khatri, Naveen; Madan, A K

2014-03-01

The histamine H₃ receptor has been perceived as an auspicious target for the treatment of various central and peripheral nervous system diseases. In present study, a wide variety of 60 2D and 3D molecular descriptors (MDs) were successfully utilized for the development of models for the prediction of antagonist activity of sulfonylurea derivatives for histamine H₃ receptors. Models were developed through decision tree (DT), random forest (RF) and moving average analysis (MAA). Dragon software version 6.0.28 was employed for calculation of values of diverse MDs of each analogue involved in the data set. The DT classified and correctly predicted the input data with an impressive non-error rate of 94% in the training set and 82.5% during cross validation. RF correctly classified the analogues into active and inactive with a non-error rate of 79.3%. The MAA based models predicted the antagonist histamine H₃ receptor activity with non-error rate up to 90%. Active ranges of the proposed MAA based models not only exhibited high potency but also showed improved safety as indicated by relatively high values of selectivity index. The statistical significance of the models was assessed through sensitivity, specificity, non-error rate, Matthew's correlation coefficient and intercorrelation analysis. Proposed models offer vast potential for providing lead structures for development of potent but safe H₃ receptor antagonist sulfonylurea derivatives. Copyright © 2013 Elsevier Inc. All rights reserved.

Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma.

PubMed

Zhang, Bin; He, Xin; Ouyang, Fusheng; Gu, Dongsheng; Dong, Yuhao; Zhang, Lu; Mo, Xiaokai; Huang, Wenhui; Tian, Jie; Zhang, Shuixing

2017-09-10

We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failure and distant failure in advanced nasopharyngeal carcinoma (NPC). We enrolled 110 patients with advanced NPC. A total of 970 radiomic features were extracted from MRI images for each patient. Six feature selection methods and nine classification methods were evaluated in terms of their performance. We applied the 10-fold cross-validation as the criterion for feature selection and classification. We repeated each combination for 50 times to obtain the mean area under the curve (AUC) and test error. We observed that the combination methods Random Forest (RF) + RF (AUC, 0.8464 ± 0.0069; test error, 0.3135 ± 0.0088) had the highest prognostic performance, followed by RF + Adaptive Boosting (AdaBoost) (AUC, 0.8204 ± 0.0095; test error, 0.3384 ± 0.0097), and Sure Independence Screening (SIS) + Linear Support Vector Machines (LSVM) (AUC, 0.7883 ± 0.0096; test error, 0.3985 ± 0.0100). Our radiomics study identified optimal machine-learning methods for the radiomics-based prediction of local failure and distant failure in advanced NPC, which could enhance the applications of radiomics in precision oncology and clinical practice. Copyright © 2017 Elsevier B.V. All rights reserved.

Quality assurance for online adapted treatment plans: Benchmarking and delivery monitoring simulation

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

Li, Taoran, E-mail: taoran.li.duke@gmail.com; Wu, Qiuwen; Yang, Yun

Purpose: An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. Methods: The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system wasmore » designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system’s performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Results: Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system’s ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. Conclusions: The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.« less

Quality assurance for online adapted treatment plans: benchmarking and delivery monitoring simulation.

PubMed

Li, Taoran; Wu, Qiuwen; Yang, Yun; Rodrigues, Anna; Yin, Fang-Fang; Jackie Wu, Q

2015-01-01

An important challenge facing online adaptive radiation therapy is the development of feasible and efficient quality assurance (QA). This project aimed to validate the deliverability of online adapted plans and develop a proof-of-concept online delivery monitoring system for online adaptive radiation therapy QA. The first part of this project benchmarked automatically online adapted prostate treatment plans using traditional portal dosimetry IMRT QA. The portal dosimetry QA results of online adapted plans were compared to original (unadapted) plans as well as randomly selected prostate IMRT plans from our clinic. In the second part, an online delivery monitoring system was designed and validated via a simulated treatment with intentional multileaf collimator (MLC) errors. This system was based on inputs from the dynamic machine information (DMI), which continuously reports actual MLC positions and machine monitor units (MUs) at intervals of 50 ms or less during delivery. Based on the DMI, the system performed two levels of monitoring/verification during the delivery: (1) dynamic monitoring of cumulative fluence errors resulting from leaf position deviations and visualization using fluence error maps (FEMs); and (2) verification of MLC positions against the treatment plan for potential errors in MLC motion and data transfer at each control point. Validation of the online delivery monitoring system was performed by introducing intentional systematic MLC errors (ranging from 0.5 to 2 mm) to the DMI files for both leaf banks. These DMI files were analyzed by the proposed system to evaluate the system's performance in quantifying errors and revealing the source of errors, as well as to understand patterns in the FEMs. In addition, FEMs from 210 actual prostate IMRT beams were analyzed using the proposed system to further validate its ability to catch and identify errors, as well as establish error magnitude baselines for prostate IMRT delivery. Online adapted plans were found to have similar delivery accuracy in comparison to clinical IMRT plans when validated with portal dosimetry IMRT QA. FEMs for the simulated deliveries with intentional MLC errors exhibited distinct patterns for different MLC error magnitudes and directions, indicating that the proposed delivery monitoring system is highly specific in detecting the source of errors. Implementing the proposed QA system for online adapted plans revealed excellent delivery accuracy: over 99% of leaf position differences were within 0.5 mm, and >99% of pixels in the FEMs had fluence errors within 0.5 MU. Patterns present in the FEMs and MLC control point analysis for actual patient cases agreed with the error pattern analysis results, further validating the system's ability to reveal and differentiate MLC deviations. Calculation of the fluence map based on the DMI was performed within 2 ms after receiving each DMI input. The proposed online delivery monitoring system requires minimal additional resources and time commitment to the current clinical workflow while still maintaining high sensitivity to leaf position errors and specificity to error types. The presented online delivery monitoring system therefore represents a promising QA system candidate for online adaptive radiation therapy.

Why Does a Method That Fails Continue To Be Used: The Answer

PubMed Central

Templeton, Alan R.

2009-01-01

It has been claimed that hundreds of researchers use nested clade phylogeographic analysis (NCPA) based on what the method promises rather than requiring objective validation of the method. The supposed failure of NCPA is based upon the argument that validating it by using positive controls ignored type I error, and that computer simulations have shown a high type I error. The first argument is factually incorrect: the previously published validation analysis fully accounted for both type I and type II errors. The simulations that indicate a 75% type I error rate have serious flaws and only evaluate outdated versions of NCPA. These outdated type I error rates fall precipitously when the 2003 version of single locus NCPA is used or when the 2002 multi-locus version of NCPA is used. It is shown that the treewise type I errors in single-locus NCPA can be corrected to the desired nominal level by a simple statistical procedure, and that multilocus NCPA reconstructs a simulated scenario used to discredit NCPA with 100% accuracy. Hence, NCPA is a not a failed method at all, but rather has been validated both by actual data and by simulated data in a manner that satisfies the published criteria given by its critics. The critics have come to different conclusions because they have focused on the pre-2002 versions of NCPA and have failed to take into account the extensive developments in NCPA since 2002. Hence, researchers can choose to use NCPA based upon objective critical validation that shows that NCPA delivers what it promises. PMID:19335340

A comparative experimental evaluation of uncertainty estimation methods for two-component PIV

NASA Astrophysics Data System (ADS)

Boomsma, Aaron; Bhattacharya, Sayantan; Troolin, Dan; Pothos, Stamatios; Vlachos, Pavlos

2016-09-01

Uncertainty quantification in planar particle image velocimetry (PIV) measurement is critical for proper assessment of the quality and significance of reported results. New uncertainty estimation methods have been recently introduced generating interest about their applicability and utility. The present study compares and contrasts current methods, across two separate experiments and three software packages in order to provide a diversified assessment of the methods. We evaluated the performance of four uncertainty estimation methods, primary peak ratio (PPR), mutual information (MI), image matching (IM) and correlation statistics (CS). The PPR method was implemented and tested in two processing codes, using in-house open source PIV processing software (PRANA, Purdue University) and Insight4G (TSI, Inc.). The MI method was evaluated in PRANA, as was the IM method. The CS method was evaluated using DaVis (LaVision, GmbH). Utilizing two PIV systems for high and low-resolution measurements and a laser doppler velocimetry (LDV) system, data were acquired in a total of three cases: a jet flow and a cylinder in cross flow at two Reynolds numbers. LDV measurements were used to establish a point validation against which the high-resolution PIV measurements were validated. Subsequently, the high-resolution PIV measurements were used as a reference against which the low-resolution PIV data were assessed for error and uncertainty. We compared error and uncertainty distributions, spatially varying RMS error and RMS uncertainty, and standard uncertainty coverages. We observed that qualitatively, each method responded to spatially varying error (i.e. higher error regions resulted in higher uncertainty predictions in that region). However, the PPR and MI methods demonstrated reduced uncertainty dynamic range response. In contrast, the IM and CS methods showed better response, but under-predicted the uncertainty ranges. The standard coverages (68% confidence interval) ranged from approximately 65%-77% for PPR and MI methods, 40%-50% for IM and near 50% for CS. These observations illustrate some of the strengths and weaknesses of the methods considered herein and identify future directions for development and improvement.

SMAP RADAR Calibration and Validation

NASA Astrophysics Data System (ADS)

West, R. D.; Jaruwatanadilok, S.; Chaubel, M. J.; Spencer, M.; Chan, S. F.; Chen, C. W.; Fore, A.

2015-12-01

The Soil Moisture Active Passive (SMAP) mission launched on Jan 31, 2015. The mission employs L-band radar and radiometer measurements to estimate soil moisture with 4% volumetric accuracy at a resolution of 10 km, and freeze-thaw state at a resolution of 1-3 km. Immediately following launch, there was a three month instrument checkout period, followed by six months of level 1 (L1) calibration and validation. In this presentation, we will discuss the calibration and validation activities and results for the L1 radar data. Early SMAP radar data were used to check commanded timing parameters, and to work out issues in the low- and high-resolution radar processors. From April 3-13 the radar collected receive only mode data to conduct a survey of RFI sources. Analysis of the RFI environment led to a preferred operating frequency. The RFI survey data were also used to validate noise subtraction and scaling operations in the radar processors. Normal radar operations resumed on April 13. All radar data were examined closely for image quality and calibration issues which led to improvements in the radar data products for the beta release at the end of July. Radar data were used to determine and correct for small biases in the reported spacecraft attitude. Geo-location was validated against coastline positions and the known positions of corner reflectors. Residual errors at the time of the beta release are about 350 m. Intra-swath biases in the high-resolution backscatter images are reduced to less than 0.3 dB for all polarizations. Radiometric cross-calibration with Aquarius was performed using areas of the Amazon rain forest. Cross-calibration was also examined using ocean data from the low-resolution processor and comparing with the Aquarius wind model function. Using all a-priori calibration constants provided good results with co-polarized measurements matching to better than 1 dB, and cross-polarized measurements matching to about 1 dB in the beta release. During the second half of the L1 cal/val period, the RFI removal algorithm will be tuned for optimal performance, and the Faraday rotation corrections used in radar processing will be further developed and validated. This work is supported by the SMAP project at the Jet Propulsion Laboratory, California Institute of Technology.

Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

PubMed

Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-07-21

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

RBF kernel based support vector regression to estimate the blood volume and heart rate responses during hemodialysis.

PubMed

Javed, Faizan; Chan, Gregory S H; Savkin, Andrey V; Middleton, Paul M; Malouf, Philip; Steel, Elizabeth; Mackie, James; Lovell, Nigel H

2009-01-01

This paper uses non-linear support vector regression (SVR) to model the blood volume and heart rate (HR) responses in 9 hemodynamically stable kidney failure patients during hemodialysis. Using radial bias function (RBF) kernels the non-parametric models of relative blood volume (RBV) change with time as well as percentage change in HR with respect to RBV were obtained. The e-insensitivity based loss function was used for SVR modeling. Selection of the design parameters which includes capacity (C), insensitivity region (e) and the RBF kernel parameter (sigma) was made based on a grid search approach and the selected models were cross-validated using the average mean square error (AMSE) calculated from testing data based on a k-fold cross-validation technique. Linear regression was also applied to fit the curves and the AMSE was calculated for comparison with SVR. For the model based on RBV with time, SVR gave a lower AMSE for both training (AMSE=1.5) as well as testing data (AMSE=1.4) compared to linear regression (AMSE=1.8 and 1.5). SVR also provided a better fit for HR with RBV for both training as well as testing data (AMSE=15.8 and 16.4) compared to linear regression (AMSE=25.2 and 20.1).

Candidate soil indicators for monitoring the progress of constructed wetlands toward a natural state: a statistical approach

USGS Publications Warehouse

Stapanian, Martin A.; Adams, Jean V.; Fennessy, M. Siobhan; Mack, John; Micacchion, Mick

2013-01-01

A persistent question among ecologists and environmental managers is whether constructed wetlands are structurally or functionally equivalent to naturally occurring wetlands. We examined 19 variables collected from 10 constructed and nine natural emergent wetlands in Ohio, USA. Our primary objective was to identify candidate indicators of wetland class (natural or constructed), based on measurements of soil properties and an index of vegetation integrity, that can be used to track the progress of constructed wetlands toward a natural state. The method of nearest shrunken centroids was used to find a subset of variables that would serve as the best classifiers of wetland class, and error rate was calculated using a five-fold cross-validation procedure. The shrunken differences of percent total organic carbon (% TOC) and percent dry weight of the soil exhibited the greatest distances from the overall centroid. Classification based on these two variables yielded a misclassification rate of 11% based on cross-validation. Our results indicate that % TOC and percent dry weight can be used as candidate indicators of the status of emergent, constructed wetlands in Ohio and for assessing the performance of mitigation. The method of nearest shrunken centroids has excellent potential for further applications in ecology.

A Simple Endoscopic Technique for Measuring the Cross-Sectional Area of the Upper Airway in a Rabbit Model.

PubMed

Wistermayer, Paul R; McIlwain, Wesley R; Ieronimakis, Nicholas; Rogers, Derek J

2018-04-01

Validate an accurate and reproducible method of measuring the cross-sectional area (CSA) of the upper airway. This is a prospective animal study done at a tertiary care medical treatment facility. Control images were obtained using endotracheal tubes of varying sizes. In vivo images were obtained from various timepoints of a concurrent study on subglottic stenosis. Using a 0° rod telescope, an instrument was placed at the level of interest, and a photo was obtained. Three independent and blinded raters then measured the CSA of the narrowest portion of the airway using open source image analysis software. Each blinded rater measured the CSA of 79 photos. The t testing to assess for accuracy showed no difference between measured and known CSAs of the control images ( P = .86), with an average error of 1.5% (SD = 5.5%). All intraclass correlation (ICC) values for intrarater agreement showed excellent agreement (ICC > .75). Interrater reliability among all raters in control (ICC = .975; 95% CI, .817-.995) and in vivo (ICC = .846;, 95% CI, .780-.896) images showed excellent agreement. We validate a simple, accurate, and reproducible method of measuring the CSA of the airway that can be used in a clinical or research setting.

Computational Depth of Anesthesia via Multiple Vital Signs Based on Artificial Neural Networks.

PubMed

Sadrawi, Muammar; Fan, Shou-Zen; Abbod, Maysam F; Jen, Kuo-Kuang; Shieh, Jiann-Shing

2015-01-01

This study evaluated the depth of anesthesia (DoA) index using artificial neural networks (ANN) which is performed as the modeling technique. Totally 63-patient data is addressed, for both modeling and testing of 17 and 46 patients, respectively. The empirical mode decomposition (EMD) is utilized to purify between the electroencephalography (EEG) signal and the noise. The filtered EEG signal is subsequently extracted to achieve a sample entropy index by every 5-second signal. Then, it is combined with other mean values of vital signs, that is, electromyography (EMG), heart rate (HR), pulse, systolic blood pressure (SBP), diastolic blood pressure (DBP), and signal quality index (SQI) to evaluate the DoA index as the input. The 5 doctor scores are averaged to obtain an output index. The mean absolute error (MAE) is utilized as the performance evaluation. 10-fold cross-validation is performed in order to generalize the model. The ANN model is compared with the bispectral index (BIS). The results show that the ANN is able to produce lower MAE than BIS. For the correlation coefficient, ANN also has higher value than BIS tested on the 46-patient testing data. Sensitivity analysis and cross-validation method are applied in advance. The results state that EMG has the most effecting parameter, significantly.

Computational Depth of Anesthesia via Multiple Vital Signs Based on Artificial Neural Networks

PubMed Central

Sadrawi, Muammar; Fan, Shou-Zen; Abbod, Maysam F.; Jen, Kuo-Kuang; Shieh, Jiann-Shing

2015-01-01

This study evaluated the depth of anesthesia (DoA) index using artificial neural networks (ANN) which is performed as the modeling technique. Totally 63-patient data is addressed, for both modeling and testing of 17 and 46 patients, respectively. The empirical mode decomposition (EMD) is utilized to purify between the electroencephalography (EEG) signal and the noise. The filtered EEG signal is subsequently extracted to achieve a sample entropy index by every 5-second signal. Then, it is combined with other mean values of vital signs, that is, electromyography (EMG), heart rate (HR), pulse, systolic blood pressure (SBP), diastolic blood pressure (DBP), and signal quality index (SQI) to evaluate the DoA index as the input. The 5 doctor scores are averaged to obtain an output index. The mean absolute error (MAE) is utilized as the performance evaluation. 10-fold cross-validation is performed in order to generalize the model. The ANN model is compared with the bispectral index (BIS). The results show that the ANN is able to produce lower MAE than BIS. For the correlation coefficient, ANN also has higher value than BIS tested on the 46-patient testing data. Sensitivity analysis and cross-validation method are applied in advance. The results state that EMG has the most effecting parameter, significantly. PMID:26568957

The cross-validated AUC for MCP-logistic regression with high-dimensional data.

PubMed

Jiang, Dingfeng; Huang, Jian; Zhang, Ying

2013-10-01

We propose a cross-validated area under the receiving operator characteristic (ROC) curve (CV-AUC) criterion for tuning parameter selection for penalized methods in sparse, high-dimensional logistic regression models. We use this criterion in combination with the minimax concave penalty (MCP) method for variable selection. The CV-AUC criterion is specifically designed for optimizing the classification performance for binary outcome data. To implement the proposed approach, we derive an efficient coordinate descent algorithm to compute the MCP-logistic regression solution surface. Simulation studies are conducted to evaluate the finite sample performance of the proposed method and its comparison with the existing methods including the Akaike information criterion (AIC), Bayesian information criterion (BIC) or Extended BIC (EBIC). The model selected based on the CV-AUC criterion tends to have a larger predictive AUC and smaller classification error than those with tuning parameters selected using the AIC, BIC or EBIC. We illustrate the application of the MCP-logistic regression with the CV-AUC criterion on three microarray datasets from the studies that attempt to identify genes related to cancers. Our simulation studies and data examples demonstrate that the CV-AUC is an attractive method for tuning parameter selection for penalized methods in high-dimensional logistic regression models.

Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

PubMed Central

Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-01-01

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most US and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004–2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross validation R2 of 0.724. Cross-validated root mean squared prediction error (RMSPE) of the model was 5.55 μg/m3. This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City. PMID:26061488

In-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz based on qualitative and quantitative uses of near-infrared spectroscopy.

PubMed

Wu, Yongjiang; Jin, Ye; Ding, Haiying; Luan, Lianjun; Chen, Yong; Liu, Xuesong

2011-09-01

The application of near-infrared (NIR) spectroscopy for in-line monitoring of extraction process of scutellarein from Erigeron breviscapus (vant.) Hand-Mazz was investigated. For NIR measurements, two fiber optic probes designed to transmit NIR radiation through a 2 mm pathlength flow cell were utilized to collect spectra in real-time. High performance liquid chromatography (HPLC) was used as a reference method to determine scutellarein in extract solution. Partial least squares regression (PLSR) calibration model of Savitzky-Golay smoothing NIR spectra in the 5450-10,000 cm(-1) region gave satisfactory predictive results for scutellarein. The results showed that the correlation coefficients of calibration and cross validation were 0.9967 and 0.9811, respectively, and the root mean square error of calibration and cross validation were 0.044 and 0.105, respectively. Furthermore, both the moving block standard deviation (MBSD) method and conformity test were used to identify the end point of extraction process, providing real-time data and instant feedback about the extraction course. The results obtained in this study indicated that the NIR spectroscopy technique provides an efficient and environmentally friendly approach for fast determination of scutellarein and end point control of extraction process. Copyright © 2011 Elsevier B.V. All rights reserved.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network.

PubMed

Liu, Ruixin; Zhang, Xiaodong; Zhang, Lu; Gao, Xiaojie; Li, Huiling; Shi, Junhan; Li, Xuelin

2014-06-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue.

Bitterness intensity prediction of berberine hydrochloride using an electronic tongue and a GA-BP neural network

PubMed Central

LIU, RUIXIN; ZHANG, XIAODONG; ZHANG, LU; GAO, XIAOJIE; LI, HUILING; SHI, JUNHAN; LI, XUELIN

2014-01-01

The aim of this study was to predict the bitterness intensity of a drug using an electronic tongue (e-tongue). The model drug of berberine hydrochloride was used to establish a bitterness prediction model (BPM), based on the taste evaluation of bitterness intensity by a taste panel, the data provided by the e-tongue and a genetic algorithm-back-propagation neural network (GA-BP) modeling method. The modeling characteristics of the GA-BP were compared with those of multiple linear regression, partial least square regression and BP methods. The determination coefficient of the BPM was 0.99965±0.00004, the root mean square error of cross-validation was 0.1398±0.0488 and the correlation coefficient of the cross-validation between the true and predicted values was 0.9959±0.0027. The model is superior to the other three models based on these indicators. In conclusion, the model established in this study has a high fitting degree and may be used for the bitterness prediction modeling of berberine hydrochloride of different concentrations. The model also provides a reference for the generation of BPMs of other drugs. Additionally, the algorithm of the study is able to conduct a rapid and accurate quantitative analysis of the data provided by the e-tongue. PMID:24926369

Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Goring, Simon

2017-01-01

Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.

Cross-cultural validation of the Depression Anxiety Stress Scale-21 in China.

PubMed

Wang, Kui; Shi, Hai-Song; Geng, Fu-Lei; Zou, Lai-Quan; Tan, Shu-Ping; Wang, Yi; Neumann, David L; Shum, David H K; Chan, Raymond C K

2016-05-01

The gap between the demand and delivery of mental health services in mainland China can be reduced by validating freely available and psychometrically sound psychological instruments. The present research examined the Chinese version of the 21-item Depression Anxiety Stress Scales (DASS-21). Study 1 administered the DASS-21 to 1,815 Chinese college students and found internal consistency indices (Cronbach's alpha) of .83, .80, and .82 for the Depression, Anxiety, and Stress subscales, respectively, and .92 for the total DASS total. Test-retest reliability over a 6-month interval was .39 to .46 for each of the 3 subscales and .46 for the total DASS. Moderate convergent validity of the Depression and Anxiety subscales was demonstrated via significant correlations with the Chinese Beck Depression Inventory (r = .51 at Time 1 and r = .64 at Time 2) and the Chinese State-Trait Anxiety Inventory (r = .41), respectively. Confirmatory factor analyses supported the original 3-factor model with 1 minor change (nonnormed fit index [NNFI] = .964, comparative fit index [CFI] = .968, and root mean square error of approximation [RMSEA] = .079). Study 2 examined the clinical utility of the Chinese DASS-21 in 166 patients with schizophrenia and 90 matched healthy controls. Patients had higher Depression and Anxiety but not Stress subscale scores than healthy controls. A discriminant function composed of the linear combination of 3 subscale scores correctly discriminated 69.92% of participants, which again supported the potential clinical utility of the DASS in mainland China. Taken together, findings in these studies support the cross-cultural validity of the DASS-21 in China. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A cross-cultural validation of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) in Turkey and the USA

NASA Astrophysics Data System (ADS)

Welch, Anita G.; Cakir, Mustafa; Peterson, Claudette M.; Ray, Chris M.

2012-04-01

Background . Studies exploring the relationship between students' achievement and the quality of the classroom learning environments have shown that there is a strong relationship between these two concepts. Learning environment instruments are constantly being revised and updated, including for use in different cultures, which requires continued validation efforts. Purpose The purpose of this study was to establish cross-cultural reliability and validity of the Technology-Rich Outcomes-Focused Learning Environment Inventory (TROFLEI) in both Turkey and the USA. Sample Approximately 980 students attending grades 9-12 in Turkey and 130 students attending grades 9-12 in the USA participated in the study. Design and method Scale reliability analyses and confirmatory factor analysis (CFA) were performed separately for Turkish and US participants for both actual and preferred responses to each scale to confirm the structure of the TROFLEI across these two distinct samples. Results Cronbach's alpha reliability coefficients, ranging from α = 0.820 to 0.931 for Turkish participants and from α = 0.778 to 0.939 for US participants, indicated that all scales have satisfactory internal consistency for both samples. Confirmatory factor analyses resulted in evidence of adequate model fit across both samples for both actual and preferred responses, with the root mean square error of approximation ranging from 0.052 to 0.057 and the comparative fit index ranging from 0.920 to 0.982. Conclusions This study provides initial evidence that the TROFLEI is valid for use in both the Turkish and US high-school populations (grades 9-12). However, the psychometric properties should be examined further with different populations, such as middle-school students (grades 6-8).

Measurement of conjugated linoleic acid (CLA) in CLA-rich soy oil by attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR).

PubMed

Kadamne, Jeta V; Jain, Vishal P; Saleh, Mohammed; Proctor, Andrew

2009-11-25

Conjugated linoleic acid (CLA) isomers in oils are currently measured as fatty acid methyl esters by a gas chromatography-flame ionization detector (GC-FID) technique, which requires approximately 2 h to complete the analysis. Hence, we aim to develop a method to rapidly determine CLA isomers in CLA-rich soy oil. Soy oil with 0.38-25.11% total CLA was obtained by photo-isomerization of 96 soy oil samples for 24 h. A sample was withdrawn at 30 min intervals with repeated processing using a second batch of oil. Six replicates of GC-FID fatty acid analysis were conducted for each oil sample. The oil samples were scanned using attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), and the spectrum was collected. Calibration models were developed using partial least-squares (PLS-1) regression using Unscrambler software. Models were validated using a full cross-validation technique and tested using samples that were not included in the calibration sample set. Measured and predicted total CLA, trans,trans CLA isomers, total mono trans CLA isomers, trans-10,cis-12 CLA, trans-9,cis-11 CLA and cis-10,trans-12 CLA, and cis-9,trans-11 CLA had cross-validated coefficients of determinations (R2v) of 0.97, 0.98, 0.97, 0.98, 0.97, and 0.99 and corresponding root-mean-square error of validation (RMSEV) of 1.14, 0.69, 0.27, 0.07, 0.14, and 0.07% CLA, respectively. The ATR-FTIR technique is a rapid and less expensive method for determining CLA isomers in linoleic acid photo-isomerized soy oil than GC-FID.

Cross-cultural adaptation and psychometric assessment of the Chinese version of the comprehensive needs assessment tool for cancer caregivers (CNAT-C).

PubMed

Zhang, Yin-Ping; Zhao, Xin-Shuang; Zhang, Bei; Zhang, Lu-Lu; Ni, Chun-Ping; Hao, Nan; Shi, Chang-Bei; Porr, Caroline

2015-07-01

The comprehensive needs assessment tool for cancer caregivers (CNAT-C) is a systematic and comprehensive needs assessment tool for the family caregivers. The purpose of this project was twofold: (1) to adapt the CNAT-C to Mainland China's cultural context and (2) to evaluate the psychometric properties of the newly adapted Chinese CNAT-C. Cross-cultural adaptation of the original CNAT-C was performed according to published guidelines. A pilot study was conducted in Mainland China with 30 Chinese family cancer caregivers. A subsequent validation study was conducted with 205 Chinese cancer caregivers from Mainland China. Construct validity was determined through exploratory and confirmatory factor analyses. Reliability was determined using internal consistency and test-retest reliability. The split-half coefficient for the overall Chinese CNAT-C scale was 0.77. Principal component analysis resulted in an eight-factor structure explaining 68.11 % of the total variance. The comparative fit index (CFI) was 0.91 from the modified model confirmatory factor analysis. The Chi-square divided by degrees of freedom was 1.98, and the root mean squared error of approximation (RMSEA) was 0.079. In relation to the known-group validation, significant differences were found in the Chinese CNAT-C scale according to various caregiver characteristics. Internal consistency was high for the Chinese CNAT-C reaching a Cronbach α value of 0.94. Test-retest reliability was 0.85. The newly adapted Chinese CNAT-C scale possesses adequate validity, test-retest reliability, and internal consistency and therefore may be used to ascertain holistic health and support needs of cancer patients' family caregivers in Mainland China.

Examination of efficacious, efficient, and socially valid error-correction procedures to teach sight words and prepositions to children with autism spectrum disorder.

PubMed

Kodak, Tiffany; Campbell, Vincent; Bergmann, Samantha; LeBlanc, Brittany; Kurtz-Nelson, Eva; Cariveau, Tom; Haq, Shaji; Zemantic, Patricia; Mahon, Jacob

2016-09-01

Prior research shows that learners have idiosyncratic responses to error-correction procedures during instruction. Thus, assessments that identify error-correction strategies to include in instruction can aid practitioners in selecting individualized, efficacious, and efficient interventions. The current investigation conducted an assessment to compare 5 error-correction procedures that have been evaluated in the extant literature and are common in instructional practice for children with autism spectrum disorder (ASD). Results showed that the assessment identified efficacious and efficient error-correction procedures for all participants, and 1 procedure was efficient for 4 of the 5 participants. To examine the social validity of error-correction procedures, participants selected among efficacious and efficient interventions in a concurrent-chains assessment. We discuss the results in relation to prior research on error-correction procedures and current instructional practices for learners with ASD. © 2016 Society for the Experimental Analysis of Behavior.

Error Analysis and Validation for Insar Height Measurement Induced by Slant Range

NASA Astrophysics Data System (ADS)

Zhang, X.; Li, T.; Fan, W.; Geng, X.

2018-04-01

InSAR technique is an important method for large area DEM extraction. Several factors have significant influence on the accuracy of height measurement. In this research, the effect of slant range measurement for InSAR height measurement was analysis and discussed. Based on the theory of InSAR height measurement, the error propagation model was derived assuming no coupling among different factors, which directly characterise the relationship between slant range error and height measurement error. Then the theoretical-based analysis in combination with TanDEM-X parameters was implemented to quantitatively evaluate the influence of slant range error to height measurement. In addition, the simulation validation of InSAR error model induced by slant range was performed on the basis of SRTM DEM and TanDEM-X parameters. The spatial distribution characteristics and error propagation rule of InSAR height measurement were further discussed and evaluated.

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

PubMed

Sharma, H S S; Reinard, N

2004-12-01

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

COMPI Fertility Problem Stress Scales is a brief, valid and reliable tool for assessing stress in patients seeking treatment.

PubMed

Sobral, Maria P; Costa, Maria E; Schmidt, Lone; Martins, Mariana V

2017-02-01

Are the Copenhagen Multi-Centre Psychosocial Infertility research program Fertility Problem Stress Scales (COMPI-FPSS) a reliable and valid measure across gender and culture? The COMPI-FPSS is a valid and reliable measure, presenting excellent or good fit in the majority of the analyzed countries, and demonstrating full invariance across genders and partial invariance across cultures. Cross-cultural and gender validation is needed to consider a measure as standard care within fertility. The present study is the first attempting to establish comparability of fertility-related stress across genders and countries. Cross-sectional study. First, we tested the structure of the COMPI-FPSS. Then, reliability and validity (convergent and discriminant) were examined for the final model. Finally, measurement invariance both across genders and cultures was tested. Our final sample had 3923 fertility patients (1691 men and 2232 women) recruited in clinical settings from seven different countries: Denmark, China, Croatia, Germany, Greece, Hungary and Sweden. Participants had a mean age of 34 years and the majority (84%) were childless. Findings confirmed the original three-factor structure of the COMPI-FPSS, although suggesting a shortened measurement model using less items that fitted the data better than the full version model. While data from the Chinese and Croatian subsamples did not fit, all other counties presented good fit (χ 2 /df ≤ 5.4; comparative fit index ≥ 0.94; root-mean-square error of approximation ≤ 0.07; modified expected cross-validation index ≤ 0.77). In general, reliability, convergent validity, and discriminant validity were observed in all subscales from each country (composite reliability ≥ 0.63; average variance extracted ≥ 0.38; squared correlation ≥ 0.13). Full invariance was established across genders, and partial invariance was demonstrated across countries. Generalizability regarding the validation of the COMPI-FPSS cannot be made regarding infertile individuals not seeking treatment, or non-European patients. This study did not investigate predictive validity, and hence the capability of this instrument in detecting changes in fertility-specific adjustment over time and predicting the psychological impact needs to be established in future research. Besides extending knowledge on the psychometric properties of one of the most used fertility stress questionnaire, this study demonstrates both research and clinical usefulness of the COMPI-FPSS. This study was supported by European Union Funds (FEDER/COMPETE-Operational Competitiveness Program, and by national funds (FCT-Portuguese Foundation for Science and Technology) under the projects PTDC/MHC-PSC/4195/2012 and SFRH/BPD/85789/2012). There are no conflicts of interest to declare. N/A. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Development of Wind Speed Retrieval from Cross-Polarization Chinese Gaofen-3 Synthetic Aperture Radar in Typhoons

PubMed Central

Yuan, Xinzhe; Sun, Jian; Zhou, Wei; Zhang, Qingjun

2018-01-01

The purpose of our work is to determine the feasibility and effectiveness of retrieving sea surface wind speeds from C-band cross-polarization (herein vertical-horizontal, VH) Chinese Gaofen-3 (GF-3) SAR images in typhoons. In this study, we have collected three GF-3 SAR images acquired in Global Observation (GLO) and Wide ScanSAR (WSC) mode during the summer of 2017 from the China Sea, which includes the typhoons Noru, Doksuri and Talim. These images were collocated with wind simulations at 0.12° grids from a numeric model, called the Regional Assimilation and Prediction System-Typhoon model (GRAPES-TYM). Recent research shows that GRAPES-TYM has a good performance for typhoon simulation in the China Sea. Based on the dataset, the dependence of wind speed and of radar incidence angle on normalized radar cross (NRCS) of VH-polarization GF-3 SAR have been investigated, after which an empirical algorithm for wind speed retrieval from VH-polarization GF-3 SAR was tuned. An additional four VH-polarization GF-3 SAR images in three typhoons, Noru, Hato and Talim, were investigated in order to validate the proposed algorithm. SAR-derived winds were compared with measurements from Windsat winds at 0.25° grids with wind speeds up to 40 m/s, showing a 5.5 m/s root mean square error (RMSE) of wind speed and an improved RMSE of 5.1 m/s wind speed was achieved compared with the retrieval results validated against GRAPES-TYM winds. It is concluded that the proposed algorithm is a promising potential technique for strong wind retrieval from cross-polarization GF-3 SAR images without encountering a signal saturation problem. PMID:29385068

Instruments to assess self-care among healthy children: A systematic review of measurement properties.

PubMed

Urpí-Fernández, Ana-María; Zabaleta-Del-Olmo, Edurne; Montes-Hidalgo, Javier; Tomás-Sábado, Joaquín; Roldán-Merino, Juan-Francisco; Lluch-Canut, María-Teresa

2017-12-01

To identify, critically appraise and summarize the measurement properties of instruments to assess self-care in healthy children. Assessing self-care is a proper consideration for nursing practice and nursing research. No systematic review summarizes instruments of measurement validated in healthy children. Psychometric review in accordance with the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) panel. MEDLINE, CINAHL, PsycINFO, Web of Science and Open Grey were searched from their inception to December 2016. Validation studies with a healthy child population were included. Search was not restricted by language. Two reviewers independently assessed the methodological quality of included studies using the COSMIN checklist. Eleven studies were included in the review assessing the measurement properties of ten instruments. There was a maximum of two studies per instrument. None of the studies evaluated the properties of test-retest reliability, measurement error, criterion validity and responsiveness. Internal consistency and structural validity were rated as "excellent" or "good" in four studies. Four studies were rated as "excellent" in content validity. Cross-cultural validity was rated as "poor" in the two studies (three instruments) which cultural adaptation was carried out. The evidence available does not allow firm conclusions about the instruments identified in terms of reliability and validity. Future research should focus on generate evidence about a wider range of measurement properties of these instruments using a rigorous methodology, as well as instrument testing on different countries and child population. © 2017 John Wiley & Sons Ltd.

Measurement of children's physical activity using a pedometer with a built-in memory.

PubMed

Trapp, Georgina S A; Giles-Corti, Billie; Bulsara, Max; Christian, Hayley E; Timperio, Anna F; McCormack, Gavin R; Villanueva, Karen

2013-05-01

We evaluated the accuracy of the Accusplit AH120 pedometer (built-in memory) for recording step counts of children during treadmill walking against (1) observer counted steps and (2) concurrently measured steps using the previously validated Yamax Digiwalker SW-700 pedometer. This was a cross-sectional validation study performed under controlled settings. Forty five 9-12-year-olds walked on treadmills at speeds of 42, 66 and 90m/min to simulate slow, moderate and fast walking wearing Accusplit and Yamax pedometers concurrently on their right hip. Observer counted steps were captured by video camera and manually counted. Absolute value of percent error was calculated for each comparison. Bland-Altman plots were constructed to show the distribution of the individual (criterion-comparison) scores around zero. Both pedometers under-recorded observer counted steps at all three walk speeds. Absolute value of percent error was highest at the slowest walk speed (Accusplit=46.9%; Yamax=44.1%) and lowest at the fastest walk speed (Accusplit=8.6%; Yamax=8.9%). Bland-Altman plots showed high agreement between the pedometers for all three walk speeds. Using pedometers with built-in memory capabilities eliminates the need for children to manually log step counts daily, potentially improving data accuracy and completeness. Step counts from the Accusplit (built-in memory) and Yamax (widely used) pedometers were comparable across all speeds, but their level of accuracy was dependent on walking pace. Pedometers should be used with caution in children as they significantly undercount steps, and this error is greatest at slower walk speeds. Copyright © 2012 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Quantification of landfill methane using modified Intergovernmental Panel on Climate Change's waste model and error function analysis.

PubMed

Govindan, Siva Shangari; Agamuthu, P

2014-10-01

Waste management can be regarded as a cross-cutting environmental 'mega-issue'. Sound waste management practices support the provision of basic needs for general health, such as clean air, clean water and safe supply of food. In addition, climate change mitigation efforts can be achieved through reduction of greenhouse gas emissions from waste management operations, such as landfills. Landfills generate landfill gas, especially methane, as a result of anaerobic degradation of the degradable components of municipal solid waste. Evaluating the mode of generation and collection of landfill gas has posted a challenge over time. Scientifically, landfill gas generation rates are presently estimated using numerical models. In this study the Intergovernmental Panel on Climate Change's Waste Model is used to estimate the methane generated from a Malaysian sanitary landfill. Key parameters of the model, which are the decay rate and degradable organic carbon, are analysed in two different approaches; the bulk waste approach and waste composition approach. The model is later validated using error function analysis and optimum decay rate, and degradable organic carbon for both approaches were also obtained. The best fitting values for the bulk waste approach are a decay rate of 0.08 y(-1) and degradable organic carbon value of 0.12; and for the waste composition approach the decay rate was found to be 0.09 y(-1) and degradable organic carbon value of 0.08. From this validation exercise, the estimated error was reduced by 81% and 69% for the bulk waste and waste composition approach, respectively. In conclusion, this type of modelling could constitute a sensible starting point for landfills to introduce careful planning for efficient gas recovery in individual landfills. © The Author(s) 2014.

Estimating Gestational Age From Ultrasound Fetal Biometrics.

PubMed

Skupski, Daniel W; Owen, John; Kim, Sungduk; Fuchs, Karin M; Albert, Paul S; Grantz, Katherine L

2017-08-01

To compare the accuracy of a new formula with one developed in 1984 (and still in common use) and to develop and compare racial and ethnic-specific and racial and ethnic-neutral formulas. The Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons was a prospective cohort study that recruited women in four self-reported racial-ethnic groups-non-Hispanic black, Hispanic, non-Hispanic white, and Asian-with singleton gestations from 12 U.S. centers (2009-2013). Women with a certain last menstrual period confirmed by first-trimester ultrasonogram had longitudinal fetal measurements by credentialed study ultrasonographers blinded to the gestational age at their five follow-up visits. Regression analyses were performed with linear mixed models to develop gestational age estimating formulas. Repeated cross-validation was used for validation. The estimation error was defined as the mean squared difference between the estimated and observed gestational age and was used to compare the formulas' accuracy. The new formula estimated the gestational age (±2 SD) within ±7 days from 14 to 20 weeks of gestation, ±10 days from 21 to 27 weeks of gestation, and ±17 days from 28 to 40 weeks of gestation. The new formula performed significantly better than a formula developed in 1984 with an estimation error of 10.4 compared with 11.2 days from 21 to 27 weeks of gestation and 17.0 compared with 19.8 days at 28-40 weeks of gestation, respectively. Racial and ethnic-specific formulas did not outperform the racial and ethnic-neutral formula. The NICHD gestational age estimation formula is associated with smaller errors than a well-established historical formula. Racial and ethnic-specific formulas are not superior to a racial-ethnic-neutral one.

Development of a transformation model to derive general population-based utility: Mapping the pruritus-visual analog scale (VAS) to the EQ-5D utility.

PubMed

Park, Sun-Young; Park, Eun-Ja; Suh, Hae Sun; Ha, Dongmun; Lee, Eui-Kyung

2017-08-01

Although nonpreference-based disease-specific measures are widely used in clinical studies, they cannot generate utilities for economic evaluation. A solution to this problem is to estimate utilities from disease-specific instruments using the mapping function. This study aimed to develop a transformation model for mapping the pruritus-visual analog scale (VAS) to the EuroQol 5-Dimension 3-Level (EQ-5D-3L) utility index in pruritus. A cross-sectional survey was conducted with a sample (n = 268) drawn from the general population of South Korea. Data were randomly divided into 2 groups, one for estimating and the other for validating mapping models. To select the best model, we developed and compared 3 separate models using demographic information and the pruritus-VAS as independent variables. The predictive performance was assessed using the mean absolute deviation and root mean square error in a separate dataset. Among the 3 models, model 2 using age, age squared, sex, and the pruritus-VAS as independent variables had the best performance based on the goodness of fit and model simplicity, with a log likelihood of 187.13. The 3 models had similar precision errors based on mean absolute deviation and root mean square error in the validation dataset. No statistically significant difference was observed between the mean observed and predicted values in all models. In conclusion, model 2 was chosen as the preferred mapping model. Outcomes measured as the pruritus-VAS can be transformed into the EQ-5D-3L utility index using this mapping model, which makes an economic evaluation possible when only pruritus-VAS data are available. © 2017 John Wiley & Sons, Ltd.

Development of an aerobic capacity prediction model from one-mile run/walk performance in adolescents aged 13-16 years.

PubMed

Burns, Ryan D; Hannon, James C; Brusseau, Timothy A; Eisenman, Patricia A; Shultz, Barry B; Saint-Maurice, Pedro F; Welk, Gregory J; Mahar, Matthew T

2016-01-01

A popular algorithm to predict VO2Peak from the one-mile run/walk test (1MRW) includes body mass index (BMI), which manifests practical issues in school settings. The purpose of this study was to develop an aerobic capacity model from 1MRW in adolescents independent of BMI. Cardiorespiratory endurance data were collected on 90 adolescents aged 13-16 years. The 1MRW was administered on an outside track and a laboratory VO2Peak test was conducted using a maximal treadmill protocol. Multiple linear regression was employed to develop the prediction model. Results yielded the following algorithm: VO2Peak = 7.34 × (1MRW speed in m s(-1)) + 0.23 × (age × sex) + 17.75. The New Model displayed a multiple correlation and prediction error of R = 0.81, standard error of the estimate = 4.78 ml kg(-1) · min(-1), with measured VO2Peak and good criterion-referenced (CR) agreement into FITNESSGRAM's Healthy Fitness Zone (Kappa = 0.62; percentage agreement = 84.4%; Φ = 0.62). The New Model was validated using k-fold cross-validation and showed homoscedastic residuals across the range of predicted scores. The omission of BMI did not compromise accuracy of the model. In conclusion, the New Model displayed good predictive accuracy and good CR agreement with measured VO2Peak in adolescents aged 13-16 years.

A Multidimensional Computerized Adaptive Short-Form Quality of Life Questionnaire Developed and Validated for Multiple Sclerosis: The MusiQoL-MCAT.

PubMed

Michel, Pierre; Baumstarck, Karine; Ghattas, Badih; Pelletier, Jean; Loundou, Anderson; Boucekine, Mohamed; Auquier, Pascal; Boyer, Laurent

2016-04-01

The aim was to develop a multidimensional computerized adaptive short-form questionnaire, the MusiQoL-MCAT, from a fixed-length QoL questionnaire for multiple sclerosis.A total of 1992 patients were enrolled in this international cross-sectional study. The development of the MusiQoL-MCAT was based on the assessment of between-items MIRT model fit followed by real-data simulations. The MCAT algorithm was based on Bayesian maximum a posteriori estimation of latent traits and Kullback-Leibler information item selection. We examined several simulations based on a fixed number of items. Accuracy was assessed using correlations (r) between initial IRT scores and MCAT scores. Precision was assessed using the standard error measurement (SEM) and the root mean square error (RMSE).The multidimensional graded response model was used to estimate item parameters and IRT scores. Among the MCAT simulations, the 16-item version of the MusiQoL-MCAT was selected because the accuracy and precision became stable with 16 items with satisfactory levels (r ≥ 0.9, SEM ≤ 0.55, and RMSE ≤ 0.3). External validity of the MusiQoL-MCAT was satisfactory.The MusiQoL-MCAT presents satisfactory properties and can individually tailor QoL assessment to each patient, making it less burdensome to patients and better adapted for use in clinical practice.

A Multidimensional Computerized Adaptive Short-Form Quality of Life Questionnaire Developed and Validated for Multiple Sclerosis

PubMed Central

Michel, Pierre; Baumstarck, Karine; Ghattas, Badih; Pelletier, Jean; Loundou, Anderson; Boucekine, Mohamed; Auquier, Pascal; Boyer, Laurent

2016-01-01

Abstract The aim was to develop a multidimensional computerized adaptive short-form questionnaire, the MusiQoL-MCAT, from a fixed-length QoL questionnaire for multiple sclerosis. A total of 1992 patients were enrolled in this international cross-sectional study. The development of the MusiQoL-MCAT was based on the assessment of between-items MIRT model fit followed by real-data simulations. The MCAT algorithm was based on Bayesian maximum a posteriori estimation of latent traits and Kullback–Leibler information item selection. We examined several simulations based on a fixed number of items. Accuracy was assessed using correlations (r) between initial IRT scores and MCAT scores. Precision was assessed using the standard error measurement (SEM) and the root mean square error (RMSE). The multidimensional graded response model was used to estimate item parameters and IRT scores. Among the MCAT simulations, the 16-item version of the MusiQoL-MCAT was selected because the accuracy and precision became stable with 16 items with satisfactory levels (r ≥ 0.9, SEM ≤ 0.55, and RMSE ≤ 0.3). External validity of the MusiQoL-MCAT was satisfactory. The MusiQoL-MCAT presents satisfactory properties and can individually tailor QoL assessment to each patient, making it less burdensome to patients and better adapted for use in clinical practice. PMID:27057832

In-line monitoring of cocrystallization process and quantification of carbamazepine-nicotinamide cocrystal using Raman spectroscopy and chemometric tools.

PubMed

Soares, Frederico L F; Carneiro, Renato L

2017-06-05

A cocrystallization process may involve several molecular species, which are generally solid under ambient conditions. Thus, accurate monitoring of different components that might appear during the reaction is necessary, as well as quantification of the final product. This work reports for the first time the synthesis of carbamazepine-nicotinamide cocrystal in aqueous media with a full conversion. The reactions were monitored by Raman spectroscopy coupled with Multivariate Curve Resolution - Alternating Least Squares, and the quantification of the final product among its coformers was performed using Raman spectroscopy and Partial Least Squares regression. The slurry reaction was made in four different conditions: room temperature, 40°C, 60°C and 80°C. The slurry reaction at 80°C enabled a full conversion of initial substrates into the cocrystal form, using water as solvent for a greener method. The employment of MCR-ALS coupled with Raman spectroscopy enabled to observe the main steps of the reactions, such as drug dissolution, nucleation and crystallization of the cocrystal. The PLS models gave mean errors of cross validation around 2.0 (% wt/wt), and errors of validation between 2.5 and 8.2 (% wt/wt) for all components. These were good results since the spectra of cocrystals and the physical mixture of the coformers present some similar peaks. Copyright © 2017 Elsevier B.V. All rights reserved.

In-line monitoring of cocrystallization process and quantification of carbamazepine-nicotinamide cocrystal using Raman spectroscopy and chemometric tools

NASA Astrophysics Data System (ADS)

Soares, Frederico L. F.; Carneiro, Renato L.

2017-06-01

A cocrystallization process may involve several molecular species, which are generally solid under ambient conditions. Thus, accurate monitoring of different components that might appear during the reaction is necessary, as well as quantification of the final product. This work reports for the first time the synthesis of carbamazepine-nicotinamide cocrystal in aqueous media with a full conversion. The reactions were monitored by Raman spectroscopy coupled with Multivariate Curve Resolution - Alternating Least Squares, and the quantification of the final product among its coformers was performed using Raman spectroscopy and Partial Least Squares regression. The slurry reaction was made in four different conditions: room temperature, 40 °C, 60 °C and 80 °C. The slurry reaction at 80 °C enabled a full conversion of initial substrates into the cocrystal form, using water as solvent for a greener method. The employment of MCR-ALS coupled with Raman spectroscopy enabled to observe the main steps of the reactions, such as drug dissolution, nucleation and crystallization of the cocrystal. The PLS models gave mean errors of cross validation around 2.0 (% wt/wt), and errors of validation between 2.5 and 8.2 (% wt/wt) for all components. These were good results since the spectra of cocrystals and the physical mixture of the coformers present some similar peaks.

Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution.

PubMed

Koch, Cosima; Posch, Andreas E; Goicoechea, Héctor C; Herwig, Christoph; Lendl, Bernhard

2014-01-07

This paper presents the quantification of Penicillin V and phenoxyacetic acid, a precursor, inline during Pencillium chrysogenum fermentations by FTIR spectroscopy and partial least squares (PLS) regression and multivariate curve resolution - alternating least squares (MCR-ALS). First, the applicability of an attenuated total reflection FTIR fiber optic probe was assessed offline by measuring standards of the analytes of interest and investigating matrix effects of the fermentation broth. Then measurements were performed inline during four fed-batch fermentations with online HPLC for the determination of Penicillin V and phenoxyacetic acid as reference analysis. PLS and MCR-ALS models were built using these data and validated by comparison of single analyte spectra with the selectivity ratio of the PLS models and the extracted spectral traces of the MCR-ALS models, respectively. The achieved root mean square errors of cross-validation for the PLS regressions were 0.22 g L(-1) for Penicillin V and 0.32 g L(-1) for phenoxyacetic acid and the root mean square errors of prediction for MCR-ALS were 0.23 g L(-1) for Penicillin V and 0.15 g L(-1) for phenoxyacetic acid. A general work-flow for building and assessing chemometric regression models for the quantification of multiple analytes in bioprocesses by FTIR spectroscopy is given. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

System and method for forward error correction

NASA Technical Reports Server (NTRS)

Cole, Robert M. (Inventor); Bishop, James E. (Inventor)

2006-01-01

A system and method are provided for transferring a packet across a data link. The packet may include a stream of data symbols which is delimited by one or more framing symbols. Corruptions of the framing symbol which result in valid data symbols may be mapped to invalid symbols. If it is desired to transfer one of the valid data symbols that has been mapped to an invalid symbol, the data symbol may be replaced with an unused symbol. At the receiving end, these unused symbols are replaced with the corresponding valid data symbols. The data stream of the packet may be encoded with forward error correction information to detect and correct errors in the data stream.

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

PubMed Central

Costa, Daniel G.; Guedes, Luiz Affonso

2011-01-01

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks. PMID:22163908

Development of analysis technique to predict the material behavior of blowing agent

NASA Astrophysics Data System (ADS)

Hwang, Ji Hoon; Lee, Seonggi; Hwang, So Young; Kim, Naksoo

2014-11-01

In order to numerically simulate the foaming behavior of mastic sealer containing the blowing agent, a foaming and driving force model are needed which incorporate the foaming characteristics. Also, the elastic stress model is required to represent the material behavior of co-existing phase of liquid state and the cured polymer. It is important to determine the thermal properties such as thermal conductivity and specific heat because foaming behavior is heavily influenced by temperature change. In this study, three models are proposed to explain the foaming process and material behavior during and after the process. To obtain the material parameters in each model, following experiments and the numerical simulations are performed: thermal test, simple shear test and foaming test. The error functions are defined as differences between the experimental measurements and the numerical simulation results, and then the parameters are determined by minimizing the error functions. To ensure the validity of the obtained parameters, the confirmation simulation for each model is conducted by applying the determined parameters. The cross-verification is performed by measuring the foaming/shrinkage force. The results of cross-verification tended to follow the experimental results. Interestingly, it was possible to estimate the micro-deformation occurring in automobile roof surface by applying the proposed model to oven process analysis. The application of developed analysis technique will contribute to the design with minimized micro-deformation.

On the validity and robustness of the scale error phenomenon in early childhood.

PubMed

DeLoache, Judy S; LoBue, Vanessa; Vanderborght, Mieke; Chiong, Cynthia

2013-02-01

Scale errors is a term referring to very young children's serious efforts to perform actions on miniature replica objects that are impossible due to great differences in the size of the child's body and the size of the target objects. We report three studies providing further documentation of scale errors and investigating the validity and robustness of the phenomenon. In the first, we establish that 2-year-olds' behavior in response to prompts to "pretend" with miniature replica objects differs dramatically from scale errors. The second and third studies address the robustness of the phenomenon and its relative imperviousness to attempts to influence the rate of scale errors. Copyright © 2012 Elsevier Inc. All rights reserved.

A new approach to the characterization of subtle errors in everyday action: implications for mild cognitive impairment.

PubMed

Seligman, Sarah C; Giovannetti, Tania; Sestito, John; Libon, David J

2014-01-01

Mild functional difficulties have been associated with early cognitive decline in older adults and increased risk for conversion to dementia in mild cognitive impairment, but our understanding of this decline has been limited by a dearth of objective methods. This study evaluated the reliability and validity of a new system to code subtle errors on an established performance-based measure of everyday action and described preliminary findings within the context of a theoretical model of action disruption. Here 45 older adults completed the Naturalistic Action Test (NAT) and neuropsychological measures. NAT performance was coded for overt errors, and subtle action difficulties were scored using a novel coding system. An inter-rater reliability coefficient was calculated. Validity of the coding system was assessed using a repeated-measures ANOVA with NAT task (simple versus complex) and error type (overt versus subtle) as within-group factors. Correlation/regression analyses were conducted among overt NAT errors, subtle NAT errors, and neuropsychological variables. The coding of subtle action errors was reliable and valid, and episodic memory breakdown predicted subtle action disruption. Results suggest that the NAT can be useful in objectively assessing subtle functional decline. Treatments targeting episodic memory may be most effective in addressing early functional impairment in older age.

New methodology to reconstruct in 2-D the cuspal enamel of modern human lower molars.

PubMed

Modesto-Mata, Mario; García-Campos, Cecilia; Martín-Francés, Laura; Martínez de Pinillos, Marina; García-González, Rebeca; Quintino, Yuliet; Canals, Antoni; Lozano, Marina; Dean, M Christopher; Martinón-Torres, María; Bermúdez de Castro, José María

2017-08-01

In the last years different methodologies have been developed to reconstruct worn teeth. In this article, we propose a new 2-D methodology to reconstruct the worn enamel of lower molars. Our main goals are to reconstruct molars with a high level of accuracy when measuring relevant histological variables and to validate the methodology calculating the errors associated with the measurements. This methodology is based on polynomial regression equations, and has been validated using two different dental variables: cuspal enamel thickness and crown height of the protoconid. In order to perform the validation process, simulated worn modern human molars were employed. The associated errors of the measurements were also estimated applying methodologies previously proposed by other authors. The mean percentage error estimated in reconstructed molars for these two variables in comparison with their own real values is -2.17% for the cuspal enamel thickness of the protoconid and -3.18% for the crown height of the protoconid. This error significantly improves the results of other methodologies, both in the interobserver error and in the accuracy of the measurements. The new methodology based on polynomial regressions can be confidently applied to the reconstruction of cuspal enamel of lower molars, as it improves the accuracy of the measurements and reduces the interobserver error. The present study shows that it is important to validate all methodologies in order to know the associated errors. This new methodology can be easily exportable to other modern human populations, the human fossil record and forensic sciences. © 2017 Wiley Periodicals, Inc.

Evaluation of a moderate resolution, satellite-based impervious surface map using an independent, high-resolution validation data set

USGS Publications Warehouse

Jones, J.W.; Jarnagin, T.

2009-01-01

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.

Validation of a new method for finding the rotational axes of the knee using both marker-based roentgen stereophotogrammetric analysis and 3D video-based motion analysis for kinematic measurements.

PubMed

Roland, Michelle; Hull, M L; Howell, S M

2011-05-01

In a previous paper, we reported the virtual axis finder, which is a new method for finding the rotational axes of the knee. The virtual axis finder was validated through simulations that were subject to limitations. Hence, the objective of the present study was to perform a mechanical validation with two measurement modalities: 3D video-based motion analysis and marker-based roentgen stereophotogrammetric analysis (RSA). A two rotational axis mechanism was developed, which simulated internal-external (or longitudinal) and flexion-extension (FE) rotations. The actual axes of rotation were known with respect to motion analysis and RSA markers within ± 0.0006 deg and ± 0.036 mm and ± 0.0001 deg and ± 0.016 mm, respectively. The orientation and position root mean squared errors for identifying the longitudinal rotation (LR) and FE axes with video-based motion analysis (0.26 deg, 0.28 m, 0.36 deg, and 0.25 mm, respectively) were smaller than with RSA (1.04 deg, 0.84 mm, 0.82 deg, and 0.32 mm, respectively). The random error or precision in the orientation and position was significantly better (p=0.01 and p=0.02, respectively) in identifying the LR axis with video-based motion analysis (0.23 deg and 0.24 mm) than with RSA (0.95 deg and 0.76 mm). There was no significant difference in the bias errors between measurement modalities. In comparing the mechanical validations to virtual validations, the virtual validations produced comparable errors to those of the mechanical validation. The only significant difference between the errors of the mechanical and virtual validations was the precision in the position of the LR axis while simulating video-based motion analysis (0.24 mm and 0.78 mm, p=0.019). These results indicate that video-based motion analysis with the equipment used in this study is the superior measurement modality for use with the virtual axis finder but both measurement modalities produce satisfactory results. The lack of significant differences between validation techniques suggests that the virtual sensitivity analysis previously performed was appropriately modeled. Thus, the virtual axis finder can be applied with a thorough understanding of its errors in a variety of test conditions.

Water equivalent thickness of immobilization devices in proton therapy planning - Modelling at treatment planning and validation by measurements with a multi-layer ionization chamber.

PubMed

Fellin, Francesco; Righetto, Roberto; Fava, Giovanni; Trevisan, Diego; Amelio, Dante; Farace, Paolo

2017-03-01

To investigate the range errors made in treatment planning due to the presence of the immobilization devices along the proton beam path. The measured water equivalent thickness (WET) of selected devices was measured by a high-energy spot and a multi-layer ionization chamber and compared with that predicted by treatment planning system (TPS). Two treatment couches, two thermoplastic masks (both un-stretched and stretched) and one headrest were selected. At TPS, every immobilization device was modelled as being part of the patient. The following parameters were assessed: CT acquisition protocol, dose-calculation grid-sizes (1.5 and 3.0mm) and beam-entrance with respect to the devices (coplanar and non-coplanar). Finally, the potential errors produced by a wrong manual separation between treatment couch and the CT table (not present during treatment) were investigated. In the thermoplastic mask, there was a clear effect due to beam entrance, a moderate effect due to the CT protocols and almost no effect due to TPS grid-size, with 1mm errors observed only when thick un-stretched portions were crossed by non-coplanar beams. In the treatment couches the WET errors were negligible (<0.3mm) regardless of the grid-size and CT protocol. The potential range errors produced in the manual separation between treatment couch and CT table were small with 1.5mm grid-size, but could be >0.5mm with a 3.0mm grid-size. In the headrest, WET errors were negligible (0.2mm). With only one exception (un-stretched mask, non-coplanar beams), the WET of all the immobilization devices was properly modelled by the TPS. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Automated Cross-Sectional Measurement Method of Intracranial Dural Venous Sinuses.

PubMed

Lublinsky, S; Friedman, A; Kesler, A; Zur, D; Anconina, R; Shelef, I

2016-03-01

MRV is an important blood vessel imaging and diagnostic tool for the evaluation of stenosis, occlusions, or aneurysms. However, an accurate image-processing tool for vessel comparison is unavailable. The purpose of this study was to develop and test an automated technique for vessel cross-sectional analysis. An algorithm for vessel cross-sectional analysis was developed that included 7 main steps: 1) image registration, 2) masking, 3) segmentation, 4) skeletonization, 5) cross-sectional planes, 6) clustering, and 7) cross-sectional analysis. Phantom models were used to validate the technique. The method was also tested on a control subject and a patient with idiopathic intracranial hypertension (4 large sinuses tested: right and left transverse sinuses, superior sagittal sinus, and straight sinus). The cross-sectional area and shape measurements were evaluated before and after lumbar puncture in patients with idiopathic intracranial hypertension. The vessel-analysis algorithm had a high degree of stability with <3% of cross-sections manually corrected. All investigated principal cranial blood sinuses had a significant cross-sectional area increase after lumbar puncture (P ≤ .05). The average triangularity of the transverse sinuses was increased, and the mean circularity of the sinuses was decreased by 6% ± 12% after lumbar puncture. Comparison of phantom and real data showed that all computed errors were <1 voxel unit, which confirmed that the method provided a very accurate solution. In this article, we present a novel automated imaging method for cross-sectional vessels analysis. The method can provide an efficient quantitative detection of abnormalities in the dural sinuses. © 2016 by American Journal of Neuroradiology.

Structural Validation of a French Food Frequency Questionnaire of 94 Items.

PubMed

Gazan, Rozenn; Vieux, Florent; Darmon, Nicole; Maillot, Matthieu

2017-01-01

Food frequency questionnaires (FFQs) are used to estimate the usual food and nutrient intakes over a period of time. Such estimates can suffer from measurement errors, either due to bias induced by respondent's answers or to errors induced by the structure of the questionnaire (e.g., using a limited number of food items and an aggregated food database with average portion sizes). The "structural validation" presented in this study aims to isolate and quantify the impact of the inherent structure of a FFQ on the estimation of food and nutrient intakes, independently of respondent's perception of the questionnaire. A semi-quantitative FFQ ( n  = 94 items, including 50 items with questions on portion sizes) and an associated aggregated food composition database (named the item-composition database) were developed, based on the self-reported weekly dietary records of 1918 adults (18-79 years-old) in the French Individual and National Dietary Survey 2 (INCA2), and the French CIQUAL 2013 food-composition database of all the foods ( n  = 1342 foods) declared as consumed in the population. Reference intakes of foods ("REF_FOOD") and nutrients ("REF_NUT") were calculated for each adult using the food-composition database and the amounts of foods self-reported in his/her dietary record. Then, answers to the FFQ were simulated for each adult based on his/her self-reported dietary record. "FFQ_FOOD" and "FFQ_NUT" intakes were estimated using the simulated answers and the item-composition database. Measurement errors (in %), spearman correlations and cross-classification were used to compare "REF_FOOD" with "FFQ_FOOD" and "REF_NUT" with "FFQ_NUT". Compared to "REF_NUT," "FFQ_NUT" total quantity and total energy intake were underestimated on average by 198 g/day and 666 kJ/day, respectively. "FFQ_FOOD" intakes were well estimated for starches, underestimated for most of the subgroups, and overestimated for some subgroups, in particular vegetables. Underestimation were mainly due to the use of portion sizes, leading to an underestimation of most of nutrients, except free sugars which were overestimated. The "structural validation" by simulating answers to a FFQ based on a reference dietary survey is innovative and pragmatic and allows quantifying the error induced by the simplification of the method of collection.

Experimental methods to validate measures of emotional state and readiness for duty in critical operations.

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

Weston, Louise Marie

2007-09-01

A recent report on criticality accidents in nuclear facilities indicates that human error played a major role in a significant number of incidents with serious consequences and that some of these human errors may be related to the emotional state of the individual. A pre-shift test to detect a deleterious emotional state could reduce the occurrence of such errors in critical operations. The effectiveness of pre-shift testing is a challenge because of the need to gather predictive data in a relatively short test period and the potential occurrence of learning effects due to a requirement for frequent testing. This reportmore » reviews the different types of reliability and validity methods and testing and statistical analysis procedures to validate measures of emotional state. The ultimate value of a validation study depends upon the percentage of human errors in critical operations that are due to the emotional state of the individual. A review of the literature to identify the most promising predictors of emotional state for this application is highly recommended.« less

Permanent-File-Validation Utility Computer Program

NASA Technical Reports Server (NTRS)

Derry, Stephen D.

1988-01-01

Errors in files detected and corrected during operation. Permanent File Validation (PFVAL) utility computer program provides CDC CYBER NOS sites with mechanism to verify integrity of permanent file base. Locates and identifies permanent file errors in Mass Storage Table (MST) and Track Reservation Table (TRT), in permanent file catalog entries (PFC's) in permit sectors, and in disk sector linkage. All detected errors written to listing file and system and job day files. Program operates by reading system tables , catalog track, permit sectors, and disk linkage bytes to vaidate expected and actual file linkages. Used extensively to identify and locate errors in permanent files and enable online correction, reducing computer-system downtime.

An empirical assessment of validation practices for molecular classifiers

PubMed Central

Castaldi, Peter J.; Dahabreh, Issa J.

2011-01-01

Proposed molecular classifiers may be overfit to idiosyncrasies of noisy genomic and proteomic data. Cross-validation methods are often used to obtain estimates of classification accuracy, but both simulations and case studies suggest that, when inappropriate methods are used, bias may ensue. Bias can be bypassed and generalizability can be tested by external (independent) validation. We evaluated 35 studies that have reported on external validation of a molecular classifier. We extracted information on study design and methodological features, and compared the performance of molecular classifiers in internal cross-validation versus external validation for 28 studies where both had been performed. We demonstrate that the majority of studies pursued cross-validation practices that are likely to overestimate classifier performance. Most studies were markedly underpowered to detect a 20% decrease in sensitivity or specificity between internal cross-validation and external validation [median power was 36% (IQR, 21–61%) and 29% (IQR, 15–65%), respectively]. The median reported classification performance for sensitivity and specificity was 94% and 98%, respectively, in cross-validation and 88% and 81% for independent validation. The relative diagnostic odds ratio was 3.26 (95% CI 2.04–5.21) for cross-validation versus independent validation. Finally, we reviewed all studies (n = 758) which cited those in our study sample, and identified only one instance of additional subsequent independent validation of these classifiers. In conclusion, these results document that many cross-validation practices employed in the literature are potentially biased and genuine progress in this field will require adoption of routine external validation of molecular classifiers, preferably in much larger studies than in current practice. PMID:21300697

Design and Validation of an Infrared Badal Optometer for Laser Speckle (IBOLS)

PubMed Central

Teel, Danielle F. W.; Copland, R. James; Jacobs, Robert J.; Wells, Thad; Neal, Daniel R.; Thibos, Larry N.

2009-01-01

Purpose To validate the design of an infrared wavefront aberrometer with a Badal optometer employing the principle of laser speckle generated by a spinning disk and infrared light. The instrument was designed for subjective meridional refraction in infrared light by human patients. Methods Validation employed a model eye with known refractive error determined with an objective infrared wavefront aberrometer. The model eye was used to produce a speckle pattern on an artificial retina with controlled amounts of ametropia introduced with auxiliary ophthalmic lenses. A human observer performed the psychophysical task of observing the speckle pattern (with the aid of a video camera sensitive to infrared radiation) formed on the artificial retina. Refraction was performed by adjusting the vergence of incident light with the Badal optometer to nullify the motion of laser speckle. Validation of the method was performed for different levels of spherical ametropia and for various configurations of an astigmatic model eye. Results Subjective measurements of meridional refractive error over the range −4D to + 4D agreed with astigmatic refractive errors predicted by the power of the model eye in the meridian of motion of the spinning disk. Conclusions Use of a Badal optometer to control laser speckle is a valid method for determining subjective refractive error at infrared wavelengths. Such an instrument will be useful for comparing objective measures of refractive error obtained for the human eye with autorefractors and wavefront aberrometers that employ infrared radiation. PMID:18772719

The Most Common Geometric and Semantic Errors in CityGML Datasets

NASA Astrophysics Data System (ADS)

Biljecki, F.; Ledoux, H.; Du, X.; Stoter, J.; Soon, K. H.; Khoo, V. H. S.

2016-10-01

To be used as input in most simulation and modelling software, 3D city models should be geometrically and topologically valid, and semantically rich. We investigate in this paper what is the quality of currently available CityGML datasets, i.e. we validate the geometry/topology of the 3D primitives (Solid and MultiSurface), and we validate whether the semantics of the boundary surfaces of buildings is correct or not. We have analysed all the CityGML datasets we could find, both from portals of cities and on different websites, plus a few that were made available to us. We have thus validated 40M surfaces in 16M 3D primitives and 3.6M buildings found in 37 CityGML datasets originating from 9 countries, and produced by several companies with diverse software and acquisition techniques. The results indicate that CityGML datasets without errors are rare, and those that are nearly valid are mostly simple LOD1 models. We report on the most common errors we have found, and analyse them. One main observation is that many of these errors could be automatically fixed or prevented with simple modifications to the modelling software. Our principal aim is to highlight the most common errors so that these are not repeated in the future. We hope that our paper and the open-source software we have developed will help raise awareness for data quality among data providers and 3D GIS software producers.

Cross-calibration of MODIS with ETM+ and ALI sensors for long-term monitoring of land surface processes

USGS Publications Warehouse

Meyer, D.; Chander, G.

2006-01-01

Increasingly, data from multiple sensors are used to gain a more complete understanding of land surface processes at a variety of scales. Although higher-level products (e.g., vegetation cover, albedo, surface temperature) derived from different sensors can be validated independently, the degree to which these sensors and their products can be compared to one another is vastly improved if their relative spectroradiometric responses are known. Most often, sensors are directly calibrated to diffuse solar irradiation or vicariously to ground targets. However, space-based targets are not traceable to metrological standards, and vicarious calibrations are expensive and provide a poor sampling of a sensor's full dynamic range. Crosscalibration of two sensors can augment these methods if certain conditions can be met: (1) the spectral responses are similar, (2) the observations are reasonably concurrent (similar atmospheric & solar illumination conditions), (3) errors due to misregistrations of inhomogeneous surfaces can be minimized (including scale differences), and (4) the viewing geometry is similar (or, some reasonable knowledge of surface bi-directional reflectance distribution functions is available). This study explores the impacts of cross-calibrating sensors when such conditions are met to some degree but not perfectly. In order to constrain the range of conditions at some level, the analysis is limited to sensors where cross-calibration studies have been conducted (Enhanced Thematic Mapper Plus (ETM+) on Landsat-7 (L7), Advance Land Imager (ALI) and Hyperion on Earth Observer-1 (EO-1)) and including systems having somewhat dissimilar geometry, spatial resolution & spectral response characteristics but are still part of the so-called "A.M. constellation" (Moderate Resolution Imaging Spectrometer (MODIS) aboard the Terra platform). Measures for spectral response differences and methods for cross calibrating such sensors are provided in this study. These instruments are cross calibrated using the Railroad Valley playa in Nevada. Best fit linear coefficients (slope and offset) are provided for ALI-to-MODIS and ETM+-to-MODIS cross calibrations, and root-mean-squared errors (RMSEs) and correlation coefficients are provided to quantify the uncertainty in these relationships. In theory, the linear fits and uncertainties can be used to compare radiance and reflectance products derived from each instrument.

A rational approach to legacy data validation when transitioning between electronic health record systems.

PubMed

Pageler, Natalie M; Grazier G'Sell, Max Jacob; Chandler, Warren; Mailes, Emily; Yang, Christine; Longhurst, Christopher A

2016-09-01

The objective of this project was to use statistical techniques to determine the completeness and accuracy of data migrated during electronic health record conversion. Data validation during migration consists of mapped record testing and validation of a sample of the data for completeness and accuracy. We statistically determined a randomized sample size for each data type based on the desired confidence level and error limits. The only error identified in the post go-live period was a failure to migrate some clinical notes, which was unrelated to the validation process. No errors in the migrated data were found during the 12- month post-implementation period. Compared to the typical industry approach, we have demonstrated that a statistical approach to sampling size for data validation can ensure consistent confidence levels while maximizing efficiency of the validation process during a major electronic health record conversion. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Statistically Controlling for Confounding Constructs Is Harder than You Think

PubMed Central

Westfall, Jacob; Yarkoni, Tal

2016-01-01

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

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.

Procedural Error and Task Interruption

DTIC Science & Technology

2016-09-30

red for research on errors and individual differences . Results indicate predictive validity for fluid intelligence and specifi c forms of work...TERMS procedural error, task interruption, individual differences , fluid intelligence, sleep deprivation 16. SECURITY CLASSIFICATION OF: 17...and individual differences . It generates rich data on several kinds of errors, including procedural errors in which steps are skipped or repeated

Two-dimensional radial laser scanning for circular marker detection and external mobile robot tracking.

PubMed

Teixidó, Mercè; Pallejà, Tomàs; Font, Davinia; Tresanchez, Marcel; Moreno, Javier; Palacín, Jordi

2012-11-28

This paper presents the use of an external fixed two-dimensional laser scanner to detect cylindrical targets attached to moving devices, such as a mobile robot. This proposal is based on the detection of circular markers in the raw data provided by the laser scanner by applying an algorithm for outlier avoidance and a least-squares circular fitting. Some experiments have been developed to empirically validate the proposal with different cylindrical targets in order to estimate the location and tracking errors achieved, which are generally less than 20 mm in the area covered by the laser sensor. As a result of the validation experiments, several error maps have been obtained in order to give an estimate of the uncertainty of any location computed. This proposal has been validated with a medium-sized mobile robot with an attached cylindrical target (diameter 200 mm). The trajectory of the mobile robot was estimated with an average location error of less than 15 mm, and the real location error in each individual circular fitting was similar to the error estimated with the obtained error maps. The radial area covered in this validation experiment was up to 10 m, a value that depends on the radius of the cylindrical target and the radial density of the distance range points provided by the laser scanner but this area can be increased by combining the information of additional external laser scanners.

The work role functioning questionnaire 2.0 (Dutch version): examination of its reliability, validity and responsiveness in the general working population.

PubMed

Abma, Femke I; van der Klink, Jac J L; Bültmann, Ute

2013-03-01

The promotion of a sustainable, healthy and productive working life attracts more and more attention. Recently the Work Role Functioning Questionnaire (WRFQ) has been cross-culturally translated and adapted to Dutch. This questionnaire aims to measure the health-related work functioning of workers with health problems. The aim of this study is to evaluate the reliability, validity (including five new items) and responsiveness of the WRFQ 2.0 in the working population. A longitudinal study was conducted among workers. The reliability (internal consistency, test-retest reliability, measurement error), validity (structural validity-factor analysis, construct validity by means of hypotheses testing) and responsiveness of the WRFQ 2.0 were evaluated. A total of N = 553 workers completed the survey. The final WRFQ 2.0 has four subscales and showed very good internal consistency, moderate test-retest reliability, good construct validity and moderate responsiveness in the working population. The WRFQ was able to distinguish between groups with different levels of mental health, physical health, fatigue and need for recovery. A moderate correlation was found between WRFQ and related constructs respectively work ability and work productivity. A weak relationship was found with general self-rated health, work engagement and work involvement. The WRFQ 2.0 is a reliable and valid instrument to measure health-related work functioning in the working population. Further validation in larger samples is recommended, especially for test-retest reliability, responsiveness and the questionnaire's ability to predict the future course of health-related work functioning.

Simulated Driving Assessment (SDA) for Teen Drivers: Results from a Validation Study

PubMed Central

McDonald, Catherine C.; Kandadai, Venk; Loeb, Helen; Seacrist, Thomas S.; Lee, Yi-Ching; Winston, Zachary; Winston, Flaura K.

2015-01-01

Background Driver error and inadequate skill are common critical reasons for novice teen driver crashes, yet few validated, standardized assessments of teen driving skills exist. The purpose of this study was to evaluate the construct and criterion validity of a newly developed Simulated Driving Assessment (SDA) for novice teen drivers. Methods The SDA's 35-minute simulated drive incorporates 22 variations of the most common teen driver crash configurations. Driving performance was compared for 21 inexperienced teens (age 16–17 years, provisional license ≤90 days) and 17 experienced adults (age 25–50 years, license ≥5 years, drove ≥100 miles per week, no collisions or moving violations ≤3 years). SDA driving performance (Error Score) was based on driving safety measures derived from simulator and eye-tracking data. Negative driving outcomes included simulated collisions or run-off-the-road incidents. A professional driving evaluator/instructor reviewed videos of SDA performance (DEI Score). Results The SDA demonstrated construct validity: 1.) Teens had a higher Error Score than adults (30 vs. 13, p=0.02); 2.) For each additional error committed, the relative risk of a participant's propensity for a simulated negative driving outcome increased by 8% (95% CI: 1.05–1.10, p<0.01). The SDA demonstrated criterion validity: Error Score was correlated with DEI Score (r=−0.66, p<0.001). Conclusions This study supports the concept of validated simulated driving tests like the SDA to assess novice driver skill in complex and hazardous driving scenarios. The SDA, as a standard protocol to evaluate teen driver performance, has the potential to facilitate screening and assessment of teen driving readiness and could be used to guide targeted skill training. PMID:25740939

Study on the Rationality and Validity of Probit Models of Domino Effect to Chemical Process Equipment caused by Overpressure

NASA Astrophysics Data System (ADS)

Sun, Dongliang; Huang, Guangtuan; Jiang, Juncheng; Zhang, Mingguang; Wang, Zhirong

2013-04-01

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Some models considering propagation probability and threshold values of the domino effect caused by overpressure have been proposed in previous study. In order to prove the rationality and validity of the models reported in the reference, two boundary values of three damage degrees reported were considered as random variables respectively in the interval [0, 100%]. Based on the overpressure data for damage to the equipment and the damage state, and the calculation method reported in the references, the mean square errors of the four categories of damage probability models of overpressure were calculated with random boundary values, and then a relationship of mean square error vs. the two boundary value was obtained, the minimum of mean square error was obtained, compared with the result of the present work, mean square error decreases by about 3%. Therefore, the error was in the acceptable range of engineering applications, the models reported can be considered reasonable and valid.

Computational Modeling of Aortic Valvular Stenosis to Asses the Range of Validity of Gorlin Equation

NASA Astrophysics Data System (ADS)

Okpara, Emanuel; Agarwal, Ramesh; Rifkin, Robert; Wendl, Mike

2003-11-01

It is well known from clinical observations that the underestimation errors occur with the use of Gorlin formula (1) for the calculation of valve area of the stenotic aortic valve in patients with low cardiac output, that is in low flow states. Since 1951, empirical modifications to Gorlin formula have been proposed in the literaure by many researchers. In this paper, we study the mild to severe aortic valve stenosis for low to high flow rates by employing a simplified model of aortic valve. The aortic valve stenosis is modeled by a circular orifice in a flat plate embedded in the cross-section of a rigid tube (aorta). Experimental results are available for this configuration for the validation of a CFD solver "FLUENT". The numerical data base generated for this model for various degrees of stenoses and flow rates is employed to asses the range of validity of Gorlin's equation. Modifications to Gorlin formula are suggested to make it valid for all flow rates to determine the valve area for clinical use. (1) R. Gorlin and S. Gorlin," Hydraulic Formula for Calculation of the Area of Stenotic Mitral Valve, Other Cardiac Valves and Central Circulatory Shunts," Am. Heart Journal, Vol. 41, 1951, pp. 1-29.

Masking of errors in transmission of VAPC-coded speech

NASA Technical Reports Server (NTRS)

Cox, Neil B.; Froese, Edwin L.

1990-01-01

A subjective evaluation is provided of the bit error sensitivity of the message elements of a Vector Adaptive Predictive (VAPC) speech coder, along with an indication of the amenability of these elements to a popular error masking strategy (cross frame hold over). As expected, a wide range of bit error sensitivity was observed. The most sensitive message components were the short term spectral information and the most significant bits of the pitch and gain indices. The cross frame hold over strategy was found to be useful for pitch and gain information, but it was not beneficial for the spectral information unless severe corruption had occurred.

A MIMO radar quadrature and multi-channel amplitude-phase error combined correction method based on cross-correlation

NASA Astrophysics Data System (ADS)

Yun, Lingtong; Zhao, Hongzhong; Du, Mengyuan

2018-04-01

Quadrature and multi-channel amplitude-phase error have to be compensated in the I/Q quadrature sampling and signal through multi-channel. A new method that it doesn't need filter and standard signal is presented in this paper. And it can combined estimate quadrature and multi-channel amplitude-phase error. The method uses cross-correlation and amplitude ratio between the signal to estimate the two amplitude-phase errors simply and effectively. And the advantages of this method are verified by computer simulation. Finally, the superiority of the method is also verified by measure data of outfield experiments.

Sensitivity Analysis of Nuclide Importance to One-Group Neutron Cross Sections

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

Sekimoto, Hiroshi; Nemoto, Atsushi; Yoshimura, Yoshikane

The importance of nuclides is useful when investigating nuclide characteristics in a given neutron spectrum. However, it is derived using one-group microscopic cross sections, which may contain large errors or uncertainties. The sensitivity coefficient shows the effect of these errors or uncertainties on the importance.The equations for calculating sensitivity coefficients of importance to one-group nuclear constants are derived using the perturbation method. Numerical values are also evaluated for some important cases for fast and thermal reactor systems.Many characteristics of the sensitivity coefficients are derived from the derived equations and numerical results. The matrix of sensitivity coefficients seems diagonally dominant. However,more » it is not always satisfied in a detailed structure. The detailed structure of the matrix and the characteristics of coefficients are given.By using the obtained sensitivity coefficients, some demonstration calculations have been performed. The effects of error and uncertainty of nuclear data and of the change of one-group cross-section input caused by fuel design changes through the neutron spectrum are investigated. These calculations show that the sensitivity coefficient is useful when evaluating error or uncertainty of nuclide importance caused by the cross-section data error or uncertainty and when checking effectiveness of fuel cell or core design change for improving neutron economy.« less

Development of a refractive error quality of life scale for Thai adults (the REQ-Thai).

PubMed

Sukhawarn, Roongthip; Wiratchai, Nonglak; Tatsanavivat, Pyatat; Pitiyanuwat, Somwung; Kanato, Manop; Srivannaboon, Sabong; Guyatt, Gordon H

2011-08-01

To develop a scale for measuring refractive error quality of life (QOL) for Thai adults. The full survey comprised 424 respondents from 5 medical centers in Bangkok and from 3 medical centers in Chiangmai, Songkla and KhonKaen provinces. Participants were emmetropes and persons with refractive correction with visual acuity of 20/30 or better An item reduction process was employed by combining 3 methods-expert opinion, impact method and item-total correlation methods. The classical reliability testing and the validity testing including convergent, discriminative and construct validity was performed. The developed questionnaire comprised 87 items in 6 dimensions: 1) quality of vision, 2) visual function, 3) social function, 4) psychological function, 5) symptoms and 6) refractive correction problems. It is the 5-level Likert scale type. The Cronbach's Alpha coefficients of its dimensions ranged from 0.756 to 0. 979. All validity testing were shown to be valid. The construct validity was validated by the confirmatory factor analysis. A short version questionnaire comprised 48 items with good reliability and validity was also developed. This is the first validated instrument for measuring refractive error quality of life for Thai adults that was developed with strong research methodology and large sample size.

Determination of Semivariogram Models to Krige Hourly and Daily Solar Irradiance in Western Nebraska(.

NASA Astrophysics Data System (ADS)

Merino, G. G.; Jones, D.; Stooksbury, D. E.; Hubbard, K. G.

2001-06-01

In this paper, linear and spherical semivariogram models were determined for use in kriging hourly and daily solar irradiation for every season of the year. The data used to generate the models were from 18 weather stations in western Nebraska. The models generated were tested using cross validation. The performance of the spherical and linear semivariogram models were compared with each other and also with the semivariogram models based on the best fit to the sample semivariogram of a particular day or hour. There were no significant differences in the performance of the three models. This result and the comparable errors produced by the models in kriging indicated that the linear and spherical models could be used to perform kriging at any hour and day of the year without deriving an individual semivariogram model for that day or hour.The seasonal mean absolute errors associated with kriging, within the network, when using the spherical or the linear semivariograms models were between 10% and 13% of the mean irradiation for daily irradiation and between 12% and 20% for hourly irradiation. These errors represent an improvement of 1%-2% when compared with replacing data at a given site with the data of the nearest weather station.

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

PubMed

Li, Wen-bing; Yao, Lin-tao; Liu, Mu-hua; Huang, Lin; Yao, Ming-yin; Chen, Tian-bing; He, Xiu-wen; Yang, Ping; Hu, Hui-qin; Nie, Jiang-hui

2015-05-01

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

Predicting Pilot Error in Nextgen: Pilot Performance Modeling and Validation Efforts

NASA Technical Reports Server (NTRS)

Wickens, Christopher; Sebok, Angelia; Gore, Brian; Hooey, Becky

2012-01-01

We review 25 articles presenting 5 general classes of computational models to predict pilot error. This more targeted review is placed within the context of the broader review of computational models of pilot cognition and performance, including such aspects as models of situation awareness or pilot-automation interaction. Particular emphasis is placed on the degree of validation of such models against empirical pilot data, and the relevance of the modeling and validation efforts to Next Gen technology and procedures.

Computer adaptive test approach to the assessment of children and youth with brachial plexus birth palsy.

PubMed

Mulcahey, M J; Merenda, Lisa; Tian, Feng; Kozin, Scott; James, Michelle; Gogola, Gloria; Ni, Pengsheng

2013-01-01

This study examined the psychometric properties of item pools relevant to upper-extremity function and activity performance and evaluated simulated 5-, 10-, and 15-item computer adaptive tests (CATs). In a multicenter, cross-sectional study of 200 children and youth with brachial plexus birth palsy (BPBP), parents responded to upper-extremity (n = 52) and activity (n = 34) items using a 5-point response scale. We used confirmatory and exploratory factor analysis, ordinal logistic regression, item maps, and standard errors to evaluate the psychometric properties of the item banks. Validity was evaluated using analysis of variance and Pearson correlation coefficients. Results show that the two item pools have acceptable model fit, scaled well for children and youth with BPBP, and had good validity, content range, and precision. Simulated CATs performed comparably to the full item banks, suggesting that a reduced number of items provide similar information to the entire set of items. Copyright © 2013 by the American Occupational Therapy Association, Inc.

Comparison of artificial intelligence classifiers for SIP attack data

NASA Astrophysics Data System (ADS)

Safarik, Jakub; Slachta, Jiri

2016-05-01

Honeypot application is a source of valuable data about attacks on the network. We run several SIP honeypots in various computer networks, which are separated geographically and logically. Each honeypot runs on public IP address and uses standard SIP PBX ports. All information gathered via honeypot is periodically sent to the centralized server. This server classifies all attack data by neural network algorithm. The paper describes optimizations of a neural network classifier, which lower the classification error. The article contains the comparison of two neural network algorithm used for the classification of validation data. The first is the original implementation of the neural network described in recent work; the second neural network uses further optimizations like input normalization or cross-entropy cost function. We also use other implementations of neural networks and machine learning classification algorithms. The comparison test their capabilities on validation data to find the optimal classifier. The article result shows promise for further development of an accurate SIP attack classification engine.

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression.

PubMed

Martínez Gila, Diego Manuel; Cano Marchal, Pablo; Gómez Ortega, Juan; Gámez García, Javier

2018-03-25

Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation.

Sexing California Clapper Rails using morphological measurements

USGS Publications Warehouse

Overton, Cory T.; Casazza, Michael L.; Takekawa, John Y.; Rohmer, Tobias M.

2009-01-01

California Clapper Rails (Rallus longirostris obsoletus) have monomorphic plumage, a trait that makes identification of sex difficult without extensive behavioral observation or genetic testing. Using 31 Clapper Rails (22 females, 9 males), caught in south San Francisco Bay, CA, and using easily measurable morphological characteristics, we developed a discriminant function to distinguish sex. We then validated this function on 33 additional rails. Seven morphological measurements were considered, resulting in three which were selected in the discriminate function: culmen length, tarsometatarsus length, and flat wing length. We had no classification errors for the development or testing datasets either with resubstitution or cross-validation procedures. Male California Clapper Rails were 6-22% larger than females for individual morphological traits, and the largest difference was in body mass.  Variables in our discriminant function closely match variables developed for sexing Clapper Rails of Gulf Coast populations. However, a universal discriminant function to sex all Clapper Rail subspecies is not likely because of large and inconsistent differences in morphological traits among subspecies. 

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression

PubMed Central

Cano Marchal, Pablo; Gómez Ortega, Juan; Gámez García, Javier

2018-01-01

Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation. PMID:29587403

Modeling RP-1 fuel advanced distillation data using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry and partial least squares analysis.

PubMed

Kehimkar, Benjamin; Parsons, Brendon A; Hoggard, Jamin C; Billingsley, Matthew C; Bruno, Thomas J; Synovec, Robert E

2015-01-01

Recent efforts in predicting rocket propulsion (RP-1) fuel performance through modeling put greater emphasis on obtaining detailed and accurate fuel properties, as well as elucidating the relationships between fuel compositions and their properties. Herein, we study multidimensional chromatographic data obtained by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (GC × GC-TOFMS) to analyze RP-1 fuels. For GC × GC separations, RTX-Wax (polar stationary phase) and RTX-1 (non-polar stationary phase) columns were implemented for the primary and secondary dimensions, respectively, to separate the chemical compound classes (alkanes, cycloalkanes, aromatics, etc.), providing a significant level of chemical compositional information. The GC × GC-TOFMS data were analyzed using partial least squares regression (PLS) chemometric analysis to model and predict advanced distillation curve (ADC) data for ten RP-1 fuels that were previously analyzed using the ADC method. The PLS modeling provides insight into the chemical species that impact the ADC data. The PLS modeling correlates compositional information found in the GC × GC-TOFMS chromatograms of each RP-1 fuel, and their respective ADC, and allows prediction of the ADC for each RP-1 fuel with good precision and accuracy. The root-mean-square error of calibration (RMSEC) ranged from 0.1 to 0.5 °C, and was typically below ∼0.2 °C, for the PLS calibration of the ADC modeling with GC × GC-TOFMS data, indicating a good fit of the model to the calibration data. Likewise, the predictive power of the overall method via PLS modeling was assessed using leave-one-out cross-validation (LOOCV) yielding root-mean-square error of cross-validation (RMSECV) ranging from 1.4 to 2.6 °C, and was typically below ∼2.0 °C, at each % distilled measurement point during the ADC analysis.

Analysis of Twenty-Two Performance Properties of Diesel, Gasoline, and Jet Fuels Using a Field-Portable Near-Infrared (NIR) Analyzer.

PubMed

Brouillette, Carl; Smith, Wayne; Shende, Chetan; Gladding, Zack; Farquharson, Stuart; Morris, Robert E; Cramer, Jeffrey A; Schmitigal, Joel

2016-05-01

The change in custody of fuel shipments at depots, pipelines, and ports could benefit from an analyzer that could rapidly verify that properties are within specifications. To meet this need, the design requirements for a fuel analyzer based on near-infrared (NIR) spectroscopy, such as spectral region and resolution, were examined. It was found that the 1000 to 1600 nm region, containing the second CH overtone and combination vibrational modes of hydrocarbons, provided the best near-infrared to fuel property correlations when path length was taken into account, whereas 4 cm(-1) resolution provided only a modest improvement compared to 16 cm(-1) resolution when four or more latent variables were used. Based on these results, a field-portable near-infrared fuel analyzer was built that employed an incandescent light source, sample compartment optics to hold 2 mL glass sample vials with ∼1 cm path length, a transmission grating, and a 256 channel InGaAs detector that measured the above stated wavelength range with 5-6 nm (∼32 cm(-1)) resolution. The analyzer produced high signal-to-noise ratio (SNR) spectra of samples in 5 s. Twenty-two property correlation models were developed for diesel, gasoline, and jet fuels with root mean squared error of correlation - cross-validated values that compared favorably to corresponding ASTM reproducibility values. The standard deviations of predicted properties for repeat measurements at 4, 24, and 38℃ were often better than ASTM documented repeatability values. The analyzer and diesel property models were tested by measuring seven diesel samples at a local ASTM certification laboratory. The standard deviations between the analyzer determined values and the ASTM measured values for these samples were generally better than the model root mean squared error of correlation-cross-validated values for each property. © The Author(s) 2016.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

PubMed

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

Laser Metrology Heterodyne Phase-Locked Loop

NASA Technical Reports Server (NTRS)

Loya, Frank; Halverson, Peter

2009-01-01

A method reduces sensitivity to noise in a signal from a laser heterodyne interferometer. The phase-locked loop (PLL) removes glitches that occur in a zero-crossing detector s output [that can happen if the signal-to-noise ratio (SNR) of the heterodyne signal is low] by the use of an internal oscillator that produces a square-wave signal at a frequency that is inherently close to the heterodyne frequency. It also contains phase-locking circuits that lock the phase of the oscillator to the output of the zero-crossing detector. Because the PLL output is an oscillator signal, it is glitch-free. This enables the ability to make accurate phase measurements in spite of low SNR, creates an immunity to phase error caused by shifts in the heterodyne frequency (i.e. if the target moves causing Doppler shift), and maintains a valid phase even when the signal drops out for brief periods of time, such as when the laser is blocked by a stray object.

Clustering redshift distributions for the Dark Energy Survey

NASA Astrophysics Data System (ADS)

Helsby, Jennifer

Accurate determination of photometric redshifts and their errors is critical for large scale structure and weak lensing studies for constraining cosmology from deep, wide imaging surveys. Current photometric redshift methods suffer from bias and scatter due to incomplete training sets. Exploiting the clustering between a sample of galaxies for which we have spectroscopic redshifts and a sample of galaxies for which the redshifts are unknown can allow us to reconstruct the true redshift distribution of the unknown sample. Here we use this method in both simulations and early data from the Dark Energy Survey (DES) to determine the true redshift distributions of galaxies in photometric redshift bins. We find that cross-correlating with the spectroscopic samples currently used for training provides a useful test of photometric redshifts and provides reliable estimates of the true redshift distribution in a photometric redshift bin. We discuss the use of the cross-correlation method in validating template- or learning-based approaches to redshift estimation and its future use in Stage IV surveys.

Developing a dengue forecast model using machine learning: A case study in China.

PubMed

Guo, Pi; Liu, Tao; Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

2017-10-01

In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.

Multibody Kinematics Optimization for the Estimation of Upper and Lower Limb Human Joint Kinematics: A Systematized Methodological Review.

PubMed

Begon, Mickaël; Andersen, Michael Skipper; Dumas, Raphaël

2018-03-01

Multibody kinematics optimization (MKO) aims to reduce soft tissue artefact (STA) and is a key step in musculoskeletal modeling. The objective of this review was to identify the numerical methods, their validation and performance for the estimation of the human joint kinematics using MKO. Seventy-four papers were extracted from a systematized search in five databases and cross-referencing. Model-derived kinematics were obtained using either constrained optimization or Kalman filtering to minimize the difference between measured (i.e., by skin markers, electromagnetic or inertial sensors) and model-derived positions and/or orientations. While hinge, universal, and spherical joints prevail, advanced models (e.g., parallel and four-bar mechanisms, elastic joint) have been introduced, mainly for the knee and shoulder joints. Models and methods were evaluated using: (i) simulated data based, however, on oversimplified STA and joint models; (ii) reconstruction residual errors, ranging from 4 mm to 40 mm; (iii) sensitivity analyses which highlighted the effect (up to 36 deg and 12 mm) of model geometrical parameters, joint models, and computational methods; (iv) comparison with other approaches (i.e., single body kinematics optimization and nonoptimized kinematics); (v) repeatability studies that showed low intra- and inter-observer variability; and (vi) validation against ground-truth bone kinematics (with errors between 1 deg and 22 deg for tibiofemoral rotations and between 3 deg and 10 deg for glenohumeral rotations). Moreover, MKO was applied to various movements (e.g., walking, running, arm elevation). Additional validations, especially for the upper limb, should be undertaken and we recommend a more systematic approach for the evaluation of MKO. In addition, further model development, scaling, and personalization methods are required to better estimate the secondary degrees-of-freedom (DoF).

Population pharmacokinetics and maximum a posteriori probability Bayesian estimator of abacavir: application of individualized therapy in HIV-infected infants and toddlers

PubMed Central

Zhao, Wei; Cella, Massimo; Della Pasqua, Oscar; Burger, David; Jacqz-Aigrain, Evelyne

2012-01-01

AIMS To develop a population pharmacokinetic model for abacavir in HIV-infected infants and toddlers, which will be used to describe both once and twice daily pharmacokinetic profiles, identify covariates that explain variability and propose optimal time points to optimize the area under the concentration–time curve (AUC) targeted dosage and individualize therapy. METHODS The pharmacokinetics of abacavir was described with plasma concentrations from 23 patients using nonlinear mixed-effects modelling (NONMEM) software. A two-compartment model with first-order absorption and elimination was developed. The final model was validated using bootstrap, visual predictive check and normalized prediction distribution errors. The Bayesian estimator was validated using the cross-validation and simulation–estimation method. RESULTS The typical population pharmacokinetic parameters and relative standard errors (RSE) were apparent systemic clearance (CL) 13.4 l h−1 (RSE 6.3%), apparent central volume of distribution 4.94 l (RSE 28.7%), apparent peripheral volume of distribution 8.12 l (RSE14.2%), apparent intercompartment clearance 1.25 l h−1 (RSE 16.9%) and absorption rate constant 0.758 h−1 (RSE 5.8%). The covariate analysis identified weight as the individual factor influencing the apparent oral clearance: CL = 13.4 × (weight/12)1.14. The maximum a posteriori probability Bayesian estimator, based on three concentrations measured at 0, 1 or 2, and 3 h after drug intake allowed predicting individual AUC0–t. CONCLUSIONS The population pharmacokinetic model developed for abacavir in HIV-infected infants and toddlers accurately described both once and twice daily pharmacokinetic profiles. The maximum a posteriori probability Bayesian estimator of AUC0–t was developed from the final model and can be used routinely to optimize individual dosing. PMID:21988586

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

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

Cross-cultural application of the Korean version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 15-Palliative Care.

PubMed

Shin, Dong Wook; Choi, Ji Eun; Miyashita, Mitsunori; Choi, Jin Young; Kang, Jina; Baik, Young Ji; Mo, Ha Na; Park, Jeanno; Kim, Hea-Ja; Park, Eun Cheol

2011-02-01

The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 15-Palliative Care (EORTC QLQ-C15-PAL) is a shortened version of the EORTC QLQ-C30, developed for use in advanced cancer patients. We evaluated the psychometric properties of the Korean version of the EORTC QLQ-C15-PAL to determine if this tool can be used to evaluate Korean patients with cancer who receive palliative care. A multicenter, cross-sectional survey was performed in palliative care units and hospices in Korea from September to October 2009. A total of 102 patients with cancer completed the questionnaires that included the EORTC QLQ-C15-PAL. The compliance rate was high, with the missing rate for each item ranging from 0% to 7.8% (mean 3.1%). A multitrait scaling analysis revealed good convergent and discriminant validity, with only three scaling errors. The Cronbach's alpha coefficients ranged from 0.65 to 0.89. The questionnaire discriminated among patient subgroups with different clinical profiles (e.g., performance status and degree of oral intake), thereby demonstrating the clinical validity of this tool. Our findings indicate that the Korean version of the EORTC QLQ-C15-PAL is a reliable and valid instrument with regard to its psychometric properties. This tool is suitable for measuring quality of life, particularly with regard to physical aspects, in Korean cancer patients who receive palliative care. Copyright © 2011 U.S. Cancer Pain Relief Committee. Published by Elsevier Inc. All rights reserved.

Design and validation of a portable, inexpensive and multi-beam timing light system using the Nintendo Wii hand controllers.

PubMed

Clark, Ross A; Paterson, Kade; Ritchie, Callan; Blundell, Simon; Bryant, Adam L

2011-03-01

Commercial timing light systems (CTLS) provide precise measurement of athletes running velocity, however they are often expensive and difficult to transport. In this study an inexpensive, wireless and portable timing light system was created using the infrared camera in Nintendo Wii hand controllers (NWHC). System creation with gold-standard validation. A Windows-based software program using NWHC to replicate a dual-beam timing gate was created. Firstly, data collected during 2m walking and running trials were validated against a 3D kinematic system. Secondly, data recorded during 5m running trials at various intensities from standing or flying starts were compared to a single beam CTLS and the independent and average scores of three handheld stopwatch (HS) operators. Intraclass correlation coefficient and Bland-Altman plots were used to assess validity. Absolute error quartiles and percentage of trials in absolute error threshold ranges were used to determine accuracy. The NWHC system was valid when compared against the 3D kinematic system (ICC=0.99, median absolute error (MAR)=2.95%). For the flying 5m trials the NWHC system possessed excellent validity and precision (ICC=0.97, MAR<3%) when compared with the CTLS. In contrast, the NWHC system and the HS values during standing start trials possessed only modest validity (ICC<0.75) and accuracy (MAR>8%). A NWHC timing light system is inexpensive, portable and valid for assessing running velocity. Errors in the 5m standing start trials may have been due to erroneous event detection by either the commercial or NWHC-based timing light systems. Copyright © 2010 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Cross-cultural validity of the theory of planned behavior for predicting healthy food choice in secondary school students of Inner Mongolia.

PubMed

Shimazaki, Takashi; Bao, Hugejiletu; Deli, Geer; Uechi, Hiroaki; Lee, Ying-Hua; Miura, Kayo; Takenaka, Koji

2017-11-01

Unhealthy eating behavior is a serious health concern among secondary school students in Inner Mongolia. To predict their healthy food choices and devise methods of correcting unhealthy choices, we sought to confirm the cross-cultural validity of the theory of planned behavior among Inner Mongolian students. A cross-sectional study, conducted between November and December 2014. Overall, 3047 students were enrolled. We devised a questionnaire based on the theory of planned behavior to measure its components (intentions, attitudes, subjective norms, and perceived behavioral control) in relation to healthy food choices; we also assessed their current engagement in healthy food choices. A principal component analysis revealed high contribution rates for the components (69.32%-88.77%). A confirmatory factor analysis indicated that the components of the questionnaire had adequate model fit (goodness of fit index=0.997, adjusted goodness of fit index=0.984, comparative fit index=0.998, and root mean square error of approximation=0.049). Notably, data from participants within the suburbs did not support the theory of planned behavior construction. Several paths did not predict the hypothesis variables. However, attitudes toward healthy food choices strongly predicted behavioral intention (path coefficients 0.49-0.77, p<0.01), regardless of demographic characteristics. Our results support that the theory of planned behavior can apply to secondary school students in urban areas. Furthermore, attitudes towards healthy food choices were the best predictor of behavioral intentions to engage in such choices in Inner Mongolian students. Copyright © 2017 Diabetes India. Published by Elsevier Ltd. All rights reserved.

A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals

PubMed Central

Bonato, Matteo; Papini, Gabriele; Bosio, Andrea; Mohammed, Rahil A.; Bonomi, Alberto G.; Moore, Jonathan P.; Merati, Giampiero; La Torre, Antonio; Kubis, Hans-Peter

2016-01-01

Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included. PMID:27959935

A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals.

PubMed

Sartor, Francesco; Bonato, Matteo; Papini, Gabriele; Bosio, Andrea; Mohammed, Rahil A; Bonomi, Alberto G; Moore, Jonathan P; Merati, Giampiero; La Torre, Antonio; Kubis, Hans-Peter

2016-01-01

Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included.

TH-CD-202-06: A Method for Characterizing and Validating Dynamic Lung Density Change During Quiet Respiration

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

Dou, T; Ruan, D; Heinrich, M

2016-06-15

Purpose: To obtain a functional relationship that calibrates the lung tissue density change under free breathing conditions through correlating Jacobian values to the Hounsfield units. Methods: Free-breathing lung computed tomography images were acquired using a fast helical CT protocol, where 25 scans were acquired per patient. Using a state-of-the-art deformable registration algorithm, a set of the deformation vector fields (DVF) was generated to provide spatial mapping from the reference image geometry to the other free-breathing scans. These DVFs were used to generate Jacobian maps, which estimate voxelwise volume change. Subsequently, the set of 25 corresponding Jacobian and voxel intensity inmore » Hounsfield units (HU) were collected and linear regression was performed based on the mass conservation relationship to correlate the volume change to density change. Based on the resulting fitting coefficients, the tissues were classified into parenchymal (Type I), vascular (Type II), and soft tissue (Type III) types. These coefficients modeled the voxelwise density variation during quiet breathing. The accuracy of the proposed method was assessed using mean absolute difference in HU between the CT scan intensities and the model predicted values. In addition, validation experiments employing a leave-five-out method were performed to evaluate the model accuracy. Results: The computed mean model errors were 23.30±9.54 HU, 29.31±10.67 HU, and 35.56±20.56 HU, respectively, for regions I, II, and III, respectively. The cross validation experiments averaged over 100 trials had mean errors of 30.02 ± 1.67 HU over the entire lung. These mean values were comparable with the estimated CT image background noise. Conclusion: The reported validation experiment statistics confirmed the lung density modeling during free breathing. The proposed technique was general and could be applied to a wide range of problem scenarios where accurate dynamic lung density information is needed. This work was supported in part by NIH R01 CA0096679.« less

Measuring positive mental health in Canada: construct validation of the Mental Health Continuum—Short Form

PubMed Central

Heather, Orpana; Julie, Vachon; Jennifer, Dykxhoorn; Gayatri, Jayaraman

2017-01-01

Abstract Introduction: Positive mental health is increasingly recognized as an important focus for public health policies and programs. In Canada, the Mental Health Continuum— Short Form (MHC-SF) was identified as a promising measure to include on population surveys to measure positive mental health. It proposes to measure a three-factor model of positive mental health including emotional, social and psychological well-being. The purpose of this study was to examine whether the MHC-SF is an adequate measure of positive mental health for Canadian adults. Methods: We conducted confirmatory factor analysis (CFA) using data from the 2012 Canadian Community Health Survey (CCHS)—Mental Health Component (CCHS-MH), and cross-validated the model using data from the CCHS 2011–2012 annual cycle. We examined criterion-related validity through correlations of MHC-SF subscale scores with positively and negatively associated concepts (e.g. life satisfaction and psychological distress, respectively). Results: We confirmed the validity of the three-factor model of emotional, social and psychological well-being through CFA on two independent samples, once four correlated errors between items on the social well-being scale were added. We observed significant correlations in the anticipated direction between emotional, psychological and social well-being scores and related concepts. Cronbach’s alpha for both emotional and psychological well-being subscales was 0.82; for social well-being it was 0.77. Conclusion: Our study suggests that the MHC-SF measures a three-factor model of positive mental health in the Canadian population. However, caution is warranted when using the social well-being scale, which did not function as well as the other factors, as evidenced by the need to add several correlated error terms to obtain adequate model fit, a higher level of missing data on these questions and weaker correlations with related constructs. Social well-being is important in a comprehensive measure of positive mental health, and further research is recommended. PMID:28402801

Measuring positive mental health in Canada: construct validation of the Mental Health Continuum-Short Form.

PubMed

Orpana, Heather; Vachon, Julie; Dykxhoorn, Jennifer; Jayaraman, Gayatri

2017-04-01

Positive mental health is increasingly recognized as an important focus for public health policies and programs. In Canada, the Mental Health Continuum-Short Form (MHC-SF) was identified as a promising measure to include on population surveys to measure positive mental health. It proposes to measure a three-factor model of positive mental health including emotional, social and psychological well-being. The purpose of this study was to examine whether the MHC-SF is an adequate measure of positive mental health for Canadian adults. We conducted confirmatory factor analysis (CFA) using data from the 2012 Canadian Community Health Survey (CCHS)-Mental Health Component (CCHS-MH), and cross-validated the model using data from the CCHS 2011-2012 annual cycle. We examined criterion-related validity through correlations of MHC-SF subscale scores with positively and negatively associated concepts (e.g. life satisfaction and psychological distress, respectively). We confirmed the validity of the three-factor model of emotional, social and psychological well-being through CFA on two independent samples, once four correlated errors between items on the social well-being scale were added. We observed significant correlations in the anticipated direction between emotional, psychological and social well-being scores and related concepts. Cronbach's alpha for both emotional and psychological well-being subscales was 0.82; for social well-being it was 0.77. Our study suggests that the MHC-SF measures a three-factor model of positive mental health in the Canadian population. However, caution is warranted when using the social well-being scale, which did not function as well as the other factors, as evidenced by the need to add several correlated error terms to obtain adequate model fit, a higher level of missing data on these questions and weaker correlations with related constructs. Social well-being is important in a comprehensive measure of positive mental health, and further research is recommended.

Continuous correction of differential path length factor in near-infrared spectroscopy

PubMed Central

Moore, Jason H.; Diamond, Solomon G.

2013-01-01

Abstract. In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively correct for artificially introduced errors in DPF and to reduce the cross-talk error in simulation. With experimental CW-NIRS data, the hemodynamic estimates from EKF differ significantly from the WLSQ (p<0.001). The cross-correlations among residuals at different wavelengths were found to be significantly reduced by the EKF method compared to WLSQ in three physiologically relevant spectral bands 0.04 to 0.15 Hz, 0.15 to 0.4 Hz and 0.4 to 2.0 Hz (p<0.001). This observed reduction in residual cross-correlation is consistent with reduced cross-talk error in the hemodynamic estimates from the proposed EKF method. PMID:23640027

Continuous correction of differential path length factor in near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Talukdar, Tanveer; Moore, Jason H.; Diamond, Solomon G.

2013-05-01

In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively correct for artificially introduced errors in DPF and to reduce the cross-talk error in simulation. With experimental CW-NIRS data, the hemodynamic estimates from EKF differ significantly from the WLSQ (p<0.001). The cross-correlations among residuals at different wavelengths were found to be significantly reduced by the EKF method compared to WLSQ in three physiologically relevant spectral bands 0.04 to 0.15 Hz, 0.15 to 0.4 Hz and 0.4 to 2.0 Hz (p<0.001). This observed reduction in residual cross-correlation is consistent with reduced cross-talk error in the hemodynamic estimates from the proposed EKF method.

Error Orientation and Reflection at Work

ERIC Educational Resources Information Center

Hetzner, Stefanie; Gartmeier, Martin; Heid, Helmut; Gruber, Hans

2011-01-01

Reflection on events at work, including errors is often as a means to learn effectively through work. In a cross-sectional field study in the banking sector, we investigated attitudes towards workplace errors (i.e. error orientation) as predictors of reflective activity. We assumed the organisational climate for psychological safety to have a…

Multimodal assessment of visual attention using the Bethesda Eye & Attention Measure (BEAM).

PubMed

Ettenhofer, Mark L; Hershaw, Jamie N; Barry, David M

2016-01-01

Computerized cognitive tests measuring manual response time (RT) and errors are often used in the assessment of visual attention. Evidence suggests that saccadic RT and errors may also provide valuable information about attention. This study was conducted to examine a novel approach to multimodal assessment of visual attention incorporating concurrent measurements of saccadic eye movements and manual responses. A computerized cognitive task, the Bethesda Eye & Attention Measure (BEAM) v.34, was designed to evaluate key attention networks through concurrent measurement of saccadic and manual RT and inhibition errors. Results from a community sample of n = 54 adults were analyzed to examine effects of BEAM attention cues on manual and saccadic RT and inhibition errors, internal reliability of BEAM metrics, relationships between parallel saccadic and manual metrics, and relationships of BEAM metrics to demographic characteristics. Effects of BEAM attention cues (alerting, orienting, interference, gap, and no-go signals) were consistent with previous literature examining key attention processes. However, corresponding saccadic and manual measurements were weakly related to each other, and only manual measurements were related to estimated verbal intelligence or years of education. This study provides preliminary support for the feasibility of multimodal assessment of visual attention using the BEAM. Results suggest that BEAM saccadic and manual metrics provide divergent measurements. Additional research will be needed to obtain comprehensive normative data, to cross-validate BEAM measurements with other indicators of neural and cognitive function, and to evaluate the utility of these metrics within clinical populations of interest.

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

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

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

Standard Errors for National Trends in International Large-Scale Assessments in the Case of Cross-National Differential Item Functioning

ERIC Educational Resources Information Center

Sachse, Karoline A.; Haag, Nicole

2017-01-01

Standard errors computed according to the operational practices of international large-scale assessment studies such as the Programme for International Student Assessment's (PISA) or the Trends in International Mathematics and Science Study (TIMSS) may be biased when cross-national differential item functioning (DIF) and item parameter drift are…

Survival analysis with error-prone time-varying covariates: a risk set calibration approach

PubMed Central

Liao, Xiaomei; Zucker, David M.; Li, Yi; Spiegelman, Donna

2010-01-01

Summary Occupational, environmental, and nutritional epidemiologists are often interested in estimating the prospective effect of time-varying exposure variables such as cumulative exposure or cumulative updated average exposure, in relation to chronic disease endpoints such as cancer incidence and mortality. From exposure validation studies, it is apparent that many of the variables of interest are measured with moderate to substantial error. Although the ordinary regression calibration approach is approximately valid and efficient for measurement error correction of relative risk estimates from the Cox model with time-independent point exposures when the disease is rare, it is not adaptable for use with time-varying exposures. By re-calibrating the measurement error model within each risk set, a risk set regression calibration method is proposed for this setting. An algorithm for a bias-corrected point estimate of the relative risk using an RRC approach is presented, followed by the derivation of an estimate of its variance, resulting in a sandwich estimator. Emphasis is on methods applicable to the main study/external validation study design, which arises in important applications. Simulation studies under several assumptions about the error model were carried out, which demonstrated the validity and efficiency of the method in finite samples. The method was applied to a study of diet and cancer from Harvard’s Health Professionals Follow-up Study (HPFS). PMID:20486928

A novel validation and calibration method for motion capture systems based on micro-triangulation.

PubMed

Nagymáté, Gergely; Tuchband, Tamás; Kiss, Rita M

2018-06-06

Motion capture systems are widely used to measure human kinematics. Nevertheless, users must consider system errors when evaluating their results. Most validation techniques for these systems are based on relative distance and displacement measurements. In contrast, our study aimed to analyse the absolute volume accuracy of optical motion capture systems by means of engineering surveying reference measurement of the marker coordinates (uncertainty: 0.75 mm). The method is exemplified on an 18 camera OptiTrack Flex13 motion capture system. The absolute accuracy was defined by the root mean square error (RMSE) between the coordinates measured by the camera system and by engineering surveying (micro-triangulation). The original RMSE of 1.82 mm due to scaling error was managed to be reduced to 0.77 mm while the correlation of errors to their distance from the origin reduced from 0.855 to 0.209. A simply feasible but less accurate absolute accuracy compensation method using tape measure on large distances was also tested, which resulted in similar scaling compensation compared to the surveying method or direct wand size compensation by a high precision 3D scanner. The presented validation methods can be less precise in some respects as compared to previous techniques, but they address an error type, which has not been and cannot be studied with the previous validation methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predicting free-living energy expenditure using a miniaturized ear-worn sensor: an evaluation against doubly labeled water.

PubMed

Bouarfa, Loubna; Atallah, Louis; Kwasnicki, Richard Mark; Pettitt, Claire; Frost, Gary; Yang, Guang-Zhong

2014-02-01

Accurate estimation of daily total energy expenditure (EE)is a prerequisite for assisted weight management and assessing certain health conditions. The use of wearable sensors for predicting free-living EE is challenged by consistent sensor placement, user compliance, and estimation methods used. This paper examines whether a single ear-worn accelerometer can be used for EE estimation under free-living conditions.An EE prediction model as first derived and validated in a controlled setting using healthy subjects involving different physical activities. Ten different activities were assessed showing a tenfold cross validation error of 0.24. Furthermore, the EE prediction model shows a mean absolute deviation(MAD) below 1.2 metabolic equivalent of tasks. The same model was applied to a free-living setting with a different population for further validation. The results were compared against those derived from doubly labeled water. In free-living settings, the predicted daily EE has a correlation of 0.74, p 0.008, and a MAD of 272 kcal day. These results demonstrate that laboratory-derived prediction models can be used to predict EE under free-living conditions [corrected].

Mirage: a visible signature evaluation tool

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Meehan, Alaster J.; Shao, Q. T.; Richards, Noel

2017-10-01

This paper presents the Mirage visible signature evaluation tool, designed to provide a visible signature evaluation capability that will appropriately reflect the effect of scene content on the detectability of targets, providing a capability to assess visible signatures in the context of the environment. Mirage is based on a parametric evaluation of input images, assessing the value of a range of image metrics and combining them using the boosted decision tree machine learning method to produce target detectability estimates. It has been developed using experimental data from photosimulation experiments, where human observers search for vehicle targets in a variety of digital images. The images used for tool development are synthetic (computer generated) images, showing vehicles in many different scenes and exhibiting a wide variation in scene content. A preliminary validation has been performed using k-fold cross validation, where 90% of the image data set was used for training and 10% of the image data set was used for testing. The results of the k-fold validation from 200 independent tests show a prediction accuracy between Mirage predictions of detection probability and observed probability of detection of r(262) = 0:63, p < 0:0001 (Pearson correlation) and a MAE = 0:21 (mean absolute error).

Classification of breast cancer cytological specimen using convolutional neural network

NASA Astrophysics Data System (ADS)

Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

2017-01-01

The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

PubMed

Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

2007-03-07

Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

Acoustic Evidence for Phonologically Mismatched Speech Errors

ERIC Educational Resources Information Center

Gormley, Andrea

2015-01-01

Speech errors are generally said to accommodate to their new phonological context. This accommodation has been validated by several transcription studies. The transcription methodology is not the best choice for detecting errors at this level, however, as this type of error can be difficult to perceive. This paper presents an acoustic analysis of…

Perceptual Bias in Speech Error Data Collection: Insights from Spanish Speech Errors

ERIC Educational Resources Information Center

Perez, Elvira; Santiago, Julio; Palma, Alfonso; O'Seaghdha, Padraig G.

2007-01-01

This paper studies the reliability and validity of naturalistic speech errors as a tool for language production research. Possible biases when collecting naturalistic speech errors are identified and specific predictions derived. These patterns are then contrasted with published reports from Germanic languages (English, German and Dutch) and one…

Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation

PubMed Central

Adams, James; Kruger, Uwe; Geis, Elizabeth; Gehn, Eva; Fimbres, Valeria; Pollard, Elena; Mitchell, Jessica; Ingram, Julie; Hellmers, Robert; Quig, David; Hahn, Juergen

2017-01-01

Introduction A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate with the severity of ASD. Methods In order to further investigate these points, this paper performs the most detailed statistical analysis to date of a data set in this field. First morning urine samples were collected from 67 children and adults with ASD and 50 neurotypical controls of similar age and gender. The samples were analyzed to determine the levels of 10 urinary toxic metals (UTM). Autism-related symptoms were assessed with eleven behavioral measures. Statistical analysis was used to distinguish participants on the ASD spectrum and neurotypical participants based upon the UTM data alone. The analysis also included examining the association of autism severity with toxic metal excretion data using linear and nonlinear analysis. “Leave-one-out” cross-validation was used to ensure statistical independence of results. Results and Discussion Average excretion levels of several toxic metals (lead, tin, thallium, antimony) were significantly higher in the ASD group. However, ASD classification using univariate statistics proved difficult due to large variability, but nonlinear multivariate statistical analysis significantly improved ASD classification with Type I/II errors of 15% and 18%, respectively. These results clearly indicate that the urinary toxic metal excretion profiles of participants in the ASD group were significantly different from those of the neurotypical participants. Similarly, nonlinear methods determined a significantly stronger association between the behavioral measures and toxic metal excretion. The association was strongest for the Aberrant Behavior Checklist (including subscales on Irritability, Stereotypy, Hyperactivity, and Inappropriate Speech), but significant associations were found for UTM with all eleven autism-related assessments with cross-validation R2 values ranging from 0.12–0.48. PMID:28068407

Measuring socioeconomic status in multicountry studies: results from the eight-country MAL-ED study

PubMed Central

2014-01-01

Background There is no standardized approach to comparing socioeconomic status (SES) across multiple sites in epidemiological studies. This is particularly problematic when cross-country comparisons are of interest. We sought to develop a simple measure of SES that would perform well across diverse, resource-limited settings. Methods A cross-sectional study was conducted with 800 children aged 24 to 60 months across eight resource-limited settings. Parents were asked to respond to a household SES questionnaire, and the height of each child was measured. A statistical analysis was done in two phases. First, the best approach for selecting and weighting household assets as a proxy for wealth was identified. We compared four approaches to measuring wealth: maternal education, principal components analysis, Multidimensional Poverty Index, and a novel variable selection approach based on the use of random forests. Second, the selected wealth measure was combined with other relevant variables to form a more complete measure of household SES. We used child height-for-age Z-score (HAZ) as the outcome of interest. Results Mean age of study children was 41 months, 52% were boys, and 42% were stunted. Using cross-validation, we found that random forests yielded the lowest prediction error when selecting assets as a measure of household wealth. The final SES index included access to improved water and sanitation, eight selected assets, maternal education, and household income (the WAMI index). A 25% difference in the WAMI index was positively associated with a difference of 0.38 standard deviations in HAZ (95% CI 0.22 to 0.55). Conclusions Statistical learning methods such as random forests provide an alternative to principal components analysis in the development of SES scores. Results from this multicountry study demonstrate the validity of a simplified SES index. With further validation, this simplified index may provide a standard approach for SES adjustment across resource-limited settings. PMID:24656134

Update: Validation, Edits, and Application Processing. Phase II and Error-Prone Model Report.

ERIC Educational Resources Information Center

Gray, Susan; And Others

An update to the Validation, Edits, and Application Processing and Error-Prone Model Report (Section 1, July 3, 1980) is presented. The objective is to present the most current data obtained from the June 1980 Basic Educational Opportunity Grant applicant and recipient files and to determine whether the findings reported in Section 1 of the July…

The Error Prone Model and the Basic Grants Validation Selection System. Draft Final Report.

ERIC Educational Resources Information Center

System Development Corp., Falls Church, VA.

An evaluation of existing and proposed mechanisms to ensure data accuracy for the Pell Grant program is reported, and recommendations for efficient detection of fraud and error in the program are offered. One study objective was to examine the existing system of pre-established criteria (PEC), which are validation criteria that select students on…

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2015-01-01

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

Simulating trait evolution for cross-cultural comparison.

PubMed

Nunn, Charles L; Arnold, Christian; Matthews, Luke; Borgerhoff Mulder, Monique

2010-12-12

Cross-cultural anthropologists have increasingly used phylogenetic methods to study cultural variation. Because cultural behaviours can be transmitted horizontally among socially defined groups, however, it is important to assess whether phylogeny-based methods--which were developed to study vertically transmitted traits among biological taxa--are appropriate for studying group-level cultural variation. Here, we describe a spatially explicit simulation model that can be used to generate data with known degrees of horizontal donation. We review previous results from this model showing that horizontal transmission increases the type I error rate of phylogenetically independent contrasts in studies of correlated evolution. These conclusions apply to cases in which two traits are transmitted as a pair, but horizontal transmission may be less problematic when traits are unlinked. We also use the simulation model to investigate whether measures of homology (the consistency index and the retention index) can detect horizontal transmission of cultural traits. Higher rates of evolutionary change have a stronger depressive impact on measures of homology than higher rates of horizontal transmission; thus, low consistency or retention indices are not necessarily indicative of 'ethnogenesis'. Collectively, these studies demonstrate the importance of using simulations to assess the validity of methods in cross-cultural research.

Quantification of construction waste prevented by BIM-based design validation: Case studies in South Korea.

PubMed

Won, Jongsung; Cheng, Jack C P; Lee, Ghang

2016-03-01

Waste generated in construction and demolition processes comprised around 50% of the solid waste in South Korea in 2013. Many cases show that design validation based on building information modeling (BIM) is an effective means to reduce the amount of construction waste since construction waste is mainly generated due to improper design and unexpected changes in the design and construction phases. However, the amount of construction waste that could be avoided by adopting BIM-based design validation has been unknown. This paper aims to estimate the amount of construction waste prevented by a BIM-based design validation process based on the amount of construction waste that might be generated due to design errors. Two project cases in South Korea were studied in this paper, with 381 and 136 design errors detected, respectively during the BIM-based design validation. Each design error was categorized according to its cause and the likelihood of detection before construction. The case studies show that BIM-based design validation could prevent 4.3-15.2% of construction waste that might have been generated without using BIM. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comparison of smartphone and paper data-collection tools in the Burden of Obstructive Lung Disease (BOLD) study in Gezira state, Sudan

PubMed Central

Ahmed, Rana; Robinson, Ryan; Elsony, Asma; Thomson, Rachael; Squire, S. Bertel; Malmborg, Rasmus; Burney, Peter

2018-01-01

Introduction Data collection using paper-based questionnaires can be time consuming and return errors affect data accuracy, completeness, and information quality in health surveys. We compared smartphone and paper-based data collection systems in the Burden of Obstructive Lung Disease (BOLD) study in rural Sudan. Methods This exploratory pilot study was designed to run in parallel with the cross-sectional household survey. The Open Data Kit was used to programme questionnaires in Arabic into smartphones. We included 100 study participants (83% women; median age = 41.5 ± 16.4 years) from the BOLD study from 3 rural villages in East-Gezira and Kamleen localities of Gezira state, Sudan. Questionnaire data were collected using smartphone and paper-based technologies simultaneously. We used Kappa statistics and inter-rater class coefficient to test agreement between the two methods. Results Symptoms reported included cough (24%), phlegm (15%), wheezing (17%), and shortness of breath (18%). One in five were or had been cigarette smokers. The two data collection methods varied between perfect to slight agreement across the 204 variables evaluated (Kappa varied between 1.00 and 0.02 and inter-rater coefficient between 1.00 and -0.12). Errors were most commonly seen with paper questionnaires (83% of errors seen) vs smartphones (17% of errors seen) administered questionnaires with questions with complex skip-patterns being a major source of errors in paper questionnaires. Automated checks and validations in smartphone-administered questionnaires avoided skip-pattern related errors. Incomplete and inconsistent records were more likely seen on paper questionnaires. Conclusion Compared to paper-based data collection, smartphone technology worked well for data collection in the study, which was conducted in a challenging rural environment in Sudan. This approach provided timely, quality data with fewer errors and inconsistencies compared to paper-based data collection. We recommend this method for future BOLD studies and other population-based studies in similar settings. PMID:29518132

Development and validation of a composite scoring system for robot-assisted surgical training--the Robotic Skills Assessment Score.

PubMed

Chowriappa, Ashirwad J; Shi, Yi; Raza, Syed Johar; Ahmed, Kamran; Stegemann, Andrew; Wilding, Gregory; Kaouk, Jihad; Peabody, James O; Menon, Mani; Hassett, James M; Kesavadas, Thenkurussi; Guru, Khurshid A

2013-12-01

A standardized scoring system does not exist in virtual reality-based assessment metrics to describe safe and crucial surgical skills in robot-assisted surgery. This study aims to develop an assessment score along with its construct validation. All subjects performed key tasks on previously validated Fundamental Skills of Robotic Surgery curriculum, which were recorded, and metrics were stored. After an expert consensus for the purpose of content validation (Delphi), critical safety determining procedural steps were identified from the Fundamental Skills of Robotic Surgery curriculum and a hierarchical task decomposition of multiple parameters using a variety of metrics was used to develop Robotic Skills Assessment Score (RSA-Score). Robotic Skills Assessment mainly focuses on safety in operative field, critical error, economy, bimanual dexterity, and time. Following, the RSA-Score was further evaluated for construct validation and feasibility. Spearman correlation tests performed between tasks using the RSA-Scores indicate no cross correlation. Wilcoxon rank sum tests were performed between the two groups. The proposed RSA-Score was evaluated on non-robotic surgeons (n = 15) and on expert-robotic surgeons (n = 12). The expert group demonstrated significantly better performance on all four tasks in comparison to the novice group. Validation of the RSA-Score in this study was carried out on the Robotic Surgical Simulator. The RSA-Score is a valid scoring system that could be incorporated in any virtual reality-based surgical simulator to achieve standardized assessment of fundamental surgical tents during robot-assisted surgery. Copyright © 2013 Elsevier Inc. All rights reserved.

Noncredible cognitive performance at clinical evaluation of adult ADHD: An embedded validity indicator in a visuospatial working memory test.

PubMed

Fuermaier, Anselm B M; Tucha, Oliver; Koerts, Janneke; Lange, Klaus W; Weisbrod, Matthias; Aschenbrenner, Steffen; Tucha, Lara

2017-12-01

The assessment of performance validity is an essential part of the neuropsychological evaluation of adults with attention-deficit/hyperactivity disorder (ADHD). Most available tools, however, are inaccurate regarding the identification of noncredible performance. This study describes the development of a visuospatial working memory test, including a validity indicator for noncredible cognitive performance of adults with ADHD. Visuospatial working memory of adults with ADHD (n = 48) was first compared to the test performance of healthy individuals (n = 48). Furthermore, a simulation design was performed including 252 individuals who were randomly assigned to either a control group (n = 48) or to 1 of 3 simulation groups who were requested to feign ADHD (n = 204). Additional samples of 27 adults with ADHD and 69 instructed simulators were included to cross-validate findings from the first samples. Adults with ADHD showed impaired visuospatial working memory performance of medium size as compared to healthy individuals. Simulation groups committed significantly more errors and had shorter response times as compared to patients with ADHD. Moreover, binary logistic regression analysis was carried out to derive a validity index that optimally differentiates between true and feigned ADHD. ROC analysis demonstrated high classification rates of the validity index, as shown in excellent specificity (95.8%) and adequate sensitivity (60.3%). The visuospatial working memory test as presented in this study therefore appears sensitive in indicating cognitive impairment of adults with ADHD. Furthermore, the embedded validity index revealed promising results concerning the detection of noncredible cognitive performance of adults with ADHD. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The PDB_REDO server for macromolecular structure model optimization.

PubMed

Joosten, Robbie P; Long, Fei; Murshudov, Garib N; Perrakis, Anastassis

2014-07-01

The refinement and validation of a crystallographic structure model is the last step before the coordinates and the associated data are submitted to the Protein Data Bank (PDB). The success of the refinement procedure is typically assessed by validating the models against geometrical criteria and the diffraction data, and is an important step in ensuring the quality of the PDB public archive [Read et al. (2011 ▶), Structure, 19, 1395-1412]. The PDB_REDO procedure aims for 'constructive validation', aspiring to consistent and optimal refinement parameterization and pro-active model rebuilding, not only correcting errors but striving for optimal interpretation of the electron density. A web server for PDB_REDO has been implemented, allowing thorough, consistent and fully automated optimization of the refinement procedure in REFMAC and partial model rebuilding. The goal of the web server is to help practicing crystallo-graphers to improve their model prior to submission to the PDB. For this, additional steps were implemented in the PDB_REDO pipeline, both in the refinement procedure, e.g. testing of resolution limits and k-fold cross-validation for small test sets, and as new validation criteria, e.g. the density-fit metrics implemented in EDSTATS and ligand validation as implemented in YASARA. Innovative ways to present the refinement and validation results to the user are also described, which together with auto-generated Coot scripts can guide users to subsequent model inspection and improvement. It is demonstrated that using the server can lead to substantial improvement of structure models before they are submitted to the PDB.

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.

LACIE performance predictor final operational capability program description, volume 1

NASA Technical Reports Server (NTRS)

1976-01-01

The program EPHEMS computes the orbital parameters for up to two vehicles orbiting the earth for up to 549 days. The data represents a continuous swath about the earth, producing tables which can be used to determine when and if certain land segments will be covered. The program GRID processes NASA's climatology tape to obtain the weather indices along with associated latitudes and longitudes. The program LUMP takes substrata historical data and sample segment ID, crop window, crop window error and statistical data, checks for valid input parameters and generates the segment ID file, crop window file and the substrata historical file. Finally, the System Error Executive (SEE) Program checks YES error and truth data, CAMS error data, and signature extension data for validity and missing elements. A message is printed for each error found.