Sampling methods for microbiological analysis of red meat and poultry carcasses.

PubMed

Capita, Rosa; Prieto, Miguel; Alonso-Calleja, Carlos

2004-06-01

Microbiological analysis of carcasses at slaughterhouses is required in the European Union for evaluating the hygienic performance of carcass production processes as required for effective hazard analysis critical control point implementation. The European Union microbial performance standards refer exclusively to the excision method, even though swabbing using the wet/dry technique is also permitted when correlation between both destructive and nondestructive methods can be established. For practical and economic reasons, the swab technique is the most extensively used carcass surface-sampling method. The main characteristics, advantages, and limitations of the common excision and swabbing methods are described here.

Model-Based Linkage Analysis of a Quantitative Trait.

PubMed

Song, Yeunjoo E; Song, Sunah; Schnell, Audrey H

2017-01-01

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

Reliability-Based Stability Analysis of Rock Slopes Using Numerical Analysis and Response Surface Method

NASA Astrophysics Data System (ADS)

Dadashzadeh, N.; Duzgun, H. S. B.; Yesiloglu-Gultekin, N.

2017-08-01

While advanced numerical techniques in slope stability analysis are successfully used in deterministic studies, they have so far found limited use in probabilistic analyses due to their high computation cost. The first-order reliability method (FORM) is one of the most efficient probabilistic techniques to perform probabilistic stability analysis by considering the associated uncertainties in the analysis parameters. However, it is not possible to directly use FORM in numerical slope stability evaluations as it requires definition of a limit state performance function. In this study, an integrated methodology for probabilistic numerical modeling of rock slope stability is proposed. The methodology is based on response surface method, where FORM is used to develop an explicit performance function from the results of numerical simulations. The implementation of the proposed methodology is performed by considering a large potential rock wedge in Sumela Monastery, Turkey. The accuracy of the developed performance function to truly represent the limit state surface is evaluated by monitoring the slope behavior. The calculated probability of failure is compared with Monte Carlo simulation (MCS) method. The proposed methodology is found to be 72% more efficient than MCS, while the accuracy is decreased with an error of 24%.

Individual and population pharmacokinetic compartment analysis: a graphic procedure for quantification of predictive performance.

PubMed

Eksborg, Staffan

2013-01-01

Pharmacokinetic studies are important for optimizing of drug dosing, but requires proper validation of the used pharmacokinetic procedures. However, simple and reliable statistical methods suitable for evaluation of the predictive performance of pharmacokinetic analysis are essentially lacking. The aim of the present study was to construct and evaluate a graphic procedure for quantification of predictive performance of individual and population pharmacokinetic compartment analysis. Original data from previously published pharmacokinetic compartment analyses after intravenous, oral, and epidural administration, and digitized data, obtained from published scatter plots of observed vs predicted drug concentrations from population pharmacokinetic studies using the NPEM algorithm and NONMEM computer program and Bayesian forecasting procedures, were used for estimating the predictive performance according to the proposed graphical method and by the method of Sheiner and Beal. The graphical plot proposed in the present paper proved to be a useful tool for evaluation of predictive performance of both individual and population compartment pharmacokinetic analysis. The proposed method is simple to use and gives valuable information concerning time- and concentration-dependent inaccuracies that might occur in individual and population pharmacokinetic compartment analysis. Predictive performance can be quantified by the fraction of concentration ratios within arbitrarily specified ranges, e.g. within the range 0.8-1.2.

Efficient reliability analysis of structures with the rotational quasi-symmetric point- and the maximum entropy methods

NASA Astrophysics Data System (ADS)

Xu, Jun; Dang, Chao; Kong, Fan

2017-10-01

This paper presents a new method for efficient structural reliability analysis. In this method, a rotational quasi-symmetric point method (RQ-SPM) is proposed for evaluating the fractional moments of the performance function. Then, the derivation of the performance function's probability density function (PDF) is carried out based on the maximum entropy method in which constraints are specified in terms of fractional moments. In this regard, the probability of failure can be obtained by a simple integral over the performance function's PDF. Six examples, including a finite element-based reliability analysis and a dynamic system with strong nonlinearity, are used to illustrate the efficacy of the proposed method. All the computed results are compared with those by Monte Carlo simulation (MCS). It is found that the proposed method can provide very accurate results with low computational effort.

Lipidomic analysis of biological samples: Comparison of liquid chromatography, supercritical fluid chromatography and direct infusion mass spectrometry methods.

PubMed

Lísa, Miroslav; Cífková, Eva; Khalikova, Maria; Ovčačíková, Magdaléna; Holčapek, Michal

2017-11-24

Lipidomic analysis of biological samples in a clinical research represents challenging task for analytical methods given by the large number of samples and their extreme complexity. In this work, we compare direct infusion (DI) and chromatography - mass spectrometry (MS) lipidomic approaches represented by three analytical methods in terms of comprehensiveness, sample throughput, and validation results for the lipidomic analysis of biological samples represented by tumor tissue, surrounding normal tissue, plasma, and erythrocytes of kidney cancer patients. Methods are compared in one laboratory using the identical analytical protocol to ensure comparable conditions. Ultrahigh-performance liquid chromatography/MS (UHPLC/MS) method in hydrophilic interaction liquid chromatography mode and DI-MS method are used for this comparison as the most widely used methods for the lipidomic analysis together with ultrahigh-performance supercritical fluid chromatography/MS (UHPSFC/MS) method showing promising results in metabolomics analyses. The nontargeted analysis of pooled samples is performed using all tested methods and 610 lipid species within 23 lipid classes are identified. DI method provides the most comprehensive results due to identification of some polar lipid classes, which are not identified by UHPLC and UHPSFC methods. On the other hand, UHPSFC method provides an excellent sensitivity for less polar lipid classes and the highest sample throughput within 10min method time. The sample consumption of DI method is 125 times higher than for other methods, while only 40μL of organic solvent is used for one sample analysis compared to 3.5mL and 4.9mL in case of UHPLC and UHPSFC methods, respectively. Methods are validated for the quantitative lipidomic analysis of plasma samples with one internal standard for each lipid class. Results show applicability of all tested methods for the lipidomic analysis of biological samples depending on the analysis requirements. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of parallel algorithms for electrical power management in space applications

NASA Technical Reports Server (NTRS)

Berry, Frederick C.

1989-01-01

The application of parallel techniques for electrical power system analysis is discussed. The Newton-Raphson method of load flow analysis was used along with the decomposition-coordination technique to perform load flow analysis. The decomposition-coordination technique enables tasks to be performed in parallel by partitioning the electrical power system into independent local problems. Each independent local problem represents a portion of the total electrical power system on which a loan flow analysis can be performed. The load flow analysis is performed on these partitioned elements by using the Newton-Raphson load flow method. These independent local problems will produce results for voltage and power which can then be passed to the coordinator portion of the solution procedure. The coordinator problem uses the results of the local problems to determine if any correction is needed on the local problems. The coordinator problem is also solved by an iterative method much like the local problem. The iterative method for the coordination problem will also be the Newton-Raphson method. Therefore, each iteration at the coordination level will result in new values for the local problems. The local problems will have to be solved again along with the coordinator problem until some convergence conditions are met.

The Effect of Laminar Flow on Rotor Hover Performance

NASA Technical Reports Server (NTRS)

Overmeyer, Austin D.; Martin, Preston B.

2017-01-01

The topic of laminar flow effects on hover performance is introduced with respect to some historical efforts where laminar flow was either measured or attempted. An analysis method is outlined using combined blade element, momentum method coupled to an airfoil analysis method, which includes the full e(sup N) transition model. The analysis results compared well with the measured hover performance including the measured location of transition on both the upper and lower blade surfaces. The analysis method is then used to understand the upper limits of hover efficiency as a function of disk loading. The impact of laminar flow is higher at low disk loading, but significant improvement in terms of power loading appears possible even up to high disk loading approaching 20 ps f. A optimum planform design equation is derived for cases of zero profile drag and finite drag levels. These results are intended to be a guide for design studies and as a benchmark to compare higher fidelity analysis results. The details of the analysis method are given to enable other researchers to use the same approach for comparison to other approaches.

An exact computational method for performance analysis of sequential test algorithms for detecting network intrusions

NASA Astrophysics Data System (ADS)

Chen, Xinjia; Lacy, Fred; Carriere, Patrick

2015-05-01

Sequential test algorithms are playing increasingly important roles for quick detecting network intrusions such as portscanners. In view of the fact that such algorithms are usually analyzed based on intuitive approximation or asymptotic analysis, we develop an exact computational method for the performance analysis of such algorithms. Our method can be used to calculate the probability of false alarm and average detection time up to arbitrarily pre-specified accuracy.

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

PubMed

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

Methods for Conducting Cognitive Task Analysis for a Decision Making Task.

DTIC Science & Technology

1996-01-01

Cognitive task analysis (CTA) improves traditional task analysis procedures by analyzing the thought processes of performers while they complete a...for using these methods to conduct a CTA for domains which involve critical decision making tasks in naturalistic settings. The cognitive task analysis methods

Comparative analysis of techniques for evaluating the effectiveness of aircraft computing systems

NASA Technical Reports Server (NTRS)

Hitt, E. F.; Bridgman, M. S.; Robinson, A. C.

1981-01-01

Performability analysis is a technique developed for evaluating the effectiveness of fault-tolerant computing systems in multiphase missions. Performability was evaluated for its accuracy, practical usefulness, and relative cost. The evaluation was performed by applying performability and the fault tree method to a set of sample problems ranging from simple to moderately complex. The problems involved as many as five outcomes, two to five mission phases, permanent faults, and some functional dependencies. Transient faults and software errors were not considered. A different analyst was responsible for each technique. Significantly more time and effort were required to learn performability analysis than the fault tree method. Performability is inherently as accurate as fault tree analysis. For the sample problems, fault trees were more practical and less time consuming to apply, while performability required less ingenuity and was more checkable. Performability offers some advantages for evaluating very complex problems.

A simple method for plasma total vitamin C analysis suitable for routine clinical laboratory use.

PubMed

Robitaille, Line; Hoffer, L John

2016-04-21

In-hospital hypovitaminosis C is highly prevalent but almost completely unrecognized. Medical awareness of this potentially important disorder is hindered by the inability of most hospital laboratories to determine plasma vitamin C concentrations. The availability of a simple, reliable method for analyzing plasma vitamin C could increase opportunities for routine plasma vitamin C analysis in clinical medicine. Plasma vitamin C can be analyzed by high performance liquid chromatography (HPLC) with electrochemical (EC) or ultraviolet (UV) light detection. We modified existing UV-HPLC methods for plasma total vitamin C analysis (the sum of ascorbic and dehydroascorbic acid) to develop a simple, constant-low-pH sample reduction procedure followed by isocratic reverse-phase HPLC separation using a purely aqueous low-pH non-buffered mobile phase. Although EC-HPLC is widely recommended over UV-HPLC for plasma total vitamin C analysis, the two methods have never been directly compared. We formally compared the simplified UV-HPLC method with EC-HPLC in 80 consecutive clinical samples. The simplified UV-HPLC method was less expensive, easier to set up, required fewer reagents and no pH adjustments, and demonstrated greater sample stability than many existing methods for plasma vitamin C analysis. When compared with the gold-standard EC-HPLC method in 80 consecutive clinical samples exhibiting a wide range of plasma vitamin C concentrations, it performed equivalently. The easy set up, simplicity and sensitivity of the plasma vitamin C analysis method described here could make it practical in a normally equipped hospital laboratory. Unlike any prior UV-HPLC method for plasma total vitamin C analysis, it was rigorously compared with the gold-standard EC-HPLC method and performed equivalently. Adoption of this method could increase the availability of plasma vitamin C analysis in clinical medicine.

Material nonlinear analysis via mixed-iterative finite element method

NASA Technical Reports Server (NTRS)

Sutjahjo, Edhi; Chamis, Christos C.

1992-01-01

The performance of elastic-plastic mixed-iterative analysis is examined through a set of convergence studies. Membrane and bending behaviors are tested using 4-node quadrilateral finite elements. The membrane result is excellent, which indicates the implementation of elastic-plastic mixed-iterative analysis is appropriate. On the other hand, further research to improve bending performance of the method seems to be warranted.

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schierman, John D.; Lovell, T. A.; Schmidt, David K.

1993-01-01

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.

Validating the performance of one-time decomposition for fMRI analysis using ICA with automatic target generation process.

PubMed

Yao, Shengnan; Zeng, Weiming; Wang, Nizhuan; Chen, Lei

2013-07-01

Independent component analysis (ICA) has been proven to be effective for functional magnetic resonance imaging (fMRI) data analysis. However, ICA decomposition requires to optimize the unmixing matrix iteratively whose initial values are generated randomly. Thus the randomness of the initialization leads to different ICA decomposition results. Therefore, just one-time decomposition for fMRI data analysis is not usually reliable. Under this circumstance, several methods about repeated decompositions with ICA (RDICA) were proposed to reveal the stability of ICA decomposition. Although utilizing RDICA has achieved satisfying results in validating the performance of ICA decomposition, RDICA cost much computing time. To mitigate the problem, in this paper, we propose a method, named ATGP-ICA, to do the fMRI data analysis. This method generates fixed initial values with automatic target generation process (ATGP) instead of being produced randomly. We performed experimental tests on both hybrid data and fMRI data to indicate the effectiveness of the new method and made a performance comparison of the traditional one-time decomposition with ICA (ODICA), RDICA and ATGP-ICA. The proposed method demonstrated that it not only could eliminate the randomness of ICA decomposition, but also could save much computing time compared to RDICA. Furthermore, the ROC (Receiver Operating Characteristic) power analysis also denoted the better signal reconstruction performance of ATGP-ICA than that of RDICA. Copyright © 2013 Elsevier Inc. All rights reserved.

Static aeroelastic analysis and tailoring of a single-element racing car wing

NASA Astrophysics Data System (ADS)

Sadd, Christopher James

This thesis presents the research from an Engineering Doctorate research programme in collaboration with Reynard Motorsport Ltd, a manufacturer of racing cars. Racing car wing design has traditionally considered structures to be rigid. However, structures are never perfectly rigid and the interaction between aerodynamic loading and structural flexibility has a direct impact on aerodynamic performance. This interaction is often referred to as static aeroelasticity and the focus of this research has been the development of a computational static aeroelastic analysis method to improve the design of a single-element racing car wing. A static aeroelastic analysis method has been developed by coupling a Reynolds-Averaged Navier-Stokes CFD analysis method with a Finite Element structural analysis method using an iterative scheme. Development of this method has included assessment of CFD and Finite Element analysis methods and development of data transfer and mesh deflection methods. Experimental testing was also completed to further assess the computational analyses. The computational and experimental results show a good correlation and these studies have also shown that a Navier-Stokes static aeroelastic analysis of an isolated wing can be performed at an acceptable computational cost. The static aeroelastic analysis tool was used to assess methods of tailoring the structural flexibility of the wing to increase its aerodynamic performance. These tailoring methods were then used to produce two final wing designs to increase downforce and reduce drag respectively. At the average operating dynamic pressure of the racing car, the computational analysis predicts that the downforce-increasing wing has a downforce of C[1]=-1.377 in comparison to C[1]=-1.265 for the original wing. The computational analysis predicts that the drag-reducing wing has a drag of C[d]=0.115 in comparison to C[d]=0.143 for the original wing.

Review of the Air-Coupled Impact-Echo Method for Non-Destructive Testing

NASA Astrophysics Data System (ADS)

Nowotarski, Piotr; Dubas, Sebastian; Milwicz, Roman

2017-10-01

The article presents the general idea of Air-Coupled Impact-Echo (ACIE) method which is one of the non-destructive testing (NDT) techniques used in the construction industry. One of the main advantages of the general Impact Echo (IE) method is that it is sufficient to access from one side to that of the structure which greatly facilitate research in the road facilities or places which are difficult to access and diagnose. The main purpose of the article is to present state-of-the-art related to ACIE method based on the publications available at Thomson Reuters Web of Science Core Collection database (WOS) with the further analysis of the mentioned methods. Deeper analysis was also performed for the newest publications published within last 3 years related to ACIE for investigation on the subject of main focus of the researchers and scientists to try to define possible regions where additional examination and work is necessary. One of the main conclusions that comes from the performed analysis is that ACIE methods can be widely used for performing NDT of concrete structures and can be performed faster than standard IE method thanks to the Air-coupled sensors. What is more, 92.3% of the analysed recent research described in publications connected with ACIE was performed in laboratories, and only 23.1% in-situ on real structures. This indicates that method requires further research to prepare test stand ready to perform analysis on real objects outside laboratory conditions. Moreover, algorithms that are used for data processing and later presentation in ACIE method are still being developed and there is no universal solution available for all kinds of the existing and possible to find defects, which indicates possible research area for further works. Authors are of the opinion that emerging ACIE method could be good opportunity for ND testing especially for concrete structures. Development and refinement of test stands that will allow to perform in-situ tests could shorten the overall time of the research and with the connection of implementation of higher accuracy algorithms for data analysis better precision of defects localization can be achieved.

Challenges in microarray class discovery: a comprehensive examination of normalization, gene selection and clustering

PubMed Central

2010-01-01

Background Cluster analysis, and in particular hierarchical clustering, is widely used to extract information from gene expression data. The aim is to discover new classes, or sub-classes, of either individuals or genes. Performing a cluster analysis commonly involve decisions on how to; handle missing values, standardize the data and select genes. In addition, pre-processing, involving various types of filtration and normalization procedures, can have an effect on the ability to discover biologically relevant classes. Here we consider cluster analysis in a broad sense and perform a comprehensive evaluation that covers several aspects of cluster analyses, including normalization. Result We evaluated 2780 cluster analysis methods on seven publicly available 2-channel microarray data sets with common reference designs. Each cluster analysis method differed in data normalization (5 normalizations were considered), missing value imputation (2), standardization of data (2), gene selection (19) or clustering method (11). The cluster analyses are evaluated using known classes, such as cancer types, and the adjusted Rand index. The performances of the different analyses vary between the data sets and it is difficult to give general recommendations. However, normalization, gene selection and clustering method are all variables that have a significant impact on the performance. In particular, gene selection is important and it is generally necessary to include a relatively large number of genes in order to get good performance. Selecting genes with high standard deviation or using principal component analysis are shown to be the preferred gene selection methods. Hierarchical clustering using Ward's method, k-means clustering and Mclust are the clustering methods considered in this paper that achieves the highest adjusted Rand. Normalization can have a significant positive impact on the ability to cluster individuals, and there are indications that background correction is preferable, in particular if the gene selection is successful. However, this is an area that needs to be studied further in order to draw any general conclusions. Conclusions The choice of cluster analysis, and in particular gene selection, has a large impact on the ability to cluster individuals correctly based on expression profiles. Normalization has a positive effect, but the relative performance of different normalizations is an area that needs more research. In summary, although clustering, gene selection and normalization are considered standard methods in bioinformatics, our comprehensive analysis shows that selecting the right methods, and the right combinations of methods, is far from trivial and that much is still unexplored in what is considered to be the most basic analysis of genomic data. PMID:20937082

Monitoring the metering performance of an electronic voltage transformer on-line based on cyber-physics correlation analysis

NASA Astrophysics Data System (ADS)

Zhang, Zhu; Li, Hongbin; Tang, Dengping; Hu, Chen; Jiao, Yang

2017-10-01

Metering performance is the key parameter of an electronic voltage transformer (EVT), and it requires high accuracy. The conventional off-line calibration method using a standard voltage transformer is not suitable for the key equipment in a smart substation, which needs on-line monitoring. In this article, we propose a method for monitoring the metering performance of an EVT on-line based on cyber-physics correlation analysis. By the electrical and physical properties of a substation running in three-phase symmetry, the principal component analysis method is used to separate the metering deviation caused by the primary fluctuation and the EVT anomaly. The characteristic statistics of the measured data during operation are extracted, and the metering performance of the EVT is evaluated by analyzing the change in statistics. The experimental results show that the method successfully monitors the metering deviation of a Class 0.2 EVT accurately. The method demonstrates the accurate evaluation of on-line monitoring of the metering performance on an EVT without a standard voltage transformer.

Performance analysis of a Principal Component Analysis ensemble classifier for Emotiv headset P300 spellers.

PubMed

Elsawy, Amr S; Eldawlatly, Seif; Taher, Mohamed; Aly, Gamal M

2014-01-01

The current trend to use Brain-Computer Interfaces (BCIs) with mobile devices mandates the development of efficient EEG data processing methods. In this paper, we demonstrate the performance of a Principal Component Analysis (PCA) ensemble classifier for P300-based spellers. We recorded EEG data from multiple subjects using the Emotiv neuroheadset in the context of a classical oddball P300 speller paradigm. We compare the performance of the proposed ensemble classifier to the performance of traditional feature extraction and classifier methods. Our results demonstrate the capability of the PCA ensemble classifier to classify P300 data recorded using the Emotiv neuroheadset with an average accuracy of 86.29% on cross-validation data. In addition, offline testing of the recorded data reveals an average classification accuracy of 73.3% that is significantly higher than that achieved using traditional methods. Finally, we demonstrate the effect of the parameters of the P300 speller paradigm on the performance of the method.

Estimating optical imaging system performance for space applications

NASA Technical Reports Server (NTRS)

Sinclair, K. F.

1972-01-01

The critical system elements of an optical imaging system are identified and a method for an initial assessment of system performance is presented. A generalized imaging system is defined. A system analysis is considered, followed by a component analysis. An example of the method is given using a film imaging system.

Method of assessing heterogeneity in images

DOEpatents

Jacob, Richard E.; Carson, James P.

2016-08-23

A method of assessing heterogeneity in images is disclosed. 3D images of an object are acquired. The acquired images may be filtered and masked. Iterative decomposition is performed on the masked images to obtain image subdivisions that are relatively homogeneous. Comparative analysis, such as variogram analysis or correlogram analysis, is performed of the decomposed images to determine spatial relationships between regions of the images that are relatively homogeneous.

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Determination of dasatinib in the tablet dosage form by ultra high performance liquid chromatography, capillary zone electrophoresis, and sequential injection analysis.

PubMed

Gonzalez, Aroa Garcia; Taraba, Lukáš; Hraníček, Jakub; Kozlík, Petr; Coufal, Pavel

2017-01-01

Dasatinib is a novel oral prescription drug proposed for treating adult patients with chronic myeloid leukemia. Three analytical methods, namely ultra high performance liquid chromatography, capillary zone electrophoresis, and sequential injection analysis, were developed, validated, and compared for determination of the drug in the tablet dosage form. The total analysis time of optimized ultra high performance liquid chromatography and capillary zone electrophoresis methods was 2.0 and 2.2 min, respectively. Direct ultraviolet detection with detection wavelength of 322 nm was employed in both cases. The optimized sequential injection analysis method was based on spectrophotometric detection of dasatinib after a simple colorimetric reaction with folin ciocalteau reagent forming a blue-colored complex with an absorbance maximum at 745 nm. The total analysis time was 2.5 min. The ultra high performance liquid chromatography method provided the lowest detection and quantitation limits and the most precise and accurate results. All three newly developed methods were demonstrated to be specific, linear, sensitive, precise, and accurate, providing results satisfactorily meeting the requirements of the pharmaceutical industry, and can be employed for the routine determination of the active pharmaceutical ingredient in the tablet dosage form. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Scalable parallel elastic-plastic finite element analysis using a quasi-Newton method with a balancing domain decomposition preconditioner

NASA Astrophysics Data System (ADS)

Yusa, Yasunori; Okada, Hiroshi; Yamada, Tomonori; Yoshimura, Shinobu

2018-04-01

A domain decomposition method for large-scale elastic-plastic problems is proposed. The proposed method is based on a quasi-Newton method in conjunction with a balancing domain decomposition preconditioner. The use of a quasi-Newton method overcomes two problems associated with the conventional domain decomposition method based on the Newton-Raphson method: (1) avoidance of a double-loop iteration algorithm, which generally has large computational complexity, and (2) consideration of the local concentration of nonlinear deformation, which is observed in elastic-plastic problems with stress concentration. Moreover, the application of a balancing domain decomposition preconditioner ensures scalability. Using the conventional and proposed domain decomposition methods, several numerical tests, including weak scaling tests, were performed. The convergence performance of the proposed method is comparable to that of the conventional method. In particular, in elastic-plastic analysis, the proposed method exhibits better convergence performance than the conventional method.

Probabilistic Parameter Uncertainty Analysis of Single Input Single Output Control Systems

NASA Technical Reports Server (NTRS)

Smith, Brett A.; Kenny, Sean P.; Crespo, Luis G.

2005-01-01

The current standards for handling uncertainty in control systems use interval bounds for definition of the uncertain parameters. This approach gives no information about the likelihood of system performance, but simply gives the response bounds. When used in design, current methods of m-analysis and can lead to overly conservative controller design. With these methods, worst case conditions are weighted equally with the most likely conditions. This research explores a unique approach for probabilistic analysis of control systems. Current reliability methods are examined showing the strong areas of each in handling probability. A hybrid method is developed using these reliability tools for efficiently propagating probabilistic uncertainty through classical control analysis problems. The method developed is applied to classical response analysis as well as analysis methods that explore the effects of the uncertain parameters on stability and performance metrics. The benefits of using this hybrid approach for calculating the mean and variance of responses cumulative distribution functions are shown. Results of the probabilistic analysis of a missile pitch control system, and a non-collocated mass spring system, show the added information provided by this hybrid analysis.

A Model of Risk Analysis in Analytical Methodology for Biopharmaceutical Quality Control.

PubMed

Andrade, Cleyton Lage; Herrera, Miguel Angel De La O; Lemes, Elezer Monte Blanco

2018-01-01

One key quality control parameter for biopharmaceutical products is the analysis of residual cellular DNA. To determine small amounts of DNA (around 100 pg) that may be in a biologically derived drug substance, an analytical method should be sensitive, robust, reliable, and accurate. In principle, three techniques have the ability to measure residual cellular DNA: radioactive dot-blot, a type of hybridization; threshold analysis; and quantitative polymerase chain reaction. Quality risk management is a systematic process for evaluating, controlling, and reporting of risks that may affects method capabilities and supports a scientific and practical approach to decision making. This paper evaluates, by quality risk management, an alternative approach to assessing the performance risks associated with quality control methods used with biopharmaceuticals, using the tool hazard analysis and critical control points. This tool provides the possibility to find the steps in an analytical procedure with higher impact on method performance. By applying these principles to DNA analysis methods, we conclude that the radioactive dot-blot assay has the largest number of critical control points, followed by quantitative polymerase chain reaction, and threshold analysis. From the analysis of hazards (i.e., points of method failure) and the associated method procedure critical control points, we conclude that the analytical methodology with the lowest risk for performance failure for residual cellular DNA testing is quantitative polymerase chain reaction. LAY ABSTRACT: In order to mitigate the risk of adverse events by residual cellular DNA that is not completely cleared from downstream production processes, regulatory agencies have required the industry to guarantee a very low level of DNA in biologically derived pharmaceutical products. The technique historically used was radioactive blot hybridization. However, the technique is a challenging method to implement in a quality control laboratory: It is laborious, time consuming, semi-quantitative, and requires a radioisotope. Along with dot-blot hybridization, two alternatives techniques were evaluated: threshold analysis and quantitative polymerase chain reaction. Quality risk management tools were applied to compare the techniques, taking into account the uncertainties, the possibility of circumstances or future events, and their effects upon method performance. By illustrating the application of these tools with DNA methods, we provide an example of how they can be used to support a scientific and practical approach to decision making and can assess and manage method performance risk using such tools. This paper discusses, considering the principles of quality risk management, an additional approach to the development and selection of analytical quality control methods using the risk analysis tool hazard analysis and critical control points. This tool provides the possibility to find the method procedural steps with higher impact on method reliability (called critical control points). Our model concluded that the radioactive dot-blot assay has the larger number of critical control points, followed by quantitative polymerase chain reaction and threshold analysis. Quantitative polymerase chain reaction is shown to be the better alternative analytical methodology in residual cellular DNA analysis. © PDA, Inc. 2018.

Frequency Spectrum Method-Based Stress Analysis for Oil Pipelines in Earthquake Disaster Areas

PubMed Central

Wu, Xiaonan; Lu, Hongfang; Huang, Kun; Wu, Shijuan; Qiao, Weibiao

2015-01-01

When a long distance oil pipeline crosses an earthquake disaster area, inertial force and strong ground motion can cause the pipeline stress to exceed the failure limit, resulting in bending and deformation failure. To date, researchers have performed limited safety analyses of oil pipelines in earthquake disaster areas that include stress analysis. Therefore, using the spectrum method and theory of one-dimensional beam units, CAESAR II is used to perform a dynamic earthquake analysis for an oil pipeline in the XX earthquake disaster area. This software is used to determine if the displacement and stress of the pipeline meet the standards when subjected to a strong earthquake. After performing the numerical analysis, the primary seismic action axial, longitudinal and horizontal displacement directions and the critical section of the pipeline can be located. Feasible project enhancement suggestions based on the analysis results are proposed. The designer is able to utilize this stress analysis method to perform an ultimate design for an oil pipeline in earthquake disaster areas; therefore, improving the safe operation of the pipeline. PMID:25692790

Frequency spectrum method-based stress analysis for oil pipelines in earthquake disaster areas.

PubMed

Wu, Xiaonan; Lu, Hongfang; Huang, Kun; Wu, Shijuan; Qiao, Weibiao

2015-01-01

When a long distance oil pipeline crosses an earthquake disaster area, inertial force and strong ground motion can cause the pipeline stress to exceed the failure limit, resulting in bending and deformation failure. To date, researchers have performed limited safety analyses of oil pipelines in earthquake disaster areas that include stress analysis. Therefore, using the spectrum method and theory of one-dimensional beam units, CAESAR II is used to perform a dynamic earthquake analysis for an oil pipeline in the XX earthquake disaster area. This software is used to determine if the displacement and stress of the pipeline meet the standards when subjected to a strong earthquake. After performing the numerical analysis, the primary seismic action axial, longitudinal and horizontal displacement directions and the critical section of the pipeline can be located. Feasible project enhancement suggestions based on the analysis results are proposed. The designer is able to utilize this stress analysis method to perform an ultimate design for an oil pipeline in earthquake disaster areas; therefore, improving the safe operation of the pipeline.

[Comparative analysis of modification of Misgav-Ladach and Pfannenstiel methods for cesarean section in the material of Fetal-Maternal Clinical Department PMMH-RI between 1994-1999].

PubMed

Pawłowicz, P; Wilczyński, J; Stachowiak, G

2000-04-01

Comparative analysis of own modification of Misgav-Ladach (mML) and Pfannenstiel methods for caesarean section in the material of Fetal-Maternal Medicine Clinical Department PMMH-RI between 1994-99. Study group consists of 242 patients. In all women from this group we performed caesarean section using Misgav-Ladach method. Among all patients from control group counting 285 women we performed caesarean section applying Pfannenstiel method. To analyse clinical postoperative course in both groups we took account several parameters. Statistical analysis revealed that most of clinical postoperative course parameters was significantly better values in the study group we performed caesarean section using Misgav-Ladach method. The benefits of Misgav-Ladach method, with less pain post-operatively and quicker recovery, are all a by-product of doing the least harm during surgery and removing every unnecessary step. This method is appealing for its simplicity, ease of execution and its time-saving advantage.

Methods for the survey and genetic analysis of populations

DOEpatents

Ashby, Matthew

2003-09-02

The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

Evaluation of Contamination Inspection and Analysis Methods through Modeling System Performance

NASA Technical Reports Server (NTRS)

Seasly, Elaine; Dever, Jason; Stuban, Steven M. F.

2016-01-01

Contamination is usually identified as a risk on the risk register for sensitive space systems hardware. Despite detailed, time-consuming, and costly contamination control efforts during assembly, integration, and test of space systems, contaminants are still found during visual inspections of hardware. Improved methods are needed to gather information during systems integration to catch potential contamination issues earlier and manage contamination risks better. This research explores evaluation of contamination inspection and analysis methods to determine optical system sensitivity to minimum detectable molecular contamination levels based on IEST-STD-CC1246E non-volatile residue (NVR) cleanliness levels. Potential future degradation of the system is modeled given chosen modules representative of optical elements in an optical system, minimum detectable molecular contamination levels for a chosen inspection and analysis method, and determining the effect of contamination on the system. By modeling system performance based on when molecular contamination is detected during systems integration and at what cleanliness level, the decision maker can perform trades amongst different inspection and analysis methods and determine if a planned method is adequate to meet system requirements and manage contamination risk.

Performance analysis of successive over relaxation method for solving glioma growth model

NASA Astrophysics Data System (ADS)

Hussain, Abida; Faye, Ibrahima; Muthuvalu, Mohana Sundaram

2016-11-01

Brain tumor is one of the prevalent cancers in the world that lead to death. In light of the present information of the properties of gliomas, mathematical models have been developed by scientists to quantify the proliferation and invasion dynamics of glioma. In this study, one-dimensional glioma growth model is considered, and finite difference method is used to discretize the problem. Then, two stationary methods, namely Gauss-Seidel (GS) and Successive Over Relaxation (SOR) are used to solve the governing algebraic system. The performance of the methods are evaluated in terms of number of iteration and computational time. On the basis of performance analysis, SOR method is shown to be more superior compared to GS method.

Time-dependent inertia analysis of vehicle mechanisms

NASA Astrophysics Data System (ADS)

Salmon, James Lee

Two methods for performing transient inertia analysis of vehicle hardware systems are developed in this dissertation. The analysis techniques can be used to predict the response of vehicle mechanism systems to the accelerations associated with vehicle impacts. General analytical methods for evaluating translational or rotational system dynamics are generated and evaluated for various system characteristics. The utility of the derived techniques are demonstrated by applying the generalized methods to two vehicle systems. Time dependent acceleration measured during a vehicle to vehicle impact are used as input to perform a dynamic analysis of an automobile liftgate latch and outside door handle. Generalized Lagrange equations for a non-conservative system are used to formulate a second order nonlinear differential equation defining the response of the components to the transient input. The differential equation is solved by employing the fourth order Runge-Kutta method. The events are then analyzed using commercially available two dimensional rigid body dynamic analysis software. The results of the two analytical techniques are compared to experimental data generated by high speed film analysis of tests of the two components performed on a high G acceleration sled at Ford Motor Company.

Cluster Correspondence Analysis.

PubMed

van de Velden, M; D'Enza, A Iodice; Palumbo, F

2017-03-01

A method is proposed that combines dimension reduction and cluster analysis for categorical data by simultaneously assigning individuals to clusters and optimal scaling values to categories in such a way that a single between variance maximization objective is achieved. In a unified framework, a brief review of alternative methods is provided and we show that the proposed method is equivalent to GROUPALS applied to categorical data. Performance of the methods is appraised by means of a simulation study. The results of the joint dimension reduction and clustering methods are compared with the so-called tandem approach, a sequential analysis of dimension reduction followed by cluster analysis. The tandem approach is conjectured to perform worse when variables are added that are unrelated to the cluster structure. Our simulation study confirms this conjecture. Moreover, the results of the simulation study indicate that the proposed method also consistently outperforms alternative joint dimension reduction and clustering methods.

Comparison of normalization methods for the analysis of metagenomic gene abundance data.

PubMed

Pereira, Mariana Buongermino; Wallroth, Mikael; Jonsson, Viktor; Kristiansson, Erik

2018-04-20

In shotgun metagenomics, microbial communities are studied through direct sequencing of DNA without any prior cultivation. By comparing gene abundances estimated from the generated sequencing reads, functional differences between the communities can be identified. However, gene abundance data is affected by high levels of systematic variability, which can greatly reduce the statistical power and introduce false positives. Normalization, which is the process where systematic variability is identified and removed, is therefore a vital part of the data analysis. A wide range of normalization methods for high-dimensional count data has been proposed but their performance on the analysis of shotgun metagenomic data has not been evaluated. Here, we present a systematic evaluation of nine normalization methods for gene abundance data. The methods were evaluated through resampling of three comprehensive datasets, creating a realistic setting that preserved the unique characteristics of metagenomic data. Performance was measured in terms of the methods ability to identify differentially abundant genes (DAGs), correctly calculate unbiased p-values and control the false discovery rate (FDR). Our results showed that the choice of normalization method has a large impact on the end results. When the DAGs were asymmetrically present between the experimental conditions, many normalization methods had a reduced true positive rate (TPR) and a high false positive rate (FPR). The methods trimmed mean of M-values (TMM) and relative log expression (RLE) had the overall highest performance and are therefore recommended for the analysis of gene abundance data. For larger sample sizes, CSS also showed satisfactory performance. This study emphasizes the importance of selecting a suitable normalization methods in the analysis of data from shotgun metagenomics. Our results also demonstrate that improper methods may result in unacceptably high levels of false positives, which in turn may lead to incorrect or obfuscated biological interpretation.

Development of an SPE/CE method for analyzing HAAs

USGS Publications Warehouse

Zhang, L.; Capel, P.D.; Hozalski, R.M.

2007-01-01

The haloacetic acid (HAA) analysis methods approved by the US Environmental Protection Agency involve extraction and derivatization of HAAs (typically to their methyl ester form) and analysis by gas chromatography (GC) with electron capture detection (ECD). Concerns associated with these methods include the time and effort of the derivatization process, use of potentially hazardous chemicals or conditions during methylation, poor recoveries because of low extraction efficiencies for some HAAs or matrix effects from sulfate, and loss of tribromoacetic acid because of decarboxylation. The HAA analysis method introduced here uses solid-phase extraction (SPE) followed by capillary electrophoresis (CE) analysis. The method is accurate, reproducible, sensitive, relatively safe, and easy to perform, and avoids the use of large amounts of solvent for liquid-liquid extraction and the potential hazards and hassles of derivatization. The cost of analyzing HAAs using this method should be lower than the currently approved methods, and utilities with a GC/ECD can perform the analysis in-house.

Dredged Material Analysis Tools; Performance of Acute and Chronic Sediment Toxicity Methods

DTIC Science & Technology

2008-04-01

Chronic Sediment Toxicity Methods Jeffery Steevens, Alan Kennedy, Daniel Farrar, Cory McNemar, Mark R. Reiss, Roy K. Kropp, Jon Doi, and Todd Bridges...Research Program ERDC/EL TR-08-16 April 2008 Dredged Material Analysis Tools Performance of Acute and Chronic Sediment Toxicity Methods Jeffery...potential advan- tages and disadvantages of using chronic sediment toxicity tests with relevant benthic macroinvertebrates as part of dredged material

Acoustic prediction methods for the NASA generalized advanced propeller analysis system (GAPAS)

NASA Technical Reports Server (NTRS)

Padula, S. L.; Block, P. J. W.

1984-01-01

Classical methods of propeller performance analysis are coupled with state-of-the-art Aircraft Noise Prediction Program (ANOPP:) techniques to yield a versatile design tool, the NASA Generalized Advanced Propeller Analysis System (GAPAS) for the novel quiet and efficient propellers. ANOPP is a collection of modular specialized programs. GAPAS as a whole addresses blade geometry and aerodynamics, rotor performance and loading, and subsonic propeller noise.

Analysis of Photovoltaic System Energy Performance Evaluation Method

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

Kurtz, S.; Newmiller, J.; Kimber, A.

2013-11-01

Documentation of the energy yield of a large photovoltaic (PV) system over a substantial period can be useful to measure a performance guarantee, as an assessment of the health of the system, for verification of a performance model to then be applied to a new system, or for a variety of other purposes. Although the measurement of this performance metric might appear to be straight forward, there are a number of subtleties associated with variations in weather and imperfect data collection that complicate the determination and data analysis. A performance assessment is most valuable when it is completed with amore » very low uncertainty and when the subtleties are systematically addressed, yet currently no standard exists to guide this process. This report summarizes a draft methodology for an Energy Performance Evaluation Method, the philosophy behind the draft method, and the lessons that were learned by implementing the method.« less

Validity of the assessment method of skeletal maturation by cervical vertebrae: a systematic review and meta-analysis.

PubMed

Cericato, G O; Bittencourt, M A V; Paranhos, L R

2015-01-01

To perform a systematic review with meta-analysis to answer the question: is the cervical vertebrae maturation index (CVMI) effective to replace hand-wrist radiograph (gold standard) in determining the pubertal growth spurt in patients undergoing bone growth? A search in three databases was performed, in which studies were selected that compared one of the two main assessment methods for cervical vertebrae (Hassel B, Farman AG. Skeletal maturation evaluation using cervical vertebrae. Am J Orthod Dentofacial Orthop 1995; 107: 58-66, or Baccetti T, Franchi L, McNamara JA Jr. An improved version of the cervical vertebral maturation (CVM) method for the assessment of mandibular growth. Angle Orthod 2002; 72: 316-23) to a carpal assessment method. The main methodological data from each of the texts were collected and tabulated after. Later, the meta-analysis of the correlation coefficients obtained was performed. 19 articles were selected from an initial 206 articles collected. Regardless of the method used, the results of the meta-analysis showed that every article selected presented a positive correlation between skeletal maturation assessment performed by cervical vertebrae and carpal methods, with discrepancy of values between genders indicating higher correlation for the female gender (0.925; 0.878) than for the male (0.879; 0.842). When the assessment was performed without gender separation, correlation was significant (0.592; 0.688) but lower in the cases when genders were separated. With the results of this meta-analysis, it is safe to affirm that both CVMIs used in the present study are reliable to replace the hand-wrist radiograph in predicting the pubertal growth spurt, considering that the highest values were found in female samples, especially in the method by Hassel and Farman.

Light-frame wall and floor systems : analysis and performance

Treesearch

G. Sherwood; R. C. Moody

1989-01-01

This report describes methods of predicting the performance of light-frame wood structures with emphasis on floor and wall systems. Methods of predicting structural performance, fire safety, and environmental concerns including thermal, moisture, and acoustic performance are addressed in the three major sections.

Comparing Indirect Effects in Different Groups in Single-Group and Multi-Group Structural Equation Models

PubMed Central

Ryu, Ehri; Cheong, Jeewon

2017-01-01

In this article, we evaluated the performance of statistical methods in single-group and multi-group analysis approaches for testing group difference in indirect effects and for testing simple indirect effects in each group. We also investigated whether the performance of the methods in the single-group approach was affected when the assumption of equal variance was not satisfied. The assumption was critical for the performance of the two methods in the single-group analysis: the method using a product term for testing the group difference in a single path coefficient, and the Wald test for testing the group difference in the indirect effect. Bootstrap confidence intervals in the single-group approach and all methods in the multi-group approach were not affected by the violation of the assumption. We compared the performance of the methods and provided recommendations. PMID:28553248

Analysis of Lard in Lipstick Formulation Using FTIR Spectroscopy and Multivariate Calibration: A Comparison of Three Extraction Methods.

PubMed

Waskitho, Dri; Lukitaningsih, Endang; Sudjadi; Rohman, Abdul

2016-01-01

Analysis of lard extracted from lipstick formulation containing castor oil has been performed using FTIR spectroscopic method combined with multivariate calibration. Three different extraction methods were compared, namely saponification method followed by liquid/liquid extraction with hexane/dichlorometane/ethanol/water, saponification method followed by liquid/liquid extraction with dichloromethane/ethanol/water, and Bligh & Dyer method using chloroform/methanol/water as extracting solvent. Qualitative and quantitative analysis of lard were performed using principle component (PCA) and partial least square (PLS) analysis, respectively. The results showed that, in all samples prepared by the three extraction methods, PCA was capable of identifying lard at wavelength region of 1200-800 cm -1 with the best result was obtained by Bligh & Dyer method. Furthermore, PLS analysis at the same wavelength region used for qualification showed that Bligh and Dyer was the most suitable extraction method with the highest determination coefficient (R 2 ) and the lowest root mean square error of calibration (RMSEC) as well as root mean square error of prediction (RMSEP) values.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

Structural reliability analysis under evidence theory using the active learning kriging model

NASA Astrophysics Data System (ADS)

Yang, Xufeng; Liu, Yongshou; Ma, Panke

2017-11-01

Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.

Comparison of various extraction techniques for the determination of polycyclic aromatic hydrocarbons in worms.

PubMed

Mooibroek, D; Hoogerbrugge, R; Stoffelsen, B H G; Dijkman, E; Berkhoff, C J; Hogendoorn, E A

2002-10-25

Two less laborious extraction methods, viz. (i) a simplified liquid extraction using light petroleum or (ii) microwave-assisted solvent extraction (MASE), for the analysis of polycyclic aromatic hydrocarbons (PAHs) in samples of the compost worm Eisenia andrei, were compared with a reference method. After extraction and concentration, analytical methodology consisted of a cleanup of (part) of the extract with high-performance gel permeation chromatography (HPGPC) and instrumental analysis of 15 PAHs with reversed-phase liquid chromatography with fluorescence detection (RPLC-FLD). Comparison of the methods was done by analysing samples with incurred residues (n=15, each method) originating from an experiment in which worms were exposed to a soil contaminated with PAHs. Simultaneously, the performance of the total lipid determination of each method was established. Evaluation of the data by means of principal component analysis (PCA) and analysis of variance (ANOVA) revealed that the performance of the light petroleum method for both the extraction of PAHs (concentration range 1-30 ng/g) and lipid content corresponds very well with the reference method. Compared to the reference method, the MASE method yielded somewhat lower concentrations for the less volatile PAHs, e.g., dibenzo[ah]anthracene and benzo[ghi]perylene and provided a significant higher amount of co-extracted material.

Comparative study on DuPont analysis and DEA models for measuring stock performance using financial ratio

NASA Astrophysics Data System (ADS)

Arsad, Roslah; Shaari, Siti Nabilah Mohd; Isa, Zaidi

2017-11-01

Determining stock performance using financial ratio is challenging for many investors and researchers. Financial ratio can indicate the strengths and weaknesses of a company's stock performance. There are five categories of financial ratios namely liquidity, efficiency, leverage, profitability and market ratios. It is important to interpret the ratio correctly for proper financial decision making. The purpose of this study is to compare the performance of listed companies in Bursa Malaysia using Data Envelopment Analysis (DEA) and DuPont analysis Models. The study is conducted in 2015 involving 116 consumer products companies listed in Bursa Malaysia. The estimation method of Data Envelopment Analysis computes the efficiency scores and ranks the companies accordingly. The Alirezaee and Afsharian's method of analysis based Charnes, Cooper and Rhodes (CCR) where Constant Return to Scale (CRS) is employed. The DuPont analysis is a traditional tool for measuring the operating performance of companies. In this study, DuPont analysis is used to evaluate three different aspects such as profitability, efficiency of assets utilization and financial leverage. Return on Equity (ROE) is also calculated in DuPont analysis. This study finds that both analysis models provide different rankings of the selected samples. Hypothesis testing based on Pearson's correlation, indicates that there is no correlation between rankings produced by DEA and DuPont analysis. The DEA ranking model proposed by Alirezaee and Asharian is unstable. The method cannot provide complete ranking because the values of Balance Index is equal and zero.

On the effectiveness of recession analysis methods for capturing the characteristic storage-discharge relation: An intercomparison study

NASA Astrophysics Data System (ADS)

Chen, X.; Kumar, M.; Basso, S.; Marani, M.

2017-12-01

Storage-discharge (S-Q) relations are widely used to derive watershed properties and predict streamflow responses. These relations are often obtained using different recession analysis methods, which vary in recession period identification criteria and Q vs. -dQ/dt fitting scheme. Although previous studies have indicated that different recession analysis methods can result in significantly different S-Q relations and subsequently derived hydrological variables, this observation has often been overlooked and S-Q relations have been used in as is form. This study evaluated the effectiveness of four recession analysis methods in obtaining the characteristic S-Q relation and reconstructing the streamflow. Results indicate that while some methods generally performed better than others, none of them consistently outperformed the others. Even the best-performing method could not yield accurate reconstructed streamflow time series and its PDFs in some watersheds, implying that either derived S-Q relations might not be reliable or S-Q relations cannot be used for hydrological simulations. Notably, accuracy of the methods is influenced by the extent of scatter in the ln(-dQ/dt) vs. ln(Q) plot. In addition, the derived S-Q relation was very sensitive to the criteria used for identifying recession periods. This result raises a warning sign against indiscriminate application of recession analysis methods and derived S-Q relations for watershed characterizations or hydrologic simulations. Thorough evaluation of representativeness of the derived S-Q relation should be performed before it is used for hydrologic analysis.

The Current State of Human Performance Technology: A Citation Network Analysis of "Performance Improvement Quarterly," 1988-2010

ERIC Educational Resources Information Center

Cho, Yonjoo; Jo, Sung Jun; Park, Sunyoung; Kang, Ingu; Chen, Zengguan

2011-01-01

This study conducted a citation network analysis (CNA) of human performance technology (HPT) to examine its current state of the field. Previous reviews of the field have used traditional research methods, such as content analysis, survey, Delphi, and citation analysis. The distinctive features of CNA come from using a social network analysis…

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

40 CFR Table 2 to Subpart Cccc of... - Requirements for Performance Tests

Code of Federal Regulations, 2010 CFR

2010-07-01

... port's location and the number of traverse points Method 1* 3. Measure volumetric flow rate. Method 2* 4. Perform gas analysis to determine the dry molecular weight of the stack gas Method 3* 5...

Java Programs for Using Newmark's Method and Simplified Decoupled Analysis to Model Slope Performance During Earthquakes

USGS Publications Warehouse

Jibson, Randall W.; Jibson, Matthew W.

2003-01-01

Landslides typically cause a large proportion of earthquake damage, and the ability to predict slope performance during earthquakes is important for many types of seismic-hazard analysis and for the design of engineered slopes. Newmark's method for modeling a landslide as a rigid-plastic block sliding on an inclined plane provides a useful method for predicting approximate landslide displacements. Newmark's method estimates the displacement of a potential landslide block as it is subjected to earthquake shaking from a specific strong-motion record (earthquake acceleration-time history). A modification of Newmark's method, decoupled analysis, allows modeling landslides that are not assumed to be rigid blocks. This open-file report is available on CD-ROM and contains Java programs intended to facilitate performing both rigorous and simplified Newmark sliding-block analysis and a simplified model of decoupled analysis. For rigorous analysis, 2160 strong-motion records from 29 earthquakes are included along with a search interface for selecting records based on a wide variety of record properties. Utilities are available that allow users to add their own records to the program and use them for conducting Newmark analyses. Also included is a document containing detailed information about how to use Newmark's method to model dynamic slope performance. This program will run on any platform that supports the Java Runtime Environment (JRE) version 1.3, including Windows, Mac OSX, Linux, Solaris, etc. A minimum of 64 MB of available RAM is needed, and the fully installed program requires 400 MB of disk space.

Combustor kinetic energy efficiency analysis of the hypersonic research engine data

NASA Astrophysics Data System (ADS)

Hoose, K. V.

1993-11-01

A one-dimensional method for measuring combustor performance is needed to facilitate design and development scramjet engines. A one-dimensional kinetic energy efficiency method is used for measuring inlet and nozzle performance. The objective of this investigation was to assess the use of kinetic energy efficiency as an indicator for scramjet combustor performance. A combustor kinetic energy efficiency analysis was performed on the Hypersonic Research Engine (HRE) data. The HRE data was chosen for this analysis due to its thorough documentation and availability. The combustor, inlet, and nozzle kinetic energy efficiency values were utilized to determine an overall engine kinetic energy efficiency. Finally, a kinetic energy effectiveness method was developed to eliminate thermochemical losses from the combustion of fuel and air. All calculated values exhibit consistency over the flight speed range. Effects from fuel injection, altitude, angle of attack, subsonic-supersonic combustion transition, and inlet spike position are shown and discussed. The results of analyzing the HRE data indicate that the kinetic energy efficiency method is effective as a measure of scramjet combustor performance.

The Identification of Software Failure Regions

DTIC Science & Technology

1990-06-01

be used to detect non-obviously redundant test cases. A preliminary examination of the manual analysis method is performed with a set of programs ...failure regions are defined and a method of failure region analysis is described in detail. The thesis describes how this analysis may be used to detect...is the termination of the ability of a functional unit to perform its required function. (Glossary, 1983) The presence of faults in program code

Study on behaviors and performances of universal N-glycopeptide enrichment methods.

PubMed

Xue, Yu; Xie, Juanjuan; Fang, Pan; Yao, Jun; Yan, Guoquan; Shen, Huali; Yang, Pengyuan

2018-04-16

Glycosylation is a crucial process in protein biosynthesis. However, the analysis of glycopeptides through MS remains challenging due to the microheterogeneity and macroheterogeneity of the glycoprotein. Selective enrichment of glycopeptides from complex samples prior to MS analysis is essential for successful glycoproteome research. In this work, we systematically investigated the behaviors and performances of boronic acid chemistry, ZIC-HILIC, and PGC of glycopeptide enrichment to promote understanding of these methods. We also optimized boronic acid chemistry and ZIC-HILIC enrichment methods and applied them to enrich glycopeptides from mouse liver. The intact N-glycopeptides were interpreted using the in-house analysis software pGlyco 2.0. We found that boronic acid chemistry in this study preferred to capture glycopeptides with high mannose glycans, ZIC-HILIC enriched most N-glycopeptides and did not show significant preference during enrichment and PGC was not suitable for separating glycopeptides with a long amino acid sequence. We performed a detailed study on the behaviors and performances of boronic acid chemistry, ZIC-HILIC, and PGC enrichment methods and provide a better understanding of enrichment methods for further glycoproteomics research.

Parallel-vector solution of large-scale structural analysis problems on supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1989-01-01

A direct linear equation solution method based on the Choleski factorization procedure is presented which exploits both parallel and vector features of supercomputers. The new equation solver is described, and its performance is evaluated by solving structural analysis problems on three high-performance computers. The method has been implemented using Force, a generic parallel FORTRAN language.

Rapid qualitative and quantitative analysis of proanthocyanidin oligomers and polymers by ultra-performance liquid chromatography – tandem mass spectrometry (UPLC-MS/MS)

USDA-ARS?s Scientific Manuscript database

We developed a rapid method with ultra-performance liquid chromatography – tandem mass spectrometry (UPLC-MS/MS) for the qualitative and quantitative analysis of plant proanthocyanidins (PAs) directly from crude plant extracts. The method utilizes a range of cone voltages to achieve the depolymeriza...

Determination of low molecular weight thiols using monobromobimane fluorescent labeling and high-performance liquid chromatography

NASA Technical Reports Server (NTRS)

Fahey, Robert C.; Newton, Gerald L.

1988-01-01

Methods are described for the preparation and high-performance liquid chromatography (HPLC) analysis of monobromobimane derivatives of low molecular weight thiols in extracts of biological samples. Typical problems encountered in the development and application of these methods are discussed. Analysis of mung bean extract is used as an example.

Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Lavelle, Thomas M.; Patnaik, Surya

2003-01-01

The neural network and regression methods of NASA Glenn Research Center s COMETBOARDS design optimization testbed were used to generate approximate analysis and design models for a subsonic aircraft operating at Mach 0.85 cruise speed. The analytical model is defined by nine design variables: wing aspect ratio, engine thrust, wing area, sweep angle, chord-thickness ratio, turbine temperature, pressure ratio, bypass ratio, fan pressure; and eight response parameters: weight, landing velocity, takeoff and landing field lengths, approach thrust, overall efficiency, and compressor pressure and temperature. The variables were adjusted to optimally balance the engines to the airframe. The solution strategy included a sensitivity model and the soft analysis model. Researchers generated the sensitivity model by training the approximators to predict an optimum design. The trained neural network predicted all response variables, within 5-percent error. This was reduced to 1 percent by the regression method. The soft analysis model was developed to replace aircraft analysis as the reanalyzer in design optimization. Soft models have been generated for a neural network method, a regression method, and a hybrid method obtained by combining the approximators. The performance of the models is graphed for aircraft weight versus thrust as well as for wing area and turbine temperature. The regression method followed the analytical solution with little error. The neural network exhibited 5-percent maximum error over all parameters. Performance of the hybrid method was intermediate in comparison to the individual approximators. Error in the response variable is smaller than that shown in the figure because of a distortion scale factor. The overall performance of the approximators was considered to be satisfactory because aircraft analysis with NASA Langley Research Center s FLOPS (Flight Optimization System) code is a synthesis of diverse disciplines: weight estimation, aerodynamic analysis, engine cycle analysis, propulsion data interpolation, mission performance, airfield length for landing and takeoff, noise footprint, and others.

An optimal design of wind turbine and ship structure based on neuro-response surface method

NASA Astrophysics Data System (ADS)

Lee, Jae-Chul; Shin, Sung-Chul; Kim, Soo-Young

2015-07-01

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

Sigma metric analysis for performance of creatinine with fresh frozen serum.

PubMed

Kang, Fengfeng; Zhang, Chuanbao; Wang, Wei; Wang, Zhiguo

2016-01-01

Six sigma provides an objective and quantitative methodology to describe the laboratory testing performance. In this study, we conducted a national trueness verification scheme with fresh frozen serum (FFS) for serum creatinine to evaluate its performance in China. Two different concentration levels of FFS, targeted with reference method, were sent to 98 laboratories in China. Imprecision and bias of the measurement procedure were calculated for each participant to further evaluate the sigma value. Quality goal index (QGI) analysis was used to investigate the reason of unacceptable performance for laboratories with σ < 3. Our study indicated that the sample with high concentration of creatinine had preferable sigma values. For the enzymatic method, 7.0% (5/71) to 45.1% (32/71) of the laboratories need to improve their measurement procedures (σ < 3). And for the Jaffe method, the percentages were from 11.5% (3/26) to 73.1% (19/26). QGI analysis suggested that most of the laboratories (62.5% for the enzymatic method and 68.4% for the Jaffe method) should make an effort to improve the trueness (QGI > 1.2). Only 3.1-5.3% of the laboratories should improve both of the precision and trueness. Sigma metric analysis of the serum creatinine assays is disappointing, which was mainly due to the unacceptable analytical bias according to the QGI analysis. Further effort is needed to enhance the trueness of the creatinine measurement.

Performance assessment of methods for estimation of fractal dimension from scanning electron microscope images.

PubMed

Risović, Dubravko; Pavlović, Zivko

2013-01-01

Processing of gray scale images in order to determine the corresponding fractal dimension is very important due to widespread use of imaging technologies and application of fractal analysis in many areas of science, technology, and medicine. To this end, many methods for estimation of fractal dimension from gray scale images have been developed and routinely used. Unfortunately different methods (dimension estimators) often yield significantly different results in a manner that makes interpretation difficult. Here, we report results of comparative assessment of performance of several most frequently used algorithms/methods for estimation of fractal dimension. To that purpose, we have used scanning electron microscope images of aluminum oxide surfaces with different fractal dimensions. The performance of algorithms/methods was evaluated using the statistical Z-score approach. The differences between performances of six various methods are discussed and further compared with results obtained by electrochemical impedance spectroscopy on the same samples. The analysis of results shows that the performance of investigated algorithms varies considerably and that systematically erroneous fractal dimensions could be estimated using certain methods. The differential cube counting, triangulation, and box counting algorithms showed satisfactory performance in the whole investigated range of fractal dimensions. Difference statistic is proved to be less reliable generating 4% of unsatisfactory results. The performances of the Power spectrum, Partitioning and EIS were unsatisfactory in 29%, 38%, and 75% of estimations, respectively. The results of this study should be useful and provide guidelines to researchers using/attempting fractal analysis of images obtained by scanning microscopy or atomic force microscopy. © Wiley Periodicals, Inc.

Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications.

PubMed

Ruijter, Jan M; Pfaffl, Michael W; Zhao, Sheng; Spiess, Andrej N; Boggy, Gregory; Blom, Jochen; Rutledge, Robert G; Sisti, Davide; Lievens, Antoon; De Preter, Katleen; Derveaux, Stefaan; Hellemans, Jan; Vandesompele, Jo

2013-01-01

RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription (RT) in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In parallel with the democratization of RT-qPCR and its increasing use in biomedical research or biomarker discovery, we witnessed a growth in the number of gene expression data analysis methods. Most of these methods are based on the principle that the position of the amplification curve with respect to the cycle-axis is a measure for the initial target quantity: the later the curve, the lower the target quantity. However, most methods differ in the mathematical algorithms used to determine this position, as well as in the way the efficiency of the PCR reaction (the fold increase of product per cycle) is determined and applied in the calculations. Moreover, there is dispute about whether the PCR efficiency is constant or continuously decreasing. Together this has lead to the development of different methods to analyze amplification curves. In published comparisons of these methods, available algorithms were typically applied in a restricted or outdated way, which does not do them justice. Therefore, we aimed at development of a framework for robust and unbiased assessment of curve analysis performance whereby various publicly available curve analysis methods were thoroughly compared using a previously published large clinical data set (Vermeulen et al., 2009) [11]. The original developers of these methods applied their algorithms and are co-author on this study. We assessed the curve analysis methods' impact on transcriptional biomarker identification in terms of expression level, statistical significance, and patient-classification accuracy. The concentration series per gene, together with data sets from unpublished technical performance experiments, were analyzed in order to assess the algorithms' precision, bias, and resolution. While large differences exist between methods when considering the technical performance experiments, most methods perform relatively well on the biomarker data. The data and the analysis results per method are made available to serve as benchmark for further development and evaluation of qPCR curve analysis methods (http://qPCRDataMethods.hfrc.nl). Copyright © 2012 Elsevier Inc. All rights reserved.

Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

High-performance liquid chromatography with fluorescence detection for the rapid analysis of pheophytins and pyropheophytins in virgin olive oil.

PubMed

Li, Xueqi; Woodman, Michael; Wang, Selina C

2015-08-01

Pheophytins and pyropheophytin are degradation products of chlorophyll pigments, and their ratios can be used as a sensitive indicator of stress during the manufacturing and storage of olive oil. They increase over time depending on the storage condition and if the oil is exposed to heat treatments during the refining process. The traditional analysis method includes solvent- and time-consuming steps of solid-phase extraction followed by analysis by high-performance liquid chromatography with ultraviolet detection. We developed an improved dilute/fluorescence method where multi-step sample preparation was replaced by a simple isopropanol dilution before the high-performance liquid chromatography injection. A quaternary solvent gradient method was used to include a fourth strong solvent wash on a quaternary gradient pump, which avoided the need to premix any solvents and greatly reduced the oil residues on the column from previous analysis. This new method not only reduces analysis cost and time but shows reliability, repeatability, and improved sensitivity, especially important for low-level samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis.

PubMed

Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

2016-12-13

In untargeted metabolomics analysis, several factors (e.g., unwanted experimental &biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data.

Performance Evaluation and Online Realization of Data-driven Normalization Methods Used in LC/MS based Untargeted Metabolomics Analysis

PubMed Central

Li, Bo; Tang, Jing; Yang, Qingxia; Cui, Xuejiao; Li, Shuang; Chen, Sijie; Cao, Quanxing; Xue, Weiwei; Chen, Na; Zhu, Feng

2016-01-01

In untargeted metabolomics analysis, several factors (e.g., unwanted experimental & biological variations and technical errors) may hamper the identification of differential metabolic features, which requires the data-driven normalization approaches before feature selection. So far, ≥16 normalization methods have been widely applied for processing the LC/MS based metabolomics data. However, the performance and the sample size dependence of those methods have not yet been exhaustively compared and no online tool for comparatively and comprehensively evaluating the performance of all 16 normalization methods has been provided. In this study, a comprehensive comparison on these methods was conducted. As a result, 16 methods were categorized into three groups based on their normalization performances across various sample sizes. The VSN, the Log Transformation and the PQN were identified as methods of the best normalization performance, while the Contrast consistently underperformed across all sub-datasets of different benchmark data. Moreover, an interactive web tool comprehensively evaluating the performance of 16 methods specifically for normalizing LC/MS based metabolomics data was constructed and hosted at http://server.idrb.cqu.edu.cn/MetaPre/. In summary, this study could serve as a useful guidance to the selection of suitable normalization methods in analyzing the LC/MS based metabolomics data. PMID:27958387

Assessing performance of an Electronic Health Record (EHR) using Cognitive Task Analysis.

PubMed

Saitwal, Himali; Feng, Xuan; Walji, Muhammad; Patel, Vimla; Zhang, Jiajie

2010-07-01

Many Electronic Health Record (EHR) systems fail to provide user-friendly interfaces due to the lack of systematic consideration of human-centered computing issues. Such interfaces can be improved to provide easy to use, easy to learn, and error-resistant EHR systems to the users. To evaluate the usability of an EHR system and suggest areas of improvement in the user interface. The user interface of the AHLTA (Armed Forces Health Longitudinal Technology Application) was analyzed using the Cognitive Task Analysis (CTA) method called GOMS (Goals, Operators, Methods, and Selection rules) and an associated technique called KLM (Keystroke Level Model). The GOMS method was used to evaluate the AHLTA user interface by classifying each step of a given task into Mental (Internal) or Physical (External) operators. This analysis was performed by two analysts independently and the inter-rater reliability was computed to verify the reliability of the GOMS method. Further evaluation was performed using KLM to estimate the execution time required to perform the given task through application of its standard set of operators. The results are based on the analysis of 14 prototypical tasks performed by AHLTA users. The results show that on average a user needs to go through 106 steps to complete a task. To perform all 14 tasks, they would spend about 22 min (independent of system response time) for data entry, of which 11 min are spent on more effortful mental operators. The inter-rater reliability analysis performed for all 14 tasks was 0.8 (kappa), indicating good reliability of the method. This paper empirically reveals and identifies the following finding related to the performance of AHLTA: (1) large number of average total steps to complete common tasks, (2) high average execution time and (3) large percentage of mental operators. The user interface can be improved by reducing (a) the total number of steps and (b) the percentage of mental effort, required for the tasks. 2010 Elsevier Ireland Ltd. All rights reserved.

Application of the Bootstrap Methods in Factor Analysis.

ERIC Educational Resources Information Center

Ichikawa, Masanori; Konishi, Sadanori

1995-01-01

A Monte Carlo experiment was conducted to investigate the performance of bootstrap methods in normal theory maximum likelihood factor analysis when the distributional assumption was satisfied or unsatisfied. Problems arising with the use of bootstrap methods are highlighted. (SLD)

The Kjeldahl method as a primary reference procedure for total protein in certified reference materials used in clinical chemistry. II. Selection of direct Kjeldahl analysis and its preliminary performance parameters.

PubMed

Vinklárková, Bára; Chromý, Vratislav; Šprongl, Luděk; Bittová, Miroslava; Rikanová, Milena; Ohnútková, Ivana; Žaludová, Lenka

2015-01-01

To select a Kjeldahl procedure suitable for the determination of total protein in reference materials used in laboratory medicine, we reviewed in our previous article Kjeldahl methods adopted by clinical chemistry and found an indirect two-step analysis by total Kjeldahl nitrogen corrected for its nonprotein nitrogen and a direct analysis made on isolated protein precipitates. In this article, we compare both procedures on various reference materials. An indirect Kjeldahl method gave falsely lower results than a direct analysis. Preliminary performance parameters qualify the direct Kjeldahl analysis as a suitable primary reference procedure for the certification of total protein in reference laboratories.

In-injection port thermal desorption for explosives trace evidence analysis.

PubMed

Sigman, M E; Ma, C Y

1999-10-01

A gas chromatographic method utilizing thermal desorption of a dry surface wipe for the analysis of explosives trace chemical evidence has been developed and validated using electron capture and negative ion chemical ionization mass spectrometric detection. Thermal desorption was performed within a split/splitless injection port with minimal instrument modification. Surface-abraded Teflon tubing provided the solid support for sample collection and desorption. Performance was characterized by desorption efficiency, reproducibility, linearity of the calibration, and method detection and quantitation limits. Method validation was performed with a series of dinitrotoluenes, trinitrotoluene, two nitroester explosives, and one nitramine explosive. The method was applied to the sampling of a single piece of debris from an explosion containing trinitrotoluene.

Study on the influence of X-ray tube spectral distribution on the analysis of bulk samples and thin films: Fundamental parameters method and theoretical coefficient algorithms

NASA Astrophysics Data System (ADS)

Sitko, Rafał

2008-11-01

Knowledge of X-ray tube spectral distribution is necessary in theoretical methods of matrix correction, i.e. in both fundamental parameter (FP) methods and theoretical influence coefficient algorithms. Thus, the influence of X-ray tube distribution on the accuracy of the analysis of thin films and bulk samples is presented. The calculations are performed using experimental X-ray tube spectra taken from the literature and theoretical X-ray tube spectra evaluated by three different algorithms proposed by Pella et al. (X-Ray Spectrom. 14 (1985) 125-135), Ebel (X-Ray Spectrom. 28 (1999) 255-266), and Finkelshtein and Pavlova (X-Ray Spectrom. 28 (1999) 27-32). In this study, Fe-Cr-Ni system is selected as an example and the calculations are performed for X-ray tubes commonly applied in X-ray fluorescence analysis (XRF), i.e., Cr, Mo, Rh and W. The influence of X-ray tube spectra on FP analysis is evaluated when quantification is performed using various types of calibration samples. FP analysis of bulk samples is performed using pure-element bulk standards and multielement bulk standards similar to the analyzed material, whereas for FP analysis of thin films, the bulk and thin pure-element standards are used. For the evaluation of the influence of X-ray tube spectra on XRF analysis performed by theoretical influence coefficient methods, two algorithms for bulk samples are selected, i.e. Claisse-Quintin (Can. Spectrosc. 12 (1967) 129-134) and COLA algorithms (G.R. Lachance, Paper Presented at the International Conference on Industrial Inorganic Elemental Analysis, Metz, France, June 3, 1981) and two algorithms (constant and linear coefficients) for thin films recently proposed by Sitko (X-Ray Spectrom. 37 (2008) 265-272).

The Performance of Methods to Test Upper-Level Mediation in the Presence of Nonnormal Data

ERIC Educational Resources Information Center

Pituch, Keenan A.; Stapleton, Laura M.

2008-01-01

A Monte Carlo study compared the statistical performance of standard and robust multilevel mediation analysis methods to test indirect effects for a cluster randomized experimental design under various departures from normality. The performance of these methods was examined for an upper-level mediation process, where the indirect effect is a fixed…

Comparing direct and iterative equation solvers in a large structural analysis software system

NASA Technical Reports Server (NTRS)

Poole, E. L.

1991-01-01

Two direct Choleski equation solvers and two iterative preconditioned conjugate gradient (PCG) equation solvers used in a large structural analysis software system are described. The two direct solvers are implementations of the Choleski method for variable-band matrix storage and sparse matrix storage. The two iterative PCG solvers include the Jacobi conjugate gradient method and an incomplete Choleski conjugate gradient method. The performance of the direct and iterative solvers is compared by solving several representative structural analysis problems. Some key factors affecting the performance of the iterative solvers relative to the direct solvers are identified.

Analysis of Carbamate Pesticides: Validation of Semi-Volatile Analysis by HPLC-MS/MS by EPA Method MS666

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

Owens, J; Koester, C

The Environmental Protection Agency's (EPA) Region 5 Chicago Regional Laboratory (CRL) developed a method for analysis of aldicarb, bromadiolone, carbofuran, oxamyl, and methomyl in water by high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS), titled Method EPA MS666. This draft standard operating procedure (SOP) was distributed to multiple EPA laboratories and to Lawrence Livermore National Laboratory, which was tasked to serve as a reference laboratory for EPA's Environmental Reference Laboratory Network (ERLN) and to develop and validate analytical procedures. The primary objective of this study was to validate and verify the analytical procedures described in MS666 for analysis of carbamatemore » pesticides in aqueous samples. The gathered data from this validation study will be used to: (1) demonstrate analytical method performance; (2) generate quality control acceptance criteria; and (3) revise the SOP to provide a validated method that would be available for use during a homeland security event. The data contained in this report will be compiled, by EPA CRL, with data generated by other EPA Regional laboratories so that performance metrics of Method EPA MS666 can be determined.« less

Analysis of Thiodiglycol: Validation of Semi-Volatile Analysis by HPLC-MS/MS by EPA Method MS777

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

Owens, J; Koester, C

The Environmental Protection Agency's (EPA) Region 5 Chicago Regional Laboratory (CRL) developed a method for the analysis of thiodiglycol, the breakdown product of the sulfur mustard HD, in water by high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS), titled Method EPA MS777 (hereafter referred to as EPA CRL SOP MS777). This draft standard operating procedure (SOP) was distributed to multiple EPA laboratories and to Lawrence Livermore National Laboratory, which was tasked to serve as a reference laboratory for EPA's Environmental Reference Laboratory Network (ERLN) and to develop and validate analytical procedures. The primary objective of this study was to verifymore » the analytical procedures described in MS777 for analysis of thiodiglycol in aqueous samples. The gathered data from this study will be used to: (1) demonstrate analytical method performance; (2) generate quality control acceptance criteria; and (3) revise the SOP to provide a validated method that would be available for use during a homeland security event. The data contained in this report will be compiled, by EPA CRL, with data generated by other EPA Regional laboratories so that performance metrics of Method EPA MS777 can be determined.« less

Single-Cell RNA-Sequencing: Assessment of Differential Expression Analysis Methods.

PubMed

Dal Molin, Alessandra; Baruzzo, Giacomo; Di Camillo, Barbara

2017-01-01

The sequencing of the transcriptomes of single-cells, or single-cell RNA-sequencing, has now become the dominant technology for the identification of novel cell types and for the study of stochastic gene expression. In recent years, various tools for analyzing single-cell RNA-sequencing data have been proposed, many of them with the purpose of performing differentially expression analysis. In this work, we compare four different tools for single-cell RNA-sequencing differential expression, together with two popular methods originally developed for the analysis of bulk RNA-sequencing data, but largely applied to single-cell data. We discuss results obtained on two real and one synthetic dataset, along with considerations about the perspectives of single-cell differential expression analysis. In particular, we explore the methods performance in four different scenarios, mimicking different unimodal or bimodal distributions of the data, as characteristic of single-cell transcriptomics. We observed marked differences between the selected methods in terms of precision and recall, the number of detected differentially expressed genes and the overall performance. Globally, the results obtained in our study suggest that is difficult to identify a best performing tool and that efforts are needed to improve the methodologies for single-cell RNA-sequencing data analysis and gain better accuracy of results.

A comparison of performance of automatic cloud coverage assessment algorithm for Formosat-2 image using clustering-based and spatial thresholding methods

NASA Astrophysics Data System (ADS)

Hsu, Kuo-Hsien

2012-11-01

Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.

Variable selection based near infrared spectroscopy quantitative and qualitative analysis on wheat wet gluten

NASA Astrophysics Data System (ADS)

Lü, Chengxu; Jiang, Xunpeng; Zhou, Xingfan; Zhang, Yinqiao; Zhang, Naiqian; Wei, Chongfeng; Mao, Wenhua

2017-10-01

Wet gluten is a useful quality indicator for wheat, and short wave near infrared spectroscopy (NIRS) is a high performance technique with the advantage of economic rapid and nondestructive test. To study the feasibility of short wave NIRS analyzing wet gluten directly from wheat seed, 54 representative wheat seed samples were collected and scanned by spectrometer. 8 spectral pretreatment method and genetic algorithm (GA) variable selection method were used to optimize analysis. Both quantitative and qualitative model of wet gluten were built by partial least squares regression and discriminate analysis. For quantitative analysis, normalization is the optimized pretreatment method, 17 wet gluten sensitive variables are selected by GA, and GA model performs a better result than that of all variable model, with R2V=0.88, and RMSEV=1.47. For qualitative analysis, automatic weighted least squares baseline is the optimized pretreatment method, all variable models perform better results than those of GA models. The correct classification rates of 3 class of <24%, 24-30%, >30% wet gluten content are 95.45, 84.52, and 90.00%, respectively. The short wave NIRS technique shows potential for both quantitative and qualitative analysis of wet gluten for wheat seed.

Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression studies

PubMed Central

Nilsson, Björn; Håkansson, Petra; Johansson, Mikael; Nelander, Sven; Fioretos, Thoas

2007-01-01

Ontological analysis facilitates the interpretation of microarray data. Here we describe new ontological analysis methods which, unlike existing approaches, are threshold-free and statistically powerful. We perform extensive evaluations and introduce a new concept, detection spectra, to characterize methods. We show that different ontological analysis methods exhibit distinct detection spectra, and that it is critical to account for this diversity. Our results argue strongly against the continued use of existing methods, and provide directions towards an enhanced approach. PMID:17488501

CSM Testbed Development and Large-Scale Structural Applications

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Gillian, R. E.; Mccleary, Susan L.; Lotts, C. G.; Poole, E. L.; Overman, A. L.; Macy, S. C.

1989-01-01

A research activity called Computational Structural Mechanics (CSM) conducted at the NASA Langley Research Center is described. This activity is developing advanced structural analysis and computational methods that exploit high-performance computers. Methods are developed in the framework of the CSM Testbed software system and applied to representative complex structural analysis problems from the aerospace industry. An overview of the CSM Testbed methods development environment is presented and some new numerical methods developed on a CRAY-2 are described. Selected application studies performed on the NAS CRAY-2 are also summarized.

An Empirical Assessment of Defense Contractor Risk 1976-1984.

DTIC Science & Technology

1986-06-01

Model to evaluate the. Department of Defense contract pricing , financing, and profit policies . ’ D*’ ’ *NTV D? 7A’:: TA E *A l ..... -:- A-i SN 0102...defense con- tractor risk-return relationship is performed utilizing four methods: mean-variance analysis of rate of return, the Capital Asset Pricing Model ...relationship is performed utilizing four methods: mean- variance analysis of rate of return, the Capital Asset Pricing Model , mean-variance analysis of total

Evaluation of the use of nodal methods for MTR neutronic analysis

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

Reitsma, F.; Mueller, E.Z.

1997-08-01

Although modern nodal methods are used extensively in the nuclear power industry, their use for research reactor analysis has been very limited. The suitability of nodal methods for material testing reactor analysis is investigated with the emphasis on the modelling of the core region (fuel assemblies). The nodal approach`s performance is compared with that of the traditional finite-difference fine mesh approach. The advantages of using nodal methods coupled with integrated cross section generation systems are highlighted, especially with respect to data preparation, simplicity of use and the possibility of performing a great variety of reactor calculations subject to strict timemore » limitations such as are required for the RERTR program.« less

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait.

PubMed

Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

2003-12-31

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits.

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait

PubMed Central

Knight, Jo; North, Bernard V; Sham, Pak C; Curtis, David

2003-01-01

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits. PMID:14975142

Probability of Failure Analysis Standards and Guidelines for Expendable Launch Vehicles

NASA Astrophysics Data System (ADS)

Wilde, Paul D.; Morse, Elisabeth L.; Rosati, Paul; Cather, Corey

2013-09-01

Recognizing the central importance of probability of failure estimates to ensuring public safety for launches, the Federal Aviation Administration (FAA), Office of Commercial Space Transportation (AST), the National Aeronautics and Space Administration (NASA), and U.S. Air Force (USAF), through the Common Standards Working Group (CSWG), developed a guide for conducting valid probability of failure (POF) analyses for expendable launch vehicles (ELV), with an emphasis on POF analysis for new ELVs. A probability of failure analysis for an ELV produces estimates of the likelihood of occurrence of potentially hazardous events, which are critical inputs to launch risk analysis of debris, toxic, or explosive hazards. This guide is intended to document a framework for POF analyses commonly accepted in the US, and should be useful to anyone who performs or evaluates launch risk analyses for new ELVs. The CSWG guidelines provide performance standards and definitions of key terms, and are being revised to address allocation to flight times and vehicle response modes. The POF performance standard allows a launch operator to employ alternative, potentially innovative methodologies so long as the results satisfy the performance standard. Current POF analysis practice at US ranges includes multiple methodologies described in the guidelines as accepted methods, but not necessarily the only methods available to demonstrate compliance with the performance standard. The guidelines include illustrative examples for each POF analysis method, which are intended to illustrate an acceptable level of fidelity for ELV POF analyses used to ensure public safety. The focus is on providing guiding principles rather than "recipe lists." Independent reviews of these guidelines were performed to assess their logic, completeness, accuracy, self- consistency, consistency with risk analysis practices, use of available information, and ease of applicability. The independent reviews confirmed the general validity of the performance standard approach and suggested potential updates to improve the accuracy each of the example methods, especially to address reliability growth.

A Shot Number Based Approach to Performance Analysis in Table Tennis

PubMed Central

Yoshida, Kazuto; Yamada, Koshi

2017-01-01

Abstract The current study proposes a novel approach that improves the conventional performance analysis in table tennis by introducing the concept of frequency, or the number of shots, of each shot number. The improvements over the conventional method are as follows: better accuracy of the evaluation of skills and tactics of players, additional insights into scoring and returning skills and ease of understanding the results with a single criterion. The performance analysis of matches played at the 2012 Summer Olympics in London was conducted using the proposed method. The results showed some effects of the shot number and gender differences in table tennis. Furthermore, comparisons were made between Chinese players and players from other countries, what threw light on the skills and tactics of the Chinese players. The present findings demonstrate that the proposed method provides useful information and has some advantages over the conventional method. PMID:28210334

Comparative analysis of the modified enclosed energy metric for self-focusing holograms from digital lensless holographic microscopy.

PubMed

Trujillo, Carlos; Garcia-Sucerquia, Jorge

2015-06-01

A comparative analysis of the performance of the modified enclosed energy (MEE) method for self-focusing holograms recorded with digital lensless holographic microscopy is presented. Notwithstanding the MEE analysis previously published, no extended analysis of its performance has been reported. We have tested the MEE in terms of the minimum axial distance allowed between the set of reconstructed holograms to search for the focal plane and the elapsed time to obtain the focused image. These parameters have been compared with those for some of the already reported methods in the literature. The MEE achieves better results in terms of self-focusing quality but at a higher computational cost. Despite its longer processing time, the method remains within a time frame to be technologically attractive. Modeled and experimental holograms have been utilized in this work to perform the comparative study.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Simultaneous determination of rhamnose, xylitol, arabitol, fructose, glucose, inositol, sucrose, maltose in jujube (Zizyphus jujube Mill.) extract: comparison of HPLC-ELSD, LC-ESI-MS/MS and GC-MS.

PubMed

Sun, Shihao; Wang, Hui; Xie, Jianping; Su, Yue

2016-01-01

Jujube extract is commonly used as a food additive and flavoring. The sensory properties of the extract, especially sweetness, are a critical factor determining the product quality and therefore affecting consumer acceptability. Small molecular carbohydrates make major contribution to the sweetness of the jujube extract, and their types and contents in the extract have direct influence on quality of the product. So, an appropriate qualitative and quantitative method for determination of the carbohydrates is vitally important for quality control of the product. High performance liquid chromatography-evaporative light scattering detection (HPLC-ELSD), liquid chromatography-electronic spay ionization tandem mass spectrometry (LC-ESI-MS/MS), and gas chromatography-mass spectrometry (GC-MS) methods have been developed and applied to determining small molecular carbohydrates in jujube extract, respectively. Eight sugars and alditols were identified from the extract, including rhamnose, xylitol, arabitol, fructose, glucose, inositol, sucrose, and maltose. Comparisons were carried out to investigate the performance of the methods. Although the methods have been found to perform satisfactorily, only three sugars (fructose, glucose and inositol) could be detected by all these methods. Meanwhile, a similar quantitative result for the three sugars can be obtained by the methods. Eight sugars and alditols in the jujube extract were determined by HPLC-ELSD, LC-ESI-MS/MS and GC-MS, respectively. The LC-ELSD method and the LC-ESI-MS/MS method with good precision and accuracy were suitable for quantitative analysis of carbohydrates in jujube extract; although the performance of the GC-MS method for quantitative analysis was inferior to the other methods, it has a wider scope in qualitative analysis. A multi-analysis technique should be adopted in order to obtain complete constituents of about the carbohydrates in jujube extract, and the methods should be employed according to the purpose of analysis.

Use of model calibration to achieve high accuracy in analysis of computer networks

DOEpatents

Frogner, Bjorn; Guarro, Sergio; Scharf, Guy

2004-05-11

A system and method are provided for creating a network performance prediction model, and calibrating the prediction model, through application of network load statistical analyses. The method includes characterizing the measured load on the network, which may include background load data obtained over time, and may further include directed load data representative of a transaction-level event. Probabilistic representations of load data are derived to characterize the statistical persistence of the network performance variability and to determine delays throughout the network. The probabilistic representations are applied to the network performance prediction model to adapt the model for accurate prediction of network performance. Certain embodiments of the method and system may be used for analysis of the performance of a distributed application characterized as data packet streams.

Evaluation of adding item-response theory analysis for evaluation of the European Board of Ophthalmology Diploma examination.

PubMed

Mathysen, Danny G P; Aclimandos, Wagih; Roelant, Ella; Wouters, Kristien; Creuzot-Garcher, Catherine; Ringens, Peter J; Hawlina, Marko; Tassignon, Marie-José

2013-11-01

To investigate whether introduction of item-response theory (IRT) analysis, in parallel to the 'traditional' statistical analysis methods available for performance evaluation of multiple T/F items as used in the European Board of Ophthalmology Diploma (EBOD) examination, has proved beneficial, and secondly, to study whether the overall assessment performance of the current written part of EBOD is sufficiently high (KR-20≥ 0.90) to be kept as examination format in future EBOD editions. 'Traditional' analysis methods for individual MCQ item performance comprise P-statistics, Rit-statistics and item discrimination, while overall reliability is evaluated through KR-20 for multiple T/F items. The additional set of statistical analysis methods for the evaluation of EBOD comprises mainly IRT analysis. These analysis techniques are used to monitor whether the introduction of negative marking for incorrect answers (since EBOD 2010) has a positive influence on the statistical performance of EBOD as a whole and its individual test items in particular. Item-response theory analysis demonstrated that item performance parameters should not be evaluated individually, but should be related to one another. Before the introduction of negative marking, the overall EBOD reliability (KR-20) was good though with room for improvement (EBOD 2008: 0.81; EBOD 2009: 0.78). After the introduction of negative marking, the overall reliability of EBOD improved significantly (EBOD 2010: 0.92; EBOD 2011:0.91; EBOD 2012: 0.91). Although many statistical performance parameters are available to evaluate individual items, our study demonstrates that the overall reliability assessment remains the only crucial parameter to be evaluated allowing comparison. While individual item performance analysis is worthwhile to undertake as secondary analysis, drawing final conclusions seems to be more difficult. Performance parameters need to be related, as shown by IRT analysis. Therefore, IRT analysis has proved beneficial for the statistical analysis of EBOD. Introduction of negative marking has led to a significant increase in the reliability (KR-20 > 0.90), indicating that the current examination format can be kept for future EBOD examinations. © 2013 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

A Compact Review of Multi-criteria Decision Analysis Uncertainty Techniques

DTIC Science & Technology

2013-02-01

9 3.4 PROMETHEE -GAIA Method...obtained (74). 3.4 PROMETHEE -GAIA Method Preference Ranking Organization Method for Enrichment Evaluation ( PROMETHEE ) and Geometrical Analysis for...greater understanding of the importance of their selections. The PROMETHEE method was designed to perform MCDA while accounting for each of these

SEP thrust subsystem performance sensitivity analysis

NASA Technical Reports Server (NTRS)

Atkins, K. L.; Sauer, C. G., Jr.; Kerrisk, D. J.

1973-01-01

This is a two-part report on solar electric propulsion (SEP) performance sensitivity analysis. The first part describes the preliminary analysis of the SEP thrust system performance for an Encke rendezvous mission. A detailed description of thrust subsystem hardware tolerances on mission performance is included together with nominal spacecraft parameters based on these tolerances. The second part describes the method of analysis and graphical techniques used in generating the data for Part 1. Included is a description of both the trajectory program used and the additional software developed for this analysis. Part 2 also includes a comprehensive description of the use of the graphical techniques employed in this performance analysis.

Finite element method analysis of cold forging for deformation and densification of Mo alloyed sintered steel

NASA Astrophysics Data System (ADS)

Kamakoshi, Y.; Nishida, S.; Kanbe, K.; Shohji, I.

2017-10-01

In recent years, powder metallurgy (P/M) materials have been expected to be applied to automobile products. Then, not only high cost performance but also more strength, wear resistance, long-life and so on are required for P/M materials. As an improvement method of mechanical properties of P/M materials, a densification is expected to be one of effective processes. In this study, to examine behaviours of the densification of Mo-alloyed sintered steel in a cold-forging process, finite element method (FEM) analysis was performed. Firstly, a columnar specimen was cut out from the inner part of a sintered specimen and a load-stroke diagram was obtained by the compression test. 2D FEM analysis was performed using the obtained load-stroke diagram. To correct the errors of stress between the porous mode and the rigid-elastic mode of analysis software, the analysis of a polynominal approximation was performed. As a result, the modified true stress-true strain diagram was obtained for the sintered steel with the densification. Afterwards, 3D FEM analysis of backward extrusion was carried out using the modified true stress-true strain diagram. It was confirmed that both the shape and density of the sintered steel analyzed by new FEM analysis that we suggest correspond well with experimental ones.

Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

PubMed

Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

2013-01-01

DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

Analysis of Free Modeling Predictions by RBO Aleph in CASP11

PubMed Central

Mabrouk, Mahmoud; Werner, Tim; Schneider, Michael; Putz, Ines; Brock, Oliver

2015-01-01

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue–residue contact prediction by EPC-map and contact–guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. PMID:26492194

Quality Analysis of Chlorogenic Acid and Hyperoside in Crataegi fructus

PubMed Central

Weon, Jin Bae; Jung, Youn Sik; Ma, Choong Je

2016-01-01

Background: Crataegi fructus is a herbal medicine for strong stomach, sterilization, and alcohol detoxification. Chlorogenic acid and hyperoside are the major compounds in Crataegi fructus. Objective: In this study, we established novel high-performance liquid chromatography (HPLC)-diode array detection analysis method of chlorogenic acid and hyperoside for quality control of Crataegi fructus. Materials and Methods: HPLC analysis was achieved on a reverse-phase C18 column (5 μm, 4.6 mm × 250 mm) using water and acetonitrile as mobile phase with gradient system. The method was validated for linearity, precision, and accuracy. About 31 batches of Crataegi fructus samples collected from Korea and China were analyzed by using HPLC fingerprint of developed HPLC method. Then, the contents of chlorogenic acid and hyperoside were compared for quality evaluation of Crataegi fructus. Results: The results have shown that the average contents (w/w %) of chlorogenic acid and hyperoside in Crataegi fructus collected from Korea were 0.0438% and 0.0416%, respectively, and the average contents (w/w %) of 0.0399% and 0.0325%, respectively. Conclusion: In conclusion, established HPLC analysis method was stable and could provide efficient quality evaluation for monitoring of commercial Crataegi fructus. SUMMARY Quantitative analysis method of chlorogenic acid and hyperoside in Crataegi fructus is developed by high.performance liquid chromatography.(HPLC).diode array detectionEstablished HPLC analysis method is validated with linearity, precision, and accuracyThe developed method was successfully applied for quantitative analysis of Crataegi fructus sample collected from Korea and China. Abbreviations used: HPLC: High-performance liquid chromatography, GC: Gas chromatography, MS: Mass spectrometer, LOD: Limits of detection, LOQ: Limits of quantification, RSD: Relative standard deviation, RRT: Relative retention time, RPA: Relation peak area. PMID:27076744

Rotorcraft performance data for AEDT : Methods of using the NASA Design and Analysis of Rotorcraft tool for developing data for AEDT's Rotorcraft Performance Model

DOT National Transportation Integrated Search

2016-09-01

This report documents use of the NASA Design and Analysis of Rotorcraft (NDARC) helicopter performance software tool in developing data for the FAAs Aviation Environmental Design Tool (AEDT). These data support the Rotorcraft Performance Model (RP...

Analysis of line structure in handwritten documents using the Hough transform

NASA Astrophysics Data System (ADS)

Ball, Gregory R.; Kasiviswanathan, Harish; Srihari, Sargur N.; Narayanan, Aswin

2010-01-01

In the analysis of handwriting in documents a central task is that of determining line structure of the text, e.g., number of text lines, location of their starting and end-points, line-width, etc. While simple methods can handle ideal images, real world documents have complexities such as overlapping line structure, variable line spacing, line skew, document skew, noisy or degraded images etc. This paper explores the application of the Hough transform method to handwritten documents with the goal of automatically determining global document line structure in a top-down manner which can then be used in conjunction with a bottom-up method such as connected component analysis. The performance is significantly better than other top-down methods, such as the projection profile method. In addition, we evaluate the performance of skew analysis by the Hough transform on handwritten documents.

Multi-constituent determination and fingerprint analysis of Scutellaria indica L. using ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

PubMed

Liang, Xianrui; Zhao, Cui; Su, Weike

2015-11-01

An ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry method integrating multi-constituent determination and fingerprint analysis has been established for quality assessment and control of Scutellaria indica L. The optimized method possesses the advantages of speediness, efficiency, and allows multi-constituents determination and fingerprint analysis in one chromatographic run within 11 min. 36 compounds were detected, and 23 of them were unequivocally identified or tentatively assigned. The established fingerprint method was applied to the analysis of ten S. indica samples from different geographic locations. The quality assessment was achieved by using principal component analysis. The proposed method is useful and reliable for the characterization of multi-constituents in a complex chemical system and the overall quality assessment of S. indica. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Conceptual framework on the application of biomechanical measurement methods in driving behavior study

NASA Astrophysics Data System (ADS)

Sanjaya, Kadek Heri; Sya'bana, Yukhi Mustaqim Kusuma

2017-01-01

Research on eco-friendly vehicle development in Indonesia has largely neglected ergonomic study, despite the fact that traffic accidents have resulted in greater economic cost than fuel subsidy. We have performed a biomechanical experiment on human locomotion earlier. In this article, we describe the importance of implementing the biomechanical measurement methods in transportation ergonomic study. The instruments such as electromyogram (EMG), load cell, pressure sensor, and motion analysis methods as well as cross-correlation function analysis were explained, then the possibility of their application in driving behavior study is described. We describe the potentials and challenges of the biomechanical methods concerning the future vehicle development. The methods provide greater advantages in objective and accurate measurement not only in human task performance but also its correlation with vehicle performance.

Brightness-preserving fuzzy contrast enhancement scheme for the detection and classification of diabetic retinopathy disease.

PubMed

Datta, Niladri Sekhar; Dutta, Himadri Sekhar; Majumder, Koushik

2016-01-01

The contrast enhancement of retinal image plays a vital role for the detection of microaneurysms (MAs), which are an early sign of diabetic retinopathy disease. A retinal image contrast enhancement method has been presented to improve the MA detection technique. The success rate on low-contrast noisy retinal image analysis shows the importance of the proposed method. Overall, 587 retinal input images are tested for performance analysis. The average sensitivity and specificity are obtained as 95.94% and 99.21%, respectively. The area under curve is found as 0.932 for the receiver operating characteristics analysis. The classifications of diabetic retinopathy disease are also performed here. The experimental results show that the overall MA detection method performs better than the current state-of-the-art MA detection algorithms.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

[Clinical usefulness of urine-formed elements' information obtained from bacteria detection by flow cytometry method that uses nucleic acid staining].

PubMed

Nakagawa, Hiroko; Yuno, Tomoji; Itho, Kiichi

2009-03-01

Recently, specific detection method for Bacteria, by flow cytometry method using nucleic acid staining, was developed as a function of automated urine formed elements analyzer for routine urine testing. Here, we performed a basic study on this bacteria analysis method. In addition, we also have a comparison among urine sediment analysis, urine Gram staining and urine quantitative cultivation, the conventional methods performed up to now. As a result, the bacteria analysis with flow cytometry method that uses nucleic acid staining was excellent in reproducibility, and higher sensitivity compared with microscopic urinary sediment analysis. Based on the ROC curve analysis, which settled urine culture method as standard, cut-off level of 120/microL was defined and its sensitivity = 85.7%, specificity = 88.2%. In the analysis of scattergram, accompanied with urine culture method, among 90% of rod positive samples, 80% of dots were appeared in the area of 30 degrees from axis X. In addition, one case even indicated that analysis of bacteria by flow cytometry and scattergram of time series analysis might be helpful to trace the progress of causative bacteria therefore the information supposed to be clinically significant. Reporting bacteria information with nucleic acid staining flow cytometry method is expected to contribute to a rapid diagnostics and treatment of urinary tract infections. Besides, the contribution to screening examination of microbiology and clinical chemistry, will deliver a more efficient solution to urine analysis.

76 FR 18769 - Prospective Grant of Exclusive License: Device and System for Two Dimensional Analysis of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-05

..., 2004, now expired, entitled ``Method And Apparatus for Performing Multiple Simultaneous Manipulations..., 2006 entitled ``Method And Apparatus for Performing Multiple Simultaneous Manipulations of Biomolecules...

Applied Chaos Level Test for Validation of Signal Conditions Underlying Optimal Performance of Voice Classification Methods.

PubMed

Liu, Boquan; Polce, Evan; Sprott, Julien C; Jiang, Jack J

2018-05-17

The purpose of this study is to introduce a chaos level test to evaluate linear and nonlinear voice type classification method performances under varying signal chaos conditions without subjective impression. Voice signals were constructed with differing degrees of noise to model signal chaos. Within each noise power, 100 Monte Carlo experiments were applied to analyze the output of jitter, shimmer, correlation dimension, and spectrum convergence ratio. The computational output of the 4 classifiers was then plotted against signal chaos level to investigate the performance of these acoustic analysis methods under varying degrees of signal chaos. A diffusive behavior detection-based chaos level test was used to investigate the performances of different voice classification methods. Voice signals were constructed by varying the signal-to-noise ratio to establish differing signal chaos conditions. Chaos level increased sigmoidally with increasing noise power. Jitter and shimmer performed optimally when the chaos level was less than or equal to 0.01, whereas correlation dimension was capable of analyzing signals with chaos levels of less than or equal to 0.0179. Spectrum convergence ratio demonstrated proficiency in analyzing voice signals with all chaos levels investigated in this study. The results of this study corroborate the performance relationships observed in previous studies and, therefore, demonstrate the validity of the validation test method. The presented chaos level validation test could be broadly utilized to evaluate acoustic analysis methods and establish the most appropriate methodology for objective voice analysis in clinical practice.

Meta-analysis of the efficacy of psychological and educational interventions to improve academic performance of students with learning disabilities in Iran

PubMed Central

Faramarzi, Salar; Shamsi, Abdolhossein; Samadi, Maryam; Ahmadzade, Maryam

2015-01-01

Introduction: with due attention to the importance of learning disabilities and necessity of presenting interventions for improvement of these disorders in order to prevent future problems, this study used meta-analysis of the research model on the impact of psychological and educational interventions to improve academic performance of students with learning disabilities. Methods: with the use of meta-analysis method by integrating the results of various researches, this study specifies the effect of psychological and educational interventions. In this order, 57 studies, which their methodology was accepted, were selected and meta-analysis was performed on them. The research instrument was a meta-analysis checklist. Results: The effect size for the effectiveness of psychological-educational interventions on improving the academic performance of students with mathematics disorder (0.57), impaired writing (0.50) and dyslexia (0.55) were reported. Conclusions: The result of meta-analysis showed that according to Cohen's table, the effect size is above average, and it can be said that educational and psychological interventions improve the academic performance of students with learning disabilities. PMID:26430685

Performance of Nonlinear Finite-Difference Poisson-Boltzmann Solvers

PubMed Central

Cai, Qin; Hsieh, Meng-Juei; Wang, Jun; Luo, Ray

2014-01-01

We implemented and optimized seven finite-difference solvers for the full nonlinear Poisson-Boltzmann equation in biomolecular applications, including four relaxation methods, one conjugate gradient method, and two inexact Newton methods. The performance of the seven solvers was extensively evaluated with a large number of nucleic acids and proteins. Worth noting is the inexact Newton method in our analysis. We investigated the role of linear solvers in its performance by incorporating the incomplete Cholesky conjugate gradient and the geometric multigrid into its inner linear loop. We tailored and optimized both linear solvers for faster convergence rate. In addition, we explored strategies to optimize the successive over-relaxation method to reduce its convergence failures without too much sacrifice in its convergence rate. Specifically we attempted to adaptively change the relaxation parameter and to utilize the damping strategy from the inexact Newton method to improve the successive over-relaxation method. Our analysis shows that the nonlinear methods accompanied with a functional-assisted strategy, such as the conjugate gradient method and the inexact Newton method, can guarantee convergence in the tested molecules. Especially the inexact Newton method exhibits impressive performance when it is combined with highly efficient linear solvers that are tailored for its special requirement. PMID:24723843

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.« less

Evaluating the dynamic response of in-flight thrust calculation techniques during throttle transients

NASA Technical Reports Server (NTRS)

Ray, Ronald J.

1994-01-01

New flight test maneuvers and analysis techniques for evaluating the dynamic response of in-flight thrust models during throttle transients have been developed and validated. The approach is based on the aircraft and engine performance relationship between thrust and drag. Two flight test maneuvers, a throttle step and a throttle frequency sweep, were developed and used in the study. Graphical analysis techniques, including a frequency domain analysis method, were also developed and evaluated. They provide quantitative and qualitative results. Four thrust calculation methods were used to demonstrate and validate the test technique. Flight test applications on two high-performance aircraft confirmed the test methods as valid and accurate. These maneuvers and analysis techniques were easy to implement and use. Flight test results indicate the analysis techniques can identify the combined effects of model error and instrumentation response limitations on the calculated thrust value. The methods developed in this report provide an accurate approach for evaluating, validating, or comparing thrust calculation methods for dynamic flight applications.

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

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

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

DistributedFBA.jl: High-level, high-performance flux balance analysis in Julia

DOE PAGES

Heirendt, Laurent; Thiele, Ines; Fleming, Ronan M. T.

2017-01-16

Flux balance analysis and its variants are widely used methods for predicting steady-state reaction rates in biochemical reaction networks. The exploration of high dimensional networks with such methods is currently hampered by software performance limitations. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on a subset or all the reactions of large and huge-scale networks, on any number of threads or nodes. DistributedFBA.jl is a high-level, high-performance, open-source implementation of flux balance analysis in Julia. It is tailored to solve multiple flux balance analyses on amore » subset or all the reactions of large and huge-scale networks, on any number of threads or nodes.« less

Multiple Criteria and Multiple Periods Performance Analysis: The Comparison of North African Railways

NASA Astrophysics Data System (ADS)

Sabri, Karim; Colson, Gérard E.; Mbangala, Augustin M.

2008-10-01

Multi-period differences of technical and financial performances are analysed by comparing five North African railways over the period (1990-2004). A first approach is based on the Malmquist DEA TFP index for measuring the total factors productivity change, decomposed into technical efficiency change and technological changes. A multiple criteria analysis is also performed using the PROMETHEE II method and the software ARGOS. These methods provide complementary detailed information, especially by discriminating the technological and management progresses by Malmquist and the two dimensions of performance by Promethee: that are the service to the community and the enterprises performances, often in conflict.

Quantitative analysis of regional myocardial performance in coronary artery disease

NASA Technical Reports Server (NTRS)

Stewart, D. K.; Dodge, H. T.; Frimer, M.

1975-01-01

Findings from a group of subjects with significant coronary artery stenosis are given. A group of controls determined by use of a quantitative method for the study of regional myocardial performance based on the frame-by-frame analysis of biplane left ventricular angiograms are presented. Particular emphasis was placed upon the analysis of wall motion in terms of normalized segment dimensions, timing and velocity of contraction. The results were compared with the method of subjective assessment used clinically.

Preliminary Axial Flow Turbine Design and Off-Design Performance Analysis Methods for Rotary Wing Aircraft Engines. Part 1; Validation

NASA Technical Reports Server (NTRS)

Chen, Shu-cheng, S.

2009-01-01

For the preliminary design and the off-design performance analysis of axial flow turbines, a pair of intermediate level-of-fidelity computer codes, TD2-2 (design; reference 1) and AXOD (off-design; reference 2), are being evaluated for use in turbine design and performance prediction of the modern high performance aircraft engines. TD2-2 employs a streamline curvature method for design, while AXOD approaches the flow analysis with an equal radius-height domain decomposition strategy. Both methods resolve only the flows in the annulus region while modeling the impact introduced by the blade rows. The mathematical formulations and derivations involved in both methods are documented in references 3, 4 for TD2-2) and in reference 5 (for AXOD). The focus of this paper is to discuss the fundamental issues of applicability and compatibility of the two codes as a pair of companion pieces, to perform preliminary design and off-design analysis for modern aircraft engine turbines. Two validation cases for the design and the off-design prediction using TD2-2 and AXOD conducted on two existing high efficiency turbines, developed and tested in the NASA/GE Energy Efficient Engine (GE-E3) Program, the High Pressure Turbine (HPT; two stages, air cooled) and the Low Pressure Turbine (LPT; five stages, un-cooled), are provided in support of the analysis and discussion presented in this paper.

Application of wavelet and Fuorier transforms as powerful alternatives for derivative spectrophotometry in analysis of binary mixtures: A comparative study

NASA Astrophysics Data System (ADS)

Hassan, Said A.; Abdel-Gawad, Sherif A.

2018-02-01

Two signal processing methods, namely, Continuous Wavelet Transform (CWT) and the second was Discrete Fourier Transform (DFT) were introduced as alternatives to the classical Derivative Spectrophotometry (DS) in analysis of binary mixtures. To show the advantages of these methods, a comparative study was performed on a binary mixture of Naltrexone (NTX) and Bupropion (BUP). The methods were compared by analyzing laboratory prepared mixtures of the two drugs. By comparing performance of the three methods, it was proved that CWT and DFT methods are more efficient and advantageous in analysis of mixtures with overlapped spectra than DS. The three signal processing methods were adopted for the quantification of NTX and BUP in pure and tablet forms. The adopted methods were validated according to the ICH guideline where accuracy, precision and specificity were found to be within appropriate limits.

The spa typing of methicillin-resistant Staphylococcus aureus isolates by High Resolution Melting (HRM) analysis.

PubMed

Fasihi, Yasser; Fooladi, Saba; Mohammadi, Mohammad Ali; Emaneini, Mohammad; Kalantar-Neyestanaki, Davood

2017-09-06

Molecular typing is an important tool for control and prevention of infection. A suitable molecular typing method for epidemiological investigation must be easy to perform, highly reproducible, inexpensive, rapid and easy to interpret. In this study, two molecular typing methods including the conventional PCR-sequencing method and high resolution melting (HRM) analysis were used for staphylococcal protein A (spa) typing of 30 Methicillin-resistant Staphylococcus aureus (MRSA) isolates recovered from clinical samples. Based on PCR-sequencing method results, 16 different spa types were identified among the 30 MRSA isolates. Among the 16 different spa types, 14 spa types separated by HRM method. Two spa types including t4718 and t2894 were not separated from each other. According to our results, spa typing based on HRM analysis method is very rapid, easy to perform and cost-effective, but this method must be standardized for different regions, spa types, and real-time machinery.

Apollo/Skylab suit program management systems study. Volume 2: Cost analysis

NASA Technical Reports Server (NTRS)

1974-01-01

The business management methods employed in the performance of the Apollo-Skylab Suit Program are studied. The data accumulated over the span of the contract as well as the methods used to accumulate the data are examined. Management methods associated with the monitoring and control of resources applied towards the performance of the contract are also studied and recommended upon. The primary objective is the compilation, analysis, and presentation of historical cost performance criteria. Cost data are depicted for all phases of the Apollo-Skylab program in common, meaningful terms, whereby the data may be applicable to future suit program planning efforts.

Functional connectivity analysis in EEG source space: The choice of method

PubMed Central

Knyazeva, Maria G.

2017-01-01

Functional connectivity (FC) is among the most informative features derived from EEG. However, the most straightforward sensor-space analysis of FC is unreliable owing to volume conductance effects. An alternative—source-space analysis of FC—is optimal for high- and mid-density EEG (hdEEG, mdEEG); however, it is questionable for widely used low-density EEG (ldEEG) because of inadequate surface sampling. Here, using simulations, we investigate the performance of the two source FC methods, the inverse-based source FC (ISFC) and the cortical partial coherence (CPC). To examine the effects of localization errors of the inverse method on the FC estimation, we simulated an oscillatory source with varying locations and SNRs. To compare the FC estimations by the two methods, we simulated two synchronized sources with varying between-source distance and SNR. The simulations were implemented for hdEEG, mdEEG, and ldEEG. We showed that the performance of both methods deteriorates for deep sources owing to their inaccurate localization and smoothing. The accuracy of both methods improves with the increasing between-source distance. The best ISFC performance was achieved using hd/mdEEG, while the best CPC performance was observed with ldEEG. In conclusion, with hdEEG, ISFC outperforms CPC and therefore should be the preferred method. In the studies based on ldEEG, the CPC is a method of choice. PMID:28727750

Seventy-meter antenna performance predictions: GTD analysis compared with traditional ray-tracing methods

NASA Technical Reports Server (NTRS)

Schredder, J. M.

1988-01-01

A comparative analysis was performed, using both the Geometrical Theory of Diffraction (GTD) and traditional pathlength error analysis techniques, for predicting RF antenna gain performance and pointing corrections. The NASA/JPL 70 meter antenna with its shaped surface was analyzed for gravity loading over the range of elevation angles. Also analyzed were the effects of lateral and axial displacements of the subreflector. Significant differences were noted between the predictions of the two methods, in the effect of subreflector displacements, and in the optimal subreflector positions to focus a gravity-deformed main reflector. The results are of relevance to future design procedure.

A simplified method in comparison with comprehensive interaction incremental dynamic analysis to assess seismic performance of jacket-type offshore platforms

NASA Astrophysics Data System (ADS)

Zolfaghari, M. R.; Ajamy, A.; Asgarian, B.

2015-12-01

The primary goal of seismic reassessment procedures in oil platform codes is to determine the reliability of a platform under extreme earthquake loading. Therefore, in this paper, a simplified method is proposed to assess seismic performance of existing jacket-type offshore platforms (JTOP) in regions ranging from near-elastic to global collapse. The simplified method curve exploits well agreement between static pushover (SPO) curve and the entire summarized interaction incremental dynamic analysis (CI-IDA) curve of the platform. Although the CI-IDA method offers better understanding and better modelling of the phenomenon, it is a time-consuming and challenging task. To overcome the challenges, the simplified procedure, a fast and accurate approach, is introduced based on SPO analysis. Then, an existing JTOP in the Persian Gulf is presented to illustrate the procedure, and finally a comparison is made between the simplified method and CI-IDA results. The simplified method is very informative and practical for current engineering purposes. It is able to predict seismic performance elasticity to global dynamic instability with reasonable accuracy and little computational effort.

NAA For Human Serum Analysis: Comparison With Conventional Analyses

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

Oliveira, Laura C.; Zamboni, Cibele B.; Medeiros, Jose A. G.

2010-08-04

Instrumental and Comparator methods of Neutron Activation Analysis (NAA) were applied to determine elements of clinical relevancy in serum samples of adult population (Sao Paulo city, Brazil). A comparison with the conventional analyses, Colorimetric for calcium, Titrymetric for chlorine and Ion Specific Electrode for sodium and potassium determination were also performed permitting a discussion about the performance of NAA methods for clinical chemistry research.

An Excel‐based implementation of the spectral method of action potential alternans analysis

PubMed Central

Pearman, Charles M.

2014-01-01

Abstract Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro‐arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T‐wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. PMID:25501439

How Is Wilson Disease Inherited?

MedlinePlus

... ATP7B gene have been identified thus far. Testing Methods Available Linkage analysis (Haplotype analysis) Molecular genetic testing ... genetic counselor who can carefully discuss the best method of testing to perform and the benefits, limitations, ...

Testing an automated method to estimate ground-water recharge from streamflow records

USGS Publications Warehouse

Rutledge, A.T.; Daniel, C.C.

1994-01-01

The computer program, RORA, allows automated analysis of streamflow hydrographs to estimate ground-water recharge. Output from the program, which is based on the recession-curve-displacement method (often referred to as the Rorabaugh method, for whom the program is named), was compared to estimates of recharge obtained from a manual analysis of 156 years of streamflow record from 15 streamflow-gaging stations in the eastern United States. Statistical tests showed that there was no significant difference between paired estimates of annual recharge by the two methods. Tests of results produced by the four workers who performed the manual method showed that results can differ significantly between workers. Twenty-two percent of the variation between manual and automated estimates could be attributed to having different workers perform the manual method. The program RORA will produce estimates of recharge equivalent to estimates produced manually, greatly increase the speed od analysis, and reduce the subjectivity inherent in manual analysis.

Parameters Estimation For A Patellofemoral Joint Of A Human Knee Using A Vector Method

NASA Astrophysics Data System (ADS)

Ciszkiewicz, A.; Knapczyk, J.

2015-08-01

Position and displacement analysis of a spherical model of a human knee joint using the vector method was presented. Sensitivity analysis and parameter estimation were performed using the evolutionary algorithm method. Computer simulations for the mechanism with estimated parameters proved the effectiveness of the prepared software. The method itself can be useful when solving problems concerning the displacement and loads analysis in the knee joint.

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Quantitative Determination of Cannabinoids in Cannabis and Cannabis Products Using Ultra-High-Performance Supercritical Fluid Chromatography and Diode Array/Mass Spectrometric Detection.

PubMed

Wang, Mei; Wang, Yan-Hong; Avula, Bharathi; Radwan, Mohamed M; Wanas, Amira S; Mehmedic, Zlatko; van Antwerp, John; ElSohly, Mahmoud A; Khan, Ikhlas A

2017-05-01

Ultra-high-performance supercritical fluid chromatography (UHPSFC) is an efficient analytical technique and has not been fully employed for the analysis of cannabis. Here, a novel method was developed for the analysis of 30 cannabis plant extracts and preparations using UHPSFC/PDA-MS. Nine of the most abundant cannabinoids, viz. CBD, ∆ 8 -THC, THCV, ∆ 9 -THC, CBN, CBG, THCA-A, CBDA, and CBGA, were quantitatively determined (RSDs < 6.9%). Unlike GC methods, no derivatization or decarboxylation was required prior to UHPSFC analysis. The UHPSFC chromatographic separation of cannabinoids displayed an inverse elution order compared to UHPLC. Combining with PDA-MS, this orthogonality is valuable for discrimination of cannabinoids in complex matrices. The developed method was validated, and the quantification results were compared with a standard UHPLC method. The RSDs of these two methods were within ±13.0%. Finally, chemometric analysis including principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to differentiate between cannabis samples. © 2016 American Academy of Forensic Sciences.

Advancing our thinking in presence-only and used-available analysis.

PubMed

Warton, David; Aarts, Geert

2013-11-01

1. The problems of analysing used-available data and presence-only data are equivalent, and this paper uses this equivalence as a platform for exploring opportunities for advancing analysis methodology. 2. We suggest some potential methodological advances in used-available analysis, made possible via lessons learnt in the presence-only literature, for example, using modern methods to improve predictive performance. We also consider the converse - potential advances in presence-only analysis inspired by used-available methodology. 3. Notwithstanding these potential advances in methodology, perhaps a greater opportunity is in advancing our thinking about how to apply a given method to a particular data set. 4. It is shown by example that strikingly different results can be achieved for a single data set by applying a given method of analysis in different ways - hence having chosen a method of analysis, the next step of working out how to apply it is critical to performance. 5. We review some key issues to consider in deciding how to apply an analysis method: apply the method in a manner that reflects the study design; consider data properties; and use diagnostic tools to assess how reasonable a given analysis is for the data at hand. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Fast and comprehensive analysis of secondary metabolites in cocoa products using ultra high-performance liquid chromatography directly after pressurized liquid extraction.

PubMed

Damm, Irina; Enger, Eileen; Chrubasik-Hausmann, Sigrun; Schieber, Andreas; Zimmermann, Benno F

2016-08-01

Fast methods for the extraction and analysis of various secondary metabolites from cocoa products were developed and optimized regarding speed and separation efficiency. Extraction by pressurized liquid extraction is automated and the extracts are analyzed by rapid reversed-phase ultra high-performance liquid chromatography and normal-phase high-performance liquid chromatography methods. After extraction, no further sample treatment is required before chromatographic analysis. The analytes comprise monomeric and oligomeric flavanols, flavonols, methylxanthins, N-phenylpropenoyl amino acids, and phenolic acids. Polyphenols and N-phenylpropenoyl amino acids are separated in a single run of 33 min, procyanidins are analyzed by normal-phase high-performance liquid chromatography within 16 min, and methylxanthins require only 6 min total run time. A fourth method is suitable for phenolic acids, but only protocatechuic acid was found in relevant quantities. The optimized methods were validated and applied to 27 dark chocolates, one milk chocolate, two cocoa powders and two food supplements based on cocoa extract. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Performance analysis of the ascent propulsion system of the Apollo spacecraft

NASA Technical Reports Server (NTRS)

Hooper, J. C., III

1973-01-01

Activities involved in the performance analysis of the Apollo lunar module ascent propulsion system are discussed. A description of the ascent propulsion system, including hardware, instrumentation, and system characteristics, is included. The methods used to predict the inflight performance and to establish performance uncertainties of the ascent propulsion system are discussed. The techniques of processing the telemetered flight data and performing postflight performance reconstruction to determine actual inflight performance are discussed. Problems that have been encountered and results from the analysis of the ascent propulsion system performance during the Apollo 9, 10, and 11 missions are presented.

Psychoactive Substance Use and School Performance among Adolescents in Public Secondary Schools in Uganda

ERIC Educational Resources Information Center

Rukundo, Aloysius; Kibanja, Grace; Steffens, Karl

2014-01-01

Introduction: Psychoactive substance use among adolescents influences behavioral and cognitive processes and is associated with adolescents' performance in school. We therefore sought to investigate association of PASU with adolescents' school performance. Methods: We employed quantitative methods of data collection and analysis. To test the…

A Self-Directed Method for Cell-Type Identification and Separation of Gene Expression Microarrays

PubMed Central

Zuckerman, Neta S.; Noam, Yair; Goldsmith, Andrea J.; Lee, Peter P.

2013-01-01

Gene expression analysis is generally performed on heterogeneous tissue samples consisting of multiple cell types. Current methods developed to separate heterogeneous gene expression rely on prior knowledge of the cell-type composition and/or signatures - these are not available in most public datasets. We present a novel method to identify the cell-type composition, signatures and proportions per sample without need for a-priori information. The method was successfully tested on controlled and semi-controlled datasets and performed as accurately as current methods that do require additional information. As such, this method enables the analysis of cell-type specific gene expression using existing large pools of publically available microarray datasets. PMID:23990767

Free wake analysis of hover performance using a new influence coefficient method

NASA Technical Reports Server (NTRS)

Quackenbush, Todd R.; Bliss, Donald B.; Ong, Ching Cho; Ching, Cho Ong

1990-01-01

A new approach to the prediction of helicopter rotor performance using a free wake analysis was developed. This new method uses a relaxation process that does not suffer from the convergence problems associated with previous time marching simulations. This wake relaxation procedure was coupled to a vortex-lattice, lifting surface loads analysis to produce a novel, self contained performance prediction code: EHPIC (Evaluation of Helicopter Performance using Influence Coefficients). The major technical features of the EHPIC code are described and a substantial amount of background information on the capabilities and proper operation of the code is supplied. Sample problems were undertaken to demonstrate the robustness and flexibility of the basic approach. Also, a performance correlation study was carried out to establish the breadth of applicability of the code, with very favorable results.

An Analysis of Effects of Variable Factors on Weapon Performance

DTIC Science & Technology

1993-03-01

ALTERNATIVE ANALYSIS A. CATEGORICAL DATA ANALYSIS Statistical methodology for categorical data analysis traces its roots to the work of Francis Galton in the...choice of statistical tests . This thesis examines an analysis performed by Surface Warfare Development Group (SWDG). The SWDG analysis is shown to be...incorrect due to the misapplication of testing methods. A corrected analysis is presented and recommendations suggested for changes to the testing

A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data.

PubMed

Li, Xiaohong; Brock, Guy N; Rouchka, Eric C; Cooper, Nigel G F; Wu, Dongfeng; O'Toole, Timothy E; Gill, Ryan S; Eteleeb, Abdallah M; O'Brien, Liz; Rai, Shesh N

2017-01-01

Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read count variability that affects the overall sensitivity and specificity. In order to properly determine the most appropriate normalization methods, it is critical to compare the performance and shortcomings of a representative set of normalization routines based on different dataset characteristics. Therefore, we set out to evaluate the performance of the commonly used methods (DESeq, TMM-edgeR, FPKM-CuffDiff, TC, Med UQ and FQ) and two new methods we propose: Med-pgQ2 and UQ-pgQ2 (per-gene normalization after per-sample median or upper-quartile global scaling). Our per-gene normalization approach allows for comparisons between conditions based on similar count levels. Using the benchmark Microarray Quality Control Project (MAQC) and simulated datasets, we performed differential gene expression analysis to evaluate these methods. When evaluating MAQC2 with two replicates, we observed that Med-pgQ2 and UQ-pgQ2 achieved a slightly higher area under the Receiver Operating Characteristic Curve (AUC), a specificity rate > 85%, the detection power > 92% and an actual false discovery rate (FDR) under 0.06 given the nominal FDR (≤0.05). Although the top commonly used methods (DESeq and TMM-edgeR) yield a higher power (>93%) for MAQC2 data, they trade off with a reduced specificity (<70%) and a slightly higher actual FDR than our proposed methods. In addition, the results from an analysis based on the qualitative characteristics of sample distribution for MAQC2 and human breast cancer datasets show that only our gene-wise normalization methods corrected data skewed towards lower read counts. However, when we evaluated MAQC3 with less variation in five replicates, all methods performed similarly. Thus, our proposed Med-pgQ2 and UQ-pgQ2 methods perform slightly better for differential gene analysis of RNA-seq data skewed towards lowly expressed read counts with high variation by improving specificity while maintaining a good detection power with a control of the nominal FDR level.

A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data

PubMed Central

Li, Xiaohong; Brock, Guy N.; Rouchka, Eric C.; Cooper, Nigel G. F.; Wu, Dongfeng; O’Toole, Timothy E.; Gill, Ryan S.; Eteleeb, Abdallah M.; O’Brien, Liz

2017-01-01

Normalization is an essential step with considerable impact on high-throughput RNA sequencing (RNA-seq) data analysis. Although there are numerous methods for read count normalization, it remains a challenge to choose an optimal method due to multiple factors contributing to read count variability that affects the overall sensitivity and specificity. In order to properly determine the most appropriate normalization methods, it is critical to compare the performance and shortcomings of a representative set of normalization routines based on different dataset characteristics. Therefore, we set out to evaluate the performance of the commonly used methods (DESeq, TMM-edgeR, FPKM-CuffDiff, TC, Med UQ and FQ) and two new methods we propose: Med-pgQ2 and UQ-pgQ2 (per-gene normalization after per-sample median or upper-quartile global scaling). Our per-gene normalization approach allows for comparisons between conditions based on similar count levels. Using the benchmark Microarray Quality Control Project (MAQC) and simulated datasets, we performed differential gene expression analysis to evaluate these methods. When evaluating MAQC2 with two replicates, we observed that Med-pgQ2 and UQ-pgQ2 achieved a slightly higher area under the Receiver Operating Characteristic Curve (AUC), a specificity rate > 85%, the detection power > 92% and an actual false discovery rate (FDR) under 0.06 given the nominal FDR (≤0.05). Although the top commonly used methods (DESeq and TMM-edgeR) yield a higher power (>93%) for MAQC2 data, they trade off with a reduced specificity (<70%) and a slightly higher actual FDR than our proposed methods. In addition, the results from an analysis based on the qualitative characteristics of sample distribution for MAQC2 and human breast cancer datasets show that only our gene-wise normalization methods corrected data skewed towards lower read counts. However, when we evaluated MAQC3 with less variation in five replicates, all methods performed similarly. Thus, our proposed Med-pgQ2 and UQ-pgQ2 methods perform slightly better for differential gene analysis of RNA-seq data skewed towards lowly expressed read counts with high variation by improving specificity while maintaining a good detection power with a control of the nominal FDR level. PMID:28459823

Fast and simultaneous determination of 12 polyphenols in apple peel and pulp by using chemometrics-assisted high-performance liquid chromatography with diode array detection.

PubMed

Wang, Tong; Wu, Hai-Long; Xie, Li-Xia; Zhu, Li; Liu, Zhi; Sun, Xiao-Dong; Xiao, Rong; Yu, Ru-Qin

2017-04-01

In this work, a smart chemometrics-enhanced strategy, high-performance liquid chromatography, and diode array detection coupled with second-order calibration method based on alternating trilinear decomposition algorithm was proposed to simultaneously quantify 12 polyphenols in different kinds of apple peel and pulp samples. The proposed strategy proved to be a powerful tool to solve the problems of coelution, unknown interferences, and chromatographic shifts in the process of high-performance liquid chromatography analysis, making it possible for the determination of 12 polyphenols in complex apple matrices within 10 min under simple conditions of elution. The average recoveries with standard deviations, and figures of merit including sensitivity, selectivity, limit of detection, and limit of quantitation were calculated to validate the accuracy of the proposed method. Compared to the quantitative analysis results from the classic high-performance liquid chromatography method, the statistical and graphical analysis showed that our proposed strategy obtained more reliable results. All results indicated that our proposed method used in the quantitative analysis of apple polyphenols was an accurate, fast, universal, simple, and green one, and it was expected to be developed as an attractive alternative method for simultaneous determination of multitargeted analytes in complex matrices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Design and analysis of tubular permanent magnet linear generator for small-scale wave energy converter

NASA Astrophysics Data System (ADS)

Kim, Jeong-Man; Koo, Min-Mo; Jeong, Jae-Hoon; Hong, Keyyong; Cho, Il-Hyoung; Choi, Jang-Young

2017-05-01

This paper reports the design and analysis of a tubular permanent magnet linear generator (TPMLG) for a small-scale wave-energy converter. The analytical field computation is performed by applying a magnetic vector potential and a 2-D analytical model to determine design parameters. Based on analytical solutions, parametric analysis is performed to meet the design specifications of a wave-energy converter (WEC). Then, 2-D FEA is employed to validate the analytical method. Finally, the experimental result confirms the predictions of the analytical and finite element analysis (FEA) methods under regular and irregular wave conditions.

A method to evaluate performance reliability of individual subjects in laboratory research applied to work settings.

DOT National Transportation Integrated Search

1978-10-01

This report presents a method that may be used to evaluate the reliability of performance of individual subjects, particularly in applied laboratory research. The method is based on analysis of variance of a tasks-by-subjects data matrix, with all sc...

Planning for Downtown Circulation Systems. Volume 2. Analysis Techniques.

DOT National Transportation Integrated Search

1983-10-01

This volume contains the analysis and refinement stages of downtown circulator planning. Included are sections on methods for estimating patronage, costs, revenues, and impacts, and a section on methods for performing micro-level analyses.

Using Importance-Performance Analysis To Evaluate Teaching Effectiveness.

ERIC Educational Resources Information Center

Attarian, Aram

This paper introduces Importance-Performance (IP) analysis as a method to evaluate teaching effectiveness in a university outdoor program. Originally developed for use in the field of marketing, IP analysis is simple and easy to administer, and provides the instructor with a visual representation of what teaching attributes are important, how…

Supervised DNA Barcodes species classification: analysis, comparisons and results

PubMed Central

2014-01-01

Background Specific fragments, coming from short portions of DNA (e.g., mitochondrial, nuclear, and plastid sequences), have been defined as DNA Barcode and can be used as markers for organisms of the main life kingdoms. Species classification with DNA Barcode sequences has been proven effective on different organisms. Indeed, specific gene regions have been identified as Barcode: COI in animals, rbcL and matK in plants, and ITS in fungi. The classification problem assigns an unknown specimen to a known species by analyzing its Barcode. This task has to be supported with reliable methods and algorithms. Methods In this work the efficacy of supervised machine learning methods to classify species with DNA Barcode sequences is shown. The Weka software suite, which includes a collection of supervised classification methods, is adopted to address the task of DNA Barcode analysis. Classifier families are tested on synthetic and empirical datasets belonging to the animal, fungus, and plant kingdoms. In particular, the function-based method Support Vector Machines (SVM), the rule-based RIPPER, the decision tree C4.5, and the Naïve Bayes method are considered. Additionally, the classification results are compared with respect to ad-hoc and well-established DNA Barcode classification methods. Results A software that converts the DNA Barcode FASTA sequences to the Weka format is released, to adapt different input formats and to allow the execution of the classification procedure. The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model. Rule-based methods have slightly inferior classification performances, but deliver the species specific positions and nucleotide assignments. On synthetic data the supervised machine learning methods obtain superior classification performances with respect to the traditional DNA Barcode classification methods. On empirical data their classification performances are at a comparable level to the other methods. Conclusions The classification analysis shows that supervised machine learning methods are promising candidates for handling with success the DNA Barcoding species classification problem, obtaining excellent performances. To conclude, a powerful tool to perform species identification is now available to the DNA Barcoding community. PMID:24721333

Development of an automated analysis system for data from flow cytometric intracellular cytokine staining assays from clinical vaccine trials

PubMed Central

Shulman, Nick; Bellew, Matthew; Snelling, George; Carter, Donald; Huang, Yunda; Li, Hongli; Self, Steven G.; McElrath, M. Juliana; De Rosa, Stephen C.

2008-01-01

Background Intracellular cytokine staining (ICS) by multiparameter flow cytometry is one of the primary methods for determining T cell immunogenicity in HIV-1 clinical vaccine trials. Data analysis requires considerable expertise and time. The amount of data is quickly increasing as more and larger trials are performed, and thus there is a critical need for high throughput methods of data analysis. Methods A web based flow cytometric analysis system, LabKey Flow, was developed for analyses of data from standardized ICS assays. A gating template was created manually in commercially-available flow cytometric analysis software. Using this template, the system automatically compensated and analyzed all data sets. Quality control queries were designed to identify potentially incorrect sample collections. Results Comparison of the semi-automated analysis performed by LabKey Flow and the manual analysis performed using FlowJo software demonstrated excellent concordance (concordance correlation coefficient >0.990). Manual inspection of the analyses performed by LabKey Flow for 8-color ICS data files from several clinical vaccine trials indicates that template gates can appropriately be used for most data sets. Conclusions The semi-automated LabKey Flow analysis system can analyze accurately large ICS data files. Routine use of the system does not require specialized expertise. This high-throughput analysis will provide great utility for rapid evaluation of complex multiparameter flow cytometric measurements collected from large clinical trials. PMID:18615598

Towards scar-free surgery: An analysis of the increasing complexity from laparoscopic surgery to NOTES

PubMed Central

Chellali, Amine; Schwaitzberg, Steven D.; Jones, Daniel B.; Romanelli, John; Miller, Amie; Rattner, David; Roberts, Kurt E.; Cao, Caroline G.L.

2014-01-01

Background NOTES is an emerging technique for performing surgical procedures, such as cholecystectomy. Debate about its real benefit over the traditional laparoscopic technique is on-going. There have been several clinical studies comparing NOTES to conventional laparoscopic surgery. However, no work has been done to compare these techniques from a Human Factors perspective. This study presents a systematic analysis describing and comparing different existing NOTES methods to laparoscopic cholecystectomy. Methods Videos of endoscopic/laparoscopic views from fifteen live cholecystectomies were analyzed to conduct a detailed task analysis of the NOTES technique. A hierarchical task analysis of laparoscopic cholecystectomy and several hybrid transvaginal NOTES cholecystectomies was performed and validated by expert surgeons. To identify similarities and differences between these techniques, their hierarchical decomposition trees were compared. Finally, a timeline analysis was conducted to compare the steps and substeps. Results At least three variations of the NOTES technique were used for cholecystectomy. Differences between the observed techniques at the substep level of hierarchy and on the instruments being used were found. The timeline analysis showed an increase in time to perform some surgical steps and substeps in NOTES compared to laparoscopic cholecystectomy. Conclusion As pure NOTES is extremely difficult given the current state of development in instrumentation design, most surgeons utilize different hybrid methods – combination of endoscopic and laparoscopic instruments/optics. Results of our hierarchical task analysis yielded an identification of three different hybrid methods to perform cholecystectomy with significant variability amongst them. The varying degrees to which laparoscopic instruments are utilized to assist in NOTES methods appear to introduce different technical issues and additional tasks leading to an increase in the surgical time. The NOTES continuum of invasiveness is proposed here as a classification scheme for these methods, which was used to construct a clear roadmap for training and technology development. PMID:24902811

A systematic evaluation of normalization methods in quantitative label-free proteomics.

PubMed

Välikangas, Tommi; Suomi, Tomi; Elo, Laura L

2018-01-01

To date, mass spectrometry (MS) data remain inherently biased as a result of reasons ranging from sample handling to differences caused by the instrumentation. Normalization is the process that aims to account for the bias and make samples more comparable. The selection of a proper normalization method is a pivotal task for the reliability of the downstream analysis and results. Many normalization methods commonly used in proteomics have been adapted from the DNA microarray techniques. Previous studies comparing normalization methods in proteomics have focused mainly on intragroup variation. In this study, several popular and widely used normalization methods representing different strategies in normalization are evaluated using three spike-in and one experimental mouse label-free proteomic data sets. The normalization methods are evaluated in terms of their ability to reduce variation between technical replicates, their effect on differential expression analysis and their effect on the estimation of logarithmic fold changes. Additionally, we examined whether normalizing the whole data globally or in segments for the differential expression analysis has an effect on the performance of the normalization methods. We found that variance stabilization normalization (Vsn) reduced variation the most between technical replicates in all examined data sets. Vsn also performed consistently well in the differential expression analysis. Linear regression normalization and local regression normalization performed also systematically well. Finally, we discuss the choice of a normalization method and some qualities of a suitable normalization method in the light of the results of our evaluation. © The Author 2016. Published by Oxford University Press.

Chromatographic fingerprint analysis of yohimbe bark and related dietary supplements using UHPLC/UV/MS.

PubMed

Sun, Jianghao; Chen, Pei

2012-03-05

A practical ultra high-performance liquid chromatography (UHPLC) method was developed for fingerprint analysis of and determination of yohimbine in yohimbe barks and related dietary supplements. Good separation was achieved using a Waters Acquity BEH C(18) column with gradient elution using 0.1% (v/v) aqueous ammonium hydroxide and 0.1% ammonium hydroxide in methanol as the mobile phases. The study is the first reported chromatographic method that separates corynanthine from yohimbine in yohimbe bark extract. The chromatographic fingerprint analysis was applied to the analysis of 18 yohimbe commercial dietary supplement samples. Quantitation of yohimbine, the traditional method for analysis of yohimbe barks, were also performed to evaluate the results of the fingerprint analysis. Wide variability was observed in fingerprints and yohimbine content among yohimbe dietary supplement samples. For most of the dietary supplements, the yohimbine content was not consistent with the label claims. Copyright © 2011. Published by Elsevier B.V.

Dredged Material Analysis Tools; Performance of Acute and Chronic Sediment Toxicity Methods

DTIC Science & Technology

2008-07-01

Chronic Sediment Toxicity Methods Jeffery Steevens, Alan Kennedy, Daniel Farrar, Cory McNemar, Mark R. Reiss, Roy K. Kropp, Jon Doi, and Todd Bridges...Environmental Research Program ERDC/EL TR-08-16 July 2008 Revised Dredged Material Analysis Tools Performance of Acute and Chronic Sediment Toxicity ...insight into the potential advan- tages and disadvantages of using chronic sediment toxicity tests with relevant benthic macroinvertebrates as part of

Integrative Analysis of Prognosis Data on Multiple Cancer Subtypes

PubMed Central

Liu, Jin; Huang, Jian; Zhang, Yawei; Lan, Qing; Rothman, Nathaniel; Zheng, Tongzhang; Ma, Shuangge

2014-01-01

Summary In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is diverse. Examining the similarity and difference in the genetic basis of multiple subtypes of the same cancer can lead to a better understanding of their connections and distinctions. Classic meta-analysis methods analyze each subtype separately and then compare analysis results across subtypes. Integrative analysis methods, in contrast, analyze the raw data on multiple subtypes simultaneously and can outperform meta-analysis methods. In this study, prognosis data on multiple subtypes of the same cancer are analyzed. An AFT (accelerated failure time) model is adopted to describe survival. The genetic basis of multiple subtypes is described using the heterogeneity model, which allows a gene/SNP to be associated with prognosis of some subtypes but not others. A compound penalization method is developed to identify genes that contain important SNPs associated with prognosis. The proposed method has an intuitive formulation and is realized using an iterative algorithm. Asymptotic properties are rigorously established. Simulation shows that the proposed method has satisfactory performance and outperforms a penalization-based meta-analysis method and a regularized thresholding method. An NHL (non-Hodgkin lymphoma) prognosis study with SNP measurements is analyzed. Genes associated with the three major subtypes, namely DLBCL, FL, and CLL/SLL, are identified. The proposed method identifies genes that are different from alternatives and have important implications and satisfactory prediction performance. PMID:24766212

Development of a probabilistic analysis methodology for structural reliability estimation

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.

1991-01-01

The novel probabilistic analysis method for assessment of structural reliability presented, which combines fast-convolution with an efficient structural reliability analysis, can after identifying the most important point of a limit state proceed to establish a quadratic-performance function. It then transforms the quadratic function into a linear one, and applies fast convolution. The method is applicable to problems requiring computer-intensive structural analysis. Five illustrative examples of the method's application are given.

How to Compare the Security Quality Requirements Engineering (SQUARE) Method with Other Methods

DTIC Science & Technology

2007-08-01

Attack Trees for Modeling and Analysis 10 2.8 Misuse and Abuse Cases 10 2.9 Formal Methods 11 2.9.1 Software Cost Reduction 12 2.9.2 Common...modern or efficient techniques. • Requirements analysis typically is either not performed at all (identified requirements are directly specified without...any analysis or modeling) or analysis is restricted to functional re- quirements and ignores quality requirements, other nonfunctional requirements

How to begin a new topic in mathematics: does it matter to students' performance in mathematics?

PubMed

Ma, Xin; Papanastasiou, Constantinos

2006-08-01

The authors use Canadian data from the Third International Mathematics and Science Study to examine six instructional methods that mathematics teachers use to introduce new topics in mathematics on performance of eighth-grade students in six mathematical areas (mathematics as a whole, algebra, data analysis, fraction, geometry, and measurement). Results of multilevel analysis with students nested within schools show that the instructional methods of having the teacher explain the rules and definitions and looking at the textbook while the teacher talks about it had little instructional effects on student performance in any mathematical area. In contrast, the instructional method in which teachers try to solve an example related to the new topic was effective in promoting student performance across all mathematical areas.

[Enzymatic analysis of the quality of foodstuffs].

PubMed

Kolesnov, A Iu

1997-01-01

Enzymatic analysis is an independent and separate branch of enzymology and analytical chemistry. It has become one of the most important methodologies used in food analysis. Enzymatic analysis allows the quick, reliable determination of many food ingredients. Often these contents cannot be determined by conventional methods, or if methods are available, they are determined only with limited accuracy. Today, methods of enzymatic analysis are being increasingly used in the investigation of foodstuffs. Enzymatic measurement techniques are used in industry, scientific and food inspection laboratories for quality analysis. This article describes the requirements of an optimal analytical method: specificity, sample preparation, assay performance, precision, sensitivity, time requirement, analysis cost, safety of reagents.

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline

PubMed Central

2013-01-01

Background As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. Results We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS A : DE genes with non-zero effect sizes in all studies, (2) HS B : DE genes with non-zero effect sizes in one or more studies and (3) HS r : DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. Conclusions The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS A , HS B , and HS r ). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author’s publication website. PMID:24359104

Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline.

PubMed

Chang, Lun-Ching; Lin, Hui-Min; Sibille, Etienne; Tseng, George C

2013-12-21

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations. We performed 12 microarray meta-analysis methods for combining multiple simulated expression profiles, and such methods can be categorized for different hypothesis setting purposes: (1) HS(A): DE genes with non-zero effect sizes in all studies, (2) HS(B): DE genes with non-zero effect sizes in one or more studies and (3) HS(r): DE gene with non-zero effect in "majority" of studies. We then performed a comprehensive comparative analysis through six large-scale real applications using four quantitative statistical evaluation criteria: detection capability, biological association, stability and robustness. We elucidated hypothesis settings behind the methods and further apply multi-dimensional scaling (MDS) and an entropy measure to characterize the meta-analysis methods and data structure, respectively. The aggregated results from the simulation study categorized the 12 methods into three hypothesis settings (HS(A), HS(B), and HS(r)). Evaluation in real data and results from MDS and entropy analyses provided an insightful and practical guideline to the choice of the most suitable method in a given application. All source files for simulation and real data are available on the author's publication website.

Analysis of high vacuum systems using SINDA'85

NASA Technical Reports Server (NTRS)

Spivey, R. A.; Clanton, S. E.; Moore, J. D.

1993-01-01

The theory, algorithms, and test data correlation analysis of a math model developed to predict performance of the Space Station Freedom Vacuum Exhaust System are presented. The theory used to predict the flow characteristics of viscous, transition, and molecular flow is presented in detail. Development of user subroutines which predict the flow characteristics in conjunction with the SINDA'85/FLUINT analysis software are discussed. The resistance-capacitance network approach with application to vacuum system analysis is demonstrated and results from the model are correlated with test data. The model was developed to predict the performance of the Space Station Freedom Vacuum Exhaust System. However, the unique use of the user subroutines developed in this model and written into the SINDA'85/FLUINT thermal analysis model provides a powerful tool that can be used to predict the transient performance of vacuum systems and gas flow in tubes of virtually any geometry. This can be accomplished using a resistance-capacitance (R-C) method very similar to the methods used to perform thermal analyses.

Macro elemental analysis of food samples by nuclear analytical technique

NASA Astrophysics Data System (ADS)

Syahfitri, W. Y. N.; Kurniawati, S.; Adventini, N.; Damastuti, E.; Lestiani, D. D.

2017-06-01

Energy-dispersive X-ray fluorescence (EDXRF) spectrometry is a non-destructive, rapid, multi elemental, accurate, and environment friendly analysis compared with other detection methods. Thus, EDXRF spectrometry is applicable for food inspection. The macro elements calcium and potassium constitute important nutrients required by the human body for optimal physiological functions. Therefore, the determination of Ca and K content in various foods needs to be done. The aim of this work is to demonstrate the applicability of EDXRF for food analysis. The analytical performance of non-destructive EDXRF was compared with other analytical techniques; neutron activation analysis and atomic absorption spectrometry. Comparison of methods performed as cross checking results of the analysis and to overcome the limitations of the three methods. Analysis results showed that Ca found in food using EDXRF and AAS were not significantly different with p-value 0.9687, whereas p-value of K between EDXRF and NAA is 0.6575. The correlation between those results was also examined. The Pearson correlations for Ca and K were 0.9871 and 0.9558, respectively. Method validation using SRM NIST 1548a Typical Diet was also applied. The results showed good agreement between methods; therefore EDXRF method can be used as an alternative method for the determination of Ca and K in food samples.

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

Quality assessment of Herba Leonuri based on the analysis of multiple components using normal- and reversed-phase chromatographic methods.

PubMed

Dong, Shuya; He, Jiao; Hou, Huiping; Shuai, Yaping; Wang, Qi; Yang, Wenling; Sun, Zheng; Li, Qing; Bi, Kaishun; Liu, Ran

2017-12-01

A novel, improved, and comprehensive method for quality evaluation and discrimination of Herba Leonuri has been developed and validated based on normal- and reversed-phase chromatographic methods. To identify Herba Leonuri, normal- and reversed-phase high-performance thin-layer chromatography fingerprints were obtained by comparing the colors and R f values of the bands, and reversed-phase high-performance liquid chromatography fingerprints were obtained by using an Agilent Poroshell 120 SB-C18 within 28 min. By similarity analysis and hierarchical clustering analysis, we show that there are similar chromatographic patterns in Herba Leonuri samples, but significant differences in counterfeits and variants. To quantify the bio-active components of Herba Leonuri, reversed-phase high-performance liquid chromatography was performed to analyze syringate, leonurine, quercetin-3-O-robiniaglycoside, hyperoside, rutin, isoquercitrin, wogonin, and genkwanin simultaneously by single standard to determine multi-components method with rutin as internal standard. Meanwhile, normal-phase high-performance liquid chromatography was performed by using an Agilent ZORBAX HILIC Plus within 6 min to determine trigonelline and stachydrine using trigonelline as internal standard. Innovatively, among these compounds, bio-active components of quercetin-3-O-robiniaglycoside and trigonelline were first determined in Herba Leonuri. In general, the method integrating multi-chromatographic analyses offered an efficient way for the standardization and identification of Herba Leonuri. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Determining the Number of Factors in P-Technique Factor Analysis

ERIC Educational Resources Information Center

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

Enterprise architecture availability analysis using fault trees and stakeholder interviews

NASA Astrophysics Data System (ADS)

Närman, Per; Franke, Ulrik; König, Johan; Buschle, Markus; Ekstedt, Mathias

2014-01-01

The availability of enterprise information systems is a key concern for many organisations. This article describes a method for availability analysis based on Fault Tree Analysis and constructs from the ArchiMate enterprise architecture (EA) language. To test the quality of the method, several case-studies within the banking and electrical utility industries were performed. Input data were collected through stakeholder interviews. The results from the case studies were compared with availability of log data to determine the accuracy of the method's predictions. In the five cases where accurate log data were available, the yearly downtime estimates were within eight hours from the actual downtimes. The cost of performing the analysis was low; no case study required more than 20 man-hours of work, making the method ideal for practitioners with an interest in obtaining rapid availability estimates of their enterprise information systems.

High-performance equation solvers and their impact on finite element analysis

NASA Technical Reports Server (NTRS)

Poole, Eugene L.; Knight, Norman F., Jr.; Davis, D. Dale, Jr.

1990-01-01

The role of equation solvers in modern structural analysis software is described. Direct and iterative equation solvers which exploit vectorization on modern high-performance computer systems are described and compared. The direct solvers are two Cholesky factorization methods. The first method utilizes a novel variable-band data storage format to achieve very high computation rates and the second method uses a sparse data storage format designed to reduce the number of operations. The iterative solvers are preconditioned conjugate gradient methods. Two different preconditioners are included; the first uses a diagonal matrix storage scheme to achieve high computation rates and the second requires a sparse data storage scheme and converges to the solution in fewer iterations that the first. The impact of using all of the equation solvers in a common structural analysis software system is demonstrated by solving several representative structural analysis problems.

High-performance equation solvers and their impact on finite element analysis

NASA Technical Reports Server (NTRS)

Poole, Eugene L.; Knight, Norman F., Jr.; Davis, D. D., Jr.

1992-01-01

The role of equation solvers in modern structural analysis software is described. Direct and iterative equation solvers which exploit vectorization on modern high-performance computer systems are described and compared. The direct solvers are two Cholesky factorization methods. The first method utilizes a novel variable-band data storage format to achieve very high computation rates and the second method uses a sparse data storage format designed to reduce the number od operations. The iterative solvers are preconditioned conjugate gradient methods. Two different preconditioners are included; the first uses a diagonal matrix storage scheme to achieve high computation rates and the second requires a sparse data storage scheme and converges to the solution in fewer iterations that the first. The impact of using all of the equation solvers in a common structural analysis software system is demonstrated by solving several representative structural analysis problems.

Ascertainment bias from imputation methods evaluation in wheat.

PubMed

Brandariz, Sofía P; González Reymúndez, Agustín; Lado, Bettina; Malosetti, Marcos; Garcia, Antonio Augusto Franco; Quincke, Martín; von Zitzewitz, Jarislav; Castro, Marina; Matus, Iván; Del Pozo, Alejandro; Castro, Ariel J; Gutiérrez, Lucía

2016-10-04

Whole-genome genotyping techniques like Genotyping-by-sequencing (GBS) are being used for genetic studies such as Genome-Wide Association (GWAS) and Genomewide Selection (GS), where different strategies for imputation have been developed. Nevertheless, imputation error may lead to poor performance (i.e. smaller power or higher false positive rate) when complete data is not required as it is for GWAS, and each marker is taken at a time. The aim of this study was to compare the performance of GWAS analysis for Quantitative Trait Loci (QTL) of major and minor effect using different imputation methods when no reference panel is available in a wheat GBS panel. In this study, we compared the power and false positive rate of dissecting quantitative traits for imputed and not-imputed marker score matrices in: (1) a complete molecular marker barley panel array, and (2) a GBS wheat panel with missing data. We found that there is an ascertainment bias in imputation method comparisons. Simulating over a complete matrix and creating missing data at random proved that imputation methods have a poorer performance. Furthermore, we found that when QTL were simulated with imputed data, the imputation methods performed better than the not-imputed ones. On the other hand, when QTL were simulated with not-imputed data, the not-imputed method and one of the imputation methods performed better for dissecting quantitative traits. Moreover, larger differences between imputation methods were detected for QTL of major effect than QTL of minor effect. We also compared the different marker score matrices for GWAS analysis in a real wheat phenotype dataset, and we found minimal differences indicating that imputation did not improve the GWAS performance when a reference panel was not available. Poorer performance was found in GWAS analysis when an imputed marker score matrix was used, no reference panel is available, in a wheat GBS panel.

Modeling Canadian Quality Control Test Program for Steroid Hormone Receptors in Breast Cancer: Diagnostic Accuracy Study.

PubMed

Pérez, Teresa; Makrestsov, Nikita; Garatt, John; Torlakovic, Emina; Gilks, C Blake; Mallett, Susan

The Canadian Immunohistochemistry Quality Control program monitors clinical laboratory performance for estrogen receptor and progesterone receptor tests used in breast cancer treatment management in Canada. Current methods assess sensitivity and specificity at each time point, compared with a reference standard. We investigate alternative performance analysis methods to enhance the quality assessment. We used 3 methods of analysis: meta-analysis of sensitivity and specificity of each laboratory across all time points; sensitivity and specificity at each time point for each laboratory; and fitting models for repeated measurements to examine differences between laboratories adjusted by test and time point. Results show 88 laboratories participated in quality control at up to 13 time points using typically 37 to 54 histology samples. In meta-analysis across all time points no laboratories have sensitivity or specificity below 80%. Current methods, presenting sensitivity and specificity separately for each run, result in wide 95% confidence intervals, typically spanning 15% to 30%. Models of a single diagnostic outcome demonstrated that 82% to 100% of laboratories had no difference to reference standard for estrogen receptor and 75% to 100% for progesterone receptor, with the exception of 1 progesterone receptor run. Laboratories with significant differences to reference standard identified with Generalized Estimating Equation modeling also have reduced performance by meta-analysis across all time points. The Canadian Immunohistochemistry Quality Control program has a good design, and with this modeling approach has sufficient precision to measure performance at each time point and allow laboratories with a significantly lower performance to be targeted for advice.

Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Hearn, Tristan; Hendricks, Eric; Chin, Jeffrey; Gray, Justin; Moore, Kenneth T.

2016-01-01

A new engine cycle analysis tool, called Pycycle, was recently built using the OpenMDAO framework. This tool uses equilibrium chemistry based thermodynamics, and provides analytic derivatives. This allows for stable and efficient use of gradient-based optimization and sensitivity analysis methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a multi-point turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.

Development of new methodologies for evaluating the energy performance of new commercial buildings

NASA Astrophysics Data System (ADS)

Song, Suwon

The concept of Measurement and Verification (M&V) of a new building continues to become more important because efficient design alone is often not sufficient to deliver an efficient building. Simulation models that are calibrated to measured data can be used to evaluate the energy performance of new buildings if they are compared to energy baselines such as similar buildings, energy codes, and design standards. Unfortunately, there is a lack of detailed M&V methods and analysis methods to measure energy savings from new buildings that would have hypothetical energy baselines. Therefore, this study developed and demonstrated several new methodologies for evaluating the energy performance of new commercial buildings using a case-study building in Austin, Texas. First, three new M&V methods were developed to enhance the previous generic M&V framework for new buildings, including: (1) The development of a method to synthesize weather-normalized cooling energy use from a correlation of Motor Control Center (MCC) electricity use when chilled water use is unavailable, (2) The development of an improved method to analyze measured solar transmittance against incidence angle for sample glazing using different solar sensor types, including Eppley PSP and Li-Cor sensors, and (3) The development of an improved method to analyze chiller efficiency and operation at part-load conditions. Second, three new calibration methods were developed and analyzed, including: (1) A new percentile analysis added to the previous signature method for use with a DOE-2 calibration, (2) A new analysis to account for undocumented exhaust air in DOE-2 calibration, and (3) An analysis of the impact of synthesized direct normal solar radiation using the Erbs correlation on DOE-2 simulation. Third, an analysis of the actual energy savings compared to three different energy baselines was performed, including: (1) Energy Use Index (EUI) comparisons with sub-metered data, (2) New comparisons against Standards 90.1-1989 and 90.1-2001, and (3) A new evaluation of the performance of selected Energy Conservation Design Measures (ECDMs). Finally, potential energy savings were also simulated from selected improvements, including: minimum supply air flow, undocumented exhaust air, and daylighting.

Analysis of free modeling predictions by RBO aleph in CASP11.

PubMed

Mabrouk, Mahmoud; Werner, Tim; Schneider, Michael; Putz, Ines; Brock, Oliver

2016-09-01

The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue-residue contact prediction by EPC-map and contact-guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. Proteins 2016; 84(Suppl 1):87-104. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Airbreathing hypersonic vehicle design and analysis methods

NASA Technical Reports Server (NTRS)

Lockwood, Mary Kae; Petley, Dennis H.; Hunt, James L.; Martin, John G.

1996-01-01

The design, analysis, and optimization of airbreathing hypersonic vehicles requires analyses involving many highly coupled disciplines at levels of accuracy exceeding those traditionally considered in a conceptual or preliminary-level design. Discipline analysis methods including propulsion, structures, thermal management, geometry, aerodynamics, performance, synthesis, sizing, closure, and cost are discussed. Also, the on-going integration of these methods into a working environment, known as HOLIST, is described.

Using Multilevel Analysis to Monitor Test Performance across Administrations. Research Report. ETS RR-14-29

ERIC Educational Resources Information Center

Wei, Youhua; Qu, Yanxuan

2014-01-01

For a testing program with frequent administrations, it is important to understand and monitor the stability and fluctuation of test performance across administrations. Different methods have been proposed for this purpose. This study explored the potential of using multilevel analysis to understand and monitor examinees' test performance across…

Further evidence for the increased power of LOD scores compared with nonparametric methods.

PubMed

Durner, M; Vieland, V J; Greenberg, D A

1999-01-01

In genetic analysis of diseases in which the underlying model is unknown, "model free" methods-such as affected sib pair (ASP) tests-are often preferred over LOD-score methods, although LOD-score methods under the correct or even approximately correct model are more powerful than ASP tests. However, there might be circumstances in which nonparametric methods will outperform LOD-score methods. Recently, Dizier et al. reported that, in some complex two-locus (2L) models, LOD-score methods with segregation analysis-derived parameters had less power to detect linkage than ASP tests. We investigated whether these particular models, in fact, represent a situation that ASP tests are more powerful than LOD scores. We simulated data according to the parameters specified by Dizier et al. and analyzed the data by using a (a) single locus (SL) LOD-score analysis performed twice, under a simple dominant and a recessive mode of inheritance (MOI), (b) ASP methods, and (c) nonparametric linkage (NPL) analysis. We show that SL analysis performed twice and corrected for the type I-error increase due to multiple testing yields almost as much linkage information as does an analysis under the correct 2L model and is more powerful than either the ASP method or the NPL method. We demonstrate that, even for complex genetic models, the most important condition for linkage analysis is that the assumed MOI at the disease locus being tested is approximately correct, not that the inheritance of the disease per se is correctly specified. In the analysis by Dizier et al., segregation analysis led to estimates of dominance parameters that were grossly misspecified for the locus tested in those models in which ASP tests appeared to be more powerful than LOD-score analyses.

Teacher Professionalism and Team Performance Pay: A Mixed Methods Study

ERIC Educational Resources Information Center

Wells, Pamela; Combs, Julie P.; Bustamante, Rebecca M.

2012-01-01

The purpose of this mixed methods research study was to explore teachers' perceptions of their professional behaviors when they worked in schools that awarded team performance pay. Teachers' archival responses from two questionnaires were analyzed using mixed methods data analysis techniques (Year 1, n = 368; Year 2, n = 649). Most teachers had…

Semi-supervised vibration-based classification and condition monitoring of compressors

NASA Astrophysics Data System (ADS)

Potočnik, Primož; Govekar, Edvard

2017-09-01

Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.

Algorithm Summary and Evaluation: Automatic Implementation of Ringdown Analysis for Electromechanical Mode Identification from Phasor Measurements

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

Zhou, Ning; Huang, Zhenyu; Tuffner, Francis K.

2010-02-28

Small signal stability problems are one of the major threats to grid stability and reliability. Prony analysis has been successfully applied on ringdown data to monitor electromechanical modes of a power system using phasor measurement unit (PMU) data. To facilitate an on-line application of mode estimation, this paper develops a recursive algorithm for implementing Prony analysis and proposed an oscillation detection method to detect ringdown data in real time. By automatically detecting ringdown data, the proposed method helps guarantee that Prony analysis is applied properly and timely on the ringdown data. Thus, the mode estimation results can be performed reliablymore » and timely. The proposed method is tested using Monte Carlo simulations based on a 17-machine model and is shown to be able to properly identify the oscillation data for on-line application of Prony analysis. In addition, the proposed method is applied to field measurement data from WECC to show the performance of the proposed algorithm.« less

Parametric and experimental analysis using a power flow approach

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1988-01-01

Having defined and developed a structural power flow approach for the analysis of structure-borne transmission of structural vibrations, the technique is used to perform an analysis of the influence of structural parameters on the transmitted energy. As a base for comparison, the parametric analysis is first performed using a Statistical Energy Analysis approach and the results compared with those obtained using the power flow approach. The advantages of using structural power flow are thus demonstrated by comparing the type of results obtained by the two methods. Additionally, to demonstrate the advantages of using the power flow method and to show that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental investigation of structural power flow is also presented. Results are presented for an L-shaped beam for which an analytical solution has already been obtained. Furthermore, the various methods available to measure vibrational power flow are compared to investigate the advantages and disadvantages of each method.

DAKOTA Design Analysis Kit for Optimization and Terascale

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

Adams, Brian M.; Dalbey, Keith R.; Eldred, Michael S.

2010-02-24

The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes (computational models) and iterative analysis methods. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and analysis of computational models on high performance computers.A user provides a set of DAKOTA commands in an input file and launches DAKOTA. DAKOTA invokes instances of the computational models, collects their results, and performs systems analyses. DAKOTA contains algorithms for optimization with gradient and nongradient-basedmore » methods; uncertainty quantification with sampling, reliability, polynomial chaos, stochastic collocation, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Services for parallel computing, simulation interfacing, approximation modeling, fault tolerance, restart, and graphics are also included.« less

The power-proportion method for intracranial volume correction in volumetric imaging analysis.

PubMed

Liu, Dawei; Johnson, Hans J; Long, Jeffrey D; Magnotta, Vincent A; Paulsen, Jane S

2014-01-01

In volumetric brain imaging analysis, volumes of brain structures are typically assumed to be proportional or linearly related to intracranial volume (ICV). However, evidence abounds that many brain structures have power law relationships with ICV. To take this relationship into account in volumetric imaging analysis, we propose a power law based method-the power-proportion method-for ICV correction. The performance of the new method is demonstrated using data from the PREDICT-HD study.

An Excel-based implementation of the spectral method of action potential alternans analysis.

PubMed

Pearman, Charles M

2014-12-01

Action potential (AP) alternans has been well established as a mechanism of arrhythmogenesis and sudden cardiac death. Proper interpretation of AP alternans requires a robust method of alternans quantification. Traditional methods of alternans analysis neglect higher order periodicities that may have greater pro-arrhythmic potential than classical 2:1 alternans. The spectral method of alternans analysis, already widely used in the related study of microvolt T-wave alternans, has also been used to study AP alternans. Software to meet the specific needs of AP alternans analysis is not currently available in the public domain. An AP analysis tool is implemented here, written in Visual Basic for Applications and using Microsoft Excel as a shell. This performs a sophisticated analysis of alternans behavior allowing reliable distinction of alternans from random fluctuations, quantification of alternans magnitude, and identification of which phases of the AP are most affected. In addition, the spectral method has been adapted to allow detection and quantification of higher order regular oscillations. Analysis of action potential morphology is also performed. A simple user interface enables easy import, analysis, and export of collated results. © 2014 The Author. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Fingerprint analysis of Hibiscus mutabilis L. leaves based on ultra performance liquid chromatography with photodiode array detector combined with similarity analysis and hierarchical clustering analysis methods

PubMed Central

Liang, Xianrui; Ma, Meiling; Su, Weike

2013-01-01

Background: A method for chemical fingerprint analysis of Hibiscus mutabilis L. leaves was developed based on ultra performance liquid chromatography with photodiode array detector (UPLC-PAD) combined with similarity analysis (SA) and hierarchical clustering analysis (HCA). Materials and Methods: 10 batches of Hibiscus mutabilis L. leaves samples were collected from different regions of China. UPLC-PAD was employed to collect chemical fingerprints of Hibiscus mutabilis L. leaves. Results: The relative standard deviations (RSDs) of the relative retention times (RRT) and relative peak areas (RPA) of 10 characteristic peaks (one of them was identified as rutin) in precision, repeatability and stability test were less than 3%, and the method of fingerprint analysis was validated to be suitable for the Hibiscus mutabilis L. leaves. Conclusions: The chromatographic fingerprints showed abundant diversity of chemical constituents qualitatively in the 10 batches of Hibiscus mutabilis L. leaves samples from different locations by similarity analysis on basis of calculating the correlation coefficients between each two fingerprints. Moreover, the HCA method clustered the samples into four classes, and the HCA dendrogram showed the close or distant relations among the 10 samples, which was consistent to the SA result to some extent. PMID:23930008

Combining task analysis and fault tree analysis for accident and incident analysis: a case study from Bulgaria.

PubMed

Doytchev, Doytchin E; Szwillus, Gerd

2009-11-01

Understanding the reasons for incident and accident occurrence is important for an organization's safety. Different methods have been developed to achieve this goal. To better understand the human behaviour in incident occurrence we propose an analysis concept that combines Fault Tree Analysis (FTA) and Task Analysis (TA). The former method identifies the root causes of an accident/incident, while the latter analyses the way people perform the tasks in their work environment and how they interact with machines or colleagues. These methods were complemented with the use of the Human Error Identification in System Tools (HEIST) methodology and the concept of Performance Shaping Factors (PSF) to deepen the insight into the error modes of an operator's behaviour. HEIST shows the external error modes that caused the human error and the factors that prompted the human to err. To show the validity of the approach, a case study at a Bulgarian Hydro power plant was carried out. An incident - the flooding of the plant's basement - was analysed by combining the afore-mentioned methods. The case study shows that Task Analysis in combination with other methods can be applied successfully to human error analysis, revealing details about erroneous actions in a realistic situation.

Advanced composites structural concepts and materials technologies for primary aircraft structures: Structural response and failure analysis

NASA Technical Reports Server (NTRS)

Dorris, William J.; Hairr, John W.; Huang, Jui-Tien; Ingram, J. Edward; Shah, Bharat M.

1992-01-01

Non-linear analysis methods were adapted and incorporated in a finite element based DIAL code. These methods are necessary to evaluate the global response of a stiffened structure under combined in-plane and out-of-plane loading. These methods include the Arc Length method and target point analysis procedure. A new interface material model was implemented that can model elastic-plastic behavior of the bond adhesive. Direct application of this method is in skin/stiffener interface failure assessment. Addition of the AML (angle minus longitudinal or load) failure procedure and Hasin's failure criteria provides added capability in the failure predictions. Interactive Stiffened Panel Analysis modules were developed as interactive pre-and post-processors. Each module provides the means of performing self-initiated finite elements based analysis of primary structures such as a flat or curved stiffened panel; a corrugated flat sandwich panel; and a curved geodesic fuselage panel. This module brings finite element analysis into the design of composite structures without the requirement for the user to know much about the techniques and procedures needed to actually perform a finite element analysis from scratch. An interactive finite element code was developed to predict bolted joint strength considering material and geometrical non-linearity. The developed method conducts an ultimate strength failure analysis using a set of material degradation models.

The role of ecological dynamics in analysing performance in team sports.

PubMed

Vilar, Luís; Araújo, Duarte; Davids, Keith; Button, Chris

2012-01-01

Performance analysis is a subdiscipline of sports sciences and one-approach, notational analysis, has been used to objectively audit and describe behaviours of performers during different subphases of play, providing additional information for practitioners to improve future sports performance. Recent criticisms of these methods have suggested the need for a sound theoretical rationale to explain performance behaviours, not just describe them. The aim of this article was to show how ecological dynamics provides a valid theoretical explanation of performance in team sports by explaining the formation of successful and unsuccessful patterns of play, based on symmetry-breaking processes emerging from functional interactions between players and the performance environment. We offer the view that ecological dynamics is an upgrade to more operational methods of performance analysis that merely document statistics of competitive performance. In support of our arguments, we refer to exemplar data on competitive performance in team sports that have revealed functional interpersonal interactions between attackers and defenders, based on variations in the spatial positioning of performers relative to each other in critical performance areas, such as the scoring zones. Implications of this perspective are also considered for practice task design and sport development programmes.

Systems and methods for detection of blowout precursors in combustors

DOEpatents

Lieuwen, Tim C.; Nair, Suraj

2006-08-15

The present invention comprises systems and methods for detecting flame blowout precursors in combustors. The blowout precursor detection system comprises a combustor, a pressure measuring device, and blowout precursor detection unit. A combustion controller may also be used to control combustor parameters. The methods of the present invention comprise receiving pressure data measured by an acoustic pressure measuring device, performing one or a combination of spectral analysis, statistical analysis, and wavelet analysis on received pressure data, and determining the existence of a blowout precursor based on such analyses. The spectral analysis, statistical analysis, and wavelet analysis further comprise their respective sub-methods to determine the existence of blowout precursors.

MrBayes tgMC3++: A High Performance and Resource-Efficient GPU-Oriented Phylogenetic Analysis Method.

PubMed

Ling, Cheng; Hamada, Tsuyoshi; Gao, Jingyang; Zhao, Guoguang; Sun, Donghong; Shi, Weifeng

2016-01-01

MrBayes is a widespread phylogenetic inference tool harnessing empirical evolutionary models and Bayesian statistics. However, the computational cost on the likelihood estimation is very expensive, resulting in undesirably long execution time. Although a number of multi-threaded optimizations have been proposed to speed up MrBayes, there are bottlenecks that severely limit the GPU thread-level parallelism of likelihood estimations. This study proposes a high performance and resource-efficient method for GPU-oriented parallelization of likelihood estimations. Instead of having to rely on empirical programming, the proposed novel decomposition storage model implements high performance data transfers implicitly. In terms of performance improvement, a speedup factor of up to 178 can be achieved on the analysis of simulated datasets by four Tesla K40 cards. In comparison to the other publicly available GPU-oriented MrBayes, the tgMC 3 ++ method (proposed herein) outperforms the tgMC 3 (v1.0), nMC 3 (v2.1.1) and oMC 3 (v1.00) methods by speedup factors of up to 1.6, 1.9 and 2.9, respectively. Moreover, tgMC 3 ++ supports more evolutionary models and gamma categories, which previous GPU-oriented methods fail to take into analysis.

Standardization, evaluation and early-phase method validation of an analytical scheme for batch-consistency N-glycosylation analysis of recombinant produced glycoproteins.

PubMed

Zietze, Stefan; Müller, Rainer H; Brecht, René

2008-03-01

In order to set up a batch-to-batch-consistency analytical scheme for N-glycosylation analysis, several sample preparation steps including enzyme digestions and fluorophore labelling and two HPLC-methods were established. The whole method scheme was standardized, evaluated and validated according to the requirements on analytical testing in early clinical drug development by usage of a recombinant produced reference glycoprotein (RGP). The standardization of the methods was performed by clearly defined standard operation procedures. During evaluation of the methods, the major interest was in the loss determination of oligosaccharides within the analytical scheme. Validation of the methods was performed with respect to specificity, linearity, repeatability, LOD and LOQ. Due to the fact that reference N-glycan standards were not available, a statistical approach was chosen to derive accuracy from the linearity data. After finishing the validation procedure, defined limits for method variability could be calculated and differences observed in consistency analysis could be separated into significant and incidental ones.

An Integrated Low-Speed Performance and Noise Prediction Methodology for Subsonic Aircraft

NASA Technical Reports Server (NTRS)

Olson, E. D.; Mavris, D. N.

2000-01-01

An integrated methodology has been assembled to compute the engine performance, takeoff and landing trajectories, and community noise levels for a subsonic commercial aircraft. Where feasible, physics-based noise analysis methods have been used to make the results more applicable to newer, revolutionary designs and to allow for a more direct evaluation of new technologies. The methodology is intended to be used with approximation methods and risk analysis techniques to allow for the analysis of a greater number of variable combinations while retaining the advantages of physics-based analysis. Details of the methodology are described and limited results are presented for a representative subsonic commercial aircraft.

Comprehensive comparative analysis of 5'-end RNA-sequencing methods.

PubMed

Adiconis, Xian; Haber, Adam L; Simmons, Sean K; Levy Moonshine, Ami; Ji, Zhe; Busby, Michele A; Shi, Xi; Jacques, Justin; Lancaster, Madeline A; Pan, Jen Q; Regev, Aviv; Levin, Joshua Z

2018-06-04

Specialized RNA-seq methods are required to identify the 5' ends of transcripts, which are critical for studies of gene regulation, but these methods have not been systematically benchmarked. We directly compared six such methods, including the performance of five methods on a single human cellular RNA sample and a new spike-in RNA assay that helps circumvent challenges resulting from uncertainties in annotation and RNA processing. We found that the 'cap analysis of gene expression' (CAGE) method performed best for mRNA and that most of its unannotated peaks were supported by evidence from other genomic methods. We applied CAGE to eight brain-related samples and determined sample-specific transcription start site (TSS) usage, as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

Advances in three-dimensional field analysis and evaluation of performance parameters of electrical machines

NASA Astrophysics Data System (ADS)

Sivasubramaniam, Kiruba

This thesis makes advances in three dimensional finite element analysis of electrical machines and the quantification of their parameters and performance. The principal objectives of the thesis are: (1)the development of a stable and accurate method of nonlinear three-dimensional field computation and application to electrical machinery and devices; and (2)improvement in the accuracy of determination of performance parameters, particularly forces and torque computed from finite elements. Contributions are made in two general areas: a more efficient formulation for three dimensional finite element analysis which saves time and improves accuracy, and new post-processing techniques to calculate flux density values from a given finite element solution. A novel three-dimensional magnetostatic solution based on a modified scalar potential method is implemented. This method has significant advantages over the traditional total scalar, reduced scalar or vector potential methods. The new method is applied to a 3D geometry of an iron core inductor and a permanent magnet motor. The results obtained are compared with those obtained from traditional methods, in terms of accuracy and speed of computation. A technique which has been observed to improve force computation in two dimensional analysis using a local solution of Laplace's equation in the airgap of machines is investigated and a similar method is implemented in the three dimensional analysis of electromagnetic devices. A new integral formulation to improve force calculation from a smoother flux-density profile is also explored and implemented. Comparisons are made and conclusions drawn as to how much improvement is obtained and at what cost. This thesis also demonstrates the use of finite element analysis to analyze torque ripples due to rotor eccentricity in permanent magnet BLDC motors. A new method for analyzing torque harmonics based on data obtained from a time stepping finite element analysis of the machine is explored and implemented.

EEG source analysis of data from paralysed subjects

NASA Astrophysics Data System (ADS)

Carabali, Carmen A.; Willoughby, John O.; Fitzgibbon, Sean P.; Grummett, Tyler; Lewis, Trent; DeLosAngeles, Dylan; Pope, Kenneth J.

2015-12-01

One of the limitations of Encephalography (EEG) data is its quality, as it is usually contaminated with electric signal from muscle. This research intends to study results of two EEG source analysis methods applied to scalp recordings taken in paralysis and in normal conditions during the performance of a cognitive task. The aim is to determinate which types of analysis are appropriate for dealing with EEG data containing myogenic components. The data used are the scalp recordings of six subjects in normal conditions and during paralysis while performing different cognitive tasks including the oddball task which is the object of this research. The data were pre-processed by filtering it and correcting artefact, then, epochs of one second long for targets and distractors were extracted. Distributed source analysis was performed in BESA Research 6.0, using its results and information from the literature, 9 ideal locations for source dipoles were identified. The nine dipoles were used to perform discrete source analysis, fitting them to the averaged epochs for obtaining source waveforms. The results were statistically analysed comparing the outcomes before and after the subjects were paralysed. Finally, frequency analysis was performed for better explain the results. The findings were that distributed source analysis could produce confounded results for EEG contaminated with myogenic signals, conversely, statistical analysis of the results from discrete source analysis showed that this method could help for dealing with EEG data contaminated with muscle electrical signal.

PET/CT and contrast enhanced CT in single vs. two separate sessions: a cost analysis study.

PubMed

Picchio, M; Mansueto, M; Crivellaro, C; Guerra, L; Marcelli, S; Arosio, M; Sironi, S; Gianolli, L; Grimaldi, A; Messa, C

2012-06-01

Aim of the study was to quantify the economic impact of PET/CT and contrast enhanced (c.e.) CT performed in a single session examination vs. stand-alone modalities in oncological patients. One-hundred-forty-five cancer patients referred to both PET/CT and c.e. CT, to either stage (N.=46) or re-stage (N.=99) the disease, were included. Seventy-two/145 performed both studies in a single session (innovative method) and 73/145 in two different sessions (traditional method). The cost-minimization analysis was performed by evaluating: 1) institutional costs, data obtained by hospital accountability (staff, medical materials, equipment maintenance and depreciation, departments utilities); 2) patients costs, data obtained by a specific survey provided to patients (travel, food, accommodation costs, productivity loss). Economic data analysis showed that the costs for innovative method was lower than those of traditional method, both for Institution (106 € less per test) and for patient (21 € less per patient). The loss of productivity for patient and caregivers resulted lower for the innovative method than the traditional method (3 work-hour less per person). PET/CT and c.e. CT performed in a single session is more cost-effective than stand-alone modalities, by reducing both Institutional and patients costs. These advantages are mainly due to lower Institutional cost (single procedure) and to lower cost related to travel and housing.

FPGA-based multi-channel fluorescence lifetime analysis of Fourier multiplexed frequency-sweeping lifetime imaging

PubMed Central

Zhao, Ming; Li, Yu; Peng, Leilei

2014-01-01

We report a fast non-iterative lifetime data analysis method for the Fourier multiplexed frequency-sweeping confocal FLIM (Fm-FLIM) system [ Opt. Express22, 10221 ( 2014)24921725]. The new method, named R-method, allows fast multi-channel lifetime image analysis in the system’s FPGA data processing board. Experimental tests proved that the performance of the R-method is equivalent to that of single-exponential iterative fitting, and its sensitivity is well suited for time-lapse FLIM-FRET imaging of live cells, for example cyclic adenosine monophosphate (cAMP) level imaging with GFP-Epac-mCherry sensors. With the R-method and its FPGA implementation, multi-channel lifetime images can now be generated in real time on the multi-channel frequency-sweeping FLIM system, and live readout of FRET sensors can be performed during time-lapse imaging. PMID:25321778

Chemoenzymatic method for glycomics: isolation, identification, and quantitation

PubMed Central

Yang, Shuang; Rubin, Abigail; Eshghi, Shadi Toghi; Zhang, Hui

2015-01-01

Over the past decade, considerable progress has been made with respect to the analytical methods for analysis of glycans from biological sources. Regardless of the specific methods that are used, glycan analysis includes isolation, identification, and quantitation. Derivatization is indispensable to increase their identification. Derivatization of glycans can be performed by permethylation or carbodiimide coupling / esterification. By introducing a fluorophore or chromophore at their reducing end, glycans can be separated by electrophoresis or chromatography. The fluorogenically labeled glycans can be quantitated using fluorescent detection. The recently developed approaches using solid-phase such as glycoprotein immobilization for glycan extraction and on-tissue glycan mass spectrometry imaging demonstrate advantages over methods performed in solution. Derivatization of sialic acids is favorably implemented on the solid support using carbodiimide coupling, and the released glycans can be further modified at the reducing end or permethylated for quantitative analysis. In this review, methods for glycan isolation, identification, and quantitation are discussed. PMID:26390280

Probabilistic Structural Analysis Theory Development

NASA Technical Reports Server (NTRS)

Burnside, O. H.

1985-01-01

The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.

Simulation Research on Vehicle Active Suspension Controller Based on G1 Method

NASA Astrophysics Data System (ADS)

Li, Gen; Li, Hang; Zhang, Shuaiyang; Luo, Qiuhui

2017-09-01

Based on the order relation analysis method (G1 method), the optimal linear controller of vehicle active suspension is designed. The system of the main and passive suspension of the single wheel vehicle is modeled and the system input signal model is determined. Secondly, the system motion state space equation is established by the kinetic knowledge and the optimal linear controller design is completed with the optimal control theory. The weighting coefficient of the performance index coefficients of the main passive suspension is determined by the relational analysis method. Finally, the model is simulated in Simulink. The simulation results show that: the optimal weight value is determined by using the sequence relation analysis method under the condition of given road conditions, and the vehicle acceleration, suspension stroke and tire motion displacement are optimized to improve the comprehensive performance of the vehicle, and the active control is controlled within the requirements.

The Shock and Vibration Bulletin. Part 2. Invited Papers, Structural Dynamics

DTIC Science & Technology

1974-08-01

VIKING LANDER DYNAMICS 41 Mr. Joseph C. Pohlen, Martin Marietta Aerospace, Denver, Colorado Structural Dynamics PERFORMANCE OF STATISTICAL ENERGY ANALYSIS 47...aerospace structures. Analytical prediction of these environments is beyond the current scope of classical modal techniques. Statistical energy analysis methods...have been developed that circumvent the difficulties of high-frequency nodal analysis. These statistical energy analysis methods are evaluated

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Quantitative performance targets by using balanced scorecard system: application to waste management and public administration.

PubMed

Mendes, Paula; Nunes, Luis Miguel; Teixeira, Margarida Ribau

2014-09-01

This article demonstrates how decision-makers can be guided in the process of defining performance target values in the balanced scorecard system. We apply a method based on sensitivity analysis with Monte Carlo simulation to the municipal solid waste management system in Loulé Municipality (Portugal). The method includes two steps: sensitivity analysis of performance indicators to identify those performance indicators with the highest impact on the balanced scorecard model outcomes; and sensitivity analysis of the target values for the previously identified performance indicators. Sensitivity analysis shows that four strategic objectives (IPP1: Comply with the national waste strategy; IPP4: Reduce nonrenewable resources and greenhouse gases; IPP5: Optimize the life-cycle of waste; and FP1: Meet and optimize the budget) alone contribute 99.7% of the variability in overall balanced scorecard value. Thus, these strategic objectives had a much stronger impact on the estimated balanced scorecard outcome than did others, with the IPP1 and the IPP4 accounting for over 55% and 22% of the variance in overall balanced scorecard value, respectively. The remaining performance indicators contribute only marginally. In addition, a change in the value of a single indicator's target value made the overall balanced scorecard value change by as much as 18%. This may lead to involuntarily biased decisions by organizations regarding performance target-setting, if not prevented with the help of methods such as that proposed and applied in this study. © The Author(s) 2014.

Simultaneous quantitation of 14 active components in Yinchenhao decoction with an ultrahigh performance liquid chromatography-diode array detector: Method development and ingredient analysis of different commonly prepared samples.

PubMed

Yi, YaXiong; Zhang, Yong; Ding, Yue; Lu, Lu; Zhang, Tong; Zhao, Yuan; Xu, XiaoJun; Zhang, YuXin

2016-11-01

J. Sep. Sci. 2016, 39, 4147-4157 DOI: 10.1002/jssc.201600284 Yinchenhao decoction (YCHD) is a famous Chinese herbal formula recorded in the Shang Han Lun which was prescribed by Zhongjing Zhang during 150-219 AD. A novel quantitative analysis method was developed, based on ultrahigh performance liquid chromatography coupled with a diode array detector for the simultaneous determination of 14 main active components in Yinchenhao decoction. Furthermore, the method has been applied for compositional difference analysis of the 14 components in eight normal extraction samples of Yinchenhao decoction, with the aid of hierarchical clustering analysis and similarity analysis. The present research could help hospital, factory and lab choose the best way to make Yinchenhao decoction with better efficacy. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spectroscopic chemical analysis methods and apparatus

NASA Technical Reports Server (NTRS)

Hug, William F. (Inventor); Reid, Ray D. (Inventor)

2009-01-01

Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted simultaneously with native fluorescence spectroscopy to provide high levels of sensitivity and specificity in the same instrument.

The Flight Optimization System Weights Estimation Method

NASA Technical Reports Server (NTRS)

Wells, Douglas P.; Horvath, Bryce L.; McCullers, Linwood A.

2017-01-01

FLOPS has been the primary aircraft synthesis software used by the Aeronautics Systems Analysis Branch at NASA Langley Research Center. It was created for rapid conceptual aircraft design and advanced technology impact assessments. FLOPS is a single computer program that includes weights estimation, aerodynamics estimation, engine cycle analysis, propulsion data scaling and interpolation, detailed mission performance analysis, takeoff and landing performance analysis, noise footprint estimation, and cost analysis. It is well known as a baseline and common denominator for aircraft design studies. FLOPS is capable of calibrating a model to known aircraft data, making it useful for new aircraft and modifications to existing aircraft. The weight estimation method in FLOPS is known to be of high fidelity for conventional tube with wing aircraft and a substantial amount of effort went into its development. This report serves as a comprehensive documentation of the FLOPS weight estimation method. The development process is presented with the weight estimation process.

Design and Analysis Tool for External-Compression Supersonic Inlets

NASA Technical Reports Server (NTRS)

Slater, John W.

2012-01-01

A computational tool named SUPIN has been developed to design and analyze external-compression supersonic inlets for aircraft at cruise speeds from Mach 1.6 to 2.0. The inlet types available include the axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced Busemann inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flowfield is divided into parts to provide a framework for the geometry and aerodynamic modeling and the parts are defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick analysis. SUPIN provides inlet geometry in the form of coordinates and surface grids useable by grid generation methods for higher-fidelity computational fluid dynamics (CFD) analysis. SUPIN is demonstrated through a series of design studies and CFD analyses were performed to verify some of the analysis results.

Spectroscopic chemical analysis methods and apparatus

NASA Technical Reports Server (NTRS)

Reid, Ray D. (Inventor); Hug, William F. (Inventor)

2010-01-01

Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted simultaneously with native fluorescence spectroscopy to provide high levels of sensitivity and specificity in the same instrument.

Ultra-Trace Analysis of Nine Macrolides, including Tulathromycin A (Draxxin), in Edible Animal Tissues with Mini-Column Liquid Chromatography Tandem Mass Spectrometry

USDA-ARS?s Scientific Manuscript database

Analysis of 9 macrolides is presented, including tulathromycin A (Draxxin), in beef, poultry and pork muscle with a simple multi-residue extraction and analysis method using high performance liquid chromatography coupled to electrospray ionization tandem mass spectrometry. The extraction method inv...

Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.

PubMed

Simovski, Boris; Kanduri, Chakravarthi; Gundersen, Sveinung; Titov, Dmytro; Domanska, Diana; Bock, Christoph; Bossini-Castillo, Lara; Chikina, Maria; Favorov, Alexander; Layer, Ryan M; Mironov, Andrey A; Quinlan, Aaron R; Sheffield, Nathan C; Trynka, Gosia; Sandve, Geir K

2018-06-05

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

Assessment of repeatability of composition of perfumed waters by high-performance liquid chromatography combined with numerical data analysis based on cluster analysis (HPLC UV/VIS - CA).

PubMed

Ruzik, L; Obarski, N; Papierz, A; Mojski, M

2015-06-01

High-performance liquid chromatography (HPLC) with UV/VIS spectrophotometric detection combined with the chemometric method of cluster analysis (CA) was used for the assessment of repeatability of composition of nine types of perfumed waters. In addition, the chromatographic method of separating components of the perfume waters under analysis was subjected to an optimization procedure. The chromatograms thus obtained were used as sources of data for the chemometric method of cluster analysis (CA). The result was a classification of a set comprising 39 perfumed water samples with a similar composition at a specified level of probability (level of agglomeration). A comparison of the classification with the manufacturer's declarations reveals a good degree of consistency and demonstrates similarity between samples in different classes. A combination of the chromatographic method with cluster analysis (HPLC UV/VIS - CA) makes it possible to quickly assess the repeatability of composition of perfumed waters at selected levels of probability. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Developing Measures of Job Performance for Support Staff in Housing Services for People with Intellectual Disabilities

ERIC Educational Resources Information Center

Hatton, Chris; Wigham, Sarah; Craig, Jaime

2009-01-01

Background: There is an absence of research concerning the assessment of housing support worker job performance, particularly in the development of job performance measures that reflect the priorities of people with intellectual disabilities and their families. Method: A worker-oriented job analysis method was used to develop four short job…

Dual Standards of School Performance and Funding? Empirical Searches of School Funding Adequacy in Kentucky and Maine

ERIC Educational Resources Information Center

Lee, Jaekyung

2010-01-01

This study examines potential consequences of the discrepancies between national and state performance standards for school funding in Kentucky and Maine. Applying the successful schools observation method and cost function analysis method to integrated data-sets that match schools' eight-grade mathematics test performance measures to district…

Analysis of anthocyanins in commercial fruit juices by using nano-liquid chromatography-electrospray-mass spectrometry and high-performance liquid chromatography with UV-vis detector.

PubMed

Fanali, Chiara; Dugo, Laura; D'Orazio, Giovanni; Lirangi, Melania; Dachà, Marina; Dugo, Paola; Mondello, Luigi

2011-01-01

Nano-LC and conventional HPLC techniques were applied for the analysis of anthocyanins present in commercial fruit juices using a capillary column of 100 μm id and a 2.1 mm id narrow-bore C(18) column. Analytes were detected by UV-Vis at 518 nm and ESI-ion trap MS with HPLC and nano-LC, respectively. Commercial blueberry juice (14 anthocyanins detected) was used to optimize chromatographic separation of analytes and other analysis parameters. Qualitative identification of anthocyanins was performed by comparing the recorded mass spectral data with those of published papers. The use of the same mobile phase composition in both techniques revealed that the miniaturized method exhibited shorter analysis time and higher sensitivity than narrow-bore chromatography. Good intra-day and day-to-day precision of retention time was obtained in both methods with values of RSD less than 3.4 and 0.8% for nano-LC and HPLC, respectively. Quantitative analysis was performed by external standard curve calibration of cyanidin-3-O-glucoside standard. Calibration curves were linear in the concentration ranges studied, 0.1-50 and 6-50 μg/mL for HPLC-UV/Vis and nano-LC-MS, respectively. LOD and LOQ values were good for both methods. In addition to commercial blueberry juice, qualitative and quantitative analysis of other juices (e.g. raspberry, sweet cherry and pomegranate) was performed. The optimized nano-LC-MS method allowed an easy and selective identification and quantification of anthocyanins in commercial fruit juices; it offered good results, shorter analysis time and reduced mobile phase volume with respect to narrow-bore HPLC. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Antiwindup analysis and design approaches for MIMO systems

NASA Technical Reports Server (NTRS)

Marcopoli, Vincent R.; Phillips, Stephen M.

1994-01-01

Performance degradation of multiple-input multiple-output (MIMO) control systems having limited actuators is often handled by augmenting the controller with an antiwindup mechanism, which attempts to maintain system performance when limits are encountered. The goals of this paper are: (1) To develop a method to analyze antiwindup systems to determine precisely what stability and performance degradation is incurred under limited conditions. It is shown that by reformulating limited actuator commands as resulting from multiplicative perturbations to the corresponding controller requests, mu-analysis tools can be utilized to obtain quantitative measures of stability and performance degradation. (2) To propose a linear, time invariant (LTI) criterion on which to base the antiwindup design. These analysis and design methods are illustrated through the evaluation of two competing antiwindup schemes augmenting the controller of a Short Take-Off and Vertical Landing (STOVL) aircraft in transition flight.

Antiwindup analysis and design approaches for MIMO systems

NASA Technical Reports Server (NTRS)

Marcopoli, Vincent R.; Phillips, Stephen M.

1993-01-01

Performance degradation of multiple-input multiple-output (MIMO) control systems having limited actuators is often handled by augmenting the controller with an antiwindup mechanism, which attempts to maintain system performance when limits are encountered. The goals of this paper are: 1) to develop a method to analyze antiwindup systems to determine precisely what stability and performance degradation is incurred under limited conditions. It is shown that by reformulating limited actuator commands as resulting from multiplicative perturbations to the corresponding controller requests, mu-analysis tools can be utilized to obtain quantitative measures of stability and performance degradation. 2) To propose a linear, time invariant (LTI) criterion on which to base the antiwindup design. These analysis and design methods are illustrated through the evaluation of two competing antiwindup schemes augmenting the controller of a Short Take-Off and Vertical Landing (STOVL) aircraft in transition flight.

Urea free and more efficient sample preparation method for mass spectrometry based protein identification via combining the formic acid-assisted chemical cleavage and trypsin digestion.

PubMed

Wu, Shuaibin; Yang, Kaiguang; Liang, Zhen; Zhang, Lihua; Zhang, Yukui

2011-10-30

A formic acid (FA)-assisted sample preparation method was presented for protein identification via mass spectrometry (MS). Detailedly, an aqueous solution containing 2% FA and dithiothreitol was selected to perform protein denaturation, aspartic acid (D) sites cleavage and disulfide linkages reduction simultaneously at 108°C for 2h. Subsequently, FA wiped off via vacuum concentration. Finally, iodoacetamide (IAA) alkylation and trypsin digestion could be performed ordinally. A series of model proteins (BSA, β-lactoglobulin and apo-Transferrin) were treated respectively using such method, followed by matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The identified peptide number was increased by ∼ 80% in comparison with the conventional urea-assisted sample preparation method. Moreover, BSA identification was achieved efficiently down to femtomole (25 ± 0 sequence coverage and 16 ± 1 peptides) via such method. In contrast, there were not peptides identified confidently via the urea-assisted method before desalination via the C18 zip tip. The absence of urea in this sample preparation method was an advantage for the more favorable digestion and MALDI-TOF MS analysis. The performances of two methods for the real sample (rat liver proteome) were also compared, followed by a nanoflow reversed-phase liquid chromatography with electrospray ionization tandem mass spectrometry system analysis. As a result, 1335 ± 43 peptides were identified confidently (false discovery rate <1%) via FA-assisted method, corresponding to 295 ± 12 proteins (of top match=1 and requiring 2 unique peptides at least). In contrast, there were only 1107 ± 16 peptides (corresponding to 231 ± 10 proteins) obtained from the conventional urea-assisted method. It was serving as a more efficient protein sample preparation method for researching specific proteomes better, and providing assistance to develop other proteomics analysis methods, such as, peptide quantitative analysis. Copyright © 2011 Elsevier B.V. All rights reserved.

Validation of highly sensitive simultaneous targeted and untargeted analysis of keto-steroids by Girard P derivatization and stable isotope dilution-liquid chromatography-high resolution mass spectrometry.

PubMed

Frey, Alexander J; Wang, Qingqing; Busch, Christine; Feldman, Daniel; Bottalico, Lisa; Mesaros, Clementina A; Blair, Ian A; Vachani, Anil; Snyder, Nathaniel W

2016-12-01

A multiplexed quantitative method for the analysis of three major unconjugated steroids in human serum by stable isotope dilution liquid chromatography-high resolution mass spectrometry (LC-HRMS) was developed and validated on a Q Exactive Plus hybrid quadrupole/Orbitrap mass spectrometer. This quantification utilized isotope dilution and Girard P derivatization on the keto-groups of testosterone (T), androstenedione (AD) and dehydroepiandrosterone (DHEA) to improve ionization efficiency using electrospray ionization. Major isomeric compounds to T and DHEA; the inactive epimer of testosterone (epiT), and the metabolite of AD, 5α-androstanedione (5α-AD) were completely resolved on a biphenyl column within an 18min method. Inter- and intra-day method validation using LC-HRMS with qualifying product ions was performed and acceptable analytical performance was achieved. The method was further validated by comparing steroid levels from 100μL of serum from young vs older subjects. Since this approach provides high-dimensional HRMS data, untargeted analysis by age group was performed. DHEA and T were detected among the top analytes most significantly different across the two groups after untargeted LC-HRMS analysis, as well as a number of other still unknown metabolites, indicating the potential for combined targeted/untargeted analysis in steroid analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Meta‐analysis of test accuracy studies using imputation for partial reporting of multiple thresholds

PubMed Central

Deeks, J.J.; Martin, E.C.; Riley, R.D.

2017-01-01

Introduction For tests reporting continuous results, primary studies usually provide test performance at multiple but often different thresholds. This creates missing data when performing a meta‐analysis at each threshold. A standard meta‐analysis (no imputation [NI]) ignores such missing data. A single imputation (SI) approach was recently proposed to recover missing threshold results. Here, we propose a new method that performs multiple imputation of the missing threshold results using discrete combinations (MIDC). Methods The new MIDC method imputes missing threshold results by randomly selecting from the set of all possible discrete combinations which lie between the results for 2 known bounding thresholds. Imputed and observed results are then synthesised at each threshold. This is repeated multiple times, and the multiple pooled results at each threshold are combined using Rubin's rules to give final estimates. We compared the NI, SI, and MIDC approaches via simulation. Results Both imputation methods outperform the NI method in simulations. There was generally little difference in the SI and MIDC methods, but the latter was noticeably better in terms of estimating the between‐study variances and generally gave better coverage, due to slightly larger standard errors of pooled estimates. Given selective reporting of thresholds, the imputation methods also reduced bias in the summary receiver operating characteristic curve. Simulations demonstrate the imputation methods rely on an equal threshold spacing assumption. A real example is presented. Conclusions The SI and, in particular, MIDC methods can be used to examine the impact of missing threshold results in meta‐analysis of test accuracy studies. PMID:29052347

The effect of ion-exchange purification on the determination of plutonium at the New Brunswick Laboratory

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

Mitchell, W.G.; Spaletto, M.I.; Lewis, K.

The method of plutonium (Pu) determination at the Brunswick Laboratory (NBL) consists of a combination of ion-exchange purification followed by controlled-potential coulometric analysis (IE/CPC). The present report's purpose is to quantify any detectable Pu loss occurring in the ion-exchange (IE) purification step which would cause a negative bias in the NBL method for Pu analysis. The magnitude of any such loss would be contained within the reproducibility (0.05%) of the IE/CPC method which utilizes a state-of-the-art autocoulometer developed at NBL. When the NBL IE/CPC method is used for Pu analysis, any loss in ion-exchange purification (<0.05%) is confounded with themore » repeatability of the ion-exchange and the precision of the CPC analysis technique (<0.05%). Consequently, to detect a bias in the IE/CPC method due to the IE alone using the IE/CPC method itself requires that many randomized analyses on a single material be performed over time and that statistical analysis of the data be performed. The initial approach described in this report to quantify any IE loss was an independent method, Isotope Dilution Mass Spectrometry; however, the number of analyses performed was insufficient to assign a statistically significant value to the IE loss (<0.02% of 10 mg samples of Pu). The second method used for quantifying any IE loss of Pu was multiple ion exchanges of the same Pu aliquant; the small number of analyses possible per individual IE together with the column-to-column variability over multiple ion exchanges prevented statistical detection of any loss of <0.05%. 12 refs.« less

A Review of Methods for Analysis of the Expected Value of Information.

PubMed

Heath, Anna; Manolopoulou, Ioanna; Baio, Gianluca

2017-10-01

In recent years, value-of-information analysis has become more widespread in health economic evaluations, specifically as a tool to guide further research and perform probabilistic sensitivity analysis. This is partly due to methodological advancements allowing for the fast computation of a typical summary known as the expected value of partial perfect information (EVPPI). A recent review discussed some approximation methods for calculating the EVPPI, but as the research has been active over the intervening years, that review does not discuss some key estimation methods. Therefore, this paper presents a comprehensive review of these new methods. We begin by providing the technical details of these computation methods. We then present two case studies in order to compare the estimation performance of these new methods. We conclude that a method based on nonparametric regression offers the best method for calculating the EVPPI in terms of accuracy, computational time, and ease of implementation. This means that the EVPPI can now be used practically in health economic evaluations, especially as all the methods are developed in parallel with R functions and a web app to aid practitioners.

Computational structural mechanics methods research using an evolving framework

NASA Technical Reports Server (NTRS)

Knight, N. F., Jr.; Lotts, C. G.; Gillian, R. E.

1990-01-01

Advanced structural analysis and computational methods that exploit high-performance computers are being developed in a computational structural mechanics research activity sponsored by the NASA Langley Research Center. These new methods are developed in an evolving framework and applied to representative complex structural analysis problems from the aerospace industry. An overview of the methods development environment is presented, and methods research areas are described. Selected application studies are also summarized.

Reforming High School Science for Low-Performing Students Using Inquiry Methods and Communities of Practice

NASA Astrophysics Data System (ADS)

Bolden, Marsha Gail

Some schools fall short of the high demand to increase science scores on state exams because low-performing students enter high school unprepared for high school science. Low-performing students are not successful in high school for many reasons. However, using inquiry methods have improved students' understanding of science concepts. The purpose of this qualitative research study was to investigate the teachers' lived experiences with using inquiry methods to motivate low-performing high school science students in an inquiry-based program called Xtreem Science. Fifteen teachers were selected from the Xtreem Science program, a program designed to assist teachers in motivating struggling science students. The research questions involved understanding (a) teachers' experiences in using inquiry methods, (b) challenges teachers face in using inquiry methods, and (c) how teachers describe student's response to inquiry methods. Strategy of data collection and analysis included capturing and understanding the teachers' feelings, perceptions, and attitudes in their lived experience of teaching using inquiry method and their experience in motivating struggling students. Analysis of interview responses revealed teachers had some good experiences with inquiry and expressed that inquiry impacted their teaching style and approach to topics, and students felt that using inquiry methods impacted student learning for the better. Inquiry gave low-performing students opportunities to catch up and learn information that moved them to the next level of science courses. Implications for positive social change include providing teachers and school district leaders with information to help improve performance of the low performing science students.

Analysis of a virtual memory model for maintaining database views

NASA Technical Reports Server (NTRS)

Kinsley, Kathryn C.; Hughes, Charles E.

1992-01-01

This paper presents an analytical model for predicting the performance of a new support strategy for database views. This strategy, called the virtual method, is compared with traditional methods for supporting views. The analytical model's predictions of improved performance by the virtual method are then validated by comparing these results with those achieved in an experimental implementation.

Concrete Condition Assessment Using Impact-Echo Method and Extreme Learning Machines

PubMed Central

Zhang, Jing-Kui; Yan, Weizhong; Cui, De-Mi

2016-01-01

The impact-echo (IE) method is a popular non-destructive testing (NDT) technique widely used for measuring the thickness of plate-like structures and for detecting certain defects inside concrete elements or structures. However, the IE method is not effective for full condition assessment (i.e., defect detection, defect diagnosis, defect sizing and location), because the simple frequency spectrum analysis involved in the existing IE method is not sufficient to capture the IE signal patterns associated with different conditions. In this paper, we attempt to enhance the IE technique and enable it for full condition assessment of concrete elements by introducing advanced machine learning techniques for performing comprehensive analysis and pattern recognition of IE signals. Specifically, we use wavelet decomposition for extracting signatures or features out of the raw IE signals and apply extreme learning machine, one of the recently developed machine learning techniques, as classification models for full condition assessment. To validate the capabilities of the proposed method, we build a number of specimens with various types, sizes, and locations of defects and perform IE testing on these specimens in a lab environment. Based on analysis of the collected IE signals using the proposed machine learning based IE method, we demonstrate that the proposed method is effective in performing full condition assessment of concrete elements or structures. PMID:27023563

A Comparison of Three Methods for the Analysis of Skin Flap Viability: Reliability and Validity.

PubMed

Tim, Carla Roberta; Martignago, Cintia Cristina Santi; da Silva, Viviane Ribeiro; Dos Santos, Estefany Camila Bonfim; Vieira, Fabiana Nascimento; Parizotto, Nivaldo Antonio; Liebano, Richard Eloin

2018-05-01

Objective: Technological advances have provided new alternatives to the analysis of skin flap viability in animal models; however, the interrater validity and reliability of these techniques have yet to be analyzed. The present study aimed to evaluate the interrater validity and reliability of three different methods: weight of paper template (WPT), paper template area (PTA), and photographic analysis. Approach: Sixteen male Wistar rats had their cranially based dorsal skin flap elevated. On the seventh postoperative day, the viable tissue area and the necrotic area of the skin flap were recorded using the paper template method and photo image. The evaluation of the percentage of viable tissue was performed using three methods, simultaneously and independently by two raters. The analysis of interrater reliability and viability was performed using the intraclass correlation coefficient and Bland Altman Plot Analysis was used to visualize the presence or absence of systematic bias in the evaluations of data validity. Results: The results showed that interrater reliability for WPT, measurement of PTA, and photographic analysis were 0.995, 0.990, and 0.982, respectively. For data validity, a correlation >0.90 was observed for all comparisons made between the three methods. In addition, Bland Altman Plot Analysis showed agreement between the comparisons of the methods and the presence of systematic bias was not observed. Innovation: Digital methods are an excellent choice for assessing skin flap viability; moreover, they make data use and storage easier. Conclusion: Independently from the method used, the interrater reliability and validity proved to be excellent for the analysis of skin flaps' viability.

Simultaneous Aerodynamic and Structural Design Optimization (SASDO) for a 3-D Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.; Newman, Perry A.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic and Structural Design Optimization (SASDO) is shown as an extension of the Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) method. It is extended by the inclusion of structure element sizing parameters as design variables and Finite Element Method (FEM) analysis responses as constraints. The method aims to reduce the computational expense. incurred in performing shape and sizing optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, FEM structural analysis and sensitivity analysis tools. SASDO is applied to a simple. isolated, 3-D wing in inviscid flow. Results show that the method finds the saine local optimum as a conventional optimization method with some reduction in the computational cost and without significant modifications; to the analysis tools.

A Macro Analysis of DoD Logistics Systems. Volume 3. A Framework for Policy-Level Logistics Management

DTIC Science & Technology

1978-12-01

prioritization. 5 (We have chosen to use a variation of Saaty’s method in our hierarchical analysis, discussed in chapter 5, but for a purpose different ...the word "framework" to refer to an abstract structure for think- ing through policy-tieel management problems. This structure raises method - ological...readiness and logistics system performance, and we relied heavily on "structural" and trend analysis. By structural analysis, we meant a formal method for

[Research progress on mechanical performance evaluation of artificial intervertebral disc].

PubMed

Li, Rui; Wang, Song; Liao, Zhenhua; Liu, Weiqiang

2018-03-01

The mechanical properties of artificial intervertebral disc (AID) are related to long-term reliability of prosthesis. There are three testing methods involved in the mechanical performance evaluation of AID based on different tools: the testing method using mechanical simulator, in vitro specimen testing method and finite element analysis method. In this study, the testing standard, testing equipment and materials of AID were firstly introduced. Then, the present status of AID static mechanical properties test (static axial compression, static axial compression-shear), dynamic mechanical properties test (dynamic axial compression, dynamic axial compression-shear), creep and stress relaxation test, device pushout test, core pushout test, subsidence test, etc. were focused on. The experimental techniques using in vitro specimen testing method and testing results of available artificial discs were summarized. The experimental methods and research status of finite element analysis were also summarized. Finally, the research trends of AID mechanical performance evaluation were forecasted. The simulator, load, dynamic cycle, motion mode, specimen and test standard would be important research fields in the future.

Statistical analysis of RHIC beam position monitors performance

NASA Astrophysics Data System (ADS)

Calaga, R.; Tomás, R.

2004-04-01

A detailed statistical analysis of beam position monitors (BPM) performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models

PubMed Central

Chiu, Chi-yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-ling; Xiong, Momiao; Fan, Ruzong

2017-01-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data. PMID:28000696

Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.

PubMed

Chiu, Chi-Yang; Jung, Jeesun; Chen, Wei; Weeks, Daniel E; Ren, Haobo; Boehnke, Michael; Amos, Christopher I; Liu, Aiyi; Mills, James L; Ting Lee, Mei-Ling; Xiong, Momiao; Fan, Ruzong

2017-02-01

To analyze next-generation sequencing data, multivariate functional linear models are developed for a meta-analysis of multiple studies to connect genetic variant data to multiple quantitative traits adjusting for covariates. The goal is to take the advantage of both meta-analysis and pleiotropic analysis in order to improve power and to carry out a unified association analysis of multiple studies and multiple traits of complex disorders. Three types of approximate F -distributions based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants. Simulation analysis is performed to evaluate false-positive rates and power of the proposed tests. The proposed methods are applied to analyze lipid traits in eight European cohorts. It is shown that it is more advantageous to perform multivariate analysis than univariate analysis in general, and it is more advantageous to perform meta-analysis of multiple studies instead of analyzing the individual studies separately. The proposed models require individual observations. The value of the current paper can be seen at least for two reasons: (a) the proposed methods can be applied to studies that have individual genotype data; (b) the proposed methods can be used as a criterion for future work that uses summary statistics to build test statistics to meta-analyze the data.

Influence analysis in quantitative trait loci detection.

PubMed

Dou, Xiaoling; Kuriki, Satoshi; Maeno, Akiteru; Takada, Toyoyuki; Shiroishi, Toshihiko

2014-07-01

This paper presents systematic methods for the detection of influential individuals that affect the log odds (LOD) score curve. We derive general formulas of influence functions for profile likelihoods and introduce them into two standard quantitative trait locus detection methods-the interval mapping method and single marker analysis. Besides influence analysis on specific LOD scores, we also develop influence analysis methods on the shape of the LOD score curves. A simulation-based method is proposed to assess the significance of the influence of the individuals. These methods are shown useful in the influence analysis of a real dataset of an experimental population from an F2 mouse cross. By receiver operating characteristic analysis, we confirm that the proposed methods show better performance than existing diagnostics. © 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluating Language Environment Analysis System Performance for Chinese: A Pilot Study in Shanghai

ERIC Educational Resources Information Center

Gilkerson, Jill; Zhang, Yiwen; Xu, Dongxin; Richards, Jeffrey A.; Xu, Xiaojuan; Jiang, Fan; Harnsberger, James; Topping, Keith

2015-01-01

Purpose: The purpose of this study was to evaluate performance of the Language Environment Analysis (LENA) automated language-analysis system for the Chinese Shanghai dialect and Mandarin (SDM) languages. Method: Volunteer parents of 22 children aged 3-23 months were recruited in Shanghai. Families provided daylong in-home audio recordings using…

Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Hearn, Tristan; Hendricks, Eric; Chin, Jeffrey; Gray, Justin; Moore, Kenneth T.

2016-01-01

A new engine cycle analysis tool, called Pycycle, was built using the OpenMDAO framework. Pycycle provides analytic derivatives allowing for an efficient use of gradient-based optimization methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.

Efficient genotype compression and analysis of large genetic variation datasets

PubMed Central

Layer, Ryan M.; Kindlon, Neil; Karczewski, Konrad J.; Quinlan, Aaron R.

2015-01-01

Genotype Query Tools (GQT) is a new indexing strategy that expedites analyses of genome variation datasets in VCF format based on sample genotypes, phenotypes and relationships. GQT’s compressed genotype index minimizes decompression for analysis, and performance relative to existing methods improves with cohort size. We show substantial (up to 443 fold) performance gains over existing methods and demonstrate GQT’s utility for exploring massive datasets involving thousands to millions of genomes. PMID:26550772

Paule‐Mandel estimators for network meta‐analysis with random inconsistency effects

PubMed Central

Veroniki, Areti Angeliki; Law, Martin; Tricco, Andrea C.; Baker, Rose

2017-01-01

Network meta‐analysis is used to simultaneously compare multiple treatments in a single analysis. However, network meta‐analyses may exhibit inconsistency, where direct and different forms of indirect evidence are not in agreement with each other, even after allowing for between‐study heterogeneity. Models for network meta‐analysis with random inconsistency effects have the dual aim of allowing for inconsistencies and estimating average treatment effects across the whole network. To date, two classical estimation methods for fitting this type of model have been developed: a method of moments that extends DerSimonian and Laird's univariate method and maximum likelihood estimation. However, the Paule and Mandel estimator is another recommended classical estimation method for univariate meta‐analysis. In this paper, we extend the Paule and Mandel method so that it can be used to fit models for network meta‐analysis with random inconsistency effects. We apply all three estimation methods to a variety of examples that have been used previously and we also examine a challenging new dataset that is highly heterogenous. We perform a simulation study based on this new example. We find that the proposed Paule and Mandel method performs satisfactorily and generally better than the previously proposed method of moments because it provides more accurate inferences. Furthermore, the Paule and Mandel method possesses some advantages over likelihood‐based methods because it is both semiparametric and requires no convergence diagnostics. Although restricted maximum likelihood estimation remains the gold standard, the proposed methodology is a fully viable alternative to this and other estimation methods. PMID:28585257

A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study.

PubMed

AbdelRahman, Samir E; Zhang, Mingyuan; Bray, Bruce E; Kawamoto, Kensaku

2014-05-27

The aim of this study was to propose an analytical approach to develop high-performing predictive models for congestive heart failure (CHF) readmission using an operational dataset with incomplete records and changing data over time. Our analytical approach involves three steps: pre-processing, systematic model development, and risk factor analysis. For pre-processing, variables that were absent in >50% of records were removed. Moreover, the dataset was divided into a validation dataset and derivation datasets which were separated into three temporal subsets based on changes to the data over time. For systematic model development, using the different temporal datasets and the remaining explanatory variables, the models were developed by combining the use of various (i) statistical analyses to explore the relationships between the validation and the derivation datasets; (ii) adjustment methods for handling missing values; (iii) classifiers; (iv) feature selection methods; and (iv) discretization methods. We then selected the best derivation dataset and the models with the highest predictive performance. For risk factor analysis, factors in the highest-performing predictive models were analyzed and ranked using (i) statistical analyses of the best derivation dataset, (ii) feature rankers, and (iii) a newly developed algorithm to categorize risk factors as being strong, regular, or weak. The analysis dataset consisted of 2,787 CHF hospitalizations at University of Utah Health Care from January 2003 to June 2013. In this study, we used the complete-case analysis and mean-based imputation adjustment methods; the wrapper subset feature selection method; and four ranking strategies based on information gain, gain ratio, symmetrical uncertainty, and wrapper subset feature evaluators. The best-performing models resulted from the use of a complete-case analysis derivation dataset combined with the Class-Attribute Contingency Coefficient discretization method and a voting classifier which averaged the results of multi-nominal logistic regression and voting feature intervals classifiers. Of 42 final model risk factors, discharge disposition, discretized age, and indicators of anemia were the most significant. This model achieved a c-statistic of 86.8%. The proposed three-step analytical approach enhanced predictive model performance for CHF readmissions. It could potentially be leveraged to improve predictive model performance in other areas of clinical medicine.

On the Performance of T2∗ Correction Methods for Quantification of Hepatic Fat Content

PubMed Central

Reeder, Scott B.; Bice, Emily K.; Yu, Huanzhou; Hernando, Diego; Pineda, Angel R.

2014-01-01

Nonalcoholic fatty liver disease is the most prevalent chronic liver disease in Western societies. MRI can quantify liver fat, the hallmark feature of nonalcoholic fatty liver disease, so long as multiple confounding factors including T2∗ decay are addressed. Recently developed MRI methods that correct for T2∗ to improve the accuracy of fat quantification either assume a common T2∗ (single- T2∗) for better stability and noise performance or independently estimate the T2∗ for water and fat (dual- T2∗) for reduced bias, but with noise performance penalty. In this study, the tradeoff between bias and variance for different T2∗ correction methods is analyzed using the Cramér-Rao bound analysis for biased estimators and is validated using Monte Carlo experiments. A noise performance metric for estimation of fat fraction is proposed. Cramér-Rao bound analysis for biased estimators was used to compute the metric at different echo combinations. Optimization was performed for six echoes and typical T2∗ values. This analysis showed that all methods have better noise performance with very short first echo times and echo spacing of ∼π/2 for single- T2∗ correction, and ∼2π/3 for dual- T2∗ correction. Interestingly, when an echo spacing and first echo shift of ∼π/2 are used, methods without T2∗ correction have less than 5% bias in the estimates of fat fraction. PMID:21661045

The UHPLC-DAD fingerprinting method for analysis of extracellular metabolites of fungi of the genus Geosmithia (Acomycota: Hypocreales).

PubMed

Tylová, Tereza; Kolařík, Miroslav; Olšovská, Jana

2011-07-01

A new simple ultra-high-performance liquid chromatography method with diode array detection (UHPLC-DAD) was developed for chemical fingerprinting analysis of extracellular metabolites in fermentation broth of Geosmithia spp. The SPE method employing Oasis MCX strong cation-exchange mixed-mode polymeric sorbent was chosen for extraction of the metabolites. The analyses were performed on an Acquity UPLC BEH C18 column (100 × 2.1 mm i.d.; particle size, 1.7 μm; Waters) using a gradient elution program with an aqueous solution of trifluoroacetic acid and acetonitrile as the mobile phase. The applicability of the method was proved by analysis of 38 strains produced by different species and isolated from different sources (hosts). The results revealed the correlation of obtained UHPLC-DAD fingerprints with taxonomical identity.

Detecting chaos in particle accelerators through the frequency map analysis method.

PubMed

Papaphilippou, Yannis

2014-06-01

The motion of beams in particle accelerators is dominated by a plethora of non-linear effects, which can enhance chaotic motion and limit their performance. The application of advanced non-linear dynamics methods for detecting and correcting these effects and thereby increasing the region of beam stability plays an essential role during the accelerator design phase but also their operation. After describing the nature of non-linear effects and their impact on performance parameters of different particle accelerator categories, the theory of non-linear particle motion is outlined. The recent developments on the methods employed for the analysis of chaotic beam motion are detailed. In particular, the ability of the frequency map analysis method to detect chaotic motion and guide the correction of non-linear effects is demonstrated in particle tracking simulations but also experimental data.

Advancing Usability Evaluation through Human Reliability Analysis

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

Ronald L. Boring; David I. Gertman

2005-07-01

This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probabilitymore » of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.« less

Comparisons of non-Gaussian statistical models in DNA methylation analysis.

PubMed

Ma, Zhanyu; Teschendorff, Andrew E; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-06-16

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance.

Comparisons of Non-Gaussian Statistical Models in DNA Methylation Analysis

PubMed Central

Ma, Zhanyu; Teschendorff, Andrew E.; Yu, Hong; Taghia, Jalil; Guo, Jun

2014-01-01

As a key regulatory mechanism of gene expression, DNA methylation patterns are widely altered in many complex genetic diseases, including cancer. DNA methylation is naturally quantified by bounded support data; therefore, it is non-Gaussian distributed. In order to capture such properties, we introduce some non-Gaussian statistical models to perform dimension reduction on DNA methylation data. Afterwards, non-Gaussian statistical model-based unsupervised clustering strategies are applied to cluster the data. Comparisons and analysis of different dimension reduction strategies and unsupervised clustering methods are presented. Experimental results show that the non-Gaussian statistical model-based methods are superior to the conventional Gaussian distribution-based method. They are meaningful tools for DNA methylation analysis. Moreover, among several non-Gaussian methods, the one that captures the bounded nature of DNA methylation data reveals the best clustering performance. PMID:24937687

Classifying Facial Actions

PubMed Central

Donato, Gianluca; Bartlett, Marian Stewart; Hager, Joseph C.; Ekman, Paul; Sejnowski, Terrence J.

2010-01-01

The Facial Action Coding System (FACS) [23] is an objective method for quantifying facial movement in terms of component actions. This system is widely used in behavioral investigations of emotion, cognitive processes, and social interaction. The coding is presently performed by highly trained human experts. This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. These techniques include analysis of facial motion through estimation of optical flow; holistic spatial analysis, such as principal component analysis, independent component analysis, local feature analysis, and linear discriminant analysis; and methods based on the outputs of local filters, such as Gabor wavelet representations and local principal components. Performance of these systems is compared to naive and expert human subjects. Best performances were obtained using the Gabor wavelet representation and the independent component representation, both of which achieved 96 percent accuracy for classifying 12 facial actions of the upper and lower face. The results provide converging evidence for the importance of using local filters, high spatial frequencies, and statistical independence for classifying facial actions. PMID:21188284

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.

Relaxation mode analysis of a peptide system: comparison with principal component analysis.

PubMed

Mitsutake, Ayori; Iijima, Hiromitsu; Takano, Hiroshi

2011-10-28

This article reports the first attempt to apply the relaxation mode analysis method to a simulation of a biomolecular system. In biomolecular systems, the principal component analysis is a well-known method for analyzing the static properties of fluctuations of structures obtained by a simulation and classifying the structures into some groups. On the other hand, the relaxation mode analysis has been used to analyze the dynamic properties of homopolymer systems. In this article, a long Monte Carlo simulation of Met-enkephalin in gas phase has been performed. The results are analyzed by the principal component analysis and relaxation mode analysis methods. We compare the results of both methods and show the effectiveness of the relaxation mode analysis.

Philosophy of ATHEANA

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

Bley, D.C.; Cooper, S.E.; Forester, J.A.

ATHEANA, a second-generation Human Reliability Analysis (HRA) method integrates advances in psychology with engineering, human factors, and Probabilistic Risk Analysis (PRA) disciplines to provide an HRA quantification process and PRA modeling interface that can accommodate and represent human performance in real nuclear power plant events. The method uses the characteristics of serious accidents identified through retrospective analysis of serious operational events to set priorities in a search process for significant human failure events, unsafe acts, and error-forcing context (unfavorable plant conditions combined with negative performance-shaping factors). ATHEANA has been tested in a demonstration project at an operating pressurized water reactor.

A comparison of two microscale laboratory reporting methods in a secondary chemistry classroom

NASA Astrophysics Data System (ADS)

Martinez, Lance Michael

This study attempted to determine if there was a difference between the laboratory achievement of students who used a modified reporting method and those who used traditional laboratory reporting. The study also determined the relationships between laboratory performance scores and the independent variables score on the Group Assessment of Logical Thinking (GALT) test, chronological age in months, gender, and ethnicity for each of the treatment groups. The study was conducted using 113 high school students who were enrolled in first-year general chemistry classes at Pueblo South High School in Colorado. The research design used was the quasi-experimental Nonequivalent Control Group Design. The statistical treatment consisted of the Multiple Regression Analysis and the Analysis of Covariance. Based on the GALT, students in the two groups were generally in the concrete and transitional stages of the Piagetian cognitive levels. The findings of the study revealed that the traditional and the modified methods of laboratory reporting did not have any effect on the laboratory performance outcome of the subjects. However, the students who used the traditional method of reporting showed a higher laboratory performance score when evaluation was conducted using the New Standards rubric recommended by the state. Multiple Regression Analysis revealed that there was a significant relationship between the criterion variable student laboratory performance outcome of individuals who employed traditional laboratory reporting methods and the composite set of predictor variables. On the contrary, there was no significant relationship between the criterion variable student laboratory performance outcome of individuals who employed modified laboratory reporting methods and the composite set of predictor variables.

Comparing the performance of biomedical clustering methods.

PubMed

Wiwie, Christian; Baumbach, Jan; Röttger, Richard

2015-11-01

Identifying groups of similar objects is a popular first step in biomedical data analysis, but it is error-prone and impossible to perform manually. Many computational methods have been developed to tackle this problem. Here we assessed 13 well-known methods using 24 data sets ranging from gene expression to protein domains. Performance was judged on the basis of 13 common cluster validity indices. We developed a clustering analysis platform, ClustEval (http://clusteval.mpi-inf.mpg.de), to promote streamlined evaluation, comparison and reproducibility of clustering results in the future. This allowed us to objectively evaluate the performance of all tools on all data sets with up to 1,000 different parameter sets each, resulting in a total of more than 4 million calculated cluster validity indices. We observed that there was no universal best performer, but on the basis of this wide-ranging comparison we were able to develop a short guideline for biomedical clustering tasks. ClustEval allows biomedical researchers to pick the appropriate tool for their data type and allows method developers to compare their tool to the state of the art.

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time‐to‐Event Analysis

PubMed Central

Gong, Xiajing; Hu, Meng

2018-01-01

Abstract Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time‐to‐event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high‐dimensional data featured by a large number of predictor variables. Our results showed that ML‐based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high‐dimensional data. The prediction performances of ML‐based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML‐based methods provide a powerful tool for time‐to‐event analysis, with a built‐in capacity for high‐dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. PMID:29536640

Modulated Hebb-Oja learning rule--a method for principal subspace analysis.

PubMed

Jankovic, Marko V; Ogawa, Hidemitsu

2006-03-01

This paper presents analysis of the recently proposed modulated Hebb-Oja (MHO) method that performs linear mapping to a lower-dimensional subspace. Principal component subspace is the method that will be analyzed. Comparing to some other well-known methods for yielding principal component subspace (e.g., Oja's Subspace Learning Algorithm), the proposed method has one feature that could be seen as desirable from the biological point of view--synaptic efficacy learning rule does not need the explicit information about the value of the other efficacies to make individual efficacy modification. Also, the simplicity of the "neural circuits" that perform global computations and a fact that their number does not depend on the number of input and output neurons, could be seen as good features of the proposed method.

Fluorescence-based methods for detecting caries lesions: systematic review, meta-analysis and sources of heterogeneity.

PubMed

Gimenez, Thais; Braga, Mariana Minatel; Raggio, Daniela Procida; Deery, Chris; Ricketts, David N; Mendes, Fausto Medeiros

2013-01-01

Fluorescence-based methods have been proposed to aid caries lesion detection. Summarizing and analysing findings of studies about fluorescence-based methods could clarify their real benefits. We aimed to perform a comprehensive systematic review and meta-analysis to evaluate the accuracy of fluorescence-based methods in detecting caries lesions. Two independent reviewers searched PubMed, Embase and Scopus through June 2012 to identify papers/articles published. Other sources were checked to identify non-published literature. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS AND DIAGNOSTIC METHODS: The eligibility criteria were studies that: (1) have assessed the accuracy of fluorescence-based methods of detecting caries lesions on occlusal, approximal or smooth surfaces, in both primary or permanent human teeth, in the laboratory or clinical setting; (2) have used a reference standard; and (3) have reported sufficient data relating to the sample size and the accuracy of methods. A diagnostic 2×2 table was extracted from included studies to calculate the pooled sensitivity, specificity and overall accuracy parameters (Diagnostic Odds Ratio and Summary Receiver-Operating curve). The analyses were performed separately for each method and different characteristics of the studies. The quality of the studies and heterogeneity were also evaluated. Seventy five studies met the inclusion criteria from the 434 articles initially identified. The search of the grey or non-published literature did not identify any further studies. In general, the analysis demonstrated that the fluorescence-based method tend to have similar accuracy for all types of teeth, dental surfaces or settings. There was a trend of better performance of fluorescence methods in detecting more advanced caries lesions. We also observed moderate to high heterogeneity and evidenced publication bias. Fluorescence-based devices have similar overall performance; however, better accuracy in detecting more advanced caries lesions has been observed.

Analysis of Expedited Defense Contracting Methods in the Acquisition of Emerging Technology

DTIC Science & Technology

2016-12-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT ANALYSIS OF EXPEDITED DEFENSE CONTRACTING METHODS IN THE...CONTRACTING METHODS IN THE ACQUISITION OF EMERGING TECHNOLOGY 5. FUNDING NUMBERS 6. AUTHOR(S) Jacob D. Sabin and Mark K. Zakner 7. PERFORMING...firms. The DOD has authority for applying non-traditional contracting methods to better adapt to this competitive marketplace. This project studied non

Analysis of Ethanolamines: Validation of Semi-Volatile Analysis by HPLC-MS/MS by EPA Method MS888

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

Owens, J; Vu, A; Koester, C

The Environmental Protection Agency's (EPA) Region 5 Chicago Regional Laboratory (CRL) developed a method titled 'Analysis of Diethanolamine, Triethanolamine, n-Methyldiethanolamine, and n-Ethyldiethanolamine in Water by Single Reaction Monitoring Liquid Chromatography/Tandem Mass Spectrometry (LC/MS/MS): EPA Method MS888'. This draft standard operating procedure (SOP) was distributed to multiple EPA laboratories and to Lawrence Livermore National Laboratory, which was tasked to serve as a reference laboratory for EPA's Environmental Reference Laboratory Network (ERLN) and to develop and validate analytical procedures. The primary objective of this study was to validate and verify the analytical procedures described in 'EPA Method MS888' for analysis of themore » listed ethanolamines in aqueous samples. The gathered data from this validation study will be used to: (1) demonstrate analytical method performance; (2) generate quality control acceptance criteria; and (3) revise the SOP to provide a validated method that would be available for use during a homeland security event. The data contained in this report will be compiled, by EPA CRL, with data generated by other EPA Regional laboratories so that performance metrics of 'EPA Method MS888' can be determined.« less

TCP Packet Trace Analysis. M.S. Thesis

NASA Technical Reports Server (NTRS)

Shepard, Timothy J.

1991-01-01

Examination of a trace of packets collected from the network is often the only method available for diagnosing protocol performance problems in computer networks. This thesis explores the use of packet traces to diagnose performance problems of the transport protocol TCP. Unfortunately, manual examination of these traces can be so tedious that effective analysis is not possible. The primary contribution of this thesis is a graphical method of displaying the packet trace which greatly reduce, the tediousness of examining a packet trace. The graphical method is demonstrated by the examination of some packet traces of typical TCP connections. The performance of two different implementations of TCP sending data across a particular network path is compared. Traces many thousands of packets long are used to demonstrate how effectively the graphical method simplifies examination of long complicated traces. In the comparison of the two TCP implementations, the burstiness of the TCP transmitter appeared to be related to the achieved throughput. A method of quantifying this burstiness is presented and its possible relevance to understanding the performance of TCP is discussed.

Multicenter Evaluation of Epidemiological Typing of Methicillin-Resistant Staphylococcus aureus Strains by Repetitive-Element PCR Analysis

PubMed Central

Deplano, Ariane; Schuermans, Annette; Van Eldere, Johan; Witte, Wolfgang; Meugnier, Hèléne; Etienne, Jerome; Grundmann, Hajo; Jonas, Daniel; Noordhoek, Gerda T.; Dijkstra, Jolanda; van Belkum, Alex; van Leeuwen, Willem; Tassios, Panayotis T.; Legakis, Nicholas J.; van der Zee, Anneke; Bergmans, Anneke; Blanc, Dominique S.; Tenover, Fred C.; Cookson, Barry C.; O'Neil, Gael; Struelens, Marc J.

2000-01-01

Rapid and efficient epidemiologic typing systems would be useful to monitor transmission of methicillin-resistant Staphylococcus aureus (MRSA) at both local and interregional levels. To evaluate the intralaboratory performance and interlaboratory reproducibility of three recently developed repeat-element PCR (rep-PCR) methods for the typing of MRSA, 50 MRSA strains characterized by pulsed-field gel electrophoresis (PFGE) (SmaI) analysis and epidemiological data were blindly typed by inter-IS256, 16S-23S ribosomal DNA (rDNA), and MP3 PCR in 12 laboratories in eight countries using standard reagents and protocols. Performance of typing was defined by reproducibility (R), discriminatory power (D), and agreement with PFGE analysis. Interlaboratory reproducibility of pattern and type classification was assessed visually and using gel analysis software. Each typing method showed a different performance level in each center. In the center performing best with each method, inter-IS256 PCR typing achieved R = 100% and D = 100%; 16S-23S rDNA PCR, R = 100% and D = 82%; and MP3 PCR, R = 80% and D = 83%. Concordance between rep-PCR type and PFGE type ranged by center: 70 to 90% for inter-IS256 PCR, 44 to 57% for 16S-23S rDNA PCR, and 53 to 54% for MP3 PCR analysis. In conclusion, the performance of inter-IS256 PCR typing was similar to that of PFGE analysis in some but not all centers, whereas other rep-PCR protocols showed lower discrimination and intralaboratory reproducibility. None of these assays, however, was sufficiently reproducible for interlaboratory exchange of data. PMID:11015358

Evaluating Gene Set Enrichment Analysis Via a Hybrid Data Model

PubMed Central

Hua, Jianping; Bittner, Michael L.; Dougherty, Edward R.

2014-01-01

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance. PMID:24558298

Summary of Technical Operations, 1991

DTIC Science & Technology

1992-01-01

exploit commonality. The project is using the Feature-Oriented Domain Analysis ( FODA ) method, developed by the project in 1990, to perform this...the development of new movement control software. The analysis will also serve as a means of improving the FODA method. The results of this analysis ...STARS environment. The NASA Program Office has officially decided to expand the use of Rate Monotonic Analysis (RMA), which was originally isolated to

Shape design sensitivity analysis and optimal design of structural systems

NASA Technical Reports Server (NTRS)

Choi, Kyung K.

1987-01-01

The material derivative concept of continuum mechanics and an adjoint variable method of design sensitivity analysis are used to relate variations in structural shape to measures of structural performance. A domain method of shape design sensitivity analysis is used to best utilize the basic character of the finite element method that gives accurate information not on the boundary but in the domain. Implementation of shape design sensitivty analysis using finite element computer codes is discussed. Recent numerical results are used to demonstrate the accuracy obtainable using the method. Result of design sensitivity analysis is used to carry out design optimization of a built-up structure.

Liquid chromatography/electrospray ionization/isotopic dilution mass spectrometry analysis of n-(phosphonomethyl) glycine and mass spectrometry analysis of aminomethyl phosphonic acid in environmental water and vegetation matrixes.

PubMed

Grey, L; Nguyen, B; Yang, P

2001-01-01

A liquid chromatography/electrospray/mass spectrometry (LC/ES/MS) method was developed for the analysis of glyphosate (n-phosphonomethyl glycine) and its metabolite, aminomethyl phosphonic acid (AMPA) using isotope-labelled glyphosate as a method surrogate. Optimized parameters were achieved to derivatize glyphosate and AMPA using 9-fluorenylmethyl chloroformate (FMOC-Cl) in borate buffer prior to a reversed-phase LC analysis. Method spike recovery data obtained using laboratory and real world sample matrixes indicated an excellent correlation between the recovery of the native and isotope-labelled glyphosate. Hence, the first performance-based, isotope dilution MS method with superior precision, accuracy, and data quality was developed for the analysis of glyphosate. There was, however, no observable correlation between the isotope-labelled glyphosate and AMPA. Thus, the use of this procedure for the accurate analysis of AMPA was not supported. Method detection limits established using standard U.S. Environmental Protection Agency protocol were 0.06 and 0.30 microg/L, respectively, for glyphosate and AMPA in water matrixes and 0.11 and 0.53 microg/g, respectively, in vegetation matrixes. Problems, solutions, and the method performance data related to the analysis of chlorine-treated drinking water samples are discussed. Applying this method to other environmental matrixes, e.g., soil, with minimum modifications is possible, assuring accurate, multimedia studies of glyphosate concentration in the environment and the delivery of useful multimedia information for regulatory applications.

Inertial Sensor Technology for Elite Swimming Performance Analysis: A Systematic Review

PubMed Central

Mooney, Robert; Corley, Gavin; Godfrey, Alan; Quinlan, Leo R; ÓLaighin, Gearóid

2015-01-01

Technical evaluation of swimming performance is an essential factor of elite athletic preparation. Novel methods of analysis, incorporating body worn inertial sensors (i.e., Microelectromechanical systems, or MEMS, accelerometers and gyroscopes), have received much attention recently from both research and commercial communities as an alternative to video-based approaches. This technology may allow for improved analysis of stroke mechanics, race performance and energy expenditure, as well as real-time feedback to the coach, potentially enabling more efficient, competitive and quantitative coaching. The aim of this paper is to provide a systematic review of the literature related to the use of inertial sensors for the technical analysis of swimming performance. This paper focuses on providing an evaluation of the accuracy of different feature detection algorithms described in the literature for the analysis of different phases of swimming, specifically starts, turns and free-swimming. The consequences associated with different sensor attachment locations are also considered for both single and multiple sensor configurations. Additional information such as this should help practitioners to select the most appropriate systems and methods for extracting the key performance related parameters that are important to them for analysing their swimmers’ performance and may serve to inform both applied and research practices. PMID:26712760

Operation Team Spirit: Program Review and Analysis

DTIC Science & Technology

2009-06-01

research was strictly qualitative in nature. The specific method being used was exploratory case study analysis... study , method is used for the specific acts of conducting research , while methodology refers to the qualitative nature of research performed. While...the researcher . According to Leedy and Ormrod (2005), some of the types of methods and their respective purposes include: • Case study :

Why conventional detection methods fail in identifying the existence of contamination events.

PubMed

Liu, Shuming; Li, Ruonan; Smith, Kate; Che, Han

2016-04-15

Early warning systems are widely used to safeguard water security, but their effectiveness has raised many questions. To understand why conventional detection methods fail to identify contamination events, this study evaluates the performance of three contamination detection methods using data from a real contamination accident and two artificial datasets constructed using a widely applied contamination data construction approach. Results show that the Pearson correlation Euclidean distance (PE) based detection method performs better for real contamination incidents, while the Euclidean distance method (MED) and linear prediction filter (LPF) method are more suitable for detecting sudden spike-like variation. This analysis revealed why the conventional MED and LPF methods failed to identify existence of contamination events. The analysis also revealed that the widely used contamination data construction approach is misleading. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Comparison of Measurement Equivalence Methods Based on Confirmatory Factor Analysis and Item Response Theory.

ERIC Educational Resources Information Center

Flowers, Claudia P.; Raju, Nambury S.; Oshima, T. C.

Current interest in the assessment of measurement equivalence emphasizes two methods of analysis, linear, and nonlinear procedures. This study simulated data using the graded response model to examine the performance of linear (confirmatory factor analysis or CFA) and nonlinear (item-response-theory-based differential item function or IRT-Based…

Efficacy of Virtual Patients in Medical Education: A Meta-Analysis of Randomized Studies

ERIC Educational Resources Information Center

Consorti, Fabrizio; Mancuso, Rosaria; Nocioni, Martina; Piccolo, Annalisa

2012-01-01

A meta-analysis was performed to assess the Effect Size (ES) from randomized studies comparing the effect of educational interventions in which Virtual patients (VPs) were used either as an alternative method or additive to usual curriculum versus interventions based on more traditional methods. Meta-analysis was designed, conducted and reported…

Performance of Blind Source Separation Algorithms for FMRI Analysis using a Group ICA Method

PubMed Central

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D.

2007-01-01

Independent component analysis (ICA) is a popular blind source separation (BSS) technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist, however the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely information maximization, maximization of non-gaussianity, joint diagonalization of cross-cumulant matrices, and second-order correlation based methods when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study the variability among different ICA algorithms and propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA, and JADE all yield reliable results; each having their strengths in specific areas. EVD, an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for the iterative ICA algorithms, it is important to investigate the variability of the estimates from different runs. We test the consistency of the iterative algorithms, Infomax and FastICA, by running the algorithm a number of times with different initializations and note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis. PMID:17540281

Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

PubMed

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D

2007-06-01

Independent component analysis (ICA) is a popular blind source separation technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist; however, the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely, information maximization, maximization of non-Gaussianity, joint diagonalization of cross-cumulant matrices and second-order correlation-based methods, when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study variability among different ICA algorithms, and we propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA and joint approximate diagonalization of eigenmatrices (JADE) all yield reliable results, with each having its strengths in specific areas. Eigenvalue decomposition (EVD), an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for iterative ICA algorithms, it is important to investigate the variability of estimates from different runs. We test the consistency of the iterative algorithms Infomax and FastICA by running the algorithm a number of times with different initializations, and we note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies

PubMed Central

Azadeh, Ali; Sheikhalishahi, Mohammad

2014-01-01

Background A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors. PMID:26106505

Trajectories for High Specific Impulse High Specific Power Deep Space Exploration

NASA Technical Reports Server (NTRS)

Polsgrove, T.; Adams, R. B.; Brady, Hugh J. (Technical Monitor)

2002-01-01

Preliminary results are presented for two methods to approximate the mission performance of high specific impulse high specific power vehicles. The first method is based on an analytical approximation derived by Williams and Shepherd and can be used to approximate mission performance to outer planets and interstellar space. The second method is based on a parametric analysis of trajectories created using the well known trajectory optimization code, VARITOP. This parametric analysis allows the reader to approximate payload ratios and optimal power requirements for both one-way and round-trip missions. While this second method only addresses missions to and from Jupiter, future work will encompass all of the outer planet destinations and some interstellar precursor missions.

Response of the Alliance 1 Proof-of-Concept Airplane Under Gust Loads

NASA Technical Reports Server (NTRS)

Naser, A. S.; Pototzky, A. S.; Spain, C. V.

2001-01-01

This report presents the work performed by Lockheed Martin's Langley Program Office in support of NASA's Environmental Research Aircraft and Sensor Technology (ERAST) program. The primary purpose of this work was to develop and demonstrate a gust analysis method which accounts for the span-wise variation of gust velocity. This is important because these unmanned aircraft having high aspect ratios and low wing loading are very flexible, and fly at low speeds. The main focus of the work was therefore to perform a two-dimensional Power Spectrum Density (PSD) analysis of the Alliance 1 Proof-of-Concept Unmanned Aircraft, As of this writing, none of the aircraft described in this report have been constructed. They are concepts represented by analytical models. The process first involved the development of suitable structural and aeroelastic Finite Element Models (FEM). This was followed by development of a one-dimensional PSD gust analysis, and then the two-dimensional (PSD) analysis of the Alliance 1. For further validation and comparison, two additional analyses were performed. A two-dimensional PSD gust analysis was performed on a simplet MSC/NASTRAN example problem. Finally a one-dimensional discrete gust analysis was performed on Alliance 1. This report describes this process, shows the relevant comparisons between analytical methods, and discusses the physical meanings of the results.

Determining characteristics of artificial near-Earth objects using observability analysis

NASA Astrophysics Data System (ADS)

Friedman, Alex M.; Frueh, Carolin

2018-03-01

Observability analysis is a method for determining whether a chosen state of a system can be determined from the output or measurements. Knowledge of state information availability resulting from observability analysis leads to improved sensor tasking for observation of orbital debris and better control of active spacecraft. This research performs numerical observability analysis of artificial near-Earth objects. Analysis of linearization methods and state transition matrices is performed to determine the viability of applying linear observability methods to the nonlinear orbit problem. Furthermore, pre-whitening is implemented to reformulate classical observability analysis. In addition, the state in observability analysis is typically composed of position and velocity; however, including object characteristics beyond position and velocity can be crucial for precise orbit propagation. For example, solar radiation pressure has a significant impact on the orbit of high area-to-mass ratio objects in geosynchronous orbit. Therefore, determining the time required for solar radiation pressure parameters to become observable is important for understanding debris objects. In order to compare observability analysis results with and without measurement noise and an extended state, quantitative measures of observability are investigated and implemented.

Determination of mycotoxins produced by Fusarium isolates from banana fruits by capillary gas chromatography and high-performance liquid chromatography.

PubMed

Jiménez, M; Mateo, R

1997-08-22

A method of analysis for trichothecenes (nivalenol, deoxynivalenol, 3- and 15-acetyldeoxynivalenol, diacetoxyscirpenol, neosolaniol, T-2 tetraol, T-2 and HT-2 toxins), zearalenone and zearalenols, and another method for determination of fumonisin B1 are described and applied to cultures of Fusarium isolated from bananas. Both methods were adapted from different techniques of extraction, clean-up and determination of these mycotoxins. The first method involves extraction with methanol-1% aqueous sodium chloride, clean-up of extracts by partition with hexane and dichloromethane, additional solid reversed-phase clean-up and analysis of two eluates by both high-performance liquid chromatography with ultraviolet detection and capillary gas chromatography. The method for fumonisin B1 implies extraction with aqueous methanol, concentration, clean-up with water and methanol on Amberlite XAD-2 column, formation of a fluorescent 4-fluoro-7-nitrobenzofurazan derivative and analysis by high-performance liquid chromatography with fluorescence detection. Both procedures give good limits of detection and recoveries, and are considered suitable for the detection and quantification of the studied toxins in corn and rice cultures of Fusarium spp. isolated from banana fruits.

Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis

PubMed Central

2011-01-01

Background The computer-aided identification of specific gait patterns is an important issue in the assessment of Parkinson's disease (PD). In this study, a computer vision-based gait analysis approach is developed to assist the clinical assessments of PD with kernel-based principal component analysis (KPCA). Method Twelve PD patients and twelve healthy adults with no neurological history or motor disorders within the past six months were recruited and separated according to their "Non-PD", "Drug-On", and "Drug-Off" states. The participants were asked to wear light-colored clothing and perform three walking trials through a corridor decorated with a navy curtain at their natural pace. The participants' gait performance during the steady-state walking period was captured by a digital camera for gait analysis. The collected walking image frames were then transformed into binary silhouettes for noise reduction and compression. Using the developed KPCA-based method, the features within the binary silhouettes can be extracted to quantitatively determine the gait cycle time, stride length, walking velocity, and cadence. Results and Discussion The KPCA-based method uses a feature-extraction approach, which was verified to be more effective than traditional image area and principal component analysis (PCA) approaches in classifying "Non-PD" controls and "Drug-Off/On" PD patients. Encouragingly, this method has a high accuracy rate, 80.51%, for recognizing different gaits. Quantitative gait parameters are obtained, and the power spectrums of the patients' gaits are analyzed. We show that that the slow and irregular actions of PD patients during walking tend to transfer some of the power from the main lobe frequency to a lower frequency band. Our results indicate the feasibility of using gait performance to evaluate the motor function of patients with PD. Conclusion This KPCA-based method requires only a digital camera and a decorated corridor setup. The ease of use and installation of the current method provides clinicians and researchers a low cost solution to monitor the progression of and the treatment to PD. In summary, the proposed method provides an alternative to perform gait analysis for patients with PD. PMID:22074315

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis

PubMed Central

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization. PMID:29377956

Ultra-high-performance supercritical fluid chromatography with quadrupole-time-of-flight mass spectrometry (UHPSFC/QTOF-MS) for analysis of lignin-derived monomeric compounds in processed lignin samples.

PubMed

Prothmann, Jens; Sun, Mingzhe; Spégel, Peter; Sandahl, Margareta; Turner, Charlotta

2017-12-01

The conversion of lignin to potentially high-value low molecular weight compounds often results in complex mixtures of monomeric and oligomeric compounds. In this study, a method for the quantitative and qualitative analysis of 40 lignin-derived compounds using ultra-high-performance supercritical fluid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UHPSFC/QTOF-MS) has been developed. Seven different columns were explored for maximum selectivity. Makeup solvent composition and ion source settings were optimised using a D-optimal design of experiment (DoE). Differently processed lignin samples were analysed and used for the method validation. The new UHPSFC/QTOF-MS method showed good separation of the 40 compounds within only 6-min retention time, and out of these, 36 showed high ionisation efficiency in negative electrospray ionisation mode. Graphical abstract A rapid and selective method for the quantitative and qualitative analysis of 40 lignin-derived compounds using ultra-high-performance supercritical fluid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UHPSFC/QTOF-MS).

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

PubMed

Zu, Xianghuan; Yang, Chuanlei; Wang, Hechun; Wang, Yinyan

2018-01-01

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

Measuring farm sustainability using data envelope analysis with principal components: the case of Wisconsin cranberry.

PubMed

Dong, Fengxia; Mitchell, Paul D; Colquhoun, Jed

2015-01-01

Measuring farm sustainability performance is a crucial component for improving agricultural sustainability. While extensive assessments and indicators exist that reflect the different facets of agricultural sustainability, because of the relatively large number of measures and interactions among them, a composite indicator that integrates and aggregates over all variables is particularly useful. This paper describes and empirically evaluates a method for constructing a composite sustainability indicator that individually scores and ranks farm sustainability performance. The method first uses non-negative polychoric principal component analysis to reduce the number of variables, to remove correlation among variables and to transform categorical variables to continuous variables. Next the method applies common-weight data envelope analysis to these principal components to individually score each farm. The method solves weights endogenously and allows identifying important practices in sustainability evaluation. An empirical application to Wisconsin cranberry farms finds heterogeneity in sustainability practice adoption, implying that some farms could adopt relevant practices to improve the overall sustainability performance of the industry. Copyright © 2014 Elsevier Ltd. All rights reserved.

Toward Capturing Momentary Changes of Heart Rate Variability by a Dynamic Analysis Method

PubMed Central

Zhang, Haoshi; Zhu, Mingxing; Zheng, Yue; Li, Guanglin

2015-01-01

The analysis of heart rate variability (HRV) has been performed on long-term electrocardiography (ECG) recordings (12~24 hours) and short-term recordings (2~5 minutes), which may not capture momentary change of HRV. In this study, we present a new method to analyze the momentary HRV (mHRV). The ECG recordings were segmented into a series of overlapped HRV analysis windows with a window length of 5 minutes and different time increments. The performance of the proposed method in delineating the dynamics of momentary HRV measurement was evaluated with four commonly used time courses of HRV measures on both synthetic time series and real ECG recordings from human subjects and dogs. Our results showed that a smaller time increment could capture more dynamical information on transient changes. Considering a too short increment such as 10 s would cause the indented time courses of the four measures, a 1-min time increment (4-min overlapping) was suggested in the analysis of mHRV in the study. ECG recordings from human subjects and dogs were used to further assess the effectiveness of the proposed method. The pilot study demonstrated that the proposed analysis of mHRV could provide more accurate assessment of the dynamical changes in cardiac activity than the conventional measures of HRV (without time overlapping). The proposed method may provide an efficient means in delineating the dynamics of momentary HRV and it would be worthy performing more investigations. PMID:26172953

Measuring Road Network Vulnerability with Sensitivity Analysis

PubMed Central

Jun-qiang, Leng; Long-hai, Yang; Liu, Wei-yi; Zhao, Lin

2017-01-01

This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. PMID:28125706

Follow-up of solar lentigo depigmentation with a retinaldehyde-based cream by clinical evaluation and calibrated colour imaging.

PubMed

Questel, E; Durbise, E; Bardy, A-L; Schmitt, A-M; Josse, G

2015-05-01

To assess an objective method evaluating the effects of a retinaldehyde-based cream (RA-cream) on solar lentigines; 29 women randomly applied RA-cream on lentigines of one hand and a control cream on the other, once daily for 3 months. A specific method enabling a reliable visualisation of the lesions was proposed, using high-magnification colour-calibrated camera imaging. Assessment was performed using clinical evaluation by Physician Global Assessment score and image analysis. Luminance determination on the numeric images was performed either on the basis of 5 independent expert's consensus borders or probability map analysis via an algorithm automatically detecting the pigmented area. Both image analysis methods showed a similar lightening of ΔL* = 2 after a 3-month treatment by RA-cream, in agreement with single-blind clinical evaluation. High-magnification colour-calibrated camera imaging combined with probability map analysis is a fast and precise method to follow lentigo depigmentation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Microgravity isolation system design: A modern control analysis framework

NASA Technical Reports Server (NTRS)

Hampton, R. D.; Knospe, C. R.; Allaire, P. E.; Grodsinsky, C. M.

1994-01-01

Many acceleration-sensitive, microgravity science experiments will require active vibration isolation from the manned orbiters on which they will be mounted. The isolation problem, especially in the case of a tethered payload, is a complex three-dimensional one that is best suited to modern-control design methods. These methods, although more powerful than their classical counterparts, can nonetheless go only so far in meeting the design requirements for practical systems. Once a tentative controller design is available, it must still be evaluated to determine whether or not it is fully acceptable, and to compare it with other possible design candidates. Realistically, such evaluation will be an inherent part of a necessary iterative design process. In this paper, an approach is presented for applying complex mu-analysis methods to a closed-loop vibration isolation system (experiment plus controller). An analysis framework is presented for evaluating nominal stability, nominal performance, robust stability, and robust performance of active microgravity isolation systems, with emphasis on the effective use of mu-analysis methods.

Winter maintenance performance measure.

DOT National Transportation Integrated Search

2016-01-01

The Winter Performance Index is a method of quantifying winter storm events and the DOTs response to them. : It is a valuable tool for evaluating the States maintenance practices, performing post-storm analysis, training : maintenance personnel...

Development and validation of an ultra-performance convergence chromatography method for the quality control of Angelica gigas Nakai.

PubMed

Kim, Hyo Seon; Chun, Jin Mi; Kwon, Bo-In; Lee, A-Reum; Kim, Ho Kyoung; Lee, A Yeong

2016-10-01

Ultra-performance convergence chromatography, which integrates the advantages of supercritical fluid chromatography and ultra high performance liquid chromatography technologies, is an environmentally friendly analytical method that uses dramatically reduced amounts of organic solvents. An ultra-performance convergence chromatography method was developed and validated for the quantification of decursinol angelate and decursin in Angelica gigas using a CSH Fluoro-Phenyl column (2.1 mm × 150 mm, 1.7 μm) with a run time of 4 min. The method had an improved resolution and a shorter analysis time in comparison to the conventional high-performance liquid chromatography method. This method was validated in terms of linearity, precision, and accuracy. The limits of detection were 0.005 and 0.004 μg/mL for decursinol angelate and decursin, respectively, while the limits of quantitation were 0.014 and 0.012 μg/mL, respectively. The two components showed good regression (correlation coefficient (r 2 ) > 0.999), excellent precision (RSD < 2.28%), and acceptable recoveries (99.75-102.62%). The proposed method can be used to efficiently separate, characterize, and quantify decursinol angelate and decursin in Angelica gigas and its related medicinal materials or preparations, with the advantages of a shorter analysis time, greater sensitivity, and better environmental compatibility. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

Lab-on-a-chip nucleic-acid analysis towards point-of-care applications

NASA Astrophysics Data System (ADS)

Kopparthy, Varun Lingaiah

Recent infectious disease outbreaks, such as Ebola in 2013, highlight the need for fast and accurate diagnostic tools to combat the global spread of the disease. Detection and identification of the disease-causing viruses and bacteria at the genetic level is required for accurate diagnosis of the disease. Nucleic acid analysis systems have shown promise in identifying diseases such as HIV, anthrax, and Ebola in the past. Conventional nucleic acid analysis systems are still time consuming, and are not suitable for point-ofcare applications. Miniaturized nucleic acid systems has shown great promise for rapid analysis, but they have not been commercialized due to several factors such as footprint, complexity, portability, and power consumption. This dissertation presents the development of technologies and methods for a labon-a-chip nucleic acid analysis towards point-of-care applications. An oscillatory-flow PCR methodology in a thermal gradient is developed which provides real-time analysis of nucleic-acid samples. Oscillating flow PCR was performed in the microfluidic device under thermal gradient in 40 minutes. Reverse transcription PCR (RT-PCR) was achieved in the system without an additional heating element for incubation to perform reverse transcription step. A novel method is developed for the simultaneous pattering and bonding of all-glass microfluidic devices in a microwave oven. Glass microfluidic devices were fabricated in less than 4 minutes. Towards an integrated system for the detection of amplified products, a thermal sensing method is studied for the optimization of the sensor output. Calorimetric sensing method is characterized to identify design considerations and optimal parameters such as placement of the sensor, steady state response, and flow velocity for improved performance. An understanding of these developed technologies and methods will facilitate the development of lab-on-a-chip systems for point-of-care analysis.

Stability analysis for a multi-camera photogrammetric system.

PubMed

Habib, Ayman; Detchev, Ivan; Kwak, Eunju

2014-08-18

Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction.

Stability Analysis for a Multi-Camera Photogrammetric System

PubMed Central

Habib, Ayman; Detchev, Ivan; Kwak, Eunju

2014-01-01

Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction. PMID:25196012

Power Spectral Density Error Analysis of Spectral Subtraction Type of Speech Enhancement Methods

NASA Astrophysics Data System (ADS)

Händel, Peter

2006-12-01

A theoretical framework for analysis of speech enhancement algorithms is introduced for performance assessment of spectral subtraction type of methods. The quality of the enhanced speech is related to physical quantities of the speech and noise (such as stationarity time and spectral flatness), as well as to design variables of the noise suppressor. The derived theoretical results are compared with the outcome of subjective listening tests as well as successful design strategies, performed by independent research groups.

Comparison of detrending methods for fluctuation analysis in hydrology

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Chen, Yongqin David

2011-03-01

SummaryTrends within a hydrologic time series can significantly influence the scaling results of fluctuation analysis, such as rescaled range (RS) analysis and (multifractal) detrended fluctuation analysis (MF-DFA). Therefore, removal of trends is important in the study of scaling properties of the time series. In this study, three detrending methods, including adaptive detrending algorithm (ADA), Fourier-based method, and average removing technique, were evaluated by analyzing numerically generated series and observed streamflow series with obvious relative regular periodic trend. Results indicated that: (1) the Fourier-based detrending method and ADA were similar in detrending practices, and given proper parameters, these two methods can produce similarly satisfactory results; (2) detrended series by Fourier-based detrending method and ADA lose the fluctuation information at larger time scales, and the location of crossover points is heavily impacted by the chosen parameters of these two methods; and (3) the average removing method has an advantage over the other two methods, i.e., the fluctuation information at larger time scales is kept well-an indication of relatively reliable performance in detrending. In addition, the average removing method performed reasonably well in detrending a time series with regular periods or trends. In this sense, the average removing method should be preferred in the study of scaling properties of the hydrometeorolgical series with relative regular periodic trend using MF-DFA.

Propfan experimental data analysis

NASA Technical Reports Server (NTRS)

Vernon, David F.; Page, Gregory S.; Welge, H. Robert

1984-01-01

A data reduction method, which is consistent with the performance prediction methods used for analysis of new aircraft designs, is defined and compared to the method currently used by NASA using data obtained from an Ames Res. Center 11 foot transonic wind tunnel test. Pressure and flow visualization data from the Ames test for both the powered straight underwing nacelle, and an unpowered contoured overwing nacelle installation is used to determine the flow phenomena present for a wind mounted turboprop installation. The test data is compared to analytic methods, showing the analytic methods to be suitable for design and analysis of new configurations. The data analysis indicated that designs with zero interference drag levels are achieveable with proper wind and nacelle tailoring. A new overwing contoured nacelle design and a modification to the wing leading edge extension for the current wind tunnel model design are evaluated. Hardware constraints of the current model parts prevent obtaining any significant performance improvement due to a modified nacelle contouring. A new aspect ratio wing design for an up outboard rotation turboprop installation is defined, and an advanced contoured nacelle is provided.

Precipitation forecast using artificial neural networks. An application to the Guadalupe Valley, Baja California, Mexico

NASA Astrophysics Data System (ADS)

Herrera-Oliva, C. S.

2013-05-01

In this work we design and implement a method for the determination of precipitation forecast through the application of an elementary neuronal network (perceptron) to the statistical analysis of the precipitation reported in catalogues. The method is limited mainly by the catalogue length (and, in a smaller degree, by its accuracy). The method performance is measured using grading functions that evaluate a tradeoff between positive and negative aspects of performance. The method is applied to the Guadalupe Valley, Baja California, Mexico. Using consecutive intervals of dt=0.1 year, employing the data of several climatological stations situated in and surrounding this important wine industries zone. We evaluated the performance of different models of ANN, whose variables of entrance are the heights of precipitation. The results obtained were satisfactory, except for exceptional values of rain. Key words: precipitation forecast, artificial neural networks, statistical analysis

A method for environmental acoustic analysis improvement based on individual evaluation of common sources in urban areas.

PubMed

López-Pacheco, María G; Sánchez-Fernández, Luis P; Molina-Lozano, Herón

2014-01-15

Noise levels of common sources such as vehicles, whistles, sirens, car horns and crowd sounds are mixed in urban soundscapes. Nowadays, environmental acoustic analysis is performed based on mixture signals recorded by monitoring systems. These mixed signals make it difficult for individual analysis which is useful in taking actions to reduce and control environmental noise. This paper aims at separating, individually, the noise source from recorded mixtures in order to evaluate the noise level of each estimated source. A method based on blind deconvolution and blind source separation in the wavelet domain is proposed. This approach provides a basis to improve results obtained in monitoring and analysis of common noise sources in urban areas. The method validation is through experiments based on knowledge of the predominant noise sources in urban soundscapes. Actual recordings of common noise sources are used to acquire mixture signals using a microphone array in semi-controlled environments. The developed method has demonstrated great performance improvements in identification, analysis and evaluation of common urban sources. © 2013 Elsevier B.V. All rights reserved.

Cell-Free DNA Analysis in Maternal Blood: Differences in Estimates between Laboratories with Different Methodologies Using a Propensity Score Approach.

PubMed

Bevilacqua, Elisa; Jani, Jacques C; Letourneau, Alexandra; Duiella, Silvia F; Kleinfinger, Pascale; Lohmann, Laurence; Resta, Serena; Cos Sanchez, Teresa; Fils, Jean-François; Mirra, Marilyn; Benachi, Alexandra; Costa, Jean-Marc

2018-06-13

To evaluate the failure rate and performance of cell-free DNA (cfDNA) testing, mainly in terms of detection rates for trisomy 21, performed by 2 laboratories using different analytical methods. cfDNA testing was performed on 2,870 pregnancies with the HarmonyTM Prenatal Test using the targeted digital analysis of selected regions (DANSR) method, and on 2,635 pregnancies with the "Cerba test" using the genome-wide massively parallel sequencing (GW-MPS) method, with available outcomes. Propensity score analysis was used to match patients between the 2 groups. A comparison of the detection rates for trisomy 21 between the 2 laboratories was made. In all, 2,811 patients in the Harmony group and 2,530 patients in the Cerba group had no trisomy 21, 18, or 13. Postmatched comparisons of the patient characteristics indicated a higher no-result rate in the Harmony group (1.30%) than in the Cerba group (0.75%; p = 0.039). All 41 cases of trisomy 21 in the Harmony group and 93 cases in the Cerba group were detected. Both methods of cfDNA testing showed low no-result rates and a comparable performance in detecting trisomy 21; yet GW-MPS had a slightly lower no-result rate than the DANSR method. © 2018 S. Karger AG, Basel.

Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) for a 3-D Flexible Wing

NASA Technical Reports Server (NTRS)

Gumbert, Clyde R.; Hou, Gene J.-W.

2001-01-01

The formulation and implementation of an optimization method called Simultaneous Aerodynamic Analysis and Design Optimization (SAADO) are extended from single discipline analysis (aerodynamics only) to multidisciplinary analysis - in this case, static aero-structural analysis - and applied to a simple 3-D wing problem. The method aims to reduce the computational expense incurred in performing shape optimization using state-of-the-art Computational Fluid Dynamics (CFD) flow analysis, Finite Element Method (FEM) structural analysis and sensitivity analysis tools. Results for this small problem show that the method reaches the same local optimum as conventional optimization. However, unlike its application to the win,, (single discipline analysis), the method. as I implemented here, may not show significant reduction in the computational cost. Similar reductions were seen in the two-design-variable (DV) problem results but not in the 8-DV results given here.

Open-Source Photometric System for Enzymatic Nitrate Quantification

PubMed Central

Wittbrodt, B. T.; Squires, D. A.; Walbeck, J.; Campbell, E.; Campbell, W. H.; Pearce, J. M.

2015-01-01

Nitrate, the most oxidized form of nitrogen, is regulated to protect people and animals from harmful levels as there is a large over abundance due to anthropogenic factors. Widespread field testing for nitrate could begin to address the nitrate pollution problem, however, the Cadmium Reduction Method, the leading certified method to detect and quantify nitrate, demands the use of a toxic heavy metal. An alternative, the recently proposed Environmental Protection Agency Nitrate Reductase Nitrate-Nitrogen Analysis Method, eliminates this problem but requires an expensive proprietary spectrophotometer. The development of an inexpensive portable, handheld photometer will greatly expedite field nitrate analysis to combat pollution. To accomplish this goal, a methodology for the design, development, and technical validation of an improved open-source water testing platform capable of performing Nitrate Reductase Nitrate-Nitrogen Analysis Method. This approach is evaluated for its potential to i) eliminate the need for toxic chemicals in water testing for nitrate and nitrite, ii) reduce the cost of equipment to perform this method for measurement for water quality, and iii) make the method easier to carryout in the field. The device is able to perform as well as commercial proprietary systems for less than 15% of the cost for materials. This allows for greater access to the technology and the new, safer nitrate testing technique. PMID:26244342

Open-Source Photometric System for Enzymatic Nitrate Quantification.

PubMed

Wittbrodt, B T; Squires, D A; Walbeck, J; Campbell, E; Campbell, W H; Pearce, J M

2015-01-01

Nitrate, the most oxidized form of nitrogen, is regulated to protect people and animals from harmful levels as there is a large over abundance due to anthropogenic factors. Widespread field testing for nitrate could begin to address the nitrate pollution problem, however, the Cadmium Reduction Method, the leading certified method to detect and quantify nitrate, demands the use of a toxic heavy metal. An alternative, the recently proposed Environmental Protection Agency Nitrate Reductase Nitrate-Nitrogen Analysis Method, eliminates this problem but requires an expensive proprietary spectrophotometer. The development of an inexpensive portable, handheld photometer will greatly expedite field nitrate analysis to combat pollution. To accomplish this goal, a methodology for the design, development, and technical validation of an improved open-source water testing platform capable of performing Nitrate Reductase Nitrate-Nitrogen Analysis Method. This approach is evaluated for its potential to i) eliminate the need for toxic chemicals in water testing for nitrate and nitrite, ii) reduce the cost of equipment to perform this method for measurement for water quality, and iii) make the method easier to carryout in the field. The device is able to perform as well as commercial proprietary systems for less than 15% of the cost for materials. This allows for greater access to the technology and the new, safer nitrate testing technique.

Thermal protection system gap analysis using a loosely coupled fluid-structural thermal numerical method

NASA Astrophysics Data System (ADS)

Huang, Jie; Li, Piao; Yao, Weixing

2018-05-01

A loosely coupled fluid-structural thermal numerical method is introduced for the thermal protection system (TPS) gap thermal control analysis in this paper. The aerodynamic heating and structural thermal are analyzed by computational fluid dynamics (CFD) and numerical heat transfer (NHT) methods respectively. An interpolation algorithm based on the control surface is adopted for the data exchanges on the coupled surface. In order to verify the analysis precision of the loosely coupled method, a circular tube example was analyzed, and the wall temperature agrees well with the test result. TPS gap thermal control performance was studied by the loosely coupled method successfully. The gap heat flux is mainly distributed in the small region at the top of the gap which is the high temperature region. Besides, TPS gap temperature and the power of the active cooling system (CCS) calculated by the traditional uncoupled method are higher than that calculated by the coupled method obviously. The reason is that the uncoupled method doesn't consider the coupled effect between the aerodynamic heating and structural thermal, however the coupled method considers it, so TPS gap thermal control performance can be analyzed more accurately by the coupled method.

Ultra‐high performance supercritical fluid chromatography of lignin‐derived phenols from alkaline cupric oxide oxidation

PubMed Central

Sun, Mingzhe; Lidén, Gunnar; Sandahl, Margareta

2016-01-01

Traditional chromatographic methods for the analysis of lignin‐derived phenolic compounds in environmental samples are generally time consuming. In this work, an ultra‐high performance supercritical fluid chromatography method with a diode array detector for the analysis of major lignin‐derived phenolic compounds produced by alkaline cupric oxide oxidation was developed. In an analysis of a collection of 11 representative monomeric lignin phenolic compounds, all compounds were clearly separated within 6 min with excellent peak shapes, with a limit of detection of 0.5–2.5 μM, a limit of quantification of 2.5–5.0 μM, and a dynamic range of 5.0–2.0 mM (R 2 > 0.997). The new ultra‐high performance supercritical fluid chromatography method was also applied for the qualitative and quantitative analysis of lignin‐derived phenolic compounds obtained upon alkaline cupric oxide oxidation of a commercial humic acid. Ten out of the previous eleven model compounds could be quantified in the oxidized humic acid sample. The high separation power and short analysis time obtained demonstrate for the first time that supercritical fluid chromatography is a fast and reliable technique for the analysis of lignin‐derived phenols in complex environmental samples. PMID:27452148

Reliability of skeletal maturity analysis using the cervical vertebrae maturation method on dedicated software.

PubMed

Padalino, Saverio; Sfondrini, Maria Francesca; Chenuil, Laura; Scudeller, Luigia; Gandini, Paola

2014-12-01

The aim of this study was to assess the feasibility of skeletal maturation analysis using the Cervical Vertebrae Maturation (CVM) method by means of dedicated software, developed in collaboration with Outside Format (Paullo-Milan), as compared with manual analysis. From a sample of patients aged 7-21 years, we gathered 100 lateral cephalograms, 20 for each of the five CVM stages. For each cephalogram, we traced cervical vertebrae C2, C3 and C4 by hand using a lead pencil and an acetate sheet and dedicated software. All the tracings were made by an experienced operator (a dentofacial orthopedics resident) and by an inexperienced operator (a student in dental surgery). Each operator recorded the time needed to make each tracing in order to demonstrate differences in the times taken. Concordance between the manual analysis and the analysis performed using the dedicated software was 94% for the resident and 93% for the student. Interobserver concordance was 99%. The hand-tracing was quicker than that performed by means of the software (28 seconds more on average). The cervical vertebrae analysis software offers excellent clinical performance, even if the method takes longer than the manual technique. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Mycotoxin analysis: an update.

PubMed

Krska, Rudolf; Schubert-Ullrich, Patricia; Molinelli, Alexandra; Sulyok, Michael; MacDonald, Susan; Crews, Colin

2008-02-01

Mycotoxin contamination of cereals and related products used for feed can cause intoxication, especially in farm animals. Therefore, efficient analytical tools for the qualitative and quantitative analysis of toxic fungal metabolites in feed are required. Current methods usually include an extraction step, a clean-up step to reduce or eliminate unwanted co-extracted matrix components and a separation step with suitably specific detection ability. Quantitative methods of analysis for most mycotoxins use immunoaffinity clean-up with high-performance liquid chromatography (HPLC) separation in combination with UV and/or fluorescence detection. Screening of samples contaminated with mycotoxins is frequently performed by thin layer chromatography (TLC), which yields qualitative or semi-quantitative results. Nowadays, enzyme-linked immunosorbent assays (ELISA) are often used for rapid screening. A number of promising methods, such as fluorescence polarization immunoassays, dipsticks, and even newer methods such as biosensors and non-invasive techniques based on infrared spectroscopy, have shown great potential for mycotoxin analysis. Currently, there is a strong trend towards the use of multi-mycotoxin methods for the simultaneous analysis of several of the important Fusarium mycotoxins, which is best achieved by LC-MS/MS (liquid chromatography with tandem mass spectrometry). This review focuses on recent developments in the determination of mycotoxins with a special emphasis on LC-MS/MS and emerging rapid methods.

Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.

PubMed

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J

2015-12-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. (c) 2015 APA, all rights reserved).

Using Classification and Regression Trees (CART) and Random Forests to Analyze Attrition: Results From Two Simulations

PubMed Central

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J.

2016-01-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. PMID:26389526

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods.

PubMed

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines.

Quality Evaluation of Potentilla fruticosa L. by High Performance Liquid Chromatography Fingerprinting Associated with Chemometric Methods

PubMed Central

Liu, Wei; Wang, Dongmei; Liu, Jianjun; Li, Dengwu; Yin, Dongxue

2016-01-01

The present study was performed to assess the quality of Potentilla fruticosa L. sampled from distinct regions of China using high performance liquid chromatography (HPLC) fingerprinting coupled with a suite of chemometric methods. For this quantitative analysis, the main active phytochemical compositions and the antioxidant activity in P. fruticosa were also investigated. Considering the high percentages and antioxidant activities of phytochemicals, P. fruticosa samples from Kangding, Sichuan were selected as the most valuable raw materials. Similarity analysis (SA) of HPLC fingerprints, hierarchical cluster analysis (HCA), principle component analysis (PCA), and discriminant analysis (DA) were further employed to provide accurate classification and quality estimates of P. fruticosa. Two principal components (PCs) were collected by PCA. PC1 separated samples from Kangding, Sichuan, capturing 57.64% of the variance, whereas PC2 contributed to further separation, capturing 18.97% of the variance. Two kinds of discriminant functions with a 100% discrimination ratio were constructed. The results strongly supported the conclusion that the eight samples from different regions were clustered into three major groups, corresponding with their morphological classification, for which HPLC analysis confirmed the considerable variation in phytochemical compositions and that P. fruticosa samples from Kangding, Sichuan were of high quality. The results of SA, HCA, PCA, and DA were in agreement and performed well for the quality assessment of P. fruticosa. Consequently, HPLC fingerprinting coupled with chemometric techniques provides a highly flexible and reliable method for the quality evaluation of traditional Chinese medicines. PMID:26890416

CrossTalk: The Journal of Defense Software Engineering. Volume 19, Number 12, December 2006

DTIC Science & Technology

2006-12-01

Feature-Oriented Domain Analysis ( FODA ) FODA is a domain analysis and engineer- ing method that focuses on developing reusable assets [9]. By examining...Eliciting Security Requirements This article describes an approach for doing trade-off analysis among requirements elicitation methods. by Dr. Nancy R...high-level requirements are addressed and met in the requirements work products. 3. Unclear requirements Mitigation Perform requirements analysis and

DETERMINATION OF CHLOROPHEONIS, NITROPHENOIS AND METHYLPHENOIS IN GROUND-WATER SAMPLES USING HIGH PERFORMANCE LIQUID CHROMATOGRAPHY

EPA Science Inventory

A high performance liquid chromatography (HPLC) method was developed to quantitatively determine phenolic compounds and their isomers in aqueous samples. The HPLC method can analyze a mixture of 15 contaminants in the same analytical run with an analysis time of 25 minutes. The...

EPA Method 8321B (SW-846): Solvent-Extractable Nonvolatile Compounds by High Performance Liquid Chromatography-Thermospray-Mass Spectrometry (HPLC-TS-MS) or Ultraviolet (UV) Detection

EPA Pesticide Factsheets

Method 8321B describes procedures for preparation and analysis of solid, aqueous liquid, drinking water and wipe samples using high performance liquid chromatography and mass spectrometry for extractable non-volatile compounds.

DETERMINATION OF CHLOROPHENOLS, NITROPHENOLS, AND METHYLPHENOLS IN GROUND-WATER SAMPLES USING HIGH PERFORMANCE LIQUID CHROMATOGRAPHY

EPA Science Inventory

A high performance liquid chromatography (HPLC) method was developed to quantitatively determine phenolic compounds and their isomers in aqueous samples. The HPLC method can analyze a mixture of 15 contaminants in the same analytical run with an analysis time of 25 minutes. The...

Identification of suitable genes contributes to lung adenocarcinoma clustering by multiple meta-analysis methods.

PubMed

Yang, Ze-Hui; Zheng, Rui; Gao, Yuan; Zhang, Qiang

2016-09-01

With the widespread application of high-throughput technology, numerous meta-analysis methods have been proposed for differential expression profiling across multiple studies. We identified the suitable differentially expressed (DE) genes that contributed to lung adenocarcinoma (ADC) clustering based on seven popular multiple meta-analysis methods. Seven microarray expression profiles of ADC and normal controls were extracted from the ArrayExpress database. The Bioconductor was used to perform the data preliminary preprocessing. Then, DE genes across multiple studies were identified. Hierarchical clustering was applied to compare the classification performance for microarray data samples. The classification efficiency was compared based on accuracy, sensitivity and specificity. Across seven datasets, 573 ADC cases and 222 normal controls were collected. After filtering out unexpressed and noninformative genes, 3688 genes were remained for further analysis. The classification efficiency analysis showed that DE genes identified by sum of ranks method separated ADC from normal controls with the best accuracy, sensitivity and specificity of 0.953, 0.969 and 0.932, respectively. The gene set with the highest classification accuracy mainly participated in the regulation of response to external stimulus (P = 7.97E-04), cyclic nucleotide-mediated signaling (P = 0.01), regulation of cell morphogenesis (P = 0.01) and regulation of cell proliferation (P = 0.01). Evaluation of DE genes identified by different meta-analysis methods in classification efficiency provided a new perspective to the choice of the suitable method in a given application. Varying meta-analysis methods always present varying abilities, so synthetic consideration should be taken when providing meta-analysis methods for particular research. © 2015 John Wiley & Sons Ltd.

Development of high performance liquid chromatography method for miconazole analysis in powder sample

NASA Astrophysics Data System (ADS)

Hermawan, D.; Suwandri; Sulaeman, U.; Istiqomah, A.; Aboul-Enein, H. Y.

2017-02-01

A simple high performance liquid chromatography (HPLC) method has been developed in this study for the analysis of miconazole, an antifungal drug, in powder sample. The optimized HPLC system using C8 column was achieved using mobile phase composition containing methanol:water (85:15, v/v), a flow rate of 0.8 mL/min, and UV detection at 220 nm. The calibration graph was linear in the range from 10 to 50 mg/L with r 2 of 0.9983. The limit of detection (LOD) and limit of quantitation (LOQ) obtained were 2.24 mg/L and 7.47 mg/L, respectively. The present HPLC method is applicable for the determination of miconazole in the powder sample with a recovery of 101.28 % (RSD = 0.96%, n = 3). The developed HPLC method provides short analysis time, high reproducibility and high sensitivity.

Ultrafast Method for the Analysis of Fluorescence Lifetime Imaging Microscopy Data Based on the Laguerre Expansion Technique

PubMed Central

Jo, Javier A.; Fang, Qiyin; Marcu, Laura

2007-01-01

We report a new deconvolution method for fluorescence lifetime imaging microscopy (FLIM) based on the Laguerre expansion technique. The performance of this method was tested on synthetic and real FLIM images. The following interesting properties of this technique were demonstrated. 1) The fluorescence intensity decay can be estimated simultaneously for all pixels, without a priori assumption of the decay functional form. 2) The computation speed is extremely fast, performing at least two orders of magnitude faster than current algorithms. 3) The estimated maps of Laguerre expansion coefficients provide a new domain for representing FLIM information. 4) The number of images required for the analysis is relatively small, allowing reduction of the acquisition time. These findings indicate that the developed Laguerre expansion technique for FLIM analysis represents a robust and extremely fast deconvolution method that enables practical applications of FLIM in medicine, biology, biochemistry, and chemistry. PMID:19444338

Analysis Code - Data Analysis in 'Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications' (LMSMIPNFA) v. 1.0

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

Lewis, John R

R code that performs the analysis of a data set presented in the paper ‘Leveraging Multiple Statistical Methods for Inverse Prediction in Nuclear Forensics Applications’ by Lewis, J., Zhang, A., Anderson-Cook, C. It provides functions for doing inverse predictions in this setting using several different statistical methods. The data set is a publicly available data set from a historical Plutonium production experiment.

Finite time step and spatial grid effects in δf simulation of warm plasmas

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

Sturdevant, Benjamin J., E-mail: benjamin.j.sturdevant@gmail.com; Department of Applied Mathematics, University of Colorado at Boulder, Boulder, CO 80309; Parker, Scott E.

2016-01-15

This paper introduces a technique for analyzing time integration methods used with the particle weight equations in δf method particle-in-cell (PIC) schemes. The analysis applies to the simulation of warm, uniform, periodic or infinite plasmas in the linear regime and considers the collective behavior similar to the analysis performed by Langdon for full-f PIC schemes [1,2]. We perform both a time integration analysis and spatial grid analysis for a kinetic ion, adiabatic electron model of ion acoustic waves. An implicit time integration scheme is studied in detail for δf simulations using our weight equation analysis and for full-f simulations usingmore » the method of Langdon. It is found that the δf method exhibits a CFL-like stability condition for low temperature ions, which is independent of the parameter characterizing the implicitness of the scheme. The accuracy of the real frequency and damping rate due to the discrete time and spatial schemes is also derived using a perturbative method. The theoretical analysis of numerical error presented here may be useful for the verification of simulations and for providing intuition for the design of new implicit time integration schemes for the δf method, as well as understanding differences between δf and full-f approaches to plasma simulation.« less

DNA-based methods of geochemical prospecting

DOEpatents

Ashby, Matthew [Mill Valley, CA

2011-12-06

The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

Classification of LC columns based on the QSRR method and selectivity toward moclobemide and its metabolites.

PubMed

Plenis, Alina; Olędzka, Ilona; Bączek, Tomasz

2013-05-05

This paper focuses on a comparative study of the column classification system based on the quantitative structure-retention relationships (QSRR method) and column performance in real biomedical analysis. The assay was carried out for the LC separation of moclobemide and its metabolites in human plasma, using a set of 24 stationary phases. The QSRR models established for the studied stationary phases were compared with the column test performance results under two chemometric techniques - the principal component analysis (PCA) and the hierarchical clustering analysis (HCA). The study confirmed that the stationary phase classes found closely related by the QSRR approach yielded comparable separation for moclobemide and its metabolites. Therefore, the QSRR method could be considered supportive in the selection of a suitable column for the biomedical analysis offering the selection of similar or dissimilar columns with a relatively higher certainty. Copyright © 2013 Elsevier B.V. All rights reserved.

Analysis Study of Stevioside and Rebaudioside A from Stevia rebaudiana Bertoni by Normal Phase SPE and RP-HPLC

NASA Astrophysics Data System (ADS)

Martono, Y.; Rohman, A.; Riyanto, S.; Martono, S.

2018-04-01

Solid Phase Extraction (SPE) method using silica as sorbent for stevioside and rebaudiosida A analysis in Stevia rebaudiana Bertoni leaf have not been performed. The aim of this study is to develop SPE method using silica as sorbent for Reverse Phase-High Performance Liquid Chromatography (RP-HPLC) analysis of stevioside and rebaudiosida A in S. rebaudiana leaf. The results of this study indicate that the optimal conditions for normal phase SPE (silica) are conditioned with 3.0 mL of hexane. The sample loading volume is 0.1 mL. Cartridge is eluted with 1.0 mL acetonitrile: water (80: 20, v/v) to separate both analytes. The cartridge is washed with chloroform and water of 0.3 mL respectively. The developed SPE sample preparation method meets the accuracy and precision test and can be used for the analysis of stevioside and rebaudioside A by RP-HPLC.

Analysis of Publications and Citations from a Geophysics Research Institute.

ERIC Educational Resources Information Center

Frohlich, Cliff; Resler, Lynn

2001-01-01

Performs an analysis of all 1128 publications produced by scientists during their employment at the University of Texas Institute for Geophysics, thus assessing research performance using as bibliometric indicators such statistics as publications per year, citations per paper, and cited half-lives. Evaluates five different methods for determining…

EXTRACTION AND QUANTITATIVE ANALYSIS OF ELEMENTAL SULFUR FROM SULFIDE MINERAL SURFACES BY HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY. (R826189)

EPA Science Inventory

A simple method for the quantitative determination of elemental sulfur on oxidized sulfide minerals is described. Extraction of elemental sulfur in perchloroethylene and subsequent analysis with high-performance liquid chromatography were used to ascertain the total elemental ...

Analysis and quality control of carbohydrates in therapeutic proteins with fluorescence HPLC

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

Liu, Kun; Huang, Jian; Center for Informational Biology, University of Electronic Science and Technology of China, Chengdu 610054

Conbercept is an Fc fusion protein with very complicated carbohydrate profiles which must be carefully monitored through manufacturing process. Here, we introduce an optimized fluorescence derivatization high-performance liquid chromatographic method for glycan mapping in conbercept. Compared with conventional glycan analysis method, this method has much better resolution and higher reproducibility making it excellent for product quality control.

Application of integrated fluid-thermal-structural analysis methods

NASA Technical Reports Server (NTRS)

Wieting, Allan R.; Dechaumphai, Pramote; Bey, Kim S.; Thornton, Earl A.; Morgan, Ken

1988-01-01

Hypersonic vehicles operate in a hostile aerothermal environment which has a significant impact on their aerothermostructural performance. Significant coupling occurs between the aerodynamic flow field, structural heat transfer, and structural response creating a multidisciplinary interaction. Interfacing state-of-the-art disciplinary analysis methods is not efficient, hence interdisciplinary analysis methods integrated into a single aerothermostructural analyzer are needed. The NASA Langley Research Center is developing such methods in an analyzer called LIFTS (Langley Integrated Fluid-Thermal-Structural) analyzer. The evolution and status of LIFTS is reviewed and illustrated through applications.

Probabilistic methods for rotordynamics analysis

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Torng, T. Y.; Millwater, H. R.; Fossum, A. F.; Rheinfurth, M. H.

1991-01-01

This paper summarizes the development of the methods and a computer program to compute the probability of instability of dynamic systems that can be represented by a system of second-order ordinary linear differential equations. Two instability criteria based upon the eigenvalues or Routh-Hurwitz test functions are investigated. Computational methods based on a fast probability integration concept and an efficient adaptive importance sampling method are proposed to perform efficient probabilistic analysis. A numerical example is provided to demonstrate the methods.

A novel implementation of homodyne time interval analysis method for primary vibration calibration

NASA Astrophysics Data System (ADS)

Sun, Qiao; Zhou, Ling; Cai, Chenguang; Hu, Hongbo

2011-12-01

In this paper, the shortcomings and their causes of the conventional homodyne time interval analysis (TIA) method is described with respect to its software algorithm and hardware implementation, based on which a simplified TIA method is proposed with the help of virtual instrument technology. Equipped with an ordinary Michelson interferometer and dual channel synchronous data acquisition card, the primary vibration calibration system using the simplified method can perform measurements of complex sensitivity of accelerometers accurately, meeting the uncertainty requirements laid down in pertaining ISO standard. The validity and accuracy of the simplified TIA method is verified by simulation and comparison experiments with its performance analyzed. This simplified method is recommended to apply in national metrology institute of developing countries and industrial primary vibration calibration labs for its simplified algorithm and low requirements on hardware.

Aeroelastic stability and response of rotating structures

NASA Technical Reports Server (NTRS)

Keith, Theo G., Jr.

1993-01-01

A summary of the work performed during the progress period is presented. Analysis methods for predicting loads and instabilities of wind turbines were developed. Three new areas of research to aid the Advanced Turboprop Project (ATP) were initiated and developed. These three areas of research are aeroelastic analysis methods for cascades including blade and disk flexibility; stall flutter analysis; and computational aeroelasticity.

Foundation Analysis East Coast Air Combat Maneuvering Range Offshore Kitty Hawk, North Carolina.

DTIC Science & Technology

1976-09-01

1976 86 2 3 025 TABLE OF CONTENTS SECTION TITLE PAGE 1.0 INTRODUCTION 1.1 Introduction 1.01 1.2 Methods of Analysis 1.01 1.3 Personnel Resumes 1.02...piling into the desired penetration. 1.2 METHODS OF ANALYSIS The method employed to perform the computation of pipe pile capacity curves, as presented...AD-A163 522 FOUNDATION ANALYSIS EAST COAST AIR COMBAT NANsUVERING 14S RANGE OFFSHORE KITT.. CU) CREST ENGINEERING INC TULSA OK SEP 76 27-M7-97 CNES

Analysis of short-chain fatty acids in human feces: A scoping review.

PubMed

Primec, Maša; Mičetić-Turk, Dušanka; Langerholc, Tomaž

2017-06-01

Short-chain fatty acids (SCFAs) play a crucial role in maintaining homeostasis in humans, therefore the importance of a good and reliable SCFAs analytical detection has raised a lot in the past few years. The aim of this scoping review is to show the trends in the development of different methods of SCFAs analysis in feces, based on the literature published in the last eleven years in all major indexing databases. The search criteria included analytical quantification techniques of SCFAs in different human clinical and in vivo studies. SCFAs analysis is still predominantly performed using gas chromatography (GC), followed by high performance liquid chromatography (HPLC), nuclear magnetic resonance (NMR) and capillary electrophoresis (CE). Performances, drawbacks and advantages of these methods are discussed, especially in the light of choosing a proper pretreatment, as feces is a complex biological material. Further optimization to develop a simple, cost effective and robust method for routine use is needed. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis and Design of Rotors at Ultra-Low Reynolds Numbers

NASA Technical Reports Server (NTRS)

Kunz, Peter J.; Strawn, Roger C.

2003-01-01

Design tools have been developed for ultra-low Reynolds number rotors, combining enhanced actuator-ring / blade-element theory with airfoil section data based on two-dimensional Navier-Stokes calculations. This performance prediction method is coupled with an optimizer for both design and analysis applications. Performance predictions from these tools have been compared with three-dimensional Navier Stokes analyses and experimental data for a 2.5 cm diameter rotor with chord Reynolds numbers below 10,000. Comparisons among the analyses and experimental data show reasonable agreement both in the global thrust and power required, but the spanwise distributions of these quantities exhibit significant deviations. The study also reveals that three-dimensional and rotational effects significantly change local airfoil section performance. The magnitude of this issue, unique to this operating regime, may limit the applicability of blade-element type methods for detailed rotor design at ultra-low Reynolds numbers, but these methods are still useful for evaluating concept feasibility and rapidly generating initial designs for further analysis and optimization using more advanced tools.

Optimation and Determination of Fe-Oxinate Complex by Using High Performance Liquid Chromatography

NASA Astrophysics Data System (ADS)

Oktavia, B.; Nasra, E.; Sary, R. C.

2018-04-01

The need for iron will improve the industrial processes that require iron as its raw material. Control of industrial iron waste is very important to do. One method of iron analysis is to conduct indirect analysis of iron (III) ions by complexing with 8-Hydroxyquinoline or oxine. In this research, qualitative and quantitative tests of iron (III) ions in the form of complex with oxine. The analysis was performed using HPLC at a wavelength of 470 nm with an ODS C18 column. Three methods of analysis were performed: 1) Fe-oxinate complexes were prepared in an ethanol solvent so no need for separation anymore, (2) Fe-oxinate complexes were made in chloroform so that a solvent extraction was required before the complex was injected into the column while the third complex was formed in the column, wherein the eluent contains the oxide and the metal ions are then injected. The resulting chromatogram shows that the 3rd way provides a better chromatogram for iron analysis.

Determination of Total Selenium in Infant Formulas: Comparison of the Performance of FIA and MCFA Flow Systems

PubMed Central

Pistón, Mariela; Knochen, Moisés

2012-01-01

Two flow methods, based, respectively, on flow-injection analysis (FIA) and on multicommutated flow analysis (MCFA), were compared with regard to their use for the determination of total selenium in infant formulas by hydride-generation atomic absorption spectrometry. The method based on multicommutation provided lower detection and quantification limits (0.08 and 0.27 μg L−1 compared to 0.59 and 1.95 μ L−1, resp.), higher sampling frequency (160 versus. 70 samples per hour), and reduced reagent consumption. Linearity, precision, and accuracy were similar for the two methods compared. It was concluded that, while both methods proved to be appropriate for the purpose, the MCFA-based method exhibited a better performance. PMID:22505923

Thermodynamics of Gas Turbine Cycles with Analytic Derivatives in OpenMDAO

NASA Technical Reports Server (NTRS)

Gray, Justin; Chin, Jeffrey; Hearn, Tristan; Hendricks, Eric; Lavelle, Thomas; Martins, Joaquim R. R. A.

2016-01-01

A new equilibrium thermodynamics analysis tool was built based on the CEA method using the OpenMDAO framework. The new tool provides forward and adjoint analytic derivatives for use with gradient based optimization algorithms. The new tool was validated against the original CEA code to ensure an accurate analysis and the analytic derivatives were validated against finite-difference approximations. Performance comparisons between analytic and finite difference methods showed a significant speed advantage for the analytic methods. To further test the new analysis tool, a sample optimization was performed to find the optimal air-fuel equivalence ratio, , maximizing combustion temperature for a range of different pressures. Collectively, the results demonstrate the viability of the new tool to serve as the thermodynamic backbone for future work on a full propulsion modeling tool.

Structure identification methods for atomistic simulations of crystalline materials

DOE PAGES

Stukowski, Alexander

2012-05-28

Here, we discuss existing and new computational analysis techniques to classify local atomic arrangements in large-scale atomistic computer simulations of crystalline solids. This article includes a performance comparison of typical analysis algorithms such as common neighbor analysis (CNA), centrosymmetry analysis, bond angle analysis, bond order analysis and Voronoi analysis. In addition we propose a simple extension to the CNA method that makes it suitable for multi-phase systems. Finally, we introduce a new structure identification algorithm, the neighbor distance analysis, which is designed to identify atomic structure units in grain boundaries.

Sensitive analysis of blonanserin, a novel antipsychotic agent, in human plasma by ultra-performance liquid chromatography-tandem mass spectrometry.

PubMed

Ogawa, Tadashi; Hattori, Hideki; Kaneko, Rina; Ito, Kenjiro; Iwai, Masayo; Mizutani, Yoko; Arinobu, Tetsuya; Ishii, Akira; Suzuki, Osamu; Seno, Hiroshi

2010-01-01

A rapid and sensitive method for analysis of blonanserin in human plasma by ultra-performance liquid chromatography-tandem mass spectrometry is presented. After pretreatment of a plasma sample by solid-phase extraction, blonanserin was analyzed by the system with a C(18) column. This method gave satisfactory recovery rates, reproducibility, and good linearity of calibration curve in the range of 0.01-10.0 ng/mL for quality control samples spiked with blonanserin. The detection limit was as low as 1 pg/mL. This method seems very useful in forensic and clinical toxicology and pharmacokinetic studies.

Quantitative Analysis of Staphylococcal Enterotoxins A and B in Food Matrices Using Ultra High-Performance Liquid Chromatography Tandem Mass Spectrometry (UPLC-MS/MS).

PubMed

Muratovic, Aida Zuberovic; Hagström, Thomas; Rosén, Johan; Granelli, Kristina; Hellenäs, Karl-Erik

2015-09-11

A method that uses mass spectrometry (MS) for identification and quantification of protein toxins, staphylococcal enterotoxins A and B (SEA and SEB), in milk and shrimp is described. The analysis was performed using a tryptic peptide, from each of the toxins, as the target analyte together with the corresponding (13)C-labeled synthetic internal standard peptide. The performance of the method was evaluated by analyzing spiked samples in the quantification range 2.5-30 ng/g (R² = 0.92-0.99). The limit of quantification (LOQ) in milk and the limit of detection (LOD) in shrimp was 2.5 ng/g, for both SEA and SEB toxins. The in-house reproducibility (RSD) was 8%-30% and 5%-41% at different concentrations for milk and shrimp, respectively. The method was compared to the ELISA method, used at the EU-RL (France), for milk samples spiked with SEA at low levels, in the quantification range of 2.5 to 5 ng/g. The comparison showed good coherence for the two methods: 2.9 (MS)/1.8 (ELISA) and 3.6 (MS)/3.8 (ELISA) ng/g. The major advantage of the developed method is that it allows direct confirmation of the molecular identity and quantitative analysis of SEA and SEB at low nanogram levels using a label and antibody free approach. Therefore, this method is an important step in the development of alternatives to the immune-assay tests currently used for staphylococcal enterotoxin analysis.

Applications of advanced V/STOL aircraft concepts to civil utility missions. Volume 2: Appendices

NASA Technical Reports Server (NTRS)

1977-01-01

The linear performance definition curves for the lift fan aircraft, tilt rotor aircraft, and advanced helicopter are given. The computer program written to perform the mission analysis for this study is also documented, and examples of its use are shown. Methods used to derive the performance coefficients for use in the mission analysis of the lift fan aircraft are described.

A strategy for evaluating pathway analysis methods.

PubMed

Yu, Chenggang; Woo, Hyung Jun; Yu, Xueping; Oyama, Tatsuya; Wallqvist, Anders; Reifman, Jaques

2017-10-13

Researchers have previously developed a multitude of methods designed to identify biological pathways associated with specific clinical or experimental conditions of interest, with the aim of facilitating biological interpretation of high-throughput data. Before practically applying such pathway analysis (PA) methods, we must first evaluate their performance and reliability, using datasets where the pathways perturbed by the conditions of interest have been well characterized in advance. However, such 'ground truths' (or gold standards) are often unavailable. Furthermore, previous evaluation strategies that have focused on defining 'true answers' are unable to systematically and objectively assess PA methods under a wide range of conditions. In this work, we propose a novel strategy for evaluating PA methods independently of any gold standard, either established or assumed. The strategy involves the use of two mutually complementary metrics, recall and discrimination. Recall measures the consistency of the perturbed pathways identified by applying a particular analysis method to an original large dataset and those identified by the same method to a sub-dataset of the original dataset. In contrast, discrimination measures specificity-the degree to which the perturbed pathways identified by a particular method to a dataset from one experiment differ from those identifying by the same method to a dataset from a different experiment. We used these metrics and 24 datasets to evaluate six widely used PA methods. The results highlighted the common challenge in reliably identifying significant pathways from small datasets. Importantly, we confirmed the effectiveness of our proposed dual-metric strategy by showing that previous comparative studies corroborate the performance evaluations of the six methods obtained by our strategy. Unlike any previously proposed strategy for evaluating the performance of PA methods, our dual-metric strategy does not rely on any ground truth, either established or assumed, of the pathways perturbed by a specific clinical or experimental condition. As such, our strategy allows researchers to systematically and objectively evaluate pathway analysis methods by employing any number of datasets for a variety of conditions.

Quantitative determination of multi markers in five varieties of Withania somnifera using ultra-high performance liquid chromatography with hybrid triple quadrupole linear ion trap mass spectrometer combined with multivariate analysis: Application to pharmaceutical dosage forms.

PubMed

Chandra, Preeti; Kannujia, Rekha; Saxena, Ankita; Srivastava, Mukesh; Bahadur, Lal; Pal, Mahesh; Singh, Bhim Pratap; Kumar Ojha, Sanjeev; Kumar, Brijesh

2016-09-10

An ultra-high performance liquid chromatography electrospray ionization tandem mass spectrometry method has been developed and validated for simultaneous quantification of six major bioactive compounds in five varieties of Withania somnifera in various plant parts (leaf, stem and root). The analysis was accomplished on Waters ACQUITY UPLC BEH C18 column with linear gradient elution of water/formic acid (0.1%) and acetonitrile at a flow rate of 0.3mLmin(-1). The proposed method was validated with acceptable linearity (r(2), 0.9989-0.9998), precision (RSD, 0.16-2.01%), stability (RSD, 1.04-1.62%) and recovery (RSD ≤2.45%), under optimum conditions. The method was also successfully applied for the simultaneous determination of six marker compounds in twenty-six marketed formulations. Hierarchical cluster analysis and principal component analysis were applied to discriminate these twenty-six batches based on characteristics of the bioactive compounds. The results indicated that this method is advance, rapid, sensitive and suitable to reveal the quality of Withania somnifera and also capable of performing quality evaluation of polyherbal formulations having similar markers/raw herbs. Copyright © 2016 Elsevier B.V. All rights reserved.

Application of random match probability calculations to mixed STR profiles.

PubMed

Bille, Todd; Bright, Jo-Anne; Buckleton, John

2013-03-01

Mixed DNA profiles are being encountered more frequently as laboratories analyze increasing amounts of touch evidence. If it is determined that an individual could be a possible contributor to the mixture, it is necessary to perform a statistical analysis to allow an assignment of weight to the evidence. Currently, the combined probability of inclusion (CPI) and the likelihood ratio (LR) are the most commonly used methods to perform the statistical analysis. A third method, random match probability (RMP), is available. This article compares the advantages and disadvantages of the CPI and LR methods to the RMP method. We demonstrate that although the LR method is still considered the most powerful of the binary methods, the RMP and LR methods make similar use of the observed data such as peak height, assumed number of contributors, and known contributors where the CPI calculation tends to waste information and be less informative. © 2013 American Academy of Forensic Sciences.

Implementation of the Veder contact method in daily nursing home care for people with dementia: a process analysis according to the RE-AIM framework.

PubMed

Boersma, Petra; van Weert, Julia C M; van Meijel, Berno; Dröes, Rose-Marie

2017-02-01

To perform a process analysis of the implementation of the Veder contact method for gaining insight into factors that influence successful implementation. Research showed that the original Veder method, which is a 'living-room theatre performance' provided by actors, positively influenced mood and quality of life of people with dementia. Training caregivers to execute such 'performances' and accomplish the same effects as actors proved difficult. However, key elements of the method were considered suitable for application in daily care, resulting in the development of a modified version of the method, named the Veder contact method. The Veder contact method combines elements from existing psychosocial interventions, e.g. reminiscence, validation and neuro-linguistic-programming with theatrical, poetic and musical communication, and applies this into daily care. For this process analysis a multiple case study design was used with the nursing home ward (n = 6) as the unit of analysis. Eight focus groups with caregivers (n = 42) and 12 interviews with stakeholders were held. Using the Reach, Effectiveness, Adoption, Implementation, Maintenance framework, a thematic analysis was conducted. The reach of the intervention (43-86%) and aspects of implementation-effectiveness (e.g. increased experienced reciprocity in contact with residents) facilitated implementation. For adoption and implementation, both facilitators (e.g. development of competences, feasibility of the Veder contact method without requiring extra time investment) and barriers (e.g. insufficient support of management, resistance of caregivers against the Veder contact method, organisational problems) were identified. Little effort was put into maintenance: only one nursing home developed a long-term implementation strategy. The Veder contact method can be applied in daily care without additional time investments. Although adopted by many caregivers, some were reluctant using the Veder contact method. Organisational factors (e.g. staffing and management changes, budget cuts) impeded long-term implementation. The findings from this study can be used for the development of successful implementation strategies for the Veder contact method and other person-centred care methods. © 2016 John Wiley & Sons Ltd.

Analytical approaches for MCPD esters and glycidyl esters in food and biological samples: a review and future perspectives.

PubMed

Crews, C; Chiodini, A; Granvogl, M; Hamlet, C; Hrnčiřík, K; Kuhlmann, J; Lampen, A; Scholz, G; Weisshaar, R; Wenzl, T; Jasti, P R; Seefelder, W

2013-01-01

Esters of 2 - and 3-monochloropropane-1,2-diol (MCPD) and glycidol esters are important contaminants of processed edible oils used as foods or food ingredients. This review describes the occurrence and analysis of MCPD esters and glycidol esters in vegetable oils and some other foods. The focus is on the analytical methods based on both direct and indirect methods. Methods of analysis applied to oils and lipid extracts of foods have been based on transesterification to free MCPD and determination by gas chromatography-mass spectrometry (indirect methods) and by high-performance liquid chromatography-mass spectrometry (direct methods). The evolution and performance of the different methods is described and their advantages and disadvantages are discussed. The application of direct and indirect methods to the analysis of foods and to research studies is described. The metabolism and fate of MCPD esters and glycidol esters in biological systems and the methods used to study these in body tissues studies are described. A clear understanding of the chemistry of the methods is important when choosing those suitable for the desired application, and will contribute to the mitigation of these contaminants.

Novel and successful free comments method for sensory characterization of chocolate ice cream: A comparative study between pivot profile and comment analysis.

PubMed

Fonseca, Fernando G A; Esmerino, Erick A; Filho, Elson R Tavares; Ferraz, Juliana P; da Cruz, Adriano G; Bolini, Helena M A

2016-05-01

Rapid sensory profiling methods have gained space in the sensory evaluation field. Techniques using direct analysis of the terms generated by consumers are considered easy to perform, without specific training requirements, thus improving knowledge about consumer perceptions on various products. This study aimed to determine the sensory profile of different commercial samples of chocolate ice cream, labeled as conventional and light or diet, using the "comment analysis" and "pivot profile" methods, based on consumers' perceptions. In the comment analysis task, consumers responded to 2 separate open questions describing the sensory attributes they liked or disliked in each sample. In the pivot profile method, samples were served in pairs (consisting of a coded sample and pivot), and consumers indicated the higher and lower intensity attributes in the target sample compared with the pivot. We observed that both methods were able to characterize the different chocolate ice cream samples using consumer perception, with high correlation results and configurational similarity (regression vector coefficient=0.917) between them. However, it is worth emphasizing that comment analysis is performed intuitively by consumers, whereas the pivot profile method showed high analytical and discriminative power even using consumers, proving to be a promising technique for routine application when classical descriptive methods cannot be used. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The comparative performance of PMI estimation in skeletal remains by three methods (C-14, luminol test and OHI): analysis of 20 cases.

PubMed

Cappella, Annalisa; Gibelli, Daniele; Muccino, Enrico; Scarpulla, Valentina; Cerutti, Elisa; Caruso, Valentina; Sguazza, Emanuela; Mazzarelli, Debora; Cattaneo, Cristina

2015-01-27

When estimating post-mortem interval (PMI) in forensic anthropology, the only method able to give an unambiguous result is the analysis of C-14, although the procedure is expensive. Other methods, such as luminol tests and histological analysis, can be performed as preliminary investigations and may allow the operators to gain a preliminary indication concerning PMI, but they lack scientific verification, although luminol testing has been somewhat more accredited in the past few years. Such methods in fact may provide some help as they are inexpensive and can give a fast response, especially in the phase of preliminary investigations. In this study, 20 court cases of human skeletonized remains were dated by the C-14 method. For two cases, results were chronologically set after the 1950s; for one case, the analysis was not possible technically. The remaining 17 cases showed an archaeological or historical collocation. The same bone samples were also screened with histological examination and with the luminol test. Results showed that only four cases gave a positivity to luminol and a high Oxford Histology Index (OHI) score at the same time: among these, two cases were dated as recent by the radiocarbon analysis. Thus, only two false-positive results were given by the combination of these methods and no false negatives. Thus, the combination of two qualitative methods (luminol test and microscopic analysis) may represent a promising solution to cases where many fragments need to be quickly tested.

Analysis of imazaquin in soybeans by solid-phase extraction and high-performance liquid chromatography.

PubMed

Guo, C; Hu, J-Y; Chen, X-Y; Li, J-Z

2008-02-01

An analytical method for the determination imazaquin residues in soybeans was developed. The developed liquid/liquid partition and strong anion exchange solid-phase extraction procedures provide the effective cleanup, removing the greatest number of sample matrix interferences. By optimizing mobile-phase pH water/acetonitrile conditions with phosphoric acid, using a C-18 reverse-phase chromatographic column and employing ultraviolet detection, excellent peak resolution was achieved. The combined cleanup and chromatographic method steps reported herein were sensitive and reliable for determining the imazaquin residues in soybean samples. This method is characterized by recovery >88.4%, precision <6.7% CV, and sensitivity of 0.005 ppm, in agreement with directives for method validation in residue analysis. Imazaquin residues in soybeans were further confirmed by high performance liquid chromatography-mass spectrometry (LC-MS). The proposed method was successfully applied to the analysis of imazaquin residues in soybean samples grown in an experimental field after treatments of imazaquin formulation.

Neutral monosaccharide composition analysis of plant-derived oligo- and polysaccharides by high performance liquid chromatography.

PubMed

Yan, Jun; Shi, Songshan; Wang, Hongwei; Liu, Ruimin; Li, Ning; Chen, Yonglin; Wang, Shunchun

2016-01-20

A novel analytical method for neutral monosaccharide composition analysis of plant-derived oligo- and polysaccharides was developed using hydrophilic interaction liquid chromatography coupled to a charged aerosol detector. The effects of column type, additives, pH and column temperature on retention and separation were evaluated. Additionally, the method could distinguish potential impurities in samples, including chloride, sulfate and sodium, from sugars. The results of validation demonstrated that this method had good linearity (R(2) ≥ 0.9981), high precision (relative standard deviation ≤ 4.43%), and adequate accuracy (94.02-103.37% recovery) and sensitivity (detection limit: 15-40 ng). Finally, the monosaccharide compositions of the polysaccharide from Eclipta prostrasta L. and stachyose were successfully profiled through this method. This report represents the first time that all of these common monosaccharides could be well-separated and determined simultaneously by high performance liquid chromatography without additional derivatization. This newly developed method is convenient, efficient and reliable for monosaccharide analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quanti cation, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.« less

Objective comparison of particle tracking methods.

PubMed

Chenouard, Nicolas; Smal, Ihor; de Chaumont, Fabrice; Maška, Martin; Sbalzarini, Ivo F; Gong, Yuanhao; Cardinale, Janick; Carthel, Craig; Coraluppi, Stefano; Winter, Mark; Cohen, Andrew R; Godinez, William J; Rohr, Karl; Kalaidzidis, Yannis; Liang, Liang; Duncan, James; Shen, Hongying; Xu, Yingke; Magnusson, Klas E G; Jaldén, Joakim; Blau, Helen M; Paul-Gilloteaux, Perrine; Roudot, Philippe; Kervrann, Charles; Waharte, François; Tinevez, Jean-Yves; Shorte, Spencer L; Willemse, Joost; Celler, Katherine; van Wezel, Gilles P; Dan, Han-Wei; Tsai, Yuh-Show; Ortiz de Solórzano, Carlos; Olivo-Marin, Jean-Christophe; Meijering, Erik

2014-03-01

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.

Computed tomographic-based quantification of emphysema and correlation to pulmonary function and mechanics.

PubMed

Washko, George R; Criner, Gerald J; Mohsenifar, Zab; Sciurba, Frank C; Sharafkhaneh, Amir; Make, Barry J; Hoffman, Eric A; Reilly, John J

2008-06-01

Computed tomographic based indices of emphysematous lung destruction may highlight differences in disease pathogenesis and further enable the classification of subjects with Chronic Obstructive Pulmonary Disease. While there are multiple techniques that can be utilized for such radiographic analysis, there is very little published information comparing the performance of these methods in a clinical case series. Our objective was to examine several quantitative and semi-quantitative methods for the assessment of the burden of emphysema apparent on computed tomographic scans and compare their ability to predict lung mechanics and function. Automated densitometric analysis was performed on 1094 computed tomographic scans collected upon enrollment into the National Emphysema Treatment Trial. Trained radiologists performed an additional visual grading of emphysema on high resolution CT scans. Full pulmonary function test results were available for correlation, with a subset of subjects having additional measurements of lung static recoil. There was a wide range of emphysematous lung destruction apparent on the CT scans and univariate correlations to measures of lung function were of modest strength. No single method of CT scan analysis clearly outperformed the rest of the group. Quantification of the burden of emphysematous lung destruction apparent on CT scan is a weak predictor of lung function and mechanics in severe COPD with no uniformly superior method found to perform this analysis. The CT based quantification of emphysema may augment pulmonary function testing in the characterization of COPD by providing complementary phenotypic information.

Analysis of messy data with heteroscedastic in mean models

NASA Astrophysics Data System (ADS)

Trianasari, Nurvita; Sumarni, Cucu

2016-02-01

In the analysis of the data, we often faced with the problem of data where the data did not meet some assumptions. In conditions of such data is often called data messy. This problem is a consequence of the data that generates outliers that bias or error estimation. To analyze the data messy, there are three approaches, namely standard analysis, transform data and data analysis methods rather than a standard. Simulations conducted to determine the performance of a third comparative test procedure on average often the model variance is not homogeneous. Data simulation of each scenario is raised as much as 500 times. Next, we do the analysis of the average comparison test using three methods, Welch test, mixed models and Welch-r test. Data generation is done through software R version 3.1.2. Based on simulation results, these three methods can be used for both normal and abnormal case (homoscedastic). The third method works very well on data balanced or unbalanced when there is no violation in the homogenity's assumptions variance. For balanced data, the three methods still showed an excellent performance despite the violation of the assumption of homogeneity of variance, with the requisite degree of heterogeneity is high. It can be shown from the level of power test above 90 percent, and the best to Welch method (98.4%) and the Welch-r method (97.8%). For unbalanced data, Welch method will be very good moderate at in case of heterogeneity positive pair with a 98.2% power. Mixed models method will be very good at case of highly heterogeneity was negative negative pairs with power. Welch-r method works very well in both cases. However, if the level of heterogeneity of variance is very high, the power of all method will decrease especially for mixed models methods. The method which still works well enough (power more than 50%) is Welch-r method (62.6%), and the method of Welch (58.6%) in the case of balanced data. If the data are unbalanced, Welch-r method works well enough in the case of highly heterogeneous positive positive or negative negative pairs, there power are 68.8% and 51% consequencly. Welch method perform well enough only in the case of highly heterogeneous variety of positive positive pairs with it is power of 64.8%. While mixed models method is good in the case of a very heterogeneous variety of negative partner with 54.6% power. So in general, when there is a variance is not homogeneous case, Welch method is applied to the data rank (Welch-r) has a better performance than the other methods.

Spectroscopic chemical analysis methods and apparatus

NASA Technical Reports Server (NTRS)

Hug, William F. (Inventor); Reid, Ray D. (Inventor); Bhartia, Rohit (Inventor)

2013-01-01

Spectroscopic chemical analysis methods and apparatus are disclosed which employ deep ultraviolet (e.g. in the 200 nm to 300 nm spectral range) electron beam pumped wide bandgap semiconductor lasers, incoherent wide bandgap semiconductor light emitting devices, and hollow cathode metal ion lasers to perform non-contact, non-invasive detection of unknown chemical analytes. These deep ultraviolet sources enable dramatic size, weight and power consumption reductions of chemical analysis instruments. Chemical analysis instruments employed in some embodiments include capillary and gel plane electrophoresis, capillary electrochromatography, high performance liquid chromatography, flow cytometry, flow cells for liquids and aerosols, and surface detection instruments. In some embodiments, Raman spectroscopic detection methods and apparatus use ultra-narrow-band angle tuning filters, acousto-optic tuning filters, and temperature tuned filters to enable ultra-miniature analyzers for chemical identification. In some embodiments Raman analysis is conducted along with photoluminescence spectroscopy (i.e. fluorescence and/or phosphorescence spectroscopy) to provide high levels of sensitivity and specificity in the same instrument.

GEOS-2 C-band radar system project. Spectral analysis as related to C-band radar data analysis

NASA Technical Reports Server (NTRS)

1972-01-01

Work performed on spectral analysis of data from the C-band radars tracking GEOS-2 and on the development of a data compaction method for the GEOS-2 C-band radar data is described. The purposes of the spectral analysis study were to determine the optimum data recording and sampling rates for C-band radar data and to determine the optimum method of filtering and smoothing the data. The optimum data recording and sampling rate is defined as the rate which includes an optimum compromise between serial correlation and the effects of frequency folding. The goal in development of a data compaction method was to reduce to a minimum the amount of data stored, while maintaining all of the statistical information content of the non-compacted data. A digital computer program for computing estimates of the power spectral density function of sampled data was used to perform the spectral analysis study.

Dynamic test/analysis correlation using reduced analytical models

NASA Technical Reports Server (NTRS)

Mcgowan, Paul E.; Angelucci, A. Filippo; Javeed, Mehzad

1992-01-01

Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System (IRS) reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

Differences in the Performance of Children with Specific Language Impairment and Their Typically Developing Peers on Nonverbal Cognitive Tests: A Meta-Analysis

ERIC Educational Resources Information Center

Gallinat, Erica; Spaulding, Tammie J.

2014-01-01

Purpose: This study used meta-analysis to investigate the difference in nonverbal cognitive test performance of children with specific language impairment (SLI) and their typically developing (TD) peers. Method: The meta-analysis included studies (a) that were published between 1995 and 2012 of children with SLI who were age matched (and not…

Insulation commonality assessment (phase 1). Volume 2: Section 7.0 through 16.0. [evaluation of materials used for spacecraft thermal insulation

NASA Technical Reports Server (NTRS)

1973-01-01

The heat transfer characteristics of various materials used for the thermal insulation of spacecraft are discussed. Techniques for conducting thermal performance analysis, structural performance analysis, and dynamic analysis are described. Processes for producing and finishing the materials are explained. The methods for determining reliability, system safety, materials tests, and design effectiveness are explained.

Bridging Human Reliability Analysis and Psychology, Part 1: The Psychological Literature Review for the IDHEAS Method

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

April M. Whaley; Stacey M. L. Hendrickson; Ronald L. Boring

In response to Staff Requirements Memorandum (SRM) SRM-M061020, the U.S. Nuclear Regulatory Commission (NRC) is sponsoring work to update the technical basis underlying human reliability analysis (HRA) in an effort to improve the robustness of HRA. The ultimate goal of this work is to develop a hybrid of existing methods addressing limitations of current HRA models and in particular issues related to intra- and inter-method variabilities and results. This hybrid method is now known as the Integrated Decision-tree Human Event Analysis System (IDHEAS). Existing HRA methods have looked at elements of the psychological literature, but there has not previously beenmore » a systematic attempt to translate the complete span of cognition from perception to action into mechanisms that can inform HRA. Therefore, a first step of this effort was to perform a literature search of psychology, cognition, behavioral science, teamwork, and operating performance to incorporate current understanding of human performance in operating environments, thus affording an improved technical foundation for HRA. However, this literature review went one step further by mining the literature findings to establish causal relationships and explicit links between the different types of human failures, performance drivers and associated performance measures ultimately used for quantification. This is the first of two papers that detail the literature review (paper 1) and its product (paper 2). This paper describes the literature review and the high-level architecture used to organize the literature review, and the second paper (Whaley, Hendrickson, Boring, & Xing, these proceedings) describes the resultant cognitive framework.« less

Performance evaluation of infrared imaging system in field test

NASA Astrophysics Data System (ADS)

Wang, Chensheng; Guo, Xiaodong; Ren, Tingting; Zhang, Zhi-jie

2014-11-01

Infrared imaging system has been applied widely in both military and civilian fields. Since the infrared imager has various types and different parameters, for system manufacturers and customers, there is great demand for evaluating the performance of IR imaging systems with a standard tool or platform. Since the first generation IR imager was developed, the standard method to assess the performance has been the MRTD or related improved methods which are not perfect adaptable for current linear scanning imager or 2D staring imager based on FPA detector. For this problem, this paper describes an evaluation method based on the triangular orientation discrimination metric which is considered as the effective and emerging method to evaluate the synthesis performance of EO system. To realize the evaluation in field test, an experiment instrument is developed. And considering the importance of operational environment, the field test is carried in practical atmospheric environment. The test imagers include panoramic imaging system and staring imaging systems with different optics and detectors parameters (both cooled and uncooled). After showing the instrument and experiment setup, the experiment results are shown. The target range performance is analyzed and discussed. In data analysis part, the article gives the range prediction values obtained from TOD method, MRTD method and practical experiment, and shows the analysis and results discussion. The experimental results prove the effectiveness of this evaluation tool, and it can be taken as a platform to give the uniform performance prediction reference.

Comparing the performance of FA, DFA and DMA using different synthetic long-range correlated time series

PubMed Central

Shao, Ying-Hui; Gu, Gao-Feng; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Sornette, Didier

2012-01-01

Notwithstanding the significant efforts to develop estimators of long-range correlations (LRC) and to compare their performance, no clear consensus exists on what is the best method and under which conditions. In addition, synthetic tests suggest that the performance of LRC estimators varies when using different generators of LRC time series. Here, we compare the performances of four estimators [Fluctuation Analysis (FA), Detrended Fluctuation Analysis (DFA), Backward Detrending Moving Average (BDMA), and Centred Detrending Moving Average (CDMA)]. We use three different generators [Fractional Gaussian Noises, and two ways of generating Fractional Brownian Motions]. We find that CDMA has the best performance and DFA is only slightly worse in some situations, while FA performs the worst. In addition, CDMA and DFA are less sensitive to the scaling range than FA. Hence, CDMA and DFA remain “The Methods of Choice” in determining the Hurst index of time series. PMID:23150785

Performances of CN-columns for the analysis of γ-oryzanol and its p-coumarate and caffeate derivatives by normal phase HPLC and a validated method of quantitation.

PubMed

D'Ambrosio, Michele

2013-06-15

γ-Oryzanol is an important phytochemical used in pharmaceutical, alimentary and cosmetic preparations. The present article, for the first time, discloses the performances of NP-HPLC in separating γ-oryzanol components and develops a validated method for its routine quantification. The analysis is performed on a cyanopropyl bonded column using the hexane/MTBE gradient elution and UV detection at 325 nm. The method allows: the separation of steryl ferulate, p-coumarate and caffeate esters, the separation of cis- from trans-ferulate isomers, the splitting of steroid moieties into saturated and unsaturated at the side chain. The optimised method provides excellent linear response (R(2)=0.99997), high precision (RSD<1.0%) and satisfactory accuracy (R(∗)=70-86%). In conclusion, the established method presents the details of the procedure and the experimental conditions in order to achieve the required precision and instrumental accuracy. The method is fast and sensitive and it could be a suitable tool for quality assurance and determination of origin. Copyright © 2012 Elsevier Ltd. All rights reserved.

IDHEAS – A NEW APPROACH FOR HUMAN RELIABILITY ANALYSIS

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

G. W. Parry; J.A Forester; V.N. Dang

2013-09-01

This paper describes a method, IDHEAS (Integrated Decision-Tree Human Event Analysis System) that has been developed jointly by the US NRC and EPRI as an improved approach to Human Reliability Analysis (HRA) that is based on an understanding of the cognitive mechanisms and performance influencing factors (PIFs) that affect operator responses. The paper describes the various elements of the method, namely the performance of a detailed cognitive task analysis that is documented in a crew response tree (CRT), and the development of the associated time-line to identify the critical tasks, i.e. those whose failure results in a human failure eventmore » (HFE), and an approach to quantification that is based on explanations of why the HFE might occur.« less

Quantitative Analysis of Ca, Mg, and K in the Roots of Angelica pubescens f. biserrata by Laser-Induced Breakdown Spectroscopy Combined with Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Wang, J.; Shi, M.; Zheng, P.; Xue, Sh.; Peng, R.

2018-03-01

Laser-induced breakdown spectroscopy has been applied for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens Maxim. f. biserrata Shan et Yuan used in traditional Chinese medicine. Ca II 317.993 nm, Mg I 517.268 nm, and K I 769.896 nm spectral lines have been chosen to set up calibration models for the analysis using the external standard and artificial neural network methods. The linear correlation coefficients of the predicted concentrations versus the standard concentrations of six samples determined by the artificial neural network method are 0.9896, 0.9945, and 0.9911 for Ca, Mg, and K, respectively, which are better than for the external standard method. The artificial neural network method also gives better performance comparing with the external standard method for the average and maximum relative errors, average relative standard deviations, and most maximum relative standard deviations of the predicted concentrations of Ca, Mg, and K in the six samples. Finally, it is proved that the artificial neural network method gives better performance compared to the external standard method for the quantitative analysis of Ca, Mg, and K in the roots of Angelica pubescens.

Evaluating Service Quality from Patients' Perceptions: Application of Importance-performance Analysis Method.

PubMed

Mohebifar, Rafat; Hasani, Hana; Barikani, Ameneh; Rafiei, Sima

2016-08-01

Providing high service quality is one of the main functions of health systems. Measuring service quality is the basic prerequisite for improving quality. The aim of this study was to evaluate the quality of service in teaching hospitals using importance-performance analysis matrix. A descriptive-analytic study was conducted through a cross-sectional method in six academic hospitals of Qazvin, Iran, in 2012. A total of 360 patients contributed to the study. The sampling technique was stratified random sampling. Required data were collected based on a standard questionnaire (SERVQUAL). Data analysis was done through SPSS version 18 statistical software and importance-performance analysis matrix. The results showed a significant gap between importance and performance in all five dimensions of service quality (p < 0.05). In reviewing the gap, "reliability" (2.36) and "assurance" (2.24) dimensions had the highest quality gap and "responsiveness" had the lowest gap (1.97). Also, according to findings, reliability and assurance were in Quadrant (I), empathy was in Quadrant (II), and tangibles and responsiveness were in Quadrant (IV) of the importance-performance matrix. The negative gap in all dimensions of quality shows that quality improvement is necessary in all dimensions. Using quality and diagnosis measurement instruments such as importance-performance analysis will help hospital managers with planning of service quality improvement and achieving long-term goals.

Challenges in leveraging existing human performance data for quantifying the IDHEAS HRA method

DOE PAGES

Liao, Huafei N.; Groth, Katrina; Stevens-Adams, Susan

2015-07-29

Our article documents an exploratory study for collecting and using human performance data to inform human error probability (HEP) estimates for a new human reliability analysis (HRA) method, the IntegrateD Human Event Analysis System (IDHEAS). The method was based on cognitive models and mechanisms underlying human behaviour and employs a framework of 14 crew failure modes (CFMs) to represent human failures typical for human performance in nuclear power plant (NPP) internal, at-power events [1]. A decision tree (DT) was constructed for each CFM to assess the probability of the CFM occurring in different contexts. Data needs for IDHEAS quantification aremore » discussed. Then, the data collection framework and process is described and how the collected data were used to inform HEP estimation is illustrated with two examples. Next, five major technical challenges are identified for leveraging human performance data for IDHEAS quantification. Furthermore, these challenges reflect the data needs specific to IDHEAS. More importantly, they also represent the general issues with current human performance data and can provide insight for a path forward to support HRA data collection, use, and exchange for HRA method development, implementation, and validation.« less

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

PubMed Central

2017-01-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

Calibration and Data Analysis of the MC-130 Air Balance

NASA Technical Reports Server (NTRS)

Booth, Dennis; Ulbrich, N.

2012-01-01

Design, calibration, calibration analysis, and intended use of the MC-130 air balance are discussed. The MC-130 balance is an 8.0 inch diameter force balance that has two separate internal air flow systems and one external bellows system. The manual calibration of the balance consisted of a total of 1854 data points with both unpressurized and pressurized air flowing through the balance. A subset of 1160 data points was chosen for the calibration data analysis. The regression analysis of the subset was performed using two fundamentally different analysis approaches. First, the data analysis was performed using a recently developed extension of the Iterative Method. This approach fits gage outputs as a function of both applied balance loads and bellows pressures while still allowing the application of the iteration scheme that is used with the Iterative Method. Then, for comparison, the axial force was also analyzed using the Non-Iterative Method. This alternate approach directly fits loads as a function of measured gage outputs and bellows pressures and does not require a load iteration. The regression models used by both the extended Iterative and Non-Iterative Method were constructed such that they met a set of widely accepted statistical quality requirements. These requirements lead to reliable regression models and prevent overfitting of data because they ensure that no hidden near-linear dependencies between regression model terms exist and that only statistically significant terms are included. Finally, a comparison of the axial force residuals was performed. Overall, axial force estimates obtained from both methods show excellent agreement as the differences of the standard deviation of the axial force residuals are on the order of 0.001 % of the axial force capacity.

Improved score statistics for meta-analysis in single-variant and gene-level association studies.

PubMed

Yang, Jingjing; Chen, Sai; Abecasis, Gonçalo

2018-06-01

Meta-analysis is now an essential tool for genetic association studies, allowing them to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate the power loss problem by the standard meta-analysis methods for unbalanced studies, and further propose novel meta-analysis methods performing equivalently to the joint analysis under both balanced and unbalanced settings. We derive improved meta-score-statistics that can accurately approximate the joint-score-statistics with combined individual-level data, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies. In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard methods. We further showed the power gain of our methods in gene-level tests with 26 unbalanced studies of age-related macular degeneration . In addition, we took the meta-analysis of three unbalanced studies of type 2 diabetes as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, our improved meta-score-statistics with corrections for population stratification can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses. © 2018 WILEY PERIODICALS, INC.

Quantitative analysis of benzodiazepines in vitreous humor by high-performance liquid chromatography

PubMed Central

Bazmi, Elham; Behnoush, Behnam; Akhgari, Maryam; Bahmanabadi, Leila

2016-01-01

Objective: Benzodiazepines are frequently screened drugs in emergency toxicology, drugs of abuse testing, and in forensic cases. As the variations of benzodiazepines concentrations in biological samples during bleeding, postmortem changes, and redistribution could be biasing forensic medicine examinations, hence selecting a suitable sample and a validated accurate method is essential for the quantitative analysis of these main drug categories. The aim of this study was to develop a valid method for the determination of four benzodiazepines (flurazepam, lorazepam, alprazolam, and diazepam) in vitreous humor using liquid–liquid extraction and high-performance liquid chromatography. Methods: Sample preparation was carried out using liquid–liquid extraction with n-hexane: ethyl acetate and subsequent detection by high-performance liquid chromatography method coupled to diode array detector. This method was applied to quantify benzodiazepines in 21 authentic vitreous humor samples. Linear curve for each drug was obtained within the range of 30–3000 ng/mL with coefficient of correlation higher than 0.99. Results: The limit of detection and quantitation were 30 and 100 ng/mL respectively for four drugs. The method showed an appropriate intra- and inter-day precision (coefficient of variation < 10%). Benzodiazepines recoveries were estimated to be over 80%. The method showed high selectivity; no additional peak due to interfering substances in samples was observed. Conclusion: The present method was selective, sensitive, accurate, and precise for the quantitative analysis of benzodiazepines in vitreous humor samples in forensic toxicology laboratory. PMID:27635251

FE-DEM Analysis of the Effect of Tread Pattern on the Tractive Performance of Tires Operating on Sand

NASA Astrophysics Data System (ADS)

Nakashima, Hiroshi; Takatsu, Yuzuru; Shinone, Hisanori; Matsukawa, Hisao; Kasetani, Takahiro

Soil-tire system interaction is a fundamental and important research topic in terramechanics. We applied a 2D finite element, discrete element method (FE-DEM), using FEM for the tire and the bottom soil layer and DEM for the surface soil layer. Satisfactory performance analysis was achieved. In this study, to clarify the capabilities and limitations of the method for soil-tire interaction analysis, the tractive performance of real automobile tires with two different tread patterns—smooth and grooved—was analyzed by FE-DEM, and the numerical results compared with the experimental results obtained using an indoor traction measurement system. The analysis of tractive performance could be performed with sufficient accuracy by the proposed 2D dynamic FE-DEM. FE-DEM obtained larger drawbar pull for a tire with a grooved tread pattern, which was verified by the experimental results. Moreover, the result for the grooved tire showed almost the same gross tractive effort and similar running resistance as in experiments. However, for a tire with smooth tread pattern, the analyzed gross tractive effort and running resistance behaved differently than the experimental results, largely due to the difference in tire sinkage in FE-DEM.

Classifying Higher Education Institutions in Korea: A Performance-Based Approach

ERIC Educational Resources Information Center

Shin, Jung Cheol

2009-01-01

The purpose of this study was to classify higher education institutions according to institutional performance rather than predetermined benchmarks. Institutional performance was defined as research performance and classified using Hierarchical Cluster Analysis, a statistical method that classifies objects according to specified classification…

Nondestructive examination using neutron activated positron annihilation

DOEpatents

Akers, Douglas W.; Denison, Arthur B.

2001-01-01

A method is provided for performing nondestructive examination of a metal specimen using neutron activated positron annihilation wherein the positron emitter source is formed within the metal specimen. The method permits in situ nondestructive examination and has the advantage of being capable of performing bulk analysis to determine embrittlement, fatigue and dislocation within a metal specimen.

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

Harris, L.; Owel, W.R.

This paper discusses the VISA (Vulnerability of Integrated Safeguards Analysis) method, developed in 1976-77 for the Nuclear Regulatory Commission, and which has been adapted more recently to a broader range of uses. The performance of VISA systems is evaluated in terms of how they perform as an integrated safeguards/security system. The resulting method has been designated VISA-2. 7 refs.

High Performance Liquid Chromatographic Analysis of Phytoplankton Pigments Using a C16-Amide Column

EPA Science Inventory

A reverse-phase high performance liquid chromatographic (RP-HPLC) method was developed to analyze in a single run, most polar and non-polar chlorophylls and carotenoids from marine phytoplankton. The method is based on a RP-C16-Amide column and a ternary gradient system consistin...

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Big Data Toolsets to Pharmacometrics: Application of Machine Learning for Time-to-Event Analysis.

PubMed

Gong, Xiajing; Hu, Meng; Zhao, Liang

2018-05-01

Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized under various preset scenarios, i.e., with linear vs. nonlinear and dependent vs. independent predictors in the proportional hazard function, or with high-dimensional data featured by a large number of predictor variables. Our results showed that ML-based methods outperformed the Cox model in prediction performance as assessed by concordance index and in identifying the preset influential variables for high-dimensional data. The prediction performances of ML-based methods are also less sensitive to data size and censoring rates than the Cox regression model. In conclusion, ML-based methods provide a powerful tool for time-to-event analysis, with a built-in capacity for high-dimensional data and better performance when the predictor variables assume nonlinear relationships in the hazard function. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Redundancy analysis allows improved detection of methylation changes in large genomic regions.

PubMed

Ruiz-Arenas, Carlos; González, Juan R

2017-12-14

DNA methylation is an epigenetic process that regulates gene expression. Methylation can be modified by environmental exposures and changes in the methylation patterns have been associated with diseases. Methylation microarrays measure methylation levels at more than 450,000 CpGs in a single experiment, and the most common analysis strategy is to perform a single probe analysis to find methylation probes associated with the outcome of interest. However, methylation changes usually occur at the regional level: for example, genomic structural variants can affect methylation patterns in regions up to several megabases in length. Existing DMR methods provide lists of Differentially Methylated Regions (DMRs) of up to only few kilobases in length, and cannot check if a target region is differentially methylated. Therefore, these methods are not suitable to evaluate methylation changes in large regions. To address these limitations, we developed a new DMR approach based on redundancy analysis (RDA) that assesses whether a target region is differentially methylated. Using simulated and real datasets, we compared our approach to three common DMR detection methods (Bumphunter, blockFinder, and DMRcate). We found that Bumphunter underestimated methylation changes and blockFinder showed poor performance. DMRcate showed poor power in the simulated datasets and low specificity in the real data analysis. Our method showed very high performance in all simulation settings, even with small sample sizes and subtle methylation changes, while controlling type I error. Other advantages of our method are: 1) it estimates the degree of association between the DMR and the outcome; 2) it can analyze a targeted or region of interest; and 3) it can evaluate the simultaneous effects of different variables. The proposed methodology is implemented in MEAL, a Bioconductor package designed to facilitate the analysis of methylation data. We propose a multivariate approach to decipher whether an outcome of interest alters the methylation pattern of a region of interest. The method is designed to analyze large target genomic regions and outperforms the three most popular methods for detecting DMRs. Our method can evaluate factors with more than two levels or the simultaneous effect of more than one continuous variable, which is not possible with the state-of-the-art methods.

Failure analysis of electronic parts: Laboratory methods. [for destructive and nondestructive testing

NASA Technical Reports Server (NTRS)

Anstead, R. J. (Editor); Goldberg, E. (Editor)

1975-01-01

Failure analysis test methods are presented for use in analyzing candidate electronic parts and in improving future design reliability. Each test is classified as nondestructive, semidestructive, or destructive. The effects upon applicable part types (i.e. integrated circuit, transitor) are discussed. Methodology is given for performing the following: immersion tests, radio graphic tests, dewpoint tests, gas ambient analysis, cross sectioning, and ultraviolet examination.

Task 2 Report: Algorithm Development and Performance Analysis

DTIC Science & Technology

1993-07-01

separated peaks ............................................. 39 7-16 Example ILGC data for schedule 3 phosphites showing an analysis method which integrates...more closely follows the baseline ................. 40 7-18 Example R.GC data for schedule 3 phosphites showing an analysis method resulting in unwanted...much of the ambiguity that can arise in GC/MS with trace environmental samples, for example. Correlated chromatography, on the other hand, separates the

A new automated spectral feature extraction method and its application in spectral classification and defective spectra recovery

NASA Astrophysics Data System (ADS)

Wang, Ke; Guo, Ping; Luo, A.-Li

2017-03-01

Spectral feature extraction is a crucial procedure in automated spectral analysis. This procedure starts from the spectral data and produces informative and non-redundant features, facilitating the subsequent automated processing and analysis with machine-learning and data-mining techniques. In this paper, we present a new automated feature extraction method for astronomical spectra, with application in spectral classification and defective spectra recovery. The basic idea of our approach is to train a deep neural network to extract features of spectra with different levels of abstraction in different layers. The deep neural network is trained with a fast layer-wise learning algorithm in an analytical way without any iterative optimization procedure. We evaluate the performance of the proposed scheme on real-world spectral data. The results demonstrate that our method is superior regarding its comprehensive performance, and the computational cost is significantly lower than that for other methods. The proposed method can be regarded as a new valid alternative general-purpose feature extraction method for various tasks in spectral data analysis.

Effects of Small-Group Learning on Transfer: A Meta-Analysis

ERIC Educational Resources Information Center

Pai, Hui-Hua; Sears, David A.; Maeda, Yukiko

2015-01-01

This study investigated the potential benefit of small-group learning on transfer performance using the method of meta-analysis. Results showed positive support for the hypothesis that small-group learning can increase students' transfer performance (average effect size of 0.30). Unlike reviews of effects of cooperation on learning, this…

Error Ratio Analysis: Alternate Mathematics Assessment for General and Special Educators.

ERIC Educational Resources Information Center

Miller, James H.; Carr, Sonya C.

1997-01-01

Eighty-seven elementary students in grades four, five, and six, were administered a 30-item multiplication instrument to assess performance in computation across grade levels. An interpretation of student performance using error ratio analysis is provided and the use of this method with groups of students for instructional decision making is…

Human Schedule Performance, Protocol Analysis, and the "Silent Dog" Methodology

ERIC Educational Resources Information Center

Cabello, Francisco; Luciano, Carmen; Gomez, Inmaculada; Barnes-Holmes, Dermot

2004-01-01

The purpose of the current experiment was to investigate the role of private verbal behavior on the operant performances of human adults, using a protocol analysis procedure with additional methodological controls (the "silent dog" method). Twelve subjects were exposed to fixed ratio 8 and differential reinforcement of low rate 3-s schedules. For…

Increasing the percentage of renewable energy in the Southwestern United States

USDA-ARS?s Scientific Manuscript database

An analysis was performed on the states in the Southwestern United States to determine methods to increase the proportion of wind and solar generated electricity in those states to levels as high as 40% of total electricity used. This analysis was performed by comparing the monthly and diurnal elect...

Demonstrating the Financial Benefit of Human Resource Development: Status and Update on the Theory and Practice.

ERIC Educational Resources Information Center

Swanson, Richard A.

1998-01-01

A research review identified findings about the financial analysis method, forecasting of the financial benefits of human resource development (HRD), and recent financial analysis research: (1) HRD embedded in a performance improvement framework yielded high return on investment; and (2) HRD interventions focused on performance variables forecast…

Demonstration and Evaluation of Solid Phase Microextraction for the Assessment of Bioavailability and Contaminant Mobility. ESTCP Cost and Performance Report

DTIC Science & Technology

2012-08-01

subsequent chemical analysis (into acetonitrile for high-performance liquid chromatography [ HPLC ] analysis or hexane for gas chromatography [GC... analysis ) is rapid and complete. In this work, PAHs were analyzed by Waters 2795 HPLC with fluorescent detection (USEPA Method 8310) and PCBs were...detection limits by direct water injection versus SPME with PDMS and coefficient of variation and correlation coefficient for SPME. Analysis by HPLC

The role of motion analysis in elite soccer: contemporary performance measurement techniques and work rate data.

PubMed

Carling, Christopher; Bloomfield, Jonathan; Nelsen, Lee; Reilly, Thomas

2008-01-01

The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game, especially due to the increased physical demands of match-play. The monitoring of players' work rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university-based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players' physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role that motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, and identify practical implications of the established body of knowledge, while highlighting areas that require further exploration.

Methods of analyzing crude oil

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

Cooks, Robert Graham; Jjunju, Fred Paul Mark; Li, Anyin

The invention generally relates to methods of analyzing crude oil. In certain embodiments, methods of the invention involve obtaining a crude oil sample, and subjecting the crude oil sample to mass spectrometry analysis. In certain embodiments, the method is performed without any sample pre-purification steps.

Data-driven freeway performance evaluation framework for project prioritization and decision making.

DOT National Transportation Integrated Search

2017-01-01

This report describes methods that potentially can be incorporated into the performance monitoring and planning processes for freeway performance evaluation and decision making. Reliability analysis was conducted on the selected I-15 corridor by empl...

Data-driven freeway performance evaluation framework for project prioritization and decision making.

DOT National Transportation Integrated Search

2015-03-01

This report describes methods that potentially can be incorporated into the performance monitoring and planning : processes for freeway performance evaluation and decision making. Reliability analysis is conducted on the selected : I-15 corridor by e...

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

Fan fault diagnosis based on symmetrized dot pattern analysis and image matching

NASA Astrophysics Data System (ADS)

Xu, Xiaogang; Liu, Haixiao; Zhu, Hao; Wang, Songling

2016-07-01

To detect the mechanical failure of fans, a new diagnostic method based on the symmetrized dot pattern (SDP) analysis and image matching is proposed. Vibration signals of 13 kinds of running states are acquired on a centrifugal fan test bed and reconstructed by the SDP technique. The SDP pattern templates of each running state are established. An image matching method is performed to diagnose the fault. In order to improve the diagnostic accuracy, the single template, multiple templates and clustering fault templates are used to perform the image matching.

Performance Analysis and Design Synthesis (PADS) computer program. Volume 3: User manual

NASA Technical Reports Server (NTRS)

1972-01-01

The two-fold purpose of the Performance Analysis and Design Synthesis (PADS) computer program is discussed. The program can size launch vehicles in conjunction with calculus-of-variations optimal trajectories and can also be used as a general purpose branched trajectory optimization program. For trajectory optimization alone or with sizing, PADS has two trajectory modules. The first trajectory module uses the method of steepest descent. The second module uses the method of quasi-linearization, which requires a starting solution from the first trajectory module.

Automated Parameter Studies Using a Cartesian Method

NASA Technical Reports Server (NTRS)

Murman, Scott M.; Aftosimis, Michael J.; Nemec, Marian

2004-01-01

Computational Fluid Dynamics (CFD) is now routinely used to analyze isolated points in a design space by performing steady-state computations at fixed flight conditions (Mach number, angle of attack, sideslip), for a fixed geometric configuration of interest. This "point analysis" provides detailed information about the flowfield, which aides an engineer in understanding, or correcting, a design. A point analysis is typically performed using high fidelity methods at a handful of critical design points, e.g. a cruise or landing configuration, or a sample of points along a flight trajectory.

[Rapid detection of caffeine in blood by freeze-out extraction].

PubMed

Bekhterev, V N; Gavrilova, S N; Kozina, E P; Maslakov, I V

2010-01-01

A new method for the detection of caffeine in blood has been proposed based on the combination of extraction and freezing-out to eliminate the influence of sample matrix. Metrological characteristics of the method are presented. Selectivity of detection is achieved by optimal conditions of analysis by high performance liquid chromatography. The method is technically simple and cost-efficient, it ensures rapid performance of the studies.

Validation of Ion Chromatographic Method for Determination of Standard Inorganic Anions in Treated and Untreated Drinking Water

NASA Astrophysics Data System (ADS)

Ivanova, V.; Surleva, A.; Koleva, B.

2018-06-01

An ion chromatographic method for determination of fluoride, chloride, nitrate and sulphate in untreated and treated drinking waters was described. An automated 850 IC Professional, Metrohm system equipped with conductivity detector and Metrosep A Supp 7-250 (250 x 4 mm) column was used. The validation of the method was performed for simultaneous determination of all studied analytes and the results have showed that the validated method fits the requirements of the current water legislation. The main analytical characteristics were estimated for each of studied analytes: limits of detection, limits of quantification, working and linear ranges, repeatability and intermediate precision, recovery. The trueness of the method was estimated by analysis of certified reference material for soft drinking water. Recovery test was performed on spiked drinking water samples. An uncertainty was estimated. The method was applied for analysis of drinking waters before and after chlorination.

Incorporating uncertainty regarding applicability of evidence from meta-analyses into clinical decision making.

PubMed

Kriston, Levente; Meister, Ramona

2014-03-01

Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.

[Qualitative and quantitative analysis of amygdalin and its metabolite prunasin in plasma by ultra-high performance liquid chromatography-tandem quadrupole time of flight mass spectrometry and ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry].

PubMed

Gao, Meng; Wang, Yuesheng; Wei, Huizhen; Ouyang, Hui; He, Mingzhen; Zeng, Lianqing; Shen, Fengyun; Guo, Qiang; Rao, Yi

2014-06-01

A method was developed for the determination of amygdalin and its metabolite prunasin in rat plasma after intragastric administration of Maxing shigan decoction. The analytes were identified by ultra-high performance liquid chromatography-tandem quadrupole time of flight mass spectrometry and quantitatively determined by ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry. After purified by liquid-liquid extraction, the qualitative analysis of amygdalin and prunasin in the plasma sample was performed on a Shim-pack XR-ODS III HPLC column (75 mm x 2.0 mm, 1.6 microm), using acetonitrile-0.1% (v/v) formic acid aqueous solution. The detection was performed on a Triple TOF 5600 quadrupole time of flight mass spectrometer. The quantitative analysis of amygdalin and prunasin in the plasma sample was performed by separation on an Agilent C18 HPLC column (50 mm x 2.1 mm, 1.7 microm), using acetonitrile-0.1% (v/v) formic acid aqueous solution. The detection was performed on an AB Q-TRAP 4500 triple quadrupole mass spectrometer utilizing electrospray ionization (ESI) interface operated in negative ion mode and multiple-reaction monitoring (MRM) mode. The qualitative analysis results showed that amygdalin and its metabolite prunasin were detected in the plasma sample. The quantitative analysis results showed that the linear range of amygdalin was 1.05-4 200 ng/mL with the correlation coefficient of 0.999 0 and the linear range of prunasin was 1.25-2 490 ng/mL with the correlation coefficient of 0.997 0. The method had a good precision with the relative standard deviations (RSDs) lower than 9.20% and the overall recoveries varied from 82.33% to 95.25%. The limits of detection (LODs) of amygdalin and prunasin were 0.50 ng/mL. With good reproducibility, the method is simple, fast and effective for the qualitative and quantitative analysis of the amygdalin and prunasin in plasma sample of rats which were administered by Maxing shigan decoction.

Model Reduction via Principe Component Analysis and Markov Chain Monte Carlo (MCMC) Methods

NASA Astrophysics Data System (ADS)

Gong, R.; Chen, J.; Hoversten, M. G.; Luo, J.

2011-12-01

Geophysical and hydrogeological inverse problems often include a large number of unknown parameters, ranging from hundreds to millions, depending on parameterization and problems undertaking. This makes inverse estimation and uncertainty quantification very challenging, especially for those problems in two- or three-dimensional spatial domains. Model reduction technique has the potential of mitigating the curse of dimensionality by reducing total numbers of unknowns while describing the complex subsurface systems adequately. In this study, we explore the use of principal component analysis (PCA) and Markov chain Monte Carlo (MCMC) sampling methods for model reduction through the use of synthetic datasets. We compare the performances of three different but closely related model reduction approaches: (1) PCA methods with geometric sampling (referred to as 'Method 1'), (2) PCA methods with MCMC sampling (referred to as 'Method 2'), and (3) PCA methods with MCMC sampling and inclusion of random effects (referred to as 'Method 3'). We consider a simple convolution model with five unknown parameters as our goal is to understand and visualize the advantages and disadvantages of each method by comparing their inversion results with the corresponding analytical solutions. We generated synthetic data with noise added and invert them under two different situations: (1) the noised data and the covariance matrix for PCA analysis are consistent (referred to as the unbiased case), and (2) the noise data and the covariance matrix are inconsistent (referred to as biased case). In the unbiased case, comparison between the analytical solutions and the inversion results show that all three methods provide good estimates of the true values and Method 1 is computationally more efficient. In terms of uncertainty quantification, Method 1 performs poorly because of relatively small number of samples obtained, Method 2 performs best, and Method 3 overestimates uncertainty due to inclusion of random effects. However, in the biased case, only Method 3 correctly estimates all the unknown parameters, and both Methods 1 and 2 provide wrong values for the biased parameters. The synthetic case study demonstrates that if the covariance matrix for PCA analysis is inconsistent with true models, the PCA methods with geometric or MCMC sampling will provide incorrect estimates.

Evaluation of the Match External Load in Soccer: Methods Comparison.

PubMed

Castagna, Carlo; Varley, Matthew; Póvoas, Susana C A; D'Ottavio, Stefano

2017-04-01

To test the interchangeability of 2 match-analysis approaches for external-load detection considering arbitrary selected speeds and metabolic power (MP) thresholds in male top-level soccer. Data analyses were performed considering match physical performance of 60 matches (1200 player cases) of randomly selected Spanish, German, and English first-division championship matches (2013-14 season). Match analysis was performed with a validated semiautomated multicamera system operating at 25 Hz. During a match, players covered 10,673 ± 348 m, of which 1778 ± 208 m and 2759 ± 241 m were performed at high intensity, as measured using speed (≥16 km/h, HI) and metabolic power (≥20 W/kg, MPHI) notations. High-intensity notations were nearly perfectly associated (r = .93, P < .0001). A huge method bias (980.63 ± 87.82 m, d = 11.67) was found when considering MPHI and HI. Very large correlations were found between match total distance covered and MPHI (r = .84, P < .0001) and HI (r = .74, P < .0001). Player high-intensity decelerations (≥-2 m/s 2 ) were very largely associated with MPHI (r = .73, P < .0001). The speed and MP methods are highly interchangeable at relative level (magnitude rank) but not absolute level (measure magnitude). The 2 physical match-analysis methods can be independently used to track match external load in elite-level players. However, match-analyst decisions must be based on use of a single method to avoid bias in external-load determination.

Rapid self-assembly of DNA on a microfluidic chip

PubMed Central

Zheng, Yao; Footz, Tim; Manage, Dammika P; Backhouse, Christopher James

2005-01-01

Background DNA self-assembly methods have played a major role in enabling methods for acquiring genetic information without having to resort to sequencing, a relatively slow and costly procedure. However, even self-assembly processes tend to be very slow when they rely upon diffusion on a large scale. Miniaturisation and integration therefore hold the promise of greatly increasing this speed of operation. Results We have developed a rapid method for implementing the self-assembly of DNA within a microfluidic system by electrically extracting the DNA from an environment containing an uncharged denaturant. By controlling the parameters of the electrophoretic extraction and subsequent analysis of the DNA we are able to control when the hybridisation occurs as well as the degree of hybridisation. By avoiding off-chip processing or long thermal treatments we are able to perform this hybridisation rapidly and can perform hybridisation, sizing, heteroduplex analysis and single-stranded conformation analysis within a matter of minutes. The rapidity of this analysis allows the sampling of transient effects that may improve the sensitivity of mutation detection. Conclusions We believe that this method will aid the integration of self-assembly methods upon microfluidic chips. The speed of this analysis also appears to provide information upon the dynamics of the self-assembly process. PMID:15717935

Design of A Cyclone Separator Using Approximation Method

NASA Astrophysics Data System (ADS)

Sin, Bong-Su; Choi, Ji-Won; Lee, Kwon-Hee

2017-12-01

A Separator is a device installed in industrial applications to separate mixed objects. The separator of interest in this research is a cyclone type, which is used to separate a steam-brine mixture in a geothermal plant. The most important performance of the cyclone separator is the collection efficiency. The collection efficiency in this study is predicted by performing the CFD (Computational Fluid Dynamics) analysis. This research defines six shape design variables to maximize the collection efficiency. Thus, the collection efficiency is set up as the objective function in optimization process. Since the CFD analysis requires a lot of calculation time, it is impossible to obtain the optimal solution by linking the gradient-based optimization algorithm. Thus, two approximation methods are introduced to obtain an optimum design. In this process, an L18 orthogonal array is adopted as a DOE method, and kriging interpolation method is adopted to generate the metamodel for the collection efficiency. Based on the 18 analysis results, the relative importance of each variable to the collection efficiency is obtained through the ANOVA (analysis of variance). The final design is suggested considering the results obtained from two optimization methods. The fluid flow analysis of the cyclone separator is conducted by using the commercial CFD software, ANSYS-CFX.

Issues in benchmarking human reliability analysis methods : a literature review.

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

Lois, Erasmia; Forester, John Alan; Tran, Tuan Q.

There is a diversity of human reliability analysis (HRA) methods available for use in assessing human performance within probabilistic risk assessment (PRA). Due to the significant differences in the methods, including the scope, approach, and underlying models, there is a need for an empirical comparison investigating the validity and reliability of the methods. To accomplish this empirical comparison, a benchmarking study is currently underway that compares HRA methods with each other and against operator performance in simulator studies. In order to account for as many effects as possible in the construction of this benchmarking study, a literature review was conducted,more » reviewing past benchmarking studies in the areas of psychology and risk assessment. A number of lessons learned through these studies are presented in order to aid in the design of future HRA benchmarking endeavors.« less

Issues in Benchmarking Human Reliability Analysis Methods: A Literature Review

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

Ronald L. Boring; Stacey M. L. Hendrickson; John A. Forester

There is a diversity of human reliability analysis (HRA) methods available for use in assessing human performance within probabilistic risk assessments (PRA). Due to the significant differences in the methods, including the scope, approach, and underlying models, there is a need for an empirical comparison investigating the validity and reliability of the methods. To accomplish this empirical comparison, a benchmarking study comparing and evaluating HRA methods in assessing operator performance in simulator experiments is currently underway. In order to account for as many effects as possible in the construction of this benchmarking study, a literature review was conducted, reviewing pastmore » benchmarking studies in the areas of psychology and risk assessment. A number of lessons learned through these studies are presented in order to aid in the design of future HRA benchmarking endeavors.« less

Motor current signature analysis for gearbox condition monitoring under transient speeds using wavelet analysis and dual-level time synchronous averaging

NASA Astrophysics Data System (ADS)

Bravo-Imaz, Inaki; Davari Ardakani, Hossein; Liu, Zongchang; García-Arribas, Alfredo; Arnaiz, Aitor; Lee, Jay

2017-09-01

This paper focuses on analyzing motor current signature for fault diagnosis of gearboxes operating under transient speed regimes. Two different strategies are evaluated, extensively tested and compared to analyze the motor current signature in order to implement a condition monitoring system for gearboxes in industrial machinery. A specially designed test bench is used, thoroughly monitored to fully characterize the experiments, in which gears in different health status are tested. The measured signals are analyzed using discrete wavelet decomposition, in different decomposition levels using a range of mother wavelets. Moreover, a dual-level time synchronous averaging analysis is performed on the same signal to compare the performance of the two methods. From both analyses, the relevant features of the signals are extracted and cataloged using a self-organizing map, which allows for an easy detection and classification of the diverse health states of the gears. The results demonstrate the effectiveness of both methods for diagnosing gearbox faults. A slightly better performance was observed for dual-level time synchronous averaging method. Based on the obtained results, the proposed methods can used as effective and reliable condition monitoring procedures for gearbox condition monitoring using only motor current signature.

Tubularized incised plate urethroplasty for hypospadias reoperation: a review and meta-analysis.

PubMed

Mousavi, Seyed A; Aarabi, Mohsen

2014-01-01

Tubularized Incised Plate (TIP) urethroplasty is a technique for urethral reconstruction of hypospadias although there are some controversies for its use in recurrent cases. The aim of this study was to review the results of TIP technique in various studies and the usage of different flaps for covering the repair site. Extensive Search was performed for articles published between 1994 and 2013 in common electronic databases. The overall TIP complication rates were estimated by a fixed effects model meta-analysis. 17 articles of hypospadia repair using the TIP method were reviewed. All studies performed surgery and repair on the basis of the Snodgrass's method; however, some introduced modifications to the method. The prevalence of complications in repeated TIP surgery was 11.1 to 33.3% and the most prevalent complication in different studies was fistula. Based on the meta-analysis, the overall estimation of complications was 21.8% (95% CI: 18.3 to 25.5). Most studies performed the incision of the urethral plate to create a supportive coverage upon neourethra, and confirmed its success. We recommend further investigation on using different flaps in well-designed randomized controlled trials to choose the best surgical method for repairing recurrent hypospadias.

Rank Determination of Mental Functions by 1D Wavelets and Partial Correlation.

PubMed

Karaca, Y; Aslan, Z; Cattani, C; Galletta, D; Zhang, Y

2017-01-01

The main aim of this paper is to classify mental functions by the Wechsler Adult Intelligence Scale-Revised tests with a mixed method based on wavelets and partial correlation. The Wechsler Adult Intelligence Scale-Revised is a widely used test designed and applied for the classification of the adults cognitive skills in a comprehensive manner. In this paper, many different intellectual profiles have been taken into consideration to measure the relationship between the mental functioning and psychological disorder. We propose a method based on wavelets and correlation analysis for classifying mental functioning, by the analysis of some selected parameters measured by the Wechsler Adult Intelligence Scale-Revised tests. In particular, 1-D Continuous Wavelet Analysis, 1-D Wavelet Coefficient Method and Partial Correlation Method have been analyzed on some Wechsler Adult Intelligence Scale-Revised parameters such as School Education, Gender, Age, Performance Information Verbal and Full Scale Intelligence Quotient. In particular, we will show that gender variable has a negative but a significant role on age and Performance Information Verbal factors. The age parameters also has a significant relation in its role on Performance Information Verbal and Full Scale Intelligence Quotient change.

High-frequency video capture and a computer program with frame-by-frame angle determination functionality as tools that support judging in artistic gymnastics.

PubMed

Omorczyk, Jarosław; Nosiadek, Leszek; Ambroży, Tadeusz; Nosiadek, Andrzej

2015-01-01

The main aim of this study was to verify the usefulness of selected simple methods of recording and fast biomechanical analysis performed by judges of artistic gymnastics in assessing a gymnast's movement technique. The study participants comprised six artistic gymnastics judges, who assessed back handsprings using two methods: a real-time observation method and a frame-by-frame video analysis method. They also determined flexion angles of knee and hip joints using the computer program. In the case of the real-time observation method, the judges gave a total of 5.8 error points with an arithmetic mean of 0.16 points for the flexion of the knee joints. In the high-speed video analysis method, the total amounted to 8.6 error points and the mean value amounted to 0.24 error points. For the excessive flexion of hip joints, the sum of the error values was 2.2 error points and the arithmetic mean was 0.06 error points during real-time observation. The sum obtained using frame-by-frame analysis method equaled 10.8 and the mean equaled 0.30 error points. Error values obtained through the frame-by-frame video analysis of movement technique were higher than those obtained through the real-time observation method. The judges were able to indicate the number of the frame in which the maximal joint flexion occurred with good accuracy. Using the real-time observation method as well as the high-speed video analysis performed without determining the exact angle for assessing movement technique were found to be insufficient tools for improving the quality of judging.

Practical Use of Computationally Frugal Model Analysis Methods

DOE PAGES

Hill, Mary C.; Kavetski, Dmitri; Clark, Martyn; ...

2015-03-21

Computationally frugal methods of model analysis can provide substantial benefits when developing models of groundwater and other environmental systems. Model analysis includes ways to evaluate model adequacy and to perform sensitivity and uncertainty analysis. Frugal methods typically require 10s of parallelizable model runs; their convenience allows for other uses of the computational effort. We suggest that model analysis be posed as a set of questions used to organize methods that range from frugal to expensive (requiring 10,000 model runs or more). This encourages focus on method utility, even when methods have starkly different theoretical backgrounds. We note that many frugalmore » methods are more useful when unrealistic process-model nonlinearities are reduced. Inexpensive diagnostics are identified for determining when frugal methods are advantageous. Examples from the literature are used to demonstrate local methods and the diagnostics. We suggest that the greater use of computationally frugal model analysis methods would allow questions such as those posed in this work to be addressed more routinely, allowing the environmental sciences community to obtain greater scientific insight from the many ongoing and future modeling efforts« less

Component-specific modeling

NASA Technical Reports Server (NTRS)

Mcknight, R. L.

1985-01-01

A series of interdisciplinary modeling and analysis techniques that were specialized to address three specific hot section components are presented. These techniques will incorporate data as well as theoretical methods from many diverse areas including cycle and performance analysis, heat transfer analysis, linear and nonlinear stress analysis, and mission analysis. Building on the proven techniques already available in these fields, the new methods developed will be integrated into computer codes to provide an accurate, and unified approach to analyzing combustor burner liners, hollow air cooled turbine blades, and air cooled turbine vanes. For these components, the methods developed will predict temperature, deformation, stress and strain histories throughout a complete flight mission.

Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods.

PubMed

Cao, Ying; Rajan, Suja S; Wei, Peng

2016-12-01

A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.

Quality assessment of crude and processed Arecae semen based on colorimeter and HPLC combined with chemometrics methods.

PubMed

Sun, Meng; Yan, Donghui; Yang, Xiaolu; Xue, Xingyang; Zhou, Sujuan; Liang, Shengwang; Wang, Shumei; Meng, Jiang

2017-05-01

Raw Arecae Semen, the seed of Areca catechu L., as well as Arecae Semen Tostum and Arecae semen carbonisata are traditionally processed by stir-baking for subsequent use in a variety of clinical applications. These three Arecae semen types, important Chinese herbal drugs, have been used in China and other Asian countries for thousands of years. In this study, the sensory technologies of a colorimeter and sensitive validated high-performance liquid chromatography with diode array detection were employed to discriminate raw Arecae semen and its processed drugs. The color parameters of the samples were determined by a colorimeter instrument CR-410. Moreover, the fingerprints of the four alkaloids of arecaidine, guvacine, arecoline and guvacoline were surveyed by high-performance liquid chromatography. Subsequently, Student's t test, the analysis of variance, fingerprint similarity analysis, hierarchical cluster analysis, principal component analysis, factor analysis and Pearson's correlation test were performed for final data analysis. The results obtained demonstrated a significant color change characteristic for components in raw Arecae semen and its processed drugs. Crude and processed Arecae semen could be determined based on colorimetry and high-performance liquid chromatography with a diode array detector coupled with chemometrics methods for a comprehensive quality evaluation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dehydrated Carbon Coupled with Laser-Induced Breakdown Spectrometry (LIBS) for the Determination of Heavy Metals in Solutions.

PubMed

Niu, Guanghui; Shi, Qi; Xu, Mingjun; Lai, Hongjun; Lin, Qingyu; Liu, Kunping; Duan, Yixiang

2015-10-01

In this article, a novel and alternative method of laser-induced breakdown spectroscopy (LIBS) analysis for liquid sample is proposed, which involves the removal of metal ions from a liquid to a solid substrate using a cost-efficient adsorbent, dehydrated carbon, obtained using a dehydration reaction. Using this new technique, researchers can detect trace metal ions in solutions qualitatively and quantitatively, and the drawbacks of performing liquid analysis using LIBS can be avoided because the analysis is performed on a solid surface. To achieve better performance using this technique, we considered parameters potentially influencing both adsorption performance and LIBS analysis. The calibration curves were evaluated, and the limits of detection obtained for Cu(2+), Pb(2+), and Cr(3+) were 0.77, 0.065, and 0.46 mg/L, respectively, which are better than those in the previous studies. In addition, compared to other absorbents, the adsorbent used in this technique is much cheaper in cost, easier to obtain, and has fewer or no other elements other than C, H, and O that could result in spectral interference during analysis. We also used the recommended method to analyze spiked samples, obtaining satisfactory results. Thus, this new technique is helpful and promising for use in wastewater analysis and management.

An improved method for the analysis of sennosides in Cassia angustifolia by high-performance liquid chromatography.

PubMed

Bala, S; Uniyal, G C; Dubey, T; Singh, S P

2001-01-01

A reversed-phase column liquid chromatographic method for the analysis of sennosides A and B present in leaf and pod extracts of Cassia angustifolia has been developed using a Symmetry C18 column and a linear binary gradient profile. The method can be utilised for the quantitative determination of other sennosides as a baseline resolution for most of the constituents was achieved. The method is economical in terms of the time taken and the amount of solvent used (25 mL) for each analysis. The validity of the method with respect to analysis was confirmed by comparing the UV spectra of each peak with those of reference compounds using a photodiode array detector.

Parametric Methods for Dynamic 11C-Phenytoin PET Studies.

PubMed

Mansor, Syahir; Yaqub, Maqsood; Boellaard, Ronald; Froklage, Femke E; de Vries, Anke; Bakker, Esther D M; Voskuyl, Rob A; Eriksson, Jonas; Schwarte, Lothar A; Verbeek, Joost; Windhorst, Albert D; Lammertsma, Adriaan A

2017-03-01

In this study, the performance of various methods for generating quantitative parametric images of dynamic 11 C-phenytoin PET studies was evaluated. Methods: Double-baseline 60-min dynamic 11 C-phenytoin PET studies, including online arterial sampling, were acquired for 6 healthy subjects. Parametric images were generated using Logan plot analysis, a basis function method, and spectral analysis. Parametric distribution volume (V T ) and influx rate ( K 1 ) were compared with those obtained from nonlinear regression analysis of time-activity curves. In addition, global and regional test-retest (TRT) variability was determined for parametric K 1 and V T values. Results: Biases in V T observed with all parametric methods were less than 5%. For K 1 , spectral analysis showed a negative bias of 16%. The mean TRT variabilities of V T and K 1 were less than 10% for all methods. Shortening the scan duration to 45 min provided similar V T and K 1 with comparable TRT performance compared with 60-min data. Conclusion: Among the various parametric methods tested, the basis function method provided parametric V T and K 1 values with the least bias compared with nonlinear regression data and showed TRT variabilities lower than 5%, also for smaller volume-of-interest sizes (i.e., higher noise levels) and shorter scan duration. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Structural design of composite rotor blades with consideration of manufacturability, durability, and manufacturing uncertainties

NASA Astrophysics Data System (ADS)

Li, Leihong

A modular structural design methodology for composite blades is developed. This design method can be used to design composite rotor blades with sophisticate geometric cross-sections. This design method hierarchically decomposed the highly-coupled interdisciplinary rotor analysis into global and local levels. In the global level, aeroelastic response analysis and rotor trim are conduced based on multi-body dynamic models. In the local level, variational asymptotic beam sectional analysis methods are used for the equivalent one-dimensional beam properties. Compared with traditional design methodology, the proposed method is more efficient and accurate. Then, the proposed method is used to study three different design problems that have not been investigated before. The first is to add manufacturing constraints into design optimization. The introduction of manufacturing constraints complicates the optimization process. However, the design with manufacturing constraints benefits the manufacturing process and reduces the risk of violating major performance constraints. Next, a new design procedure for structural design against fatigue failure is proposed. This procedure combines the fatigue analysis with the optimization process. The durability or fatigue analysis employs a strength-based model. The design is subject to stiffness, frequency, and durability constraints. Finally, the manufacturing uncertainty impacts on rotor blade aeroelastic behavior are investigated, and a probabilistic design method is proposed to control the impacts of uncertainty on blade structural performance. The uncertainty factors include dimensions, shapes, material properties, and service loads.

Comparative Analysis of Various Single-tone Frequency Estimation Techniques in High-order Instantaneous Moments Based Phase Estimation Method

NASA Astrophysics Data System (ADS)

Rajshekhar, G.; Gorthi, Sai Siva; Rastogi, Pramod

2010-04-01

For phase estimation in digital holographic interferometry, a high-order instantaneous moments (HIM) based method was recently developed which relies on piecewise polynomial approximation of phase and subsequent evaluation of the polynomial coefficients using the HIM operator. A crucial step in the method is mapping the polynomial coefficient estimation to single-tone frequency determination for which various techniques exist. The paper presents a comparative analysis of the performance of the HIM operator based method in using different single-tone frequency estimation techniques for phase estimation. The analysis is supplemented by simulation results.

Analysis of titanium content in titanium tetrachloride solution

NASA Astrophysics Data System (ADS)

Bi, Xiaoguo; Dong, Yingnan; Li, Shanshan; Guan, Duojiao; Wang, Jianyu; Tang, Meiling

2018-03-01

Strontium titanate, barium titan and lead titanate are new type of functional ceramic materials with good prospect, and titanium tetrachloride is a commonly in the production such products. Which excellent electrochemical performance of ferroelectric tempreature coefficient effect.In this article, three methods are used to calibrate the samples of titanium tetrachloride solution by back titration method, replacement titration method and gravimetric analysis method. The results show that the back titration method has many good points, for example, relatively simple operation, easy to judgment the titration end point, better accuracy and precision of analytical results, the relative standard deviation not less than 0.2%. So, it is the ideal of conventional analysis methods in the mass production.

Comparison of landmark-based and automatic methods for cortical surface registration

PubMed Central

Pantazis, Dimitrios; Joshi, Anand; Jiang, Jintao; Shattuck, David; Bernstein, Lynne E.; Damasio, Hanna; Leahy, Richard M.

2009-01-01

Group analysis of structure or function in cerebral cortex typically involves as a first step the alignment of the cortices. A surface based approach to this problem treats the cortex as a convoluted surface and coregisters across subjects so that cortical landmarks or features are aligned. This registration can be performed using curves representing sulcal fundi and gyral crowns to constrain the mapping. Alternatively, registration can be based on the alignment of curvature metrics computed over the entire cortical surface. The former approach typically involves some degree of user interaction in defining the sulcal and gyral landmarks while the latter methods can be completely automated. Here we introduce a cortical delineation protocol consisting of 26 consistent landmarks spanning the entire cortical surface. We then compare the performance of a landmark-based registration method that uses this protocol with that of two automatic methods implemented in the software packages FreeSurfer and BrainVoyager. We compare performance in terms of discrepancy maps between the different methods, the accuracy with which regions of interest are aligned, and the ability of the automated methods to correctly align standard cortical landmarks. Our results show similar performance for ROIs in the perisylvian region for the landmark based method and FreeSurfer. However, the discrepancy maps showed larger variability between methods in occipital and frontal cortex and also that automated methods often produce misalignment of standard cortical landmarks. Consequently, selection of the registration approach should consider the importance of accurate sulcal alignment for the specific task for which coregistration is being performed. When automatic methods are used, the users should ensure that sulci in regions of interest in their studies are adequately aligned before proceeding with subsequent analysis. PMID:19796696

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.

Ultra-high performance supercritical fluid chromatography of lignin-derived phenols from alkaline cupric oxide oxidation.

PubMed

Sun, Mingzhe; Lidén, Gunnar; Sandahl, Margareta; Turner, Charlotta

2016-08-01

Traditional chromatographic methods for the analysis of lignin-derived phenolic compounds in environmental samples are generally time consuming. In this work, an ultra-high performance supercritical fluid chromatography method with a diode array detector for the analysis of major lignin-derived phenolic compounds produced by alkaline cupric oxide oxidation was developed. In an analysis of a collection of 11 representative monomeric lignin phenolic compounds, all compounds were clearly separated within 6 min with excellent peak shapes, with a limit of detection of 0.5-2.5 μM, a limit of quantification of 2.5-5.0 μM, and a dynamic range of 5.0-2.0 mM (R(2) > 0.997). The new ultra-high performance supercritical fluid chromatography method was also applied for the qualitative and quantitative analysis of lignin-derived phenolic compounds obtained upon alkaline cupric oxide oxidation of a commercial humic acid. Ten out of the previous eleven model compounds could be quantified in the oxidized humic acid sample. The high separation power and short analysis time obtained demonstrate for the first time that supercritical fluid chromatography is a fast and reliable technique for the analysis of lignin-derived phenols in complex environmental samples. © 2016 The Authors, Journal of Separation Science Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Culture Representation in Human Reliability Analysis

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

David Gertman; Julie Marble; Steven Novack

Understanding human-system response is critical to being able to plan and predict mission success in the modern battlespace. Commonly, human reliability analysis has been used to predict failures of human performance in complex, critical systems. However, most human reliability methods fail to take culture into account. This paper takes an easily understood state of the art human reliability analysis method and extends that method to account for the influence of culture, including acceptance of new technology, upon performance. The cultural parameters used to modify the human reliability analysis were determined from two standard industry approaches to cultural assessment: Hofstede’s (1991)more » cultural factors and Davis’ (1989) technology acceptance model (TAM). The result is called the Culture Adjustment Method (CAM). An example is presented that (1) reviews human reliability assessment with and without cultural attributes for a Supervisory Control and Data Acquisition (SCADA) system attack, (2) demonstrates how country specific information can be used to increase the realism of HRA modeling, and (3) discusses the differences in human error probability estimates arising from cultural differences.« less

7 CFR 98.4 - Analytical methods.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 3 2014-01-01 2014-01-01 false Analytical methods. 98.4 Section 98.4 Agriculture... Analytical methods. (a) The majority of analytical methods used by the USDA laboratories to perform analyses of meat, meat food products and MREs are listed as follows: (1) Official Methods of Analysis of AOAC...

40 CFR 63.805 - Performance test methods.

Code of Federal Regulations, 2011 CFR

2011-07-01

... alternative method for determining the VHAP content of the coating. In the event of any inconsistency between... Collection of Coating and Ink Samples for VOC Content Analysis by Reference Method 24 and Reference Method... (see § 63.801); (iii) Use any alternative protocol and test method provided they meet either the...

Assessing FAÇADE Visibility in 3d City Models for City Marketing

NASA Astrophysics Data System (ADS)

Albrecht, F.; Moser, J.; Hijazi, I.

2013-08-01

In city marketing, different applications require the evaluation of the visual impression of displays in the urban environment on people that visit the city. Therefore, this research focuses on the way how visual displays on façades for movie performances are perceived during a cultural event triggered by city marketing. We describe the different visibility analysis methods that are applicable to the analysis of façades. The methods advanced from the domains of Geographic Information Science, architecture and computer graphics. A detailed scenario is described in order to perform a requirements analysis for identifying the requirements to visibility information. This visibility information needs to describe the visual perception of displays on façades adequately. The requirements are compared to the visibility information that can be provided by the visibility methods. A discussion of the comparison summarizes the advantages and disadvantages of existing visibility analysis methods for describing the visibility of façades. The results show that part of the researched approaches is able to support the requirements to visibility information. But they also show that for a complete support of the entire analysis workflow, there remain unsolved workflow integration issues.

Uncertainty Analysis of NASA Glenn's 8- by 6-Foot Supersonic Wind Tunnel

NASA Technical Reports Server (NTRS)

Stephens, Julia E.; Hubbard, Erin P.; Walter, Joel A.; McElroy, Tyler

2016-01-01

An analysis was performed to determine the measurement uncertainty of the Mach Number of the 8- by 6-foot Supersonic Wind Tunnel at the NASA Glenn Research Center. This paper details the analysis process used, including methods for handling limited data and complicated data correlations. Due to the complexity of the equations used, a Monte Carlo Method was utilized for this uncertainty analysis. A summary of the findings are presented as pertains to understanding what the uncertainties are, how they impact various research tests in the facility, and methods of reducing the uncertainties in the future.

Field evaluation of personal sampling methods for multiple bioaerosols.

PubMed

Wang, Chi-Hsun; Chen, Bean T; Han, Bor-Cheng; Liu, Andrew Chi-Yeu; Hung, Po-Chen; Chen, Chih-Yong; Chao, Hsing Jasmine

2015-01-01

Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC) filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters) and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min). Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

Indirect synthesis of multi-degree of freedom transient systems. [linear programming for a kinematically linear system

NASA Technical Reports Server (NTRS)

Pilkey, W. D.; Chen, Y. H.

1974-01-01

An indirect synthesis method is used in the efficient optimal design of multi-degree of freedom, multi-design element, nonlinear, transient systems. A limiting performance analysis which requires linear programming for a kinematically linear system is presented. The system is selected using system identification methods such that the designed system responds as closely as possible to the limiting performance. The efficiency is a result of the method avoiding the repetitive systems analyses accompanying other numerical optimization methods.

A comparison of methods to predict historical daily streamflow time series in the southeastern United States

USGS Publications Warehouse

Farmer, William H.; Archfield, Stacey A.; Over, Thomas M.; Hay, Lauren E.; LaFontaine, Jacob H.; Kiang, Julie E.

2015-01-01

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.

Determination of steroid sex hormones in wastewater by stir bar sorptive extraction based on poly(vinylpyridine-ethylene dimethacrylate) monolithic material and liquid chromatographic analysis.

PubMed

Huang, Xiaojia; Lin, Jianbin; Yuan, Dongxing; Hu, Rongzong

2009-04-17

In this study, a simple and rapid method was developed for the determination of seven steroid hormones in wastewater. Sample preparation and analysis were performed by stir bar sorptive extraction (SBSE) based on poly(vinylpyridine-ethylene dimethacrylate) monolithic material (SBSEM) combined with high-performance liquid chromatography with diode array detection. To achieve the optimum extraction performance, several main parameters, including extraction and desorption time, pH value and contents of inorganic salt in the sample matrix, were investigated. Under the optimized experimental conditions, the method showed good linearity and repeatability, as well as advantages such as sensitivity, simplicity, low cost and high feasibility. The extraction performance of SBSEM to the target compounds also compared with commercial SBSE which used polydimethylsiloxane as coating. Finally, the proposed method was successfully applied to the determination of the target compounds in wastewater samples. The recoveries of spiked target compounds in real samples ranged from 48.2% to 110%.

Design optimization of hydraulic turbine draft tube based on CFD and DOE method

NASA Astrophysics Data System (ADS)

Nam, Mun chol; Dechun, Ba; Xiangji, Yue; Mingri, Jin

2018-03-01

In order to improve performance of the hydraulic turbine draft tube in its design process, the optimization for draft tube is performed based on multi-disciplinary collaborative design optimization platform by combining the computation fluid dynamic (CFD) and the design of experiment (DOE) in this paper. The geometrical design variables are considered as the median section in the draft tube and the cross section in its exit diffuser and objective function is to maximize the pressure recovery factor (Cp). Sample matrixes required for the shape optimization of the draft tube are generated by optimal Latin hypercube (OLH) method of the DOE technique and their performances are evaluated through computational fluid dynamic (CFD) numerical simulation. Subsequently the main effect analysis and the sensitivity analysis of the geometrical parameters of the draft tube are accomplished. Then, the design optimization of the geometrical design variables is determined using the response surface method. The optimization result of the draft tube shows a marked performance improvement over the original.

Objective comparison of particle tracking methods

PubMed Central

Chenouard, Nicolas; Smal, Ihor; de Chaumont, Fabrice; Maška, Martin; Sbalzarini, Ivo F.; Gong, Yuanhao; Cardinale, Janick; Carthel, Craig; Coraluppi, Stefano; Winter, Mark; Cohen, Andrew R.; Godinez, William J.; Rohr, Karl; Kalaidzidis, Yannis; Liang, Liang; Duncan, James; Shen, Hongying; Xu, Yingke; Magnusson, Klas E. G.; Jaldén, Joakim; Blau, Helen M.; Paul-Gilloteaux, Perrine; Roudot, Philippe; Kervrann, Charles; Waharte, François; Tinevez, Jean-Yves; Shorte, Spencer L.; Willemse, Joost; Celler, Katherine; van Wezel, Gilles P.; Dan, Han-Wei; Tsai, Yuh-Show; de Solórzano, Carlos Ortiz; Olivo-Marin, Jean-Christophe; Meijering, Erik

2014-01-01

Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Since manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized, for the first time, an open competition, in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to important practical conclusions for users and developers. PMID:24441936

Simultaneous separation by reversed-phase high-performance liquid chromatography and mass spectral identification of anthocyanins and flavonols in Shiraz grape skin.

PubMed

Downey, Mark O; Rochfort, Simone

2008-08-01

A limitation of large-scale viticultural trials is the time and cost of comprehensive compositional analysis of the fruit by high-performance liquid chromatography (HPLC). In addition, separate methods have generally been required to identify and quantify different classes of metabolites. To address these shortcomings a reversed-phase HPLC method was developed to simultaneously separate the anthocyanins and flavonols present in grape skins. The method employs a methanol and water gradient acidified with 10% formic acid with a run-time of 48 min including re-equilibration. Identity of anthocyanins and flavonols in Shiraz (Vitis vinifera L.) skin was confirmed by mass spectral analysis.

Probabilistic finite elements for fracture and fatigue analysis

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Lawrence, M.; Besterfield, G. H.

1989-01-01

The fusion of the probabilistic finite element method (PFEM) and reliability analysis for probabilistic fracture mechanics (PFM) is presented. A comprehensive method for determining the probability of fatigue failure for curved crack growth was developed. The criterion for failure or performance function is stated as: the fatigue life of a component must exceed the service life of the component; otherwise failure will occur. An enriched element that has the near-crack-tip singular strain field embedded in the element is used to formulate the equilibrium equation and solve for the stress intensity factors at the crack-tip. Performance and accuracy of the method is demonstrated on a classical mode 1 fatigue problem.

An evaluation of HEMT potential for millimeter-wave signal sources using interpolation and harmonic balance techniques

NASA Technical Reports Server (NTRS)

Kwon, Youngwoo; Pavlidis, Dimitris; Tutt, Marcel N.

1991-01-01

A large-signal analysis method based on an harmonic balance technique and a 2-D cubic spline interpolation function has been developed and applied to the prediction of InP-based HEMT oscillator performance for frequencies extending up to the submillimeter-wave range. The large-signal analysis method uses a limited number of DC and small-signal S-parameter data and allows the accurate characterization of HEMT large-signal behavior. The method has been validated experimentally using load-pull measurement. Oscillation frequency, power performance, and load requirements are discussed, with an operation capability of 300 GHz predicted using state-of-the-art devices (fmax is approximately equal to 450 GHz).

Iris recognition based on robust principal component analysis

NASA Astrophysics Data System (ADS)

Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong

2014-11-01

Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

Performance of two alternative methods for Listeria detection throughout Serro Minas cheese ripening.

PubMed

Mata, Gardênia Márcia Silva Campos; Martins, Evandro; Machado, Solimar Gonçalves; Pinto, Maximiliano Soares; de Carvalho, Antônio Fernandes; Vanetti, Maria Cristina Dantas

2016-01-01

The ability of pathogens to survive cheese ripening is a food-security concern. Therefore, this study aimed to evaluate the performance of two alternative methods of analysis of Listeria during the ripening of artisanal Minas cheese. These methods were tested and compared with the conventional method: Lateral Flow System™, in cheeses produced on laboratory scale using raw milk collected from different farms and inoculated with Listeria innocua; and VIDAS(®)-LMO, in cheese samples collected from different manufacturers in Serro, Minas Gerais, Brazil. These samples were also characterized in terms of lactic acid bacteria, coliforms and physical-chemical analysis. In the inoculated samples, L. innocua was detected by Lateral Flow System™ method with 33% false-negative and 68% accuracy results. L. innocua was only detected in the inoculated samples by the conventional method at 60-days of cheese ripening. L. monocytogenes was not detected by the conventional and the VIDAS(®)-LMO methods in cheese samples collected from different manufacturers, which impairs evaluating the performance of this alternative method. We concluded that the conventional method provided a better recovery of L. innocua throughout cheese ripening, being able to detect L. innocua at 60-day, aging period which is required by the current legislation. Copyright © 2016 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.

Automatic adventitious respiratory sound analysis: A systematic review.

PubMed

Pramono, Renard Xaviero Adhi; Bowyer, Stuart; Rodriguez-Villegas, Esther

2017-01-01

Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established. To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works. A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification. Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated. Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved. A total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis. Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions. A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventional non-automatic identification. This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases.

Automatic adventitious respiratory sound analysis: A systematic review

PubMed Central

Bowyer, Stuart; Rodriguez-Villegas, Esther

2017-01-01

Background Automatic detection or classification of adventitious sounds is useful to assist physicians in diagnosing or monitoring diseases such as asthma, Chronic Obstructive Pulmonary Disease (COPD), and pneumonia. While computerised respiratory sound analysis, specifically for the detection or classification of adventitious sounds, has recently been the focus of an increasing number of studies, a standardised approach and comparison has not been well established. Objective To provide a review of existing algorithms for the detection or classification of adventitious respiratory sounds. This systematic review provides a complete summary of methods used in the literature to give a baseline for future works. Data sources A systematic review of English articles published between 1938 and 2016, searched using the Scopus (1938-2016) and IEEExplore (1984-2016) databases. Additional articles were further obtained by references listed in the articles found. Search terms included adventitious sound detection, adventitious sound classification, abnormal respiratory sound detection, abnormal respiratory sound classification, wheeze detection, wheeze classification, crackle detection, crackle classification, rhonchi detection, rhonchi classification, stridor detection, stridor classification, pleural rub detection, pleural rub classification, squawk detection, and squawk classification. Study selection Only articles were included that focused on adventitious sound detection or classification, based on respiratory sounds, with performance reported and sufficient information provided to be approximately repeated. Data extraction Investigators extracted data about the adventitious sound type analysed, approach and level of analysis, instrumentation or data source, location of sensor, amount of data obtained, data management, features, methods, and performance achieved. Data synthesis A total of 77 reports from the literature were included in this review. 55 (71.43%) of the studies focused on wheeze, 40 (51.95%) on crackle, 9 (11.69%) on stridor, 9 (11.69%) on rhonchi, and 18 (23.38%) on other sounds such as pleural rub, squawk, as well as the pathology. Instrumentation used to collect data included microphones, stethoscopes, and accelerometers. Several references obtained data from online repositories or book audio CD companions. Detection or classification methods used varied from empirically determined thresholds to more complex machine learning techniques. Performance reported in the surveyed works were converted to accuracy measures for data synthesis. Limitations Direct comparison of the performance of surveyed works cannot be performed as the input data used by each was different. A standard validation method has not been established, resulting in different works using different methods and performance measure definitions. Conclusion A review of the literature was performed to summarise different analysis approaches, features, and methods used for the analysis. The performance of recent studies showed a high agreement with conventional non-automatic identification. This suggests that automated adventitious sound detection or classification is a promising solution to overcome the limitations of conventional auscultation and to assist in the monitoring of relevant diseases. PMID:28552969

Rapid scanning system for fuel drawers

DOEpatents

Caldwell, J.T.; Fehlau, P.E.; France, S.W.

A nondestructive method for uniquely distinguishing among and quantifying the mass of individual fuel plates in situ in fuel drawers utilized in nuclear reactors is described. The method is both rapid and passive, eliminating the personnel hazard of the commonly used irradiation techniques which require that the analysis be performed in proximity to an intense neutron source such as a reactor. In the present technique, only normally decaying nuclei are observed. This allows the analysis to be performed anywhere. This feature, combined with rapid scanning of a given fuel drawer (in approximately 30 s), and the computer data analysis allows the processing of large numbers of fuel drawers efficiently in the event of a loss alert.

Rapid scanning system for fuel drawers

DOEpatents

Caldwell, John T.; Fehlau, Paul E.; France, Stephen W.

1981-01-01

A nondestructive method for uniqely distinguishing among and quantifying the mass of individual fuel plates in situ in fuel drawers utilized in nuclear reactors is described. The method is both rapid and passive, eliminating the personnel hazard of the commonly used irradiation techniques which require that the analysis be performed in proximity to an intense neutron source such as a reactor. In the present technique, only normally decaying nuclei are observed. This allows the analysis to be performed anywhere. This feature, combined with rapid scanning of a given fuel drawer (in approximately 30 s), and the computer data analysis allows the processing of large numbers of fuel drawers efficiently in the event of a loss alert.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies.

PubMed

Azadeh, Ali; Sheikhalishahi, Mohammad

2015-06-01

A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

Analysis of Developmental Data: Comparison Among Alternative Methods

ERIC Educational Resources Information Center

Wilson, Ronald S.

1975-01-01

To examine the ability of the correction factor epsilon to counteract statistical bias in univariate analysis, an analysis of variance (adjusted by epsilon) and a multivariate analysis of variance were performed on the same data. The results indicated that univariate analysis is a fully protected design when used with epsilon. (JMB)

A fuzzy-based data transformation for feature extraction to increase classification performance with small medical data sets.

PubMed

Li, Der-Chiang; Liu, Chiao-Wen; Hu, Susan C

2011-05-01

Medical data sets are usually small and have very high dimensionality. Too many attributes will make the analysis less efficient and will not necessarily increase accuracy, while too few data will decrease the modeling stability. Consequently, the main objective of this study is to extract the optimal subset of features to increase analytical performance when the data set is small. This paper proposes a fuzzy-based non-linear transformation method to extend classification related information from the original data attribute values for a small data set. Based on the new transformed data set, this study applies principal component analysis (PCA) to extract the optimal subset of features. Finally, we use the transformed data with these optimal features as the input data for a learning tool, a support vector machine (SVM). Six medical data sets: Pima Indians' diabetes, Wisconsin diagnostic breast cancer, Parkinson disease, echocardiogram, BUPA liver disorders dataset, and bladder cancer cases in Taiwan, are employed to illustrate the approach presented in this paper. This research uses the t-test to evaluate the classification accuracy for a single data set; and uses the Friedman test to show the proposed method is better than other methods over the multiple data sets. The experiment results indicate that the proposed method has better classification performance than either PCA or kernel principal component analysis (KPCA) when the data set is small, and suggest creating new purpose-related information to improve the analysis performance. This paper has shown that feature extraction is important as a function of feature selection for efficient data analysis. When the data set is small, using the fuzzy-based transformation method presented in this work to increase the information available produces better results than the PCA and KPCA approaches. Copyright © 2011 Elsevier B.V. All rights reserved.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Analysis of the High-Performance Liquid Chromatography Fingerprints and Quantitative Analysis of Multicomponents by Single Marker of Products of Fermented Cordyceps sinensis

PubMed Central

Guan, Yong-mei; Jin, Chen; Zhu, Wei-feng; Yang, Ming

2018-01-01

Fermented Cordyceps sinensis, the succedaneum of Cordyceps sinensis which is extracted and separated from Cordyceps sinensis by artificial fermentation, is commonly used in eastern Asia in clinical treatments due to its health benefit. In this paper, a new strategy for differentiating and comprehensively evaluating the quality of products of fermented Cordyceps sinensis has been established, based on high-performance liquid chromatography (HPLC) fingerprint analysis combined with similar analysis (SA), hierarchical cluster analysis (HCA), and the quantitative analysis of multicomponents by single marker (QAMS). Ten common peaks were collected and analysed using SA, HCA, and QAMS. These methods indicated that 30 fermented Cordyceps sinensis samples could be categorized into two groups by HCA. Five peaks were identified as uracil, uridine, adenine, guanosine, and adenosine, and according to the results from the diode array detector, which can be used to confirm peak purity, the purities of these compounds were greater than 990. Adenosine was chosen as the internal reference substance. The relative correction factors (RCF) between adenosine and the other four nucleosides were calculated and investigated using the QAMS method. Meanwhile, the accuracy of the QAMS method was confirmed by comparing the results of that method with those of an external standard method with cosines of the angles between the groups. No significant difference between the two methods was observed. In conclusion, the method established herein was efficient, successful in identifying the products of fermented Cordyceps sinensis, and scientifically valid to be applicable in the systematic quality control of fermented Cordyceps sinensis products. PMID:29850373

Analysis of the High-Performance Liquid Chromatography Fingerprints and Quantitative Analysis of Multicomponents by Single Marker of Products of Fermented Cordyceps sinensis.

PubMed

Chen, Li-Hua; Wu, Yao; Guan, Yong-Mei; Jin, Chen; Zhu, Wei-Feng; Yang, Ming

2018-01-01

Fermented Cordyceps sinensis , the succedaneum of Cordyceps sinensis which is extracted and separated from Cordyceps sinensis by artificial fermentation, is commonly used in eastern Asia in clinical treatments due to its health benefit. In this paper, a new strategy for differentiating and comprehensively evaluating the quality of products of fermented Cordyceps sinensis has been established, based on high-performance liquid chromatography (HPLC) fingerprint analysis combined with similar analysis (SA), hierarchical cluster analysis (HCA), and the quantitative analysis of multicomponents by single marker (QAMS). Ten common peaks were collected and analysed using SA, HCA, and QAMS. These methods indicated that 30 fermented Cordyceps sinensis samples could be categorized into two groups by HCA. Five peaks were identified as uracil, uridine, adenine, guanosine, and adenosine, and according to the results from the diode array detector, which can be used to confirm peak purity, the purities of these compounds were greater than 990. Adenosine was chosen as the internal reference substance. The relative correction factors (RCF) between adenosine and the other four nucleosides were calculated and investigated using the QAMS method. Meanwhile, the accuracy of the QAMS method was confirmed by comparing the results of that method with those of an external standard method with cosines of the angles between the groups. No significant difference between the two methods was observed. In conclusion, the method established herein was efficient, successful in identifying the products of fermented Cordyceps sinensis , and scientifically valid to be applicable in the systematic quality control of fermented Cordyceps sinensis products.

Laboratory Analytical Procedures | Bioenergy | NREL

Science.gov Websites

analytical procedures (LAPs) to provide validated methods for biofuels and pyrolysis bio-oils research . Biomass Compositional Analysis These lab procedures provide tested and accepted methods for performing

Position Accuracy Analysis of a Robust Vision-Based Navigation

NASA Astrophysics Data System (ADS)

Gaglione, S.; Del Pizzo, S.; Troisi, S.; Angrisano, A.

2018-05-01

Using images to determine camera position and attitude is a consolidated method, very widespread for application like UAV navigation. In harsh environment, where GNSS could be degraded or denied, image-based positioning could represent a possible candidate for an integrated or alternative system. In this paper, such method is investigated using a system based on single camera and 3D maps. A robust estimation method is proposed in order to limit the effect of blunders or noisy measurements on position solution. The proposed approach is tested using images collected in an urban canyon, where GNSS positioning is very unaccurate. A previous photogrammetry survey has been performed to build the 3D model of tested area. The position accuracy analysis is performed and the effect of the robust method proposed is validated.

Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: A comparative study between different modeling methods

NASA Astrophysics Data System (ADS)

Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

2013-03-01

By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm-1. Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity.

Chromatographic and Spectrophotometric Analysis of Phenolic Compounds from Fruits of Libidibia ferrea Martius

PubMed Central

Ferreira, Magda R. A.; Fernandes, Mônica T. M.; da Silva, Wliana A. V.; Bezerra, Isabelle C. F.; de Souza, Tatiane P.; Pimentel, Maria F.; Soares, Luiz A. L.

2016-01-01

Background: Libidibia ferrea (Mart. ex Tul.) L.P. Queiroz (Fabaceae) is a tree which is native to Brazil, widely known as “Jucá,” where its herbal derivatives are used in folk medicine with several therapeutic properties. The constituents, which have already been described in the fruit, are mainly hydrolysable tannins (gallic acid [GA] and ellagic acid [EA]). Objective: The aim of this study was to investigate the phenolic variability in the fruit of L. ferrea by ultraviolet/visible (UV/VIS) and chromatographic methods (high-performance liquid chromatography [HPLC]/high-performance thin layer chromatography [HPTLC]). Materials and Methods: Several samples were collected from different regions of Brazil and the qualitative (fingerprints by HPTLC and HPLC) and quantitative analysis (UV/VIS and HPLC) of polyphenols were performed. Results: The HPTLC and HPLC profiles allowed separation and identification of both major analytical markers: EA and GA. The chemical profiles were similar in a number of spots or peaks for the samples, but some differences could be observed in the intensity or area of the analytical markers for HPTLC or HPLC, respectively. Regarding the quantitative analysis, the polyphenolic content by UV/VIS ranged from 13.99 to 37.86 g% expressed as GA or from 10.75 to 29.09 g% expressed as EA. The contents of EA and GA by liquid chromatography-reversed phase (LC-RP) method ranged from 0.57 to 2.68 g% and from 0.54 to 3.23 g%, respectively. Conclusion: The chemical profiles obtained by HPTLC or HPLC, as well as the quantitative analysis by spectrophotometry or LC-RP method, were suitable for discrimination of each herbal sample and can be used as tools for the comparative analysis of the fruits from L. ferrea. SUMMARY The polyphenols of fruits of Libidibia ferrea can be quantified by UV/VIS and HPLCThe HPLC method was able to detect the gallic and ellagic acids in several samples of fruits of Libidibia ferreaThe phenolic profiles of fruits from Libidibia ferrea by HPTLC and HPLC were reproductible. Abbreviations used: HPTLC: high performance thin layer chromatography, HPLC: high performance liquid chromatography, UV-Vis: spectrophotometry PMID:27279721

Quantitative analysis of the major constituents of St John's wort with HPLC-ESI-MS.

PubMed

Chandrasekera, Dhammitha H; Welham, Kevin J; Ashton, David; Middleton, Richard; Heinrich, Michael

2005-12-01

A method was developed to profile the major constituents of St John's wort extracts using high-performance liquid chromatography-electrospray mass spectrometry (HPLC-ESI-MS). The objective was to simultaneously separate, identify and quantify hyperforin, hypericin, pseudohypericin, rutin, hyperoside, isoquercetrin, quercitrin and chlorogenic acid using HPLC-MS. Quantification was performed using an external standardisation method with reference standards. The method consisted of two protocols: one for the analysis of flavonoids and glycosides and the other for the analysis of the more lipophilic hypericins and hyperforin. Both protocols used a reverse phase Luna phenyl hexyl column. The separation of the flavonoids and glycosides was achieved within 35 min and that of the hypericins and hyperforin within 9 min. The linear response range in ESI-MS was established for each compound and all had linear regression coefficient values greater than 0.97. Both protocols proved to be very specific for the constituents analysed. MS analysis showed no other signals within the analyte peaks. The method was robust and applicable to alcoholic tinctures, tablet/capsule extracts in various solvents and herb extracts. The method was applied to evaluate the phytopharmaceutical quality of St John's wort preparations available in the UK in order to test the method and investigate if they contain at least the main constituents and at what concentrations.

Analysis of Phosphonic Acids: Validation of Semi-Volatile Analysis by HPLC-MS/MS by EPA Method MS999

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

Owens, J; Vu, A; Koester, C

The Environmental Protection Agency's (EPA) Region 5 Chicago Regional Laboratory (CRL) developed a method titled Analysis of Diisopropyl Methylphosphonate, Ethyl Hydrogen Dimethylamidophosphate, Isopropyl Methylphosphonic Acid, Methylphosphonic Acid, and Pinacolyl Methylphosphonic Acid in Water by Multiple Reaction Monitoring Liquid Chromatography/Tandem Mass Spectrometry: EPA Version MS999. This draft standard operating procedure (SOP) was distributed to multiple EPA laboratories and to Lawrence Livermore National Laboratory, which was tasked to serve as a reference laboratory for EPA's Environmental Reference Laboratory Network (ERLN) and to develop and validate analytical procedures. The primary objective of this study was to validate and verify the analytical procedures describedmore » in EPA Method MS999 for analysis of the listed phosphonic acids and surrogates in aqueous samples. The gathered data from this validation study will be used to: (1) demonstrate analytical method performance; (2) generate quality control acceptance criteria; and (3) revise the SOP to provide a validated method that would be available for use during a homeland security event. The data contained in this report will be compiled, by EPA CRL, with data generated by other EPA Regional laboratories so that performance metrics of EPA Method MS999 can be determined.« less

Anthropometry-corrected exposure modeling as a method to improve trunk posture assessment with a single inclinometer.

PubMed

Van Driel, Robin; Trask, Catherine; Johnson, Peter W; Callaghan, Jack P; Koehoorn, Mieke; Teschke, Kay

2013-01-01

Measuring trunk posture in the workplace commonly involves subjective observation or self-report methods or the use of costly and time-consuming motion analysis systems (current gold standard). This work compared trunk inclination measurements using a simple data-logging inclinometer with trunk flexion measurements using a motion analysis system, and evaluated adding measures of subject anthropometry to exposure prediction models to improve the agreement between the two methods. Simulated lifting tasks (n=36) were performed by eight participants, and trunk postures were simultaneously measured with each method. There were significant differences between the two methods, with the inclinometer initially explaining 47% of the variance in the motion analysis measurements. However, adding one key anthropometric parameter (lower arm length) to the inclinometer-based trunk flexion prediction model reduced the differences between the two systems and accounted for 79% of the motion analysis method's variance. Although caution must be applied when generalizing lower-arm length as a correction factor, the overall strategy of anthropometric modeling is a novel contribution. In this lifting-based study, by accounting for subject anthropometry, a single, simple data-logging inclinometer shows promise for trunk posture measurement and may have utility in larger-scale field studies where similar types of tasks are performed.

Theoretical and experimental comparative analysis of beamforming methods for loudspeaker arrays under given performance constraints

NASA Astrophysics Data System (ADS)

Olivieri, Ferdinando; Fazi, Filippo Maria; Nelson, Philip A.; Shin, Mincheol; Fontana, Simone; Yue, Lang

2016-07-01

Methods for beamforming are available that provide the signals used to drive an array of sources for the implementation of systems for the so-called personal audio. In this work, performance of the delay-and-sum (DAS) method and of three widely used methods for optimal beamforming are compared by means of computer simulations and experiments in an anechoic environment using a linear array of sources with given constraints on quality of the reproduced field at the listener's position and limit to input energy to the array. Using the DAS method as a benchmark for performance, the frequency domain responses of the loudspeaker filters can be characterized in three regions. In the first region, at low frequencies, input signals designed with the optimal methods are identical and provide higher directivity performance than that of the DAS. In the second region, performance of the optimal methods are similar to the DAS method. The third region starts above the limit due to spatial aliasing. A method is presented to estimate the boundaries of these regions.

Rapid analysis of charge variants of monoclonal antibodies using non-linear salt gradient in cation-exchange high performance liquid chromatography.

PubMed

Joshi, Varsha; Kumar, Vijesh; Rathore, Anurag S

2015-08-07

A method is proposed for rapid development of a short, analytical cation exchange high performance liquid chromatography method for analysis of charge heterogeneity in monoclonal antibody products. The parameters investigated and optimized include pH, shape of elution gradient and length of the column. It is found that the most important parameter for development of a shorter method is the choice of the shape of elution gradient. In this paper, we propose a step by step approach to develop a non-linear sigmoidal shape gradient for analysis of charge heterogeneity for two different monoclonal antibody products. The use of this gradient not only decreases the run time of the method to 4min against the conventional method that takes more than 40min but also the resolution is retained. Superiority of the phosphate gradient over sodium chloride gradient for elution of mAbs is also observed. The method has been successfully evaluated for specificity, sensitivity, linearity, limit of detection, and limit of quantification. Application of this method as a potential at-line process analytical technology tool has been suggested. Copyright © 2015 Elsevier B.V. All rights reserved.

Some selected quantitative methods of thermal image analysis in Matlab.

PubMed

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Probabilistic boundary element method

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Raveendra, S. T.

1989-01-01

The purpose of the Probabilistic Structural Analysis Method (PSAM) project is to develop structural analysis capabilities for the design analysis of advanced space propulsion system hardware. The boundary element method (BEM) is used as the basis of the Probabilistic Advanced Analysis Methods (PADAM) which is discussed. The probabilistic BEM code (PBEM) is used to obtain the structural response and sensitivity results to a set of random variables. As such, PBEM performs analogous to other structural analysis codes such as finite elements in the PSAM system. For linear problems, unlike the finite element method (FEM), the BEM governing equations are written at the boundary of the body only, thus, the method eliminates the need to model the volume of the body. However, for general body force problems, a direct condensation of the governing equations to the boundary of the body is not possible and therefore volume modeling is generally required.

High temperature flow-through device for rapid solubilization and analysis

DOEpatents

West, Jason A. A. [Castro Valley, CA; Hukari, Kyle W [San Ramon, CA; Patel, Kamlesh D [Dublin, CA; Peterson, Kenneth A [Albuquerque, NM; Renzi, Ronald F [Tracy, CA

2009-09-22

Devices and methods for thermally lysing of biological material, for example vegetative bacterial cells and bacterial spores, are provided. Hot solution methods for solubilizing bacterial spores are described. Systems for direct analysis are disclosed including thermal lysers coupled to sample preparation stations. Integrated systems capable of performing sample lysis, labeling and protein fingerprint analysis of biological material, for example, vegetative bacterial cells, bacterial spores and viruses are provided.

High temperature flow-through device for rapid solubilization and analysis

DOEpatents

West, Jason A. A.; Hukari, Kyle W.; Patel, Kamlesh D.; Peterson, Kenneth A.; Renzi, Ronald F.

2013-04-23

Devices and methods for thermally lysing of biological material, for example vegetative bacterial cells and bacterial spores, are provided. Hot solution methods for solubilizing bacterial spores are described. Systems for direct analysis are disclosed including thermal lysers coupled to sample preparation stations. Integrated systems capable of performing sample lysis, labeling and protein fingerprint analysis of biological material, for example, vegetative bacterial cells, bacterial spores and viruses are provided.

Performance Analysis and Experimental Validation of the Direct Strain Imaging Method

Treesearch

Athanasios Iliopoulos; John G. Michopoulos; John C. Hermanson

2013-01-01

Direct Strain Imaging accomplishes full field measurement of the strain tensor on the surface of a deforming body, by utilizing arbitrarily oriented engineering strain measurements originating from digital imaging. In this paper an evaluation of the method’s performance with respect to its operating parameter space is presented along with a preliminary...

Influence of Installation Effects on Pile Bearing Capacity in Cohesive Soils - Large Deformation Analysis Via Finite Element Method

NASA Astrophysics Data System (ADS)

Konkol, Jakub; Bałachowski, Lech

2017-03-01

In this paper, the whole process of pile construction and performance during loading is modelled via large deformation finite element methods such as Coupled Eulerian Lagrangian (CEL) and Updated Lagrangian (UL). Numerical study consists of installation process, consolidation phase and following pile static load test (SLT). The Poznań site is chosen as the reference location for the numerical analysis, where series of pile SLTs have been performed in highly overconsolidated clay (OCR ≈ 12). The results of numerical analysis are compared with corresponding field tests and with so-called "wish-in-place" numerical model of pile, where no installation effects are taken into account. The advantages of using large deformation numerical analysis are presented and its application to the pile designing is shown.

Integrated Aero-Propulsion CFD Methodology for the Hyper-X Flight Experiment

NASA Technical Reports Server (NTRS)

Cockrell, Charles E., Jr.; Engelund, Walter C.; Bittner, Robert D.; Dilley, Arthur D.; Jentink, Tom N.; Frendi, Abdelkader

2000-01-01

Computational fluid dynamics (CFD) tools have been used extensively in the analysis and development of the X-43A Hyper-X Research Vehicle (HXRV). A significant element of this analysis is the prediction of integrated vehicle aero-propulsive performance, which includes an integration of aerodynamic and propulsion flow fields. This paper describes analysis tools used and the methodology for obtaining pre-flight predictions of longitudinal performance increments. The use of higher-fidelity methods to examine flow-field characteristics and scramjet flowpath component performance is also discussed. Limited comparisons with available ground test data are shown to illustrate the approach used to calibrate methods and assess solution accuracy. Inviscid calculations to evaluate lateral-directional stability characteristics are discussed. The methodology behind 3D tip-to-tail calculations is described and the impact of 3D exhaust plume expansion in the afterbody region is illustrated. Finally, future technology development needs in the area of hypersonic propulsion-airframe integration analysis are discussed.

Comparison of core-shell and totally porous ultra high performance liquid chromatographic stationary phases based on their selectivity towards alfuzosin compounds.

PubMed

Szulfer, Jarosław; Plenis, Alina; Bączek, Tomasz

2014-06-13

This paper focuses on the application of a column classification system based on the Katholieke Universiteit Leuven for the characterization of physicochemical properties of core-shell and ultra-high performance liquid chromatographic stationary phases, followed by the verification of the reliability of the obtained column classification in pharmaceutical practice. In the study, 7 stationary phases produced in core-shell technology and 18 ultra-high performance liquid chromatographic columns were chromatographically tested, and ranking lists were built on the FKUL-values calculated against two selected reference columns. In the column performance test, an analysis of alfuzosin in the presence of related substances was carried out using the brands of the stationary phases with the highest ranking positions. Next, a system suitability test as described by the European Pharmacopoeia monograph was performed. Moreover, a study was also performed to achieve a purposeful shortening of the analysis time of the compounds of interest using the selected stationary phases. Finally, it was checked whether methods using core-shell and ultra-high performance liquid chromatographic columns can be an interesting alternative to the high-performance liquid chromatographic method for the analysis of alfuzosin in pharmaceutical practice. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of statistical and standard algorithms for detecting muscle onset with surface electromyography.

PubMed

Tenan, Matthew S; Tweedell, Andrew J; Haynes, Courtney A

2017-01-01

The timing of muscle activity is a commonly applied analytic method to understand how the nervous system controls movement. This study systematically evaluates six classes of standard and statistical algorithms to determine muscle onset in both experimental surface electromyography (EMG) and simulated EMG with a known onset time. Eighteen participants had EMG collected from the biceps brachii and vastus lateralis while performing a biceps curl or knee extension, respectively. Three established methods and three statistical methods for EMG onset were evaluated. Linear envelope, Teager-Kaiser energy operator + linear envelope and sample entropy were the established methods evaluated while general time series mean/variance, sequential and batch processing of parametric and nonparametric tools, and Bayesian changepoint analysis were the statistical techniques used. Visual EMG onset (experimental data) and objective EMG onset (simulated data) were compared with algorithmic EMG onset via root mean square error and linear regression models for stepwise elimination of inferior algorithms. The top algorithms for both data types were analyzed for their mean agreement with the gold standard onset and evaluation of 95% confidence intervals. The top algorithms were all Bayesian changepoint analysis iterations where the parameter of the prior (p0) was zero. The best performing Bayesian algorithms were p0 = 0 and a posterior probability for onset determination at 60-90%. While existing algorithms performed reasonably, the Bayesian changepoint analysis methodology provides greater reliability and accuracy when determining the singular onset of EMG activity in a time series. Further research is needed to determine if this class of algorithms perform equally well when the time series has multiple bursts of muscle activity.

On Bi-Grid Local Mode Analysis of Solution Techniques for 3-D Euler and Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Ibraheem, S. O.; Demuren, A. O.

1994-01-01

A procedure is presented for utilizing a bi-grid stability analysis as a practical tool for predicting multigrid performance in a range of numerical methods for solving Euler and Navier-Stokes equations. Model problems based on the convection, diffusion and Burger's equation are used to illustrate the superiority of the bi-grid analysis as a predictive tool for multigrid performance in comparison to the smoothing factor derived from conventional von Neumann analysis. For the Euler equations, bi-grid analysis is presented for three upwind difference based factorizations, namely Spatial, Eigenvalue and Combination splits, and two central difference based factorizations, namely LU and ADI methods. In the former, both the Steger-Warming and van Leer flux-vector splitting methods are considered. For the Navier-Stokes equations, only the Beam-Warming (ADI) central difference scheme is considered. In each case, estimates of multigrid convergence rates from the bi-grid analysis are compared to smoothing factors obtained from single-grid stability analysis. Effects of grid aspect ratio and flow skewness are examined. Both predictions are compared with practical multigrid convergence rates for 2-D Euler and Navier-Stokes solutions based on the Beam-Warming central scheme.

The Analysis Performance Method Naive Bayes Andssvm Determine Pattern Groups of Disease

NASA Astrophysics Data System (ADS)

Sitanggang, Rianto; Tulus; Situmorang, Zakarias

2017-12-01

Information is a very important element and into the daily needs of the moment, to get a precise and accurate information is not easy, this research can help decision makers and make a comparison. Researchers perform data mining techniques to analyze the performance of methods and algorithms naïve Bayes methods Smooth Support Vector Machine (ssvm) in the grouping of the disease.The pattern of disease that is often suffered by people in the group can be in the detection area of the collection of information contained in the medical record. Medical records have infromasi disease by patients in coded according to standard WHO. Processing of medical record data to find patterns of this group of diseases that often occur in this community take the attribute address, sex, type of disease, and age. Determining the next analysis is grouping of four ersebut attribute. From the results of research conducted on the dataset fever diabete mellitus, naïve Bayes method produces an average value of 99% and an accuracy and SSVM method produces an average value of 93% accuracy

Analysis Method for Non-Nominal First Acquisition

NASA Technical Reports Server (NTRS)

Sieg, Detlef; Mugellesi-Dow, Roberta

2007-01-01

First this paper describes a method how the trajectory of the launcher can be modelled for the contingency analysis without having much information about the launch vehicle itself. From a dense sequence of state vectors a velocity profile is derived which is sufficiently accurate to enable the Flight Dynamics Team to integrate parts of the launcher trajectory on its own and to simulate contingency cases by modifying the velocity profile. Then the paper focuses on the thorough visibility analysis which has to follow the contingency case or burn performance simulations. In the ideal case it is possible to identify a ground station which is able to acquire the satellite independent from the burn performance. The correlations between the burn performance and the pointing at subsequent ground stations are derived with the aim of establishing simple guidelines which can be applied quickly and which significantly improve the chance of acquisition at subsequent ground stations. In the paper the method is applied to the Soyuz/Fregat launch with the MetOp satellite. Overall the paper shows that the launcher trajectory modelling with the simulation of contingency cases in connection with a ground station visibility analysis leads to a proper selection of ground stations and acquisition methods. In the MetOp case this ensured successful contact of all ground stations during the first hour after separation without having to rely on any early orbit determination result or state vector update.

Applying systems ergonomics methods in sport: A systematic review.

PubMed

Hulme, Adam; Thompson, Jason; Plant, Katherine L; Read, Gemma J M; Mclean, Scott; Clacy, Amanda; Salmon, Paul M

2018-04-16

As sports systems become increasingly more complex, competitive, and technology-centric, there is a greater need for systems ergonomics methods to consider the performance, health, and safety of athletes in context with the wider settings in which they operate. Therefore, the purpose of this systematic review was to identify and critically evaluate studies which have applied a systems ergonomics research approach in the context of sports performance and injury management. Five databases (PubMed, Scopus, ScienceDirect, Web of Science, and SPORTDiscus) were searched for the dates 01 January 1990 to 01 August 2017, inclusive, for original peer-reviewed journal articles and conference papers. Reported analyses were underpinned by a recognised systems ergonomics method, and study aims were related to the optimisation of sports performance (e.g. communication, playing style, technique, tactics, or equipment), and/or the management of sports injury (i.e. identification, prevention, or treatment). A total of seven articles were identified. Two articles were focussed on understanding and optimising sports performance, whereas five examined sports injury management. The methods used were the Event Analysis of Systemic Teamwork, Cognitive Work Analysis (the Work Domain Analysis Abstraction Hierarchy), Rasmussen's Risk Management Framework, and the Systems Theoretic Accident Model and Processes method. The individual sport application was distance running, whereas the team sports contexts examined were cycling, football, Australian Football League, and rugby union. The included systems ergonomics applications were highly flexible, covering both amateur and elite sports contexts. The studies were rated as valuable, providing descriptions of injury controls and causation, the factors influencing injury management, the allocation of responsibilities for injury prevention, as well as the factors and their interactions underpinning sports performance. Implications and future directions for research are described. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Impact of Size and Specialisation on Universities' Department Performance: A DEA Analysis Applied to Austrian Universities

ERIC Educational Resources Information Center

Leitner, Karl-Heinz; Prikoszovits, Julia; Schaffhauser-Linzatti, Michaela; Stowasser, Rainer; Wagner, Karin

2007-01-01

This paper explores the performance efficiency of natural and technical science departments at Austrian universities using Data Envelopment Analysis (DEA). We present DEA as an alternative tool for benchmarking and ranking the assignment of decision-making units (organisations and organisational units). The method applies a multiple input and…

Understanding the Relationship between School-Based Management, Emotional Intelligence and Performance of Religious Upper Secondary School Principals in Banten Province

ERIC Educational Resources Information Center

Muslihah, Oleh Eneng

2015-01-01

The research examines the correlation between the understanding of school-based management, emotional intelligences and headmaster performance. Data was collected, using quantitative methods. The statistical analysis used was the Pearson Correlation, and multivariate regression analysis. The results of this research suggest firstly that there is…

Performance Evaluation of Technical Institutions: An Application of Data Envelopment Analysis

ERIC Educational Resources Information Center

Debnath, Roma Mitra; Shankar, Ravi; Kumar, Surender

2008-01-01

Technical institutions (TIs) are playing an important role in making India a knowledge hub of this century. There is still great diversity in their relative performance, which is a matter of concern to the education planner. This article employs the method of data envelopment analysis (DEA) to compare the relative efficiency of TIs in India. The…

Discovering body site and severity modifiers in clinical texts

PubMed Central

Dligach, Dmitriy; Bethard, Steven; Becker, Lee; Miller, Timothy; Savova, Guergana K

2014-01-01

Objective To research computational methods for discovering body site and severity modifiers in clinical texts. Methods We cast the task of discovering body site and severity modifiers as a relation extraction problem in the context of a supervised machine learning framework. We utilize rich linguistic features to represent the pairs of relation arguments and delegate the decision about the nature of the relationship between them to a support vector machine model. We evaluate our models using two corpora that annotate body site and severity modifiers. We also compare the model performance to a number of rule-based baselines. We conduct cross-domain portability experiments. In addition, we carry out feature ablation experiments to determine the contribution of various feature groups. Finally, we perform error analysis and report the sources of errors. Results The performance of our method for discovering body site modifiers achieves F1 of 0.740–0.908 and our method for discovering severity modifiers achieves F1 of 0.905–0.929. Discussion Results indicate that both methods perform well on both in-domain and out-domain data, approaching the performance of human annotators. The most salient features are token and named entity features, although syntactic dependency features also contribute to the overall performance. The dominant sources of errors are infrequent patterns in the data and inability of the system to discern deeper semantic structures. Conclusions We investigated computational methods for discovering body site and severity modifiers in clinical texts. Our best system is released open source as part of the clinical Text Analysis and Knowledge Extraction System (cTAKES). PMID:24091648

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

Databases for rRNA gene profiling of microbial communities

DOEpatents

Ashby, Matthew

2013-07-02

The present invention relates to methods for performing surveys of the genetic diversity of a population. The invention also relates to methods for performing genetic analyses of a population. The invention further relates to methods for the creation of databases comprising the survey information and the databases created by these methods. The invention also relates to methods for analyzing the information to correlate the presence of nucleic acid markers with desired parameters in a sample. These methods have application in the fields of geochemical exploration, agriculture, bioremediation, environmental analysis, clinical microbiology, forensic science and medicine.

Local regression type methods applied to the study of geophysics and high frequency financial data

NASA Astrophysics Data System (ADS)

Mariani, M. C.; Basu, K.

2014-09-01

In this work we applied locally weighted scatterplot smoothing techniques (Lowess/Loess) to Geophysical and high frequency financial data. We first analyze and apply this technique to the California earthquake geological data. A spatial analysis was performed to show that the estimation of the earthquake magnitude at a fixed location is very accurate up to the relative error of 0.01%. We also applied the same method to a high frequency data set arising in the financial sector and obtained similar satisfactory results. The application of this approach to the two different data sets demonstrates that the overall method is accurate and efficient, and the Lowess approach is much more desirable than the Loess method. The previous works studied the time series analysis; in this paper our local regression models perform a spatial analysis for the geophysics data providing different information. For the high frequency data, our models estimate the curve of best fit where data are dependent on time.

Multifractal Cross Wavelet Analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.

Analysis of anabolic steroids in urine by gas chromatography-microchip atmospheric pressure photoionization-mass spectrometry with chlorobenzene as dopant.

PubMed

Hintikka, Laura; Haapala, Markus; Kuuranne, Tiia; Leinonen, Antti; Kostiainen, Risto

2013-10-18

A gas chromatography-microchip atmospheric pressure photoionization-tandem mass spectrometry (GC-μAPPI-MS/MS) method was developed for the analysis of anabolic androgenic steroids in urine as their trimethylsilyl derivatives. The method utilizes a heated nebulizer microchip in atmospheric pressure photoionization mode (μAPPI) with chlorobenzene as dopant, which provides high ionization efficiency by producing abundant radical cations with minimal fragmentation. The performance of GC-μAPPI-MS/MS was evaluated with respect to repeatability, linearity, linear range, and limit of detection (LOD). The results confirmed the potential of the method for doping control analysis of anabolic steroids. Repeatability (RSD<10%), linearity (R(2)≥0.996) and sensitivity (LODs 0.05-0.1ng/mL) were acceptable. Quantitative performance of the method was tested and compared with that of conventional GC-electron ionization-MS, and the results were in good agreement. Copyright © 2013 Elsevier B.V. All rights reserved.

Manufacturing error sensitivity analysis and optimal design method of cable-network antenna structures

NASA Astrophysics Data System (ADS)

Zong, Yali; Hu, Naigang; Duan, Baoyan; Yang, Guigeng; Cao, Hongjun; Xu, Wanye

2016-03-01

Inevitable manufacturing errors and inconsistency between assumed and actual boundary conditions can affect the shape precision and cable tensions of a cable-network antenna, and even result in failure of the structure in service. In this paper, an analytical sensitivity analysis method of the shape precision and cable tensions with respect to the parameters carrying uncertainty was studied. Based on the sensitivity analysis, an optimal design procedure was proposed to alleviate the effects of the parameters that carry uncertainty. The validity of the calculated sensitivities is examined by those computed by a finite difference method. Comparison with a traditional design method shows that the presented design procedure can remarkably reduce the influence of the uncertainties on the antenna performance. Moreover, the results suggest that especially slender front net cables, thick tension ties, relatively slender boundary cables and high tension level can improve the ability of cable-network antenna structures to resist the effects of the uncertainties on the antenna performance.

Image analysis of pubic bone for age estimation in a computed tomography sample.

PubMed

López-Alcaraz, Manuel; González, Pedro Manuel Garamendi; Aguilera, Inmaculada Alemán; López, Miguel Botella

2015-03-01

Radiology has demonstrated great utility for age estimation, but most of the studies are based on metrical and morphological methods in order to perform an identification profile. A simple image analysis-based method is presented, aimed to correlate the bony tissue ultrastructure with several variables obtained from the grey-level histogram (GLH) of computed tomography (CT) sagittal sections of the pubic symphysis surface and the pubic body, and relating them with age. The CT sample consisted of 169 hospital Digital Imaging and Communications in Medicine (DICOM) archives of known sex and age. The calculated multiple regression models showed a maximum R (2) of 0.533 for females and 0.726 for males, with a high intra- and inter-observer agreement. The method suggested is considered not only useful for performing an identification profile during virtopsy, but also for application in further studies in order to attach a quantitative correlation for tissue ultrastructure characteristics, without complex and expensive methods beyond image analysis.

Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images.

PubMed

Rangel-Fonseca, Piero; Gómez-Vieyra, Armando; Malacara-Hernández, Daniel; Wilson, Mario C; Williams, David R; Rossi, Ethan A

2013-12-01

Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automated algorithms have been developed to detect the position of individual photoreceptor cells; however, most of these methods are not well suited for characterizing the RPE mosaic. We have developed an algorithm for RPE cell segmentation and show its performance here on simulated and real fluorescence AO images of the RPE mosaic. Algorithm performance was compared to manual cell identification and yielded better than 91% correspondence. This method can be used to segment RPE cells for morphometric analysis of the RPE mosaic and speed the analysis of both healthy and diseased RPE mosaics.

Clinical omics analysis of colorectal cancer incorporating copy number aberrations and gene expression data.

PubMed

Yoshida, Tsuyoshi; Kobayashi, Takumi; Itoda, Masaya; Muto, Taika; Miyaguchi, Ken; Mogushi, Kaoru; Shoji, Satoshi; Shimokawa, Kazuro; Iida, Satoru; Uetake, Hiroyuki; Ishikawa, Toshiaki; Sugihara, Kenichi; Mizushima, Hiroshi; Tanaka, Hiroshi

2010-07-29

Colorectal cancer (CRC) is one of the most frequently occurring cancers in Japan, and thus a wide range of methods have been deployed to study the molecular mechanisms of CRC. In this study, we performed a comprehensive analysis of CRC, incorporating copy number aberration (CRC) and gene expression data. For the last four years, we have been collecting data from CRC cases and organizing the information as an "omics" study by integrating many kinds of analysis into a single comprehensive investigation. In our previous studies, we had experienced difficulty in finding genes related to CRC, as we observed higher noise levels in the expression data than in the data for other cancers. Because chromosomal aberrations are often observed in CRC, here, we have performed a combination of CNA analysis and expression analysis in order to identify some new genes responsible for CRC. This study was performed as part of the Clinical Omics Database Project at Tokyo Medical and Dental University. The purpose of this study was to investigate the mechanism of genetic instability in CRC by this combination of expression analysis and CNA, and to establish a new method for the diagnosis and treatment of CRC. Comprehensive gene expression analysis was performed on 79 CRC cases using an Affymetrix Gene Chip, and comprehensive CNA analysis was performed using an Affymetrix DNA Sty array. To avoid the contamination of cancer tissue with normal cells, laser micro-dissection was performed before DNA/RNA extraction. Data analysis was performed using original software written in the R language. We observed a high percentage of CNA in colorectal cancer, including copy number gains at 7, 8q, 13 and 20q, and copy number losses at 8p, 17p and 18. Gene expression analysis provided many candidates for CRC-related genes, but their association with CRC did not reach the level of statistical significance. The combination of CNA and gene expression analysis, together with the clinical information, suggested UGT2B28, LOC440995, CXCL6, SULT1B1, RALBP1, TYMS, RAB12, RNMT, ARHGDIB, S1000A2, ABHD2, OIT3 and ABHD12 as genes that are possibly associated with CRC. Some of these genes have already been reported as being related to CRC. TYMS has been reported as being associated with resistance to the anti-cancer drug 5-fluorouracil, and we observed a copy number increase for this gene. RALBP1, ARHGDIB and S100A2 have been reported as oncogenes, and we observed copy number increases in each. ARHGDIB has been reported as a metastasis-related gene, and our data also showed copy number increases of this gene in cases with metastasis. The combination of CNA analysis and gene expression analysis was a more effective method for finding genes associated with the clinicopathological classification of CRC than either analysis alone. Using this combination of methods, we were able to detect genes that have already been associated with CRC. We also identified additional candidate genes that may be new markers or targets for this form of cancer.

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.

PubMed

You, Zhu-Hong; Lei, Ying-Ke; Zhu, Lin; Xia, Junfeng; Wang, Bing

2013-01-01

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time.

Development and validation of high-performance liquid chromatography and high-performance thin-layer chromatography methods for the quantification of khellin in Ammi visnaga seed

PubMed Central

Kamal, Abid; Khan, Washim; Ahmad, Sayeed; Ahmad, F. J.; Saleem, Kishwar

2015-01-01

Objective: The present study was used to design simple, accurate and sensitive reversed phase-high-performance liquid chromatography RP-HPLC and high-performance thin-layer chromatography (HPTLC) methods for the development of quantification of khellin present in the seeds of Ammi visnaga. Materials and Methods: RP-HPLC analysis was performed on a C18 column with methanol: Water (75: 25, v/v) as a mobile phase. The HPTLC method involved densitometric evaluation of khellin after resolving it on silica gel plate using ethyl acetate: Toluene: Formic acid (5.5:4.0:0.5, v/v/v) as a mobile phase. Results: The developed HPLC and HPTLC methods were validated for precision (interday, intraday and intersystem), robustness and accuracy, limit of detection and limit of quantification. The relationship between the concentration of standard solutions and the peak response was linear in both HPLC and HPTLC methods with the concentration range of 10–80 μg/mL in HPLC and 25–1,000 ng/spot in HPTLC for khellin. The % relative standard deviation values for method precision was found to be 0.63–1.97%, 0.62–2.05% in HPLC and HPTLC for khellin respectively. Accuracy of the method was checked by recovery studies conducted at three different concentration levels and the average percentage recovery was found to be 100.53% in HPLC and 100.08% in HPTLC for khellin. Conclusions: The developed HPLC and HPTLC methods for the quantification of khellin were found simple, precise, specific, sensitive and accurate which can be used for routine analysis and quality control of A. visnaga and several formulations containing it as an ingredient. PMID:26681890

Separation of Intercepted Multi-Radar Signals Based on Parameterized Time-Frequency Analysis

NASA Astrophysics Data System (ADS)

Lu, W. L.; Xie, J. W.; Wang, H. M.; Sheng, C.

2016-09-01

Modern radars use complex waveforms to obtain high detection performance and low probabilities of interception and identification. Signals intercepted from multiple radars overlap considerably in both the time and frequency domains and are difficult to separate with primary time parameters. Time-frequency analysis (TFA), as a key signal-processing tool, can provide better insight into the signal than conventional methods. In particular, among the various types of TFA, parameterized time-frequency analysis (PTFA) has shown great potential to investigate the time-frequency features of such non-stationary signals. In this paper, we propose a procedure for PTFA to separate overlapped radar signals; it includes five steps: initiation, parameterized time-frequency analysis, demodulating the signal of interest, adaptive filtering and recovering the signal. The effectiveness of the method was verified with simulated data and an intercepted radar signal received in a microwave laboratory. The results show that the proposed method has good performance and has potential in electronic reconnaissance applications, such as electronic intelligence, electronic warfare support measures, and radar warning.

Comparison of two thin-film microextractions for the analysis of estrogens in aqueous tea extract and environmental water samples by high performance liquid chromatography-ultraviolet detection.

PubMed

Cai, Pei-Shan; Li, Dan; Chen, Jing; Xiong, Chao-Mei; Ruan, Jin-Lan

2015-04-15

Two thin-film microextractions (TFME), octadecylsilane (ODS)-polyacrylonitrile (PAN)-TFME and polar enhanced phase (PEP)-PAN-TFME have been proposed for the analysis of bisphenol-A, diethylstilbestrol and 17β-estradiol in aqueous tea extract and environmental water samples followed by high performance liquid chromatography-ultraviolet detection. Both thin-films were prepared by spraying. The influencing factors including pH, extraction time, desorption solvent, desorption volume, desorption time, ion strength and reusability were investigated. Under the optimal conditions, the two TFME methods are similar in terms of the analytical performance evaluated by standard addition method. The limits of detection for three estrogens in environmental water and aqueous tea extract matrix ranged from 1.3 to 1.6 and 2.8 to 7.1 ng mL(-1) by the two TFME methods, respectively. Both approaches were applied for the analysis of analytes in real aqueous tea extract and environmental water samples, presenting satisfactory recoveries ranged from 87.3% to 109.4% for the spiked samples. Copyright © 2014 Elsevier Ltd. All rights reserved.