Evidence of seasonal variation in longitudinal growth of height in a sample of boys from Stuttgart Carlsschule, 1771-1793, using combined principal component analysis and maximum likelihood principle.

PubMed

Lehmann, A; Scheffler, Ch; Hermanussen, M

2010-02-01

Recent progress in modelling individual growth has been achieved by combining the principal component analysis and the maximum likelihood principle. This combination models growth even in incomplete sets of data and in data obtained at irregular intervals. We re-analysed late 18th century longitudinal growth of German boys from the boarding school Carlsschule in Stuttgart. The boys, aged 6-23 years, were measured at irregular 3-12 monthly intervals during the period 1771-1793. At the age of 18 years, mean height was 1652 mm, but height variation was large. The shortest boy reached 1474 mm, the tallest 1826 mm. Measured height closely paralleled modelled height, with mean difference of 4 mm, SD 7 mm. Seasonal height variation was found. Low growth rates occurred in spring and high growth rates in summer and autumn. The present study demonstrates that combining the principal component analysis and the maximum likelihood principle enables growth modelling in historic height data also. Copyright (c) 2009 Elsevier GmbH. All rights reserved.

Using qualitative comparative analysis in a systematic review of a complex intervention.

PubMed

Kahwati, Leila; Jacobs, Sara; Kane, Heather; Lewis, Megan; Viswanathan, Meera; Golin, Carol E

2016-05-04

Systematic reviews evaluating complex interventions often encounter substantial clinical heterogeneity in intervention components and implementation features making synthesis challenging. Qualitative comparative analysis (QCA) is a non-probabilistic method that uses mathematical set theory to study complex phenomena; it has been proposed as a potential method to complement traditional evidence synthesis in reviews of complex interventions to identify key intervention components or implementation features that might explain effectiveness or ineffectiveness. The objective of this study was to describe our approach in detail and examine the suitability of using QCA within the context of a systematic review. We used data from a completed systematic review of behavioral interventions to improve medication adherence to conduct two substantive analyses using QCA. The first analysis sought to identify combinations of nine behavior change techniques/components (BCTs) found among effective interventions, and the second analysis sought to identify combinations of five implementation features (e.g., agent, target, mode, time span, exposure) found among effective interventions. For each substantive analysis, we reframed the review's research questions to be designed for use with QCA, calibrated sets (i.e., transformed raw data into data used in analysis), and identified the necessary and/or sufficient combinations of BCTs and implementation features found in effective interventions. Our application of QCA for each substantive analysis is described in detail. We extended the original review findings by identifying seven combinations of BCTs and four combinations of implementation features that were sufficient for improving adherence. We found reasonable alignment between several systematic review steps and processes used in QCA except that typical approaches to study abstraction for some intervention components and features did not support a robust calibration for QCA. QCA was suitable for use within a systematic review of medication adherence interventions and offered insights beyond the single dimension stratifications used in the original completed review. Future prospective use of QCA during a review is needed to determine the optimal way to efficiently integrate QCA into existing approaches to evidence synthesis of complex interventions.

Differentiating Organic and Conventional Sage by Chromatographic and Mass Spectrometry Flow-Injection Fingerprints Combined with Principal Component Analysis

PubMed Central

Gao, Boyan; Lu, Yingjian; Sheng, Yi; Chen, Pei; Yu, Liangli (Lucy)

2013-01-01

High performance liquid chromatography (HPLC) and flow injection electrospray ionization with ion trap mass spectrometry (FIMS) fingerprints combined with the principal component analysis (PCA) were examined for their potential in differentiating commercial organic and conventional sage samples. The individual components in the sage samples were also characterized with an ultra-performance liquid chromatography with a quadrupole-time of flight mass spectrometer (UPLC Q-TOF MS). The results suggested that both HPLC and FIMS fingerprints combined with PCA could differentiate organic and conventional sage samples effectively. FIMS may serve as a quick test capable of distinguishing organic and conventional sages in 1 min, and could potentially be developed for high-throughput applications; whereas HPLC fingerprints could provide more chemical composition information with a longer analytical time. PMID:23464755

An Effective Solution to Discover Synergistic Drugs for Anti-Cerebral Ischemia from Traditional Chinese Medicinal Formulae

PubMed Central

Lu, Peng; Chen, Chang; Fu, Meihong; Fang, Jing; Gao, Jian; Zhu, Li; Liang, Rixin; Shen, Xin; Yang, Hongjun

2013-01-01

Recently, the pharmaceutical industry has shifted to pursuing combination therapies that comprise more than one active ingredient. Interestingly, combination therapies have been used for more than 2500 years in traditional Chinese medicine (TCM). Understanding optimal proportions and synergistic mechanisms of multi-component drugs are critical for developing novel strategies to combat complex diseases. A new multi-objective optimization algorithm based on least angle regression-partial least squares was proposed to construct the predictive model to evaluate the synergistic effect of the three components of a novel combination drug Yi-qi-jie-du formula (YJ), which came from clinical TCM prescription for the treatment of encephalopathy. Optimal proportion of the three components, ginsenosides (G), berberine (B) and jasminoidin (J) was determined via particle swarm optimum. Furthermore, the combination mechanisms were interpreted using PLS VIP and principal components analysis. The results showed that YJ had optimal proportion 3(G): 2(B): 0.5(J), and it yielded synergy in the treatment of rats impaired by middle cerebral artery occlusion induced focal cerebral ischemia. YJ with optimal proportion had good pharmacological effects on acute ischemic stroke. The mechanisms study demonstrated that the combination of G, B and J could exhibit the strongest synergistic effect. J might play an indispensable role in the formula, especially when combined with B for the acute stage of stroke. All these data in this study suggested that in the treatment of acute ischemic stroke, besides restoring blood supply and protecting easily damaged cells in the area of the ischemic penumbra as early as possible, we should pay more attention to the removal of the toxic metabolites at the same time. Mathematical system modeling may be an essential tool for the analysis of the complex pharmacological effects of multi-component drug. The powerful mathematical analysis method could greatly improve the efficiency in finding new combination drug from TCM. PMID:24236065

Indentification and Analysis of Occludin Phosphosites: A Combined Mass Spectroscoy and Bioinformatics Approach

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

Sundstrom, J.; Tash, B; Murakami, T

2009-01-01

The molecular function of occludin, an integral membrane component of tight junctions, remains unclear. VEGF-induced phosphorylation sites were mapped on occludin by combining MS data analysis with bioinformatics. In vivo phosphorylation of Ser490 was validated and protein interaction studies combined with crystal structure analysis suggest that Ser490 phosphorylation attenuates the interaction between occludin and ZO-1. This study demonstrates that combining MS data and bioinformatics can successfully identify novel phosphorylation sites from limiting samples.

The GeoViz Toolkit: Using component-oriented coordination methods for geographic visualization and analysis

PubMed Central

Hardisty, Frank; Robinson, Anthony C.

2010-01-01

In this paper we present the GeoViz Toolkit, an open-source, internet-delivered program for geographic visualization and analysis that features a diverse set of software components which can be flexibly combined by users who do not have programming expertise. The design and architecture of the GeoViz Toolkit allows us to address three key research challenges in geovisualization: allowing end users to create their own geovisualization and analysis component set on-the-fly, integrating geovisualization methods with spatial analysis methods, and making geovisualization applications sharable between users. Each of these tasks necessitates a robust yet flexible approach to inter-tool coordination. The coordination strategy we developed for the GeoViz Toolkit, called Introspective Observer Coordination, leverages and combines key advances in software engineering from the last decade: automatic introspection of objects, software design patterns, and reflective invocation of methods. PMID:21731423

Evaluation of RTV as a Moldable Matrix When Combined With Molecular Sieve and Organic Hydrogen Getter

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

Knight, J. A.

2011-12-01

This work was undertaken in an effort to develop a combined RTV 615/3Å molecular sieve/DEB molded component. A molded RTV 615/3Å molecular sieve component is currently in production, and an RTV 615/DEB component was produced in the past. However, all three materials have never before been combined in a single production part, and this is an opportunity to create a new component capable of being molded to shape, performing desiccation, and hydrogen gettering. This analysis looked at weapons system parameters and how they might influence part design. It also looked at material processing and how it related to mixing, activatingmore » a dessicant, and hydrogen uptake testing.« less

[A study of Boletus bicolor from different areas using Fourier transform infrared spectrometry].

PubMed

Zhou, Zai-Jin; Liu, Gang; Ren, Xian-Pei

2010-04-01

It is hard to differentiate the same species of wild growing mushrooms from different areas by macromorphological features. In this paper, Fourier transform infrared (FTIR) spectroscopy combined with principal component analysis was used to identify 58 samples of boletus bicolor from five different areas. Based on the fingerprint infrared spectrum of boletus bicolor samples, principal component analysis was conducted on 58 boletus bicolor spectra in the range of 1 350-750 cm(-1) using the statistical software SPSS 13.0. According to the result, the accumulated contributing ratio of the first three principal components accounts for 88.87%. They included almost all the information of samples. The two-dimensional projection plot using first and second principal component is a satisfactory clustering effect for the classification and discrimination of boletus bicolor. All boletus bicolor samples were divided into five groups with a classification accuracy of 98.3%. The study demonstrated that wild growing boletus bicolor at species level from different areas can be identified by FTIR spectra combined with principal components analysis.

Definition of Contravariant Velocity Components

NASA Technical Reports Server (NTRS)

Hung, Ching-moa; Kwak, Dochan (Technical Monitor)

2002-01-01

In this paper we have reviewed the basics of tensor analysis in an attempt to clarify some misconceptions regarding contravariant and covariant vector components as used in fluid dynamics. We have indicated that contravariant components are components of a given vector expressed as a unique combination of the covariant base vector system and, vice versa, that the covariant components are components of a vector expressed with the contravariant base vector system. Mathematically, expressing a vector with a combination of base vector is a decomposition process for a specific base vector system. Hence, the contravariant velocity components are decomposed components of velocity vector along the directions of coordinate lines, with respect to the covariant base vector system. However, the contravariant (and covariant) components are not physical quantities. Their magnitudes and dimensions are controlled by their corresponding covariant (and contravariant) base vectors.

A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

PubMed

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

A Stock Market Forecasting Model Combining Two-Directional Two-Dimensional Principal Component Analysis and Radial Basis Function Neural Network

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.

2015-01-01

In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483

Grey Relational Analysis Coupled with Principal Component Analysis for Optimization of Stereolithography Process to Enhance Part Quality

NASA Astrophysics Data System (ADS)

Raju, B. S.; Sekhar, U. Chandra; Drakshayani, D. N.

2017-08-01

The paper investigates optimization of stereolithography process for SL5530 epoxy resin material to enhance part quality. The major characteristics indexed for performance selected to evaluate the processes are tensile strength, Flexural strength, Impact strength and Density analysis and corresponding process parameters are Layer thickness, Orientation and Hatch spacing. In this study, the process is intrinsically with multiple parameters tuning so that grey relational analysis which uses grey relational grade as performance index is specially adopted to determine the optimal combination of process parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively desired. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of process parameters. Hence, this confirm that the proposed approach in this study can be an useful tool to improve the process parameters in stereolithography process, which is very useful information for machine designers as well as RP machine users.

Exergo-Economic Analysis of an Experimental Aircraft Turboprop Engine Under Low Torque Condition

NASA Astrophysics Data System (ADS)

Atilgan, Ramazan; Turan, Onder; Aydin, Hakan

Exergo-economic analysis is an unique combination of exergy analysis and cost analysis conducted at the component level. In exergo-economic analysis, cost of each exergy stream is determined. Inlet and outlet exergy streams of the each component are associated to a monetary cost. This is essential to detect cost-ineffective processes and identify technical options which could improve the cost effectiveness of the overall energy system. In this study, exergo-economic analysis is applied to an aircraft turboprop engine. Analysis is based on experimental values at low torque condition (240 N m). Main components of investigated turboprop engine are the compressor, the combustor, the gas generator turbine, the free power turbine and the exhaust. Cost balance equations have been formed for all components individually and exergo-economic parameters including cost rates and unit exergy costs have been calculated for each component.

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics.

PubMed

Song, Yuqiao; Liao, Jie; Dong, Junxing; Chen, Li

2015-09-01

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher’s discriminant analysis

PubMed Central

Mao, Zhi-Hua; Yin, Jian-Hua; Zhang, Xue-Xi; Wang, Xiao; Xia, Yang

2016-01-01

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain the quantitative information of content and spatial distribution of principal components in cartilage by combining with chemometrics methods. In this study, FTIRI combining with principal component analysis (PCA) and Fisher’s discriminant analysis (FDA) was applied to identify the healthy and osteoarthritic (OA) articular cartilage samples. Ten 10-μm thick sections of canine cartilages were imaged at 6.25μm/pixel in FTIRI. The infrared spectra extracted from the FTIR images were imported into SPSS software for PCA and FDA. Based on the PCA result of 2 principal components, the healthy and OA cartilage samples were effectively discriminated by the FDA with high accuracy of 94% for the initial samples (training set) and cross validation, as well as 86.67% for the prediction group. The study showed that cartilage degeneration became gradually weak with the increase of the depth. FTIRI combined with chemometrics may become an effective method for distinguishing healthy and OA cartilages in future. PMID:26977354

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Using principal component analysis and annual seasonal trend analysis to assess karst rocky desertification in southwestern China.

PubMed

Zhang, Zhiming; Ouyang, Zhiyun; Xiao, Yi; Xiao, Yang; Xu, Weihua

2017-06-01

Increasing exploitation of karst resources is causing severe environmental degradation because of the fragility and vulnerability of karst areas. By integrating principal component analysis (PCA) with annual seasonal trend analysis (ASTA), this study assessed karst rocky desertification (KRD) within a spatial context. We first produced fractional vegetation cover (FVC) data from a moderate-resolution imaging spectroradiometer normalized difference vegetation index using a dimidiate pixel model. Then, we generated three main components of the annual FVC data using PCA. Subsequently, we generated the slope image of the annual seasonal trends of FVC using median trend analysis. Finally, we combined the three PCA components and annual seasonal trends of FVC with the incidence of KRD for each type of carbonate rock to classify KRD into one of four categories based on K-means cluster analysis: high, moderate, low, and none. The results of accuracy assessments indicated that this combination approach produced greater accuracy and more reasonable KRD mapping than the average FVC based on the vegetation coverage standard. The KRD map for 2010 indicated that the total area of KRD was 78.76 × 10 3  km 2 , which constitutes about 4.06% of the eight southwest provinces of China. The largest KRD areas were found in Yunnan province. The combined PCA and ASTA approach was demonstrated to be an easily implemented, robust, and flexible method for the mapping and assessment of KRD, which can be used to enhance regional KRD management schemes or to address assessment of other environmental issues.

Electronic Nose Based on Independent Component Analysis Combined with Partial Least Squares and Artificial Neural Networks for Wine Prediction

PubMed Central

Aguilera, Teodoro; Lozano, Jesús; Paredes, José A.; Álvarez, Fernando J.; Suárez, José I.

2012-01-01

The aim of this work is to propose an alternative way for wine classification and prediction based on an electronic nose (e-nose) combined with Independent Component Analysis (ICA) as a dimensionality reduction technique, Partial Least Squares (PLS) to predict sensorial descriptors and Artificial Neural Networks (ANNs) for classification purpose. A total of 26 wines from different regions, varieties and elaboration processes have been analyzed with an e-nose and tasted by a sensory panel. Successful results have been obtained in most cases for prediction and classification. PMID:22969387

Application of ambient ionization high resolution mass spectrometry to determination of the botanical provenance of the constituents of psychoactive drug mixtures.

PubMed

Lesiak, Ashton D; Musah, Rabi A

2016-09-01

A continuing challenge in analytical chemistry is species-level determination of the constituents of mixtures that are made of a combination of plant species. There is an added urgency to identify components in botanical mixtures that have mind altering properties, due to the increasing global abuse of combinations of such plants. Here we demonstrate the proof of principle that ambient ionization mass spectrometry, namely direct analysis in real time-high resolution mass spectrometry (DART-HRMS), and statistical analysis tools can be used to rapidly determine the individual components within a psychoactive brew (Ayahuasca) made from a mixture of botanicals. Five plant species used in Ayahuasca preparations were subjected to DART-HRMS analysis. The chemical fingerprint of each was reproducible but unique, thus enabling discrimination between them. The presence of important biomarkers, including N,N-dimethyltryptamine, harmaline and harmine, was confirmed using in-source collision-induced dissociation (CID). Six Ayahuasca brews made from combinations of various plant species were shown to possess a high level of similarity, despite having been made from different constituents. Nevertheless, the application of principal component analysis (PCA) was useful in distinguishing between each of the brews based on the botanical species used in the preparations. From a training set based on 900 individual analyses, three principal components covered 86.38% of the variance, and the leave-one-out cross validation was 98.88%. This is the first report of ambient ionization MS being successfully used for determination of the individual components of plant mixtures. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Independent component analysis decomposition of hospital emergency department throughput measures

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Henry

2016-05-01

We present a method adapted from medical sensor data analysis, viz. independent component analysis of electroencephalography data, to health system analysis. Timely and effective care in a hospital emergency department is measured by throughput measures such as median times patients spent before they were admitted as an inpatient, before they were sent home, before they were seen by a healthcare professional. We consider a set of five such measures collected at 3,086 hospitals distributed across the U.S. One model of the performance of an emergency department is that these correlated throughput measures are linear combinations of some underlying sources. The independent component analysis decomposition of the data set can thus be viewed as transforming a set of performance measures collected at a site to a collection of outputs of spatial filters applied to the whole multi-measure data. We compare the independent component sources with the output of the conventional principal component analysis to show that the independent components are more suitable for understanding the data sets through visualizations.

CARBON CONTAINING COMPONENT OF THE LOS ANGELES AEROSOL: SOURCE APPORTIONMENT AND CONTRIBUTIONS TO THE VISIBILITY BUDGET

EPA Science Inventory

Source resolution of the organic component of the fine fraction of the ambient aerosol (d(sub p) < 3.5 micrometers) has been carried out by combining source information from the organic component with thermal analysis and local emission inventories. The primary and secondary carb...

Differentiation of Organically and Conventionally Grown Tomatoes by Chemometric Analysis of Combined Data from Proton Nuclear Magnetic Resonance and Mid-infrared Spectroscopy and Stable Isotope Analysis.

PubMed

Hohmann, Monika; Monakhova, Yulia; Erich, Sarah; Christoph, Norbert; Wachter, Helmut; Holzgrabe, Ulrike

2015-11-04

Because the basic suitability of proton nuclear magnetic resonance spectroscopy ((1)H NMR) to differentiate organic versus conventional tomatoes was recently proven, the approach to optimize (1)H NMR classification models (comprising overall 205 authentic tomato samples) by including additional data of isotope ratio mass spectrometry (IRMS, δ(13)C, δ(15)N, and δ(18)O) and mid-infrared (MIR) spectroscopy was assessed. Both individual and combined analytical methods ((1)H NMR + MIR, (1)H NMR + IRMS, MIR + IRMS, and (1)H NMR + MIR + IRMS) were examined using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and common components and specific weight analysis (ComDim). With regard to classification abilities, fused data of (1)H NMR + MIR + IRMS yielded better validation results (ranging between 95.0 and 100.0%) than individual methods ((1)H NMR, 91.3-100%; MIR, 75.6-91.7%), suggesting that the combined examination of analytical profiles enhances authentication of organically produced tomatoes.

From progressive to finite deformation, and back: the universal deformation matrix

NASA Astrophysics Data System (ADS)

Provost, A.; Buisson, C.; Merle, O.

2003-04-01

It is widely accepted that any finite strain recorded in the field may be interpreted in terms of the simultaneous combination of a pure shear component with one or several simple shear components. To predict strain in geological structures, approximate solutions may be obtained by multiplying successive small increments of each elementary strain component. A more rigorous method consists in achieving the simultaneous combination in the velocity gradient tensor but solutions already proposed in the literature are valid for special cases only and cannot be used, e.g., for the general combination of a pure shear component and six elementary simple shear components. In this paper, we show that the combination of any strain components is as simple as a mouse click, both analytically and numerically. The finite deformation matrix is given by L=exp(L.Δt) where L.Δt is the time-integrated velocity gradient tensor. This method makes it possible to predict finite strain for any combination of strain components. Reciprocally, L.Δt=ln(D) , which allows to unravel the simplest deformation history that might be liable for a given finite deformation. Given the strain ellipsoid only, it is still possible to constrain the range of compatible deformation matrices and thus the range of strain component combinations. Interestingly, certain deformation matrices, though geologically sensible, have no real logarithm so cannot be explained by a deformation history implying strain rate components with constant proportions, what implies significant changes of the stress field during the history of deformation. The study as a whole opens the possibility for further investigations on deformation analysis in general, the method could be used wathever the configuration is.

Design of fuel cell powered data centers for sufficient reliability and availability

NASA Astrophysics Data System (ADS)

Ritchie, Alexa J.; Brouwer, Jacob

2018-04-01

It is challenging to design a sufficiently reliable fuel cell electrical system for use in data centers, which require 99.9999% uptime. Such a system could lower emissions and increase data center efficiency, but the reliability and availability of such a system must be analyzed and understood. Currently, extensive backup equipment is used to ensure electricity availability. The proposed design alternative uses multiple fuel cell systems each supporting a small number of servers to eliminate backup power equipment provided the fuel cell design has sufficient reliability and availability. Potential system designs are explored for the entire data center and for individual fuel cells. Reliability block diagram analysis of the fuel cell systems was accomplished to understand the reliability of the systems without repair or redundant technologies. From this analysis, it was apparent that redundant components would be necessary. A program was written in MATLAB to show that the desired system reliability could be achieved by a combination of parallel components, regardless of the number of additional components needed. Having shown that the desired reliability was achievable through some combination of components, a dynamic programming analysis was undertaken to assess the ideal allocation of parallel components.

Text analysis devices, articles of manufacture, and text analysis methods

DOEpatents

Turner, Alan E; Hetzler, Elizabeth G; Nakamura, Grant C

2015-03-31

Text analysis devices, articles of manufacture, and text analysis methods are described according to some aspects. In one aspect, a text analysis device includes a display configured to depict visible images, and processing circuitry coupled with the display and wherein the processing circuitry is configured to access a first vector of a text item and which comprises a plurality of components, to access a second vector of the text item and which comprises a plurality of components, to weight the components of the first vector providing a plurality of weighted values, to weight the components of the second vector providing a plurality of weighted values, and to combine the weighted values of the first vector with the weighted values of the second vector to provide a third vector.

Comparative study on fast classification of brick samples by combination of principal component analysis and linear discriminant analysis using stand-off and table-top laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Vítková, Gabriela; Prokeš, Lubomír; Novotný, Karel; Pořízka, Pavel; Novotný, Jan; Všianský, Dalibor; Čelko, Ladislav; Kaiser, Jozef

2014-11-01

Focusing on historical aspect, during archeological excavation or restoration works of buildings or different structures built from bricks it is important to determine, preferably in-situ and in real-time, the locality of bricks origin. Fast classification of bricks on the base of Laser-Induced Breakdown Spectroscopy (LIBS) spectra is possible using multivariate statistical methods. Combination of principal component analysis (PCA) and linear discriminant analysis (LDA) was applied in this case. LIBS was used to classify altogether the 29 brick samples from 7 different localities. Realizing comparative study using two different LIBS setups - stand-off and table-top it is shown that stand-off LIBS has a big potential for archeological in-field measurements.

Combined seismic plus live-load analysis of highway bridges.

DOT National Transportation Integrated Search

2011-10-01

"The combination of seismic and vehicle live loadings on bridges is an important design consideration. There are well-established design : provisions for how the individual loadings affect bridge response: structural components that carry vertical li...

Neural network for photoplethysmographic respiratory rate monitoring

NASA Astrophysics Data System (ADS)

Johansson, Anders

2001-10-01

The photoplethysmographic signal (PPG) includes respiratory components seen as frequency modulation of the heart rate (respiratory sinus arrhythmia, RSA), amplitude modulation of the cardiac pulse, and respiratory induced intensity variations (RIIV) in the PPG baseline. The aim of this study was to evaluate the accuracy of these components in determining respiratory rate, and to combine the components in a neural network for improved accuracy. The primary goal is to design a PPG ventilation monitoring system. PPG signals were recorded from 15 healthy subjects. From these signals, the systolic waveform, diastolic waveform, respiratory sinus arrhythmia, pulse amplitude and RIIV were extracted. By using simple algorithms, the rates of false positive and false negative detection of breaths were calculated for each of the five components in a separate analysis. Furthermore, a simple neural network (NN) was tried out in a combined pattern recognition approach. In the separate analysis, the error rates (sum of false positives and false negatives) ranged from 9.7% (pulse amplitude) to 14.5% (systolic waveform). The corresponding value of the NN analysis was 9.5-9.6%.

A new statistical PCA-ICA algorithm for location of R-peaks in ECG.

PubMed

Chawla, M P S; Verma, H K; Kumar, Vinod

2008-09-16

The success of ICA to separate the independent components from the mixture depends on the properties of the electrocardiogram (ECG) recordings. This paper discusses some of the conditions of independent component analysis (ICA) that could affect the reliability of the separation and evaluation of issues related to the properties of the signals and number of sources. Principal component analysis (PCA) scatter plots are plotted to indicate the diagnostic features in the presence and absence of base-line wander in interpreting the ECG signals. In this analysis, a newly developed statistical algorithm by authors, based on the use of combined PCA-ICA for two correlated channels of 12-channel ECG data is proposed. ICA technique has been successfully implemented in identifying and removal of noise and artifacts from ECG signals. Cleaned ECG signals are obtained using statistical measures like kurtosis and variance of variance after ICA processing. This analysis also paper deals with the detection of QRS complexes in electrocardiograms using combined PCA-ICA algorithm. The efficacy of the combined PCA-ICA algorithm lies in the fact that the location of the R-peaks is bounded from above and below by the location of the cross-over points, hence none of the peaks are ignored or missed.

Identification and apportionment of hazardous elements in the sediments in the Yangtze River estuary.

PubMed

Wang, Jiawei; Liu, Ruimin; Wang, Haotian; Yu, Wenwen; Xu, Fei; Shen, Zhenyao

2015-12-01

In this study, positive matrix factorization (PMF) and principal components analysis (PCA) were combined to identify and apportion pollution-based sources of hazardous elements in the surface sediments in the Yangtze River estuary (YRE). Source identification analysis indicated that PC1, including Al, Fe, Mn, Cr, Ni, As, Cu, and Zn, can be defined as a sewage component; PC2, including Pb and Sb, can be considered as an atmospheric deposition component; and PC3, containing Cd and Hg, can be considered as an agricultural nonpoint component. To better identify the sources and quantitatively apportion the concentrations to their sources, eight sources were identified with PMF: agricultural/industrial sewage mixed (18.6 %), mining wastewater (15.9 %), agricultural fertilizer (14.5 %), atmospheric deposition (12.8 %), agricultural nonpoint (10.6 %), industrial wastewater (9.8 %), marine activity (9.0 %), and nickel plating industry (8.8 %). Overall, the hazardous element content seems to be more connected to anthropogenic activity instead of natural sources. The PCA results laid the foundation for the PMF analysis by providing a general classification of sources. PMF resolves more factors with a higher explained variance than PCA; PMF provided both the internal analysis and the quantitative analysis. The combination of the two methods can provide more reasonable and reliable results.

Research on criticality analysis method of CNC machine tools components under fault rate correlation

NASA Astrophysics Data System (ADS)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

Respiratory protective device design using control system techniques

NASA Technical Reports Server (NTRS)

Burgess, W. A.; Yankovich, D.

1972-01-01

The feasibility of a control system analysis approach to provide a design base for respiratory protective devices is considered. A system design approach requires that all functions and components of the system be mathematically identified in a model of the RPD. The mathematical notations describe the operation of the components as closely as possible. The individual component mathematical descriptions are then combined to describe the complete RPD. Finally, analysis of the mathematical notation by control system theory is used to derive compensating component values that force the system to operate in a stable and predictable manner.

Meta-analysis of graduated driver licensing laws: effectiveness of specific program components : traffic tech.

DOT National Transportation Integrated Search

2015-11-01

Graduated driver licensing (GDL) programs in the United States do not represent a single homogeneous intervention; rather, they contain different combinations and variations of program components. Programs vary by the duration of each stage of the GD...

HepG2 cells biospecific extraction and HPLC-ESI-MS analysis for screening potential antiatherosclerotic active components in Bupeuri radix.

PubMed

Liu, Shuqiang; Tan, Zhibin; Li, Pingting; Gao, Xiaoling; Zeng, Yuaner; Wang, Shuling

2016-03-20

HepG2 cells biospecific extraction method and high performance liquid chromatography-electrospray ionization-mass spectrometry (HPLC-ESI-MS) analysis was proposed for screening of potential antiatherosclerotic active components in Bupeuri radix, a well-known Traditional Chinese Medicine (TCM). The hypothesis suggested that when cells are incubated together with the extracts of TCM, the potential bioactive components in the TCM should selectively combine with the receptor or channel of HepG2 cells, then the eluate which contained biospecific component binding to HepG2 cells was identified using HPLC-ESI-MS analysis. The potential bioactive components of Bupeuri radix were investigated using the proposed approach. Five compounds in the saikosaponins of Bupeuri radix were detected as these components selectively combined with HepG2 cells, among these compounds, two potentially bioactive compounds namely saikosaponin b1 and saikosaponin b2 (SSb2) were identified by comparing with the chromatography of the standard sample and analysis of the structural clearance characterization of MS. Then SSb2 was used to assess the uptake of DiI-high density lipoprotein (HDL) in HepG2 cells for antiatherosclerotic activity. The results have showed that SSb2, with indicated concentrations (5, 15, 25, and 40 μM) could remarkably uptake dioctadecylindocarbocyanine labeled- (DiI) -HDL in HepG2 cells (Vs control group, *P<0.01). In conclusion, the application of HepG2 biospecific extraction coupled with HPLC-ESI-MS analysis is a rapid, convenient, and reliable method for screening potential bioactive components in TCM and SSb2 may be a valuable novel drug agent for the treatment of atherosclerosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Analysis of the Laser Drilling Process for the Combination with a Single-Lip Deep Hole Drilling Process with Small Diameters

NASA Astrophysics Data System (ADS)

Biermann, Dirk; Heilmann, Markus

Due to the tendency of downsizing of components, also the industrial relevance of bore holes with small diameters and high length-to-diameter ratios rises with the growing requirements on parts. In these applications, the combination of laser pre-drilling and single-lip deep hole drilling can shorten the process chain in machining components with non-planar surfaces, or can reduce tool wear in machining case-hardened materials. In this research, the combination of these processes was realized and investigated for the very first time.

The Psychometric Assessment of Children with Learning Disabilities: An Index Derived from a Principal Components Analysis of the WISC-R.

ERIC Educational Resources Information Center

Lawson, J. S.; Inglis, James

1984-01-01

A learning disability index (LDI) for the assessment of intellectual deficits on the Wechsler Intelligence Scale for Children-Revised (WISC-R) is described. The Factor II score coefficients derived from an unrotated principal components analysis of the WISC-R normative data, in combination with the individual's scaled scores, are used for this…

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

Authentication of virgin olive oil by a novel curve resolution approach combined with visible spectroscopy.

PubMed

Ferreiro-González, Marta; Barbero, Gerardo F; Álvarez, José A; Ruiz, Antonio; Palma, Miguel; Ayuso, Jesús

2017-04-01

Adulteration of olive oil is not only a major economic fraud but can also have major health implications for consumers. In this study, a combination of visible spectroscopy with a novel multivariate curve resolution method (CR), principal component analysis (PCA) and linear discriminant analysis (LDA) is proposed for the authentication of virgin olive oil (VOO) samples. VOOs are well-known products with the typical properties of a two-component system due to the two main groups of compounds that contribute to the visible spectra (chlorophylls and carotenoids). Application of the proposed CR method to VOO samples provided the two pure-component spectra for the aforementioned families of compounds. A correlation study of the real spectra and the resolved component spectra was carried out for different types of oil samples (n=118). LDA using the correlation coefficients as variables to discriminate samples allowed the authentication of 95% of virgin olive oil samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Combining features from ERP components in single-trial EEG for discriminating four-category visual objects.

PubMed

Wang, Changming; Xiong, Shi; Hu, Xiaoping; Yao, Li; Zhang, Jiacai

2012-10-01

Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.

Noninvasive deep Raman detection with 2D correlation analysis

NASA Astrophysics Data System (ADS)

Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug

2014-07-01

The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.

A Component Analysis of Schedule Thinning during Functional Communication Training

ERIC Educational Resources Information Center

Betz, Alison M.; Fisher, Wayne W.; Roane, Henry S.; Mintz, Joslyn C.; Owen, Todd M.

2013-01-01

One limitation of functional communication training (FCT) is that individuals may request reinforcement via the functional communication response (FCR) at exceedingly high rates. Multiple schedules with alternating periods of reinforcement and extinction of the FCR combined with gradually lengthening the extinction-component interval can…

Synergistic reaction of silver nitrate, silver nanoparticles, and methylene blue against bacteria

PubMed Central

Li, Runze; Chen, Jie; Cesario, Thomas C.; Wang, Xin; Yuan, Joshua S.; Rentzepis, Peter M.

2016-01-01

In this paper we describe the antibacterial effect of methylene blue, MB, and silver nitrate reacting alone and in combination against five bacterial strains including Serratia marcescens and Escherichia coli bacteria. The data presented suggest that when the two components are combined and react together against bacteria, the effects can be up to three orders of magnitude greater than that of the sum of the two components reacting alone against bacteria. Analysis of the experimental data provides proof that a synergistic mechanism is operative within a dose range when the two components react together, and additive when reacting alone against bacteria. PMID:27849602

A Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis

PubMed Central

Wagatsuma, Hiroaki

2017-01-01

EEG signals contain a large amount of ocular artifacts with different time-frequency properties mixing together in EEGs of interest. The artifact removal has been substantially dealt with by existing decomposition methods known as PCA and ICA based on the orthogonality of signal vectors or statistical independence of signal components. We focused on the signal morphology and proposed a systematic decomposition method to identify the type of signal components on the basis of sparsity in the time-frequency domain based on Morphological Component Analysis (MCA), which provides a way of reconstruction that guarantees accuracy in reconstruction by using multiple bases in accordance with the concept of “dictionary.” MCA was applied to decompose the real EEG signal and clarified the best combination of dictionaries for this purpose. In our proposed semirealistic biological signal analysis with iEEGs recorded from the brain intracranially, those signals were successfully decomposed into original types by a linear expansion of waveforms, such as redundant transforms: UDWT, DCT, LDCT, DST, and DIRAC. Our result demonstrated that the most suitable combination for EEG data analysis was UDWT, DST, and DIRAC to represent the baseline envelope, multifrequency wave-forms, and spiking activities individually as representative types of EEG morphologies. PMID:28194221

Pharmacophore modeling, docking, and principal component analysis based clustering: combined computer-assisted approaches to identify new inhibitors of the human rhinovirus coat protein.

PubMed

Steindl, Theodora M; Crump, Carolyn E; Hayden, Frederick G; Langer, Thierry

2005-10-06

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

Multibody model reduction by component mode synthesis and component cost analysis

NASA Technical Reports Server (NTRS)

Spanos, J. T.; Mingori, D. L.

1990-01-01

The classical assumed-modes method is widely used in modeling the dynamics of flexible multibody systems. According to the method, the elastic deformation of each component in the system is expanded in a series of spatial and temporal functions known as modes and modal coordinates, respectively. This paper focuses on the selection of component modes used in the assumed-modes expansion. A two-stage component modal reduction method is proposed combining Component Mode Synthesis (CMS) with Component Cost Analysis (CCA). First, each component model is truncated such that the contribution of the high frequency subsystem to the static response is preserved. Second, a new CMS procedure is employed to assemble the system model and CCA is used to further truncate component modes in accordance with their contribution to a quadratic cost function of the system output. The proposed method is demonstrated with a simple example of a flexible two-body system.

Resolving fluorophores by unmixing multispectral fluorescence tomography with independent component analysis

NASA Astrophysics Data System (ADS)

Pu, Huangsheng; Zhang, Guanglei; He, Wei; Liu, Fei; Guang, Huizhi; Zhang, Yue; Bai, Jing; Luo, Jianwen

2014-09-01

It is a challenging problem to resolve and identify drug (or non-specific fluorophore) distribution throughout the whole body of small animals in vivo. In this article, an algorithm of unmixing multispectral fluorescence tomography (MFT) images based on independent component analysis (ICA) is proposed to solve this problem. ICA is used to unmix the data matrix assembled by the reconstruction results from MFT. Then the independent components (ICs) that represent spatial structures and the corresponding spectrum courses (SCs) which are associated with spectral variations can be obtained. By combining the ICs with SCs, the recovered MFT images can be generated and fluorophore concentration can be calculated. Simulation studies, phantom experiments and animal experiments with different concentration contrasts and spectrum combinations are performed to test the performance of the proposed algorithm. Results demonstrate that the proposed algorithm can not only provide the spatial information of fluorophores, but also recover the actual reconstruction of MFT images.

Towards the identification of plant and animal binders on Australian stone knives.

PubMed

Blee, Alisa J; Walshe, Keryn; Pring, Allan; Quinton, Jamie S; Lenehan, Claire E

2010-07-15

There is limited information regarding the nature of plant and animal residues used as adhesives, fixatives and pigments found on Australian Aboriginal artefacts. This paper reports the use of FTIR in combination with the chemometric tools principal component analysis (PCA) and hierarchical clustering (HC) for the analysis and identification of Australian plant and animal fixatives on Australian stone artefacts. Ten different plant and animal residues were able to be discriminated from each other at a species level by combining FTIR spectroscopy with the chemometric data analysis methods, principal component analysis (PCA) and hierarchical clustering (HC). Application of this method to residues from three broken stone knives from the collections of the South Australian Museum indicated that two of the handles of knives were likely to have contained beeswax as the fixative whilst Spinifex resin was the probable binder on the third. Copyright 2010 Elsevier B.V. All rights reserved.

Recovery of a spectrum based on a compressive-sensing algorithm with weighted principal component analysis

NASA Astrophysics Data System (ADS)

Dafu, Shen; Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang

2017-07-01

The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.

Exploratory Application of Neuropharmacometabolomics in Severe Childhood Traumatic Brain Injury.

PubMed

Hagos, Fanuel T; Empey, Philip E; Wang, Pengcheng; Ma, Xiaochao; Poloyac, Samuel M; Bayır, Hülya; Kochanek, Patrick M; Bell, Michael J; Clark, Robert S B

2018-05-07

To employ metabolomics-based pathway and network analyses to evaluate the cerebrospinal fluid metabolome after severe traumatic brain injury in children and the capacity of combination therapy with probenecid and N-acetylcysteine to impact glutathione-related and other pathways and networks, relative to placebo treatment. Analysis of cerebrospinal fluid obtained from children enrolled in an Institutional Review Board-approved, randomized, placebo-controlled trial of a combination of probenecid and N-acetylcysteine after severe traumatic brain injury (Trial Registration NCT01322009). Thirty-six-bed PICU in a university-affiliated children's hospital. Twelve children 2-18 years old after severe traumatic brain injury and five age-matched control subjects. Probenecid (25 mg/kg) and N-acetylcysteine (140 mg/kg) or placebo administered via naso/orogastric tube. The cerebrospinal fluid metabolome was analyzed in samples from traumatic brain injury patients 24 hours after the first dose of drugs or placebo and control subjects. Feature detection, retention time, alignment, annotation, and principal component analysis and statistical analysis were conducted using XCMS-online. The software "mummichog" was used for pathway and network analyses. A two-component principal component analysis revealed clustering of each of the groups, with distinct metabolomics signatures. Several novel pathways with plausible mechanistic involvement in traumatic brain injury were identified. A combination of metabolomics and pathway/network analyses showed that seven glutathione-centered pathways and two networks were enriched in the cerebrospinal fluid of traumatic brain injury patients treated with probenecid and N-acetylcysteine versus placebo-treated patients. Several additional pathways/networks consisting of components that are known substrates of probenecid-inhibitable transporters were also identified, providing additional mechanistic validation. This proof-of-concept neuropharmacometabolomics assessment reveals alterations in known and previously unidentified metabolic pathways and supports therapeutic target engagement of the combination of probenecid and N-acetylcysteine treatment after severe traumatic brain injury in children.

Source Determination of Red Gel Pen Inks using Raman Spectroscopy and Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy combined with Pearson's Product Moment Correlation Coefficients and Principal Component Analysis.

PubMed

Mohamad Asri, Muhammad Naeim; Mat Desa, Wan Nur Syuhaila; Ismail, Dzulkiflee

2018-01-01

The potential combination of two nondestructive techniques, that is, Raman spectroscopy (RS) and attenuated total reflectance-fourier transform infrared (ATR-FTIR) spectroscopy with Pearson's product moment correlation (PPMC) coefficient (r) and principal component analysis (PCA) to determine the actual source of red gel pen ink used to write a simulated threatening note, was examined. Eighteen (18) red gel pens purchased from Japan and Malaysia from November to December 2014 where one of the pens was used to write a simulated threatening note were analyzed using RS and ATR-FTIR spectroscopy, respectively. The spectra of all the red gel pen inks including the ink deposited on the simulated threatening note gathered from the RS and ATR-FTIR analyses were subjected to PPMC coefficient (r) calculation and principal component analysis (PCA). The coefficients r = 0.9985 and r = 0.9912 for pairwise combination of RS and ATR-FTIR spectra respectively and similarities in terms of PC1 and PC2 scores of one of the inks to the ink deposited on the simulated threatening note substantiated the feasibility of combining RS and ATR-FTIR spectroscopy with PPMC coefficient (r) and PCA for successful source determination of red gel pen inks. The development of pigment spectral library had allowed the ink deposited on the threatening note to be identified as XSL Poppy Red (CI Pigment Red 112). © 2017 American Academy of Forensic Sciences.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Greater impairment of postprandial triacylglycerol than glucose response in metabolic syndrome subjects with fasting hyperglycaemia.

PubMed

Jackson, Kim G; Walden, Charlotte M; Murray, Peter; Smith, Adrian M; Minihane, Anne M; Lovegrove, Julie A; Williams, Christine M

2013-08-01

Studies have started to question whether a specific component or combinations of metabolic syndrome (MetS) components may be more important in relation to cardiovascular disease risk. Our aim was to examine the impact of the presence of raised fasting glucose as a MetS component on postprandial lipaemia. Men classified with the MetS underwent a sequential test meal investigation, in which blood samples were taken at regular intervals after a test breakfast (t=0 min) and lunch (t=330 min). Lipids, glucose and insulin were measured in the fasting and postprandial samples. MetS subjects with 3 or 4 components were subdivided into those without (n=34) and with (n=23) fasting hyperglycaemia (≥5.6 mmol/l), irrespective of the combination of components. Fasting lipids and insulin were similar in the two groups, with glucose significantly higher in the men with glucose as a MetS component (P<0.001). Following the test meals, there were higher maximum concentration (maxC), area under the curve (AUC) and incremental AUC (P ≤0.016) for the postprandial triacylglycerol (TAG) response in men with fasting hyperglycaemia. Greater glucose AUC (P<0.001) and insulin maxC (P=0.010) were also observed in these individuals after the test meals. Multiple regression analysis revealed fasting glucose to be an important predictor of the postprandial TAG and glucose response. Our data analysis has revealed a greater impairment of postprandial TAG than glucose response in MetS subjects with raised fasting glucose. The worsening of postprandial lipaemic control may contribute to the greater CVD risk reported in individuals with MetS component combinations which include hyperglycaemia. Copyright © 2013 Elsevier Inc. All rights reserved.

Estimating locations and total magnetization vectors of compact magnetic sources from scalar, vector, or tensor magnetic measurements through combined Helbig and Euler analysis

USGS Publications Warehouse

Phillips, J.D.; Nabighian, M.N.; Smith, D.V.; Li, Y.

2007-01-01

The Helbig method for estimating total magnetization directions of compact sources from magnetic vector components is extended so that tensor magnetic gradient components can be used instead. Depths of the compact sources can be estimated using the Euler equation, and their dipole moment magnitudes can be estimated using a least squares fit to the vector component or tensor gradient component data. ?? 2007 Society of Exploration Geophysicists.

Joint variability of global runoff and global sea surface temperatures

USGS Publications Warehouse

McCabe, G.J.; Wolock, D.M.

2008-01-01

Global land surface runoff and sea surface temperatures (SST) are analyzed to identify the primary modes of variability of these hydroclimatic data for the period 1905-2002. A monthly water-balance model first is used with global monthly temperature and precipitation data to compute time series of annual gridded runoff for the analysis period. The annual runoff time series data are combined with gridded annual sea surface temperature data, and the combined dataset is subjected to a principal components analysis (PCA) to identify the primary modes of variability. The first three components from the PCA explain 29% of the total variability in the combined runoff/SST dataset. The first component explains 15% of the total variance and primarily represents long-term trends in the data. The long-term trends in SSTs are evident as warming in all of the oceans. The associated long-term trends in runoff suggest increasing flows for parts of North America, South America, Eurasia, and Australia; decreasing runoff is most notable in western Africa. The second principal component explains 9% of the total variance and reflects variability of the El Ni??o-Southern Oscillation (ENSO) and its associated influence on global annual runoff patterns. The third component explains 5% of the total variance and indicates a response of global annual runoff to variability in North Aflantic SSTs. The association between runoff and North Atlantic SSTs may explain an apparent steplike change in runoff that occurred around 1970 for a number of continental regions.

Copper-free route to triazole-modified peptidomimetic by the combination of two multicomponent reactions in one pot.

PubMed

Niu, Teng-fei; Gu, Lin; Yi, Wen-bin; Cai, Chun

2012-05-14

An efficient copper-free protocol for the synthesis of 5-methyl-1H-1,2,3-triazole-modified peptidomimetics through the combination of Ugi four-component reaction with a three-component cycloaddition, has been developed. The copper-free straightforward process is suitable for drug discovery. The chemoselective preparation of 1,4-disubstituted, triazole-modified peptidomimetics by using alkynyl substituted amines may have potential biological and synthetic application. At last, a "Lapinski type" analysis of the physical properties was performed, which is expected to help drug discovery.

Wilderness ecology: virgin plant communities of the Boundary Waters Canoe Area.

Treesearch

Lewis F. Ohmann; Robert R. Ream

1971-01-01

Describes virgin plant communities in the Boundary Waters Canoe Area. Data from all vegetative components of 106 virgin upland stands were used to construct a community classification through a combination of agglomerative clustering and principal components analysis. Discusses the relation of communities to their environment and to past wildfires.

ERP Go/NoGo condition effects are better detected with separate PCAs.

PubMed

Barry, Robert J; De Blasio, Frances M; Fogarty, Jack S; Karamacoska, Diana

2016-08-01

We explored the separation of Go and NoGo effects in the ERP components elicited in an equiprobable Go/NoGo task, using different forms of temporal Principal Components Analysis (PCA). Following exploratory simulation studies assessing the PCA impact of latency jitter and between-condition latency differences in the P3 latency range, an empirical study compared results of a Combined PCA carried out using both Go and NoGo ERPs together as input, with those from two Separate PCAs carried out on the Go and NoGo ERPs separately. The simulation studies indicated that Separate PCAs provide adequate component recovery in the presence of P3 latency jitter, and that Combined PCAs provide good separation of components only when systematic condition-related latency differences are sufficiently large (here ~110ms). In the empirical data, broadly-similar components were obtained from the Combined and Separate PCAs, supporting previous findings from Combined PCA investigations, and the consequent interpretations of the sequential processing involved. However, the Separate PCAs generated latency differences for components in the Go and NoGo processing chains that better matched the late Go/NoGo ERP peaks, and produced better-defined and larger components that fitted the stages in a hypothetical processing schema developed for this paradigm. Overall, the Separate PCAs yielded a better partitioning of the ERP variance associated with the Go and NoGo conditions, and should be considered as the first choice in future investigations if systematic component or subcomponent latency differences are present or suspected. Copyright © 2016 Elsevier B.V. All rights reserved.

The analysis of ensembles of moderately saturated interstellar lines

NASA Technical Reports Server (NTRS)

Jenkins, E. B.

1986-01-01

It is shown that the combined equivalent widths for a large population of Gaussian-like interstellar line components, each with different central optical depths tau(0) and velocity dispersions b, exhibit a curve of growth (COG) which closely mimics that of a single, pure Gaussian distribution in velocity. Two parametric distributions functions for the line populations are considered: a bivariate Gaussian for tau(0) and b and a power law distribution for tau(0) combined with a Gaussian dispersion for b. First, COGs for populations having an extremely large number of nonoverlapping components are derived, and the implications are shown by focusing on the doublet-ratio analysis for a pair of lines whose f-values differ by a factor of two. The consequences of having, instead of an almost infinite number of lines, a relatively small collection of components added together for each member of a doublet are examined. The theory of how the equivalent widths grow for populations of overlapping Gaussian profiles is developed. Examples of the composite COG analysis applied to existing collections of high-resolution interstellar line data are presented.

Tracing and separating plasma components causing matrix effects in hydrophilic interaction chromatography-electrospray ionization mass spectrometry.

PubMed

Ekdahl, Anja; Johansson, Maria C; Ahnoff, Martin

2013-04-01

Matrix effects on electrospray ionization were investigated for plasma samples analysed by hydrophilic interaction chromatography (HILIC) in gradient elution mode, and HILIC columns of different chemistries were tested for separation of plasma components and model analytes. By combining mass spectral data with post-column infusion traces, the following components of protein-precipitated plasma were identified and found to have significant effect on ionization: urea, creatinine, phosphocholine, lysophosphocholine, sphingomyelin, sodium ion, chloride ion, choline and proline betaine. The observed effect on ionization was both matrix-component and analyte dependent. The separation of identified plasma components and model analytes on eight columns was compared, using pair-wise linear correlation analysis and principal component analysis (PCA). Large changes in selectivity could be obtained by change of column, while smaller changes were seen when the mobile phase buffer was changed from ammonium formate pH 3.0 to ammonium acetate pH 4.5. While results from PCA and linear correlation analysis were largely in accord, linear correlation analysis was judged to be more straight-forward in terms of conduction and interpretation.

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution

PubMed Central

Feng, Xiao-Liang; He, Yun-biao; Liang, Yi-Zeng; Wang, Yu-Lin; Huang, Lan-Fang; Xie, Jian-Wei

2013-01-01

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria. PMID:24286016

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution.

PubMed

Feng, Xiao-Liang; He, Yun-Biao; Liang, Yi-Zeng; Wang, Yu-Lin; Huang, Lan-Fang; Xie, Jian-Wei

2013-01-01

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria.

[Quality evaluation of rhubarb dispensing granules based on multi-component simultaneous quantitative analysis and bioassay].

PubMed

Tan, Peng; Zhang, Hai-Zhu; Zhang, Ding-Kun; Wu, Shan-Na; Niu, Ming; Wang, Jia-Bo; Xiao, Xiao-He

2017-07-01

This study attempts to evaluate the quality of Chinese formula granules by combined use of multi-component simultaneous quantitative analysis and bioassay. The rhubarb dispensing granules were used as the model drug for demonstrative study. The ultra-high performance liquid chromatography (UPLC) method was adopted for simultaneously quantitative determination of the 10 anthraquinone derivatives (such as aloe emodin-8-O-β-D-glucoside) in rhubarb dispensing granules; purgative biopotency of different batches of rhubarb dispensing granules was determined based on compound diphenoxylate tablets-induced mouse constipation model; blood activating biopotency of different batches of rhubarb dispensing granules was determined based on in vitro rat antiplatelet aggregation model; SPSS 22.0 statistical software was used for correlation analysis between 10 anthraquinone derivatives and purgative biopotency, blood activating biopotency. The results of multi-components simultaneous quantitative analysisshowed that there was a great difference in chemical characterizationand certain differences inpurgative biopotency and blood activating biopotency among 10 batches of rhubarb dispensing granules. The correlation analysis showed that the intensity of purgative biopotency was significantly correlated with the content of conjugated anthraquinone glycosides (P<0.01), and the intensity of blood activating biopotency was significantly correlated with the content of free anthraquinone (P<0.01). In summary, the combined use of multi-component simultaneous quantitative analysis and bioassay can achieve objective quantification and more comprehensive reflection on overall quality difference among different batches of rhubarb dispensing granules. Copyright© by the Chinese Pharmaceutical Association.

Strategies for Increasing the Market Share of Recycled Products—A Games Theory Approach

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.; Pollalis, Yannis A.

2009-08-01

A methodological framework (including 28 activity stages and 10 decision nodes) has been designed under the form of an algorithmic procedure for the development of strategies for increasing the market share of recycled products within a games theory context. A case example is presented referring to a paper market, where a recycling company (RC) is in competition with a virgin-raw-material-using company (VC). The strategies of the VC, for increasing its market share, are the strengthening of (and advertisement based on) the high quality (VC1), the high reliability (VC2), the combination quality and reliability, putting emphasis on the first component (VC3), the combination quality and reliability, putting emphasis on the second component (VC4). The strategies of the RC, for increasing its market share, are proper advertisement based on the low price of produced recycled paper satisfying minimum quality requirements (RC1), the combination of low price with sensitization of the public as regards environmental and materials-saving issues, putting emphasis on the first component (RC2), the same combination, putting emphasis on the second component (RC3). Analysis of all possible situations for the case example under examination is also presented.

Rapid differentiation of Chinese hop varieties (Humulus lupulus) using volatile fingerprinting by HS-SPME-GC-MS combined with multivariate statistical analysis.

PubMed

Liu, Zechang; Wang, Liping; Liu, Yumei

2018-01-18

Hops impart flavor to beer, with the volatile components characterizing the various hop varieties and qualities. Fingerprinting, especially flavor fingerprinting, is often used to identify 'flavor products' because inconsistencies in the description of flavor may lead to an incorrect definition of beer quality. Compared to flavor fingerprinting, volatile fingerprinting is simpler and easier. We performed volatile fingerprinting using head space-solid phase micro-extraction gas chromatography-mass spectrometry combined with similarity analysis and principal component analysis (PCA) for evaluating and distinguishing between three major Chinese hops. Eighty-four volatiles were identified, which were classified into seven categories. Volatile fingerprinting based on similarity analysis did not yield any obvious result. By contrast, hop varieties and qualities were identified using volatile fingerprinting based on PCA. The potential variables explained the variance in the three hop varieties. In addition, the dendrogram and principal component score plot described the differences and classifications of hops. Volatile fingerprinting plus multivariate statistical analysis can rapidly differentiate between the different varieties and qualities of the three major Chinese hops. Furthermore, this method can be used as a reference in other fields. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

A conservative method of testing whether combination analgesics produce additive or synergistic effects using evidence from acute pain and migraine.

PubMed

Moore, R A; Derry, C J; Derry, S; Straube, S; McQuay, H J

2012-04-01

Fixed-dose combination analgesics are used widely, and available both on prescription and over-the-counter. Combination drugs should provide more analgesia than with any single drug in the combination, but there is no evidence in humans about whether oral combinations have just additive effects, or are synergistic or even subadditive. We suggest that the measured result for the combination would be the summation of the absolute benefit increase (effect of active drug minus effect of placebo) of each component of a combination if effects were (merely) additive, and greater than the sum of the absolute benefits if they were synergistic. We tested measured effects of combination analgesics against the sum of the absolute benefits in acute pain and migraine using meta-analysis where individual components and combinations were tested against placebo in the same trials, and verified the result with meta-analyses where individual components and combinations were tested against placebo in different trials. Results showed that expected numbers needed to treat (NNT) for additive effects were generally within the 95% confidence interval of measured NNTs. This was true for combinations of paracetamol plus ibuprofen and paracetamol plus opioids in acute pain, and naproxen plus sumatriptan in migraine, but not where efficacy was very low or very high, nor combinations of paracetamol plus dextropropoxyphene. There was no evidence of synergy, defined as supra-additive effects. © 2011 European Federation of International Association for the Study of Pain Chapters.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2004-03-23

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following prediction or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The hybrid method herein means a combination of an initial calibration step with subsequent analysis by an inverse multivariate analysis method. A spectral shape herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The shape can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Component-based subspace linear discriminant analysis method for face recognition with one training sample

NASA Astrophysics Data System (ADS)

Huang, Jian; Yuen, Pong C.; Chen, Wen-Sheng; Lai, J. H.

2005-05-01

Many face recognition algorithms/systems have been developed in the last decade and excellent performances have also been reported when there is a sufficient number of representative training samples. In many real-life applications such as passport identification, only one well-controlled frontal sample image is available for training. Under this situation, the performance of existing algorithms will degrade dramatically or may not even be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples with lower dimension than the original image, but also consider the face detection localization error while training. After that, we propose a subspace LDA method, which is tailor-made for a small number of training samples, for the local feature projection to maximize the discrimination power. Theoretical analysis and experiment results show that our proposed subspace LDA is efficient and overcomes the limitations in existing LDA methods. Finally, we combine the contributions of each local component bunch with a weighted combination scheme to draw the recognition decision. A FERET database is used for evaluating the proposed method and results are encouraging.

Fluorescence fingerprint as an instrumental assessment of the sensory quality of tomato juices.

PubMed

Trivittayasil, Vipavee; Tsuta, Mizuki; Imamura, Yoshinori; Sato, Tsuneo; Otagiri, Yuji; Obata, Akio; Otomo, Hiroe; Kokawa, Mito; Sugiyama, Junichi; Fujita, Kaori; Yoshimura, Masatoshi

2016-03-15

Sensory analysis is an important standard for evaluating food products. However, as trained panelists and time are required for the process, the potential of using fluorescence fingerprint as a rapid instrumental method to approximate sensory characteristics was explored in this study. Thirty-five out of 44 descriptive sensory attributes were found to show a significant difference between samples (analysis of variance test). Principal component analysis revealed that principal component 1 could capture 73.84 and 75.28% variance for aroma category and combined flavor and taste category respectively. Fluorescence fingerprints of tomato juices consisted of two visible peaks at excitation/emission wavelengths of 290/350 and 315/425 nm and a long narrow emission peak at 680 nm. The 680 nm peak was only clearly observed in juices obtained from tomatoes cultivated to be eaten raw. The ability to predict overall sensory profiles was investigated by using principal component 1 as a regression target. Fluorescence fingerprint could predict principal component 1 of both aroma and combined flavor and taste with a coefficient of determination above 0.8. The results obtained in this study indicate the potential of using fluorescence fingerprint as an instrumental method for assessing sensory characteristics of tomato juices. © 2015 Society of Chemical Industry.

Application of Hyperspectral Imaging and Chemometric Calibrations for Variety Discrimination of Maize Seeds

PubMed Central

Zhang, Xiaolei; Liu, Fei; He, Yong; Li, Xiaoli

2012-01-01

Hyperspectral imaging in the visible and near infrared (VIS-NIR) region was used to develop a novel method for discriminating different varieties of commodity maize seeds. Firstly, hyperspectral images of 330 samples of six varieties of maize seeds were acquired using a hyperspectral imaging system in the 380–1,030 nm wavelength range. Secondly, principal component analysis (PCA) and kernel principal component analysis (KPCA) were used to explore the internal structure of the spectral data. Thirdly, three optimal wavelengths (523, 579 and 863 nm) were selected by implementing PCA directly on each image. Then four textural variables including contrast, homogeneity, energy and correlation were extracted from gray level co-occurrence matrix (GLCM) of each monochromatic image based on the optimal wavelengths. Finally, several models for maize seeds identification were established by least squares-support vector machine (LS-SVM) and back propagation neural network (BPNN) using four different combinations of principal components (PCs), kernel principal components (KPCs) and textural features as input variables, respectively. The recognition accuracy achieved in the PCA-GLCM-LS-SVM model (98.89%) was the most satisfactory one. We conclude that hyperspectral imaging combined with texture analysis can be implemented for fast classification of different varieties of maize seeds. PMID:23235456

Visualizing Java uncertainty

NASA Astrophysics Data System (ADS)

Knight, Claire; Munro, Malcolm

2001-07-01

Distributed component based systems seem to be the immediate future for software development. The use of such techniques, object oriented languages, and the combination with ever more powerful higher-level frameworks has led to the rapid creation and deployment of such systems to cater for the demand of internet and service driven business systems. This diversity of solution through both components utilised and the physical/virtual locations of those components can provide powerful resolutions to the new demand. The problem lies in the comprehension and maintenance of such systems because they then have inherent uncertainty. The components combined at any given time for a solution may differ, the messages generated, sent, and/or received may differ, and the physical/virtual locations cannot be guaranteed. Trying to account for this uncertainty and to build in into analysis and comprehension tools is important for both development and maintenance activities.

A combined cICA-EEMD analysis of EEG recordings from depressed or schizophrenic patients during olfactory stimulation

NASA Astrophysics Data System (ADS)

Götz, Th; Stadler, L.; Fraunhofer, G.; Tomé, A. M.; Hausner, H.; Lang, E. W.

2017-02-01

Objective. We propose a combination of a constrained independent component analysis (cICA) with an ensemble empirical mode decomposition (EEMD) to analyze electroencephalographic recordings from depressed or schizophrenic subjects during olfactory stimulation. Approach. EEMD serves to extract intrinsic modes (IMFs) underlying the recorded EEG time. The latter then serve as reference signals to extract the most similar underlying independent component within a constrained ICA. The extracted modes are further analyzed considering their power spectra. Main results. The analysis of the extracted modes reveals clear differences in the related power spectra between the disease characteristics of depressed and schizophrenic patients. Such differences appear in the high frequency γ-band in the intrinsic modes, but also in much more detail in the low frequency range in the α-, θ- and δ-bands. Significance. The proposed method provides various means to discriminate both disease pictures in a clinical environment.

The combined use of order tracking techniques for enhanced Fourier analysis of order components

NASA Astrophysics Data System (ADS)

Wang, K. S.; Heyns, P. S.

2011-04-01

Order tracking is one of the most important vibration analysis techniques for diagnosing faults in rotating machinery. It can be performed in many different ways, each of these with distinct advantages and disadvantages. However, in the end the analyst will often use Fourier analysis to transform the data from a time series to frequency or order spectra. It is therefore surprising that the study of the Fourier analysis of order-tracked systems seems to have been largely ignored in the literature. This paper considers the frequently used Vold-Kalman filter-based order tracking and computed order tracking techniques. The main pros and cons of each technique for Fourier analysis are discussed and the sequential use of Vold-Kalman filtering and computed order tracking is proposed as a novel idea to enhance the results of Fourier analysis for determining the order components. The advantages of the combined use of these order tracking techniques are demonstrated numerically on an SDOF rotor simulation model. Finally, the approach is also demonstrated on experimental data from a real rotating machine.

Some Interesting Applications of Probabilistic Techiques in Structural Dynamic Analysis of Rocket Engines

NASA Technical Reports Server (NTRS)

Brown, Andrew M.

2014-01-01

Numerical and Analytical methods developed to determine damage accumulation in specific engine components when speed variation included. Dither Life Ratio shown to be well over factor of 2 for specific example. Steady-State assumption shown to be accurate for most turbopump cases, allowing rapid calculation of DLR. If hot-fire speed data unknown, Monte Carlo method developed that uses speed statistics for similar engines. Application of techniques allow analyst to reduce both uncertainty and excess conservatism. High values of DLR could allow previously unacceptable part to pass HCF criteria without redesign. Given benefit and ease of implementation, recommend that any finite life turbomachine component analysis adopt these techniques. Probability Values calculated, compared, and evaluated for several industry-proposed methods for combining random and harmonic loads. Two new excel macros written to calculate combined load for any specific probability level. Closed form Curve fits generated for widely used 3(sigma) and 2(sigma) probability levels. For design of lightweight aerospace components, obtaining accurate, reproducible, statistically meaningful answer critical.

Quantitative structure-activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods.

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure-activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7-7-1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure-activity relationship model suggested is robust and satisfactory.

Quantitative structure–activity relationship study of P2X7 receptor inhibitors using combination of principal component analysis and artificial intelligence methods

PubMed Central

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

P2X7 antagonist activity for a set of 49 molecules of the P2X7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. The activity of these compounds was estimated by means of combination of principal component analysis (PCA), as a well-known data reduction method, genetic algorithm (GA), as a variable selection technique, and artificial neural network (ANN), as a non-linear modeling method. First, a linear regression, combined with PCA, (principal component regression) was operated to model the structure–activity relationships, and afterwards a combination of PCA and ANN algorithm was employed to accurately predict the biological activity of the P2X7 antagonist. PCA preserves as much of the information as possible contained in the original data set. Seven most important PC's to the studied activity were selected as the inputs of ANN box by an efficient variable selection method, GA. The best computational neural network model was a fully-connected, feed-forward model with 7−7−1 architecture. The developed ANN model was fully evaluated by different validation techniques, including internal and external validation, and chemical applicability domain. All validations showed that the constructed quantitative structure–activity relationship model suggested is robust and satisfactory. PMID:26600858

Univariate and multivariate molecular spectral analyses of lipid related molecular structural components in relation to nutrient profile in feed and food mixtures

NASA Astrophysics Data System (ADS)

Abeysekara, Saman; Damiran, Daalkhaijav; Yu, Peiqiang

2013-02-01

The objectives of this study were (i) to determine lipid related molecular structures components (functional groups) in feed combination of cereal grain (barley, Hordeum vulgare) and wheat (Triticum aestivum) based dried distillers grain solubles (wheat DDGSs) from bioethanol processing at five different combination ratios using univariate and multivariate molecular spectral analyses with infrared Fourier transform molecular spectroscopy, and (ii) to correlate lipid-related molecular-functional structure spectral profile to nutrient profiles. The spectral intensity of (i) CH3 asymmetric, CH2 asymmetric, CH3 symmetric and CH2 symmetric groups, (ii) unsaturation (Cdbnd C) group, and (iii) carbonyl ester (Cdbnd O) group were determined. Spectral differences of functional groups were detected by hierarchical cluster analysis (HCA) and principal components analysis (PCA). The results showed that the combination treatments significantly inflicted modifications (P < 0.05) in nutrient profile and lipid related molecular spectral intensity (CH2 asymmetric stretching peak height, CH2 symmetric stretching peak height, ratio of CH2 to CH3 symmetric stretching peak intensity, and carbonyl peak area). Ratio of CH2 to CH3 symmetric stretching peak intensity, and carbonyl peak significantly correlated with nutrient profiles. Both PCA and HCA differentiated lipid-related spectrum. In conclusion, the changes of lipid molecular structure spectral profiles through feed combination could be detected using molecular spectroscopy. These changes were associated with nutrient profiles and functionality.

ECOPASS - a multivariate model used as an index of growth performance of poplar clones

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

Ceulemans, R.; Impens, I.

The model (ECOlogical PASSport) reported was constructed by principal component analysis from a combination of biochemical, anatomical/morphological and ecophysiological gas exchange parameters measured on 5 fast growing poplar clones. Productivity data were 10 selected trees in 3 plantations in Belgium and given as m.a.i.(b.a.). The model is shown to be able to reflect not only genetic origin and the relative effects of the different parameters of the clones, but also their production potential. Multiple regression analysis of the 4 principal components showed a high cumulative correlation (96%) between the 3 components related to ecophysiological, biochemical and morphological parameters, and productivity;more » the ecophysiological component alone correlated 85% with productivity.« less

Hierarchical Regularity in Multi-Basin Dynamics on Protein Landscapes

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Kostov, Konstatin S.; Komatsuzaki, Tamiki

2004-04-01

We analyze time series of potential energy fluctuations and principal components at several temperatures for two kinds of off-lattice 46-bead models that have two distinctive energy landscapes. The less-frustrated "funnel" energy landscape brings about stronger nonstationary behavior of the potential energy fluctuations at the folding temperature than the other, rather frustrated energy landscape at the collapse temperature. By combining principal component analysis with an embedding nonlinear time-series analysis, it is shown that the fast fluctuations with small amplitudes of 70-80% of the principal components cause the time series to become almost "random" in only 100 simulation steps. However, the stochastic feature of the principal components tends to be suppressed through a wide range of degrees of freedom at the transition temperature.

Single-step methods for predicting orbital motion considering its periodic components

NASA Astrophysics Data System (ADS)

Lavrov, K. N.

1989-01-01

Modern numerical methods for integration of ordinary differential equations can provide accurate and universal solutions to celestial mechanics problems. The implicit single sequence algorithms of Everhart and multiple step computational schemes using a priori information on periodic components can be combined to construct implicit single sequence algorithms which combine their advantages. The construction and analysis of the properties of such algorithms are studied, utilizing trigonometric approximation of the solutions of differential equations containing periodic components. The algorithms require 10 percent more machine memory than the Everhart algorithms, but are twice as fast, and yield short term predictions valid for five to ten orbits with good accuracy and five to six times faster than algorithms using other methods.

INTEGRATED ENVIRONMENTAL ASSESSMENT OF THE MID-ATLANTIC REGION WITH ANALYTICAL NETWORK PROCESS

EPA Science Inventory

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account interdependency among variables, the method was capable of ran...

Discrimination of red and white rice bran from Indonesia using HPLC fingerprint analysis combined with chemometrics.

PubMed

Sabir, Aryani; Rafi, Mohamad; Darusman, Latifah K

2017-04-15

HPLC fingerprint analysis combined with chemometrics was developed to discriminate between the red and the white rice bran grown in Indonesia. The major component in rice bran is γ-oryzanol which consisted of 4 main compounds, namely cycloartenol ferulate, cyclobranol ferulate, campesterol ferulate and β-sitosterol ferulate. Separation of these four compounds along with other compounds was performed using C18 and methanol-acetonitrile with gradient elution system. By using these intensity variations, principal component and discriminant analysis were performed to discriminate the two samples. Discriminant analysis was successfully discriminated the red from the white rice bran with predictive ability of the model showed a satisfactory classification for the test samples. The results of this study indicated that the developed method was suitable as quality control method for rice bran in terms of identification and discrimination of the red and the white rice bran. Copyright © 2016 Elsevier Ltd. All rights reserved.

Semi-blind Bayesian inference of CMB map and power spectrum

NASA Astrophysics Data System (ADS)

Vansyngel, Flavien; Wandelt, Benjamin D.; Cardoso, Jean-François; Benabed, Karim

2016-04-01

We present a new blind formulation of the cosmic microwave background (CMB) inference problem. The approach relies on a phenomenological model of the multifrequency microwave sky without the need for physical models of the individual components. For all-sky and high resolution data, it unifies parts of the analysis that had previously been treated separately such as component separation and power spectrum inference. We describe an efficient sampling scheme that fully explores the component separation uncertainties on the inferred CMB products such as maps and/or power spectra. External information about individual components can be incorporated as a prior giving a flexible way to progressively and continuously introduce physical component separation from a maximally blind approach. We connect our Bayesian formalism to existing approaches such as Commander, spectral mismatch independent component analysis (SMICA), and internal linear combination (ILC), and discuss possible future extensions.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer.

PubMed

Gu, Haiwei; Pan, Zhengzheng; Xi, Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

2011-02-07

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology. Copyright © 2010 Elsevier B.V. All rights reserved.

Effects of changes along the risk chain on flood risk

NASA Astrophysics Data System (ADS)

Duha Metin, Ayse; Apel, Heiko; Viet Dung, Nguyen; Guse, Björn; Kreibich, Heidi; Schröter, Kai; Vorogushyn, Sergiy; Merz, Bruno

2017-04-01

Interactions of hydrological and socio-economic factors shape flood disaster risk. For this reason, assessment of flood risk ideally takes into account the whole flood risk chain from atmospheric processes, through the catchment and river system processes to the damage mechanisms in the affected areas. Since very different processes at various scales are interacting along the flood risk, the impact of the single components is rather unclear. However for flood risk management, it is required to know the controlling factor of flood damages. The present study, using the flood-prone Mulde catchment in Germany, discusses the sensitivity of flood risk to disturbances along the risk chain: How do disturbances propagate through the risk chain? How do different disturbances combine or conflict and affect flood risk? In this sensitivity analysis, the five components of the flood risk change are included. These are climate, catchment, river system, exposure and vulnerability. A model framework representing the complete risk chain is combined with observational data to understand how the sensitivities evolve along the risk chain by considering three plausible change scenarios for each of five components. The flood risk is calculated by using the Regional Flood Model (RFM) which is based on a continuous simulation approach, including rainfall-runoff, 1D river network, 2D hinterland inundation and damage estimation models. The sensitivity analysis covers more than 240 scenarios with different combinations of the five components. It is investigated how changes in different components affect risk indicators, such as the risk curve and expected annual damage (EAD). In conclusion, it seems that changes in exposure and vulnerability seem to outweigh changes in hazard.

Optimized principal component analysis on coronagraphic images of the fomalhaut system

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

Meshkat, Tiffany; Kenworthy, Matthew A.; Quanz, Sascha P.

We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing angular differential imaging and locally optimized combination of images (LOCI) for increasing the contrast achievable next to a bright star. The stellar point spread function (PSF) is constructed by removing linear combinations of principal components, allowing the flux from an extrasolar planet to shine through. The number of principal components used determines how well the stellar PSF is globally modeled. Using more principal components may decrease the number of speckles in the final image, but also increases themore » background noise. We apply PCA to Fomalhaut Very Large Telescope NaCo images acquired at 4.05 μm with an apodized phase plate. We do not detect any companions, with a model dependent upper mass limit of 13-18 M {sub Jup} from 4-10 AU. PCA achieves greater sensitivity than the LOCI algorithm for the Fomalhaut coronagraphic data by up to 1 mag. We make several adaptations to the PCA code and determine which of these prove the most effective at maximizing the signal-to-noise from a planet very close to its parent star. We demonstrate that optimizing the number of principal components used in PCA proves most effective for pulling out a planet signal.« less

Methodology for modeling the devolatilization of refuse-derived fuel from thermogravimetric analysis of municipal solid waste components

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

Fritsky, K.J.; Miller, D.L.; Cernansky, N.P.

1994-09-01

A methodology was introduced for modeling the devolatilization characteristics of refuse-derived fuel (RFD) in terms of temperature-dependent weight loss. The basic premise of the methodology is that RDF is modeled as a combination of select municipal solid waste (MSW) components. Kinetic parameters are derived for each component from thermogravimetric analyzer (TGA) data measured at a specific set of conditions. These experimentally derived parameters, along with user-derived parameters, are inputted to model equations for the purpose of calculating thermograms for the components. The component thermograms are summed to create a composite thermogram that is an estimate of the devolatilization for themore » as-modeled RFD. The methodology has several attractive features as a thermal analysis tool for waste fuels. 7 refs., 10 figs., 3 tabs.« less

Phase I/II study of sorafenib in combination with temsirolimus for recurrent glioblastoma or gliosarcoma: North American Brain Tumor Consortium study 05-02

PubMed Central

Lee, Eudocia Q.; Kuhn, John; Lamborn, Kathleen R.; Abrey, Lauren; DeAngelis, Lisa M.; Lieberman, Frank; Robins, H. Ian; Chang, Susan M.; Yung, W. K. Alfred; Drappatz, Jan; Mehta, Minesh P.; Levin, Victor A.; Aldape, Kenneth; Dancey, Janet E.; Wright, John J.; Prados, Michael D.; Cloughesy, Timothy F.; Gilbert, Mark R.; Wen, Patrick Y.

2012-01-01

The activity of single-agent targeted molecular therapies in glioblastoma has been limited to date. The North American Brain Tumor Consortium examined the safety, pharmacokinetics, and efficacy of combination therapy with sorafenib, a small molecule inhibitor of Raf, vascular endothelial growth factor receptor 2, and platelet-derived growth factor receptor–β, and temsirolimus (CCI-779), an inhibitor of mammalian target of rapamycin. This was a phase I/II study. The phase I component used a standard 3 × 3 dose escalation scheme to determine the safety and tolerability of this combination therapy. The phase II component used a 2-stage design; the primary endpoint was 6-month progression-free survival (PFS6) rate. Thirteen patients enrolled in the phase I component. The maximum tolerated dosage (MTD) for combination therapy was sorafenib 800 mg daily and temsirolimus 25 mg once weekly. At the MTD, grade 3 thrombocytopenia was the dose-limiting toxicity. Eighteen patients were treated in the phase II component. At interim analysis, the study was terminated and did not proceed to the second stage. No patients remained progression free at 6 months. Median PFS was 8 weeks. The toxicity of this combination therapy resulted in a maximum tolerated dose of temsirolimus that was only one-tenth of the single-agent dose. Minimal activity in recurrent glioblastoma multiforme was seen at the MTD of the 2 combined agents. PMID:23099651

TH-C-19A-11: Toward An Optimized Multi-Point Scintillation Detector

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

Duguay-Drouin, P; Delage, ME; Centre Hospitalier University de Quebec, Quebec, QC

Purpose: The purpose of this work is to characterize a 2-points mPSDs' optical chain using a spectral analysis to help selecting the optimal components for the detector. Methods: Twenty different 2-points mPSD combinations were built using 4 plastic scintillators (BCF10, BCF12, BCF60, BC430; St-Gobain) and quantum dots (QDs). The scintillator is said to be proximal when near the photodetector, and distal otherwise. A 15m optical fiber (ESKA GH-4001) was coupled to the scintillating component and connected to a spectrometer (Shamrock, Andor and QEPro, OceanOptics). These scintillation components were irradiated at 125kVp; a spectrum for each scintillator was obtained by irradiationmore » of individual scintillator and shielding the second component, thus talking into account light propagation in all components and interfaces. The combined total spectrum was also acquired and involved simultaneous irradiation of the two scintillators for each possible combination. The shape and intensity were characterized. Results: QDs in proximal position absorb almost all the light signal from distal plastic scintillators and emit in its own emission wavelength, with 100% of the signal in the QD range (625–700nm) for the combination BCF12/QD. However, discrimination is possible when QD is in distal position in combination with blue scintillators, total signal being 73% in the blue range (400-550nm) and 27% in QD range. Similar results are obtained with the orange scintillator (BC430). For optimal signal intensity, BCF12 should always be in proximal position, e.g. having 50% more intensity when coupled with BCF60 in distal position (BCF12/BCF60) compared to the BCF60/BCF12 combination. Conclusion: Different combinations of plastic scintillators and QD were built and their emission spectra were studied. We established a preferential order for the scintillating components in the context of an optimized 2-points mPSD. In short, the components with higher wavelength emission spectrum should be distal and lower wavelength in the proximal position.« less

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

NASA Astrophysics Data System (ADS)

Zhang, Ying-Zhi; Liu, Jin-Tong; Shen, Gui-Xiang; Long, Zhe; Sun, Shu-Guang

2017-07-01

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system.

Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology.

PubMed

Hou, Jiebin; Chen, Wei; Lu, Hongtao; Zhao, Hongxia; Gao, Songyan; Liu, Wenrui; Dong, Xin; Guo, Zhiyong

2018-01-01

Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb.) Merr (DS) has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use. Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein-protein interaction (PPI) relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model. Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD), were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was then constructed. The expressions of CTSD, p-p38 MAPK, and p-CDK-2 were shown to be increased in the oxalate group and decreased in kidney tissue by the DS treatment. Luteolin, apigenin, and genistein could protect oxalate-stimulated tubular cells as active components of DS. Conclusion: The potential targets including the CTSD, p38 MAPK, and CDK2 of DS in oxalate-induced kidney injuries and the active components (luteolin, apigenin, and genistein) of DS were successfully identified in this study by combining proteomics analysis, network pharmacology prediction, and experimental validation.

Sparse principal component analysis in medical shape modeling

NASA Astrophysics Data System (ADS)

Sjöstrand, Karl; Stegmann, Mikkel B.; Larsen, Rasmus

2006-03-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims at producing easily interpreted models through sparse loadings, i.e. each new variable is a linear combination of a subset of the original variables. One of the aims of using SPCA is the possible separation of the results into isolated and easily identifiable effects. This article introduces SPCA for shape analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA algorithm has been implemented using Matlab and is available for download. The general behavior of the algorithm is investigated, and strengths and weaknesses are discussed. The original report on the SPCA algorithm argues that the ordering of modes is not an issue. We disagree on this point and propose several approaches to establish sensible orderings. A method that orders modes by decreasing variance and maximizes the sum of variances for all modes is presented and investigated in detail.

A novel approach combining self-organizing map and parallel factor analysis for monitoring water quality of watersheds under non-point source pollution

PubMed Central

Zhang, Yixiang; Liang, Xinqiang; Wang, Zhibo; Xu, Lixian

2015-01-01

High content of organic matter in the downstream of watersheds underscored the severity of non-point source (NPS) pollution. The major objectives of this study were to characterize and quantify dissolved organic matter (DOM) in watersheds affected by NPS pollution, and to apply self-organizing map (SOM) and parallel factor analysis (PARAFAC) to assess fluorescence properties as proxy indicators for NPS pollution and labor-intensive routine water quality indicators. Water from upstreams and downstreams was sampled to measure dissolved organic carbon (DOC) concentrations and excitation-emission matrix (EEM). Five fluorescence components were modeled with PARAFAC. The regression analysis between PARAFAC intensities (Fmax) and raw EEM measurements indicated that several raw fluorescence measurements at target excitation-emission wavelength region could provide similar DOM information to massive EEM measurements combined with PARAFAC. Regression analysis between DOC concentration and raw EEM measurements suggested that some regions in raw EEM could be used as surrogates for labor-intensive routine indicators. SOM can be used to visualize the occurrence of pollution. Relationship between DOC concentration and PARAFAC components analyzed with SOM suggested that PARAFAC component 2 might be the major part of bulk DOC and could be recognized as a proxy indicator to predict the DOC concentration. PMID:26526140

Developing and Evaluating Creativity Gamification Rehabilitation System: The Application of PCA-ANFIS Based Emotions Model

ERIC Educational Resources Information Center

Su, Chung-Ho; Cheng, Ching-Hsue

2016-01-01

This study aims to explore the factors in a patient's rehabilitation achievement after a total knee replacement (TKR) patient exercises, using a PCA-ANFIS emotion model-based game rehabilitation system, which combines virtual reality (VR) and motion capture technology. The researchers combine a principal component analysis (PCA) and an adaptive…

Decomposing the Apoptosis Pathway Into Biologically Interpretable Principal Components

PubMed Central

Wang, Min; Kornblau, Steven M; Coombes, Kevin R

2018-01-01

Principal component analysis (PCA) is one of the most common techniques in the analysis of biological data sets, but applying PCA raises 2 challenges. First, one must determine the number of significant principal components (PCs). Second, because each PC is a linear combination of genes, it rarely has a biological interpretation. Existing methods to determine the number of PCs are either subjective or computationally extensive. We review several methods and describe a new R package, PCDimension, that implements additional methods, the most important being an algorithm that extends and automates a graphical Bayesian method. Using simulations, we compared the methods. Our newly automated procedure is competitive with the best methods when considering both accuracy and speed and is the most accurate when the number of objects is small compared with the number of attributes. We applied the method to a proteomics data set from patients with acute myeloid leukemia. Proteins in the apoptosis pathway could be explained using 6 PCs. By clustering the proteins in PC space, we were able to replace the PCs by 6 “biological components,” 3 of which could be immediately interpreted from the current literature. We expect this approach combining PCA with clustering to be widely applicable. PMID:29881252

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.

PubMed

Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein

2017-12-13

As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms 1D wavelet.

Investigating the composition characteristics of dissolved and particulate/colloidal organic matter in effluent-dominated stream using fluorescence spectroscopy combined with multivariable analysis.

PubMed

Yu, Min-Da; He, Xiao-Song; Xi, Bei-Dou; Gao, Ru-Tai; Zhao, Xian-Wei; Zhang, Hui; Huang, Cai-Hong; Tan, Wenbing

2018-03-01

Fluorescence excitation-emission matrix (EEM) spectroscopy combined with principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to investigate the compositional characteristics of dissolved and particulate/colloidal organic matter and its correlations with nitrogen, phosphorus, and heavy metals in an effluent-dominated stream, Northern China. The results showed that dissolved organic matter (DOM) was comprised of fulvic-like, humic-like, and protein-like components in the water samples, and fulvic-like substances were the main fraction of DOM among them. Particulate/colloidal organic matter (PcOM) consisted of fulvic-like and protein-like matter. Fulvic-like substances existed in the larger molecular form in PcOM, and they comprised a large amount of nitrogen and polar functional groups. On the other hand, protein-like components in PcOM were low in benzene ring and bound to heavy metals. It could be concluded that nitrogen, phosphorus, and heavy metals in effluent had an effect on the compositional characteristics of natural DOM and PcOM, which may deepen our understanding about the environmental behaviors of organic matter in effluent.

The use of multidate multichannel radiance data in urban feature analysis

NASA Technical Reports Server (NTRS)

Duggin, M. J.; Rowntree, R.; Emmons, M.; Hubbard, N.; Odell, A. W.

1986-01-01

Two images were obtained from thematic mappers on Landsats 4 and 5 over the Washington, DC area during November 1982 and March 1984. Selected training areas containing different types of urban land use were examined,one area consisting entirely of forest. Mean digital radiance values for each bandpass in each image were examined, and variances, standard deviations, and covariances between bandpasses were calculated. It has been found that two bandpasses caused forested areas to stand out from other land use types, especially for the November 1982 image. In order to evaluate quantitatively the possible utility of the principal components analysis in selected feature extraction, the eigenvectors were evaluated for principal axes rotations which rendered each selected land use type most separable from all other land use types. The evaluated eigenvectors were plotted as a function of land use type, whose order was decided by considering anticipated shadow component and by examining the relative loadings indicative of vegetation for each of the principal components for the different features considered. The analysis was performed for each seven-band image separately and for the two combined images. It was found that by combining the two images, more dramatic land use type separation could be obtained.

Gravity Tides Extracted from Relative Gravimeter Data by Combining Empirical Mode Decomposition and Independent Component Analysis

NASA Astrophysics Data System (ADS)

Yu, Hongjuan; Guo, Jinyun; Kong, Qiaoli; Chen, Xiaodong

2018-04-01

The static observation data from a relative gravimeter contain noise and signals such as gravity tides. This paper focuses on the extraction of the gravity tides from the static relative gravimeter data for the first time applying the combined method of empirical mode decomposition (EMD) and independent component analysis (ICA), called the EMD-ICA method. The experimental results from the CG-5 gravimeter (SCINTREX Limited Ontario Canada) data show that the gravity tides time series derived by EMD-ICA are consistent with the theoretical reference (Longman formula) and the RMS of their differences only reaches 4.4 μGal. The time series of the gravity tides derived by EMD-ICA have a strong correlation with the theoretical time series and the correlation coefficient is greater than 0.997. The accuracy of the gravity tides estimated by EMD-ICA is comparable to the theoretical model and is slightly higher than that of independent component analysis (ICA). EMD-ICA could overcome the limitation of ICA having to process multiple observations and slightly improve the extraction accuracy and reliability of gravity tides from relative gravimeter data compared to that estimated with ICA.

Experimental design based 3-D QSAR analysis of steroid-protein interactions: Application to human CBG complexes

NASA Astrophysics Data System (ADS)

Norinder, Ulf

1990-12-01

An experimental design based 3-D QSAR analysis using a combination of principal component and PLS analysis is presented and applied to human corticosteroid-binding globulin complexes. The predictive capability of the created model is good. The technique can also be used as guidance when selecting new compounds to be investigated.

Least-dependent-component analysis based on mutual information

NASA Astrophysics Data System (ADS)

Stögbauer, Harald; Kraskov, Alexander; Astakhov, Sergey A.; Grassberger, Peter

2004-12-01

We propose to use precise estimators of mutual information (MI) to find the least dependent components in a linearly mixed signal. On the one hand, this seems to lead to better blind source separation than with any other presently available algorithm. On the other hand, it has the advantage, compared to other implementations of “independent” component analysis (ICA), some of which are based on crude approximations for MI, that the numerical values of the MI can be used for (i) estimating residual dependencies between the output components; (ii) estimating the reliability of the output by comparing the pairwise MIs with those of remixed components; and (iii) clustering the output according to the residual interdependencies. For the MI estimator, we use a recently proposed k -nearest-neighbor-based algorithm. For time sequences, we combine this with delay embedding, in order to take into account nontrivial time correlations. After several tests with artificial data, we apply the resulting MILCA (mutual-information-based least dependent component analysis) algorithm to a real-world dataset, the ECG of a pregnant woman.

Decoupled 1D/3D analysis of a hydraulic valve

NASA Astrophysics Data System (ADS)

Mehring, Carsten; Zopeya, Ashok; Latham, Matt; Ihde, Thomas; Massie, Dan

2014-10-01

Analysis approaches during product development of fluid valves and other aircraft fluid delivery components vary greatly depending on the development stage. Traditionally, empirical or simplistic one-dimensional tools are being deployed during preliminary design, whereas detailed analysis such as CFD (Computational Fluid Dynamics) tools are used to refine a selected design during the detailed design stage. In recent years, combined 1D/3D co-simulation has been deployed specifically for system level simulations requiring an increased level of analysis detail for one or more components. The present paper presents a decoupled 1D/3D analysis approach where 3D CFD analysis results are utilized to enhance the fidelity of a dynamic 1D modelin context of an aircraft fuel valve.

Solvent extraction of oil-sand components for determination of trace elements by neutron activation analysis

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

Jacobs, F.S.; Filby, R.H.

Instrumental neutron activation analysis was used to measure the concentrations of 30 elements in Athabasca oil sands and oil-sand components. The oil sands were separated into solid residue, bitumen, and fines by Soxhlet extraction with toluene-bitumen extract. The mineral content of the extracted bitumen was dependent on the treatment of the oil sand prior to extraction. The geochemically important and organically associated trace element contents of the bitumen (and asphaltenes) were determined by subtracting the mineral contributions from the total measured concentrations. The method allows analysis of the bitumen without the necessity of ultracentrifugation or membrane filtration, which might removemore » geochemically important components of the bitumen. The method permits classification of trace elements into organic and inorganic combinations.« less

Fracture mechanics concepts in reliability analysis of monolithic ceramics

NASA Technical Reports Server (NTRS)

Manderscheid, Jane M.; Gyekenyesi, John P.

1987-01-01

Basic design concepts for high-performance, monolithic ceramic structural components are addressed. The design of brittle ceramics differs from that of ductile metals because of the inability of ceramic materials to redistribute high local stresses caused by inherent flaws. Random flaw size and orientation requires that a probabilistic analysis be performed in order to determine component reliability. The current trend in probabilistic analysis is to combine linear elastic fracture mechanics concepts with the two parameter Weibull distribution function to predict component reliability under multiaxial stress states. Nondestructive evaluation supports this analytical effort by supplying data during verification testing. It can also help to determine statistical parameters which describe the material strength variation, in particular the material threshold strength (the third Weibull parameter), which in the past was often taken as zero for simplicity.

Predictors of burnout among correctional mental health professionals.

PubMed

Gallavan, Deanna B; Newman, Jody L

2013-02-01

This study focused on the experience of burnout among a sample of correctional mental health professionals. We examined the relationship of a linear combination of optimism, work family conflict, and attitudes toward prisoners with two dimensions derived from the Maslach Burnout Inventory and the Professional Quality of Life Scale. Initially, three subscales from the Maslach Burnout Inventory and two subscales from the Professional Quality of Life Scale were subjected to principal components analysis with oblimin rotation in order to identify underlying dimensions among the subscales. This procedure resulted in two components accounting for approximately 75% of the variance (r = -.27). The first component was labeled Negative Experience of Work because it seemed to tap the experience of being emotionally spent, detached, and socially avoidant. The second component was labeled Positive Experience of Work and seemed to tap a sense of competence, success, and satisfaction in one's work. Two multiple regression analyses were subsequently conducted, in which Negative Experience of Work and Positive Experience of Work, respectively, were predicted from a linear combination of optimism, work family conflict, and attitudes toward prisoners. In the first analysis, 44% of the variance in Negative Experience of Work was accounted for, with work family conflict and optimism accounting for the most variance. In the second analysis, 24% of the variance in Positive Experience of Work was accounted for, with optimism and attitudes toward prisoners accounting for the most variance.

Study of advanced techniques for determining the long-term performance of components

NASA Technical Reports Server (NTRS)

1972-01-01

A study was conducted of techniques having the capability of determining the performance and reliability of components for spacecraft liquid propulsion applications for long term missions. The study utilized two major approaches; improvement in the existing technology, and the evolution of new technology. The criteria established and methods evolved are applicable to valve components. Primary emphasis was placed on the propellants oxygen difluoride and diborane combination. The investigation included analysis, fabrication, and tests of experimental equipment to provide data and performance criteria.

Differentiation of Aurantii Fructus Immaturus from Poniciri Trifoliatae Fructus Immaturus using Flow- injection Mass spectrometric (FIMS) Metabolic Fingerprinting Method Combined with Chemometrics

PubMed Central

Zhao, Yang; Chang, Yuan-Shiun; Chen, Pei

2015-01-01

A flow-injection mass spectrometric metabolic fingerprinting method in combination with chemometrics was used to differentiate Aurantii Fructus Immaturus from its counterfeit Poniciri Trifoliatae Fructus Immaturus. Flow-injection mass spectrometric (FIMS) fingerprints of 9 Aurantii Fructus Immaturus samples and 12 Poniciri Trifoliatae Fructus Immaturus samples were acquired and analyzed using principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA). The authentic herbs were differentiated from their counterfeits easily. Eight characteristic components which were responsible for the difference between the samples were tentatively identified. Furthermore, three out of the eight components, naringin, hesperidin, and neohesperidin, were quantified. The results are useful to help identify the authenticity of Aurantii Fructus Immaturus. PMID:25622204

Fuel cell on-site integrated energy system parametric analysis of a residential complex

NASA Technical Reports Server (NTRS)

Simons, S. N.

1977-01-01

A parametric energy-use analysis was performed for a large apartment complex served by a fuel cell on-site integrated energy system (OS/IES). The variables parameterized include operating characteristics for four phosphoric acid fuel cells, eight OS/IES energy recovery systems, and four climatic locations. The annual fuel consumption for selected parametric combinations are presented and a breakeven economic analysis is presented for one parametric combination. The results show fuel cell electrical efficiency and system component choice have the greatest effect on annual fuel consumption; fuel cell thermal efficiency and geographic location have less of an effect.

Nano-enabled tribological thin film coatings: global patent scenario.

PubMed

Sivudu, Kurva S; Mahajan, Yashwant R; Joshi, Shrikant V

2014-01-01

The aim of this paper is to present current status and future prospects of nano-enabled tribological thin film coatings based on worldwide patent landscape analysis. The study also presents an overview of technological trends by carrying out state-of-the-art literature analysis, including survey of corporate websites. Nanostructured tribological coatings encompass a wide spectrum of nanoscale microstructures, including nanocrystalline, nanolayered, nano-multilayered, nanocomposite, nanogradient structures or their unique combinations, which are composed of single or multi-component phases. The distinct microstructural features of the coatings impart outstanding tribological properties combined with multifunctional attributes to the coated components. Their unique combination of remarkable properties make them ideal candidates for a wide range of applications in diverse fields such as cutting and metalworking tools, biomedical devices, automotive engine components, wear parts, hard disc drives etc. The patent landscape analysis has revealed that nano-enabled tribological thin film coatings have significant potential for commercial applications in view of the lion's share of corporate industry in patenting activity. The largest patent portfolio is held by Japan followed by USA, Germany, Sweden and China. The prominent players involved in this field are Mitsubishi Materials Corp., Sandvik Aktiebolag, Hitachi Ltd., Sumitomo Electric Industries Ltd., OC Oerlikon Corp., and so on. The outstanding potential of nanostructured thin film tribological coatings is yet to be fully unravelled and, therefore, immense opportunities are available in future for microstructurally engineered novel coatings to enhance their performance and functionality by many folds.

Joining X-Ray to Lensing: An Accurate Combined Analysis of MACS J0416.1-2403

NASA Astrophysics Data System (ADS)

Bonamigo, M.; Grillo, C.; Ettori, S.; Caminha, G. B.; Rosati, P.; Mercurio, A.; Annunziatella, M.; Balestra, I.; Lombardi, M.

2017-06-01

We present a novel approach for a combined analysis of X-ray and gravitational lensing data and apply this technique to the merging galaxy cluster MACS J0416.1-2403. The method exploits the information on the intracluster gas distribution that comes from a fit of the X-ray surface brightness and then includes the hot gas as a fixed mass component in the strong-lensing analysis. With our new technique, we can separate the collisional from the collision-less diffuse mass components, thus obtaining a more accurate reconstruction of the dark matter distribution in the core of a cluster. We introduce an analytical description of the X-ray emission coming from a set of dual pseudo-isothermal elliptical mass distributions, which can be directly used in most lensing softwares. By combining Chandra observations with Hubble Frontier Fields imaging and Multi Unit Spectroscopic Explorer spectroscopy in MACS J0416.1-2403, we measure a projected gas-to-total mass fraction of approximately 10% at 350 kpc from the cluster center. Compared to the results of a more traditional cluster mass model (diffuse halos plus member galaxies), we find a significant difference in the cumulative projected mass profile of the dark matter component and that the dark matter over total mass fraction is almost constant, out to more than 350 kpc. In the coming era of large surveys, these results show the need of multiprobe analyses for detailed dark matter studies in galaxy clusters.

Latent effects decision analysis

DOEpatents

Cooper, J Arlin [Albuquerque, NM; Werner, Paul W [Albuquerque, NM

2004-08-24

Latent effects on a system are broken down into components ranging from those far removed in time from the system under study (latent) to those which closely effect changes in the system. Each component is provided with weighted inputs either by a user or from outputs of other components. A non-linear mathematical process known as `soft aggregation` is performed on the inputs to each component to provide information relating to the component. This information is combined in decreasing order of latency to the system to provide a quantifiable measure of an attribute of a system (e.g., safety) or to test hypotheses (e.g., for forensic deduction or decisions about various system design options).

A photometric study of the eclipsing binary RX Hercules

NASA Technical Reports Server (NTRS)

Jeffreys, K. W.

1980-01-01

A new photoelectric light curve of RX Hercules, a binary system with similar components, has been analyzed using Wood's computer model. RX Her, using Popper's spectroscopic mass ratio of q = 0.8472, turned out to be composed of a dimmer AO component and a larger B9.5 component. This detached system, upon analysis of the residuals in secondary minimum, shows some asymmetry during ingress which then disappears just before secondary minimum. The eccentricity e = 0.022 determined in this study is a little larger than previously published values of e = 0.018. In combination with the spectroscopic analysis of Popper, and ubvy data of Olson and Hill and Hilditch new photometric elements for RX Her were found.

Probabilistic/Fracture-Mechanics Model For Service Life

NASA Technical Reports Server (NTRS)

Watkins, T., Jr.; Annis, C. G., Jr.

1991-01-01

Computer program makes probabilistic estimates of lifetime of engine and components thereof. Developed to fill need for more accurate life-assessment technique that avoids errors in estimated lives and provides for statistical assessment of levels of risk created by engineering decisions in designing system. Implements mathematical model combining techniques of statistics, fatigue, fracture mechanics, nondestructive analysis, life-cycle cost analysis, and management of engine parts. Used to investigate effects of such engine-component life-controlling parameters as return-to-service intervals, stresses, capabilities for nondestructive evaluation, and qualities of materials.

SCADA alarms processing for wind turbine component failure detection

NASA Astrophysics Data System (ADS)

Gonzalez, E.; Reder, M.; Melero, J. J.

2016-09-01

Wind turbine failure and downtime can often compromise the profitability of a wind farm due to their high impact on the operation and maintenance (O&M) costs. Early detection of failures can facilitate the changeover from corrective maintenance towards a predictive approach. This paper presents a cost-effective methodology to combine various alarm analysis techniques, using data from the Supervisory Control and Data Acquisition (SCADA) system, in order to detect component failures. The approach categorises the alarms according to a reviewed taxonomy, turning overwhelming data into valuable information to assess component status. Then, different alarms analysis techniques are applied for two purposes: the evaluation of the SCADA alarm system capability to detect failures, and the investigation of the relation between components faults being followed by failure occurrences in others. Various case studies are presented and discussed. The study highlights the relationship between faulty behaviour in different components and between failures and adverse environmental conditions.

Rapid detection of milk adulteration using intact protein flow injection mass spectrometric fingerprints combined with chemometrics.

PubMed

Du, Lijuan; Lu, Weiying; Cai, Zhenzhen Julia; Bao, Lei; Hartmann, Christoph; Gao, Boyan; Yu, Liangli Lucy

2018-02-01

Flow injection mass spectrometry (FIMS) combined with chemometrics was evaluated for rapidly detecting economically motivated adulteration (EMA) of milk. Twenty-two pure milk and thirty-five counterparts adulterated with soybean, pea, and whey protein isolates at 0.5, 1, 3, 5, and 10% (w/w) levels were analyzed. The principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), and support vector machine (SVM) classification models indicated that the adulterated milks could successfully be classified from the pure milks. FIMS combined with chemometrics might be an effective method to detect possible EMA in milk. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lifetime Reliability Prediction of Ceramic Structures Under Transient Thermomechanical Loads

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Jadaan, Osama J.; Gyekenyesi, John P.

2005-01-01

An analytical methodology is developed to predict the probability of survival (reliability) of ceramic components subjected to harsh thermomechanical loads that can vary with time (transient reliability analysis). This capability enables more accurate prediction of ceramic component integrity against fracture in situations such as turbine startup and shutdown, operational vibrations, atmospheric reentry, or other rapid heating or cooling situations (thermal shock). The transient reliability analysis methodology developed herein incorporates the following features: fast-fracture transient analysis (reliability analysis without slow crack growth, SCG); transient analysis with SCG (reliability analysis with time-dependent damage due to SCG); a computationally efficient algorithm to compute the reliability for components subjected to repeated transient loading (block loading); cyclic fatigue modeling using a combined SCG and Walker fatigue law; proof testing for transient loads; and Weibull and fatigue parameters that are allowed to vary with temperature or time. Component-to-component variation in strength (stochastic strength response) is accounted for with the Weibull distribution, and either the principle of independent action or the Batdorf theory is used to predict the effect of multiaxial stresses on reliability. The reliability analysis can be performed either as a function of the component surface (for surface-distributed flaws) or component volume (for volume-distributed flaws). The transient reliability analysis capability has been added to the NASA CARES/ Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code. CARES/Life was also updated to interface with commercially available finite element analysis software, such as ANSYS, when used to model the effects of transient load histories. Examples are provided to demonstrate the features of the methodology as implemented in the CARES/Life program.

Chemometric analysis of multisensor hyperspectral images of precipitated atmospheric particulate matter.

PubMed

Ofner, Johannes; Kamilli, Katharina A; Eitenberger, Elisabeth; Friedbacher, Gernot; Lendl, Bernhard; Held, Andreas; Lohninger, Hans

2015-09-15

The chemometric analysis of multisensor hyperspectral data allows a comprehensive image-based analysis of precipitated atmospheric particles. Atmospheric particulate matter was precipitated on aluminum foils and analyzed by Raman microspectroscopy and subsequently by electron microscopy and energy dispersive X-ray spectroscopy. All obtained images were of the same spot of an area of 100 × 100 μm(2). The two hyperspectral data sets and the high-resolution scanning electron microscope images were fused into a combined multisensor hyperspectral data set. This multisensor data cube was analyzed using principal component analysis, hierarchical cluster analysis, k-means clustering, and vertex component analysis. The detailed chemometric analysis of the multisensor data allowed an extensive chemical interpretation of the precipitated particles, and their structure and composition led to a comprehensive understanding of atmospheric particulate matter.

Univariate and multivariate molecular spectral analyses of lipid related molecular structural components in relation to nutrient profile in feed and food mixtures.

PubMed

Abeysekara, Saman; Damiran, Daalkhaijav; Yu, Peiqiang

2013-02-01

The objectives of this study were (i) to determine lipid related molecular structures components (functional groups) in feed combination of cereal grain (barley, Hordeum vulgare) and wheat (Triticum aestivum) based dried distillers grain solubles (wheat DDGSs) from bioethanol processing at five different combination ratios using univariate and multivariate molecular spectral analyses with infrared Fourier transform molecular spectroscopy, and (ii) to correlate lipid-related molecular-functional structure spectral profile to nutrient profiles. The spectral intensity of (i) CH(3) asymmetric, CH(2) asymmetric, CH(3) symmetric and CH(2) symmetric groups, (ii) unsaturation (CC) group, and (iii) carbonyl ester (CO) group were determined. Spectral differences of functional groups were detected by hierarchical cluster analysis (HCA) and principal components analysis (PCA). The results showed that the combination treatments significantly inflicted modifications (P<0.05) in nutrient profile and lipid related molecular spectral intensity (CH(2) asymmetric stretching peak height, CH(2) symmetric stretching peak height, ratio of CH(2) to CH(3) symmetric stretching peak intensity, and carbonyl peak area). Ratio of CH(2) to CH(3) symmetric stretching peak intensity, and carbonyl peak significantly correlated with nutrient profiles. Both PCA and HCA differentiated lipid-related spectrum. In conclusion, the changes of lipid molecular structure spectral profiles through feed combination could be detected using molecular spectroscopy. These changes were associated with nutrient profiles and functionality. Copyright © 2012 Elsevier B.V. All rights reserved.

Synergism between NF-kappa B inhibitor, celastrol, and XIAP inhibitor, embelin, in an acute myeloid leukemia cell line, HL-60.

PubMed

Pazhang, Yaghub; Jaliani, Hossein Zarei; Imani, Mehdi; Dariushnejad, Hassan

2016-01-01

Embelin and celastrol, inhibitors of XIAP and NF-κB proteins respectively, have been derived from natural sources and shown anti-tumor activities against different cancer cell lines. Some interactions have recently been discovered between XIAP and NF-κB pathways, but the effects of these inhibitors in combination have not been investigated yet. We have studied possible synergistic effects of embelin in combination with celastrol, in an acute myeloid leukemia model, HL-60 cell line. Cytotoxicity of embelin and celastrol, separately and in combination, was determined by MTT assay and flow cytometry. Chou-Talalay's method was used to assess the synergistic effect of two components. Immunocytochemistry and western blot analysis of the two tumor marker proteins. (survivin and COX-2) was also performed to investigate downstream effects of two components. Analysis of MTT assay and flow cytometry showed that there is a substantial synergistic effect in some affected fractions of drug-treated HL-60. cells, while in other affected fractions a mild synergism or additive effect was observed. Immunocytochemistry and western blot analysis revealed that the expression of survivin and COX-2 proteins was reduced in treated cells. Embelin and celastrol showed potent antitumor activity and synergistic effects in combination. Therefore targeting XIAP and NF-κB pathways simultaneously can be investigated in more detail to make use of embelin and celastrol as a combination therapy of cancer.

QUINCE System; State-of-the-Art Review

DTIC Science & Technology

1978-06-01

linguistic data base in terms of semantic feature set, interlingual transfer component, contrastive lexical/syntactic studies and contextual analysis ...and Syntactical Studies 3.3.1 Contrastlve Lexical Studies 3.3.2 Contrastlve Syntactic Studies 3.4 Contextual Analysis 3.4.1 Elided Subjects...and English, combined with contextual analysis of language- specific characteristics of Chinese ^re offered as the most promising solutions In this

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Calhoun, Vince D.

2013-01-01

Extraction of relevant features from multitask functional MRI (fMRI) data in order to identify potential biomarkers for disease, is an attractive goal. In this paper, we introduce a novel feature-based framework, which is sensitive and accurate in detecting group differences (e.g. controls vs. patients) by proposing three key ideas. First, we integrate two goal-directed techniques: coefficient-constrained independent component analysis (CC-ICA) and principal component analysis with reference (PCA-R), both of which improve sensitivity to group differences. Secondly, an automated artifact-removal method is developed for selecting components of interest derived from CC-ICA, with an average accuracy of 91%. Finally, we propose a strategy for optimal feature/component selection, aiming to identify optimal group-discriminative brain networks as well as the tasks within which these circuits are engaged. The group-discriminating performance is evaluated on 15 fMRI feature combinations (5 single features and 10 joint features) collected from 28 healthy control subjects and 25 schizophrenia patients. Results show that a feature from a sensorimotor task and a joint feature from a Sternberg working memory (probe) task and an auditory oddball (target) task are the top two feature combinations distinguishing groups. We identified three optimal features that best separate patients from controls, including brain networks consisting of temporal lobe, default mode and occipital lobe circuits, which when grouped together provide improved capability in classifying group membership. The proposed framework provides a general approach for selecting optimal brain networks which may serve as potential biomarkers of several brain diseases and thus has wide applicability in the neuroimaging research community. PMID:19457398

The quality of social relationships in ravens

PubMed Central

Fraser, Orlaith N.; Bugnyar, Thomas

2015-01-01

The quality of a social relationship represents the history of past social interactions between two individuals, from which the nature and outcome of future interactions can be predicted. Current theory predicts that relationship quality comprises three separate components, its value, compatibility and security. This study is the first to investigate the components of relationship quality in a large-brained bird. Following methods recently used to obtain quantitative measures of each relationship quality component in chimpanzees, Pan troglodytes, we entered data on seven behavioural variables from a group of 11 ravens, Corvus corax, into a principal components analysis. The characteristics of the extracted components matched those predicted for value, compatibility and security, and were labelled as such. When the effects of kinship and sex combination on each relationship quality component were analysed, we found that kin had more valuable relationships, whereas females had less secure and compatible relationships, although the effect of sex combination on compatibility only applied to nonkin. These patterns are consistent with what little knowledge we have of raven relationships from aviary studies and show that the components of relationship quality in ravens may indeed be analogous to those in chimpanzees. PMID:25821236

Blood hyperviscosity identification with reflective spectroscopy of tongue tip based on principal component analysis combining artificial neural network.

PubMed

Liu, Ming; Zhao, Jing; Lu, XiaoZuo; Li, Gang; Wu, Taixia; Zhang, LiFu

2018-05-10

With spectral methods, noninvasive determination of blood hyperviscosity in vivo is very potential and meaningful in clinical diagnosis. In this study, 67 male subjects (41 health, and 26 hyperviscosity according to blood sample analysis results) participate. Reflectance spectra of subjects' tongue tips is measured, and a classification method bases on principal component analysis combined with artificial neural network model is built to identify hyperviscosity. Hold-out and Leave-one-out methods are used to avoid significant bias and lessen overfitting problem, which are widely accepted in the model validation. To measure the performance of the classification, sensitivity, specificity, accuracy and F-measure are calculated, respectively. The accuracies with 100 times Hold-out method and 67 times Leave-one-out method are 88.05% and 97.01%, respectively. Experimental results indicate that the built classification model has certain practical value and proves the feasibility of using spectroscopy to identify hyperviscosity by noninvasive determination.

Insight into the heavy metal binding potential of dissolved organic matter in MSW leachate using EEM quenching combined with PARAFAC analysis.

PubMed

Wu, Jun; Zhang, Hua; He, Pin-Jing; Shao, Li-Ming

2011-02-01

Dissolved organic matter (DOM) plays an important role in heavy metal migration from municipal solid waste (MSW) to aquatic environments via the leachate pathway. In this study, fluorescence excitation-emission matrix (EEM) quenching combined with parallel factor (PARAFAC) analysis was adopted to characterize the binding properties of four heavy metals (Cu, Pb, Zn and Cd) and DOM in MSW leachate. Nine leachate samples were collected from various stages of MSW management, including collection, transportation, incineration, landfill and subsequent leachate treatment. Three humic-like components and one protein-like component were identified in the MSW-derived DOM by PARAFAC. Significant differences in quenching effects were observed between components and metal ions, and a relatively consistent trend in metal quenching curves was observed among various leachate samples. Among the four heavy metals, Cu(II) titration led to fluorescence quenching of all four PARAFAC-derived components. Additionally, strong quenching effects were only observed in protein-like and fulvic acid (FA)-like components with the addition of Pb(II), which suggested that these fractions are mainly responsible for Pb(II) binding in MSW-derived DOM. Moreover, the significant quenching effects of the FA-like component by the four heavy metals revealed that the FA-like fraction in MSW-derived DOM plays an important role in heavy metal speciation; therefore, it may be useful as an indicator to assess the potential ability of heavy metal binding and migration. © 2010 Elsevier Ltd. All rights reserved.

Visuomotor coordination and cortical connectivity of modular motor learning.

PubMed

Burgos, Pablo I; Mariman, Juan J; Makeig, Scott; Rivera-Lillo, Gonzalo; Maldonado, Pedro E

2018-05-15

The ability to transfer sensorimotor skill components to new actions and the capacity to use skill components from whole actions are characteristic of the adaptability of the human sensorimotor system. However, behavioral evidence suggests complex limitations for transfer after combined or modular learning of motor adaptations. Also, to date, only behavioral analysis of the consequences of the modular learning has been reported, with little understanding of the sensorimotor mechanisms of control and the interaction between cortical areas. We programmed a video game with distorted kinematic and dynamic features to test the ability to combine sensorimotor skill components learned modularly (composition) and the capacity to use separate sensorimotor skill components learned in combination (decomposition). We examined motor performance, eye-hand coordination, and EEG connectivity. When tested for integrated learning, we found that combined practice initially performed better than separated practice, but differences disappeared after integrated practice. Separate learning promotes fewer anticipatory control mechanisms (depending more on feedback control), evidenced in a lower gaze leading behavior and in higher connectivity between visual and premotor domains, in comparison with the combined practice. The sensorimotor system can acquire motor modules in a separated or integrated manner. However, the system appears to require integrated practice to coordinate the adaptations with the skill learning and the networks involved in the integrated behavior. This integration seems to be related to the acquisition of anticipatory mechanism of control and with the decrement of feedback control. © 2018 Wiley Periodicals, Inc.

Characterizing fluorescent dissolved organic matter in a membrane bioreactor via excitation-emission matrix combined with parallel factor analysis.

PubMed

Maqbool, Tahir; Quang, Viet Ly; Cho, Jinwoo; Hur, Jin

2016-06-01

In this study, we successfully tracked the dynamic changes in different constitutes of bound extracellular polymeric substances (bEPS), soluble microbial products (SMP), and permeate during the operation of bench scale membrane bioreactors (MBRs) via fluorescence excitation-emission matrix (EEM) combined with parallel factor analysis (PARAFAC). Three fluorescent groups were identified, including two protein-like (tryptophan-like C1 and tyrosine-like C2) and one microbial humic-like components (C3). In bEPS, protein-like components were consistently more dominant than C3 during the MBR operation, while their relative abundance in SMP depended on aeration intensities. C1 of bEPS exhibited a linear correlation (R(2)=0.738; p<0.01) with bEPS amounts in sludge, and C2 was closely related to the stability of sludge. The protein-like components were more greatly responsible for membrane fouling. Our study suggests that EEM-PARAFAC can be a promising monitoring tool to provide further insight into process evaluation and membrane fouling during MBR operation. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Resolving excitation emission matrix spectroscopy of estuarine CDOM with parallel factor analysis and its application in organic pollution monitoring].

PubMed

Guo, Wei-Dong; Huang, Jian-Ping; Hong, Hua-Sheng; Xu, Jing; Deng, Xun

2010-06-01

The distribution and estuarine behavior of fluorescent components of chromophoric dissolved organic matter (CDOM) from Jiulong Estuary were determined by fluorescence excitation emission matrix spectroscopy (EEMs) combined with parallel factor analysis (PARAFAC). The feasibility of these components as tracers for organic pollution in estuarine environments was also evaluated. Four separate fluorescent components were identified by PARAFAC, including three humic-like components (C1: 240, 310/382 nm; C2: 230, 250, 340/422 nm; C4: 260, 390/482 nm) and one protein-like components (C3: 225, 275/342 nm). These results indicated that UV humic-like peak A area designated by traditional "peak-picking method" was not a single peak but actually a combination of several fluorescent components, and it also had inherent links to so-called marine humic-like peak M or terrestrial humic-like peak C. Component C2 which include peak M decreased with increase of salinity in Jiulong Estuary, demonstrating that peak M can not be thought as the specific indicator of the "marine" humic-like component. Two humic-like components C1 and C2 showed additional behavior in the turbidity maximum region (salinity < 6) and then conservative mixing behavior for the rest estuarine region, while humic-like components C4 showed conservative mixing behavior for the whole estuarine region. However, the protein-like component C3 showed nonconservative mixing behavior, suggesting it had autochthonous estuarine origin. EEMs-PARAFAC can provide fluorescent fingerprint to differentiate the DOM features for three tributaries of Jiulong River. The observed linear relationships between humic-like components and absorption coefficient a (280) with chemical oxygen demand (COD) and biological oxygen demand (BOD5) suggest that the optical properties of CDOM may provide a fast in-situ way to monitor the variation of the degree of organic pollution in estuarine environments.

Tracking variations in fluorescent-dissolved organic matter in an aerobic submerged membrane bioreactor using excitation-emission matrix spectra combined with parallel factor analysis.

PubMed

Hur, Jin; Shin, Jaewon; Kang, Minsun; Cho, Jinwoo

2014-08-01

In this study, the variations in the fluorescent components of dissolved organic matter (DOM) were tracked for an aerobic submerged membrane bioreactor (MBR) at three different operation stages (cake layer formation, condensation, and after cleaning). The fluorescent DOM was characterized using excitation-emission matrix (EEM) spectroscopy combined with parallel factor analysis (PARAFAC). Non-aromatic carbon structures appear to be actively involved in the membrane fouling for the cake layer formation stage as revealed by much higher UV-absorbing DOM per organic carbon found in the effluent versus those inside the reactor. Four fluorescent components were successfully identified from the reactor and the effluent DOMs by EEM-PARAFAC modeling. Among those in the reactor, microbial humic-like fluorescence was the most abundant component at the cake layer formation stage and tryptophan-like fluorescence at the condensation stage. In contrast to the reactor, relatively similar composition of the PARAFAC components was exhibited for the effluent at all three stages. Tryptophan-like fluorescence displayed the largest difference between the reactor and the effluent, suggesting that this component could be a good tracer for membrane fouling. It appears that the fluorescent DOM was involved in membrane fouling by cake layer formation rather than by internal pore adsorption because its difference between the reactor and the effluent was the highest among all the four components, even after the membrane cleaning. Our study provided an insight into the fate and the behavior fluorescent DOM components for an MBR system, which could be an indicator of the membrane fouling.

NIR monitoring of in-service wood structures

Treesearch

Michela Zanetti; Timothy G. Rials; Douglas Rammer

2005-01-01

Near infrared spectroscopy (NIRS) was used to study a set of Southern Yellow Pine boards exposed to natural weathering for different periods of exposure time. This non-destructive spectroscopic technique is a very powerful tool to predict the weathering of wood when used in combination with multivariate analysis (Principal Component Analysis, PCA, and Projection to...

AlleleCoder: a PERL script for coding codominant polymorphism data for PCA analysis

USDA-ARS?s Scientific Manuscript database

A useful biological interpretation of diploid heterozygotes is in terms of the dose of the common allele (0, 1 or 2 copies). We have developed a PERL script that converts FASTA files into coded spreadsheets suitable for Principal Component Analysis (PCA). In combination with R and R Commander, two- ...

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG.

PubMed

Bai, Ou; Lin, Peter; Vorbach, Sherry; Li, Jiang; Furlani, Steve; Hallett, Mark

2007-12-01

To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG). Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD); temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT); pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention. Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could be the basis for a potential brain-computer interface based on human natural movement, which might reduce the requirement of long-term training. Effective combinations of computational methods can classify human movement intention from single trial EEG with reasonable accuracy.

Quality Assessment of Kumu Injection, a Traditional Chinese Medicine Preparation, Using HPLC Combined with Chemometric Methods and Qualitative and Quantitative Analysis of Multiple Alkaloids by Single Marker.

PubMed

Wang, Ning; Li, Zhi-Yong; Zheng, Xiao-Li; Li, Qiao; Yang, Xin; Xu, Hui

2018-04-09

Kumu injection (KMI) is a common-used traditional Chinese medicine (TCM) preparation made from Picrasma quassioides (D. Don) Benn. rich in alkaloids. An innovative technique for quality assessment of KMI was developed using high performance liquid chromatography (HPLC) combined with chemometric methods and qualitative and quantitative analysis of multi-components by single marker (QAMS). Nigakinone (PQ-6, 5-hydroxy-4-methoxycanthin-6-one), one of the most abundant alkaloids responsible for the major pharmacological activities of Kumu, was used as a reference substance. Six alkaloids in KMI were quantified, including 6-hydroxy- β -carboline-1-carboxylic acid (PQ-1), 4,5-dimethoxycanthin-6-one (PQ-2), β -carboline-1-carboxylic acid (PQ-3), β -carboline-1-propanoic acid (PQ-4), 3-methylcanthin-5,6-dione (PQ-5), and PQ-6. Based on the outcomes of twenty batches of KMI samples, the contents of six alkaloids were used for further chemometric analysis. By hierarchical cluster analysis (HCA), radar plots, and principal component analysis (PCA), all the KMI samples could be categorized into three groups, which were closely related to production date and indicated the crucial influence of herbal raw material on end products of KMI. QAMS combined with chemometric analysis could accurately measure and clearly distinguish the different quality samples of KMI. Hence, QAMS is a feasible and promising method for the quality control of KMI.

Exploring Geographical Differentiation of the Hoelen Medicinal Mushroom, Wolfiporia extensa (Agaricomycetes), Using Fourier-Transform Infrared Spectroscopy Combined with Multivariate Analysis.

PubMed

Li, Yan; Zhang, Ji; Zhao, Yanli; Liu, Honggao; Wang, Yuanzhong; Jin, Hang

2016-01-01

In this study the geographical differentiation of dried sclerotia of the medicinal mushroom Wolfiporia extensa, obtained from different regions in Yunnan Province, China, was explored using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate data analysis. The FT-IR spectra of 97 samples were obtained for wave numbers ranging from 4000 to 400 cm-1. Then, the fingerprint region of 1800-600 cm-1 of the FT-IR spectrum, rather than the full spectrum, was analyzed. Different pretreatments were applied on the spectra, and a discriminant analysis model based on the Mahalanobis distance was developed to select an optimal pretreatment combination. Two unsupervised pattern recognition procedures- principal component analysis and hierarchical cluster analysis-were applied to enhance the authenticity of discrimination of the specimens. The results showed that excellent classification could be obtained after optimizing spectral pretreatment. The tested samples were successfully discriminated according to their geographical locations. The chemical properties of dried sclerotia of W. extensa were clearly dependent on the mushroom's geographical origins. Furthermore, an interesting finding implied that the elevations of collection areas may have effects on the chemical components of wild W. extensa sclerotia. Overall, this study highlights the feasibility of FT-IR spectroscopy combined with multivariate data analysis in particular for exploring the distinction of different regional W. extensa sclerotia samples. This research could also serve as a basis for the exploitation and utilization of medicinal mushrooms.

Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Guo, Taomei; Xu, Yaqin; Zhao, Xiaojie; Yao, Li

2007-03-01

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.

Combined Raman and autofluorescence ex vivo diagnostics of skin cancer in near-infrared and visible regions

NASA Astrophysics Data System (ADS)

Bratchenko, Ivan A.; Artemyev, Dmitry N.; Myakinin, Oleg O.; Khristoforova, Yulia A.; Moryatov, Alexander A.; Kozlov, Sergey V.; Zakharov, Valery P.

2017-02-01

The differentiation of skin melanomas and basal cell carcinomas (BCCs) was demonstrated based on combined analysis of Raman and autofluorescence spectra stimulated by visible and NIR lasers. It was ex vivo tested on 39 melanomas and 40 BCCs. Six spectroscopic criteria utilizing information about alteration of melanin, porphyrins, flavins, lipids, and collagen content in tumor with a comparison to healthy skin were proposed. The measured correlation between the proposed criteria makes it possible to define weakly correlated criteria groups for discriminant analysis and principal components analysis application. It was shown that the accuracy of cancerous tissues classification reaches 97.3% for a combined 6-criteria multimodal algorithm, while the accuracy determined separately for each modality does not exceed 79%. The combined 6-D method is a rapid and reliable tool for malignant skin detection and classification.

The Use of Probabilistic Methods to Evaluate the Systems Impact of Component Design Improvements on Large Turbofan Engines

NASA Technical Reports Server (NTRS)

Packard, Michael H.

2002-01-01

Probabilistic Structural Analysis (PSA) is now commonly used for predicting the distribution of time/cycles to failure of turbine blades and other engine components. These distributions are typically based on fatigue/fracture and creep failure modes of these components. Additionally, reliability analysis is used for taking test data related to particular failure modes and calculating failure rate distributions of electronic and electromechanical components. How can these individual failure time distributions of structural, electronic and electromechanical component failure modes be effectively combined into a top level model for overall system evaluation of component upgrades, changes in maintenance intervals, or line replaceable unit (LRU) redesign? This paper shows an example of how various probabilistic failure predictions for turbine engine components can be evaluated and combined to show their effect on overall engine performance. A generic model of a turbofan engine was modeled using various Probabilistic Risk Assessment (PRA) tools (Quantitative Risk Assessment Software (QRAS) etc.). Hypothetical PSA results for a number of structural components along with mitigation factors that would restrict the failure mode from propagating to a Loss of Mission (LOM) failure were used in the models. The output of this program includes an overall failure distribution for LOM of the system. The rank and contribution to the overall Mission Success (MS) is also given for each failure mode and each subsystem. This application methodology demonstrates the effectiveness of PRA for assessing the performance of large turbine engines. Additionally, the effects of system changes and upgrades, the application of different maintenance intervals, inclusion of new sensor detection of faults and other upgrades were evaluated in determining overall turbine engine reliability.

Composite Load Spectra for Select Space Propulsion Structural Components

NASA Technical Reports Server (NTRS)

Ho, Hing W.; Newell, James F.

1994-01-01

Generic load models are described with multiple levels of progressive sophistication to simulate the composite (combined) load spectra (CLS) that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades and liquid oxygen (LOX) posts. These generic (coupled) models combine the deterministic models for composite load dynamic, acoustic, high-pressure and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients are then determined using advanced probabilistic simulation methods with and without strategically selected experimental data. The entire simulation process is included in a CLS computer code. Applications of the computer code to various components in conjunction with the PSAM (Probabilistic Structural Analysis Method) to perform probabilistic load evaluation and life prediction evaluations are also described to illustrate the effectiveness of the coupled model approach.

Application of third molar development and eruption models in estimating dental age in Malay sub-adults.

PubMed

Mohd Yusof, Mohd Yusmiaidil Putera; Cauwels, Rita; Deschepper, Ellen; Martens, Luc

2015-08-01

The third molar development (TMD) has been widely utilized as one of the radiographic method for dental age estimation. By using the same radiograph of the same individual, third molar eruption (TME) information can be incorporated to the TMD regression model. This study aims to evaluate the performance of dental age estimation in individual method models and the combined model (TMD and TME) based on the classic regressions of multiple linear and principal component analysis. A sample of 705 digital panoramic radiographs of Malay sub-adults aged between 14.1 and 23.8 years was collected. The techniques described by Gleiser and Hunt (modified by Kohler) and Olze were employed to stage the TMD and TME, respectively. The data was divided to develop three respective models based on the two regressions of multiple linear and principal component analysis. The trained models were then validated on the test sample and the accuracy of age prediction was compared between each model. The coefficient of determination (R²) and root mean square error (RMSE) were calculated. In both genders, adjusted R² yielded an increment in the linear regressions of combined model as compared to the individual models. The overall decrease in RMSE was detected in combined model as compared to TMD (0.03-0.06) and TME (0.2-0.8). In principal component regression, low value of adjusted R(2) and high RMSE except in male were exhibited in combined model. Dental age estimation is better predicted using combined model in multiple linear regression models. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Characterization of extracellular polymeric substances in biofilms under long-term exposure to ciprofloxacin antibiotic using fluorescence excitation-emission matrix and parallel factor analysis.

PubMed

Gu, Chaochao; Gao, Pin; Yang, Fan; An, Dongxuan; Munir, Mariya; Jia, Hanzhong; Xue, Gang; Ma, Chunyan

2017-05-01

The presence of antibiotic residues in the environment has been regarded as an emerging concern due to their potential adverse environmental consequences such as antibiotic resistance. However, the interaction between antibiotics and extracellular polymeric substances (EPSs) of biofilms in wastewater treatment systems is not entirely clear. In this study, the effect of ciprofloxacin (CIP) antibiotic on biofilm EPS matrix was investigated and characterized using fluorescence excitation-emission matrix (EEM) and parallel factor (PARAFAC) analysis. Physicochemical analysis showed that the proteins were the major EPS fraction, and their contents increased gradually with an increase in CIP concentration (0-300 μg/L). Based on the characterization of biofilm tightly bound EPS (TB-EPS) by EEM, three fluorescent components were identified by PARAFAC analysis. Component C1 was associated with protein-like substances, and components C2 and C3 belonged to humic-like substances. Component C1 exhibited an increasing trend as the CIP addition increased. Pearson's correlation results showed that CIP correlated significantly with the protein contents and component C1, while strong correlations were also found among UV 254 , dissolved organic carbon, humic acids, and component C3. A combined use of EEM-PARAFAC analysis and chemical measurements was demonstrated as a favorable approach for the characterization of variations in biofilm EPS in the presence of CIP antibiotic.

An approach for evaluating the respiratory irritation of mixtures: application to metalworking fluids.

PubMed

Schaper, M M; Detwiler-Okabayashi, K A

1995-01-01

Recently, the sensory and pulmonary irritating properties of ten metalworking fluids (MWF) were assessed using a mouse bioassay. Relative potency of the MWFs was estimated, but it was not possible to identify the component(s) responsible for the the respiratory irritation induced by each MWF. One of the ten fluids, MWF "ET", produced sensory and pulmonary irritation in mice, and it was of moderate potency in comparison to the other nine MWFs. MWF "E" had three major components: tall oil fatty acids (TOFA), sodium sulfonate (SA), and paraffinic oil (PO). In the present study, the sensory and pulmonary irritating properties of these individual components of MWF "E" were evaluated. Mixtures of the three components were also prepared and similarly evaluated. This analysis revealed that the sensory irritation from MWF "E" was largely due to TOFA, whereas SA produced the pulmonary irritation observed with MWF "E". Both TOFA and SA were more potent irritants than was MWF "E", and the potency of TOFA and/or SA was diminished through combination with PO. There was no evidence of synergism of the components when combined to form MWF "E". This approach for identifying the biologically "active" component(s) in a mixture should be useful for other MWFs. Furthermore, the approach should be easily adapted for other applications involving concerns with mixtures.

Analysis of biodiesel and biodiesel-petrodiesel blends by high performance thin layer chromatography combined with easy ambient sonic-spray ionization mass spectrometry.

PubMed

Eberlin, Livia S; Abdelnur, Patricia V; Passero, Alan; de Sa, Gilberto F; Daroda, Romeu J; de Souza, Vanderlea; Eberlin, Marcos N

2009-08-01

High performance thin layer chromatography (HPTLC) combined with on-spot detection and characterization via easy ambient sonic-spray ionization mass spectrometry (EASI-MS) is applied to the analysis of biodiesel (B100) and biodiesel-petrodiesel blends (BX). HPTLC provides chromatographic resolution of major components whereas EASI-MS allows on-spot characterization performed directly on the HPTLC surface at ambient conditions. Constituents (M) are detected by EASI-MS in a one component-one ion fashion as either [M + Na](+) or [M + H](+). For both B100 and BX samples, typical profiles of fatty acid methyl esters (FAME) detected as [FAME + Na](+) ions allow biodiesel typification. The spectrum of the petrodiesel spot displays a homologous series of protonated alkyl pyridines which are characteristic for petrofuels (natural markers). The spectrum for residual or admixture oil spots is characterized by sodiated triglycerides [TAG + Na](+). The application of HPTLC to analyze B100 and BX samples and its combination with EASI-MS for on-spot characterization and quality control is demonstrated.

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Determination of butter adulteration with margarine using Raman spectroscopy.

PubMed

Uysal, Reyhan Selin; Boyaci, Ismail Hakki; Genis, Hüseyin Efe; Tamer, Ugur

2013-12-15

In this study, adulteration of butter with margarine was analysed using Raman spectroscopy combined with chemometric methods (principal component analysis (PCA), principal component regression (PCR), partial least squares (PLS)) and artificial neural networks (ANNs). Different butter and margarine samples were mixed at various concentrations ranging from 0% to 100% w/w. PCA analysis was applied for the classification of butters, margarines and mixtures. PCR, PLS and ANN were used for the detection of adulteration ratios of butter. Models were created using a calibration data set and developed models were evaluated using a validation data set. The coefficient of determination (R(2)) values between actual and predicted values obtained for PCR, PLS and ANN for the validation data set were 0.968, 0.987 and 0.978, respectively. In conclusion, a combination of Raman spectroscopy with chemometrics and ANN methods can be applied for testing butter adulteration. Copyright © 2013 Elsevier Ltd. All rights reserved.

[HPLC fingerprint of flavonoids in Sophora flavescens and determination of five components].

PubMed

Ma, Hong-Yan; Zhou, Wan-Shan; Chu, Fu-Jiang; Wang, Dong; Liang, Sheng-Wang; Li, Shao

2013-08-01

A simple and reliable method of high-performance liquid chromatography with photodiode array detection (HPLC-DAD) was developed to evaluate the quality of a traditional Chinese medicine Sophora flavescens through establishing chromatographic fingerprint and simultaneous determination of five flavonoids, including trifolirhizin, maackiain, kushenol I, kurarinone and sophoraflavanone G. The optimal conditions of separation and detection were achieved on an ULTIMATE XB-C18 column (4.6 mm x 250 mm, 5 microm) with a gradient of acetonitrile and water, detected at 295 nm. In the chromatographic fingerprint, 13 peaks were selected as the characteristic peaks to assess the similarities of different samples collected from different origins in China according to similarity evaluation for chromatographic fingerprint of traditional chinese medicine (2004AB) and principal component analysis (PCA) were used in data analysis. There were significant differences in the fingerprint chromatograms between S. flavescens and S. tonkinensis. Principal component analysis showed that kurarinone and sophoraflavanone G were the most important component. In quantitative analysis, the five components showed good regression (R > 0.999) with linear ranges, and their recoveries were in the range of 96.3% - 102.3%. This study indicated that the combination of quantitative and chromatographic fingerprint analysis can be readily utilized as a quality control method for S. flavescens and its related traditional Chinese medicinal preparations.

Chemical information obtained from Auger depth profiles by means of advanced factor analysis (MLCFA)

NASA Astrophysics Data System (ADS)

De Volder, P.; Hoogewijs, R.; De Gryse, R.; Fiermans, L.; Vennik, J.

1993-01-01

The advanced multivariate statistical technique "maximum likelihood common factor analysis (MLCFA)" is shown to be superior to "principal component analysis (PCA)" for decomposing overlapping peaks into their individual component spectra of which neither the number of components nor the peak shape of the component spectra is known. An examination of the maximum resolving power of both techniques, MLCFA and PCA, by means of artificially created series of multicomponent spectra confirms this finding unambiguously. Substantial progress in the use of AES as a chemical-analysis technique is accomplished through the implementation of MLCFA. Chemical information from Auger depth profiles is extracted by investigating the variation of the line shape of the Auger signal as a function of the changing chemical state of the element. In particular, MLCFA combined with Auger depth profiling has been applied to problems related to steelcord-rubber tyre adhesion. MLCFA allows one to elucidate the precise nature of the interfacial layer of reaction products between natural rubber vulcanized on a thin brass layer. This study reveals many interesting chemical aspects of the oxi-sulfidation of brass undetectable with classical AES.

Simplified Phased-Mission System Analysis for Systems with Independent Component Repairs

NASA Technical Reports Server (NTRS)

Somani, Arun K.

1996-01-01

Accurate analysis of reliability of system requires that it accounts for all major variations in system's operation. Most reliability analyses assume that the system configuration, success criteria, and component behavior remain the same. However, multiple phases are natural. We present a new computationally efficient technique for analysis of phased-mission systems where the operational states of a system can be described by combinations of components states (such as fault trees or assertions). Moreover, individual components may be repaired, if failed, as part of system operation but repairs are independent of the system state. For repairable systems Markov analysis techniques are used but they suffer from state space explosion. That limits the size of system that can be analyzed and it is expensive in computation. We avoid the state space explosion. The phase algebra is used to account for the effects of variable configurations, repairs, and success criteria from phase to phase. Our technique yields exact (as opposed to approximate) results. We demonstrate our technique by means of several examples and present numerical results to show the effects of phases and repairs on the system reliability/availability.

[Applications of three-dimensional fluorescence spectrum of dissolved organic matter to identification of red tide algae].

PubMed

Lü, Gui-Cai; Zhao, Wei-Hong; Wang, Jiang-Tao

2011-01-01

The identification techniques for 10 species of red tide algae often found in the coastal areas of China were developed by combining the three-dimensional fluorescence spectra of fluorescence dissolved organic matter (FDOM) from the cultured red tide algae with principal component analysis. Based on the results of principal component analysis, the first principal component loading spectrum of three-dimensional fluorescence spectrum was chosen as the identification characteristic spectrum for red tide algae, and the phytoplankton fluorescence characteristic spectrum band was established. Then the 10 algae species were tested using Bayesian discriminant analysis with a correct identification rate of more than 92% for Pyrrophyta on the level of species, and that of more than 75% for Bacillariophyta on the level of genus in which the correct identification rates were more than 90% for the phaeodactylum and chaetoceros. The results showed that the identification techniques for 10 species of red tide algae based on the three-dimensional fluorescence spectra of FDOM from the cultured red tide algae and principal component analysis could work well.

[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

PubMed

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

Understanding deformation mechanisms during powder compaction using principal component analysis of compression data.

PubMed

Roopwani, Rahul; Buckner, Ira S

2011-10-14

Principal component analysis (PCA) was applied to pharmaceutical powder compaction. A solid fraction parameter (SF(c/d)) and a mechanical work parameter (W(c/d)) representing irreversible compression behavior were determined as functions of applied load. Multivariate analysis of the compression data was carried out using PCA. The first principal component (PC1) showed loadings for the solid fraction and work values that agreed with changes in the relative significance of plastic deformation to consolidation at different pressures. The PC1 scores showed the same rank order as the relative plasticity ranking derived from the literature for common pharmaceutical materials. The utility of PC1 in understanding deformation was extended to binary mixtures using a subset of the original materials. Combinations of brittle and plastic materials were characterized using the PCA method. The relationships between PC1 scores and the weight fractions of the mixtures were typically linear showing ideal mixing in their deformation behaviors. The mixture consisting of two plastic materials was the only combination to show a consistent positive deviation from ideality. The application of PCA to solid fraction and mechanical work data appears to be an effective means of predicting deformation behavior during compaction of simple powder mixtures. Copyright © 2011 Elsevier B.V. All rights reserved.

Quantitative analysis of detailed lignin monomer composition by pyrolysis-gas chromatography combined with preliminary acetylation of the samples.

PubMed

Sonoda, T; Ona, T; Yokoi, H; Ishida, Y; Ohtani, H; Tsuge, S

2001-11-15

Detailed quantitative analysis of lignin monomer composition comprising p-coumaryl, coniferyl, and sinapyl alcohol and p-coumaraldehyde, coniferaldehyde, and sinapaldehyde in plant has not been studied from every point mainly because of artifact formation during the lignin isolation procedure, partial loss of the lignin components inherent in the chemical degradative methods, and difficulty in the explanation of the complex spectra generally observed for the lignin components. Here we propose a new method to quantify lignin monomer composition in detail by pyrolysis-gas chromatography (Py-GC) using acetylated lignin samples. The lignin acetylation procedure would contribute to prevent secondary formation of cinnamaldehydes from the corresponding alcohol forms during pyrolysis, which are otherwise unavoidable in conventional Py-GC process to some extent. On the basis of the characteristic peaks on the pyrograms of the acetylated sample, lignin monomer compositions in various dehydrogenative polymers (DHP) as lignin model compounds were determined, taking even minor components such as cinnamaldehydes into consideration. The observed compositions by Py-GC were in good agreement with the supplied lignin monomer contents on DHP synthesis. The new Py-GC method combined with sample preacetylation allowed us an accurate quantitative analysis of detailed lignin monomer composition using a microgram order of extractive-free plant samples.

EFICAz2: enzyme function inference by a combined approach enhanced by machine learning.

PubMed

Arakaki, Adrian K; Huang, Ying; Skolnick, Jeffrey

2009-04-13

We previously developed EFICAz, an enzyme function inference approach that combines predictions from non-completely overlapping component methods. Two of the four components in the original EFICAz are based on the detection of functionally discriminating residues (FDRs). FDRs distinguish between member of an enzyme family that are homofunctional (classified under the EC number of interest) or heterofunctional (annotated with another EC number or lacking enzymatic activity). Each of the two FDR-based components is associated to one of two specific kinds of enzyme families. EFICAz exhibits high precision performance, except when the maximal test to training sequence identity (MTTSI) is lower than 30%. To improve EFICAz's performance in this regime, we: i) increased the number of predictive components and ii) took advantage of consensual information from the different components to make the final EC number assignment. We have developed two new EFICAz components, analogs to the two FDR-based components, where the discrimination between homo and heterofunctional members is based on the evaluation, via Support Vector Machine models, of all the aligned positions between the query sequence and the multiple sequence alignments associated to the enzyme families. Benchmark results indicate that: i) the new SVM-based components outperform their FDR-based counterparts, and ii) both SVM-based and FDR-based components generate unique predictions. We developed classification tree models to optimally combine the results from the six EFICAz components into a final EC number prediction. The new implementation of our approach, EFICAz2, exhibits a highly improved prediction precision at MTTSI < 30% compared to the original EFICAz, with only a slight decrease in prediction recall. A comparative analysis of enzyme function annotation of the human proteome by EFICAz2 and KEGG shows that: i) when both sources make EC number assignments for the same protein sequence, the assignments tend to be consistent and ii) EFICAz2 generates considerably more unique assignments than KEGG. Performance benchmarks and the comparison with KEGG demonstrate that EFICAz2 is a powerful and precise tool for enzyme function annotation, with multiple applications in genome analysis and metabolic pathway reconstruction. The EFICAz2 web service is available at: http://cssb.biology.gatech.edu/skolnick/webservice/EFICAz2/index.html.

On the potential of seismic rotational motion measurements for extraterrestrial seismology

NASA Astrophysics Data System (ADS)

Schmelzbach, Cedric; Sollberger, David; Khan, Amir; Greenhalgh, Stewart; Van Renterghem, Cederic; Robertsson, Johan

2017-04-01

Classically, seismological recordings consist of measurements of translational ground motion only. However, in addition to three vector components of translation there are three components of rotation to consider, leading to six degrees of freedom. Of particular interest is thereby the fact that measuring rotational motion means isolating shear (S) waves. Recording the rotational motion requires dedicated rotational sensors. Alternatively, since the rotational motion is given by the curl of the vectorial displacements, the rotational motion around the two horizontal axes can be computed from the horizontal spatial gradients of vertical translational recordings if standard translational seismometers are placed in an areal array at the free surface. This follows from the zero stress free surface condition. Combining rotational and translational motion measurements opens up new ways of analyzing seismic data, such as facilitating much improved arrival identification and wavefield separation (e.g., P-/S-wave separation), and local slowness (arrival direction and velocity) determination. Such combined measurements maximize the seismic information content that a single six-component station or a small station array can provide, and are of particular interest for sparse or single-station measurements such as in extraterrestrial seismology. We demonstrate the value of the analysis of combined translational and rotational recordings by re-evaluating data from the Apollo 17 lunar seismic profiling experiment (LSPE). The LSPE setup consisted of four vertical-component geophones arranged in a star-like geometry. This areal receiver layout enables computing the horizontal spatial gradients by spatial finite differencing of the vertical-component data for two perpendicular directions and, hence, the estimation of rotational motion around two horizontal axes. Specifically, the recorded seismic waveform data originated from eight explosive packages as well as from continuously listening to the natural lunar seismic activity of moonquakes. As an example, the combined analysis of translational and rotational motion from the active-source LSPE data provides, for the first time, the possibility to extract S-wave information from the enigmatic and reverbatory lunar seismic waveform data, which hithertofore had masked later arriving S-waves. The identification of S-waves enables to characterize the shallow lunar crust in a full elastic sense. The resultant Poisson's ratio profile allows discriminating shallow basalt layers of different degree of fracturing. Our successful analysis of the Apollo 17 data highlights the anticipated significant value of rotational measurements for future extraterrestrial seismology missions.

Staff nurse commitment, work relationships, and turnover intentions: a latent profile analysis.

PubMed

Gellatly, Ian R; Cowden, Tracy L; Cummings, Greta G

2014-01-01

The three-component model of organization commitment has typically been studied using a variable-centered rather than a person-centered approach, preventing a more complete understanding of how these forms of commitment are felt and expressed as a whole. Latent profile analysis was used to identify qualitatively distinct categories or profiles of staff nurses' commitment. Then, associations of the profiles with perceived work unit relations and turnover intentions were examined. Three hundred thirty-six registered nurses provided data on affective, normative, and continuance commitment, perceived work unit relations, and turnover intentions. Latent profile analysis of the nurses' commitment scores revealed six distinct profile groups. Work unit relations and turnover intentions were compared in the six profile-defined groups. Staff nurses with profiles characterized by high affective commitment and/or high normative commitment in relation to other components experienced stronger work unit relations and reported lower turnover intentions. Profiles characterized by high continuance commitment relative to other components or by low overall commitment experienced poorer work unit relations, and the turnover risk was higher. High continuance commitment in combination with high affective and normative commitment was experienced differently than high continuance commitment in combination with low affective and normative commitment. Healthcare organizations often foster commitment by using continuance commitment-enhancing strategies (e.g., offer high salaries and attractive benefits) that may inadvertently introduce behavioral risk. This work suggests the importance of changing the context in which continuance commitment occurs by strengthening the other two components.

Analysis of singular interface stresses in dissimilar material joints for plasma facing components

NASA Astrophysics Data System (ADS)

You, J. H.; Bolt, H.

2001-10-01

Duplex joint structures are typical material combinations for the actively cooled plasma facing components of fusion devices. The structural integrity under the incident heat loads from the plasma is one of the most crucial issues in the technology of these components. The most critical domain in a duplex joint component is the free surface edge of the bond interface between heterogeneous materials. This is due to the fact that the thermal stress usually shows a singular intensification in this region. If the plasma facing armour tile consists of a brittle material, the existence of the stress singularity can be a direct cause of failure. The present work introduces a comprehensive analytical tool to estimate the impact of the stress singularity for duplex PFC design and quantifies the relative stress intensification in various materials joints by use of a model formulated by Munz and Yang. Several candidate material combinations of plasma facing armour and metallic heat sink are analysed and the results are compared with each other.

Geographical classification of Epimedium based on HPLC fingerprint analysis combined with multi-ingredients quantitative analysis.

PubMed

Xu, Ning; Zhou, Guofu; Li, Xiaojuan; Lu, Heng; Meng, Fanyun; Zhai, Huaqiang

2017-05-01

A reliable and comprehensive method for identifying the origin and assessing the quality of Epimedium has been developed. The method is based on analysis of HPLC fingerprints, combined with similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and multi-ingredient quantitative analysis. Nineteen batches of Epimedium, collected from different areas in the western regions of China, were used to establish the fingerprints and 18 peaks were selected for the analysis. Similarity analysis, HCA and PCA all classified the 19 areas into three groups. Simultaneous quantification of the five major bioactive ingredients in the Epimedium samples was also carried out to confirm the consistency of the quality tests. These methods were successfully used to identify the geographical origin of the Epimedium samples and to evaluate their quality. Copyright © 2016 John Wiley & Sons, Ltd.

Faster tissue interface analysis from Raman microscopy images using compressed factorisation

NASA Astrophysics Data System (ADS)

Palmer, Andrew D.; Bannerman, Alistair; Grover, Liam; Styles, Iain B.

2013-06-01

The structure of an artificial ligament was examined using Raman microscopy in combination with novel data analysis. Basis approximation and compressed principal component analysis are shown to provide efficient compression of confocal Raman microscopy images, alongside powerful methods for unsupervised analysis. This scheme allows the acceleration of data mining, such as principal component analysis, as they can be performed on the compressed data representation, providing a decrease in the factorisation time of a single image from five minutes to under a second. Using this workflow the interface region between a chemically engineered ligament construct and a bone-mimic anchor was examined. Natural ligament contains a striated interface between the bone and tissue that provides improved mechanical load tolerance, a similar interface was found in the ligament construct.

Ground resonance analysis using a substructure modeling approach

NASA Technical Reports Server (NTRS)

Chen, S.-Y.; Berman, A.; Austin, E. E.

1984-01-01

A convenient and versatile procedure for modeling and analyzing ground resonance phenomena is described and illustrated. A computer program is used which dynamically couples differential equations with nonlinear and time dependent coefficients. Each set of differential equations may represent a component such as a rotor, fuselage, landing gear, or a failed damper. Arbitrary combinations of such components may be formulated into a model of a system. When the coupled equations are formed, a procedure is executed which uses a Floquet analysis to determine the stability of the system. Illustrations of the use of the procedures along with the numerical examples are presented.

Ground resonance analysis using a substructure modeling approach

NASA Technical Reports Server (NTRS)

Chen, S. Y.; Austin, E. E.; Berman, A.

1985-01-01

A convenient and versatile procedure for modeling and analyzing ground resonance phenomena is described and illustrated. A computer program is used which dynamically couples differential equations with nonlinear and time dependent coefficients. Each set of differential equations may represent a component such as a rotor, fuselage, landing gear, or a failed damper. Arbitrary combinations of such components may be formulated into a model of a system. When the coupled equations are formed, a procedure is executed which uses a Floquet analysis to determine the stability of the system. Illustrations of the use of the procedures along with the numerical examples are presented.

Component analysis of Iranian crack; a newly abused narcotic substance in iran.

PubMed

Farhoudian, Ali; Sadeghi, Mandana; Khoddami Vishteh, Hamid Reza; Moazen, Babak; Fekri, Monir; Rahimi Movaghar, Afarin

2014-01-01

Iranian crack is a new form of narcotic substance that has found widespread prevalence in Iran in the past years. Crack only nominally resembles crack cocaine as it is widely different in its clinical signs. Thus the present study aims to quantify the chemical combination of this drug. The samples included 18 specimen of Crack collected from different zones of Tehran, Iran. All specimens were in the form of inodorous cream solid powdery substance. TLC and HPLC methods were used to perform semi-quantitative and quantitative analysis of the components, respectively. The TLC analysis showed no cocaine compound in the specimens while they all revealed to contain heroin, codeine, morphine and caffeine. All but two specimens contained thebaine. None of the specimens contained amphetamine, benzodiazepines, tricyclic antidepressants, aspirin, barbiturates, tramadol and buprenorphine. Acetaminophen was found in four specimens. HPLC revealed heroin to be the foundation substance in all specimens and most of them contained a significant amount of acetylcodeine. The present analysis of the chemical combination of Crack showed that this substance is a heroin-based narcotic which is basically different from the cocaine-based crack used in Western countries. Studies like the present one at different time points, especially when abnormal clinical signs are detected, can reveal the chemical combination of the target substance and contribute to the clinical management of its acute or chronic poisoning.

Solvent Hold Tank Sample Results for MCU-15-129-130-131: January 2015 Monthly Sample

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

Fondeur, F. F.; Taylor-Pashow, K. M. L.

2015-02-19

SRNL received one set of SHT samples (MCU-15-129, MCU-15-130, and MCU-15-131), pulled on 01/25/2015 for analysis. The samples were combined and analyzed for composition. Analysis of the composite sample MCU-15-129-130-131 indicated low concentrations of the suppressor (TiDG), of the extractant (MaxCalix), and of the modifier (CS-7SB) in the solvent relative to their nominal values. This analysis confirms a downward trend of these components. No impurities were found in this solvent. The laboratory will continue to monitor the quality of the solvent in particular for any new impurity or degradation of the solvent components.

Liquid contrabands classification based on energy dispersive X-ray diffraction and hybrid discriminant analysis

NASA Astrophysics Data System (ADS)

YangDai, Tianyi; Zhang, Li

2016-02-01

Energy dispersive X-ray diffraction (EDXRD) combined with hybrid discriminant analysis (HDA) has been utilized for classifying the liquid materials for the first time. The XRD spectra of 37 kinds of liquid contrabands and daily supplies were obtained using an EDXRD test bed facility. The unique spectra of different samples reveal XRD's capability to distinguish liquid contrabands from daily supplies. In order to create a system to detect liquid contrabands, the diffraction spectra were subjected to HDA which is the combination of principal components analysis (PCA) and linear discriminant analysis (LDA). Experiments based on the leave-one-out method demonstrate that HDA is a practical method with higher classification accuracy and lower noise sensitivity than the other methods in this application. The study shows the great capability and potential of the combination of XRD and HDA for liquid contrabands classification.

Multivariate analysis of the immune response to a vaccine as an alternative to the repetition of animal challenge studies for vaccines with demonstrated efficacy.

PubMed

Chapat, Ludivine; Hilaire, Florence; Bouvet, Jérome; Pialot, Daniel; Philippe-Reversat, Corinne; Guiot, Anne-Laure; Remolue, Lydie; Lechenet, Jacques; Andreoni, Christine; Poulet, Hervé; Day, Michael J; De Luca, Karelle; Cariou, Carine; Cupillard, Lionel

2017-07-01

The assessment of vaccine combinations, or the evaluation of the impact of minor modifications of one component in well-established vaccines, requires animal challenges in the absence of previously validated correlates of protection. As an alternative, we propose conducting a multivariate analysis of the specific immune response to the vaccine. This approach is consistent with the principles of the 3Rs (Refinement, Reduction and Replacement) and avoids repeating efficacy studies based on infectious challenges in vivo. To validate this approach, a set of nine immunological parameters was selected in order to characterize B and T lymphocyte responses against canine rabies virus and to evaluate the compatibility between two canine vaccines, an inactivated rabies vaccine (RABISIN ® ) and a combined vaccine (EURICAN ® DAPPi-Lmulti) injected at two different sites in the same animals. The analysis was focused on the magnitude and quality of the immune response. The multi-dimensional picture given by this 'immune fingerprint' was used to assess the impact of the concomitant injection of the combined vaccine on the immunogenicity of the rabies vaccine. A principal component analysis fully discriminated the control group from the groups vaccinated with RABISIN ® alone or RABISIN ® +EURICAN ® DAPPi-Lmulti and confirmed the compatibility between the rabies vaccines. This study suggests that determining the immune fingerprint, combined with a multivariate statistical analysis, is a promising approach to characterizing the immunogenicity of a vaccine with an established record of efficacy. It may also avoid the need to repeat efficacy studies involving challenge infection in case of minor modifications of the vaccine or for compatibility studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Design and integration of an all-in-one biomicrofluidic chip

PubMed Central

Liu, Liyu; Cao, Wenbin; Wu, Jingbo; Wen, Weijia; Chang, Donald Choy; Sheng, Ping

2008-01-01

We demonstrate a highly integrated microfluidic chip with the function of DNA amplification. The integrated chip combines giant electrorheological-fluid actuated micromixer and micropump with a microheater array, all formed using soft lithography. Internal functional components are based on polydimethylsiloxane (PDMS) and silver∕carbon black-PDMS composites. The system has the advantages of small size with a high degree of integration, high polymerase chain reaction efficiency, digital control and simple fabrication at low cost. This integration approach shows promise for a broad range of applications in chemical synthesis and biological sensing∕analysis, as different components can be combined to target desired functionalities, with flexible designs of different microchips easily realizable through soft lithography. PMID:19693370

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

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

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

EGSIEM combination service: combination of GRACE monthly K-band solutions on normal equation level

NASA Astrophysics Data System (ADS)

Meyer, Ulrich; Jean, Yoomin; Arnold, Daniel; Jäggi, Adrian

2017-04-01

The European Gravity Service for Improved Emergency Management (EGSIEM) project offers a scientific combination service, combining for the first time monthly GRACE gravity fields of different analysis centers (ACs) on normal equation (NEQ) level and thus taking all correlations between the gravity field coefficients and pre-eliminated orbit and instrument parameters correctly into account. Optimal weights for the individual NEQs are commonly derived by variance component estimation (VCE), as is the case for the products of the International VLBI Service (IVS) or the DTRF2008 reference frame realisation that are also derived by combination on NEQ-level. But variance factors are based on post-fit residuals and strongly depend on observation sampling and noise modeling, which both are very diverse in case of the individual EGSIEM ACs. These variance factors do not necessarily represent the true error levels of the estimated gravity field parameters that are still governed by analysis noise. We present a combination approach where weights are derived on solution level, thereby taking the analysis noise into account.

Hyperchromatic laser scanning cytometry

NASA Astrophysics Data System (ADS)

Tárnok, Attila; Mittag, Anja

2007-02-01

In the emerging fields of high-content and high-throughput single cell analysis for Systems Biology and Cytomics multi- and polychromatic analysis of biological specimens has become increasingly important. Combining different technologies and staining methods polychromatic analysis (i.e. using 8 or more fluorescent colors at a time) can be pushed forward to measure anything stainable in a cell, an approach termed hyperchromatic cytometry. For cytometric cell analysis microscope based Slide Based Cytometry (SBC) technologies are ideal as, unlike flow cytometry, they are non-consumptive, i.e. the analyzed sample is fixed on the slide. Based on the feature of relocation identical cells can be subsequently reanalyzed. In this manner data on the single cell level after manipulation steps can be collected. In this overview various components for hyperchromatic cytometry are demonstrated for a SBC instrument, the Laser Scanning Cytometer (Compucyte Corp., Cambridge, MA): 1) polychromatic cytometry, 2) iterative restaining (using the same fluorochrome for restaining and subsequent reanalysis), 3) differential photobleaching (differentiating fluorochromes by their different photostability), 4) photoactivation (activating fluorescent nanoparticles or photocaged dyes), and 5) photodestruction (destruction of FRET dyes). With the intelligent combination of several of these techniques hyperchromatic cytometry allows to quantify and analyze virtually all components of relevance on the identical cell. The combination of high-throughput and high-content SBC analysis with high-resolution confocal imaging allows clear verification of phenotypically distinct subpopulations of cells with structural information. The information gained per specimen is only limited by the number of available antibodies and by sterical hindrance.

A feasibility study on age-related factors of wrist pulse using principal component analysis.

PubMed

Jang-Han Bae; Young Ju Jeon; Sanghun Lee; Jaeuk U Kim

2016-08-01

Various analysis methods for examining wrist pulse characteristics are needed for accurate pulse diagnosis. In this feasibility study, principal component analysis (PCA) was performed to observe age-related factors of wrist pulse from various analysis parameters. Forty subjects in the age group of 20s and 40s were participated, and their wrist pulse signal and respiration signal were acquired with the pulse tonometric device. After pre-processing of the signals, twenty analysis parameters which have been regarded as values reflecting pulse characteristics were calculated and PCA was performed. As a results, we could reduce complex parameters to lower dimension and age-related factors of wrist pulse were observed by combining-new analysis parameter derived from PCA. These results demonstrate that PCA can be useful tool for analyzing wrist pulse signal.

Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis

NASA Astrophysics Data System (ADS)

Dion, J.-L.; Tawfiq, I.; Chevallier, G.

2012-01-01

This work is a contribution in the field of Operational Modal Analysis to identify the modal parameters of mechanical structures using only measured responses. The study deals with structural responses coupled with harmonic components amplitude and frequency modulated in a short range, a common combination for mechanical systems with engines and other rotating machines in operation. These harmonic components generate misleading data interpreted erroneously by the classical methods used in OMA. The present work attempts to differentiate maxima in spectra stemming from harmonic components and structural modes. The detection method proposed is based on the so-called Optimized Spectral Kurtosis and compared with others definitions of Spectral Kurtosis described in the literature. After a parametric study of the method, a critical study is performed on numerical simulations and then on an experimental structure in operation in order to assess the method's performance.

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

1997-01-01

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

1998-01-01

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

Biological effective dose for comparison and combination of external beam and low-dose rate interstitial brachytherapy prostate cancer treatment plans

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

Jani, Ashesh B.; Hand, Christopher M.; Lujan, Anthony E.

2004-03-31

We report a methodology for comparing and combining dose information from external beam radiotherapy (EBRT) and interstitial brachytherapy (IB) components of prostate cancer treatment using the biological effective dose (BED). On a prototype early-stage prostate cancer patient treated with EBRT and low-dose rate I-125 brachytherapy, a 3-dimensional dose distribution was calculated for each of the EBRT and IB portions of treatment. For each component of treatment, the BED was calculated on a point-by-point basis to produce a BED distribution. These individual BED distributions could then be summed for combined therapies. BED dose-volume histograms (DVHs) of the prostate, urethra, rectum, andmore » bladder were produced and compared for various combinations of EBRT and IB. Transformation to BED enabled computation of the relative contribution of each modality to the prostate dose, as the relative weighting of EBRT and IB was varied. The BED-DVHs of the prostate and urethra demonstrated dramatically increased inhomogeneity with the introduction of even a small component of IB. However, increasing the IB portion relative to the EBRT component resulted in lower dose to the surrounding normal structures, as evidenced by the BED-DVHs of the bladder and rectum. Conformal EBRT and low-dose rate IB conventional dose distributions were successfully transformed to the common 'language' of BED distributions for comparison and for merging prostate cancer radiation treatment plans. The results of this analysis can assist physicians in quantitatively determining the best combination and weighting of radiation treatment modalities for individual patients.« less

Pepper seed variety identification based on visible/near-infrared spectral technology

NASA Astrophysics Data System (ADS)

Li, Cuiling; Wang, Xiu; Meng, Zhijun; Fan, Pengfei; Cai, Jichen

2016-11-01

Pepper is a kind of important fruit vegetable, with the expansion of pepper hybrid planting area, detection of pepper seed purity is especially important. This research used visible/near infrared (VIS/NIR) spectral technology to detect the variety of single pepper seed, and chose hybrid pepper seeds "Zhuo Jiao NO.3", "Zhuo Jiao NO.4" and "Zhuo Jiao NO.5" as research sample. VIS/NIR spectral data of 80 "Zhuo Jiao NO.3", 80 "Zhuo Jiao NO.4" and 80 "Zhuo Jiao NO.5" pepper seeds were collected, and the original spectral data was pretreated with standard normal variable (SNV) transform, first derivative (FD), and Savitzky-Golay (SG) convolution smoothing methods. Principal component analysis (PCA) method was adopted to reduce the dimension of the spectral data and extract principal components, according to the distribution of the first principal component (PC1) along with the second principal component(PC2) in the twodimensional plane, similarly, the distribution of PC1 coupled with the third principal component(PC3), and the distribution of PC2 combined with PC3, distribution areas of three varieties of pepper seeds were divided in each twodimensional plane, and the discriminant accuracy of PCA was tested through observing the distribution area of samples' principal components in validation set. This study combined PCA and linear discriminant analysis (LDA) to identify single pepper seed varieties, results showed that with the FD preprocessing method, the discriminant accuracy of pepper seed varieties was 98% for validation set, it concludes that using VIS/NIR spectral technology is feasible for identification of single pepper seed varieties.

Stereovision Imaging in Smart Mobile Phone Using Add on Prisms

NASA Astrophysics Data System (ADS)

Bar-Magen Numhauser, Jonathan; Zalevsky, Zeev

2014-03-01

In this work we present the use of a prism-based add on component installed on top of a smart phone to achieve stereovision capabilities using iPhone mobile operating system. Through these components and the combination of the appropriate application programming interface and mathematical algorithms the obtained results will permit the analysis of possible enhancements for new uses to such system, in a variety of areas including medicine and communications.

Conformational states and folding pathways of peptides revealed by principal-independent component analyses.

PubMed

Nguyen, Phuong H

2007-05-15

Principal component analysis is a powerful method for projecting multidimensional conformational space of peptides or proteins onto lower dimensional subspaces in which the main conformations are present, making it easier to reveal the structures of molecules from e.g. molecular dynamics simulation trajectories. However, the identification of all conformational states is still difficult if the subspaces consist of more than two dimensions. This is mainly due to the fact that the principal components are not independent with each other, and states in the subspaces cannot be visualized. In this work, we propose a simple and fast scheme that allows one to obtain all conformational states in the subspaces. The basic idea is that instead of directly identifying the states in the subspace spanned by principal components, we first transform this subspace into another subspace formed by components that are independent of one other. These independent components are obtained from the principal components by employing the independent component analysis method. Because of independence between components, all states in this new subspace are defined as all possible combinations of the states obtained from each single independent component. This makes the conformational analysis much simpler. We test the performance of the method by analyzing the conformations of the glycine tripeptide and the alanine hexapeptide. The analyses show that our method is simple and quickly reveal all conformational states in the subspaces. The folding pathways between the identified states of the alanine hexapeptide are analyzed and discussed in some detail. 2007 Wiley-Liss, Inc.

Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach

PubMed Central

Appia, Vikram; Ganapathy, Balaji; Yezzi, Anthony; Faber, Tracy

2014-01-01

We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divisions) in an image and then combines these locally accurate segmentation curves to obtain a global segmentation. The training data for our approach consists of training shapes and associated auxiliary (target) masks. The masks indicate the various regions of the shape exhibiting highly correlated variations locally which may be rather independent of the variations in the distant parts of the global shape. Thus, in a sense, we are clustering the variations exhibited in the training data set. We then use a parametric model to implicitly represent each localized segmentation curve as a combination of the local shape priors obtained by representing the training shapes and the masks as a collection of signed distance functions. We also propose a parametric model to combine the locally evolved segmentation curves into a single hybrid (global) segmentation. Finally, we combine the evolution of these semilocal and global parameters to minimize an objective energy function. The resulting algorithm thus provides a globally accurate solution, which retains the local variations in shape. We present some results to illustrate how our approach performs better than the traditional approach with fully global PCA. PMID:25520901

Cognitive inhibition of number/length interference in a Piaget-like task: evidence by combining ERP and MEG.

PubMed

Joliot, Marc; Leroux, Gaëlle; Dubal, Stéphanie; Tzourio-Mazoyer, Nathalie; Houdé, Olivier; Mazoyer, Bernard; Petit, Laurent

2009-08-01

We combined event-related potential (ERP) and magnetoencephalography (MEG) acquisition and analysis to investigate the electrophysiological markers of the inhibitory processes involved in the number/length interference in a Piaget-like numerical task. Eleven healthy subjects performed four gradually interfering conditions with the heuristic "length equals number" to be inhibited. Low resolution tomography reconstruction was performed on the combined grand averaged electromagnetic data at the early (N1, P1) and late (P2, N2, P3(early) and P3(late)) latencies. Every condition was analyzed at both scalp and regional brain levels. The inhibitory processes were visible on the late components of the electromagnetic brain activity. A right P2-related frontal orbital activation reflected the change of strategy in the inhibitory processes. N2-related SMA/cingulate activation revealed the first occurrence of the stimuli processing to be inhibited. Both P3 components revealed the working memory processes operating in a medial temporal complex and the mental imagery processes subtended by the precuneus. Simultaneous ERP and MEG signal acquisition and analysis allowed to describe the spatiotemporal patterns of neural networks involved in the inhibition of the "length equals number" interference. Combining ERP and MEG ensured a sensitivity which could be reached previously only through invasive intracortical recordings.

Confocal Raman microscopy and multivariate statistical analysis for determination of different penetration abilities of caffeine and propylene glycol applied simultaneously in a mixture on porcine skin ex vivo.

PubMed

Mujica Ascencio, Saul; Choe, ChunSik; Meinke, Martina C; Müller, Rainer H; Maksimov, George V; Wigger-Alberti, Walter; Lademann, Juergen; Darvin, Maxim E

2016-07-01

Propylene glycol is one of the known substances added in cosmetic formulations as a penetration enhancer. Recently, nanocrystals have been employed also to increase the skin penetration of active components. Caffeine is a component with many applications and its penetration into the epidermis is controversially discussed in the literature. In the present study, the penetration ability of two components - caffeine nanocrystals and propylene glycol, applied topically on porcine ear skin in the form of a gel, was investigated ex vivo using two confocal Raman microscopes operated at different excitation wavelengths (785nm and 633nm). Several depth profiles were acquired in the fingerprint region and different spectral ranges, i.e., 526-600cm(-1) and 810-880cm(-1) were chosen for independent analysis of caffeine and propylene glycol penetration into the skin, respectively. Multivariate statistical methods such as principal component analysis (PCA) and linear discriminant analysis (LDA) combined with Student's t-test were employed to calculate the maximum penetration depths of each substance (caffeine and propylene glycol). The results show that propylene glycol penetrates significantly deeper than caffeine (20.7-22.0μm versus 12.3-13.0μm) without any penetration enhancement effect on caffeine. The results confirm that different substances, even if applied onto the skin as a mixture, can penetrate differently. The penetration depths of caffeine and propylene glycol obtained using two different confocal Raman microscopes are comparable showing that both types of microscopes are well suited for such investigations and that multivariate statistical PCA-LDA methods combined with Student's t-test are very useful for analyzing the penetration of different substances into the skin. Copyright © 2016 Elsevier B.V. All rights reserved.

Temporal Processing of Dynamic Positron Emission Tomography via Principal Component Analysis in the Sinogram Domain

NASA Astrophysics Data System (ADS)

Chen, Zhe; Parker, B. J.; Feng, D. D.; Fulton, R.

2004-10-01

In this paper, we compare various temporal analysis schemes applied to dynamic PET for improved quantification, image quality and temporal compression purposes. We compare an optimal sampling schedule (OSS) design, principal component analysis (PCA) applied in the image domain, and principal component analysis applied in the sinogram domain; for region-of-interest quantification, sinogram-domain PCA is combined with the Huesman algorithm to quantify from the sinograms directly without requiring reconstruction of all PCA channels. Using a simulated phantom FDG brain study and three clinical studies, we evaluate the fidelity of the compressed data for estimation of local cerebral metabolic rate of glucose by a four-compartment model. Our results show that using a noise-normalized PCA in the sinogram domain gives similar compression ratio and quantitative accuracy to OSS, but with substantially better precision. These results indicate that sinogram-domain PCA for dynamic PET can be a useful preprocessing stage for PET compression and quantification applications.

Life Predicted in a Probabilistic Design Space for Brittle Materials With Transient Loads

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Palfi, Tamas; Reh, Stefan

2005-01-01

Analytical techniques have progressively become more sophisticated, and now we can consider the probabilistic nature of the entire space of random input variables on the lifetime reliability of brittle structures. This was demonstrated with NASA s CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code combined with the commercially available ANSYS/Probabilistic Design System (ANSYS/PDS), a probabilistic analysis tool that is an integral part of the ANSYS finite-element analysis program. ANSYS/PDS allows probabilistic loads, component geometry, and material properties to be considered in the finite-element analysis. CARES/Life predicts the time dependent probability of failure of brittle material structures under generalized thermomechanical loading--such as that found in a turbine engine hot-section. Glenn researchers coupled ANSYS/PDS with CARES/Life to assess the effects of the stochastic variables of component geometry, loading, and material properties on the predicted life of the component for fully transient thermomechanical loading and cyclic loading.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Developing tools for digital radar image data evaluation

NASA Technical Reports Server (NTRS)

Domik, G.; Leberl, F.; Raggam, J.

1986-01-01

The refinement of radar image analysis methods has led to a need for a systems approach to radar image processing software. Developments stimulated through satellite radar are combined with standard image processing techniques to create a user environment to manipulate and analyze airborne and satellite radar images. One aim is to create radar products for the user from the original data to enhance the ease of understanding the contents. The results are called secondary image products and derive from the original digital images. Another aim is to support interactive SAR image analysis. Software methods permit use of a digital height model to create ortho images, synthetic images, stereo-ortho images, radar maps or color combinations of different component products. Efforts are ongoing to integrate individual tools into a combined hardware/software environment for interactive radar image analysis.

Identification of chemical components in Baidianling Capsule based on gas chromatography-mass spectrometry and high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry.

PubMed

Wu, Wenying; Chen, Yu; Wang, Binjie; Sun, Xiaoyang; Guo, Ping; Chen, Xiaohui

2017-08-01

Baidianling Capsule, which is made from 16 Chinese herbs, has been widely used for treating vitiligo clinically. In this study, the sensitive and rapid method has been developed for the analysis of chemical components in Baidianling Capsule by gas chromatography-mass spectrometry in combination with retention indices and high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry. Firstly, a total of 110 potential volatile compounds obtained from different extraction procedures including alkanes, alkenes, alkynes, ketones, ethers, aldehydes, alcohols, phenols, organic acids, esters, furans, pyrrole, acid amides, heterocycles, and oxides were detected from Baidianling Capsule by gas chromatography-mass spectrometry, of which 75 were identified by mass spectrometry in combination with the retention index. Then, a total of 124 components were tentatively identified by high-performance liquid chromatography combined with Fourier transform ion cyclotron resonance mass spectrometry. Fifteen constituents from Baidianling Capsule were accurately identified by comparing the retention times with those of reference compounds, others were identified by comparing the retention times and mass spectrometry data, as well as retrieving the reference literature. This study provides a practical strategy for rapidly screening and identifying the multiple constituents of a complex traditional Chinese medicine. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Towards program theory validation: Crowdsourcing the qualitative analysis of participant experiences.

PubMed

Harman, Elena; Azzam, Tarek

2018-02-01

This exploratory study examines a novel tool for validating program theory through crowdsourced qualitative analysis. It combines a quantitative pattern matching framework traditionally used in theory-driven evaluation with crowdsourcing to analyze qualitative interview data. A sample of crowdsourced participants are asked to read an interview transcript and identify whether program theory components (Activities and Outcomes) are discussed and to highlight the most relevant passage about that component. The findings indicate that using crowdsourcing to analyze qualitative data can differentiate between program theory components that are supported by a participant's experience and those that are not. This approach expands the range of tools available to validate program theory using qualitative data, thus strengthening the theory-driven approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

How do components of evidence-based psychological treatment cluster in practice? A survey and cluster analysis.

PubMed

Gifford, Elizabeth V; Tavakoli, Sara; Weingardt, Kenneth R; Finney, John W; Pierson, Heather M; Rosen, Craig S; Hagedorn, Hildi J; Cook, Joan M; Curran, Geoff M

2012-01-01

Evidence-based psychological treatments (EBPTs) are clusters of interventions, but it is unclear how providers actually implement these clusters in practice. A disaggregated measure of EBPTs was developed to characterize clinicians' component-level evidence-based practices and to examine relationships among these practices. Survey items captured components of evidence-based treatments based on treatment integrity measures. The Web-based survey was conducted with 75 U.S. Department of Veterans Affairs (VA) substance use disorder (SUD) practitioners and 149 non-VA community-based SUD practitioners. Clinician's self-designated treatment orientations were positively related to their endorsement of those EBPT components; however, clinicians used components from a variety of EBPTs. Hierarchical cluster analysis indicated that clinicians combined and organized interventions from cognitive-behavioral therapy, the community reinforcement approach, motivational interviewing, structured family and couples therapy, 12-step facilitation, and contingency management into clusters including empathy and support, treatment engagement and activation, abstinence initiation, and recovery maintenance. Understanding how clinicians use EBPT components may lead to improved evidence-based practice dissemination and implementation. Published by Elsevier Inc.

Support vector machine based classification of fast Fourier transform spectroscopy of proteins

NASA Astrophysics Data System (ADS)

Lazarevic, Aleksandar; Pokrajac, Dragoljub; Marcano, Aristides; Melikechi, Noureddine

2009-02-01

Fast Fourier transform spectroscopy has proved to be a powerful method for study of the secondary structure of proteins since peak positions and their relative amplitude are affected by the number of hydrogen bridges that sustain this secondary structure. However, to our best knowledge, the method has not been used yet for identification of proteins within a complex matrix like a blood sample. The principal reason is the apparent similarity of protein infrared spectra with actual differences usually masked by the solvent contribution and other interactions. In this paper, we propose a novel machine learning based method that uses protein spectra for classification and identification of such proteins within a given sample. The proposed method uses principal component analysis (PCA) to identify most important linear combinations of original spectral components and then employs support vector machine (SVM) classification model applied on such identified combinations to categorize proteins into one of given groups. Our experiments have been performed on the set of four different proteins, namely: Bovine Serum Albumin, Leptin, Insulin-like Growth Factor 2 and Osteopontin. Our proposed method of applying principal component analysis along with support vector machines exhibits excellent classification accuracy when identifying proteins using their infrared spectra.

Propellant's differentiation using FTIR-photoacoustic detection for forensic studies of improvised explosive devices.

PubMed

Álvarez, Ángela; Yáñez, Jorge; Contreras, David; Saavedra, Renato; Sáez, Pedro; Amarasiriwardena, Dulasiri

2017-11-01

The use of propellant for making improvised explosive devices (IED) is an incipient criminal practice. Propellant can be used as initiator in explosive mixtures along with other components such as coal, ammonium nitrate, sulfur, etc. The identification of the propellant's brand used in homemade explosives can provide additional forensic information of this evidence. In this work, four of the most common propellant brands were characterized by Fourier-transform infrared photoacoustic spectroscopy (FTIR-PAS) which is a non-destructive micro-analytical technique. Spectra shows characteristic signals of typical compounds in the propellants, such as nitrocellulose, nitroglycerin, guanidine, diphenylamine, etc. The differentiation of propellant components was achieved by using FTIR-PAS combined with chemometric methods of classification. Principal component analysis (PCA) and soft independent modelling of class analogy (SIMCA) were used to achieve an effective differentiation and classification (100%) of propellant brands. Furthermore, propellant brand differentiation was also assessed using partial least squares discriminant analyses (PLS-DA) by leave one out cross (∼97%) and external (∼100%) validation method. Our results show the ability of FTIR-PAS combined with chemometric analysis to identify and differentiate propellant brands in different explosive formulations of IED. Copyright © 2017 Elsevier B.V. All rights reserved.

H-binding of size- and polarity-fractionated soil and lignite humic acids after removal of metal and ash components.

PubMed

Drosos, Marios; Leenheer, Jerry A; Avgeropoulos, Apostolos; Deligiannakis, Yiannis

2014-03-01

A fractionation technique, combining dialysis removal of metal and ash components with hydrofluoric acid and pH 10 citrate buffer followed by chromatography of dialysis permeate on XAD-8 resin at decreasing pH values, has been applied to lignite humic acid (lignite-HA) and soil humic acid (soil-HA). H-binding data and non ideal competitive adsorption-Donnan model parameters were obtained for the HA fractions by theoretical analysis of H-binding data which reveal a significant increase of the carboxyl and the phenolic charge for the lignite-HA fractions vs. the parental lignite humic acid (LParentalHA). The fractionated lignite-HA material consisted mainly of permeate fractions, some of which were fulvic acid-like. The fractionated soil-HA material consisted mainly of large macromolecular structures that did not permeate the dialysis membrane during deashing. Chargeable groups had comparable concentrations in soil-HA fractions and parental soil humic acid (SParentalHA), indicating minimal interference of ash components with carboxyl and phenolic (and/or enolic) groups. Fractionation of HA, combined with theoretical analysis of H-binding, can distinguish the supramolecular vs. macromolecular nature of fractions within the same parental HA.

H-binding of size- and polarity-fractionated soil and lignite humic acids after removal of metal and ash components

USGS Publications Warehouse

Drosos, Marios; Leenheer, Jerry A.; Avgeropoulos, Apostolos; Deligiannakis, Yiannis

2014-01-01

A fractionation technique, combining dialysis removal of metal and ash components with hydrofluoric acid and pH 10 citrate buffer followed by chromatography of dialysis permeate on XAD-8 resin at decreasing pH values, has been applied to lignite humic acid (lignite-HA) and soil humic acid (soil-HA). H-binding data and non ideal competitive adsorption-Donnan model parameters were obtained for the HA fractions by theoretical analysis of H-binding data which reveal a significant increase of the carboxyl and the phenolic charge for the lignite-HA fractions vs. the parental lignite humic acid (LParentalHA). The fractionated lignite-HA material consisted mainly of permeate fractions, some of which were fulvic acid-like. The fractionated soil-HA material consisted mainly of large macromolecular structures that did not permeate the dialysis membrane during deashing. Chargeable groups had comparable concentrations in soil-HA fractions and parental soil humic acid (SParentalHA), indicating minimal interference of ash components with carboxyl and phenolic (and/or enolic) groups. Fractionation of HA, combined with theoretical analysis of H-binding, can distinguish the supramolecular vs. macromolecular nature of fractions within the same parental HA.

Automated macromolecular crystallization screening

DOEpatents

Segelke, Brent W.; Rupp, Bernhard; Krupka, Heike I.

2005-03-01

An automated macromolecular crystallization screening system wherein a multiplicity of reagent mixes are produced. A multiplicity of analysis plates is produced utilizing the reagent mixes combined with a sample. The analysis plates are incubated to promote growth of crystals. Images of the crystals are made. The images are analyzed with regard to suitability of the crystals for analysis by x-ray crystallography. A design of reagent mixes is produced based upon the expected suitability of the crystals for analysis by x-ray crystallography. A second multiplicity of mixes of the reagent components is produced utilizing the design and a second multiplicity of reagent mixes is used for a second round of automated macromolecular crystallization screening. In one embodiment the multiplicity of reagent mixes are produced by a random selection of reagent components.

T-MATS Toolbox for the Modeling and Analysis of Thermodynamic Systems

NASA Technical Reports Server (NTRS)

Chapman, Jeffryes W.

2014-01-01

The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) is a MATLABSimulink (The MathWorks Inc.) plug-in for creating and simulating thermodynamic systems and controls. The package contains generic parameterized components that can be combined with a variable input iterative solver and optimization algorithm to create complex system models, such as gas turbines.

Preliminary identification of unicellular algal genus by using combined confocal resonance Raman spectroscopy with PCA and DPLS analysis

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Ping; Fang, Shaoxi; Li, Zhe; Tang, Peng; Gao, Xia; Guo, Jinsong; Tlili, Chaker; Wang, Deqiang

2018-02-01

The analysis of algae and dominant alga plays important roles in ecological and environmental fields since it can be used to forecast water bloom and control its potential deleterious effects. Herein, we combine in vivo confocal resonance Raman spectroscopy with multivariate analysis methods to preliminary identify the three algal genera in water blooms at unicellular scale. Statistical analysis of characteristic Raman peaks demonstrates that certain shifts and different normalized intensities, resulting from composition of different carotenoids, exist in Raman spectra of three algal cells. Principal component analysis (PCA) scores and corresponding loading weights show some differences from Raman spectral characteristics which are caused by vibrations of carotenoids in unicellular algae. Then, discriminant partial least squares (DPLS) classification method is used to verify the effectiveness of algal identification with confocal resonance Raman spectroscopy. Our results show that confocal resonance Raman spectroscopy combined with PCA and DPLS could handle the preliminary identification of dominant alga for forecasting and controlling of water blooms.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-01

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety.

The Raman spectrum character of skin tumor induced by UVB

NASA Astrophysics Data System (ADS)

Wu, Shulian; Hu, Liangjun; Wang, Yunxia; Li, Yongzeng

2016-03-01

In our study, the skin canceration processes induced by UVB were analyzed from the perspective of tissue spectrum. A home-made Raman spectral system with a millimeter order excitation laser spot size combined with a multivariate statistical analysis for monitoring the skin changed irradiated by UVB was studied and the discrimination were evaluated. Raman scattering signals of the SCC and normal skin were acquired. Spectral differences in Raman spectra were revealed. Linear discriminant analysis (LDA) based on principal component analysis (PCA) were employed to generate diagnostic algorithms for the classification of skin SCC and normal. The results indicated that Raman spectroscopy combined with PCA-LDA demonstrated good potential for improving the diagnosis of skin cancers.

Metabolite profiling of soy sauce using gas chromatography with time-of-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis.

PubMed

Yamamoto, Shinya; Bamba, Takeshi; Sano, Atsushi; Kodama, Yukako; Imamura, Miho; Obata, Akio; Fukusaki, Eiichiro

2012-08-01

Soy sauces, produced from different ingredients and brewing processes, have variations in components and quality. Therefore, it is extremely important to comprehend the relationship between components and the sensory attributes of soy sauces. The current study sought to perform metabolite profiling in order to devise a method of assessing the attributes of soy sauces. Quantitative descriptive analysis (QDA) data for 24 soy sauce samples were obtained from well selected sensory panelists. Metabolite profiles primarily concerning low-molecular-weight hydrophilic components were based on gas chromatography with time-of-flightmass spectrometry (GC/TOFMS). QDA data for soy sauces were accurately predicted by projection to latent structure (PLS), with metabolite profiles serving as explanatory variables and QDA data set serving as a response variable. Moreover, analysis of correlation between matrices of metabolite profiles and QDA data indicated contributing compounds that were highly correlated with QDA data. Especially, it was indicated that sugars are important components of the tastes of soy sauces. This new approach which combines metabolite profiling with QDA is applicable to analysis of sensory attributes of food as a result of the complex interaction between its components. This approach is effective to search important compounds that contribute to the attributes. Copyright © 2012 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Strategies for systemic radiotherapy of micrometastases using antibody-targeted 131I.

PubMed

Wheldon, T E; O'Donoghue, J A; Hilditch, T E; Barrett, A

1988-02-01

A simple analysis is developed to evaluate the likely effectiveness of treatment of micrometastases by antibody-targeted 131I. Account is taken of the low levels of tumour uptake of antibody-conjugated 131I presently achievable and of the "energy wastage" in targeting microscopic tumours with a radionuclide whose disintegration energy is widely dissipated. The analysis shows that only modest doses can be delivered to micrometastases when total body dose is restricted to levels which allow recovery of bone marrow. Much higher doses could be delivered to micrometastases when bone marrow rescue is used. A rationale is presented for targeted systemic radiotherapy used in combination with external beam total body irradiation (TBI) and bone marrow rescue. This has some practical advantages. The effect of the targeted component is to impose a biological non-uniformity on the total body dose distribution with regions of high tumour cell density receiving higher doses. Where targeting results in high doses to particular normal organs (e.g. liver, kidney) the total dose to these organs could be kept within tolerable limits by appropriate shielding of the external beam radiation component of the treatment. Greater levels of tumour cell kill should be achievable by the combination regime without any increase in normal tissue damage over that inflicted by conventional TBI. The predicted superiority of the combination regime is especially marked for tumours just below the threshold for detectability (e.g. approximately 1 mm-1 cm diameter). This approach has the advantage that targeted radiotherapy provides only a proportion of the total body dose, most of which is given by a familiar technique. The proportion of dose given by the targeted component could be increased as experience is gained. The predicted superiority of the combination strategy should be experimentally testable using laboratory animals. Clinical applications should be cautiously approached, with due regard to the limitations of the theoretical analysis.

The reliability of the pass/fail decision for assessments comprised of multiple components.

PubMed

Möltner, Andreas; Tımbıl, Sevgi; Jünger, Jana

2015-01-01

The decision having the most serious consequences for a student taking an assessment is the one to pass or fail that student. For this reason, the reliability of the pass/fail decision must be determined for high quality assessments, just as the measurement reliability of the point values. Assessments in a particular subject (graded course credit) are often composed of multiple components that must be passed independently of each other. When "conjunctively" combining separate pass/fail decisions, as with other complex decision rules for passing, adequate methods of analysis are necessary for estimating the accuracy and consistency of these classifications. To date, very few papers have addressed this issue; a generally applicable procedure was published by Douglas and Mislevy in 2010. Using the example of an assessment comprised of several parts that must be passed separately, this study analyzes the reliability underlying the decision to pass or fail students and discusses the impact of an improved method for identifying those who do not fulfill the minimum requirements. The accuracy and consistency of the decision to pass or fail an examinee in the subject cluster Internal Medicine/General Medicine/Clinical Chemistry at the University of Heidelberg's Faculty of Medicine was investigated. This cluster requires students to separately pass three components (two written exams and an OSCE), whereby students may reattempt to pass each component twice. Our analysis was carried out using the method described by Douglas and Mislevy. Frequently, when complex logical connections exist between the individual pass/fail decisions in the case of low failure rates, only a very low reliability for the overall decision to grant graded course credit can be achieved, even if high reliabilities exist for the various components. For the example analyzed here, the classification accuracy and consistency when conjunctively combining the three individual parts is relatively low with κ=0.49 or κ=0.47, despite the good reliability of over 0.75 for each of the three components. The option to repeat each component twice leads to a situation in which only about half of the candidates who do not satisfy the minimum requirements would fail the overall assessment, while the other half is able to continue their studies despite having deficient knowledge and skills. The method put forth by Douglas and Mislevy allows the analysis of the decision accuracy and consistency for complex combinations of scores from different components. Even in the case of highly reliable components, it is not necessarily so that a reliable pass/fail decision has been reached - for instance in the case of low failure rates. Assessments must be administered with the explicit goal of identifying examinees that do not fulfill the minimum requirements.

The reliability of the pass/fail decision for assessments comprised of multiple components

PubMed Central

Möltner, Andreas; Tımbıl, Sevgi; Jünger, Jana

2015-01-01

Objective: The decision having the most serious consequences for a student taking an assessment is the one to pass or fail that student. For this reason, the reliability of the pass/fail decision must be determined for high quality assessments, just as the measurement reliability of the point values. Assessments in a particular subject (graded course credit) are often composed of multiple components that must be passed independently of each other. When “conjunctively” combining separate pass/fail decisions, as with other complex decision rules for passing, adequate methods of analysis are necessary for estimating the accuracy and consistency of these classifications. To date, very few papers have addressed this issue; a generally applicable procedure was published by Douglas and Mislevy in 2010. Using the example of an assessment comprised of several parts that must be passed separately, this study analyzes the reliability underlying the decision to pass or fail students and discusses the impact of an improved method for identifying those who do not fulfill the minimum requirements. Method: The accuracy and consistency of the decision to pass or fail an examinee in the subject cluster Internal Medicine/General Medicine/Clinical Chemistry at the University of Heidelberg’s Faculty of Medicine was investigated. This cluster requires students to separately pass three components (two written exams and an OSCE), whereby students may reattempt to pass each component twice. Our analysis was carried out using the method described by Douglas and Mislevy. Results: Frequently, when complex logical connections exist between the individual pass/fail decisions in the case of low failure rates, only a very low reliability for the overall decision to grant graded course credit can be achieved, even if high reliabilities exist for the various components. For the example analyzed here, the classification accuracy and consistency when conjunctively combining the three individual parts is relatively low with κ=0.49 or κ=0.47, despite the good reliability of over 0.75 for each of the three components. The option to repeat each component twice leads to a situation in which only about half of the candidates who do not satisfy the minimum requirements would fail the overall assessment, while the other half is able to continue their studies despite having deficient knowledge and skills. Conclusion: The method put forth by Douglas and Mislevy allows the analysis of the decision accuracy and consistency for complex combinations of scores from different components. Even in the case of highly reliable components, it is not necessarily so that a reliable pass/fail decision has been reached – for instance in the case of low failure rates. Assessments must be administered with the explicit goal of identifying examinees that do not fulfill the minimum requirements. PMID:26483855

Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae

PubMed Central

2014-01-01

Background The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Results Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. Conclusion In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus. PMID:24961398

Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae.

PubMed

Liu, Lifang; Feizi, Amir; Österlund, Tobias; Hjort, Carsten; Nielsen, Jens

2014-06-24

The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus.

Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis.

PubMed

Ocké, Marga C

2013-05-01

This paper aims to describe different approaches for studying the overall diet with advantages and limitations. Studies of the overall diet have emerged because the relationship between dietary intake and health is very complex with all kinds of interactions. These cannot be captured well by studying single dietary components. Three main approaches to study the overall diet can be distinguished. The first method is researcher-defined scores or indices of diet quality. These are usually based on guidelines for a healthy diet or on diets known to be healthy. The second approach, using principal component or cluster analysis, is driven by the underlying dietary data. In principal component analysis, scales are derived based on the underlying relationships between food groups, whereas in cluster analysis, subgroups of the population are created with people that cluster together based on their dietary intake. A third approach includes methods that are driven by a combination of biological pathways and the underlying dietary data. Reduced rank regression defines linear combinations of food intakes that maximally explain nutrient intakes or intermediate markers of disease. Decision tree analysis identifies subgroups of a population whose members share dietary characteristics that influence (intermediate markers of) disease. It is concluded that all approaches have advantages and limitations and essentially answer different questions. The third approach is still more in an exploration phase, but seems to have great potential with complementary value. More insight into the utility of conducting studies on the overall diet can be gained if more attention is given to methodological issues.

Differentiating organic and conventional sage by chromatographic and mass spectrometry flow-injection fingerprints

USDA-ARS?s Scientific Manuscript database

High performance liquid chromatography (UPLC) and flow injection electrospray ionization with ion trap mass spectrometry (FIMS) fingerprints combined with the principal component analysis (PCA) were examined for their potential in differentiating commercial organic and conventional sage samples. The...

Patient phenotypes associated with outcomes after aneurysmal subarachnoid hemorrhage: a principal component analysis.

PubMed

Ibrahim, George M; Morgan, Benjamin R; Macdonald, R Loch

2014-03-01

Predictors of outcome after aneurysmal subarachnoid hemorrhage have been determined previously through hypothesis-driven methods that often exclude putative covariates and require a priori knowledge of potential confounders. Here, we apply a data-driven approach, principal component analysis, to identify baseline patient phenotypes that may predict neurological outcomes. Principal component analysis was performed on 120 subjects enrolled in a prospective randomized trial of clazosentan for the prevention of angiographic vasospasm. Correlation matrices were created using a combination of Pearson, polyserial, and polychoric regressions among 46 variables. Scores of significant components (with eigenvalues>1) were included in multivariate logistic regression models with incidence of severe angiographic vasospasm, delayed ischemic neurological deficit, and long-term outcome as outcomes of interest. Sixteen significant principal components accounting for 74.6% of the variance were identified. A single component dominated by the patients' initial hemodynamic status, World Federation of Neurosurgical Societies score, neurological injury, and initial neutrophil/leukocyte counts was significantly associated with poor outcome. Two additional components were associated with angiographic vasospasm, of which one was also associated with delayed ischemic neurological deficit. The first was dominated by the aneurysm-securing procedure, subarachnoid clot clearance, and intracerebral hemorrhage, whereas the second had high contributions from markers of anemia and albumin levels. Principal component analysis, a data-driven approach, identified patient phenotypes that are associated with worse neurological outcomes. Such data reduction methods may provide a better approximation of unique patient phenotypes and may inform clinical care as well as patient recruitment into clinical trials. http://www.clinicaltrials.gov. Unique identifier: NCT00111085.

Moisture and Structural Analysis for High Performance Hybrid Wall Assemblies

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

Grin, A.; Lstiburek, J.

2012-09-01

This report describes the work conducted by the Building Science Corporation (BSC) Building America Research Team's 'Energy Efficient Housing Research Partnerships' project. Based on past experience in the Building America program, they have found that combinations of materials and approaches---in other words, systems--usually provide optimum performance. No single manufacturer typically provides all of the components for an assembly, nor has the specific understanding of all the individual components necessary for optimum performance.

Quantization of Motor Activity into Primitives and Time-Frequency Atoms Using Independent Component Analysis and Matching Pursuit Algorithms

DTIC Science & Technology

2001-10-25

form: (1) A is a scaling factor, t is time and r a coordinate vector describing the limb configuration. We...combination of limb state and EMG. In our early examination of EMG we detected underlying groups of muscles and phases of activity by inspection and...representations of EEG or other biological signals has been thoroughly explored. Such components might be used as a basis for neuroprosthetic control

Gender differences in the prevalence and development of metabolic syndrome in Chinese population with abdominal obesity.

PubMed

Xu, Shaoyong; Gao, Bin; Xing, Ying; Ming, Jie; Bao, Junxiang; Zhang, Qiang; Wan, Yi; Ji, Qiuhe

2013-01-01

Not all the people with metabolic syndrome (MS) have abdominal obesity (AO). The study aimed to investigate gender differences in the prevalence and development of MS in Chinese population with abdominal obesity, which has rarely been reported. Data were obtained from the 2007-08 China National Diabetes and Metabolic Disorders Study, and participants were divided into two samples for analysis. Sample 1 consisted of 19,046 people with abdominal obesity, while sample 2 included 2,124 people meeting pre-specified requirements. Survival analysis was used to analyze the development of MS. The age-standardized prevalence of MS in Chinese population with AO was 49.5%. The prevalence in males (73.7%) was significantly higher than that in females (36.9%). Males had significantly higher proportions of combinations of three or four MS components than females (36.4% vs. 30.2% and 18.4% vs. 5%, respectively). MS developed quick at first and became slow down later. Half of the participants with AO developed to MS after 3.9 years (95% CI: 3.7-4.1) from the initial metabolic abnormal component, whereas 75% developed to MS after 7.7 years (95% CI: 7.5-7.9). Compared with females, Chinese males with AO should receive more attention because of their higher prevalence of MS and its components, more complex and risky combinations of abnormal components, and faster development of MS.

Climate Change and Examples of Combined HyspIRI VSWIR/TIR Advanced Level Products for Urban Ecosystems Analysis

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.

2010-01-01

It is estimated that 60-80% of the world population will live in urban environments by the end of this century. This growth of the urban population will effect the climate. This slide presentation examines the use of combined HyspIRI Visible ShortWave Infrared (VSWIR)/Thermal Infrared (TIR) to observe, monitor, measure and model many of the components that comprise urban ecosystems cycles.

[Vis-NIR spectroscopic pattern recognition combined with SG smoothing applied to breed screening of transgenic sugarcane].

PubMed

Liu, Gui-Song; Guo, Hao-Song; Pan, Tao; Wang, Ji-Hua; Cao, Gan

2014-10-01

Based on Savitzky-Golay (SG) smoothing screening, principal component analysis (PCA) combined with separately supervised linear discriminant analysis (LDA) and unsupervised hierarchical clustering analysis (HCA) were used for non-destructive visible and near-infrared (Vis-NIR) detection for breed screening of transgenic sugarcane. A random and stability-dependent framework of calibration, prediction, and validation was proposed. A total of 456 samples of sugarcane leaves planting in the elongating stage were collected from the field, which was composed of 306 transgenic (positive) samples containing Bt and Bar gene and 150 non-transgenic (negative) samples. A total of 156 samples (negative 50 and positive 106) were randomly selected as the validation set; the remaining samples (negative 100 and positive 200, a total of 300 samples) were used as the modeling set, and then the modeling set was subdivided into calibration (negative 50 and positive 100, a total of 150 samples) and prediction sets (negative 50 and positive 100, a total of 150 samples) for 50 times. The number of SG smoothing points was ex- panded, while some modes of higher derivative were removed because of small absolute value, and a total of 264 smoothing modes were used for screening. The pairwise combinations of first three principal components were used, and then the optimal combination of principal components was selected according to the model effect. Based on all divisions of calibration and prediction sets and all SG smoothing modes, the SG-PCA-LDA and SG-PCA-HCA models were established, the model parameters were optimized based on the average prediction effect for all divisions to produce modeling stability. Finally, the model validation was performed by validation set. With SG smoothing, the modeling accuracy and stability of PCA-LDA, PCA-HCA were signif- icantly improved. For the optimal SG-PCA-LDA model, the recognition rate of positive and negative validation samples were 94.3%, 96.0%; and were 92.5%, 98.0% for the optimal SG-PCA-LDA model, respectively. Vis-NIR spectro- scopic pattern recognition combined with SG smoothing could be used for accurate recognition of transgenic sugarcane leaves, and provided a convenient screening method for transgenic sugarcane breeding.

3D inelastic analysis methods for hot section components

NASA Technical Reports Server (NTRS)

Dame, L. T.; Chen, P. C.; Hartle, M. S.; Huang, H. T.

1985-01-01

The objective is to develop analytical tools capable of economically evaluating the cyclic time dependent plasticity which occurs in hot section engine components in areas of strain concentration resulting from the combination of both mechanical and thermal stresses. Three models were developed. A simple model performs time dependent inelastic analysis using the power law creep equation. The second model is the classical model of Professors Walter Haisler and David Allen of Texas A and M University. The third model is the unified model of Bodner, Partom, et al. All models were customized for linear variation of loads and temperatures with all material properties and constitutive models being temperature dependent.

Empirical studies of solar flares: Comparison of X-ray and H alpha filtergrams and analysis of the energy balance of the X-ray plasma

NASA Technical Reports Server (NTRS)

Moore, R. L.

1979-01-01

The physics of solar flares was investigated through a combined analysis of X-ray filtergrams of the high temperature coronal component of flares and H alpha filtergrams of the low temperature chromospheric component. The data were used to study the magnetic field configuration and its changes in solar flares, and to examine the chromospheric location and structure of X-ray bright points (XPB) and XPB flares. Each topic and the germane data are discussed. The energy balance of the thermal X-ray plasma in flares, while not studied, is addressed.

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

Romano, J.D.; Woan, G.

Data from the Laser Interferometer Space Antenna (LISA) is expected to be dominated by frequency noise from its lasers. However, the noise from any one laser appears more than once in the data and there are combinations of the data that are insensitive to this noise. These combinations, called time delay interferometry (TDI) variables, have received careful study and point the way to how LISA data analysis may be performed. Here we approach the problem from the direction of statistical inference, and show that these variables are a direct consequence of a principal component analysis of the problem. We presentmore » a formal analysis for a simple LISA model and show that there are eigenvectors of the noise covariance matrix that do not depend on laser frequency noise. Importantly, these orthogonal basis vectors correspond to linear combinations of TDI variables. As a result we show that the likelihood function for source parameters using LISA data can be based on TDI combinations of the data without loss of information.« less

Quantitative analysis of the anti-inflammatory activity of orengedokuto II: berberine is responsible for the inhibition of NO production.

PubMed

Oshima, Naohiro; Shimizu, Tomofumi; Narukawa, Yuji; Hada, Noriyasu; Kiuchi, Fumiyuki

2018-06-01

Orengedokuto is a Kampo formula that has been used for removing "heat" and "poison" to treat inflammation, hypertension, gastrointestinal disorders, and liver and cerebrovascular diseases. We report here our analysis of the anti-inflammatory effect of the component crude drugs of orengedokuto and their constituents using the inhibition of nitric oxide (NO) production in the murine macrophage-like cell line J774.1. An initial comparison of NO production inhibitory activities of the extracts of the component crude drugs and their combinations revealed that the activity could be attributed to Phellodendron Bark and Coptis Rhizome. Berberine (1), the major constituent of these crude drugs, showed potent activity (IC 50 4.73 ± 1.46 μM). Quantitative analysis of 1 in the extracts of all combinations of component crude drugs revealed that the amount of 1 in each extract of the combination of Scutellaria Root with either Phellodendron Bark and/or Coptis Rhizome was lower than that in the corresponding mixtures of the extracts of the individual crude drugs and that 1 was present in the precipitates formed during the decoction process. To the contrary, the differences in the amounts of 1 were smaller in the extracts containing Gardenia Fruit. These results indicated that the constituents of Scutellaria Root precipitated with 1 and that the constituents of Gardenia Fruit dissolved the precipitates. To identify the constituents affecting the solubility of 1, we fractionated the hot-water extracts of Scutellaria Root based on solubility tests of 1 to give baicalin (2), wogonin (3) and oroxyloside (4), which formed precipitates with 1.

Development and Characterization of Nanostructured Cermet Coatings Produced by Co-electrodeposition

NASA Astrophysics Data System (ADS)

Farrokhzad, Mohammad Ali

Nanostructured cermet (ceramic-metallic) coatings are a group of materials that combine properties possessed by ceramics, such as oxidation resistance and high hardness, and the properties of metals such as strength and ductility. These coatings consist of nano-sized metal-oxide particles (i.e. Al2 O3) dispersed into a corrosion resistant metal matrix such as nickel. Cermet coatings have been used in many industrial applications such as cutting tools and jet engines where high temperature and erosion resistance performance are required. However, despite the promising properties, the lack of experimental data and theories on high temperature oxidation and mechanical properties of cermet coatings have restricted their full potential to be used in technologies for oil sand production such as In-Situ Combustion (ISC). In this study, the structure of cermet coatings was investigated to identify the characteristics that give rise to oxidation performance and wear resistance properties of cermet coatings. The experimental oxidation results on the single-component oxide cermet coatings showed that when Al2O3 and TiO2 were combined in the electrolyte, the new combination can improve oxidation performance (less mass gain) as compared to a pure Ni coating. Based on the oxidation and micro-hardness results, a new group of nanostructured cermet coatings (double-component oxides) was developed and investigated using long term oxidation tests, thermo-gravimetric analysis in mixed gas, thermal cycling, micro-hardness and abrasive wear tests. The mechanical analysis of the newly developed coatings showed improved resistance against wear and thermal cycling compared to single-component oxide cermet and pure Ni coatings. Furthermore, some new theoretical analysis were also put forward that aims at a new explanation of high temperature oxidation for cermet coatings.

Combining multiple regression and principal component analysis for accurate predictions for column ozone in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Rajab, Jasim M.; MatJafri, M. Z.; Lim, H. S.

2013-06-01

This study encompasses columnar ozone modelling in the peninsular Malaysia. Data of eight atmospheric parameters [air surface temperature (AST), carbon monoxide (CO), methane (CH4), water vapour (H2Ovapour), skin surface temperature (SSKT), atmosphere temperature (AT), relative humidity (RH), and mean surface pressure (MSP)] data set, retrieved from NASA's Atmospheric Infrared Sounder (AIRS), for the entire period (2003-2008) was employed to develop models to predict the value of columnar ozone (O3) in study area. The combined method, which is based on using both multiple regressions combined with principal component analysis (PCA) modelling, was used to predict columnar ozone. This combined approach was utilized to improve the prediction accuracy of columnar ozone. Separate analysis was carried out for north east monsoon (NEM) and south west monsoon (SWM) seasons. The O3 was negatively correlated with CH4, H2Ovapour, RH, and MSP, whereas it was positively correlated with CO, AST, SSKT, and AT during both the NEM and SWM season periods. Multiple regression analysis was used to fit the columnar ozone data using the atmospheric parameter's variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to acquire subsets of the predictor variables to be comprised in the linear regression model of the atmospheric parameter's variables. It was found that the increase in columnar O3 value is associated with an increase in the values of AST, SSKT, AT, and CO and with a drop in the levels of CH4, H2Ovapour, RH, and MSP. The result of fitting the best models for the columnar O3 value using eight of the independent variables gave about the same values of the R (≈0.93) and R2 (≈0.86) for both the NEM and SWM seasons. The common variables that appeared in both regression equations were SSKT, CH4 and RH, and the principal precursor of the columnar O3 value in both the NEM and SWM seasons was SSKT.

Multivariate Analysis of Solar Spectral Irradiance Measurements

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Rabbette, M.

2001-01-01

Principal component analysis is used to characterize approximately 7000 downwelling solar irradiance spectra retrieved at the Southern Great Plains site during an Atmospheric Radiation Measurement (ARM) shortwave intensive operating period. This analysis technique has proven to be very effective in reducing a large set of variables into a much smaller set of independent variables while retaining the information content. It is used to determine the minimum number of parameters necessary to characterize atmospheric spectral irradiance or the dimensionality of atmospheric variability. It was found that well over 99% of the spectral information was contained in the first six mutually orthogonal linear combinations of the observed variables (flux at various wavelengths). Rotation of the principal components was effective in separating various components by their independent physical influences. The majority of the variability in the downwelling solar irradiance (380-1000 nm) was explained by the following fundamental atmospheric parameters (in order of their importance): cloud scattering, water vapor absorption, molecular scattering, and ozone absorption. In contrast to what has been proposed as a resolution to a clear-sky absorption anomaly, no unexpected gaseous absorption signature was found in any of the significant components.

Interactive effects of global change factors on soil respiration and its components: a meta-analysis.

PubMed

Zhou, Lingyan; Zhou, Xuhui; Shao, Junjiong; Nie, Yuanyuan; He, Yanghui; Jiang, Liling; Wu, Zhuoting; Hosseini Bai, Shahla

2016-09-01

As the second largest carbon (C) flux between the atmosphere and terrestrial ecosystems, soil respiration (Rs) plays vital roles in regulating atmospheric CO2 concentration ([CO2 ]) and climatic dynamics in the earth system. Although numerous manipulative studies and a few meta-analyses have been conducted to determine the responses of Rs and its two components [i.e., autotrophic (Ra) and heterotrophic (Rh) respiration] to single global change factors, the interactive effects of the multiple factors are still unclear. In this study, we performed a meta-analysis of 150 multiple-factor (≥2) studies to examine the main and interactive effects of global change factors on Rs and its two components. Our results showed that elevated [CO2 ] (E), nitrogen addition (N), irrigation (I), and warming (W) induced significant increases in Rs by 28.6%, 8.8%, 9.7%, and 7.1%, respectively. The combined effects of the multiple factors, EN, EW, DE, IE, IN, IW, IEW, and DEW, were also significantly positive on Rs to a greater extent than those of the single-factor ones. For all the individual studies, the additive interactions were predominant on Rs (90.6%) and its components (≈70.0%) relative to synergistic and antagonistic ones. However, the different combinations of global change factors (e.g., EN, NW, EW, IW) indicated that the three types of interactions were all important, with two combinations for synergistic effects, two for antagonistic, and five for additive when at least eight independent experiments were considered. In addition, the interactions of elevated [CO2 ] and warming had opposite effects on Ra and Rh, suggesting that different processes may influence their responses to the multifactor interactions. Our study highlights the crucial importance of the interactive effects among the multiple factors on Rs and its components, which could inform regional and global models to assess the climate-biosphere feedbacks and improve predictions of the future states of the ecological and climate systems. © 2016 John Wiley & Sons Ltd.

Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis.

PubMed

Yang, Yan-Qin; Yin, Hong-Xu; Yuan, Hai-Bo; Jiang, Yong-Wen; Dong, Chun-Wang; Deng, Yu-Liang

2018-01-01

In the present work, a novel infrared-assisted extraction coupled to headspace solid-phase microextraction (IRAE-HS-SPME) followed by gas chromatography-mass spectrometry (GC-MS) was developed for rapid determination of the volatile components in green tea. The extraction parameters such as fiber type, sample amount, infrared power, extraction time, and infrared lamp distance were optimized by orthogonal experimental design. Under optimum conditions, a total of 82 volatile compounds in 21 green tea samples from different geographical origins were identified. Compared with classical water-bath heating, the proposed technique has remarkable advantages of considerably reducing the analytical time and high efficiency. In addition, an effective classification of green teas based on their volatile profiles was achieved by partial least square-discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). Furthermore, the application of a dual criterion based on the variable importance in the projection (VIP) values of the PLS-DA models and on the category from one-way univariate analysis (ANOVA) allowed the identification of 12 potential volatile markers, which were considered to make the most important contribution to the discrimination of the samples. The results suggest that IRAE-HS-SPME/GC-MS technique combined with multivariate analysis offers a valuable tool to assess geographical traceability of different tea varieties.

Using fluorescence spectroscopy coupled with chemometric analysis to investigate the origin, composition, and dynamics of dissolved organic matter in leachate-polluted groundwater.

PubMed

He, Xiao-Song; Xi, Bei-Dou; Gao, Ru-Tai; Wang, Lei; Ma, Yan; Cui, Dong-Yu; Tan, Wen-Bing

2015-06-01

Groundwater was collected in 2011 and 2012, and fluorescence spectroscopy coupled with chemometric analysis was employed to investigate the composition, origin, and dynamics of dissolved organic matter (DOM) in the groundwater. The results showed that the groundwater DOM comprised protein-, fulvic-, and humic-like substances, and the protein-like component originated predominantly from microbial production. The groundwater pollution by landfill leachate enhanced microbial activity and thereby increased microbial by-product-like material such as protein-like component in the groundwater. Excitation-emission matrix fluorescence spectra combined with parallel factor analysis showed that the protein-like matter content increased from 2011 to 2012 in the groundwater, whereas the fulvic- and humic-like matter concentration exhibited no significant changes. In addition, synchronous-scan fluorescence spectra coupled with two-dimensional correlation analysis showed that the change of the fulvic- and humic-like matter was faster than that of the protein-like substances, as the groundwater flowed from upstream to downstream in 2011, but slower than that of the protein-like substance in 2012 due to the enhancement of microbial activity. Fluorescence spectroscopy combined with chemometric analysis can investigate groundwater pollution characteristics and monitor DOM dynamics in groundwater.

Characterization of the volatile components in green tea by IRAE-HS-SPME/GC-MS combined with multivariate analysis

PubMed Central

Yin, Hong-Xu; Yuan, Hai-Bo; Jiang, Yong-Wen; Dong, Chun-Wang; Deng, Yu-Liang

2018-01-01

In the present work, a novel infrared-assisted extraction coupled to headspace solid-phase microextraction (IRAE-HS-SPME) followed by gas chromatography-mass spectrometry (GC-MS) was developed for rapid determination of the volatile components in green tea. The extraction parameters such as fiber type, sample amount, infrared power, extraction time, and infrared lamp distance were optimized by orthogonal experimental design. Under optimum conditions, a total of 82 volatile compounds in 21 green tea samples from different geographical origins were identified. Compared with classical water-bath heating, the proposed technique has remarkable advantages of considerably reducing the analytical time and high efficiency. In addition, an effective classification of green teas based on their volatile profiles was achieved by partial least square-discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). Furthermore, the application of a dual criterion based on the variable importance in the projection (VIP) values of the PLS-DA models and on the category from one-way univariate analysis (ANOVA) allowed the identification of 12 potential volatile markers, which were considered to make the most important contribution to the discrimination of the samples. The results suggest that IRAE-HS-SPME/GC-MS technique combined with multivariate analysis offers a valuable tool to assess geographical traceability of different tea varieties. PMID:29494626

[Evaluate drug interaction of multi-components in Morus alba leaves based on α-glucosidase inhibitory activity].

PubMed

Ji, Tao; Su, Shu-Lan; Guo, Sheng; Qian, Da-Wei; Ouyang, Zhen; Duan, Jin-Ao

2016-06-01

Column chromatography was used for enrichment and separation of flavonoids, alkaloids and polysaccharides from the extracts of Morus alba leaves; glucose oxidase method was used with sucrose as the substrate to evaluate the multi-components of M. alba leaves in α-glucosidase inhibitory models; isobole method, Chou-Talalay combination index analysis and isobolographic analysis were used to evaluate the interaction effects and dose-effect characteristics of two components, providing scientific basis for revealing the hpyerglycemic mechanism of M. alba leaves. The components analysis showed that flavonoid content was 5.3%; organic phenolic acids content was 10.8%; DNJ content was 39.4%; and polysaccharide content was 18.9%. Activity evaluation results demonstrated that flavonoids, alkaloids and polysaccharides of M. alba leaves had significant inhibitory effects on α-glucosidase, and the inhibitory rate was increased with the increasing concentration. Alkaloids showed most significant inhibitory effects among these three components. Both compatibility of alkaloids and flavonoids, and the compatibility of alkaloids and polysaccharides demonstrated synergistic effects, but the compatibility of flavonoids and polysaccharides showed no obvious synergistic effects. The results have confirmed the interaction of multi-components from M. alba leaves to regulate blood sugar, and provided scientific basis for revealing hpyerglycemic effectiveness and mechanism of the multi-components from M. alba leaves. Copyright© by the Chinese Pharmaceutical Association.

Integrating Microscopic Analysis into Existing Quality Assurance Processes

NASA Astrophysics Data System (ADS)

Frühberger, Peter; Stephan, Thomas; Beyerer, Jürgen

When technical goods, like mainboards and other electronic components, are produced, quality assurance (QA) is very important. To achieve this goal, different optical microscopes can be used to analyze a variety of specimen to gain comprehensive information by combining the acquired sensor data. In many industrial processes, cameras are used to examine these technical goods. Those cameras can analyze complete boards at once and offer a high level of accuracy when used for completeness checks. When small defects, e.g. soldered points, need to be examined in detail, those wide area cameras are limited. Microscopes with large magnification need to be used to analyze those critical areas. But microscopes alone cannot fulfill this task within a limited time schedule, because microscopic analysis of complete motherboards of a certain size is time demanding. Microscopes are limited concerning their depth of field and depth of focus, which is why additional components like XY moving tables need to be used to examine the complete surface. Yet today's industrial production quality standards require a 100 % control of the soldered components within a given time schedule. This level of quality, while keeping inspection time low, can only be achieved when combining multiple inspection devices in an optimized manner. This paper presents results and methods of combining industrial cameras with microscopy instrumenting a classificatory based approach intending to keep already deployed QA processes in place but extending them with the purpose of increasing the quality level of the produced technical goods while maintaining high throughput.

Authenticity of rice (Oryza sativa L.) geographical origin based on analysis of C, N, O and S stable isotope ratios: a preliminary case report in Korea, China and Philippine.

PubMed

Chung, Ill-Min; Kim, Jae-Kwang; Prabakaran, Mayakrishnan; Yang, Jin-Hee; Kim, Seung-Hyun

2016-05-01

Although rice (Oryza sativa L.) is the third largest food crop, relatively fewer studies have been reported on rice geographical origin based on light element isotope ratios in comparison with other foods such as wine, beef, juice, oil and milk. Therefore this study tries to discriminate the geographical origin of the same rice cultivars grown in different Asian countries using the analysis of C, N, O and S stable isotope ratios and chemometrics. The δ(15) NAIR , δ(18) OVSMOW and δ(34) SVCDT values of brown rice were more markedly influenced by geographical origin than was the δ(13) CVPDB value. In particular, the combination of δ(18) OVSMOW and δ(34) SVCDT more efficiently discriminated rice geographical origin than did the remaining combinations. Principal component analysis (PCA) revealed a clear discrimination between different rice geographical origins but not between rice genotypes. In particular, the first components of PCA discriminated rice cultivated in the Philippines from rice cultivated in China and Korea. The present findings suggest that analysis of the light element isotope composition combined with chemometrics can be potentially applicable to discriminate rice geographical origin and also may provide a valuable insight into the control of improper or fraudulent labeling regarding the geographical origin of rice worldwide. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Simultaneous Determination of Gallic Acid, Ellagic Acid, and Eugenol in Syzygium aromaticum and Verification of Chemical Antagonistic Effect by the Combination with Curcuma aromatica Using Regression Analysis

PubMed Central

Seo, Chang-Seob; Kim, Seong-Sil; Ha, Hyekyung

2013-01-01

This study was designed to perform simultaneous determination of three reference compounds in Syzygium aromaticum (SA), gallic acid, ellagic acid, and eugenol, and to investigate the chemical antagonistic effect when combining Curcuma aromatica (CA) with SA, based on chromatographic analysis. The values of LODs and LOQs were 0.01–0.11 μg/mL and 0.03–0.36 μg/mL, respectively. The intraday and interday precisions were <3.0 of RSD values, and the recovery was in the range of 92.19–103.24%, with RSD values <3.0%. Repeatability and stability were 0.38–0.73% and 0.49–2.24%, respectively. Compared with the content of reference and relative peaks in SA and SA combined with CA (SAC), the amounts of gallic acid and eugenol were increased, while that of ellagic acid was decreased in SAC (compared with SA), and most of peak areas in SA were reduced in SAC. Regression analysis of the relative peak areas between SA and SAC showed r 2 values >0.87, indicating a linear relationship between SA and SAC. These results demonstrate that the components contained in CA could affect the extraction of components of SA mainly in a decreasing manner. The antagonistic effect of CA on SA was verified by chemical analysis. PMID:23878761

Fast and simultaneously determination of light and heavy rare earth elements in monazite using combination of ultraviolet-visible spectrophotometry and multivariate analysis

NASA Astrophysics Data System (ADS)

Anggraeni, Anni; Arianto, Fernando; Mutalib, Abdul; Pratomo, Uji; Bahti, Husein H.

2017-05-01

Rare Earth Elements (REE) are elements that a lot of function for life, such as metallurgy, optical devices, and manufacture of electronic devices. Sources of REE is present in the mineral, in which each element has similar properties. Currently, to determining the content of REE is used instruments such as ICP-OES, ICP-MS, XRF, and HPLC. But in each instruments, there are still have some weaknesses. Therefore we need an alternative analytical method for the determination of rare earth metal content, one of them is by a combination of UV-Visible spectrophotometry and multivariate analysis, including Principal Component Analysis (PCA), Principal Component Regression (PCR), and Partial Least Square Regression (PLS). The purpose of this experiment is to determine the content of light and medium rare earth elements in the mineral monazite without chemical separation by using a combination of multivariate analysis and UV-Visible spectrophotometric methods. Training set created 22 variations of concentration and absorbance was measured using a UV-Vis spectrophotometer, then the data is processed by PCA, PCR, and PLSR. The results were compared and validated to obtain the mathematical equation with the smallest percent error. From this experiment, mathematical equation used PLS methods was better than PCR after validated, which has RMSE value for La, Ce, Pr, Nd, Gd, Sm, Eu, and Tb respectively 0.095; 0.573; 0.538; 0.440; 3.387; 1.240; 1.870; and 0.639.

Multidimensional profiling of components in complex mixtures of natural products for metabolic analysis, proof of concept: application to Quillaja saponins.

PubMed

Bankefors, Johan; Nord, Lars I; Kenne, Lennart

2010-02-01

A method for separation and detection of major and minor components in complex mixtures has been developed, utilising two-dimensional high-performance liquid chromatography (2D-HPLC) combined with electrospray ionisation ion-trap multiple-stage mass spectrometry (ESI-ITMS(n)). Chromatographic conditions were matched with mass spectrometric detection to maximise the number of components that could be separated. The described procedure has proven useful to discern several hundreds of saponin components when applied to Quillaja saponaria Molina bark extracts. The discrimination of each saponin component relies on the fact that three coordinates (x, y, z) for each component can be derived from the retention time of the two chromatographic steps (x, y) and the m/z-values from the multiple-stage mass spectrometry (z(n), n=1, 2, ...). Thus an improved graphical representation was obtained by combining retention times from the two-stage separation with +MS(1) (z(1)) and the additional structural information from the second mass stage +MS(2) (z(2), z(3)) corresponding to the main fragment ions. By this approach three-dimensional plots can be made that reveal both the chromatographic and structural properties of a specific mixture which can be useful in fingerprinting of complex mixtures. 2009 Elsevier B.V. All rights reserved.

[Verification of ballast water exchange for international ships anchored in Xiamen Port by CDOM tracer].

PubMed

Li, Chao; Zhang, Yan-po; Guo, Wei-dong; Zhu, Yue; Xu, Jing; Deng, Xun

2010-09-01

Fluorescence excitation-emission matrix (EEM) and absorption spectroscopy were applied to study the optical properties of 29 CDOM samples collected from different ballast tanks of nine international route vessels anchored in Xiamen Port between October 2007 and April 2008. The purpose was to examine the feasibility of these spectral properties as a tracer to verify if these vessels follow the mid-ocean ballast water exchange (BWE) regulation. Using parallel factor analysis, four fluorescent components were identified, including two humic-like components (C1: 245, 300/386 nm; C2: 250, 345/458 nm) and two protein-like components (C3: 220, 275/306 nm; C4: 235, 290/345 nm), of which C2 component was the suitable fluorescence verification indicator. The vertical distribution of all fluorescent components in ballast tank was nearly similar indicating that profile-mixing sampling was preferable. Combined use of C2 component, spectral slope ratio (SR) of absorption spectroscopy and salinity may provide reasonable verification if BWE carried out by these nine ships. The results suggested that the combined use of multiple parameters (fluorescence, absorption and salinity) would be much reliable to determine the origin of ballast water, and to provide the technical guarantee for fast examination of ballast water exchange in Chinese ports.

Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program.

PubMed

Afouxenidis, D; Polymeris, G S; Tsirliganis, N C; Kitis, G

2012-05-01

This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the GLOw Curve ANalysis INtercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters.

A novel bicomponent hemolysin from Bacillus cereus.

PubMed Central

Beecher, D J; MacMillan, J D

1990-01-01

A procedure combining isoelectric focusing (Sephadex IEF) and fast protein liquid chromatography (Superose 12; Mono-Q) removed hemolytic activity (presumably a contaminant) from partially purified preparations of the multicomponent diarrheal enterotoxin produced by Bacillus cereus. However, when the separated fractions were recombined, hemolytic activity was restored, suggesting that hemolysis is a property of the enterotoxin components. Combined fractions exhibited a unique ring pattern in gel diffusion assays in blood agar. During diffusion of the hemolysin from an agar well, the erythrocytes closest to the well were not lysed initially. After diffusion, hemolysis was observed as a sharp ring beginning several millimeters away from the edge of the well. With time the cells closer to the well were also lysed. This novel hemolysin consists of a protein (component B) which binds to or alters cells, allowing subsequent lysis by a second protein (component L). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis, isoelectric focusing, and Western blot analysis showed that hemolysin BL has properties similar to those described previously for the enterotoxin and that both components are distinct from cereolysin and cereolysin AB. Images PMID:2114359

Automated urinalysis: first experiences and a comparison between the Iris iQ200 urine microscopy system, the Sysmex UF-100 flow cytometer and manual microscopic particle counting.

PubMed

Shayanfar, Noushin; Tobler, Ulrich; von Eckardstein, Arnold; Bestmann, Lukas

2007-01-01

Automated analysis of insoluble urine components can reduce the workload of conventional microscopic examination of urine sediment and is possibly helpful for standardization. We compared the diagnostic performance of two automated urine sediment analyzers and combined dipstick/automated urine analysis with that of the traditional dipstick/microscopy algorithm. A total of 332 specimens were collected and analyzed for insoluble urine components by microscopy and automated analyzers, namely the Iris iQ200 (Iris Diagnostics) and the UF-100 flow cytometer (Sysmex). The coefficients of variation for day-to-day quality control of the iQ200 and UF-100 analyzers were 6.5% and 5.5%, respectively, for red blood cells. We reached accuracy ranging from 68% (bacteria) to 97% (yeast) for the iQ200 and from 42% (bacteria) to 93% (yeast) for the UF-100. The combination of dipstick and automated urine sediment analysis increased the sensitivity of screening to approximately 98%. We conclude that automated urine sediment analysis is sufficiently precise and improves the workflow in a routine laboratory. In addition, it allows sediment analysis of all urine samples and thereby helps to detect pathological samples that would have been missed in the conventional two-step procedure according to the European guidelines. Although it is not a substitute for microscopic sediment examination, it can, when combined with dipstick testing, reduce the number of specimens submitted to microscopy. Visual microscopy is still required for some samples, namely, dysmorphic erythrocytes, yeasts, Trichomonas, oval fat bodies, differentiation of casts and certain crystals.

Satellite ranging data analysis under LAGEOS A. O. No. OSTA 78-2

NASA Technical Reports Server (NTRS)

Shelus, P. J.

1981-01-01

LAGEOS and lunar laser ranging observations are combined to eliminate the shortcomings inherent in each technique, while accentuating the advantages of each. All three components of the Earth's rotation are produced with accuracy and precision which is compatible with observational uncertainties.

A hybrid sales forecasting scheme by combining independent component analysis with K-means clustering and support vector regression.

PubMed

Lu, Chi-Jie; Chang, Chi-Chang

2014-01-01

Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting.

A Hybrid Sales Forecasting Scheme by Combining Independent Component Analysis with K-Means Clustering and Support Vector Regression

PubMed Central

2014-01-01

Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (ICA) with K-means clustering and support vector regression (SVR). The proposed scheme first uses the ICA to extract hidden information from the observed sales data. The extracted features are then applied to K-means algorithm for clustering the sales data into several disjoined clusters. Finally, the SVR forecasting models are applied to each group to generate final forecasting results. Experimental results from information technology (IT) product agent sales data reveal that the proposed sales forecasting scheme outperforms the three comparison models and hence provides an efficient alternative for sales forecasting. PMID:25045738

Separation of pedogenic and lithogenic components of magnetic susceptibility in the Chinese loess/palaeosol sequence as determined by the CBD procedure and a mixing analysis

NASA Astrophysics Data System (ADS)

Vidic, Nataša. J.; TenPas, Jeff D.; Verosub, Kenneth L.; Singer, Michael J.

2000-08-01

Magnetic susceptibility variations in the Chinese loess/palaeosol sequences have been used extensively for palaeoclimatic interpretations. The magnetic signal of these sequences must be divided into lithogenic and pedogenic components because the palaeoclimatic record is primarily reflected in the pedogenic component. In this paper we compare two methods for separating the pedogenic and lithogenic components of the magnetic susceptibility signal: the citrate-bicarbonate-dithionite (CBD) extraction procedure, and a mixing analysis. Both methods yield good estimates of the pedogenic component, especially for the palaeosols. The CBD procedure underestimates the lithogenic component and overestimates the pedogenic component. The magnitude of this effect is moderately high in loess layers but almost negligible in palaeosols. The mixing model overestimates the lithogenic component and underestimates the pedogenic component. Both methods can be adjusted to yield better estimates of both components. The lithogenic susceptibility, as determined by either method, suggests that palaeoclimatic interpretations based only on total susceptibility will be in error and that a single estimate of the average lithogenic susceptibility is not an accurate basis for adjusting the total susceptibility. A long-term decline in lithogenic susceptibility with depth in the section suggests more intense or prolonged periods of weathering associated with the formation of the older palaeosols. The CBD procedure provides the most comprehensive information on the magnitude of the components and magnetic mineralogy of loess and palaeosols. However, the mixing analysis provides a sensitive, rapid, and easily applied alternative to the CBD procedure. A combination of the two approaches provides the most powerful and perhaps the most accurate way of separating the magnetic susceptibility components.

A computer program for cyclic plasticity and structural fatigue analysis

NASA Technical Reports Server (NTRS)

Kalev, I.

1980-01-01

A computerized tool for the analysis of time independent cyclic plasticity structural response, life to crack initiation prediction, and crack growth rate prediction for metallic materials is described. Three analytical items are combined: the finite element method with its associated numerical techniques for idealization of the structural component, cyclic plasticity models for idealization of the material behavior, and damage accumulation criteria for the fatigue failure.

The Prediction of Job Ability Requirements Using Attribute Data Based Upon the Position Analysis Questionnaire (PAQ). Technical Report No. 1.

ERIC Educational Resources Information Center

Shaw, James B.; McCormick, Ernest J.

The study was directed towards the further exploration of the use of attribute ratings as the basis for establishing the job component validity of tests, in particular by using different methods of combining "attribute-based" data with "job analysis" data to form estimates of the aptitude requirements of jobs. The primary focus…

Effect of removing the common mode errors on linear regression analysis of noise amplitudes in position time series of a regional GPS network & a case study of GPS stations in Southern California

NASA Astrophysics Data System (ADS)

Jiang, Weiping; Ma, Jun; Li, Zhao; Zhou, Xiaohui; Zhou, Boye

2018-05-01

The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126 GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.

Analysis of wastewater samples by direct combination of thin-film microextraction and desorption electrospray ionization mass spectrometry.

PubMed

Strittmatter, Nicole; Düring, Rolf-Alexander; Takáts, Zoltán

2012-09-07

An analysis method for aqueous samples by the direct combination of C18/SCX mixed mode thin-film microextraction (TFME) and desorption electrospray ionization mass spectrometry (DESI-MS) was developed. Both techniques make analytical workflow simpler and faster, hence the combination of the two techniques enables considerably shorter analysis time compared to the traditional liquid chromatography mass spectrometry (LC-MS) approach. The method was characterized using carbamazepine and triclosan as typical examples for pharmaceuticals and personal care product (PPCP) components which draw increasing attention as wastewater-derived environmental contaminants. Both model compounds were successfully detected in real wastewater samples and their concentrations determined using external calibration with isotope labeled standards. Effects of temperature, agitation, sample volume, and exposure time were investigated in the case of spiked aqueous samples. Results were compared to those of parallel HPLC-MS determinations and good agreement was found through a three orders of magnitude wide concentration range. Serious matrix effects were observed in treated wastewater, but lower limits of detection were still found to be in the low ng L(-1) range. Using an Orbitrap mass spectrometer, the technique was found to be ideal for screening purposes and led to the detection of various different PPCP components in wastewater treatment plant effluents, including beta-blockers, nonsteroidal anti-inflammatory drugs, and UV filters.

Spatial analysis of sunshine duration by combination of satellite and station data

NASA Astrophysics Data System (ADS)

Frei, C.; Stöckli, R.; Dürr, B.

2009-09-01

Sunshine duration can exhibit rich fine scale patterns associated with special meteorological phenomena, such as fog layers and topographically triggered clouds. Networks of climate stations are mostly too coarse and poorly representative to resolve these patterns explicitly. We present a method which combines station observations with satellite-derived cloud-cover data to produce km-scale fields of sunshine duration. The method is not relying on contemporous satellite information, hence it can be applied over climatological time scales. We apply and evaluate the combination method over the territory of Switzerland. The combination method is based on Universal Kriging. First, the satellite data (a Heliosat clear sky index from MSG, extending over a 5 year preiod) is subjected to a S-mode Principal Component (PC) Analysis. Second, a set of leading PC loadings (seasonally stratified) is introduced as external drift covariates and their optimal linear combination is estimated from the station data (70 stations). Finally, the stochastic component is an autocorrelated field with an exponential variogram, estimated climatologically for each calendar month. For Switzerland the leading PCs of the clear sky index depict familiar patterns of cloud variability which are inhereted in the combination process. The resulting sunshine duration fields exhibit fine-scale structures that are physically plausible, linked to the topography and characteristic of the regional climate. These patterns could not be inferred from station data and/or topographic predictors alone. A cross-validation reveals that the combination method explains between 80-90% of the spatial variance in winter and autumn months. In spring and summer the relative performance is lower (60-75% explained spatial variance) but absolute errors are smaller. Our presentation will also discuss some results from a climatology of the derived sunshine duration fields.

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.

Levelized cost-benefit analysis of proposed diagnostics for the Ammunition Transfer Arm of the US Army`s Future Armored Resupply Vehicle

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

Wilkinson, V.K.; Young, J.M.

1995-07-01

The US Army`s Project Manager, Advanced Field Artillery System/Future Armored Resupply Vehicle (PM-AFAS/FARV) is sponsoring the development of technologies that can be applied to the resupply vehicle for the Advanced Field Artillery System. The Engineering Technology Division of the Oak Ridge National Laboratory has proposed adding diagnostics/prognostics systems to four components of the Ammunition Transfer Arm of this vehicle, and a cost-benefit analysis was performed on the diagnostics/prognostics to show the potential savings that may be gained by incorporating these systems onto the vehicle. Possible savings could be in the form of reduced downtime, less unexpected or unnecessary maintenance, fewermore » regular maintenance checks. and/or tower collateral damage or loss. The diagnostics/prognostics systems are used to (1) help determine component problems, (2) determine the condition of the components, and (3) estimate the remaining life of the monitored components. The four components on the arm that are targeted for diagnostics/prognostics are (1) the electromechanical brakes, (2) the linear actuators, (3) the wheel/roller bearings, and (4) the conveyor drive system. These would be monitored using electrical signature analysis, vibration analysis, or a combination of both. Annual failure rates for the four components were obtained along with specifications for vehicle costs, crews, number of missions, etc. Accident scenarios based on component failures were postulated, and event trees for these scenarios were constructed to estimate the annual loss of the resupply vehicle, crew, arm. or mission aborts. A levelized cost-benefit analysis was then performed to examine the costs of such failures, both with and without some level of failure reduction due to the diagnostics/prognostics systems. Any savings resulting from using diagnostics/prognostics were calculated.« less

A Hybrid Approach to Composite Damage and Failure Analysis Combining Synergistic Damage Mechanics and Peridynamics

DTIC Science & Technology

2017-06-30

along the intermetallic component or at the interface between the two components of the composite. The availability of rnicroscale experimental data in...obtained with the PD model; (c) map of strain energy density; (d) the new quasi -index damage is a predictor of fai lure. As in the case of FRCs, one...which points are most likely to fail, before actual failure happens. The " quasi -damage index", shown in the formula below, is a point-wise measure

Analysis of volatile components from Melipona beecheii geopropolis from Southeast Mexico by headspace solid-phase microextraction.

PubMed

Torres-González, Ahira; López-Rivera, Paulina; Duarte-Lisci, Georgina; López-Ramírez, Ángel; Correa-Benítez, Adriana; Rivero-Cruz, J Fausto

2016-01-01

A head space solid-phase microextraction method combined with gas chromatography-mass spectrometry was developed and optimised to extract and analyse volatile compounds of Melipona beecheii geopropolis. Seventy-three constituents were identified using this technique in the sample of geopropolis collected. The main compounds detected include β-fenchene (14.53-15.45%), styrene (8.72-9.98%), benzaldehyde (7.44-7.82%) and the most relevant volatile components presents at high level in the geopropolis were terpenoids (58.17%).

Isolation of campesteryl ferulate and epi-campesteryl ferulate, two components of γ-oryzanol from rice bran.

PubMed

Bao, Yuhua; Yanase, Emiko; Nakatsuka, Shin-ichi

2013-01-01

Campesteryl ferulate (3a, 24R/α) and epi-campesteryl ferulate (3b, 24S/β), components of rice bran γ-oryzanol, were isolated by the preparative recycle HPLC system using a combination of ODS silica and cholester packed columns at over 99% purity. Their purities and structures of 3a and 3b thus obtained were confirmed by HPLC analysis and physical data (1H- and 13C-NMR, MS spectra, and X-ray crystallography).

Influence of Component Rotation in Total Knee Arthroplasty on Tibiofemoral Kinematics-A Cadaveric Investigation.

PubMed

Maderbacher, Guenther; Keshmiri, Armin; Springorum, Hans R; Maderbacher, Hermann; Grifka, Joachim; Baier, Clemens

2017-09-01

Physiological tibiofemoral kinematics have been shown to be important for good knee function after total knee arthroplasty (TKA). The purpose of the present study was to investigate the influence of component rotation on tibiofemoral kinematics during knee flexion. We asked which axial component alignment best reconstructs physiological tibiofemoral kinematics and which combinations should be avoided. Ten healthy cadaveric knees were examined. By means of a navigational device, tibiofemoral kinematics between 0° and 90° of flexion were assessed before and after TKA using the following different rotational component alignment: femoral components: ligament balanced, 6° internal, 3° external rotation, and 6° external rotation in relation to the posterior condylar line; tibial components: self-adapted, 6° internal rotation, and 6° external rotation. Physiological tibiofemoral kinematics could be partly reconstructed by TKA. Ligament-balanced femoral rotation and 6° femoral external rotation both in combination with 6° tibial component external rotation, and 3° femoral external rotation in combination with 6° tibial component internal rotation or self-aligning tibial component were able to restore tibial longitudinal rotation. Largest kinematical differences were found for the combination femoral component internal and tibial component external rotations. From a kinematic-based view, surgeons should avoid internal rotation of femoral components. However, even often recommended combinations of rotational component alignment (3° femoral external and tibial external rotation) significantly change tibiofemoral kinematics. Self-aligning tibial components solely restored tibiofemoral kinematics with the combination of 3° femoral component of external rotation. For the future, navigational devices might help to axially align components to restore patient-specific and natural tibiofemoral kinematics. Copyright © 2017 Elsevier Inc. All rights reserved.

Combining kriging, multispectral and multimodal microscopy to resolve malaria-infected erythrocyte contents.

PubMed

Dabo-Niang, S; Zoueu, J T

2012-09-01

In this communication, we demonstrate how kriging, combine with multispectral and multimodal microscopy can enhance the resolution of malaria-infected images and provide more details on their composition, for analysis and diagnosis. The results of this interpolation applied to the two principal components of multispectral and multimodal images illustrate that the examination of the content of Plasmodium falciparum infected human erythrocyte is improved. © 2012 The Authors Journal of Microscopy © 2012 Royal Microscopical Society.

Investigation of Pinus mugo essential oil oxygenated fraction by combined use of gas chromatography and dry column chromatography.

PubMed

A, M B; Coran, S A; Giannellini, V; Vincieri, F F; Moneti, G

1981-09-01

The oxygenated compounds of Pinus mugo Turra essential oil were investigated by a combination of GC and dry column chromatography (DCC) coordinated by GC data processing. The collected data resulted in a bar graph ("normalized" gas chromatogram) giving the RRT's and relative amounts of 68 components; 38 of them were identified by MS and IR. The described procedure may be used for essential oil analysis in general.

Integrating Multiple Correlated Phenotypes for Genetic Association Analysis by Maximizing Heritability

PubMed Central

Zhou, Jin J.; Cho, Michael H.; Lange, Christoph; Lutz, Sharon; Silverman, Edwin K.; Laird, Nan M.

2015-01-01

Many correlated disease variables are analyzed jointly in genetic studies in the hope of increasing power to detect causal genetic variants. One approach involves assessing the relationship between each phenotype and each single nucleotide polymorphism (SNP) individually and using a Bonferroni correction for the effective number of tests conducted. Alternatively, one can apply a multivariate regression or a dimension reduction technique, such as principal component analysis (PCA), and test for the association with the principal components (PC) of the phenotypes rather than the individual phenotypes. Inspired by the previous approaches of combining phenotypes to maximize heritability at individual SNPs, in this paper, we propose to construct a maximally heritable phenotype (MaxH) by taking advantage of the estimated total heritability and co-heritability. The heritability and co-heritability only need to be estimated once, therefore our method is applicable to genome-wide scans. MaxH phenotype is a linear combination of the individual phenotypes with increased heritability and power over the phenotypes being combined. Simulations show that the heritability and power achieved agree well with the theory for large samples and two phenotypes. We compare our approach with commonly used methods and assess both the heritability and the power of the MaxH phenotype. Moreover we provide suggestions for how to choose the phenotypes for combination. An application of our approach to a COPD genome-wide association study shows the practical relevance. PMID:26111731

Periodic component analysis as a spatial filter for SSVEP-based brain-computer interface.

PubMed

Kiran Kumar, G R; Reddy, M Ramasubba

2018-06-08

Traditional Spatial filters used for steady-state visual evoked potential (SSVEP) extraction such as minimum energy combination (MEC) require the estimation of the background electroencephalogram (EEG) noise components. Even though this leads to improved performance in low signal to noise ratio (SNR) conditions, it makes such algorithms slow compared to the standard detection methods like canonical correlation analysis (CCA) due to the additional computational cost. In this paper, Periodic component analysis (πCA) is presented as an alternative spatial filtering approach to extract the SSVEP component effectively without involving extensive modelling of the noise. The πCA can separate out components corresponding to a given frequency of interest from the background electroencephalogram (EEG) by capturing the temporal information and does not generalize SSVEP based on rigid templates. Data from ten test subjects were used to evaluate the proposed method and the results demonstrate that the periodic component analysis acts as a reliable spatial filter for SSVEP extraction. Statistical tests were performed to validate the results. The experimental results show that πCA provides significant improvement in accuracy compared to standard CCA and MEC in low SNR conditions. The results demonstrate that πCA provides better detection accuracy compared to CCA and on par with that of MEC at a lower computational cost. Hence πCA is a reliable and efficient alternative detection algorithm for SSVEP based brain-computer interface (BCI). Copyright © 2018. Published by Elsevier B.V.

Fractal analysis of scatter imaging signatures to distinguish breast pathologies

NASA Astrophysics Data System (ADS)

Eguizabal, Alma; Laughney, Ashley M.; Krishnaswamy, Venkataramanan; Wells, Wendy A.; Paulsen, Keith D.; Pogue, Brian W.; López-Higuera, José M.; Conde, Olga M.

2013-02-01

Fractal analysis combined with a label-free scattering technique is proposed for describing the pathological architecture of tumors. Clinicians and pathologists are conventionally trained to classify abnormal features such as structural irregularities or high indices of mitosis. The potential of fractal analysis lies in the fact of being a morphometric measure of the irregular structures providing a measure of the object's complexity and self-similarity. As cancer is characterized by disorder and irregularity in tissues, this measure could be related to tumor growth. Fractal analysis has been probed in the understanding of the tumor vasculature network. This work addresses the feasibility of applying fractal analysis to the scattering power map (as a physical modeling) and principal components (as a statistical modeling) provided by a localized reflectance spectroscopic system. Disorder, irregularity and cell size variation in tissue samples is translated into the scattering power and principal components magnitude and its fractal dimension is correlated with the pathologist assessment of the samples. The fractal dimension is computed applying the box-counting technique. Results show that fractal analysis of ex-vivo fresh tissue samples exhibits separated ranges of fractal dimension that could help classifier combining the fractal results with other morphological features. This contrast trend would help in the discrimination of tissues in the intraoperative context and may serve as a useful adjunct to surgeons.

Digital Learning Characteristics and Principles of Information Resources Knowledge Structuring

ERIC Educational Resources Information Center

Belichenko, Margarita; Davidovitch, Nitza; Kravchenko, Yuri

2017-01-01

Analysis of principles knowledge representation in information systems led to the necessity of improving the structuring knowledge. It is caused by the development of software component and new possibilities of information technologies. The article combines methodological aspects of structuring knowledge and effective usage of information…

Combined use of isotopic fingerprint and metabolomics analysis for the authentication of saw palmetto (Serenoa repens) extracts.

PubMed

Perini, Matteo; Paolini, Mauro; Camin, Federica; Appendino, Giovanni; Vitulo, Francesca; De Combarieu, Eric; Sardone, Nicola; Martinelli, Ernesto Marco; Pace, Roberto

2018-04-22

Saw palmetto (Serenoa repens, SP) is the most expensive oil source of the pharmaceutical and healthfood market, and its high cost and recurrent shortages have spurred the development of designer blends of fatty acids to mimic its phytochemical profile and fraudulently comply with the current authentication assays. To detect this adulteration, the combined use of isotopic fingerprint and omic analysis has been investigated, using Principal Component Analysis (PCA) to handle the complex databases generated by these techniques and to identify the possible source of the adulterants. Surprisingly, the presence of fatty acids of animal origin turned out to be widespread in commercial samples of saw palmetto oil. Copyright © 2018 Elsevier B.V. All rights reserved.

Spectroscopic and Chemometric Analysis of Binary and Ternary Edible Oil Mixtures: Qualitative and Quantitative Study.

PubMed

Jović, Ozren; Smolić, Tomislav; Primožič, Ines; Hrenar, Tomica

2016-04-19

The aim of this study was to investigate the feasibility of FTIR-ATR spectroscopy coupled with the multivariate numerical methodology for qualitative and quantitative analysis of binary and ternary edible oil mixtures. Four pure oils (extra virgin olive oil, high oleic sunflower oil, rapeseed oil, and sunflower oil), as well as their 54 binary and 108 ternary mixtures, were analyzed using FTIR-ATR spectroscopy in combination with principal component and discriminant analysis, partial least-squares, and principal component regression. It was found that the composition of all 166 samples can be excellently represented using only the first three principal components describing 98.29% of total variance in the selected spectral range (3035-2989, 1170-1140, 1120-1100, 1093-1047, and 930-890 cm(-1)). Factor scores in 3D space spanned by these three principal components form a tetrahedral-like arrangement: pure oils being at the vertices, binary mixtures at the edges, and ternary mixtures on the faces of a tetrahedron. To confirm the validity of results, we applied several cross-validation methods. Quantitative analysis was performed by minimization of root-mean-square error of cross-validation values regarding the spectral range, derivative order, and choice of method (partial least-squares or principal component regression), which resulted in excellent predictions for test sets (R(2) > 0.99 in all cases). Additionally, experimentally more demanding gas chromatography analysis of fatty acid content was carried out for all specimens, confirming the results obtained by FTIR-ATR coupled with principal component analysis. However, FTIR-ATR provided a considerably better model for prediction of mixture composition than gas chromatography, especially for high oleic sunflower oil.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Color image encryption based on gyrator transform and Arnold transform

NASA Astrophysics Data System (ADS)

Sui, Liansheng; Gao, Bo

2013-06-01

A color image encryption scheme using gyrator transform and Arnold transform is proposed, which has two security levels. In the first level, the color image is separated into three components: red, green and blue, which are normalized and scrambled using the Arnold transform. The green component is combined with the first random phase mask and transformed to an interim using the gyrator transform. The first random phase mask is generated with the sum of the blue component and a logistic map. Similarly, the red component is combined with the second random phase mask and transformed to three-channel-related data. The second random phase mask is generated with the sum of the phase of the interim and an asymmetrical tent map. In the second level, the three-channel-related data are scrambled again and combined with the third random phase mask generated with the sum of the previous chaotic maps, and then encrypted into a gray scale ciphertext. The encryption result has stationary white noise distribution and camouflage property to some extent. In the process of encryption and decryption, the rotation angle of gyrator transform, the iterative numbers of Arnold transform, the parameters of the chaotic map and generated accompanied phase function serve as encryption keys, and hence enhance the security of the system. Simulation results and security analysis are presented to confirm the security, validity and feasibility of the proposed scheme.

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

IDS contribution to ITRF2008

NASA Astrophysics Data System (ADS)

Valette, Jean-Jacques; Lemoine, Frank G.; Ferrage, Pascale; Yaya, Philippe; Altamimi, Zuheir; Willis, Pascal; Soudarin, Laurent

2010-12-01

For the first time, the International DORIS Service (IDS) has produced a technique level combination based on the contributions of seven analysis centers (ACs), including the European Space Operations Center (ESOC), Geodetic Observatory Pecny (GOP), Geoscience Australia (GAU), the NASA Goddard Space Flight Center (GSFC), the Institut Géographique National (IGN), the Institute of Astronomy, Russian Academy of Sciences (INASAN, named as INA), and CNES/CLS (named as LCA). The ACs used five different software packages to process the DORIS data from 1992 to 2008, including NAPEOS (ESA), Bernese (GOP), GEODYN (GAU, GSC), GIPSY/OASIS (INA), and GINS (LCA). The data from seven DORIS satellites, TOPEX/Poseidon, SPOT-2, SPOT-3, SPOT-4, SPOT-5, Envisat and Jason-1 were processed and all the analysis centers produced weekly SINEX files in either variance-covariance or normal equation format. The processing by the analysis centers used the latest GRACE-derived gravity models, forward modelling of atmospheric gravity, updates to the radiation pressure modelling to improve the DORIS geocenter solutions, denser parameterization of empirically determined drag coefficients to improve station and EOP solutions, especially near the solar maximum in 2001-2002, updated troposphere mapping functions, and an ITRF2005-derived station set for orbit determination, DPOD2005. The CATREF software was used to process the weekly AC solutions, and produce three iterations of an IDS global weekly combination. Between the development of the initial solution IDS-1, and the final solution, IDS-3, the ACs improved their analysis strategies and submitted updated solutions to eliminate troposphere-derived biases in the solution scale, to reduce drag-related degradations in station positioning, and to refine the estimation strategy to improve the combination geocenter solution. An analysis of the frequency content of the individual AC geocenter and scale solutions was used as the basis to define the scale and geocenter of the IDS-3 combination. The final IDS-3 combination has an internal position consistency (WRMS) that is 15 to 20 mm before 2002 and 8 to 10 mm after 2002, when 4 or 5 satellites contribute to the weekly solutions. The final IDS-3 combination includes solutions for 130 DORIS stations on 67 different sites of which 35 have occupations over 16 years (1993.0-2009.0). The EOPs from the IDS-3 combination were compared with the IERS 05 C04 time series and the RMS agreement was 0.24 mas and 0.35 mas for the X and Y components of polar motion. The comparison to ITRF2005 in station position shows an agreement of 6 to 8 mm RMS in horizontal and 10.3 mm in height. The RMS comparison to ITRF2005 in station velocity is at 1.8 mm/year on the East component, to 1.2 mm/year in North component and 1.6 mm/year in height.

Statistical techniques applied to aerial radiometric surveys (STAARS): principal components analysis user's manual. [NURE program

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

Koch, C.D.; Pirkle, F.L.; Schmidt, J.S.

1981-01-01

A Principal Components Analysis (PCA) has been written to aid in the interpretation of multivariate aerial radiometric data collected by the US Department of Energy (DOE) under the National Uranium Resource Evaluation (NURE) program. The variations exhibited by these data have been reduced and classified into a number of linear combinations by using the PCA program. The PCA program then generates histograms and outlier maps of the individual variates. Black and white plots can be made on a Calcomp plotter by the application of follow-up programs. All programs referred to in this guide were written for a DEC-10. From thismore » analysis a geologist may begin to interpret the data structure. Insight into geological processes underlying the data may be obtained.« less

Correlation between the pattern volatiles and the overall aroma of wild edible mushrooms.

PubMed

de Pinho, P Guedes; Ribeiro, Bárbara; Gonçalves, Rui F; Baptista, Paula; Valentão, Patrícia; Seabra, Rosa M; Andrade, Paula B

2008-03-12

Volatile and semivolatile components of 11 wild edible mushrooms, Suillus bellini, Suillus luteus, Suillus granulatus, Tricholomopsis rutilans, Hygrophorus agathosmus, Amanita rubescens, Russula cyanoxantha, Boletus edulis, Tricholoma equestre, Fistulina hepatica, and Cantharellus cibarius, were determined by headspace solid-phase microextraction (HS-SPME) and by liquid extraction combined with gas chromatography-mass spectrometry (GC-MS). Fifty volatiles and nonvolatiles components were formally identified and 13 others were tentatively identified. Using sensorial analysis, the descriptors "mushroomlike", "farm-feed", "floral", "honeylike", "hay-herb", and "nutty" were obtained. A correlation between sensory descriptors and volatiles was observed by applying multivariate analysis (principal component analysis and agglomerative hierarchic cluster analysis) to the sensorial and chemical data. The studied edible mushrooms can be divided in three groups. One of them is rich in C8 derivatives, such as 3-octanol, 1-octen-3-ol, trans-2-octen-1-ol, 3-octanone, and 1-octen-3-one; another one is rich in terpenic volatile compounds; and the last one is rich in methional. The presence and contents of these compounds give a considerable contribution to the sensory characteristics of the analyzed species.

Identification of oligosaccharides from histopathological sections by MALDI imaging mass spectrometry.

PubMed

Yamada, Masanori; Yao, Ikuko; Hayasaka, Takahiro; Ushijima, Masaru; Matsuura, Masaaki; Takada, Hideho; Shikata, Nobuaki; Setou, Mitsutoshi; Kwon, A-Hon; Ito, Seiji

2012-02-01

Direct tissue analysis using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) provides the means for in situ molecular analysis of a wide variety of biomolecules. This technology--known as imaging mass spectrometry (IMS)--allows the measurement of biomolecules in their native biological environments without the need for target-specific reagents such as antibodies. In this study, we applied the IMS technique to formalin-fixed paraffin-embedded samples to identify a substance(s) responsible for the intestinal obstruction caused by an unidentified foreign body. In advance of IMS analysis, some pretreatments were applied. After the deparaffinization of sections, samples were subjected to enzyme digestion. The sections co-crystallized with matrix were desorbed and ionized by a laser pulse with scanning. A combination of α-amylase digestion and the 2,5-dihydroxybenzoic acid matrix gave the best mass spectrum. With the IMS Convolution software which we developed, we could automatically extract meaningful signals from the IMS datasets. The representative peak values were m/z 1,013, 1,175, 1,337, 1,499, 1,661, 1,823, and 1,985. Thus, it was revealed that the material was polymer with a 162-Da unit size, calculated from the even intervals. In comparison with the mass spectra of the histopathological specimen and authentic materials, the main component coincided with amylopectin rather than amylose. Tandem MS analysis proved that the main components were oligosaccharides. Finally, we confirmed the identification of amylopectin by staining with periodic acid-Schiff and iodine. These results for the first time show the advantages of MALDI-IMS in combination with enzyme digestion for the direct analysis of oligosaccharides as a major component of histopathological samples.

Grouping individual independent BOLD effects: a new way to ICA group analysis

NASA Astrophysics Data System (ADS)

Duann, Jeng-Ren; Jung, Tzyy-Ping; Sejnowski, Terrence J.; Makeig, Scott

2009-04-01

A new group analysis method to summarize the task-related BOLD responses based on independent component analysis (ICA) was presented. As opposite to the previously proposed group ICA (gICA) method, which first combined multi-subject fMRI data in either temporal or spatial domain and applied ICA decomposition only once to the combined fMRI data to extract the task-related BOLD effects, the method presented here applied ICA decomposition to the individual subjects' fMRI data to first find the independent BOLD effects specifically for each individual subject. Then, the task-related independent BOLD component was selected among the resulting independent components from the single-subject ICA decomposition and hence grouped across subjects to derive the group inference. In this new ICA group analysis (ICAga) method, one does not need to assume that the task-related BOLD time courses are identical across brain areas and subjects as used in the grand ICA decomposition on the spatially concatenated fMRI data. Neither does one need to assume that after spatial normalization, the voxels at the same coordinates represent exactly the same functional or structural brain anatomies across different subjects. These two assumptions have been problematic given the recent BOLD activation evidences. Further, since the independent BOLD effects were obtained from each individual subject, the ICAga method can better account for the individual differences in the task-related BOLD effects. Unlike the gICA approach whereby the task-related BOLD effects could only be accounted for by a single unified BOLD model across multiple subjects. As a result, the newly proposed method, ICAga, was able to better fit the task-related BOLD effects at individual level and thus allow grouping more appropriate multisubject BOLD effects in the group analysis.

[Studies on the brand traceability of milk powder based on NIR spectroscopy technology].

PubMed

Guan, Xiao; Gu, Fang-Qing; Liu, Jing; Yang, Yong-Jian

2013-10-01

Brand traceability of several different kinds of milk powder was studied by combining near infrared spectroscopy diffuse reflectance mode with soft independent modeling of class analogy (SIMCA) in the present paper. The near infrared spectrum of 138 samples, including 54 Guangming milk powder samples, 43 Netherlands samples, and 33 Nestle samples and 8 Yili samples, were collected. After pretreatment of full spectrum data variables in training set, principal component analysis was performed, and the contribution rate of the cumulative variance of the first three principal components was about 99.07%. Milk powder principal component regression model based on SIMCA was established, and used to classify the milk powder samples in prediction sets. The results showed that the recognition rate of Guangming milk powder, Netherlands milk powder and Nestle milk powder was 78%, 75% and 100%, the rejection rate was 100%, 87%, and 88%, respectively. Therefore, the near infrared spectroscopy combined with SIMCA model can classify milk powder with high accuracy, and is a promising identification method of milk powder variety.

Depression-Burnout Overlap in Physicians

PubMed Central

Wurm, Walter; Vogel, Katrin; Holl, Anna; Ebner, Christoph; Bayer, Dietmar; Mörkl, Sabrina; Szilagyi, Istvan-Szilard; Hotter, Erich; Kapfhammer, Hans-Peter; Hofmann, Peter

2016-01-01

Background Whether burnout is a distinct phenomenon rather than a type of depression and whether it is a syndrome, limited to three “core” components (emotional exhaustion, depersonalization and low personal accomplishment) are subjects of current debate. We investigated the depression-burnout overlap, and the pertinence of these three components in a large, representative sample of physicians. Methods In a cross-sectional study, all Austrian physicians were invited to answer a questionnaire that included the Major Depression Inventory (MDI), the Hamburg Burnout Inventory (HBI), as well as demographic and job-related parameters. Of the 40093 physicians who received an invitation, a total of 6351 (15.8%) participated. The data of 5897 participants were suitable for analysis. Results Of the participants, 10.3% were affected by major depression. Our study results suggest that potentially 50.7% of the participants were affected by symptoms of burnout. Compared to physicians unaffected by burnout, the odds ratio of suffering from major depression was 2.99 (95% CI 2.21–4.06) for physicians with mild, 10.14 (95% CI 7.58–13.59) for physicians with moderate, 46.84 (95% CI 35.25–62.24) for physicians with severe burnout and 92.78 (95% CI 62.96–136.74) for the 3% of participants with the highest HBI_sum (sum score of all ten HBI components). The HBI components Emotional Exhaustion, Personal Accomplishment and Detachment (representing depersonalization) tend to correlate more highly with the main symptoms of major depression (sadness, lack of interest and lack of energy) than with each other. A combination of the HBI components Emotional Exhaustion, Helplessness, Inner Void and Tedium (adj.R2 = 0.92) explained more HBI_sum variance than the three “core” components (adj.R2 = 0.85) of burnout combined. Cronbach’s alpha for Emotional Exhaustion, Helplessness, Inner Void and Tedium combined was 0.90 compared to α = 0.54 for the combination of the three “core” components. Conclusions This study demonstrates the overlap of burnout and major depression in terms of symptoms and the deficiency of the three-dimensional concept of burnout. In our opinion, it might be preferable to use multidimensional burnout inventories in combination with valid depression scales than to rely exclusively on MBI when clinically assessing burnout. PMID:26930395

Recent Developments in Microsystems Fabricated by the Liga-Technique

NASA Technical Reports Server (NTRS)

Schulz, J.; Bade, K.; El-Kholi, A.; Hein, H.; Mohr, J.

1995-01-01

As an example of microsystems fabricated by the LIGA-technique (x-ray lithography, electroplating and molding), three systems are described and characterized: a triaxial acceleration sensor system, a micro-optical switch, and a microsystem for the analysis of pollutants. The fabrication technologies are reviewed with respect to the key components of the three systems: an acceleration sensor, and electrostatic actuator, and a spectrometer made by the LIGA-technique. Aa micro-pump and micro-valve made by using micromachined tools for molding and optical fiber imaging are made possible by combining LIGA and anisotropic etching of silicon in a batch process. These examples show that the combination of technologies and components is the key to complex microsystems. The design of such microsystems will be facilitated is standardized interfaces are available.

Physical Parameters of Components in Close Binary Systems: IV

NASA Astrophysics Data System (ADS)

Gazeas, K. D.; Baran, A.; Niarchos, P.; Zola, S.; Kreiner, J. M.; Ogloza, W.; Rucinski, S. M.; Zakrzewski, B.; Siwak, M.; Pigulski, A.; Drozdz, M.

2005-03-01

The paper presents new geometric, photometric and absolute parameters, derived from combined spectroscopic and photometric solutions, for ten contact binary systems. The analysis shows that three systems (EF Boo, GM Dra and SW Lac) are of W-type with shallow to moderate contact. Seven systems (V417 Aql, AH Aur, YY CrB, UX Eri, DZ Psc, GR Vir and NN Vir) are of A-type in a deep contact configuration. For six systems (V417 Aql, YY CrB, GM Dra, UX Eri, SW Lac and GR Vir) a spot model is introduced to explain the O'Connell effect in their light curves. The photometric and geometric elements of the systems are combined with the spectroscopic data taken at David Dunlap Observatory to yield the absolute parameters of the components.

An implementation of the programming structural synthesis system (PROSSS)

NASA Technical Reports Server (NTRS)

Rogers, J. L., Jr.; Sobieszczanski-Sobieski, J.; Bhat, R. B.

1981-01-01

A particular implementation of the programming structural synthesis system (PROSSS) is described. This software system combines a state of the art optimization program, a production level structural analysis program, and user supplied, problem dependent interface programs. These programs are combined using standard command language features existing in modern computer operating systems. PROSSS is explained in general with respect to this implementation along with the steps for the preparation of the programs and input data. Each component of the system is described in detail with annotated listings for clarification. The components include options, procedures, programs and subroutines, and data files as they pertain to this implementation. An example exercising each option in this implementation to allow the user to anticipate the type of results that might be expected is presented.

Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data.

PubMed

Calhoun, V D; Adali, T; Giuliani, N R; Pekar, J J; Kiehl, K A; Pearlson, G D

2006-01-01

The acquisition of both structural MRI (sMRI) and functional MRI (fMRI) data for a given study is a very common practice. However, these data are typically examined in separate analyses, rather than in a combined model. We propose a novel methodology to perform independent component analysis across image modalities, specifically, gray matter images and fMRI activation images as well as a joint histogram visualization technique. Joint independent component analysis (jICA) is used to decompose a matrix with a given row consisting of an fMRI activation image resulting from auditory oddball target stimuli and an sMRI gray matter segmentation image, collected from the same individual. We analyzed data collected on a group of schizophrenia patients and healthy controls using the jICA approach. Spatially independent joint-components are estimated and resulting components were further analyzed only if they showed a significant difference between patients and controls. The main finding was that group differences in bilateral parietal and frontal as well as posterior temporal regions in gray matter were associated with bilateral temporal regions activated by the auditory oddball target stimuli. A finding of less patient gray matter and less hemodynamic activity for target detection in these bilateral anterior temporal lobe regions was consistent with previous work. An unexpected corollary to this finding was that, in the regions showing the largest group differences, gray matter concentrations were larger in patients vs. controls, suggesting that more gray matter may be related to less functional connectivity in the auditory oddball fMRI task. Hum Brain Mapp, 2005. (c) 2005 Wiley-Liss, Inc.

Insights into the interaction between carbamazepine and natural dissolved organic matter in the Yangtze Estuary using fluorescence excitation-emission matrix spectra coupled with parallel factor analysis.

PubMed

Wang, Ying; Zhang, Manman; Fu, Jun; Li, Tingting; Wang, Jinggang; Fu, Yingyu

2016-10-01

The interaction between carbamazepine (CBZ) and dissolved organic matter (DOM) from three zones (the nearshore, the river channel, and the coastal areas) in the Yangtze Estuary was investigated using fluorescence quenching titration combined with excitation emission matrix spectra and parallel factor analysis (PARAFAC). The complexation between CBZ and DOM was demonstrated by the increase in hydrogen bonding and the disappearance of the C=O stretch obtained from the Fourier transform infrared spectroscopy analysis. The results indicated that two protein-like substances (component 2 and component3) and two humic-like substances (component 1 and 4) were identified in the DOM from the Yangtze Estuary. The fluorescence quenching curves of each component with the addition of CBZ and the Ryan and Weber model calculation results both demonstrated that the different components exhibited different complexation activities with CBZ. The protein-like components had a stronger affinity with CBZ than did the humic-like substances. On the other hand, the autochthonous tyrosine-like C2 played an important role in the complexation with DOM from the river channel and coastal areas, while C3 influenced by anthropogenic activities showed an obvious effect in the nearshore area. DOMs from the river channel have the highest binding capacity for CBZ, which may ascribe to the relatively high phenol content group in the DOM.

[Research on discrimination of cabbage and weeds based on visible and near-infrared spectrum analysis].

PubMed

Zu, Qin; Zhao, Chun-Jiang; Deng, Wei; Wang, Xiu

2013-05-01

The automatic identification of weeds forms the basis for precision spraying of crops infest. The canopy spectral reflectance within the 350-2 500 nm band of two strains of cabbages and five kinds of weeds such as barnyard grass, setaria, crabgrass, goosegrass and pigweed was acquired by ASD spectrometer. According to the spectral curve characteristics, the data in different bands were compressed with different levels to improve the operation efficiency. Firstly, the spectrum was denoised in accordance with the different order of multiple scattering correction (MSC) method and Savitzky-Golay (SG) convolution smoothing method set by different parameters, then the model was built by combining the principal component analysis (PCA) method to extract principal components, finally all kinds of plants were classified by using the soft independent modeling of class analogy (SIMCA) taxonomy and the classification results were compared. The tests results indicate that after the pretreatment of the spectral data with the method of the combination of MSC and SG set with 3rd order, 5th degree polynomial, 21 smoothing points, and the top 10 principal components extraction using PCA as a classification model input variable, 100% correct classification rate was achieved, and it is able to identify cabbage and several kinds of common weeds quickly and nondestructively.

Effectiveness of Behavioral Therapy for Chronic Low Back Pain: A Component Analysis.

ERIC Educational Resources Information Center

Turner, Judith A.; And Others

1990-01-01

Evaluated effects of group behavioral therapy including aerobic exercise, behavioral therapy alone, and aerobic exercise alone on pain and physical and psychological disability among mildly disabled chronic low-back-pain patients (n=96). The combined behavioral therapy and exercise group improved significantly more pretreatment to posttreatment…

Neuromorphic Computing: A Post-Moore's Law Complementary Architecture

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

Schuman, Catherine D; Birdwell, John Douglas; Dean, Mark

2016-01-01

We describe our approach to post-Moore's law computing with three neuromorphic computing models that share a RISC philosophy, featuring simple components combined with a flexible and programmable structure. We envision these to be leveraged as co-processors, or as data filters to provide in situ data analysis in supercomputing environments.

Prototype solar heating and combined heating and cooling systems

NASA Technical Reports Server (NTRS)

1977-01-01

System analysis activities were directed toward refining the heating system parameters. Trade studies were performed to support hardware selections for all systems and for the heating only operational test sites in particular. The heating system qualification tests were supported by predicting qualification test component performance prior to conducting the test.

Characterization of phenolic amides from cortex lycii by ultra high-performance liquid chromatography coupled with LTQ-Orbitrap mass spectrometry

USDA-ARS?s Scientific Manuscript database

High performance liquid chromatography (UPLC) and flow injection electrospray ionization with ion trap mass spectrometry (FIMS) fingerprints combined with the principal component analysis (PCA) were examined for their potential in differentiating commercial organic and conventional sage samples. The...

SELF-ORGANIZING MAPS FOR INTEGRATED ASSESSMENT OF THE MID-ATLANTIC REGION

EPA Science Inventory

A. new method was developed to perform an environmental assessment for the
Mid-Atlantic Region (MAR). This was a combination of the self-organizing map (SOM) neural network and principal component analysis (PCA). The method is capable of clustering ecosystems in terms of envi...

Analysis of Venetian-type glass fragments from the ancient city of Lezha (Albania)

NASA Astrophysics Data System (ADS)

Šmit, Ž.; Stamati, F.; Civici, N.; Vevecka-Priftaj, A.; Kos, M.; Jezeršek, D.

2009-08-01

A series of glasses excavated in the Albanian city of Lezha (ancient Lissos) were analyzed by the combined PIXE-PIGE method in air and by source-excited XRF. The analysis revealed two types of glass that can be identified as façon de Venise glass and its subsequent younger phase, produced by chemically purer components and using As 2O 3 as decolorant.

Spatial and spectral analysis of corneal epithelium injury using hyperspectral images

NASA Astrophysics Data System (ADS)

Md Noor, Siti Salwa; Michael, Kaleena; Marshall, Stephen; Ren, Jinchang

2017-12-01

Eye assessment is essential in preventing blindness. Currently, the existing methods to assess corneal epithelium injury are complex and require expert knowledge. Hence, we have introduced a non-invasive technique using hyperspectral imaging (HSI) and an image analysis algorithm of corneal epithelium injury. Three groups of images were compared and analyzed, namely healthy eyes, injured eyes, and injured eyes with stain. Dimensionality reduction using principal component analysis (PCA) was applied to reduce massive data and redundancies. The first 10 principal components (PCs) were selected for further processing. The mean vector of 10 PCs with 45 pairs of all combinations was computed and sent to two classifiers. A quadratic Bayes normal classifier (QDC) and a support vector classifier (SVC) were used in this study to discriminate the eleven eyes into three groups. As a result, the combined classifier of QDC and SVC showed optimal performance with 2D PCA features (2DPCA-QDSVC) and was utilized to classify normal and abnormal tissues, using color image segmentation. The result was compared with human segmentation. The outcome showed that the proposed algorithm produced extremely promising results to assist the clinician in quantifying a cornea injury.

Evaluation of the anxiolytic properties of myristicin, a component of nutmeg, in the male Sprague-Dawley rat.

PubMed

Leiter, Emily; Hitchcock, Gavin; Godwin, Stuart; Johnson, Michelle; Sedgwick, William; Jones, Wendy; McCall, Suzanne; Ceremuga, Thomas E

2011-04-01

The purpose of this study was to investigate the anxiolytic effects of myristicin, a major compound found in nutmeg, and its potential interaction with the gamma-aminobutyric acid (GABA(A)) receptor in male Sprague-Dawley rats. Nutmeg has traditionally been used as a spice in food preparation and as an herbal remedy in the treatment of many medical conditions, including anxiety. Fifty-five rats were divided equally into 5 groups: control (vehicle); myristicin; midazolam (positive control); flumazenil and myristicin; and midazolam and myristicin. The behavioral component of anxiety was examined by using the elevated plus-maze (open-arm and closed-arm times) along with analysis of gross and fine motor movements. Data analysis was performed using a 2-tailed multivariate analysis of variance (MANOVA) and least significant difference post-hoc test. Our data suggest that myristicin does not decrease anxiety by modulation of the GABA(A) receptor but may promote anxiogenesis. When myristicin was combined with midazolam, an antagonist-like effect similar to the flumazenil and myristicin combination was exhibited by a decrease in anxiolysis compared with the midazolam-only group. Myristicin may antagonize the anxiolytic effects of midazolam, increase anxiety, and affect motor movements.

Identification of pulmonary edema in forensic autopsy cases of fatal anaphylactic shock using Fourier transform infrared microspectroscopy.

PubMed

Lin, Hancheng; Luo, Yiwen; Wang, Lei; Deng, Kaifei; Sun, Qiran; Fang, Ruoxi; Wei, Xin; Zha, Shuai; Wang, Zhenyuan; Huang, Ping

2018-03-01

Anaphylaxis is a rapid allergic reaction that may cause sudden death. Currently, postmortem diagnosis of anaphylactic shock is sometimes difficult and often achieved through exclusion. The aim of our study was to investigate whether Fourier transform infrared (FTIR) microspectroscopy combined with pattern recognition methods would be complementary to traditional methods and provide a more accurate postmortem diagnosis of fatal anaphylactic shock. First, the results of spectral peak area analysis showed that the pulmonary edema fluid of the fatal anaphylactic shock group was richer in protein components than the control group, which included mechanical asphyxia, brain injury, and acute cardiac death. Subsequently, principle component analysis (PCA) was performed and showed that the anaphylactic shock group contained more turn and α-helix protein structures as well as less tyrosine-rich proteins than the control group. Ultimately, a partial least-square discriminant analysis (PLS-DA) model combined with a variables selection method called the genetic algorithm (GA) was built and demonstrated good separation between these two groups. This pilot study demonstrates that FTIR microspectroscopy has the potential to be an effective aid for postmortem diagnosis of fatal anaphylactic shock.

Removal of acetaminophen and naproxen by combined coagulation and adsorption using biochar: influence of combined sewer overflow components.

PubMed

Jung, Chanil; Oh, Jeill; Yoon, Yeomin

2015-07-01

The combined coagulation and adsorption of targeted acetaminophen and naproxen using activated biochar and aluminum sulfate were studied under various synthetic "combined sewer overflow" (CSO) conditions. The biochar demonstrated better adsorption performance for both acetaminophen and naproxen (removal, 94.1 and 97.7%, respectively) than that of commercially available powdered activated carbon (removal, 81.6 and 94.1%, respectively) due to superior carbonaceous structure and surface properties examined by nuclear magnetic resonance analysis. The adsorption of naproxen was more favorable, occupying active adsorption sites on the adsorbents by naproxen due to its higher adsorption affinity compared to acetaminophen. Three classified CSO components (i.e., representing hydrophobic organics, hydrophilic organics, and inorganics) played different roles in the adsorption of both adsorbates, resulted in inhibition by humic acid complexation or metal ligands and negative electrostatic repulsion under adsorption and coagulation combined system. Adsorption alone with biochar was determined to be the most effective adsorptive condition for the removal of both acetaminophen and naproxen under various CSO conditions, while both coagulation alone and combined adsorption and coagulation failed to remove the acetaminophen and naproxen adequately due to an increase in ionic strength in the presence of spiked aluminum species derived from the coagulant.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy.

PubMed

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-25

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety. Copyright © 2014 Elsevier B.V. All rights reserved.

Chromophoric dissolved organic matter (CDOM) variability in Barataria Basin using excitation-emission matrix (EEM) fluorescence and parallel factor analysis (PARAFAC).

PubMed

Singh, Shatrughan; D'Sa, Eurico J; Swenson, Erick M

2010-07-15

Chromophoric dissolved organic matter (CDOM) variability in Barataria Basin, Louisiana, USA,was examined by excitation emission matrix (EEM) fluorescence combined with parallel factor analysis (PARAFAC). CDOM optical properties of absorption and fluorescence at 355nm along an axial transect (36 stations) during March, April, and May 2008 showed an increasing trend from the marine end member to the upper basin with mean CDOM absorption of 11.06 + or - 5.01, 10.05 + or - 4.23, 11.67 + or - 6.03 (m(-)(1)) and fluorescence 0.80 + or - 0.37, 0.78 + or - 0.39, 0.75 + or - 0.51 (RU), respectively. PARAFAC analysis identified two terrestrial humic-like (component 1 and 2), one non-humic like (component 3), and one soil derived humic acid like (component 4) components. The spatial variation of the components showed an increasing trend from station 1 (near the mouth of basin) to station 36 (end member of bay; upper basin). Deviations from this increasing trend were observed at a bayou channel with very high chlorophyll-a concentrations especially for component 3 in May 2008 that suggested autochthonous production of CDOM. The variability of components with salinity indicated conservative mixing along the middle part of the transect. Component 1 and 4 were found to be relatively constant, while components 2 and 3 revealed an inverse relationship for the sampling period. Total organic carbon showed increasing trend for each of the components. An increase in humification and a decrease in fluorescence indices along the transect indicated an increase in terrestrial derived organic matter and reduced microbial activity from lower to upper basin. The use of these indices along with PARAFAC results improved dissolved organic matter characterization in the Barataria Basin. Copyright 2010 Elsevier B.V. All rights reserved.

Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images

PubMed Central

Gutmann, Michael U.; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation. PMID:24533049

Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

PubMed

Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

Systems Perturbation Analysis of a Large-Scale Signal Transduction Model Reveals Potentially Influential Candidates for Cancer Therapeutics

PubMed Central

Puniya, Bhanwar Lal; Allen, Laura; Hochfelder, Colleen; Majumder, Mahbubul; Helikar, Tomáš

2016-01-01

Dysregulation in signal transduction pathways can lead to a variety of complex disorders, including cancer. Computational approaches such as network analysis are important tools to understand system dynamics as well as to identify critical components that could be further explored as therapeutic targets. Here, we performed perturbation analysis of a large-scale signal transduction model in extracellular environments that stimulate cell death, growth, motility, and quiescence. Each of the model’s components was perturbed under both loss-of-function and gain-of-function mutations. Using 1,300 simulations under both types of perturbations across various extracellular conditions, we identified the most and least influential components based on the magnitude of their influence on the rest of the system. Based on the premise that the most influential components might serve as better drug targets, we characterized them for biological functions, housekeeping genes, essential genes, and druggable proteins. The most influential components under all environmental conditions were enriched with several biological processes. The inositol pathway was found as most influential under inactivating perturbations, whereas the kinase and small lung cancer pathways were identified as the most influential under activating perturbations. The most influential components were enriched with essential genes and druggable proteins. Moreover, known cancer drug targets were also classified in influential components based on the affected components in the network. Additionally, the systemic perturbation analysis of the model revealed a network motif of most influential components which affect each other. Furthermore, our analysis predicted novel combinations of cancer drug targets with various effects on other most influential components. We found that the combinatorial perturbation consisting of PI3K inactivation and overactivation of IP3R1 can lead to increased activity levels of apoptosis-related components and tumor-suppressor genes, suggesting that this combinatorial perturbation may lead to a better target for decreasing cell proliferation and inducing apoptosis. Finally, our approach shows a potential to identify and prioritize therapeutic targets through systemic perturbation analysis of large-scale computational models of signal transduction. Although some components of the presented computational results have been validated against independent gene expression data sets, more laboratory experiments are warranted to more comprehensively validate the presented results. PMID:26904540

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle.

PubMed

Mateescu, Raluca G; Garrick, Dorian J; Reecy, James M

2017-01-01

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis.

PubMed

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-11-22

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7-15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: "Average refraction", "Acceleration" and the combination of "Myopia stabilization" and "Late onset of refraction progress". In regression models, younger children with more severe myopia were associated with larger "Acceleration". The risk factors of "Acceleration" included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with "Stabilization", and increased outdoor time was related to "Late onset of refraction progress". We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression.

Patterns in longitudinal growth of refraction in Southern Chinese children: cluster and principal component analysis

PubMed Central

Chen, Yanxian; Chang, Billy Heung Wing; Ding, Xiaohu; He, Mingguang

2016-01-01

In the present study we attempt to use hypothesis-independent analysis in investigating the patterns in refraction growth in Chinese children, and to explore the possible risk factors affecting the different components of progression, as defined by Principal Component Analysis (PCA). A total of 637 first-born twins in Guangzhou Twin Eye Study with 6-year annual visits (baseline age 7–15 years) were available in the analysis. Cluster 1 to 3 were classified after a partitioning clustering, representing stable, slow and fast progressing groups of refraction respectively. Baseline age and refraction, paternal refraction, maternal refraction and proportion of two myopic parents showed significant differences across the three groups. Three major components of progression were extracted using PCA: “Average refraction”, “Acceleration” and the combination of “Myopia stabilization” and “Late onset of refraction progress”. In regression models, younger children with more severe myopia were associated with larger “Acceleration”. The risk factors of “Acceleration” included change of height and weight, near work, and parental myopia, while female gender, change of height and weight were associated with “Stabilization”, and increased outdoor time was related to “Late onset of refraction progress”. We therefore concluded that genetic and environmental risk factors have different impacts on patterns of refraction progression. PMID:27874105

Structures and Dynamics Division research and technology plans, FY 1982

NASA Technical Reports Server (NTRS)

Bales, K. S.

1982-01-01

Computational devices to improve efficiency for structural calculations are assessed. The potential of large arrays of microprocessors operating in parallel for finite element analysis is defined, and the impact of specialized computer hardware on static, dynamic, thermal analysis in the optimization of structural analysis and design calculations is determined. General aviation aircraft crashworthiness and occupant survivability is also considered. Mechanics technology required for design coefficient, fault tolerant advanced composite aircraft components subject to combined loads, impact, postbuckling effects and local discontinuities are developed.

Modeling energy/economy interactions for conservation and renewable energy-policy analysis

NASA Astrophysics Data System (ADS)

Groncki, P. J.

Energy policy and the implications for policy analysis and the methodological tools are discussed. The evolution of one methodological approach and the combined modeling system of the component models, their evolution in response to changing analytic needs, and the development of the integrated framework are reported. The analyses performed over the past several years are summarized. The current philosophy behind energy policy is discussed and compared to recent history. Implications for current policy analysis and methodological approaches are drawn.

On 3D inelastic analysis methods for hot section components

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Chen, P. C.; Dame, L. T.; Holt, R. V.; Huang, H.; Hartle, M.; Gellin, S.; Allen, D. H.; Haisler, W. E.

1986-01-01

Accomplishments are described for the 2-year program, to develop advanced 3-D inelastic structural stress analysis methods and solution strategies for more accurate and cost effective analysis of combustors, turbine blades and vanes. The approach was to develop a matrix of formulation elements and constitutive models. Three constitutive models were developed in conjunction with optimized iterating techniques, accelerators, and convergence criteria within a framework of dynamic time incrementing. Three formulations models were developed; an eight-noded mid-surface shell element, a nine-noded mid-surface shell element and a twenty-noded isoparametric solid element. A separate computer program was developed for each combination of constitutive model-formulation model. Each program provides a functional stand alone capability for performing cyclic nonlinear structural analysis. In addition, the analysis capabilities incorporated into each program can be abstracted in subroutine form for incorporation into other codes or to form new combinations.

The 3D inelastic analysis methods for hot section components

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Maffeo, R. J.; Tipton, M. T.; Weber, G.

1992-01-01

A two-year program to develop advanced 3D inelastic structural stress analysis methods and solution strategies for more accurate and cost effective analysis of combustors, turbine blades, and vanes is described. The approach was to develop a matrix of formulation elements and constitutive models. Three constitutive models were developed in conjunction with optimized iterating techniques, accelerators, and convergence criteria within a framework of dynamic time incrementing. Three formulation models were developed: an eight-noded midsurface shell element; a nine-noded midsurface shell element; and a twenty-noded isoparametric solid element. A separate computer program has been developed for each combination of constitutive model-formulation model. Each program provides a functional stand alone capability for performing cyclic nonlinear structural analysis. In addition, the analysis capabilities incorporated into each program can be abstracted in subroutine form for incorporation into other codes or to form new combinations.

Adaptive Postural Control for Joint Immobilization during Multitask Performance

PubMed Central

Hsu, Wei-Li

2014-01-01

Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21–29 yr) without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM) stability were examined using uncontrolled manifold (UCM) analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM); the second leads to COM position variability (VORT). The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM) was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT) tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements. PMID:25329477

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map

PubMed Central

An, Yan; Zou, Zhihong; Li, Ranran

2016-01-01

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009–2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data. PMID:26761018

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map.

PubMed

An, Yan; Zou, Zhihong; Li, Ranran

2016-01-08

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009-2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data.

Molecular diversity of toxic components from the scorpion Heterometrus petersii venom revealed by proteomic and transcriptome analysis.

PubMed

Ma, Yibao; Zhao, Yong; Zhao, Ruiming; Zhang, Weiping; He, Yawen; Wu, Yingliang; Cao, Zhijian; Guo, Lin; Li, Wenxin

2010-07-01

Scorpion venoms contain a vast untapped reservoir of natural products, which have the potential for medicinal value in drug discovery. In this study, toxin components from the scorpion Heterometrus petersii venom were evaluated by transcriptome and proteome analysis.Ten known families of venom peptides and proteins were identified, which include: two families of potassium channel toxins, four families of antimicrobial and cytolytic peptides,and one family from each of the calcium channel toxins, La1-like peptides, phospholipase A2,and the serine proteases. In addition, we also identified 12 atypical families, which include the acid phosphatases, diuretic peptides, and ten orphan families. From the data presented here, the extreme diversity and convergence of toxic components in scorpion venom was uncovered. Our work demonstrates the power of combining transcriptomic and proteomic approaches in the study of animal venoms.

Integrating a geographic information system, a scientific visualization system and an orographic precipitation model

USGS Publications Warehouse

Hay, L.; Knapp, L.

1996-01-01

Investigating natural, potential, and man-induced impacts on hydrological systems commonly requires complex modelling with overlapping data requirements, and massive amounts of one- to four-dimensional data at multiple scales and formats. Given the complexity of most hydrological studies, the requisite software infrastructure must incorporate many components including simulation modelling, spatial analysis and flexible, intuitive displays. There is a general requirement for a set of capabilities to support scientific analysis which, at this time, can only come from an integration of several software components. Integration of geographic information systems (GISs) and scientific visualization systems (SVSs) is a powerful technique for developing and analysing complex models. This paper describes the integration of an orographic precipitation model, a GIS and a SVS. The combination of these individual components provides a robust infrastructure which allows the scientist to work with the full dimensionality of the data and to examine the data in a more intuitive manner.

Analysis of observations of the dwarf nova pegasi 2010

NASA Astrophysics Data System (ADS)

Shimansky, V. V.; Mitrofanova, A. A.; Borisov, N. V.; Gabdeev, M. M.

2013-06-01

Analysis of photometric and spectroscopic observations of GSC 02197-00886 at the outburst maximum (on May 8, 2010) and at the stage of relaxation towards the quiescent (on August 4, 2010) was performed. Radiation of an optically thick accretion disc with a hot boundary layer dominates the spectra, which are consistent with the spectra of a WZ Sge-type dwarf novae. In the relaxation phase, an optically thin accretion disc with radiation in the HI and HeI emission lines is observed against the background of the absorption spectrum of a white dwarf. The parameters of GSC 02197-00886, which were determined by combining the radial velocities of the components with the assumption that the secondary component is close to mainsequence stars, differ significantly from the parameters that characterize other WZ Sge-type systems. We hypothesize that the secondary component was excited in the course of the outburst and experienced long-lasting relaxation towards the main-sequence state.

Spectral compression algorithms for the analysis of very large multivariate images

DOEpatents

Keenan, Michael R.

2007-10-16

A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

Author name recognition in degraded journal images

NASA Astrophysics Data System (ADS)

de Bodard de la Jacopière, Aliette; Likforman-Sulem, Laurence

2006-01-01

A method for extracting names in degraded documents is presented in this article. The documents targeted are images of photocopied scientific journals from various scientific domains. Due to the degradation, there is poor OCR recognition, and pieces of other articles appear on the sides of the image. The proposed approach relies on the combination of a low-level textual analysis and an image-based analysis. The textual analysis extracts robust typographic features, while the image analysis selects image regions of interest through anchor components. We report results on the University of Washington benchmark database.

Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis

NASA Astrophysics Data System (ADS)

E, Jianwei; Bao, Yanling; Ye, Jimin

2017-10-01

As one of the most vital energy resources in the world, crude oil plays a significant role in international economic market. The fluctuation of crude oil price has attracted academic and commercial attention. There exist many methods in forecasting the trend of crude oil price. However, traditional models failed in predicting accurately. Based on this, a hybrid method will be proposed in this paper, which combines variational mode decomposition (VMD), independent component analysis (ICA) and autoregressive integrated moving average (ARIMA), called VMD-ICA-ARIMA. The purpose of this study is to analyze the influence factors of crude oil price and predict the future crude oil price. Major steps can be concluded as follows: Firstly, applying the VMD model on the original signal (crude oil price), the modes function can be decomposed adaptively. Secondly, independent components are separated by the ICA, and how the independent components affect the crude oil price is analyzed. Finally, forecasting the price of crude oil price by the ARIMA model, the forecasting trend demonstrates that crude oil price declines periodically. Comparing with benchmark ARIMA and EEMD-ICA-ARIMA, VMD-ICA-ARIMA can forecast the crude oil price more accurately.

Impacts of a flash flood on drinking water quality: case study of areas most affected by the 2012 Beijing flood.

PubMed

Sun, Rubao; An, Daizhi; Lu, Wei; Shi, Yun; Wang, Lili; Zhang, Can; Zhang, Ping; Qi, Hongjuan; Wang, Qiang

2016-02-01

In this study, we present a method for identifying sources of water pollution and their relative contributions in pollution disasters. The method uses a combination of principal component analysis and factor analysis. We carried out a case study in three rural villages close to Beijing after torrential rain on July 21, 2012. Nine water samples were analyzed for eight parameters, namely turbidity, total hardness, total dissolved solids, sulfates, chlorides, nitrates, total bacterial count, and total coliform groups. All of the samples showed different degrees of pollution, and most were unsuitable for drinking water as concentrations of various parameters exceeded recommended thresholds. Principal component analysis and factor analysis showed that two factors, the degree of mineralization and agricultural runoff, and flood entrainment, explained 82.50% of the total variance. The case study demonstrates that this method is useful for evaluating and interpreting large, complex water-quality data sets.

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis.

PubMed

Nesakumar, Noel; Baskar, Chanthini; Kesavan, Srinivasan; Rayappan, John Bosco Balaguru; Alwarappan, Subbiah

2018-05-22

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm -1 with a spectral resolution of 8 cm -1 . In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm -1 , Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm -1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.

Combined proportional and additive residual error models in population pharmacokinetic modelling.

PubMed

Proost, Johannes H

2017-11-15

In pharmacokinetic modelling, a combined proportional and additive residual error model is often preferred over a proportional or additive residual error model. Different approaches have been proposed, but a comparison between approaches is still lacking. The theoretical background of the methods is described. Method VAR assumes that the variance of the residual error is the sum of the statistically independent proportional and additive components; this method can be coded in three ways. Method SD assumes that the standard deviation of the residual error is the sum of the proportional and additive components. Using datasets from literature and simulations based on these datasets, the methods are compared using NONMEM. The different coding of methods VAR yield identical results. Using method SD, the values of the parameters describing residual error are lower than for method VAR, but the values of the structural parameters and their inter-individual variability are hardly affected by the choice of the method. Both methods are valid approaches in combined proportional and additive residual error modelling, and selection may be based on OFV. When the result of an analysis is used for simulation purposes, it is essential that the simulation tool uses the same method as used during analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrated analysis, transcriptome-lipidome, reveals the effects of INO-level (INO2 and INO4) on lipid metabolism in yeast.

PubMed

Chumnanpuen, Pramote; Nookaew, Intawat; Nielsen, Jens

2013-10-16

In the yeast Saccharomyces cerevisiae, genes containing UASINO sequences are regulated by the Ino2/Ino4 and Opi1 transcription factors, and this regulation controls lipid biosynthesis. The expression level of INO2 and INO4 genes (INO-level) at different nutrient limited conditions might lead to various responses in yeast lipid metabolism. In this study, we undertook a global study on how INO-levels (transcription level of INO2 and INO4) affect lipid metabolism in yeast and we also studied the effects of single and double deletions of the two INO-genes (deficient effect). Using 2 types of nutrient limitations (carbon and nitrogen) in chemostat cultures operated at a fixed specific growth rate of 0.1 h-1 and strains having different INO-level, we were able to see the effect on expression level of the genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through combined measurements of the transcriptome, metabolome, and lipidome it was possible to obtain a large dataset that could be used to identify how the INO-level controls lipid metabolism and also establish correlations between the different components. In this study, we undertook a global study on how INO-levels (transcription level of INO2 and INO4) affect lipid metabolism in yeast and we also studied the effects of single and double deletions of the two INO-genes (deficient effect). Using 2 types of nutrient limitations (carbon and nitrogen) in chemostat cultures operated at a fixed specific growth rate of 0.1 h-1 and strains having different INO-level, we were able to see the effect on expression level of the genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through combined measurements of the transcriptome, metabolome, and lipidome it was possible to obtain a large dataset that could be used to identify how the INO-level controls lipid metabolism and also establish correlations between the different components. Our analysis showed the strength of using a combination of transcriptome and lipidome analysis to illustrate the effect of INO-levels on phospholipid metabolism and based on our analysis we established a global regulatory map.

Combining results of multiple search engines in proteomics.

PubMed

Shteynberg, David; Nesvizhskii, Alexey I; Moritz, Robert L; Deutsch, Eric W

2013-09-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques.

Combining Results of Multiple Search Engines in Proteomics*

PubMed Central

Shteynberg, David; Nesvizhskii, Alexey I.; Moritz, Robert L.; Deutsch, Eric W.

2013-01-01

A crucial component of the analysis of shotgun proteomics datasets is the search engine, an algorithm that attempts to identify the peptide sequence from the parent molecular ion that produced each fragment ion spectrum in the dataset. There are many different search engines, both commercial and open source, each employing a somewhat different technique for spectrum identification. The set of high-scoring peptide-spectrum matches for a defined set of input spectra differs markedly among the various search engine results; individual engines each provide unique correct identifications among a core set of correlative identifications. This has led to the approach of combining the results from multiple search engines to achieve improved analysis of each dataset. Here we review the techniques and available software for combining the results of multiple search engines and briefly compare the relative performance of these techniques. PMID:23720762

Validation of Shared and Specific Independent Component Analysis (SSICA) for Between-Group Comparisons in fMRI

PubMed Central

Maneshi, Mona; Vahdat, Shahabeddin; Gotman, Jean; Grova, Christophe

2016-01-01

Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named “shared and specific independent component analysis” (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i.e., components that could be considered “specific” for a group or condition. Here, we investigated the performance of SSICA on realistic simulations, and task fMRI data and compared the results with one of the state-of-the-art group ICA approaches to infer between-group differences. We examined SSICA robustness with respect to the number of allowable extracted specific components and between-group orthogonality assumptions. Furthermore, we proposed a modified formulation of the back-reconstruction method to generate group-level t-statistics maps based on SSICA results. We also evaluated the consistency and specificity of the extracted specific components by SSICA. The results on realistic simulated and real fMRI data showed that SSICA outperforms the regular group ICA approach in terms of reconstruction and classification performance. We demonstrated that SSICA is a powerful data-driven approach to detect patterns of differences in functional connectivity across groups/conditions, particularly in model-free designs such as resting-state fMRI. Our findings in task fMRI show that SSICA confirms results of the general linear model (GLM) analysis and when combined with clustering analysis, it complements GLM findings by providing additional information regarding the reliability and specificity of networks. PMID:27729843

Visualization of Global Sensitivity Analysis Results Based on a Combination of Linearly Dependent and Independent Directions

NASA Technical Reports Server (NTRS)

Davies, Misty D.; Gundy-Burlet, Karen

2010-01-01

A useful technique for the validation and verification of complex flight systems is Monte Carlo Filtering -- a global sensitivity analysis that tries to find the inputs and ranges that are most likely to lead to a subset of the outputs. A thorough exploration of the parameter space for complex integrated systems may require thousands of experiments and hundreds of controlled and measured variables. Tools for analyzing this space often have limitations caused by the numerical problems associated with high dimensionality and caused by the assumption of independence of all of the dimensions. To combat both of these limitations, we propose a technique that uses a combination of the original variables with the derived variables obtained during a principal component analysis.

Snapshot hyperspectral imaging probe with principal component analysis and confidence ellipse for classification

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-06-01

Hyperspectral imaging combines imaging and spectroscopy to provide detailed spectral information for each spatial point in the image. This gives a three-dimensional spatial-spatial-spectral datacube with hundreds of spectral images. Probe-based hyperspectral imaging systems have been developed so that they can be used in regions where conventional table-top platforms would find it difficult to access. A fiber bundle, which is made up of specially-arranged optical fibers, has recently been developed and integrated with a spectrograph-based hyperspectral imager. This forms a snapshot hyperspectral imaging probe, which is able to form a datacube using the information from each scan. Compared to the other configurations, which require sequential scanning to form a datacube, the snapshot configuration is preferred in real-time applications where motion artifacts and pixel misregistration can be minimized. Principal component analysis is a dimension-reducing technique that can be applied in hyperspectral imaging to convert the spectral information into uncorrelated variables known as principal components. A confidence ellipse can be used to define the region of each class in the principal component feature space and for classification. This paper demonstrates the use of the snapshot hyperspectral imaging probe to acquire data from samples of different colors. The spectral library of each sample was acquired and then analyzed using principal component analysis. Confidence ellipse was then applied to the principal components of each sample and used as the classification criteria. The results show that the applied analysis can be used to perform classification of the spectral data acquired using the snapshot hyperspectral imaging probe.

Combined Acquisition/Processing For Data Reduction

NASA Astrophysics Data System (ADS)

Kruger, Robert A.

1982-01-01

Digital image processing systems necessarily consist of three components: acquisition, storage/retrieval and processing. The acquisition component requires the greatest data handling rates. By coupling together the acquisition witn some online hardwired processing, data rates and capacities for short term storage can be reduced. Furthermore, long term storage requirements can be reduced further by appropriate processing and editing of image data contained in short term memory. The net result could be reduced performance requirements for mass storage, processing and communication systems. Reduced amounts of data also snouid speed later data analysis and diagnostic decision making.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information.

PubMed

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Yan, Bin; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition.

Automatic Artifact Removal from Electroencephalogram Data Based on A Priori Artifact Information

PubMed Central

Zhang, Chi; Tong, Li; Zeng, Ying; Jiang, Jingfang; Bu, Haibing; Li, Jianxin

2015-01-01

Electroencephalogram (EEG) is susceptible to various nonneural physiological artifacts. Automatic artifact removal from EEG data remains a key challenge for extracting relevant information from brain activities. To adapt to variable subjects and EEG acquisition environments, this paper presents an automatic online artifact removal method based on a priori artifact information. The combination of discrete wavelet transform and independent component analysis (ICA), wavelet-ICA, was utilized to separate artifact components. The artifact components were then automatically identified using a priori artifact information, which was acquired in advance. Subsequently, signal reconstruction without artifact components was performed to obtain artifact-free signals. The results showed that, using this automatic online artifact removal method, there were statistical significant improvements of the classification accuracies in both two experiments, namely, motor imagery and emotion recognition. PMID:26380294

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Chen, Weisheng; Wang, Yue; Chen, Rong; Zeng, Haishan

2013-01-01

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

Multimodal Neuroimaging: Basic Concepts and Classification of Neuropsychiatric Diseases.

PubMed

Tulay, Emine Elif; Metin, Barış; Tarhan, Nevzat; Arıkan, Mehmet Kemal

2018-06-01

Neuroimaging techniques are widely used in neuroscience to visualize neural activity, to improve our understanding of brain mechanisms, and to identify biomarkers-especially for psychiatric diseases; however, each neuroimaging technique has several limitations. These limitations led to the development of multimodal neuroimaging (MN), which combines data obtained from multiple neuroimaging techniques, such as electroencephalography, functional magnetic resonance imaging, and yields more detailed information about brain dynamics. There are several types of MN, including visual inspection, data integration, and data fusion. This literature review aimed to provide a brief summary and basic information about MN techniques (data fusion approaches in particular) and classification approaches. Data fusion approaches are generally categorized as asymmetric and symmetric. The present review focused exclusively on studies based on symmetric data fusion methods (data-driven methods), such as independent component analysis and principal component analysis. Machine learning techniques have recently been introduced for use in identifying diseases and biomarkers of disease. The machine learning technique most widely used by neuroscientists is classification-especially support vector machine classification. Several studies differentiated patients with psychiatric diseases and healthy controls with using combined datasets. The common conclusion among these studies is that the prediction of diseases increases when combining data via MN techniques; however, there remain a few challenges associated with MN, such as sample size. Perhaps in the future N-way fusion can be used to combine multiple neuroimaging techniques or nonimaging predictors (eg, cognitive ability) to overcome the limitations of MN.

PSHFT - COMPUTERIZED LIFE AND RELIABILITY MODELLING FOR TURBOPROP TRANSMISSIONS

NASA Technical Reports Server (NTRS)

Savage, M.

1994-01-01

The computer program PSHFT calculates the life of a variety of aircraft transmissions. A generalized life and reliability model is presented for turboprop and parallel shaft geared prop-fan aircraft transmissions. The transmission life and reliability model is a combination of the individual reliability models for all the bearings and gears in the main load paths. The bearing and gear reliability models are based on the statistical two parameter Weibull failure distribution method and classical fatigue theories. The computer program developed to calculate the transmission model is modular. In its present form, the program can analyze five different transmissions arrangements. Moreover, the program can be easily modified to include additional transmission arrangements. PSHFT uses the properties of a common block two-dimensional array to separate the component and transmission property values from the analysis subroutines. The rows correspond to specific components with the first row containing the values for the entire transmission. Columns contain the values for specific properties. Since the subroutines (which determine the transmission life and dynamic capacity) interface solely with this property array, they are separated from any specific transmission configuration. The system analysis subroutines work in an identical manner for all transmission configurations considered. Thus, other configurations can be added to the program by simply adding component property determination subroutines. PSHFT consists of a main program, a series of configuration specific subroutines, generic component property analysis subroutines, systems analysis subroutines, and a common block. The main program selects the routines to be used in the analysis and sequences their operation. The series of configuration specific subroutines input the configuration data, perform the component force and life analyses (with the help of the generic component property analysis subroutines), fill the property array, call up the system analysis routines, and finally print out the analysis results for the system and components. PSHFT is written in FORTRAN 77 and compiled on a MicroSoft FORTRAN compiler. The program will run on an IBM PC AT compatible with at least 104k bytes of memory. The program was developed in 1988.

Automotive Exterior Noise Optimization Using Grey Relational Analysis Coupled with Principal Component Analysis

NASA Astrophysics Data System (ADS)

Chen, Shuming; Wang, Dengfeng; Liu, Bo

This paper investigates optimization design of the thickness of the sound package performed on a passenger automobile. The major characteristics indexes for performance selected to evaluate the processes are the SPL of the exterior noise and the weight of the sound package, and the corresponding parameters of the sound package are the thickness of the glass wool with aluminum foil for the first layer, the thickness of the glass fiber for the second layer, and the thickness of the PE foam for the third layer. In this paper, the process is fundamentally with multiple performances, thus, the grey relational analysis that utilizes grey relational grade as performance index is especially employed to determine the optimal combination of the thickness of the different layers for the designed sound package. Additionally, in order to evaluate the weighting values corresponding to various performance characteristics, the principal component analysis is used to show their relative importance properly and objectively. The results of the confirmation experiments uncover that grey relational analysis coupled with principal analysis methods can successfully be applied to find the optimal combination of the thickness for each layer of the sound package material. Therefore, the presented method can be an effective tool to improve the vehicle exterior noise and lower the weight of the sound package. In addition, it will also be helpful for other applications in the automotive industry, such as the First Automobile Works in China, Changan Automobile in China, etc.

The Analysis of Three-Way Contingency Tables by Three-Mode Association Models.

ERIC Educational Resources Information Center

Anderson, Carolyn J.

1996-01-01

Generalizations of L. A. Goodman's RC(M) association model (1991 and earlier) are presented for three-way tables. These three-mode association models use L. R. Tucker's three-mode components model (1964, 1966) to represent the three-factor interaction or the combined effects of two- and three-factor interactions. (SLD)

Perceptions of the Students toward Studio Physics

ERIC Educational Resources Information Center

Gok, Tolga

2011-01-01

The purpose of this study was not only to report the development process of the studio model, but also to determine the students' perceptions about the studio model. This model retains the large lecture component but combines recitation and laboratory instruction into studio model. This research was based on qualitative analysis. The data of the…

Improved maintainability of space-based reusable rocket engines

NASA Technical Reports Server (NTRS)

Barkhoudarian, S.; Szemenyei, B.; Nelson, R. S.; Pauckert, R.; Harmon, T.

1988-01-01

Advanced, noninferential, noncontacting, in situ measurement technologies, combined with automated testing and expert systems, can provide continuous, automated health monitoring of critical space-based rocket engine components, requiring minimal disassembly and no manual data analysis, thus enhancing their maintainability. This paper concentrates on recent progress of noncontacting combustion chamber wall thickness condition-monitoring technologies.

THE 1998 BALTIMORE PARTICULATE MATTER EPIDEMIOLOGY-EXPOSURE STUDY: PART 1 - COMPARISON OF AMBIENT, RESIDENTIAL OUTDOOR, INDOOR AND APARTMENT PARTICULATE MATTER MONITORING

EPA Science Inventory

A combined epidemiological-exposure panel study was conducted during the summer of 1998 in Baltimore, Maryland. The objectives of the exposure analysis component of the 28-day study were to investigate the statistical relationships between particulate matter (PM) and related co...

Automated Solid Phase Extraction (SPE) LC/NMR Applied to the Structural Analysis of Extractable Compounds from a Pharmaceutical Packaging Material of Construction.

PubMed

Norwood, Daniel L; Mullis, James O; Davis, Mark; Pennino, Scott; Egert, Thomas; Gonnella, Nina C

2013-01-01

The structural analysis (i.e., identification) of organic chemical entities leached into drug product formulations has traditionally been accomplished with techniques involving the combination of chromatography with mass spectrometry. These include gas chromatography/mass spectrometry (GC/MS) for volatile and semi-volatile compounds, and various forms of liquid chromatography/mass spectrometry (LC/MS or HPLC/MS) for semi-volatile and relatively non-volatile compounds. GC/MS and LC/MS techniques are complementary for structural analysis of leachables and potentially leachable organic compounds produced via laboratory extraction of pharmaceutical container closure/delivery system components and corresponding materials of construction. Both hyphenated analytical techniques possess the separating capability, compound specific detection attributes, and sensitivity required to effectively analyze complex mixtures of trace level organic compounds. However, hyphenated techniques based on mass spectrometry are limited by the inability to determine complete bond connectivity, the inability to distinguish between many types of structural isomers, and the inability to unambiguously determine aromatic substitution patterns. Nuclear magnetic resonance spectroscopy (NMR) does not have these limitations; hence it can serve as a complement to mass spectrometry. However, NMR technology is inherently insensitive and its ability to interface with chromatography has been historically challenging. This article describes the application of NMR coupled with liquid chromatography and automated solid phase extraction (SPE-LC/NMR) to the structural analysis of extractable organic compounds from a pharmaceutical packaging material of construction. The SPE-LC/NMR technology combined with micro-cryoprobe technology afforded the sensitivity and sample mass required for full structure elucidation. Optimization of the SPE-LC/NMR analytical method was achieved using a series of model compounds representing the chemical diversity of extractables. This study demonstrates the complementary nature of SPE-LC/NMR with LC/MS for this particular pharmaceutical application. The identification of impurities leached into drugs from the components and materials associated with pharmaceutical containers, packaging components, and materials has historically been done using laboratory techniques based on the combination of chromatography with mass spectrometry. Such analytical techniques are widely recognized as having the selectivity and sensitivity required to separate the complex mixtures of impurities often encountered in such identification studies, including both the identification of leachable impurities as well as potential leachable impurities produced by laboratory extraction of packaging components and materials. However, while mass spectrometry-based analytical techniques have limitations for this application, newer analytical techniques based on the combination of chromatography with nuclear magnetic resonance spectroscopy provide an added dimension of structural definition. This article describes the development, optimization, and application of an analytical technique based on the combination of chromatography and nuclear magnetic resonance spectroscopy to the identification of potential leachable impurities from a pharmaceutical packaging material. The complementary nature of the analytical techniques for this particular pharmaceutical application is demonstrated.

Discrimination of Medicine Radix Astragali from Different Geographic Origins Using Multiple Spectroscopies Combined with Data Fusion Methods

NASA Astrophysics Data System (ADS)

Wang, Hai-Yan; Song, Chao; Sha, Min; Liu, Jun; Li, Li-Ping; Zhang, Zheng-Yong

2018-05-01

Raman spectra and ultraviolet-visible absorption spectra of four different geographic origins of Radix Astragali were collected. These data were analyzed using kernel principal component analysis combined with sparse representation classification. The results showed that the recognition rate reached 70.44% using Raman spectra for data input and 90.34% using ultraviolet-visible absorption spectra for data input. A new fusion method based on Raman combined with ultraviolet-visible data was investigated and the recognition rate was increased to 96.43%. The experimental results suggested that the proposed data fusion method effectively improved the utilization rate of the original data.

Near and mid infrared spectroscopy and multivariate data analysis in studies of oxidation of edible oils.

PubMed

Wójcicki, Krzysztof; Khmelinskii, Igor; Sikorski, Marek; Sikorska, Ewa

2015-11-15

Infrared spectroscopic techniques and chemometric methods were used to study oxidation of olive, sunflower and rapeseed oils. Accelerated oxidative degradation of oils at 60°C was monitored using peroxide values and FT-MIR ATR and FT-NIR transmittance spectroscopy. Principal component analysis (PCA) facilitated visualization and interpretation of spectral changes occurring during oxidation. Multivariate curve resolution (MCR) method found three spectral components in the NIR and MIR spectral matrix, corresponding to the oxidation products, and saturated and unsaturated structures. Good quantitative relation was found between peroxide value and contribution of oxidation products evaluated using MCR--based on NIR (R(2) = 0.890), MIR (R(2) = 0.707) and combined NIR and MIR (R(2) = 0.747) data. Calibration models for prediction peroxide value established using partial least squares (PLS) regression were characterized for MIR (R(2) = 0.701, RPD = 1.7), NIR (R(2) = 0.970, RPD = 5.3), and combined NIR and MIR data (R(2) = 0.954, RPD = 3.1). Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantitative refractive index distribution of single cell by combining phase-shifting interferometry and AFM imaging.

PubMed

Zhang, Qinnan; Zhong, Liyun; Tang, Ping; Yuan, Yingjie; Liu, Shengde; Tian, Jindong; Lu, Xiaoxu

2017-05-31

Cell refractive index, an intrinsic optical parameter, is closely correlated with the intracellular mass and concentration. By combining optical phase-shifting interferometry (PSI) and atomic force microscope (AFM) imaging, we constructed a label free, non-invasive and quantitative refractive index of single cell measurement system, in which the accurate phase map of single cell was retrieved with PSI technique and the cell morphology with nanoscale resolution was achieved with AFM imaging. Based on the proposed AFM/PSI system, we achieved quantitative refractive index distributions of single red blood cell and Jurkat cell, respectively. Further, the quantitative change of refractive index distribution during Daunorubicin (DNR)-induced Jurkat cell apoptosis was presented, and then the content changes of intracellular biochemical components were achieved. Importantly, these results were consistent with Raman spectral analysis, indicating that the proposed PSI/AFM based refractive index system is likely to become a useful tool for intracellular biochemical components analysis measurement, and this will facilitate its application for revealing cell structure and pathological state from a new perspective.

Physician performance assessment using a composite quality index.

PubMed

Liu, Kaibo; Jain, Shabnam; Shi, Jianjun

2013-07-10

Assessing physician performance is important for the purposes of measuring and improving quality of service and reducing healthcare delivery costs. In recent years, physician performance scorecards have been used to provide feedback on individual measures; however, one key challenge is how to develop a composite quality index that combines multiple measures for overall physician performance evaluation. A controversy arises over establishing appropriate weights to combine indicators in multiple dimensions, and cannot be easily resolved. In this study, we proposed a generic unsupervised learning approach to develop a single composite index for physician performance assessment by using non-negative principal component analysis. We developed a new algorithm named iterative quadratic programming to solve the numerical issue in the non-negative principal component analysis approach. We conducted real case studies to demonstrate the performance of the proposed method. We provided interpretations from both statistical and clinical perspectives to evaluate the developed composite ranking score in practice. In addition, we implemented the root cause assessment techniques to explain physician performance for improvement purposes. Copyright © 2012 John Wiley & Sons, Ltd.

Identification of Piecewise Linear Uniform Motion Blur

NASA Astrophysics Data System (ADS)

Patanukhom, Karn; Nishihara, Akinori

A motion blur identification scheme is proposed for nonlinear uniform motion blurs approximated by piecewise linear models which consist of more than one linear motion component. The proposed scheme includes three modules that are a motion direction estimator, a motion length estimator and a motion combination selector. In order to identify the motion directions, the proposed scheme is based on a trial restoration by using directional forward ramp motion blurs along different directions and an analysis of directional information via frequency domain by using a Radon transform. Autocorrelation functions of image derivatives along several directions are employed for estimation of the motion lengths. A proper motion combination is identified by analyzing local autocorrelation functions of non-flat component of trial restored results. Experimental examples of simulated and real world blurred images are given to demonstrate a promising performance of the proposed scheme.

Higher-Order Theory: Structural/MicroAnalysis Code (HOTSMAC) Developed

NASA Technical Reports Server (NTRS)

Arnold, Steven M.

2002-01-01

The full utilization of advanced materials (be they composite or functionally graded materials) in lightweight aerospace components requires the availability of accurate analysis, design, and life-prediction tools that enable the assessment of component and material performance and reliability. Recently, a new commercially available software product called HOTSMAC (Higher-Order Theory--Structural/MicroAnalysis Code) was jointly developed by Collier Research Corporation, Engineered Materials Concepts LLC, and the NASA Glenn Research Center under funding provided by Glenn's Commercial Technology Office. The analytical framework for HOTSMAC is based on almost a decade of research into the coupled micromacrostructural analysis of heterogeneous materials. Consequently, HOTSMAC offers a comprehensive approach for analyzing/designing the response of components with various microstructural details, including certain advantages not always available in standard displacement-based finite element analysis techniques. The capabilities of HOTSMAC include combined thermal and mechanical analysis, time-independent and time-dependent material behavior, and internal boundary cells (e.g., those that can be used to represent internal cooling passages, see the preceding figure) to name a few. In HOTSMAC problems, materials can be randomly distributed and/or functionally graded (as shown in the figure, wherein the inclusions are distributed linearly), or broken down by strata, such as in the case of thermal barrier coatings or composite laminates.

Biochemometrics for Natural Products Research: Comparison of Data Analysis Approaches and Application to Identification of Bioactive Compounds.

PubMed

Kellogg, Joshua J; Todd, Daniel A; Egan, Joseph M; Raja, Huzefa A; Oberlies, Nicholas H; Kvalheim, Olav M; Cech, Nadja B

2016-02-26

A central challenge of natural products research is assigning bioactive compounds from complex mixtures. The gold standard approach to address this challenge, bioassay-guided fractionation, is often biased toward abundant, rather than bioactive, mixture components. This study evaluated the combination of bioassay-guided fractionation with untargeted metabolite profiling to improve active component identification early in the fractionation process. Key to this methodology was statistical modeling of the integrated biological and chemical data sets (biochemometric analysis). Three data analysis approaches for biochemometric analysis were compared, namely, partial least-squares loading vectors, S-plots, and the selectivity ratio. Extracts from the endophytic fungi Alternaria sp. and Pyrenochaeta sp. with antimicrobial activity against Staphylococcus aureus served as test cases. Biochemometric analysis incorporating the selectivity ratio performed best in identifying bioactive ions from these extracts early in the fractionation process, yielding altersetin (3, MIC 0.23 μg/mL) and macrosphelide A (4, MIC 75 μg/mL) as antibacterial constituents from Alternaria sp. and Pyrenochaeta sp., respectively. This study demonstrates the potential of biochemometrics coupled with bioassay-guided fractionation to identify bioactive mixture components. A benefit of this approach is the ability to integrate multiple stages of fractionation and bioassay data into a single analysis.

Estimating the number of pure chemical components in a mixture by X-ray absorption spectroscopy.

PubMed

Manceau, Alain; Marcus, Matthew; Lenoir, Thomas

2014-09-01

Principal component analysis (PCA) is a multivariate data analysis approach commonly used in X-ray absorption spectroscopy to estimate the number of pure compounds in multicomponent mixtures. This approach seeks to describe a large number of multicomponent spectra as weighted sums of a smaller number of component spectra. These component spectra are in turn considered to be linear combinations of the spectra from the actual species present in the system from which the experimental spectra were taken. The dimension of the experimental dataset is given by the number of meaningful abstract components, as estimated by the cascade or variance of the eigenvalues (EVs), the factor indicator function (IND), or the F-test on reduced EVs. It is shown on synthetic and real spectral mixtures that the performance of the IND and F-test critically depends on the amount of noise in the data, and may result in considerable underestimation or overestimation of the number of components even for a signal-to-noise (s/n) ratio of the order of 80 (σ = 20) in a XANES dataset. For a given s/n ratio, the accuracy of the component recovery from a random mixture depends on the size of the dataset and number of components, which is not known in advance, and deteriorates for larger datasets because the analysis picks up more noise components. The scree plot of the EVs for the components yields one or two values close to the significant number of components, but the result can be ambiguous and its uncertainty is unknown. A new estimator, NSS-stat, which includes the experimental error to XANES data analysis, is introduced and tested. It is shown that NSS-stat produces superior results compared with the three traditional forms of PCA-based component-number estimation. A graphical user-friendly interface for the calculation of EVs, IND, F-test and NSS-stat from a XANES dataset has been developed under LabVIEW for Windows and is supplied in the supporting information. Its possible application to EXAFS data is discussed, and several XANES and EXAFS datasets are also included for download.

A carbon nanotube-gemcitabine-lentinan three-component composite for chemo-photothermal synergistic therapy of cancer.

PubMed

Zhang, Ping; Yi, Wenhui; Hou, Jin; Yoo, Sweejiang; Jin, Weiqiu; Yang, Qisheng

2018-01-01

Gemcitabine's clinical application is limited due to its short plasma half-life and poor uptake by cells. To address this problem, a drug delivery three-component composite, multiwalled carbon nanotubes (MWNTs)/gemcitabine (Ge)/lentinan (Le; MWNTs-Ge-Le), was fabricated in our study. Moreover, the combination of chemotherapy and photothermal therapy was employed to enhance antitumor efficacy. In this study, we conjugated gemcitabine and lentinan with MWNTs via a covalent and noncovalent way to functionalize with MWNTs, and the chemical structure of MWNTs-Ge-Le was characterized by Fourier transform infrared spectroscopy, Raman spectroscopy, thermogravimetric analysis and transmission electron microscopy. Using the composite and an 808 nm laser, we treated tumors, both in vitro and in vivo, and investigated the photothermal responses and the anticancer efficacy. The MWNTs-Ge-Le composite could efficiently cross cell membrane, having a higher antitumor activity than MWNTs, gemcitabine and MWNTs-Ge in vitro and in vivo. Our study on the MWNTs-Ge-Le composite with an 808 nm laser radiation showed the combination of drug therapy and near-infrared photothermal therapy possesses great synergistic antitumor efficacy. The MWNTs-Ge-Le three-component anticancer composite can serve as a promising candidate for cancer therapy in the combination of chemotherapy and photothermal therapy.

A comparative study of three tissue-cultured Dendrobium species and their wild correspondences by headspace gas chromatography-mass spectrometry combined with chemometric methods.

PubMed

Chen, Nai-Dong; You, Tao; Li, Jun; Bai, Li-Tao; Hao, Jing-Wen; Xu, Xiao-Yuan

2016-10-01

Plant tissue culture technique is widely used in the conservation and utilization of rare and endangered medicinal plants and it is crucial for tissue culture stocks to obtain the ability to produce similar bioactive components as their wild correspondences. In this paper, a headspace gas chromatography-mass spectrometry method combined with chemometric methods was applied to analyze and evaluate the volatile compounds in tissue-cultured and wild Dendrobium huoshanense Cheng and Tang, Dendrobium officinale Kimura et Migo and Dendrobium moniliforme (Linn.) Sw. In total, 63 volatile compounds were separated, with 53 being identified from the three Dendrobium spp. Different provenances of Dendrobiums had characteristic chemicals and showed remarkable quantity discrepancy of common compositions. The similarity evaluation disclosed that the accumulation of volatile compounds in Dendrobium samples might be affected by their provenance. Principal component analysis showed that the first three components explained 85.9% of data variance, demonstrating a good discrimination between samples. Gas chromatography-mass spectrometry techniques, combined with chemometrics, might be an effective strategy for identifying the species and their provenance, especially in the assessment of tissue-cultured Dendrobium quality for use in raw herbal medicines. Copyright © 2016. Published by Elsevier B.V.

Dual-energy x-ray image decomposition by independent component analysis

NASA Astrophysics Data System (ADS)

Jiang, Yifeng; Jiang, Dazong; Zhang, Feng; Zhang, Dengfu; Lin, Gang

2001-09-01

The spatial distributions of bone and soft tissue in human body are separated by independent component analysis (ICA) of dual-energy x-ray images. It is because of the dual energy imaging modelí-s conformity to the ICA model that we can apply this method: (1) the absorption in body is mainly caused by photoelectric absorption and Compton scattering; (2) they take place simultaneously but are mutually independent; and (3) for monochromatic x-ray sources the total attenuation is achieved by linear combination of these two absorption. Compared with the conventional method, the proposed one needs no priori information about the accurate x-ray energy magnitude for imaging, while the results of the separation agree well with the conventional one.

Design and Optimization of Composite Gyroscope Momentum Wheel Rings

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2007-01-01

Stress analysis and preliminary design/optimization procedures are presented for gyroscope momentum wheel rings composed of metallic, metal matrix composite, and polymer matrix composite materials. The design of these components involves simultaneously minimizing both true part volume and mass, while maximizing angular momentum. The stress analysis results are combined with an anisotropic failure criterion to formulate a new sizing procedure that provides considerable insight into the design of gyroscope momentum wheel ring components. Results compare the performance of two optimized metallic designs, an optimized SiC/Ti composite design, and an optimized graphite/epoxy composite design. The graphite/epoxy design appears to be far superior to the competitors considered unless a much greater premium is placed on volume efficiency compared to mass efficiency.

Analysis of self-recording in self-management interventions for stereotypy.

PubMed

Fritz, Jennifer N; Iwata, Brian A; Rolider, Natalie U; Camp, Erin M; Neidert, Pamela L

2012-01-01

Most treatments for stereotypy involve arrangements of antecedent or consequent events that are imposed entirely by a therapist. By contrast, results of some studies suggest that self-recording, a common component of self-management interventions, might be an effective and efficient way to reduce stereotypy. Because the procedure typically has included instructions to refrain from stereotypy, self-recording of the absence of stereotypy, and differential reinforcement of accurate recording, it is unclear which element or combination of elements produces reductions in stereotypy. We conducted a component analysis of a self-management intervention and observed that decreases in stereotypy might be attributable to instructional control or to differential reinforcement, but that self-recording per se had little effect on stereotypy.

Fabrication and Testing of Ceramic Matrix Composite Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Effinger, M. R.; Clinton, R. C., Jr.; Dennis, J.; Elam, S.; Genge, G.; Eckel, A.; Jaskowiak, M. H.; Kiser, J. D.; Lang, J.

2001-01-01

NASA has established goals for Second and Third Generation Reusable Launch Vehicles. Emphasis has been placed on significantly improving safety and decreasing the cost of transporting payloads to orbit. Ceramic matrix composites (CMC) components are being developed by NASA to enable significant increases in safety and engineer performance, while reducing costs. The development of the following CMC components are being pursued by NASA: (1) Simplex CMC Blisk; (2) Cooled CMC Nozzle Ramps; (3) Cooled CMC Thrust Chambers; and (4) CMC Gas Generator. These development efforts are application oriented, but have a strong underpinning of fundamental understanding of processing-microstructure-property relationships relative to structural analyses, nondestructive characterization, and material behavior analysis at the coupon and component and system operation levels. As each effort matures, emphasis will be placed on optimizing and demonstrating material/component durability, ideally using a combined Building Block Approach and Build and Bust Approach.

Grasp-Based Functional Coupling Between Reach- and Grasp-Related Components of Forelimb Muscle Activity

PubMed Central

Geed, Shashwati; van Kan, Peter L. E.

2017-01-01

How are appropriate combinations of forelimb muscles selected during reach-to-grasp movements in the presence of neuromotor redundancy and important task-related constraints? The authors tested whether grasp type or target location preferentially influence the selection and synergistic coupling between forelimb muscles during reach-to-grasp movements. Factor analysis applied to 14–20 forelimb electromyograms recorded from monkeys performing reach-to-grasp tasks revealed 4–6 muscle components that showed transport/preshape- or grasp-related features. Weighting coefficients of transport/preshape-related components demonstrated strongest similarities for reaches that shared the same grasp type rather than the same target location. Scaling coefficients of transport/preshape- and grasp-related components showed invariant temporal coupling. Thus, grasp type influenced strongly both transport/preshape- and grasp-related muscle components, giving rise to grasp-based functional coupling between forelimb muscles. PMID:27589010

A gravitational lens candidate discovered with the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Maoz, Dan; Bahcall, John N.; Schneider, Donald P.; Doxsey, Rodger; Bahcall, Neta A.; Filippenko, Alexei V.; Goss, W. M.; Lahav, Ofer; Yanny, Brian

1992-01-01

Evidence is reported for gravitational lensing of the high-redshift (z = 3.8) quasar 1208 + 101, observed as part of the Snapshot survey with the HST Planetary Camera. An HST V image taken on gyroscopes resolves the quasar into three point-source components, with the two fainter images having separations of 0.1 and 0.5 arcsec from the central bright component. A radio observation of the quasar with the VLA at 2 cm shows that, like most quasars of this redhsift, 1208 + 101 is radio quiet. Based on positional information alone, the probability that the observed optical components are chance superpositions of Galactic stars is small, but not negligible. Analysis of a combined ground-based spectrum of all three components, using the relative brightnesses of the HST image, supports the lensing hypothesis. If all the components are lensed images of the quasar, the observed configuration cannot be reproduced by simple lens models.

Effects of the Combination of the Main Active Components of Astragalus and Panax notoginseng on Inflammation and Apoptosis of Nerve Cell after Cerebral Ischemia-Reperfusion.

PubMed

Huang, Xiao-Ping; Ding, Huang; Lu, Jin-Dong; Tang, Ying-Hong; Deng, Bing-Xiang; Deng, Chang-Qing

2015-01-01

Astragalus and Panax notoginseng are commonly used to treat cardio-cerebrovascular diseases in China and are often combined together to promote curative effect. We speculate that the enhancement of the combination on anticerebral ischemia injury may come from the main active components. The purpose of this work was to probe the effects and mechanisms of Astragaloside IV (the active component of Astragalus) combined with Ginsenoside Rg1, Ginsenoside Rb1, and Notoginsenoside R1 (the active components of P. notoginseng) to antagonize ischemia/reperfusion (I/R) injury via inflammation and apoptosis. C57BL/6 mice were randomly divided into sham, model, Astragaloside IV, Ginsenoside Rg1, Ginsenoside Rb1, Notoginsenoside R1, four active components combination, and Edaravone groups. After administration for 3 days, bilateral common carotid arteries (CCA) were occluded with artery clip for 20[Formula: see text]min followed by reperfusion for 24[Formula: see text]h. Our results showed that the survival rate of nerve cell in hippocampal CA1 decreased while the apoptotic rate increased, and the level of caspase-3 protein in brain tissues was elevated, the expressions of TNF-a, IL-1, and ICAM-1 mRNA as well as phosphorylated nuclear factor kappa B (NF-κB) inhibitor protein α (p-IκBa) in brain tissues were up-regulated, and the nuclear translocation rate of NF-κB was raised. Additionally, the protein expressions of phosphorylated tyrosine kinase 1 (p-JAK1), phosphorylated signal transducer and activator of transcription-1 (p-STAT1), glucose regulated protein 78 (GRP78), caspase-12, and phosphorylated c-Jun N-terminal kinases 1/2 (p-JNK1/2) in brain tissues were also significantly strengthened after I/R for 24 h. All drugs could increase neurocyte survival rate in hippocampal CA1, decrease the apoptotic rate, and inhibit caspase-3 protein expression, in contrast, the effects of four active components combination were better than those of active components alone. In addition, Astragaloside IV and Ginsenoside Rg1 could down-regulate the level of TNF-α, and ICAM-1 mRNA, respectively, Notoginsenoside R1 reduced both TNF-α and ICAM-1 mRNA, and the combination of the 4 effective components had inhibitory effects on the expressions of TNF-α, IL-1β, and ICAM-1 mRNA. Astragaloside IV, Ginsenoside Rg1, Notoginsenoside R1, and 4 effective components combination were able to restrain the phosphorylation of IκBα, and relieve the nuclear translocation rate of NF-κB. Moreover, the effects of the combination are greater than those of active components alone. All drugs could suppress the phosphorylation of JAK1 induced by I/R; meanwhile the expression of p-STAT1 exhibited a decrease in Ginsenoside Rg1 and four active components combination groups. The decreases of p-JAK1 and p-STAT1 in the four active components combination group were more obvious than those in active components alone groups. Astragaloside IV, Ginsenoside Rg1, and Notoginsenoside R1 further augmented GRP78 expression caused by I/R, Notoginsenoside R1 attenuated caspase-12 protein expression, Astragaloside IV and Ginsenoside Rg1 lessened the phosphorylation of JNK1/2, and the four active components combination was capable of up-regulating GRP78 protein while down-regulating the expressions of caspase-12 and p-JNK1/2. Similarly, the effects of the four active components combination were greater than those of effective components alone. These suggested that the combination of the main active components of Astragalus and Panax notoginseng could strengthen protective effects on cerebral ischemia injury via anti-apoptosis and anti-inflammation, and the mechanisms might be associated with restraining the activation of NF-κB and JAK1/STAT1 signal pathways and regulating endoplasmic reticulum stress (ERS) after cerebral ischemia.

A physics based method for combining multiple anatomy models with application to medical simulation.

PubMed

Zhu, Yanong; Magee, Derek; Ratnalingam, Rishya; Kessel, David

2009-01-01

We present a physics based approach to the construction of anatomy models by combining components from different sources; different image modalities, protocols, and patients. Given an initial anatomy, a mass-spring model is generated which mimics the physical properties of the solid anatomy components. This helps maintain valid spatial relationships between the components, as well as the validity of their shapes. Combination can be either replacing/modifying an existing component, or inserting a new component. The external forces that deform the model components to fit the new shape are estimated from Gradient Vector Flow and Distance Transform maps. We demonstrate the applicability and validity of the described approach in the area of medical simulation, by showing the processes of non-rigid surface alignment, component replacement, and component insertion.

SIGPI. Fault Tree Cut Set System Performance

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

Patenaude, C.J.

1992-01-13

SIGPI computes the probabilistic performance of complex systems by combining cut set or other binary product data with probability information on each basic event. SIGPI is designed to work with either coherent systems, where the system fails when certain combinations of components fail, or noncoherent systems, where at least one cut set occurs only if at least one component of the system is operating properly. The program can handle conditionally independent components, dependent components, or a combination of component types and has been used to evaluate responses to environmental threats and seismic events. The three data types that can bemore » input are cut set data in disjoint normal form, basic component probabilities for independent basic components, and mean and covariance data for statistically dependent basic components.« less

SIGPI. Fault Tree Cut Set System Performance

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

Patenaude, C.J.

1992-01-14

SIGPI computes the probabilistic performance of complex systems by combining cut set or other binary product data with probability information on each basic event. SIGPI is designed to work with either coherent systems, where the system fails when certain combinations of components fail, or noncoherent systems, where at least one cut set occurs only if at least one component of the system is operating properly. The program can handle conditionally independent components, dependent components, or a combination of component types and has been used to evaluate responses to environmental threats and seismic events. The three data types that can bemore » input are cut set data in disjoint normal form, basic component probabilities for independent basic components, and mean and covariance data for statistically dependent basic components.« less

Impact of Measurement Uncertainties on Receptor Modeling of Speciated Atmospheric Mercury.

PubMed

Cheng, I; Zhang, L; Xu, X

2016-02-09

Gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurement uncertainties could potentially affect the analysis and modeling of atmospheric mercury. This study investigated the impact of GOM measurement uncertainties on Principal Components Analysis (PCA), Absolute Principal Component Scores (APCS), and Concentration-Weighted Trajectory (CWT) receptor modeling results. The atmospheric mercury data input into these receptor models were modified by combining GOM and PBM into a single reactive mercury (RM) parameter and excluding low GOM measurements to improve the data quality. PCA and APCS results derived from RM or excluding low GOM measurements were similar to those in previous studies, except for a non-unique component and an additional component extracted from the RM dataset. The percent variance explained by the major components from a previous study differed slightly compared to RM and excluding low GOM measurements. CWT results were more sensitive to the input of RM than GOM excluding low measurements. Larger discrepancies were found between RM and GOM source regions than those between RM and PBM. Depending on the season, CWT source regions of RM differed by 40-61% compared to GOM from a previous study. No improvement in correlations between CWT results and anthropogenic mercury emissions were found.

Impact of Measurement Uncertainties on Receptor Modeling of Speciated Atmospheric Mercury

PubMed Central

Cheng, I.; Zhang, L.; Xu, X.

2016-01-01

Gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurement uncertainties could potentially affect the analysis and modeling of atmospheric mercury. This study investigated the impact of GOM measurement uncertainties on Principal Components Analysis (PCA), Absolute Principal Component Scores (APCS), and Concentration-Weighted Trajectory (CWT) receptor modeling results. The atmospheric mercury data input into these receptor models were modified by combining GOM and PBM into a single reactive mercury (RM) parameter and excluding low GOM measurements to improve the data quality. PCA and APCS results derived from RM or excluding low GOM measurements were similar to those in previous studies, except for a non-unique component and an additional component extracted from the RM dataset. The percent variance explained by the major components from a previous study differed slightly compared to RM and excluding low GOM measurements. CWT results were more sensitive to the input of RM than GOM excluding low measurements. Larger discrepancies were found between RM and GOM source regions than those between RM and PBM. Depending on the season, CWT source regions of RM differed by 40–61% compared to GOM from a previous study. No improvement in correlations between CWT results and anthropogenic mercury emissions were found. PMID:26857835

Analysis of model Titan atmospheric components using ion mobility spectrometry

NASA Technical Reports Server (NTRS)

Kojiro, D. R.; Cohen, M. J.; Wernlund, R. F.; Stimac, R. M.; Humphry, D. E.; Takeuchi, N.

1991-01-01

The Gas Chromatograph-Ion Mobility Spectrometer (GC-IMS) was proposed as an analytical technique for the analysis of Titan's atmosphere during the Cassini Mission. The IMS is an atmospheric pressure, chemical detector that produces an identifying spectrum of each chemical species measured. When the IMS is combined with a GC as a GC-IMS, the GC is used to separate the sample into its individual components, or perhaps small groups of components. The IMS is then used to detect, quantify, and identify each sample component. Conventional IMS detection and identification of sample components depends upon a source of energetic radiation, such as beta radiation, which ionizes the atmospheric pressure host gas. This primary ionization initiates a sequence of ion-molecule reactions leading to the formation of sufficiently energetic positive or negative ions, which in turn ionize most constituents in the sample. In conventional IMS, this reaction sequence is dominated by the water cluster ion. However, many of the light hydrocarbons expected in Titan's atmosphere cannot be analyzed by IMS using this mechanism at the concentrations expected. Research at NASA Ames and PCP Inc., has demonstrated IMS analysis of expected Titan atmospheric components, including saturated aliphatic hydrocarbons, using two alternate sample ionizations mechanisms. The sensitivity of the IMS to hydrocarbons such as propane and butane was increased by several orders of magnitude. Both ultra dry (waterless) IMS sample ionization and metastable ionization were successfully used to analyze a model Titan atmospheric gas mixture.

Whirling and stability of flywheel systems, part I: Derivation of combined and lumped parameter models

NASA Astrophysics Data System (ADS)

Ramanujam, G.; Bert, C. W.

1983-06-01

The objective of this paper is to provide a theoretical foundation to predict many aspects of dynamic behavior of flywheel systems when spin-tested with a quill shaft support and driven by an air turbine. Theoretical analyses for the following are presented: (1) determination of natural frequencies (or for brevity critical speeds of various orders), (2) Routh-type stability analysis to determine the stability limits (i.e., the speed range within which small perturbations attenuate rather than cause catastrophic failure), and (3) forced whirling analysis to estimate the response of major components of the system to flywheel mass eccentricity and initial tilt. For the first and third kinds of analyses, two different mathematical models of the generic system are investigated. One is a seven-degree-of-freedom lumped parameter analysis, while the other is a combined distributed and lumped parameter analysis.

Uncertainty of quantitative microbiological methods of pharmaceutical analysis.

PubMed

Gunar, O V; Sakhno, N G

2015-12-30

The total uncertainty of quantitative microbiological methods, used in pharmaceutical analysis, consists of several components. The analysis of the most important sources of the quantitative microbiological methods variability demonstrated no effect of culture media and plate-count techniques in the estimation of microbial count while the highly significant effect of other factors (type of microorganism, pharmaceutical product and individual reading and interpreting errors) was established. The most appropriate method of statistical analysis of such data was ANOVA which enabled not only the effect of individual factors to be estimated but also their interactions. Considering all the elements of uncertainty and combining them mathematically the combined relative uncertainty of the test results was estimated both for method of quantitative examination of non-sterile pharmaceuticals and microbial count technique without any product. These data did not exceed 35%, appropriated for a traditional plate count methods. Copyright © 2015 Elsevier B.V. All rights reserved.

Ultra-high-performance liquid chromatography/tandem high-resolution mass spectrometry analysis of sixteen red beverages containing carminic acid: identification of degradation products by using principal component analysis/discriminant analysis.

PubMed

Gosetti, Fabio; Chiuminatto, Ugo; Mazzucco, Eleonora; Mastroianni, Rita; Marengo, Emilio

2015-01-15

The study investigates the sunlight photodegradation process of carminic acid, a natural red colourant used in beverages. For this purpose, both carminic acid aqueous standard solutions and sixteen different commercial beverages, ten containing carminic acid and six containing E120 dye, were subjected to photoirradiation. The results show different patterns of degradation, not only between the standard solutions and the beverages, but also from beverage to beverage. Due to the different beverage recipes, unpredictable reactions take place between the dye and the other ingredients. To identify the dye degradation products in a very complex scenario, a methodology was used, based on the combined use of principal component analysis with discriminant analysis and ultra-high-performance liquid chromatography coupled with tandem high resolution mass spectrometry. The methodology is unaffected by beverage composition and allows the degradation products of carminic acid dye to be identified for each beverage. Copyright © 2014 Elsevier Ltd. All rights reserved.

Differential Lipid Profiles of Normal Human Brain Matter and Gliomas by Positive and Negative Mode Desorption Electrospray Ionization – Mass Spectrometry Imaging

PubMed Central

Pirro, Valentina; Hattab, Eyas M.; Cohen-Gadol, Aaron A.; Cooks, R. Graham

2016-01-01

Desorption electrospray ionization—mass spectrometry (DESI-MS) imaging was used to analyze unmodified human brain tissue sections from 39 subjects sequentially in the positive and negative ionization modes. Acquisition of both MS polarities allowed more complete analysis of the human brain tumor lipidome as some phospholipids ionize preferentially in the positive and others in the negative ion mode. Normal brain parenchyma, comprised of grey matter and white matter, was differentiated from glioma using positive and negative ion mode DESI-MS lipid profiles with the aid of principal component analysis along with linear discriminant analysis. Principal component–linear discriminant analyses of the positive mode lipid profiles was able to distinguish grey matter, white matter, and glioma with an average sensitivity of 93.2% and specificity of 96.6%, while the negative mode lipid profiles had an average sensitivity of 94.1% and specificity of 97.4%. The positive and negative mode lipid profiles provided complementary information. Principal component–linear discriminant analysis of the combined positive and negative mode lipid profiles, via data fusion, resulted in approximately the same average sensitivity (94.7%) and specificity (97.6%) of the positive and negative modes when used individually. However, they complemented each other by improving the sensitivity and specificity of all classes (grey matter, white matter, and glioma) beyond 90% when used in combination. Further principal component analysis using the fused data resulted in the subgrouping of glioma into two groups associated with grey and white matter, respectively, a separation not apparent in the principal component analysis scores plots of the separate positive and negative mode data. The interrelationship of tumor cell percentage and the lipid profiles is discussed, and how such a measure could be used to measure residual tumor at surgical margins. PMID:27658243

A comparison of independent component analysis algorithms and measures to discriminate between EEG and artifact components.

PubMed

Dharmaprani, Dhani; Nguyen, Hoang K; Lewis, Trent W; DeLosAngeles, Dylan; Willoughby, John O; Pope, Kenneth J

2016-08-01

Independent Component Analysis (ICA) is a powerful statistical tool capable of separating multivariate scalp electrical signals into their additive independent or source components, specifically EEG or electroencephalogram and artifacts. Although ICA is a widely accepted EEG signal processing technique, classification of the recovered independent components (ICs) is still flawed, as current practice still requires subjective human decisions. Here we build on the results from Fitzgibbon et al. [1] to compare three measures and three ICA algorithms. Using EEG data acquired during neuromuscular paralysis, we tested the ability of the measures (spectral slope, peripherality and spatial smoothness) and algorithms (FastICA, Infomax and JADE) to identify components containing EMG. Spatial smoothness showed differentiation between paralysis and pre-paralysis ICs comparable to spectral slope, whereas peripherality showed less differentiation. A combination of the measures showed better differentiation than any measure alone. Furthermore, FastICA provided the best discrimination between muscle-free and muscle-contaminated recordings in the shortest time, suggesting it may be the most suited to EEG applications of the considered algorithms. Spatial smoothness results suggest that a significant number of ICs are mixed, i.e. contain signals from more than one biological source, and so the development of an ICA algorithm that is optimised to produce ICs that are easily classifiable is warranted.

Dynamic interactions of the cortical networks during thought suppression.

PubMed

Aso, Toshihiko; Nishimura, Kazuo; Kiyonaka, Takashi; Aoki, Takaaki; Inagawa, Michiyo; Matsuhashi, Masao; Tobinaga, Yoshikazu; Fukuyama, Hidenao

2016-08-01

Thought suppression has spurred extensive research in clinical and preclinical fields, particularly with regard to the paradoxical aspects of this behavior. However, the involvement of the brain's inhibitory system in the dynamics underlying the continuous effort to suppress thoughts has yet to be clarified. This study aims to provide a unified perspective for the volitional suppression of internal events incorporating the current understanding of the brain's inhibitory system. Twenty healthy volunteers underwent functional magnetic resonance imaging while they performed thought suppression blocks alternating with visual imagery blocks. The whole dataset was decomposed by group-independent component analysis into 30 components. After discarding noise components, the 20 valid components were subjected to further analysis of their temporal properties including task-relatedness and between-component residual correlation. Combining a long task period and a data-driven approach, we observed a right-side-dominant, lateral frontoparietal network to be strongly suppression related. This network exhibited increased fluctuation during suppression, which is compatible with the well-known difficulty of suppression maintenance. Between-network correlation provided further insight into the coordinated engagement of the executive control and dorsal attention networks, as well as the reciprocal activation of imagery-related components, thus revealing neural substrates associated with the rivalry between intrusive thoughts and the suppression process.

An Expanded Combined Evidence Approach to the Gavialis Problem Using Geometric Morphometric Data from Crocodylian Braincases and Eustachian Systems

PubMed Central

Gold, Maria Eugenia Leone; Brochu, Christopher A.; Norell, Mark A.

2014-01-01

The phylogenetic position of the Indian gharial (Gavialis gangeticus) is disputed - morphological characters place Gavialis as the sister to all other extant crocodylians, whereas molecular and combined analyses find Gavialis and the false gharial (Tomistoma schlegelii) to be sister taxa. Geometric morphometric techniques have only begun to be applied to this issue, but most of these studies have focused on the exterior of the skull. The braincase has provided useful phylogenetic information for basal crurotarsans, but has not been explored for the crown group. The Eustachian system is thought to vary phylogenetically in Crocodylia, but has not been analytically tested. To determine if gross morphology of the crocodylian braincase proves informative to the relationships of Gavialis and Tomistoma, we used two- and three-dimensional geometric morphometric approaches. Internal braincase images were obtained using high-resolution computerized tomography scans. A principal components analysis identified that the first component axis was primarily associated with size and did not show groupings that divide the specimens by phylogenetic affinity. Sliding semi-landmarks and a relative warp analysis indicate that a unique Eustachian morphology separates Gavialis from other extant members of Crocodylia. Ontogenetic expansion of the braincase results in a more dorsoventrally elongate median Eustachian canal. Changes in the shape of the Eustachian system do provide phylogenetic distinctions between major crocodylian clades. Each morphometric dataset, consisting of continuous morphological characters, was added independently to a combined cladistic analysis of discrete morphological and molecular characters. The braincase data alone produced a clade that included crocodylids and Gavialis, whereas the Eustachian data resulted in Gavialis being considered a basally divergent lineage. When each morphometric dataset was used in a combined analysis with discrete morphological and molecular characters, it generated a tree that matched the topology of the molecular phylogeny of Crocodylia. PMID:25198124

Monitoring and evaluating the quality consistency of Compound Bismuth Aluminate tablets by a simple quantified ratio fingerprint method combined with simultaneous determination of five compounds and correlated with antioxidant activities.

PubMed

Liu, Yingchun; Liu, Zhongbo; Sun, Guoxiang; Wang, Yan; Ling, Junhong; Gao, Jiayue; Huang, Jiahao

2015-01-01

A combination method of multi-wavelength fingerprinting and multi-component quantification by high performance liquid chromatography (HPLC) coupled with diode array detector (DAD) was developed and validated to monitor and evaluate the quality consistency of herbal medicines (HM) in the classical preparation Compound Bismuth Aluminate tablets (CBAT). The validation results demonstrated that our method met the requirements of fingerprint analysis and quantification analysis with suitable linearity, precision, accuracy, limits of detection (LOD) and limits of quantification (LOQ). In the fingerprint assessments, rather than using conventional qualitative "Similarity" as a criterion, the simple quantified ratio fingerprint method (SQRFM) was recommended, which has an important quantified fingerprint advantage over the "Similarity" approach. SQRFM qualitatively and quantitatively offers the scientific criteria for traditional Chinese medicines (TCM)/HM quality pyramid and warning gate in terms of three parameters. In order to combine the comprehensive characterization of multi-wavelength fingerprints, an integrated fingerprint assessment strategy based on information entropy was set up involving a super-information characteristic digitized parameter of fingerprints, which reveals the total entropy value and absolute information amount about the fingerprints and, thus, offers an excellent method for fingerprint integration. The correlation results between quantified fingerprints and quantitative determination of 5 marker compounds, including glycyrrhizic acid (GLY), liquiritin (LQ), isoliquiritigenin (ILG), isoliquiritin (ILQ) and isoliquiritin apioside (ILA), indicated that multi-component quantification could be replaced by quantified fingerprints. The Fenton reaction was employed to determine the antioxidant activities of CBAT samples in vitro, and they were correlated with HPLC fingerprint components using the partial least squares regression (PLSR) method. In summary, the method of multi-wavelength fingerprints combined with antioxidant activities has been proved to be a feasible and scientific procedure for monitoring and evaluating the quality consistency of CBAT.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

Classification of high-resolution multispectral satellite remote sensing images using extended morphological attribute profiles and independent component analysis

NASA Astrophysics Data System (ADS)

Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei

2017-07-01

In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.

Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis

NASA Astrophysics Data System (ADS)

Tonannavar, J.; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B.; Patil, Nikhil A.; Mulimani, B. G.

2016-02-01

We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400 cm- 1) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH.

Identification of mineral compositions in some renal calculi by FT Raman and IR spectral analysis.

PubMed

Tonannavar, J; Deshpande, Gouri; Yenagi, Jayashree; Patil, Siddanagouda B; Patil, Nikhil A; Mulimani, B G

2016-02-05

We present in this paper accurate and reliable Raman and IR spectral identification of mineral constituents in nine samples of renal calculi (kidney stones) removed from patients suffering from nephrolithiasis. The identified mineral components include Calcium Oxalate Monohydrate (COM, whewellite), Calcium Oxalate Dihydrate (COD, weddellite), Magnesium Ammonium Phosphate Hexahydrate (MAPH, struvite), Calcium Hydrogen Phosphate Dihydrate (CHPD, brushite), Pentacalcium Hydroxy Triphosphate (PCHT, hydroxyapatite) and Uric Acid (UA). The identification is based on a satisfactory assignment of all the observed IR and Raman bands (3500-400c m(-1)) to chemical functional groups of mineral components in the samples, aided by spectral analysis of pure materials of COM, MAPH, CHPD and UA. It is found that the eight samples are composed of COM as the common component, the other mineral species as common components are: MAPH in five samples, PCHT in three samples, COD in three samples, UA in three samples and CHPD in two samples. One sample is wholly composed of UA as a single component; this inference is supported by the good agreement between ab initio density functional theoretical spectra and experimental spectral measurements of both sample and pure material. A combined application of Raman and IR techniques has shown that, where the IR is ambiguous, the Raman analysis can differentiate COD from COM and PCHT from MAPH. Copyright © 2015 Elsevier B.V. All rights reserved.

Comparative analysis on flexibility requirements of typical Cryogenic Transfer lines

NASA Astrophysics Data System (ADS)

Jadon, Mohit; Kumar, Uday; Choukekar, Ketan; Shah, Nitin; Sarkar, Biswanath

2017-04-01

The cryogenic systems and their applications; primarily in large Fusion devices, utilize multiple cryogen transfer lines of various sizes and complexities to transfer cryogenic fluids from plant to the various user/ applications. These transfer lines are composed of various critical sections i.e. tee section, elbows, flexible components etc. The mechanical sustainability (under failure circumstances) of these transfer lines are primary requirement for safe operation of the system and applications. The transfer lines need to be designed for multiple design constraints conditions like line layout, support locations and space restrictions. The transfer lines are subjected to single load and multiple load combinations, such as operational loads, seismic loads, leak in insulation vacuum loads etc. [1]. The analytical calculations and flexibility analysis using professional software are performed for the typical transfer lines without any flexible component, the results were analysed for functional and mechanical load conditions. The failure modes were identified along the critical sections. The same transfer line was then refurbished with the flexible components and analysed for failure modes. The flexible components provide additional flexibility to the transfer line system and make it safe. The results obtained from the analytical calculations were compared with those obtained from the flexibility analysis software calculations. The optimization of the flexible component’s size and selection was performed and components were selected to meet the design requirements as per code.

GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution

PubMed Central

2011-01-01

Background Ontologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data. Results We present GOMMA, a generic infrastructure for managing and analyzing life science ontologies and their evolution. GOMMA utilizes a generic repository to uniformly and efficiently manage ontology versions and different kinds of mappings. Furthermore, it provides components for ontology matching, and determining evolutionary ontology changes. These components are used by analysis tools, such as the Ontology Evolution Explorer (OnEX) and the detection of unstable ontology regions. We introduce the component-based infrastructure and show analysis results for selected components and life science applications. GOMMA is available at http://dbs.uni-leipzig.de/GOMMA. Conclusions GOMMA provides a comprehensive and scalable infrastructure to manage large life science ontologies and analyze their evolution. Key functions include a generic storage of ontology versions and mappings, support for ontology matching and determining ontology changes. The supported features for analyzing ontology changes are helpful to assess their impact on ontology-dependent applications such as for term enrichment. GOMMA complements OnEX by providing functionalities to manage various versions of mappings between two ontologies and allows combining different match approaches. PMID:21914205

Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish

USGS Publications Warehouse

Dzul, Maria C.; Dixon, Philip M.; Quist, Michael C.; Dinsomore, Stephen J.; Bower, Michael R.; Wilson, Kevin P.; Gaines, D. Bailey

2013-01-01

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

Analysis of minerals containing dissolved traces of the fluid phase components water and carbon dioxide

NASA Technical Reports Server (NTRS)

Freund, Friedemann

1991-01-01

Substantial progress has been made towards a better understanding of the dissolution of common gas/fluid phase components, notably H2O and CO2, in minerals. It has been shown that the dissolution mechanisms are significantly more complex than currently believed. By judiciously combining various solid state analytical techniques, convincing evidence was obtained that traces of dissolved gas/fluid phase components undergo, at least in part, a redox conversion by which they split into reduced H2 and and reduced C on one hand and oxidized oxygen, O(-), on the other. Analysis for 2 and C as well as for any organic molecules which may form during the process of co-segregation are still impeded by the omnipresent danger of extraneous contamination. However, the presence of O(-), an unusual oxidized form of oxygen, has been proven beyond a reasonable doubt. The presence of O(-) testifies to the fact that a redox reaction must have taken place in the solid state involving the dissolved traces of gas/fluid phase components. Detailed information on the techniques used and the results obtained are given.

Effect of photodegradation and biodegradation on the concentration and composition of dissolved organic matter in diverse waterbodies

NASA Astrophysics Data System (ADS)

Manalilkada Sasidharan, S.; Dash, P.; Singh, S.; Lu, Y.

2017-12-01

The objective of this research was to quantify the effects of photodegradation and biodegradation on the dissolved organic matter (DOM) concentration and composition in five distinct waterbodies with diverse types of watershed land use and land cover in the southeastern United States. The water bodies included an agricultural pond, a lake in a predominantly forested watershed, a man-made reservoir, an estuary, and a bay. Two sets of samples were prepared from these water bodies by dispensing filtered water samples to unfiltered samples in 10:1 ratio. The first set was kept in the sunlight during the day (12 hours), and colored dissolved organic matter (CDOM) absorption and fluorescence were measured periodically over a 30-day period for examining the effects of combined photo- and biodegradation. The second set of samples was kept in the dark for examining the effects of biodegradation alone, and CDOM absorption and fluorescence were measured at the same time as the sunlight-exposed samples. Subsequently, spectrometric results in tandem with multivariate statistical analysis were used to interpret the lability vs. composition of DOM. Parallel factor analysis (PARAFAC) revealed the presence of four DOM components (C1-C4). C1 and C4 were microbial tryptophan-like, labile lighter components, while C2 and C3 were terrestrial humic like or fulvic acid type, larger aromatic refractory components. The principal component analysis (PCA) also revealed two distinct groups of DOM - C1 and C4 vs. C2 and C3. The negative PC1 loadings of C2, C3, HIX, a254 and SUVA indicated humic-like or fulvic-like structurally complex refractory aromatic DOM originated from higher plants in forested areas. C1, C4, SR, FI and BI had positive PC1 loadings, which indicated structurally simpler labile DOM were derived from agricultural areas or microbial activity. There was a decrease in dissolved organic carbon (DOC) due to combined photo- and biodegradation, and transformation of components C2, C3 into components C1, C4 was at a much faster rate than only biodegradation. This observation suggests that the presence of sunlight facilitated the degradation of larger, recalcitrant, terrestrial humic-like compounds into smaller, labile microbial components.

Determination of molecular weight distributions in native and pretreated wood.

PubMed

Leskinen, Timo; Kelley, Stephen S; Argyropoulos, Dimitris S

2015-03-30

The analysis of native wood components by size-exclusion chromatography (SEC) is challenging. Isolation, derivatization and solubilization of wood polymers is required prior to the analysis. The present approach allowed the determination of molecular weight distributions of the carbohydrates and of lignin in native and processed woods, without preparative component isolation steps. For the first time a component selective SEC analysis of sawdust preparations was made possible by the combination of two selective derivatization methods, namely; ionic liquid assisted benzoylation of the carbohydrate fraction and acetobromination of the lignin in acetic acid media. These were optimized for wood samples. The developed method was thus used to examine changes in softwood samples after degradative mechanical and/or chemical treatments, such as ball milling, steam explosion, green liquor pulping, and chemical oxidation with 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ). The methodology can also be applied to examine changes in molecular weight and lignin-carbohydrate linkages that occur during wood-based biorefinery operations, such as pretreatments, and enzymatic saccharification. Copyright © 2014 Elsevier Ltd. All rights reserved.

Icon flickering, flicker rate, and color combinations of an icon's symbol/background in visual search performance.

PubMed

Huang, Kuo-Chen; Chiang, Shu-Ying; Chen, Chen-Fu

2008-02-01

The effects of color combinations of an icon's symbol/background and components of flicker and flicker rate on visual search performance on a liquid crystal display screen were investigated with 39 subjects who searched for a target icon in a circular stimulus array (diameter = 20 cm) including one target and 19 distractors. Analysis showed that the icon's symbol/background color significantly affected search time. The search times for icons with black/red and white/blue were significantly shorter than for white/yellow, black/yellow, and black/blue. Flickering of different components of the icon significantly affected the search time. Search time for an icon's border flickering was shorter than for an icon symbol flickering; search for flicker rates of 3 and 5 Hz was shorter than that for 1 Hz. For icon's symbol/background color combinations, search error rate for black/blue was greater than for black/red and white/blue combinations, and the error rate for an icon's border flickering was lower than for an icon's symbol flickering. Interactions affected search time and error rate. Results are applicable to design of graphic user interfaces.

Analysis of metabolic syndrome components in >15 000 african americans identifies pleiotropic variants: results from the population architecture using genomics and epidemiology study.

PubMed

Carty, Cara L; Bhattacharjee, Samsiddhi; Haessler, Jeff; Cheng, Iona; Hindorff, Lucia A; Aroda, Vanita; Carlson, Christopher S; Hsu, Chun-Nan; Wilkens, Lynne; Liu, Simin; Selvin, Elizabeth; Jackson, Rebecca; North, Kari E; Peters, Ulrike; Pankow, James S; Chatterjee, Nilanjan; Kooperberg, Charles

2014-08-01

Metabolic syndrome (MetS) refers to the clustering of cardiometabolic risk factors, including dyslipidemia, central adiposity, hypertension, and hyperglycemia, in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. Using the Metabochip array in 15 148 African Americans from the Population Architecture using Genomics and Epidemiology (PAGE) study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models that lack power when associations for MetS components are null or have opposite effects, Association-analysis-based-on-subsets uses 1-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With Association-analysis-based-on-subsets, we identify 27 single nucleotide polymorphisms in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, and APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P<2.5e-7, the Bonferroni adjusted P value. Three loci replicate in a Hispanic population, n=5172. A novel African American-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2, and CETP variants, many with opposing effects (eg, the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity). We highlight a method to increase power in large-scale genomic association analyses and report a novel variant associated with all MetS components in African Americans. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications. © 2014 American Heart Association, Inc.

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Capillary electrophoresis fingerprinting and spectrophotometric determination of antioxidant potential for classification of Mentha products.

PubMed

Roblová, Vendula; Bittová, Miroslava; Kubáň, Petr; Kubáň, Vlastimil

2016-07-01

In this work aqueous infusions from ten Mentha herbal samples (four different Mentha species and six hybrids of Mentha x piperita) and 20 different peppermint teas were screened by capillary electrophoresis with UV detection. The fingerprint separation was accomplished in a 25 mM borate background electrolyte with 10% methanol at pH 9.3. The total polyphenolic content in the extracts was determined spectrophotometrically at 765 nm by a Folin-Ciocalteu phenol assay. Total antioxidant activity was determined by scavenging of 2,2-diphenyl-1-picrylhydrazyl radical at 515 nm. The peak areas of 12 dominant peaks from CE analysis, present in all samples, and the value of total polyphenolic content and total antioxidant activity obtained by spectrophotometry was combined into a single data matrix and principal component analysis was applied. The obtained principal component analysis model resulted in distinct clusters of Mentha and peppermint tea samples distinguishing the samples according to their potential protective antioxidant effect. Principal component analysis, using a non-targeted approach with no need for compound identification, was found as a new promising tool for the screening of herbal tea products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Exploratory factor analysis of the Clinical Learning Environment, Supervision and Nurse Teacher Scale (CLES+T).

PubMed

Watson, Paul Barry; Seaton, Philippa; Sims, Deborah; Jamieson, Isabel; Mountier, Jane; Whittle, Rose; Saarikoski, Mikko

2014-01-01

The Clinical Learning Environment, Supervision and Nurse Teacher (CLES+T) scale measures student nurses' perceptions of clinical learning environments. This study evaluates the construct validity and internal reliability of the CLES+T in hospital settings in New Zealand. Comparisons are made between New Zealand and Finnish data. The CLES+T scale was completed by 416 Bachelor of Nursing students following hospital clinical placements between October 2008 and December 2009. Construct validity and internal reliability were assessed using exploratory factor analysis and Cronbach's alpha. Exploratory factor analysis supports 4 factors. Cronbach's alpha ranged from .82 to .93. All items except 1 loaded on the same factors found in unpublished Finnish data. The first factor combined 2 previous components from the published Finnish component analysis and was renamed: connecting with, and learning in, communities of clinical practice. The remaining 3 factors (Nurse teacher, Supervisory relationship, and Leadership style of the manager) corresponded to previous components and their conceptualizations. The CLES+T has good internal reliability and a consistent factor structure across samples. The consistency across international samples supports faculties and hospitals using the CLES+T to benchmark the quality of clinical learning environments provided to students.

Analysis of E. rutaecarpa Alkaloids Constituents In Vitro and In Vivo by UPLC-Q-TOF-MS Combined with Diagnostic Fragment

PubMed Central

Yang, Shenshen; Tian, Meng; Yuan, Lei; Deng, Haoyue; Wang, Lei; Li, Aizhu; Hou, Zhiguo; Li, Yubo

2016-01-01

Evodia rutaecarpa (Juss.) Benth. (Rutaceae) dried ripe fruit is used for dispelling colds, soothing liver, and analgesia. Pharmacological research has proved that alkaloids are the main active ingredients of E. rutaecarpa. This study aimed to rapidly classify and identify the alkaloids constituents of E. rutaecarpa by using UPLC-Q-TOF-MS coupled with diagnostic fragments. Furthermore, the effects of the material base of E. rutaecarpa bioactive ingredients in vivo were examined such that the transitional components in the blood of rats intragastrically given E. rutaecarpa were analyzed and identified. In this study, the type of alcohol extraction of E. rutaecarpa and the corresponding blood sample were used for the analysis by UPLC-Q-TOF-MS in positive ion mode. After reviewing much of the literature and collected information on the fragments, we obtained some diagnostic fragments of the alkaloids. Combining the diagnostic fragments with the technology of UPLC-Q-TOF-MS, we identified the compounds of E. rutaecarpa and blood samples and compared the ion fragment information with that of the alkaloids in E. rutaecarpa. A total of 17 alkaloids components and 6 blood components were identified. The proposed method was rapid, accurate, and sensitive. Therefore, this technique can reliably and practically analyze the chemical constituents in traditional Chinese medicine (TCM). PMID:27446630

Effects of Structural Flexibility on Aircraft-Engine Mounts

NASA Technical Reports Server (NTRS)

Phillips, W. H.

1986-01-01

Analysis extends technique for design of widely used type of vibration-isolating mounts for aircraft engines, in which rubber mounting pads located in plane behind center of gravity of enginepropeller combination. New analysis treats problem in statics. Results of simple approach useful in providing equations for design of vibrationisolating mounts. Equations applicable in usual situation in which engine-mount structure itself relatively light and placed between large mass of engine and other heavy components of airplane.

1998 UBV Light Curves of Eclipsing Binary AI Draconis and Absolute Parameters

NASA Astrophysics Data System (ADS)

Jassur, D. M. Z.; Khaledian, M. S.; Kermani, M. H.

New UBV photometry of Algol-Type eclipsing binary star AI Dra and the absolute physical parameters of this system have been presented. The light curve analysis carried out by the method of differential corrections indicates that both components are inside their Roche-Lobes. From combining the photometric solution with spectroscopic data obtained from velocity curve analysis, it has been found that the system consist of a main sequence primary and an evolved (subgiant) secondary.

Use of NMR Metabolomics to Analyze the Targets of D-cycloserine in Mycobacteria: Role of D-Alanine Racemase

PubMed Central

Halouska, Steven; Chacon, Ofelia; Fenton, Robert J.; Zinniel, Denise K.; Barletta, Raul G.; Powers, Robert

2008-01-01

D-cycloserine (DCS) is only used with multi-drug resistant strains of tuberculosis because of serious side-effects. DCS is known to inhibit cell wall biosynthesis, but the in vivo lethal target is still unknown. We have applied NMR-based metabolomics combined with principal component analysis to monitor the in vivo affect of DCS on M. smegmatis. Our analysis suggests DCS functions by inhibiting multiple protein targets. PMID:17979227

Optical path switching based differential absorption radiometry for substance detection

NASA Technical Reports Server (NTRS)

Sachse, Glen W. (Inventor)

2005-01-01

An optical path switch divides sample path radiation into a time series of alternating first polarized components and second polarized components. The first polarized components are transmitted along a first optical path and the second polarized components along a second optical path. A first gasless optical filter train filters the first polarized components to isolate at least a first wavelength band thereby generating first filtered radiation. A second gasless optical filter train filters the second polarized components to isolate at least a second wavelength band thereby generating second filtered radiation. A beam combiner combines the first and second filtered radiation to form a combined beam of radiation. A detector is disposed to monitor magnitude of at least a portion of the combined beam alternately at the first wavelength band and the second wavelength band as an indication of the concentration of the substance in the sample path.

Optical path switching based differential absorption radiometry for substance detection

NASA Technical Reports Server (NTRS)

Sachse, Glen W. (Inventor)

2003-01-01

An optical path switch divides sample path radiation into a time series of alternating first polarized components and second polarized components. The first polarized components are transmitted along a first optical path and the second polarized components along a second optical path. A first gasless optical filter train filters the first polarized components to isolate at least a first wavelength band thereby generating first filtered radiation. A second gasless optical filter train filters the second polarized components to isolate at least a second wavelength band thereby generating second filtered radiation. A beam combiner combines the first and second filtered radiation to form a combined beam of radiation. A detector is disposed to monitor magnitude of at least a portion of the combined beam alternately at the first wavelength band and the second wavelength band as an indication of the concentration of the substance in the sample path.

Linked independent component analysis for multimodal data fusion.

PubMed

Groves, Adrian R; Beckmann, Christian F; Smith, Steve M; Woolrich, Mark W

2011-02-01

In recent years, neuroimaging studies have increasingly been acquiring multiple modalities of data and searching for task- or disease-related changes in each modality separately. A major challenge in analysis is to find systematic approaches for fusing these differing data types together to automatically find patterns of related changes across multiple modalities, when they exist. Independent Component Analysis (ICA) is a popular unsupervised learning method that can be used to find the modes of variation in neuroimaging data across a group of subjects. When multimodal data is acquired for the subjects, ICA is typically performed separately on each modality, leading to incompatible decompositions across modalities. Using a modular Bayesian framework, we develop a novel "Linked ICA" model for simultaneously modelling and discovering common features across multiple modalities, which can potentially have completely different units, signal- and contrast-to-noise ratios, voxel counts, spatial smoothnesses and intensity distributions. Furthermore, this general model can be configured to allow tensor ICA or spatially-concatenated ICA decompositions, or a combination of both at the same time. Linked ICA automatically determines the optimal weighting of each modality, and also can detect single-modality structured components when present. This is a fully probabilistic approach, implemented using Variational Bayes. We evaluate the method on simulated multimodal data sets, as well as on a real data set of Alzheimer's patients and age-matched controls that combines two very different types of structural MRI data: morphological data (grey matter density) and diffusion data (fractional anisotropy, mean diffusivity, and tensor mode). Copyright © 2010 Elsevier Inc. All rights reserved.

Searching for the main anti-bacterial components in artificial Calculus bovis using UPLC and microcalorimetry coupled with multi-linear regression analysis.

PubMed

Zang, Qing-Ce; Wang, Jia-Bo; Kong, Wei-Jun; Jin, Cheng; Ma, Zhi-Jie; Chen, Jing; Gong, Qian-Feng; Xiao, Xiao-He

2011-12-01

The fingerprints of artificial Calculus bovis extracts from different solvents were established by ultra-performance liquid chromatography (UPLC) and the anti-bacterial activities of artificial C. bovis extracts on Staphylococcus aureus (S. aureus) growth were studied by microcalorimetry. The UPLC fingerprints were evaluated using hierarchical clustering analysis. Some quantitative parameters obtained from the thermogenic curves of S. aureus growth affected by artificial C. bovis extracts were analyzed using principal component analysis. The spectrum-effect relationships between UPLC fingerprints and anti-bacterial activities were investigated using multi-linear regression analysis. The results showed that peak 1 (taurocholate sodium), peak 3 (unknown compound), peak 4 (cholic acid), and peak 6 (chenodeoxycholic acid) are more significant than the other peaks with the standard parameter estimate 0.453, -0.166, 0.749, 0.025, respectively. So, compounds cholic acid, taurocholate sodium, and chenodeoxycholic acid might be the major anti-bacterial components in artificial C. bovis. Altogether, this work provides a general model of the combination of UPLC chromatography and anti-bacterial effect to study the spectrum-effect relationships of artificial C. bovis extracts, which can be used to discover the main anti-bacterial components in artificial C. bovis or other Chinese herbal medicines with anti-bacterial effects. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Decomposition-Based Failure Mode Identification Method for Risk-Free Design of Large Systems

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Stone, Robert B.; Roberts, Rory A.; Clancy, Daniel (Technical Monitor)

2002-01-01

When designing products, it is crucial to assure failure and risk-free operation in the intended operating environment. Failures are typically studied and eliminated as much as possible during the early stages of design. The few failures that go undetected result in unacceptable damage and losses in high-risk applications where public safety is of concern. Published NASA and NTSB accident reports point to a variety of components identified as sources of failures in the reported cases. In previous work, data from these reports were processed and placed in matrix form for all the system components and failure modes encountered, and then manipulated using matrix methods to determine similarities between the different components and failure modes. In this paper, these matrices are represented in the form of a linear combination of failures modes, mathematically formed using Principal Components Analysis (PCA) decomposition. The PCA decomposition results in a low-dimensionality representation of all failure modes and components of interest, represented in a transformed coordinate system. Such a representation opens the way for efficient pattern analysis and prediction of failure modes with highest potential risks on the final product, rather than making decisions based on the large space of component and failure mode data. The mathematics of the proposed method are explained first using a simple example problem. The method is then applied to component failure data gathered from helicopter, accident reports to demonstrate its potential.

A New Approach for Quantitative Evaluation of Ultrasonic Wave Attenuation in Composites

NASA Astrophysics Data System (ADS)

Ni, Qing-Qing; Li, Ran; Xia, Hong

2017-02-01

When ultrasonic waves propagate in composite materials, the propagation behaviors result from the combination effects of various factors, such as material anisotropy and viscoelastic property, internal microstructure and defects, incident wave characteristics and interface condition between composite components. It is essential to make it clear how these factors affect the ultrasonic wave propagation and attenuation characteristics, and how they mutually interact on each other. In the present paper, based on a newly developed time-domain finite element analysis code, PZflex, a unique approach for clarifying the detailed influence mechanism of aforementioned factors is proposed, in which each attenuation component can be extracted from the overall attenuation and analyzed respectively. By taking into consideration the interrelation between each individual attenuation component, the variation behaviors of each component and internal dynamic stress distribution against material anisotropy and matrix viscosity are separately and quantitatively evaluated. From the detailed analysis results of each attenuation component, the energy dissipation at interface is a major component in ultrasonic wave attenuation characteristics, which can provide a maximum contribution rate of 68.2 % to the overall attenuation, and each attenuation component is closely related to the material anisotropy and viscoelasticity. The results clarify the correlation between ultrasonic wave propagation characteristics and material viscoelastic properties, which will be useful in the further development of ultrasonic technology in defect detection.

Using McStas for modelling complex optics, using simple building bricks

NASA Astrophysics Data System (ADS)

Willendrup, Peter K.; Udby, Linda; Knudsen, Erik; Farhi, Emmanuel; Lefmann, Kim

2011-04-01

The McStas neutron ray-tracing simulation package is a versatile tool for producing accurate neutron simulations, extensively used for design and optimization of instruments, virtual experiments, data analysis and user training.In McStas, component organization and simulation flow is intrinsically linear: the neutron interacts with the beamline components in a sequential order, one by one. Historically, a beamline component with several parts had to be implemented with a complete, internal description of all these parts, e.g. a guide component including all four mirror plates and required logic to allow scattering between the mirrors.For quite a while, users have requested the ability to allow “components inside components” or meta-components, allowing to combine functionality of several simple components to achieve more complex behaviour, i.e. four single mirror plates together defining a guide.We will here show that it is now possible to define meta-components in McStas, and present a set of detailed, validated examples including a guide with an embedded, wedged, polarizing mirror system of the Helmholtz-Zentrum Berlin type.

Temporal dynamic of malaria in a suburban area along the Niger River.

PubMed

Sissoko, Mahamadou Soumana; Sissoko, Kourane; Kamate, Bourama; Samake, Yacouba; Goita, Siaka; Dabo, Abdoulaye; Yena, Mama; Dessay, Nadine; Piarroux, Renaud; Doumbo, Ogobara K; Gaudart, Jean

2017-10-23

Even if rainfall and temperature are factors classically associated to malaria, little is known about other meteorological factors, their variability and combinations related to malaria, in association with river height variations. Furthermore, in suburban area, urbanization and growing population density should be assessed in relation to these environmental factors. The aim of this study was to assess the impact of combined environmental, meteorological and hydrological factors on malaria incidence through time in the context of urbanization. Population observational data were prospectively collected. Clinical malaria was defined as the presence of parasites in addition to clinical symptoms. Meteorological and hydrological factors were measured daily. For each factors variation indices were estimated. Urbanization was yearly estimated assessing satellite imaging and field investigations. Principal component analysis was used for dimension reduction and factors combination. Lags between malaria incidences and the main components were assessed by cross-correlation functions. Generalized additive model was used to assess relative impact of different environmental components, taking into account lags, and modelling non-linear relationships. Change-point analysis was used to determine transmission periods within years. Malaria incidences were dominated by annual periodicity and varied through time without modification of the dynamic, with no impact of the urbanization. The main meteorological factor associated with malaria was a combination of evaporation, humidity and rainfall, with a lag of 3 months. The relationship between combined temperature factors showed a linear impact until reaching high temperatures limiting malaria incidence, with a lag 3.25 months. Height and variation of the river were related to malaria incidence (respectively 6 week lag and no lag). The study emphasizes no decreasing trend of malaria incidence despite accurate access to care and control strategies in accordance to international recommendations. Furthermore, no decreasing trend was showed despite the urbanization of the area. Malaria transmission remain increase 3 months after the beginning of the dry season. Addition to evaporation versus humidity/rainfall, nonlinear relationship for temperature and river height and variations have to be taken into account when implementing malaria control programmes.

Comparison between Slow Components of HR and V[Combining Dot Above]O2 Kinetics: Functional Significance.

PubMed

Zuccarelli, Lucrezia; Porcelli, Simone; Rasica, Letizia; Marzorati, Mauro; Grassi, Bruno

2018-03-22

Aerobic exercise prescription is often based on a linear relationship between pulmonary oxygen consumption (V[Combining Dot Above]O2) and heart rate (HR). The aim of the present study was to test the hypothesis that during constant work rate (CWR) exercises at different intensities the slow component of HR kinetics occurs at lower work rate and is more pronounced that the slow component of V[Combining Dot Above]O2 kinetics. Seventeen male (age, 27±4yr) subjects performed on a cycle ergometer an incremental exercise to voluntary exhaustion and several CWR exercises: 1) moderate CWR exercises (MODERATE), below gas exchange threshold (GET); 2) heavy CWR exercise (HEAVY), at 45% of the difference between GET and V[Combining Dot Above]O2 peak (□); 3) severe CWR exercise (SEVERE), at 95% of Δ; 4) "HRCLAMPED" exercise in which work rate was continuously adjusted to maintain a constant HR, slightly higher than that determined at GET. Breath-by-breath V[Combining Dot Above]O2, HR and other variables were determined. In MODERATE, no slow component of V[Combining Dot Above]O2 kinetics was observed, whereas a slow component with a relative amplitude (with respect to the total response) of 24.8±11.0% was observed for HR kinetics. During HEAVY, the relative amplitude of the HR slow component was more pronounced than that for V[Combining Dot Above]O2 (31.6±11.2 and 23.3±9.0%, respectively). During HRCLAMPED the decrease in work rate (~14%) needed in order to maintain a constant HR was associated with a decreased V[Combining Dot Above]O2 (~10%). The HR slow component occurred at a lower work rate and was more pronounced than the V[Combining Dot Above]O2 slow component. Exercise prescriptions at specific HR values, when carried out for periods longer than a few minutes, could lead to premature fatigue.

Identification and quantification of antioxidant components of honeys from various floral sources.

PubMed

Gheldof, Nele; Wang, Xiao-Hong; Engeseth, Nicki J

2002-10-09

Little is known about the individual components of honey that are responsible for its antioxidant activity. The present study was carried out to characterize the phenolics and other antioxidants present in honeys from seven floral sources. Chromatograms of the phenolic nonpolar fraction of the honeys indicated that most honeys have similar but quantitatively different phenolic profiles. Many of the flavonoids and phenolic acids identified have been previously described as potent antioxidants. A linear correlation between phenolic content and ORAC activity was demonstrated (R(2) = 0.963, p < 0.0001). Honeys were separated by solid-phase extraction into four fractions for sugar removal and separation based on solubility to identify the relative contribution of each fraction to the antioxidant activity of honey. Antioxidant analysis of the different honey fractions suggested that the water-soluble fraction contained most of the antioxidant components. Specific water-soluble antioxidant components were quantified, including protein; gluconic acid; ascorbic acid; hydroxymethylfuraldehyde; and the combined activities of the enzymes glucose oxidase, catalase and peroxidase. Of these components, a significant correlation could be established only between protein content and ORAC activity (R(2) = 0.674, p = 0.024). In general, the antioxidant capacity of honey appeared to be a result of the combined activity of a wide range of compounds including phenolics, peptides, organic acids, enzymes, Maillard reaction products, and possibly other minor components. The phenolic compounds contributed significantly to the antioxidant capacity of honey but were not solely responsible for it.

Near-infrared confocal micro-Raman spectroscopy combined with PCA-LDA multivariate analysis for detection of esophageal cancer

NASA Astrophysics Data System (ADS)

Chen, Long; Wang, Yue; Liu, Nenrong; Lin, Duo; Weng, Cuncheng; Zhang, Jixue; Zhu, Lihuan; Chen, Weisheng; Chen, Rong; Feng, Shangyuan

2013-06-01

The diagnostic capability of using tissue intrinsic micro-Raman signals to obtain biochemical information from human esophageal tissue is presented in this paper. Near-infrared micro-Raman spectroscopy combined with multivariate analysis was applied for discrimination of esophageal cancer tissue from normal tissue samples. Micro-Raman spectroscopy measurements were performed on 54 esophageal cancer tissues and 55 normal tissues in the 400-1750 cm-1 range. The mean Raman spectra showed significant differences between the two groups. Tentative assignments of the Raman bands in the measured tissue spectra suggested some changes in protein structure, a decrease in the relative amount of lactose, and increases in the percentages of tryptophan, collagen and phenylalanine content in esophageal cancer tissue as compared to those of a normal subject. The diagnostic algorithms based on principal component analysis (PCA) and linear discriminate analysis (LDA) achieved a diagnostic sensitivity of 87.0% and specificity of 70.9% for separating cancer from normal esophageal tissue samples. The result demonstrated that near-infrared micro-Raman spectroscopy combined with PCA-LDA analysis could be an effective and sensitive tool for identification of esophageal cancer.

The correlation between biofilm biopolymer composition and membrane fouling in submerged membrane bioreactors.

PubMed

Luo, Jinxue; Zhang, Jinsong; Tan, Xiaohui; McDougald, Diane; Zhuang, Guoqiang; Fane, Anthony G; Kjelleberg, Staffan; Cohen, Yehuda; Rice, Scott A

2014-10-01

Biofouling, the combined effect of microorganism and biopolymer accumulation, significantly reduces the process efficiency of membrane bioreactors (MBRs). Here, four biofilm components, alpha-polysaccharides, beta-polysaccharides, proteins and microorganisms, were quantified in MBRs. The biomass of each component was positively correlated with the transmembrane pressure increase in MBRs. Proteins were the most abundant biopolymer in biofilms and showed the fastest rate of increase. The spatial distribution and co-localization analysis of the biofouling components indicated at least 60% of the extracellular polysaccharide (EPS) components were associated with the microbial cells when the transmembrane pressure (TMP) entered the jump phase, suggesting that the EPS components were either secreted by the biofilm cells or that the deposition of these components facilitated biofilm formation. It is suggested that biofilm formation and the accumulation of EPS are intrinsically coupled, resulting in biofouling and loss of system performance. Therefore, strategies that control biofilm formation on membranes may result in a significant improvement of MBR performance.

Performance assessment and optimisation of a large information system by combined customer relationship management and resilience engineering: a mathematical programming approach

NASA Astrophysics Data System (ADS)

Azadeh, A.; Foroozan, H.; Ashjari, B.; Motevali Haghighi, S.; Yazdanparast, R.; Saberi, M.; Torki Nejad, M.

2017-10-01

ISs and ITs play a critical role in large complex gas corporations. Many factors such as human, organisational and environmental factors affect IS in an organisation. Therefore, investigating ISs success is considered to be a complex problem. Also, because of the competitive business environment and the high amount of information flow in organisations, new issues like resilient ISs and successful customer relationship management (CRM) have emerged. A resilient IS will provide sustainable delivery of information to internal and external customers. This paper presents an integrated approach to enhance and optimise the performance of each component of a large IS based on CRM and resilience engineering (RE) in a gas company. The enhancement of the performance can help ISs to perform business tasks efficiently. The data are collected from standard questionnaires. It is then analysed by data envelopment analysis by selecting the optimal mathematical programming approach. The selected model is validated and verified by principle component analysis method. Finally, CRM and RE factors are identified as influential factors through sensitivity analysis for this particular case study. To the best of our knowledge, this is the first study for performance assessment and optimisation of large IS by combined RE and CRM.

Chemical profiling of guarana seeds (Paullinia cupana) from different geographical origins using UPLC-QTOF-MS combined with chemometrics.

PubMed

da Silva, Givaldo Souza; Canuto, Kirley Marques; Ribeiro, Paulo Riceli Vasconcelos; de Brito, Edy Sousa; Nascimento, Madson Moreira; Zocolo, Guilherme Julião; Coutinho, Janclei Pereira; de Jesus, Raildo Mota

2017-12-01

Paullinia cupana, commonly known as guarana, is an Amazonian fruit whose seeds are used to produce the powdered guarana, which is rich in caffeine and consumed for its stimulating activity. The metabolic profile of guarana from the two largest producing regions was investigated using UPLC-MS combined with multivariate statistical analysis. The principal component analysis (PCA) showed significant differences between samples produced in the states of Bahia and Amazonas. The metabolites responsible for the differentiation were identified by orthogonal partial least squares discriminant analysis (OPLS-DA). Fourteen phenolic compounds were characterized in guarana powder samples, and catechin, epicatechin, B-type procyanidin dimer, A-type procyanidin trimer and A-type procyanidin dimer were the main compounds responsible for the geographical variation of the samples. Copyright © 2017. Published by Elsevier Ltd.

Characterization of ancient glass excavated in Enez (Ancient Ainos) Turkey by combined Instrumental Neutron Activation Analysis and Fourier Transform Infrared spectrometry techniques

NASA Astrophysics Data System (ADS)

Akyuz, Sevim; Akyuz, Tanil; Mukhamedshina, Nuranya M.; Mirsagatova, A. Adiba; Basaran, Sait; Cakan, Banu

2012-05-01

Ancient glass fragments excavated in the archaeological district Enez (Ancient Ainos)-Turkey were investigated by combined Instrumental Neutron Activation Analysis (INAA) and Fourier Transform Infrared (FTIR) spectrometry techniques. Multi-elemental contents of 15 glass fragments that belong to Hellenistic, Roman, Byzantine, and Ottoman Periods, were determined by INAA. The concentrations of twenty six elements (Na, K, Ca, Sc, Cr, Mn, Fe, Co, Cu, Zn, As, Rb, Sr, Sb, Cs, Ba, Ce, Sm, Eu, Tb, Yb, Lu, Hf, Ta, Au and Th), which might be present in the samples as flux, stabilizers, colorants or opacifiers, and impurities, were examined. Chemometric treatment of the INAA data was performed and principle component analysis revealed presence of 3 distinct groups. The thermal history of the glass samples was determined by FTIR spectrometry.

The data embedding method

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

Sandford, M.T. II; Bradley, J.N.; Handel, T.G.

Data embedding is a new steganographic method for combining digital information sets. This paper describes the data embedding method and gives examples of its application using software written in the C-programming language. Sandford and Handel produced a computer program (BMPEMBED, Ver. 1.51 written for IBM PC/AT or compatible, MS/DOS Ver. 3.3 or later) that implements data embedding in an application for digital imagery. Information is embedded into, and extracted from, Truecolor or color-pallet images in Microsoft{reg_sign} bitmap (.BMP) format. Hiding data in the noise component of a host, by means of an algorithm that modifies or replaces the noise bits,more » is termed {open_quote}steganography.{close_quote} Data embedding differs markedly from conventional steganography, because it uses the noise component of the host to insert information with few or no modifications to the host data values or their statistical properties. Consequently, the entropy of the host data is affected little by using data embedding to add information. The data embedding method applies to host data compressed with transform, or {open_quote}lossy{close_quote} compression algorithms, as for example ones based on discrete cosine transform and wavelet functions. Analysis of the host noise generates a key required for embedding and extracting the auxiliary data from the combined data. The key is stored easily in the combined data. Images without the key cannot be processed to extract the embedded information. To provide security for the embedded data, one can remove the key from the combined data and manage it separately. The image key can be encrypted and stored in the combined data or transmitted separately as a ciphertext much smaller in size than the embedded data. The key size is typically ten to one-hundred bytes, and it is in data an analysis algorithm.« less

Data embedding method

NASA Astrophysics Data System (ADS)

Sandford, Maxwell T., II; Bradley, Jonathan N.; Handel, Theodore G.

1996-01-01

Data embedding is a new steganographic method for combining digital information sets. This paper describes the data embedding method and gives examples of its application using software written in the C-programming language. Sandford and Handel produced a computer program (BMPEMBED, Ver. 1.51 written for IBM PC/AT or compatible, MS/DOS Ver. 3.3 or later) that implements data embedding in an application for digital imagery. Information is embedded into, and extracted from, Truecolor or color-pallet images in MicrosoftTM bitmap (BMP) format. Hiding data in the noise component of a host, by means of an algorithm that modifies or replaces the noise bits, is termed `steganography.' Data embedding differs markedly from conventional steganography, because it uses the noise component of the host to insert information with few or no modifications to the host data values or their statistical properties. Consequently, the entropy of the host data is affected little by using data embedding to add information. The data embedding method applies to host data compressed with transform, or `lossy' compression algorithms, as for example ones based on discrete cosine transform and wavelet functions. Analysis of the host noise generates a key required for embedding and extracting the auxiliary data from the combined data. The key is stored easily in the combined data. Images without the key cannot be processed to extract the embedded information. To provide security for the embedded data, one can remove the key from the combined data and manage it separately. The image key can be encrypted and stored in the combined data or transmitted separately as a ciphertext much smaller in size than the embedded data. The key size is typically ten to one-hundred bytes, and it is derived from the original host data by an analysis algorithm.

Multiscale combination of climate model simulations and proxy records over the last millennium

NASA Astrophysics Data System (ADS)

Chen, Xin; Xing, Pei; Luo, Yong; Nie, Suping; Zhao, Zongci; Huang, Jianbin; Tian, Qinhua

2018-05-01

To highlight the compatibility of climate model simulation and proxy reconstruction at different timescales, a timescale separation merging method combining proxy records and climate model simulations is presented. Annual mean surface temperature anomalies for the last millennium (851-2005 AD) at various scales over the land of the Northern Hemisphere were reconstructed with 2° × 2° spatial resolution, using an optimal interpolation (OI) algorithm. All target series were decomposed using an ensemble empirical mode decomposition method followed by power spectral analysis. Four typical components were obtained at inter-annual, decadal, multidecadal, and centennial timescales. A total of 323 temperature-sensitive proxy chronologies were incorporated after screening for each component. By scaling the proxy components using variance matching and applying a localized OI algorithm to all four components point by point, we obtained merged surface temperatures. Independent validation indicates that the most significant improvement was for components at the inter-annual scale, but this became less evident with increasing timescales. In mid-latitude land areas, 10-30% of grids were significantly corrected at the inter-annual scale. By assimilating the proxy records, the merged results reduced the gap in response to volcanic forcing between a pure reconstruction and simulation. Difficulty remained in verifying the centennial information and quantifying corresponding uncertainties, so additional effort should be devoted to this aspect in future research.

Ultra-fast HPM detectors improve NAD(P)H FLIM

NASA Astrophysics Data System (ADS)

Becker, Wolfgang; Wetzker, Cornelia; Benda, Aleš

2018-02-01

Metabolic imaging by NAD(P)H FLIM requires the decay functions in the individual pixels to be resolved into the decay components of bound and unbound NAD(P)H. Metabolic information is contained in the lifetime and relative amplitudes of the components. The separation of the decay components and the accuracy of the amplitudes and lifetimes improves substantially by using ultra-fast HPM-100-06 and HPM-100-07 hybrid detectors. The IRF width in combination with the Becker & Hickl SPC-150N and SPC-150NX TCSPC modules is less than 20 ps. An IRF this fast does not interfere with the fluorescence decay. The usual deconvolution process in the data analysis then virtually becomes a simple curve fitting, and the parameters of the NAD(P)H decay components are obtained at unprecedented accuracy.

Ambient Field Analysis at Groningen Gas Field

NASA Astrophysics Data System (ADS)

Spica, Z.; Nakata, N.; Beroza, G. C.

2016-12-01

We analyze continuous ambient-field data at Groningen gas field (Netherlands) through cross-correlation processing. The Groningen array is composed of 75 shallow boreholes with 6 km spacing, which contain a 3C surface accelerometer and four 5-Hz 3C borehole geophones spaced at 50 m depth intervals. We successfully retrieve coherent waves from ambient seismic field on the 9 components between stations. Results show high SNR signal in the frequency range of 0.125-1 Hz, and the ZZ, ZR, RZ, RR and TT components show much stronger wave energy than other components as expected. This poster discuss the different type of waves retrieved, the utility of the combination of borehole and surface observations, future development as well as the importance to compute the 9 components of the Green's tensor to better understand the wave field propriety with ambient noise.

Embedding of multidimensional time-dependent observations.

PubMed

Barnard, J P; Aldrich, C; Gerber, M

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Embedding of multidimensional time-dependent observations

NASA Astrophysics Data System (ADS)

Barnard, Jakobus P.; Aldrich, Chris; Gerber, Marius

2001-10-01

A method is proposed to reconstruct dynamic attractors by embedding of multivariate observations of dynamic nonlinear processes. The Takens embedding theory is combined with independent component analysis to transform the embedding into a vector space of linearly independent vectors (phase variables). The method is successfully tested against prediction of the unembedded state vector in two case studies of simulated chaotic processes.

Genetic analysis of some agronomic and fiber traits in Gossypium hirsutum L. grown in field conditions

USDA-ARS?s Scientific Manuscript database

Cotton production is an essential component of the economy of Pakistan, and continuing to improve the yield and fiber quality of this crop will ensure the future stability of this industry. Combining ability describes the performance of genotypes when they are crossed together, and it is a common me...

Do elevated temperature and CO2 generally have counteracting effects on phenolic phytochemistry of boreal trees?

Treesearch

T.O. Veteli; W.J. Mattson; P. Niemela; R. Julkunen-Tiitto; S. Kellomaki; K. Kuokkanen; A. Lavola

2007-01-01

Global climate change includes concomitant changes in many components of the abiotic flux necessary for plant life. In this paper, we investigate the combined effects of elevated CO2 (720 ppm) and temperature (+2 K) on the phytochemistry of three deciduous tree species. The analysis revealed that elevated CO2 generally...

Investigation of cell wall composition related to stem lodging resistance in wheat (Triticum aestivum L.) by FTIR spectroscopy.

PubMed

Wang, Jian; Zhu, Jinmao; Huang, RuZhu; Yang, YuSheng

2012-07-01

We explored the rapid qualitative analysis of wheat cultivars with good lodging resistances by Fourier transform infrared resonance (FTIR) spectroscopy and multivariate statistical analysis. FTIR imaging showing that wheat stem cell walls were mainly composed of cellulose, pectin, protein, and lignin. Principal components analysis (PCA) was used to eliminate multicollinearity among multiple peak absorptions. PCA revealed the developmental internodes of wheat stems could be distributed from low to high along the load of the second principal component, which was consistent with the corresponding bands of cellulose in the FTIR spectra of the cell walls. Furthermore, four distinct stem populations could also be identified by spectral features related to their corresponding mechanical properties via PCA and cluster analysis. Histochemical staining of four types of wheat stems with various abilities to resist lodging revealed that cellulose contributed more than lignin to the ability to resist lodging. These results strongly suggested that the main cell wall component responsible for these differences was cellulose. Therefore, the combination of multivariate analysis and FTIR could rapidly screen wheat cultivars with good lodging resistance. Furthermore, the application of these methods to a much wider range of cultivars of unknown mechanical properties promises to be of interest.

Immune interaction between components of acellular pertussis-diphtheria-tetanus (DTaP) vaccine and Haemophilus influenzae b (Hib) conjugate vaccine in a rat model.

PubMed

Mawas, Fatme; Dickinson, Robert; Douglas-Bardsley, Alexandra; Xing, Dorothy K L; Sesardic, Dorothea; Corbel, Michael J

2006-04-24

We have previously shown that, consistent with clinical trial results, the immune response to a Haemophilus influenzae b (Hib) conjugate vaccine in a rat model was compromised and modulated when given combined with a DTaP3 vaccine, as compared to both vaccines given separately. The present study extended our investigation to evaluate the immunogenicity of all DTaP3 components in combined versus separate administration of Hib with DTaP3 and investigated immune interactions between Hib and individual components of DTaP3. Rats were immunised with Hib and DTaP3 or with Hib and individual DTaP3 components. Cellular and humoral immune responses to Hib and DTaP3 components were evaluated. Our results indicate that the immunogenicity of DTaP3 components was similar or greater in combined versus separate administration of Hib and DTaP3. Moreover, combined administration of Hib and TT reduced immunogenicity of both Hib and TT. Hib immunogenicity was also significantly reduced when given combined with FHA and following adsorption to Al(OH)3.

Identification of molecular markers associated with mite resistance in coconut (Cocos nucifera L.).

PubMed

Shalini, K V; Manjunatha, S; Lebrun, P; Berger, A; Baudouin, L; Pirany, N; Ranganath, R M; Prasad, D Theertha

2007-01-01

Coconut mite (Aceria guerreronis 'Keifer') has become a major threat to Indian coconut (Coçcos nucifera L.) cultivators and the processing industry. Chemical and biological control measures have proved to be costly, ineffective, and ecologically undesirable. Planting mite-resistant coconut cultivars is the most effective method of preventing yield loss and should form a major component of any integrated pest management stratagem. Coconut genotypes, and mite-resistant and -susceptible accessions were collected from different parts of South India. Thirty-two simple sequence repeat (SSR) and 7 RAPD primers were used for molecular analyses. In single-marker analysis, 9 SSR and 4 RAPD markers associated with mite resistance were identified. In stepwise multiple regression analysis of SSRs, a combination of 6 markers showed 100% association with mite infestation. Stepwise multiple regression analysis for RAPD data revealed that a combination of 3 markers accounted for 83.86% of mite resistance in the selected materials. Combined stepwise multiple regression analysis of RAPD and SSR data showed that a combination of 5 markers explained 100% of the association with mite resistance in coconut. Markers associated with mite resistance are important in coconut breeding programs and will facilitate the selection of mite-resistant plants at an early stage as well as mother plants for breeding programs.

Multivariate statistical analysis of stream-sediment geochemistry in the Grazer Paläozoikum, Austria

USGS Publications Warehouse

Weber, L.; Davis, J.C.

1990-01-01

The Austrian reconnaissance study of stream-sediment composition — more than 30000 clay-fraction samples collected over an area of 40000 km2 — is summarized in an atlas of regional maps that show the distributions of 35 elements. These maps, rich in information, reveal complicated patterns of element abundance that are difficult to compare on more than a small number of maps at one time. In such a study, multivariate procedures such as simultaneous R-Q mode components analysis may be helpful. They can compress a large number of variables into a much smaller number of independent linear combinations. These composite variables may be mapped and relationships sought between them and geological properties. As an example, R-Q mode components analysis is applied here to the Grazer Paläozoikum, a tectonic unit northeast of the city of Graz, which is composed of diverse lithologies and contains many mineral deposits.

Progress Towards Improved Analysis of TES X-ray Data Using Principal Component Analysis

NASA Technical Reports Server (NTRS)

Busch, S. E.; Adams, J. S.; Bandler, S. R.; Chervenak, J. A.; Eckart, M. E.; Finkbeiner, F. M.; Fixsen, D. J.; Kelley, R. L.; Kilbourne, C. A.; Lee, S.-J.;

Mental health stigmatisation in deployed UK Armed Forces: a principal components analysis.

PubMed

Fertout, Mohammed; Jones, N; Keeling, M; Greenberg, N

2015-12-01

UK military research suggests that there is a significant link between current psychological symptoms, mental health stigmatisation and perceived barriers to care (stigma/BTC). Few studies have explored the construct of stigma/BTC in depth amongst deployed UK military personnel. Three survey datasets containing a stigma/BTC scale obtained during UK deployments to Iraq and Afghanistan were combined (n=3405 personnel). Principal component analysis was used to identify the key components of stigma/BTC. The relationship between psychological symptoms, the stigma/BTC components and help seeking were examined. Two components were identified: 'potential loss of personal military credibility and trust' (stigma Component 1, five items, 49.4% total model variance) and 'negative perceptions of mental health services and barriers to help seeking' (Component 2, six items, 11.2% total model variance). Component 1 was endorsed by 37.8% and Component 2 by 9.4% of personnel. Component 1 was associated with both assessed and subjective mental health, medical appointments and admission to hospital. Stigma Component 2 was associated with subjective and assessed mental health but not with medical appointments. Neither component was associated with help-seeking for subjective psycho-social problems. Potential loss of credibility and trust appeared to be associated with help-seeking for medical reasons but not for help-seeking for subjective psychosocial problems. Those experiencing psychological symptoms appeared to minimise the effects of stigma by seeking out a socially acceptable route into care, such as the medical consultation, whereas those who experienced a subjective mental health problem appeared willing to seek help from any source. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Determination of adhesion between thermoplastic and liquid silicone rubbers in hard-soft-combinations via mechanical peeling test

NASA Astrophysics Data System (ADS)

Kühr, C.; Spörrer, A.; Altstädt, V.

2014-05-01

The production of hard-soft-combinations via multi injection molding gained more and more importance in the last years. This is attributed to different factors. One principle reason is that the use of two-component injection molding technique has many advantages such as cancelling subsequent and complex steps and shortening the process chain. Furthermore this technique allows the combination of the properties of the single components like the high stiffness of the hard component and the elastic properties of the soft component. Because of the incompatibility of some polymers the adhesion on the interface has to be determined. Thereby adhesion is not only influenced by the applied polymers, but also by the injection molding parameters and the characteristics of the mold. Besides already known combinations of thermoplastics with thermoplastic elastomers (TPE), there consists the possibility to apply liquid silicone rubber (LSR) as soft component. A thermoplastic/LSR combination gains in importance due to the specific advantages of LSR to TPE. The faintly adhesion between LSR and thermoplastics is currently one of the key challenges when dealing with those combinations. So it is coercively necessary to improve adhesion between the two components by adding an adhesion promoter. To determine the promoters influence, it is necessary to develop a suitable testing method to investigate e.g. the peel resistance. The current German standard "VDI Richtlinie 2019', which is actually only employed for thermoplastic/TPE combinations, can serve as a model to determine the adhesion of thermoplastic/LSR combinations.

Analysis of Performance of Jet Engine from Characteristics of Components I : Aerodynamic and Matching Characteristics of Turbine Component Determined with Cold Air

NASA Technical Reports Server (NTRS)

Goldstein, Arthur W

1947-01-01

The performance of the turbine component of an NACA research jet engine was investigated with cold air. The interaction and the matching of the turbine with the NACA eight-stage compressor were computed with the combination considered as a jet engine. The over-all performance of the engine was then determined. The internal aerodynamics were studied to the extent of investigating the performance of the first stator ring and its influence on the turbine performance. For this ring, the stream-filament method for computing velocity distribution permitted efficient sections to be designed, but the design condition of free-vortex flow with uniform axial velocities was not obtained.

Sandia Corporation (Albuquerque, NM)

DOEpatents

Ewsuk, Kevin G [Albuquerque, NM; Arguello, Jr., Jose G.

2006-01-31

A method of designing a primary geometry, such as for a forming die, to be used in a powder pressing application by using a combination of axisymmetric geometric shapes, transition radii, and transition spaces to simulate the geometry where the shapes can be selected from a predetermined list or menu of axisymmetric shapes and then developing a finite element mesh to represent the geometry. This mesh, along with material properties of the component to be designed and powder, is input to a standard deformation finite element code to evaluate the deformation characteristics of the component being designed. The user can develop the geometry interactively with a computer interface in minutes and execute a complete analysis of the deformation characteristics of the simulated component geometry.

Power-Combined GaN Amplifier with 2.28-W Output Power at 87 GHz

NASA Technical Reports Server (NTRS)

Fung, King Man; Ward, John; Chattopadhyay, Goutam; Lin, Robert H.; Samoska, Lorene A.; Kangaslahti, Pekka P.; Mehdi, Imran; Lambrigtsen, Bjorn H.; Goldsmith, Paul F.; Soria, Mary M.;

Perceptual reversals during binocular rivalry: ERP components and their concomitant source differences.

PubMed

Britz, Juliane; Pitts, Michael A

2011-11-01

We used an intermittent stimulus presentation to investigate event-related potential (ERP) components associated with perceptual reversals during binocular rivalry. The combination of spatiotemporal ERP analysis with source imaging and statistical parametric mapping of the concomitant source differences yielded differences in three time windows: reversals showed increased activity in early visual (∼120 ms) and in inferior frontal and anterior temporal areas (∼400-600 ms) and decreased activity in the ventral stream (∼250-350 ms). The combination of source imaging and statistical parametric mapping suggests that these differences were due to differences in generator strength and not generator configuration, unlike the initiation of reversals in right inferior parietal areas. These results are discussed within the context of the extensive network of brain areas that has been implicated in the initiation, implementation, and appraisal of bistable perceptual reversals. Copyright © 2011 Society for Psychophysiological Research.

An external-cavity quantum cascade laser operating near 5.2 µm combined with cavity ring-down spectroscopy for multi-component chemical sensing

NASA Astrophysics Data System (ADS)

Dutta Banik, Gourab; Maity, Abhijit; Som, Suman; Pal, Mithun; Pradhan, Manik

2018-04-01

We report on the performance of a widely tunable continuous wave mode-hop-free external-cavity quantum cascade laser operating at λ ~ 5.2 µm combined with cavity ring-down spectroscopy (CRDS) technique for high-resolution molecular spectroscopy. The CRDS system has been utilized for simultaneous and molecule-specific detection of several environmentally and bio-medically important trace molecular species such as nitric oxide, nitrous oxide, carbonyl sulphide and acetylene (C2H2) at ultra-low concentrations by probing numerous rotationally resolved ro-vibrational transitions in the mid-IR spectral region within a relatively small spectral range of ~0.035 cm-1. This continuous wave external-cavity quantum cascade laser-based multi-component CRDS sensor with high sensitivity and molecular specificity promises applications in environmental sensing as well as non-invasive medical diagnosis through human breath analysis.

Unified constitutive material models for nonlinear finite-element structural analysis. [gas turbine engine blades and vanes

NASA Technical Reports Server (NTRS)

Kaufman, A.; Laflen, J. H.; Lindholm, U. S.

1985-01-01

Unified constitutive material models were developed for structural analyses of aircraft gas turbine engine components with particular application to isotropic materials used for high-pressure stage turbine blades and vanes. Forms or combinations of models independently proposed by Bodner and Walker were considered. These theories combine time-dependent and time-independent aspects of inelasticity into a continuous spectrum of behavior. This is in sharp contrast to previous classical approaches that partition inelastic strain into uncoupled plastic and creep components. Predicted stress-strain responses from these models were evaluated against monotonic and cyclic test results for uniaxial specimens of two cast nickel-base alloys, B1900+Hf and Rene' 80. Previously obtained tension-torsion test results for Hastelloy X alloy were used to evaluate multiaxial stress-strain cycle predictions. The unified models, as well as appropriate algorithms for integrating the constitutive equations, were implemented in finite-element computer codes.

Histological heterogeneity in primary and metastatic classic combined hepatocellular-cholangiocarcinoma: a case series.

PubMed

De Vito, Claudio; Sarker, Debashis; Ross, Paul; Heaton, Nigel; Quaglia, Alberto

2017-11-01

Combined hepatocellular-cholangiocarcinoma (cHCC-CC) is a rare and aggressive primary liver cancer with both hepatocellular and cholangiocellular differentiation. Due to its bi-phenotypic component, cHCC-CC is a heterogeneous tumour and histopathological analysis of metastatic deposits is poorly characterized. In this retrospective study, we describe four patients in whom the histology from resected specimens of both primary and recurrent and/or metastatic tumour was available for comparison and immunohistochemical characterization. Our study shows that recurrent or metastatic deposits replicate the heterogeneity of the primary cHCC-CC, that even originally small foci of divergent differentiation can become predominant later on and that hepatocellular and cholangiocellular components can show different tropism in distant organs. In our experience, the behaviour of recurrent/metastatic cHCC-CC is unpredictable and histological examination is necessary to guide treatment options at present.

Termitarium-Inhabiting Bacillus spp. Enhanced Plant Growth and Bioactive Component in Turmeric (Curcuma longa L.).

PubMed

Chauhan, Ankit Kumar; Maheshwari, Dinesh Kumar; Dheeman, Shrivardhan; Bajpai, Vivek K

2017-02-01

Curcumin (diferuloyl methane) is the main bioactive component of turmeric (Curcuma longa L.) having remarkable multipotent medicinal and therapeutic applications. Two Bacilli isolated from termitarium soil and identified as Bacillus endophyticus TSH42 and Bacillus cereus TSH77 were used for bacterization of rhizome for raising C. longa ver. suguna for growth and enhancement. Both the strains showed remarkable PGP activities and also chemotactic in nature with high chemotactic index. Turmeric plants bacterized with strains B. endophyticus TSH42 and B. cereus TSH77 individually and in combination increased plant growth and turmeric production up to 18% in field trial in comparison to non-bacterized plants. High-performance liquid chromatography analysis was performed to determine the content of curcumin, which showed concentration of curcumin in un-inoculated turmeric as 3.66 g which increased by 13.6% (4.16 g) when combination of TSH42 and TSH77 was used.

Deviation from additivity in mixture toxicity: relevance of nonlinear dose-response relationships and cell line differences in genotoxicity assays with combinations of chemical mutagens and gamma-radiation.

PubMed

Lutz, Werner K; Vamvakas, Spyros; Kopp-Schneider, Annette; Schlatter, Josef; Stopper, Helga

2002-12-01

Sublinear dose-response relationships are often seen in toxicity testing, particularly with bioassays for carcinogenicity. This is the result of a superimposition of various effects that modulate and contribute to the process of cancer formation. Examples are saturation of detoxification pathways or DNA repair with increasing dose, or regenerative hyperplasia and indirect DNA damage as a consequence of high-dose cytotoxicity and cell death. The response to a combination treatment can appear to be supra-additive, although it is in fact dose-additive along a sublinear dose-response curve for the single agents. Because environmental exposure of humans is usually in a low-dose range and deviation from linearity is less likely at the low-dose end, combination effects should be tested at the lowest observable effect levels (LOEL) of the components. This principle has been applied to combinations of genotoxic agents in various cellular models. For statistical analysis, all experiments were analyzed for deviation from additivity with an n-factor analysis of variance with an interaction term, n being the number of components tested in combination. Benzo[a]pyrene, benz[a]anthracene, and dibenz[a,c]anthracene were tested at the LOEL, separately and in combination, for the induction of revertants in the Ames test, using Salmonella typhimurium TA100 and rat liver S9 fraction. Combined treatment produced no deviation from additivity. The induction of micronuclei in vitro was investigated with ionizing radiation from a 137Cs source and ethyl methanesulfonate. Mouse lymphoma L5178Y cells revealed a significant 40% supra-additive combination effect in an experiment based on three independent replicates for controls and single and combination treatments. On the other hand, two human lymphoblastoid cell lines (TK6 and WTK1) as well as a pilot study with human primary fibroblasts from fetal lung did not show deviation from additivity. Data derived from one cell line should therefore not be generalized. Regarding the testing of mixtures for deviation from additive toxicity, the suggested experimental protocol is easily followed by toxicologists.

iReport: a generalised Galaxy solution for integrated experimental reporting.

PubMed

Hiltemann, Saskia; Hoogstrate, Youri; der Spek, Peter van; Jenster, Guido; Stubbs, Andrew

2014-01-01

Galaxy offers a number of visualisation options with components, such as Trackster, Circster and Galaxy Charts, but currently lacks the ability to easily combine outputs from different tools into a single view or report. A number of tools produce HTML reports as output in order to combine the various output files from a single tool; however, this requires programming and knowledge of HTML, and the reports must be custom-made for each new tool. We have developed a generic and flexible reporting tool for Galaxy, iReport, that allows users to create interactive HTML reports directly from the Galaxy UI, with the ability to combine an arbitrary number of outputs from any number of different tools. Content can be organised into different tabs, and interactivity can be added to components. To demonstrate the capability of iReport we provide two publically available examples, the first is an iReport explaining about iReports, created for, and using content from the recent Galaxy Community Conference 2014. The second is a genetic report based on a trio analysis to determine candidate pathogenic variants which uses our previously developed Galaxy toolset for whole-genome NGS analysis, CGtag. These reports may be adapted for outputs from any sequencing platform and any results, such as omics data, non-high throughput results and clinical variables. iReport provides a secure, collaborative, and flexible web-based reporting system that is compatible with Galaxy (and non-Galaxy) generated content. We demonstrate its value with a real-life example of reporting genetic trio-analysis.

A New Measurement of the Cosmic-Ray Proton and Helium Spectra

NASA Astrophysics Data System (ADS)

Mocchiutti, E.; Ambriola, M.; Bartalucci, S.; Bellotti, R.; Bergström, D.; Boezio, M.; Bonicini, V.; Bravar, U.; Cafagna, F.; Carlson, P.; Casolino, M.; Ciacio, F.; Circella, M.; De Marzo, C. N.; De Pascale, M. P.; Finetti, N.; Francke, T.; Hansen, P.; Hof, M.; Kremer, J.; Menn, W.; Mitchell, J. W.; Mocchiutti, E.; Morselli, A.; Ormes, J. F.; Papini, P.; Piccardi, S.; Picozza, P.; Ricci, M.; Schiavon, P.; Simon, M.; Sparvoli, R.; Spillantini, P.; Stephens, S. A.; Stochaj, S. J.; Streitmatter, R. E.; Suffert, M.; Vacchi, A.; Vannuccini, E.; Zampa, N.; WIZARD/CAPRICE Collaboration

2001-08-01

A new measurement of the primary cosmic ray spectra was performed during the balloon-borne CAPRICE experiment in 1998. This apparatus consists of a magnet spectrometer, with a superconducting magnet and a driftchamber tracking device, a time of flight scintillator system, a silicon-tungsten imaging calorimeter and a gas ring imaging Cherenkov detector. This combination of state-of-the-art detectors provides excellent particle discrimination capabilities, such that detailed investigations of the antiproton, electron/positron, muon and primary components of cosmic rays have been performed. The analysis of the primary proton component is illustrated in this paper.

Wheat signature modeling and analysis for improved training statistics: Supplement. Simulated LANDSAT wheat radiances and radiance components

NASA Technical Reports Server (NTRS)

Malila, W. A.; Cicone, R. C.; Gleason, J. M.

1976-01-01

Simulated scanner system data values generated in support of LACIE (Large Area Crop Inventory Experiment) research and development efforts are presented. Synthetic inband (LANDSAT) wheat radiances and radiance components were computed and are presented for various wheat canopy and atmospheric conditions and scanner view geometries. Values include: (1) inband bidirectional reflectances for seven stages of wheat crop growth; (2) inband atmospheric features; and (3) inband radiances corresponding to the various combinations of wheat canopy and atmospheric conditions. Analyses of these data values are presented in the main report.

Noninvasive detection of nasopharyngeal carcinoma based on saliva proteins using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Lin, Xueliang; Lin, Duo; Ge, Xiaosong; Qiu, Sufang; Feng, Shangyuan; Chen, Rong

2017-10-01

The present study evaluated the capability of saliva analysis combining membrane protein purification with surface-enhanced Raman spectroscopy (SERS) for noninvasive detection of nasopharyngeal carcinoma (NPC). A rapid and convenient protein purification method based on cellulose acetate membrane was developed. A total of 659 high-quality SERS spectra were acquired from purified proteins extracted from the saliva samples of 170 patients with pathologically confirmed NPC and 71 healthy volunteers. Spectral analysis of those saliva protein SERS spectra revealed specific changes in some biochemical compositions, which were possibly associated with NPC transformation. Furthermore, principal component analysis combined with linear discriminant analysis (PCA-LDA) was utilized to analyze and classify the saliva protein SERS spectra from NPC and healthy subjects. Diagnostic sensitivity of 70.7%, specificity of 70.3%, and diagnostic accuracy of 70.5% could be achieved by PCA-LDA for NPC identification. These results show that this assay based on saliva protein SERS analysis holds promising potential for developing a rapid, noninvasive, and convenient clinical tool for NPC screening.

Short-term PV/T module temperature prediction based on PCA-RBF neural network

NASA Astrophysics Data System (ADS)

Li, Jiyong; Zhao, Zhendong; Li, Yisheng; Xiao, Jing; Tang, Yunfeng

2018-02-01

Aiming at the non-linearity and large inertia of temperature control in PV/T system, short-term temperature prediction of PV/T module is proposed, to make the PV/T system controller run forward according to the short-term forecasting situation to optimize control effect. Based on the analysis of the correlation between PV/T module temperature and meteorological factors, and the temperature of adjacent time series, the principal component analysis (PCA) method is used to pre-process the original input sample data. Combined with the RBF neural network theory, the simulation results show that the PCA method makes the prediction accuracy of the network model higher and the generalization performance stronger than that of the RBF neural network without the main component extraction.

A variational conformational dynamics approach to the selection of collective variables in metadynamics.

PubMed

McCarty, James; Parrinello, Michele

2017-11-28

In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.

A variational conformational dynamics approach to the selection of collective variables in metadynamics

NASA Astrophysics Data System (ADS)

McCarty, James; Parrinello, Michele

2017-11-01

In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.

PHOTOMETRIC, SPECTROSCOPIC, AND ORBITAL PERIOD STUDY OF THREE EARLY-TYPE SEMI-DETACHED SYSTEMS: XZ AQL, UX HER, AND AT PEG

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

Zola, S.; Baştürk, Ö.; Şenavcı, H. V.

2016-08-01

In this paper, we present a combined photometric, spectroscopic, and orbital period study of three early-type eclipsing binary systems: XZ Aql, UX Her, and AT Peg. As a result, we have derived the absolute parameters of their components and, on that basis, we discuss their evolutionary states. Furthermore, we compare their parameters with those of other binary systems and with theoretical models. An analysis of all available up-to-date times of minima indicated that all three systems studied here show cyclic orbital changes; their origin is discussed in detail. Finally, we performed a frequency analysis for possible pulsational behavior, and asmore » a result we suggest that XZ Aql hosts a δ Scuti component.« less

Inspection of baked carbon anodes using a combination of multi-spectral acousto-ultrasonic techniques and principal component analysis.

PubMed

Boubaker, Moez Ben; Picard, Donald; Duchesne, Carl; Tessier, Jayson; Alamdari, Houshang; Fafard, Mario

2018-05-17

This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes. The approach allows locating cracks in the blocks and the AU features were found sensitive to crack severity. The results are validated using images collected after cutting some anodes. Copyright © 2018 Elsevier B.V. All rights reserved.

Size-exclusion chromatography system for macromolecular interaction analysis

DOEpatents

Stevens, Fred J.

1988-01-01

A low pressure, microcomputer controlled system employing high performance liquid chromatography (HPLC) allows for precise analysis of the interaction of two reversibly associating macromolecules such as proteins. Since a macromolecular complex migrates faster than its components during size-exclusion chromatography, the difference between the elution profile of a mixture of two macromolecules and the summation of the elution profiles of the two components provides a quantifiable indication of the degree of molecular interaction. This delta profile is used to qualitatively reveal the presence or absence of significant interaction or to rank the relative degree of interaction in comparing samples and, in combination with a computer simulation, is further used to quantify the magnitude of the interaction in an arrangement wherein a microcomputer is coupled to analytical instrumentation in a novel manner.

Preseason Functional Movement Screen Component Tests Predict Severe Contact Injuries in Professional Rugby Union Players.

PubMed

Tee, Jason C; Klingbiel, Jannie F G; Collins, Robert; Lambert, Mike I; Coopoo, Yoga

2016-11-01

Tee, JC, Klingbiel, JFG, Collins, R, Lambert, MI, and Coopoo, Y. Preseason Functional Movement Screen component tests predict severe contact injuries in professional rugby union players. J Strength Cond Res 30(11): 3194-3203, 2016-Rugby union is a collision sport with a relatively high risk of injury. The ability of the Functional Movement Screen (FMS) or its component tests to predict the occurrence of severe (≥28 days) injuries in professional players was assessed. Ninety FMS test observations from 62 players across 4 different time periods were compared with severe injuries sustained during 6 months after FMS testing. Mean composite FMS scores were significantly lower in players who sustained severe injury (injured 13.2 ± 1.5 vs. noninjured 14.5 ± 1.4, Effect Size = 0.83, large) because of differences in in-line lunge (ILL) and active straight leg raise scores (ASLR). Receiver-operated characteristic curves and 2 × 2 contingency tables were used to determine that ASLR (cut-off 2/3) was the injury predictor with the greatest sensitivity (0.96, 95% confidence interval [CI] = 0.79-1.0). Adding the ILL in combination with ASLR (ILL + ASLR) improved the specificity of the injury prediction model (ASLR specificity = 0.29, 95% CI = 0.18-0.43 vs. ASLR + ILL specificity = 0.53, 95% CI = 0.39-0.66, p ≤ 0.05). Further analysis was performed to determine whether FMS tests could predict contact and noncontact injuries. The FMS composite score and various combinations of component tests (deep squat [DS] + ILL, ILL + ASLR, and DS + ILL + ASLR) were all significant predictors of contact injury. The FMS composite score also predicted noncontact injury, but no component test or combination thereof produced a similar result. These findings indicate that low scores on various FMS component tests are risk factors for injury in professional rugby players.

HPLC-PDA Combined with Chemometrics for Quantitation of Active Components and Quality Assessment of Raw and Processed Fruits of Xanthium strumarium L.

PubMed

Jiang, Hai; Yang, Liu; Xing, Xudong; Yan, Meiling; Guo, Xinyue; Yang, Bingyou; Wang, Qiuhong; Kuang, Haixue

2018-01-25

As a valuable herbal medicine, the fruits of Xanthium strumarium L. (Xanthii Fructus) have been widely used in raw and processed forms to achieve different therapeutic effects in practice. In this study, a comprehensive strategy was proposed for evaluating the active components in 30 batches of raw and processed Xanthii Fructus (RXF and PXF) samples, based on high-performance liquid chromatography coupled with photodiode array detection (HPLC-PDA). Twelve common peaks were detected and eight compounds of caffeoylquinic acids were simultaneously quantified in RXF and PXF. All the analytes were detected with satisfactory linearity (R² > 0.9991) over wide concentration ranges. Simultaneously, the chemically latent information was revealed by hierarchical cluster analysis (HCA) and principal component analysis (PCA). The results suggest that there were significant differences between RXF and PXF from different regions in terms of the content of eight caffeoylquinic acids. Potential chemical markers for XF were found during processing by chemometrics.

Brewing and volatiles analysis of three tea beers indicate a potential interaction between tea components and lager yeast.

PubMed

Rong, Lei; Peng, Li-Juan; Ho, Chi-Tang; Yan, Shou-He; Meurens, Marc; Zhang, Zheng-Zhu; Li, Da-Xiang; Wan, Xiao-Chun; Bao, Guan-Hu; Gao, Xue-Ling; Ling, Tie-Jun

2016-04-15

Green tea, oolong tea and black tea were separately introduced to brew three kinds of tea beers. A model was designed to investigate the tea beer flavour character. Comparison of the volatiles between the sample of tea beer plus water mixture (TBW) and the sample of combination of tea infusion and normal beer (CTB) was accomplished by triangular sensory test and HS-SPME GC-MS analysis. The PCA of GC-MS data not only showed a significant difference between volatile features of each TBW and CTB group, but also suggested some key compounds to distinguish TBW from CTB. The results of GC-MS showed that the relative concentrations of many typical tea volatiles were significantly changed after the brewing process. More interestingly, the behaviour of yeast fermentation was influenced by tea components. A potential interaction between tea components and lager yeast could be suggested. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Preparation of panax notoginseng saponins-tanshinone H(A) composite method for pulmonary delivery with spray-drying method and its characterization].

PubMed

Wang, Hua-Mei; Fu, Ting-Ming; Guo, Li-Wei

2013-02-01

To prepare panax notoginseng saponins-tanshinone II(A) composite particles for pulmonary delivery, in order to explore a dry powder particle preparation method ensuring synchronized arrival of multiple components of traditional Chinese medicine compounds at absorption sites. Panax notoginseng saponins-tanshinone II(A) composite particles were prepared with spray-drying method, and characterized by scanning electron microscopy (SEM), confocal laser scanning microscope (CLSM), X-ray diffraction (XRD), infrared analysis (IR), dry laser particle size analysis, high performance liquid chromatography (HPLC) and the aerodynamic behavior was evaluated by a Next Generation Impactor (NGI). The dry powder particles produced had narrow particle size distribution range and good aerodynamic behavior, and could realize synchronized administration of multiple components. The spray-drying method is used to combine traditional Chinese medicine components with different physical and chemical properties in the same particle, and product into traditional Chinese medicine compound particles in line with the requirements for pulmonary delivery.

Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression

NASA Astrophysics Data System (ADS)

Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem

2010-09-01

In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

Evaluation of automated sample preparation, retention time locked gas chromatography-mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species.

PubMed

Gu, Qun; David, Frank; Lynen, Frédéric; Rumpel, Klaus; Dugardeyn, Jasper; Van Der Straeten, Dominique; Xu, Guowang; Sandra, Pat

2011-05-27

In this paper, automated sample preparation, retention time locked gas chromatography-mass spectrometry (GC-MS) and data analysis methods for the metabolomics study were evaluated. A miniaturized and automated derivatisation method using sequential oximation and silylation was applied to a polar extract of 4 types (2 types×2 ages) of Arabidopsis thaliana, a popular model organism often used in plant sciences and genetics. Automation of the derivatisation process offers excellent repeatability, and the time between sample preparation and analysis was short and constant, reducing artifact formation. Retention time locked (RTL) gas chromatography-mass spectrometry was used, resulting in reproducible retention times and GC-MS profiles. Two approaches were used for data analysis. XCMS followed by principal component analysis (approach 1) and AMDIS deconvolution combined with a commercially available program (Mass Profiler Professional) followed by principal component analysis (approach 2) were compared. Several features that were up- or down-regulated in the different types were detected. Copyright © 2011 Elsevier B.V. All rights reserved.

Determining the von Mises stress power spectral density for frequency domain fatigue analysis including out-of-phase stress components

NASA Astrophysics Data System (ADS)

Bonte, M. H. A.; de Boer, A.; Liebregts, R.

2007-04-01

This paper provides a new formula to take into account phase differences in the determination of an equivalent von Mises stress power spectral density (PSD) from multiple random inputs. The obtained von Mises PSD can subsequently be used for fatigue analysis. The formula was derived for use in the commercial vehicle business and was implemented in combination with Finite Element software to predict and analyse fatigue failure in the frequency domain.

Combined braking system for hybrid vehicle

NASA Astrophysics Data System (ADS)

Kulekina, A. V.; Bakholdin, P. A.; Shchurov, N. I.

2017-10-01

The paper presents an analysis of surface vehicle’s existing braking systems. The technical solution and brake-system design were developed for use of regenerative braking energy. A technical parameters comparison of energy storage devices of various types was made. Based on the comparative analysis, it was decided to use supercapacitor because of its applicability for an electric drive intermittent operation. The calculation methods of retarder key components were proposed. Therefrom, it was made a conclusion that rebuild gasoline-electric vehicles are more efficient than gasoline ones.

A Feature Fusion Based Forecasting Model for Financial Time Series

PubMed Central

Guo, Zhiqiang; Wang, Huaiqing; Liu, Quan; Yang, Jie

2014-01-01

Predicting the stock market has become an increasingly interesting research area for both researchers and investors, and many prediction models have been proposed. In these models, feature selection techniques are used to pre-process the raw data and remove noise. In this paper, a prediction model is constructed to forecast stock market behavior with the aid of independent component analysis, canonical correlation analysis, and a support vector machine. First, two types of features are extracted from the historical closing prices and 39 technical variables obtained by independent component analysis. Second, a canonical correlation analysis method is utilized to combine the two types of features and extract intrinsic features to improve the performance of the prediction model. Finally, a support vector machine is applied to forecast the next day's closing price. The proposed model is applied to the Shanghai stock market index and the Dow Jones index, and experimental results show that the proposed model performs better in the area of prediction than other two similar models. PMID:24971455

Characterization of Hatay honeys according to their multi-element analysis using ICP-OES combined with chemometrics.

PubMed

Yücel, Yasin; Sultanoğlu, Pınar

2013-09-01

Chemical characterisation has been carried out on 45 honey samples collected from Hatay region of Turkey. The concentrations of 17 elements were determined by inductively coupled plasma optical emission spectrometry (ICP-OES). Ca, K, Mg and Na were the most abundant elements, with mean contents of 219.38, 446.93, 49.06 and 95.91 mg kg(-1) respectively. The trace element mean contents ranged between 0.03 and 15.07 mg kg(-1). Chemometric methods such as principal component analysis (PCA) and cluster analysis (CA) techniques were applied to classify honey according to mineral content. The first most important principal component (PC) was strongly associated with the value of Al, B, Cd and Co. CA showed eight clusters corresponding to the eight botanical origins of honey. PCA explained 75.69% of the variance with the first six PC variables. Chemometric analysis of the analytical data allowed the accurate classification of the honey samples according to origin. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of the GREEN (Garden Resources, Education, and Environment Nexus) Tool: An Evidence-Based Model for School Garden Integration.

PubMed

Burt, Kate Gardner; Koch, Pamela; Contento, Isobel

2017-10-01

Researchers have established the benefits of school gardens on students' academic achievement, dietary outcomes, physical activity, and psychosocial skills, yet limited research has been conducted about how school gardens become institutionalized and sustained. Our aim was to develop a tool that captures how gardens are effectively established, integrated, and sustained in schools. We conducted a sequential, exploratory, mixed-methods study. Participants were identified with the help of Grow To Learn, the organization coordinating the New York City school garden initiative, and recruited via e-mail. A stratified, purposeful sample of 21 New York City elementary and middle schools participated in this study throughout the 2013/2014 school year. The sample was stratified in their garden budgets and purposeful in that each of the schools' gardens were determined to be well integrated and sustained. The processes and strategies used by school gardeners to establish well-integrated school gardens were assessed via data collected from surveys, interviews, observations, and concept mapping. Descriptive statistics as well as multidimensional scaling and hierarchical cluster analysis were used to examine the survey and concept mapping data. Qualitative data analysis consisted of thematic coding, pattern matching, explanation building and cross-case synthesis. Nineteen components within four domains of school garden integration were found through the mixed-methods concept mapping analysis. When the analyses of other data were combined, relationships between domains and components emerged. These data resulted in the development of the GREEN (Garden Resources, Education, and Environment Nexus) Tool. When schools with integrated and sustained gardens were studied, patterns emerged about how gardeners achieve institutionalization through different combinations of critical components. These patterns are best described by the GREEN Tool, the first framework to identify how to operationalize school gardening components and describe an evidence-based strategy of successful school garden integration. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Zinc-assisted hydrodeoxygenation of biomass-derived 5-hydroxymethylfurfural to 2,5-dimethylfuran.

PubMed

Saha, Basudeb; Bohn, Christine M; Abu-Omar, Mahdi M

2014-11-01

2,5-Dimethylfuran (DMF), a promising cellulosic biofuel candidate from biomass derived intermediates, has received significant attention because of its low oxygen content, high energy density, and high octane value. A bimetallic catalyst combination containing a Lewis-acidic Zn(II) and Pd/C components is effective for 5-hydroxymethylfurfural (HMF) hydrodeoxygenation (HDO) to DMF with high conversion (99%) and selectivity (85% DMF). Control experiments for evaluating the roles of zinc and palladium revealed that ZnCl2 alone did not catalyze the reaction, whereas Pd/C produced 60% less DMF than the combination of both metals. The presence of Lewis acidic component (Zn) was also found to be beneficial for HMF HDO with Ru/C catalyst, but the synergistic effect between the two metal components is more pronounced for the Pd/Zn system than the Ru/Zn. A comparative analysis of the Pd/Zn/C catalyst to previously reported catalytic systems show that the Pd/Zn system containing at least four times less precious metal than the reported catalysts gives comparable or better DMF yields. The catalyst shows excellent recyclability up to 4 cycles, followed by a deactivation, which could be due to coke formation on the catalyst surface. The effectiveness of this combined bimetallic catalyst has also been tested for one-pot conversion of fructose to DMF. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A quantitative analysis of the F18 flight control system

NASA Technical Reports Server (NTRS)

Doyle, Stacy A.; Dugan, Joanne B.; Patterson-Hine, Ann

1993-01-01

This paper presents an informal quantitative analysis of the F18 flight control system (FCS). The analysis technique combines a coverage model with a fault tree model. To demonstrate the method's extensive capabilities, we replace the fault tree with a digraph model of the F18 FCS, the only model available to us. The substitution shows that while digraphs have primarily been used for qualitative analysis, they can also be used for quantitative analysis. Based on our assumptions and the particular failure rates assigned to the F18 FCS components, we show that coverage does have a significant effect on the system's reliability and thus it is important to include coverage in the reliability analysis.

High-level magnetic activity nature of the eclipsing binary KIC 12418816

NASA Astrophysics Data System (ADS)

Dal, H. A.; Özdarcan, O.

2018-02-01

We present comprehensive spectroscopic and photometric analysis of the detached eclipsing binary KIC 12418816, which is composed of two very similar and young main-sequence stars of spectral type K0 on a circular orbit. Combining spectroscopic and photometric modelling, we find masses and radii of the components of 0.88 ± 0.06 M⊙ and 0.85 ± 0.02 R⊙ for the primary and 0.84 ± 0.05 M⊙ and 0.84 ± 0.02 R⊙ for the secondary. Both components exhibit narrow emission features superposed on the cores of the Ca II H and K lines, while H α and H β photospheric absoprtion is more completely infilled by broader emission. Very high precision Kepler photometry reveals remarkable sinusoidal light variation at out-of-eclipse phases, indicating strong spot activity, presumably on the surface of the secondary component. Spots on the secondary component appear to migrate towards decreasing orbital phase with a migration period of 0.72 ± 0.05 yr. Besides the sinusoidal variation, we detect 81 flares and find that both components possess flare activity. Our analysis shows that 25 flares out of 81 exhibit very high energies together with lower frequency, while the rest of them are very frequent but with lower energies.

Comparison of five Lonicera flowers by simultaneous determination of multi-components with single reference standard method and principal component analysis.

PubMed

Gao, Wen; Wang, Rui; Li, Dan; Liu, Ke; Chen, Jun; Li, Hui-Jun; Xu, Xiaojun; Li, Ping; Yang, Hua

2016-01-05

The flowers of Lonicera japonica Thunb. were extensively used to treat many diseases. As the demands for L. japonica increased, some related Lonicera plants were often confused or misused. Caffeoylquinic acids were always regarded as chemical markers in the quality control of L. japonica, but they could be found in all Lonicera species. Thus, a simple and reliable method for the evaluation of different Lonicera flowers is necessary to be established. In this work a method based on single standard to determine multi-components (SSDMC) combined with principal component analysis (PCA) for control and distinguish of Lonicera species flowers have been developed. Six components including three caffeoylquinic acids and three iridoid glycosides were assayed simultaneously using chlorogenic acid as the reference standard. The credibility and feasibility of the SSDMC method were carefully validated and the results demonstrated that there were no remarkable differences compared with external standard method. Finally, a total of fifty-one batches covering five Lonicera species were analyzed and PCA was successfully applied to distinguish the Lonicera species. This strategy simplifies the processes in the quality control of multiple-componential herbal medicine which effectively adapted for improving the quality control of those herbs belonging to closely related species. Copyright © 2015 Elsevier B.V. All rights reserved.

Comprehensive two-dimensional HPLC to study the interaction of multiple components in Rheum palmatum L. with HSA by coupling a silica-bonded HSA column to a silica monolithic ODS column.

PubMed

Hu, Lianghai; Li, Xin; Feng, Shun; Kong, Liang; Su, Xingye; Chen, Xueguo; Qin, Feng; Ye, Mingliang; Zou, Hanfa

2006-04-01

A mode of comprehensive 2-D LC was developed by coupling a silica-bonded HSA column to a silica monolithic ODS column. This system combined the affinity property of the HSA column and the high-speed separation ability of the monolithic ODS column. The affinity chromatography with HSA-immobilized stationary phase was applied to study the interaction of multiple components in traditional Chinese medicines (TCMs) with HSA according to their affinity to protein in the first dimension. Then the unresolved components retained on the HSA column were further separated on the silica monolithic ODS column in the second dimension. By hyphenating the 2-D separation system to diode array detector and MS detectors, the UV and molecular weight information of the separated compounds can also be obtained. The developed separation system was applied to analysis of the extract of Rheum palmatum L., a number of low-abundant components can be separated on a single peak from the HSA column after normalization of peak heights. Six compounds were preliminarily identified according to their UV and MS spectra. It showed that this system was very useful for biological fingerprinting analysis of the components in TCMs and natural products.

Is Overactivity a Core Feature in ADHD? Familial and Receiver Operating Characteristic Curve Analysis of Mechanically Assessed Activity Level

ERIC Educational Resources Information Center

Wood, Alexis C.; Asherson, Philip; Rijsdijk, Fruhling; Kuntsi, Jonna

2009-01-01

Objective: Symptoms of overactivity form part of the "DSM-IV" criteria for the combined or hyperactive-impulsive subtypes of attention-deficit/hyperactivity disorder (ADHD); yet little data exist that would quantify the nature of the overactivity component. We aimed to quantify the ability of four different measures of motion sensor data, taken…

Analysis of chemical components from plant tissue samples

NASA Technical Reports Server (NTRS)

Laseter, J. L.

1972-01-01

Information is given on the type and concentration of sterols, free fatty acids, and total fatty acids in plant tissue samples. All samples were analyzed by gas chromatography and then by gas chromatography-mass spectrometry combination. In each case the mass spectral data was accumulated as a computer printout and plot. Typical gas chromatograms are included as well as tables describing test results.

An Analysis of Attitudes toward the Vietnam War Displayed in Children's and Young Adult Literature Published after 1982.

ERIC Educational Resources Information Center

Verhoek, Nancy A.

A study involved the creation of a 20-variable checklist for children's and young adult war literature, to be utilized as a data-recording instrument for 24 examples of literature. The checklist components were based upon a combination of cognitive and affective attributes assisting in the formulation of attitudes toward war displayed by…

Structural reliability assessment capability in NESSUS

NASA Technical Reports Server (NTRS)

Millwater, H.; Wu, Y.-T.

1992-01-01

The principal capabilities of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), an advanced computer code developed for probabilistic structural response analysis, are reviewed, and its structural reliability assessed. The code combines flexible structural modeling tools with advanced probabilistic algorithms in order to compute probabilistic structural response and resistance, component reliability and risk, and system reliability and risk. An illustrative numerical example is presented.

Structural reliability assessment capability in NESSUS

NASA Astrophysics Data System (ADS)

Millwater, H.; Wu, Y.-T.

1992-07-01

The principal capabilities of NESSUS (Numerical Evaluation of Stochastic Structures Under Stress), an advanced computer code developed for probabilistic structural response analysis, are reviewed, and its structural reliability assessed. The code combines flexible structural modeling tools with advanced probabilistic algorithms in order to compute probabilistic structural response and resistance, component reliability and risk, and system reliability and risk. An illustrative numerical example is presented.

77 FR 69509 - Combining Modal Responses and Spatial Components in Seismic Response Analysis

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-19

... available documents online in the NRC Library at http://www.nrc.gov/reading-rm/adams.html . To begin the.... ML122020A044. NRC's Public Document Room: You may examine and purchase copies of public documents at the NRC's... postulated accidents, and data that the staff needs in its review of applications for permits and licenses...

Principal components of wrist circumduction from electromagnetic surgical tracking.

PubMed

Rasquinha, Brian J; Rainbow, Michael J; Zec, Michelle L; Pichora, David R; Ellis, Randy E

2017-02-01

An electromagnetic (EM) surgical tracking system was used for a functionally calibrated kinematic analysis of wrist motion. Circumduction motions were tested for differences in subject gender and for differences in the sense of the circumduction as clockwise or counter-clockwise motion. Twenty subjects were instrumented for EM tracking. Flexion-extension motion was used to identify the functional axis. Subjects performed unconstrained wrist circumduction in a clockwise and counter-clockwise sense. Data were decomposed into orthogonal flexion-extension motions and radial-ulnar deviation motions. PCA was used to concisely represent motions. Nonparametric Wilcoxon tests were used to distinguish the groups. Flexion-extension motions were projected onto a direction axis with a root-mean-square error of [Formula: see text]. Using the first three principal components, there was no statistically significant difference in gender (all [Formula: see text]). For motion sense, radial-ulnar deviation distinguished the sense of circumduction in the first principal component ([Formula: see text]) and in the third principal component ([Formula: see text]); flexion-extension distinguished the sense in the second principal component ([Formula: see text]). The clockwise sense of circumduction could be distinguished by a multifactorial combination of components; there were no gender differences in this small population. These data constitute a baseline for normal wrist circumduction. The multifactorial PCA findings suggest that a higher-dimensional method, such as manifold analysis, may be a more concise way of representing circumduction in human joints.

Long-term behavior understanding based on the expert-based combination of short-term observations in high-resolution CCTV

NASA Astrophysics Data System (ADS)

Schutte, Klamer; Burghouts, Gertjan; van der Stap, Nanda; Westerwoudt, Victor; Bouma, Henri; Kruithof, Maarten; Baan, Jan; ten Hove, Johan-Martijn

2016-10-01

The bottleneck in situation awareness is no longer in the sensing domain but rather in the data interpretation domain, since the number of sensors is rapidly increasing and it is not affordable to increase human data-analysis capacity at the same rate. Automatic image analysis can assist a human analyst by alerting when an event of interest occurs. However, common state-of-the-art image recognition systems learn representations in high-dimensional feature spaces, which makes them less suitable to generate a user-comprehensive message. Such data-driven approaches rely on large amounts of training data, which is often not available for quite rare but high-impact incidents in the security domain. The key contribution of this paper is that we present a novel real-time system for image understanding based on generic instantaneous low-level processing components (symbols) and flexible user-definable and user-understandable combinations of these components (sentences) at a higher level for the recognition of specific relevant events in the security domain. We show that the detection of an event of interest can be enhanced by utilizing recognition of multiple short-term preparatory actions.

Combined ICA-LORETA analysis of mismatch negativity.

PubMed

Marco-Pallarés, J; Grau, C; Ruffini, G

2005-04-01

A major challenge for neuroscience is to map accurately the spatiotemporal patterns of activity of the large neuronal populations that are believed to underlie computing in the human brain. To study a specific example, we selected the mismatch negativity (MMN) brain wave (an event-related potential, ERP) because it gives an electrophysiological index of a "primitive intelligence" capable of detecting changes, even abstract ones, in a regular auditory pattern. ERPs have a temporal resolution of milliseconds but appear to result from mixed neuronal contributions whose spatial location is not fully understood. Thus, it is important to separate these sources in space and time. To tackle this problem, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. Here we implement this approach to analyze the subsecond spatiotemporal dynamics of MMN cerebral sources using trial-by-trial experimental data. We show evidence that a cerebral computation mechanism underlies MMN. This mechanism is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, which activate at distinct time intervals and are grouped in six main statistically independent components.

Development and Integration of an Advanced Stirling Convertor Linear Alternator Model for a Tool Simulating Convertor Performance and Creating Phasor Diagrams

NASA Technical Reports Server (NTRS)

Metscher, Jonathan F.; Lewandowski, Edward J.

2013-01-01

A simple model of the Advanced Stirling Convertors (ASC) linear alternator and an AC bus controller has been developed and combined with a previously developed thermodynamic model of the convertor for a more complete simulation and analysis of the system performance. The model was developed using Sage, a 1-D thermodynamic modeling program that now includes electro-magnetic components. The convertor, consisting of a free-piston Stirling engine combined with a linear alternator, has sufficiently sinusoidal steady-state behavior to allow for phasor analysis of the forces and voltages acting in the system. A MATLAB graphical user interface (GUI) has been developed to interface with the Sage software for simplified use of the ASC model, calculation of forces, and automated creation of phasor diagrams. The GUI allows the user to vary convertor parameters while fixing different input or output parameters and observe the effect on the phasor diagrams or system performance. The new ASC model and GUI help create a better understanding of the relationship between the electrical component voltages and mechanical forces. This allows better insight into the overall convertor dynamics and performance.

Evaluation of Multi-tRNA Synthetase Complex by Multiple Reaction Monitoring Mass Spectrometry Coupled with Size Exclusion Chromatography

PubMed Central

Kim, Jun Seok; Lee, Cheolju

2015-01-01

Eight aminoacyl-tRNA synthetases (M, K, Q, D, R, I, EP and LARS) and three auxiliary proteins (AIMP1, 2 and 3) are known to form a multi-tRNA synthetase complex (MSC) in mammalian cells. We combined size exclusion chromatography (SEC) with reversed-phase liquid chromatography multiple reaction monitoring mass spectrometry (RPLC-MRM-MS) to characterize MSC components and free ARS proteins in human embryonic kidney (HEK 293T) cells. Crude cell extract and affinity-purified proteins were fractionated by SEC in non-denaturing state and ARSs were monitored in each fraction by MRM-MS. The eleven MSC components appeared mostly in earlier SEC fractions demonstrating their participation in complex formation. TARSL2 and AIMP2-DX2, despite their low abundance, were co-purified with KARS and detected in the SEC fractions, where MSC appeared. Moreover, other large complex-forming ARS proteins, such as VARS and FARS, were detected in earlier fractions. The MRM-MS results were further confirmed by western blot analysis. Our study demonstrates usefulness of combined SEC-MRM analysis for the characterization of protein complexes and in understanding the behavior of minor isoforms or variant proteins. PMID:26544075

Envelope analysis of rotating machine vibrations in variable speed conditions: A comprehensive treatment

NASA Astrophysics Data System (ADS)

Abboud, D.; Antoni, J.; Sieg-Zieba, S.; Eltabach, M.

2017-02-01

Nowadays, the vibration analysis of rotating machine signals is a well-established methodology, rooted on powerful tools offered, in particular, by the theory of cyclostationary (CS) processes. Among them, the squared envelope spectrum (SES) is probably the most popular to detect random CS components which are typical symptoms, for instance, of rolling element bearing faults. Recent researches are shifted towards the extension of existing CS tools - originally devised in constant speed conditions - to the case of variable speed conditions. Many of these works combine the SES with computed order tracking after some preprocessing steps. The principal object of this paper is to organize these dispersed researches into a structured comprehensive framework. Three original features are furnished. First, a model of rotating machine signals is introduced which sheds light on the various components to be expected in the SES. Second, a critical comparison is made of three sophisticated methods, namely, the improved synchronous average, the cepstrum prewhitening, and the generalized synchronous average, used for suppressing the deterministic part. Also, a general envelope enhancement methodology which combines the latter two techniques with a time-domain filtering operation is revisited. All theoretical findings are experimentally validated on simulated and real-world vibration signals.

A rapid ATR-FTIR spectroscopic method for detection of sibutramine adulteration in tea and coffee based on hierarchical cluster and principal component analyses.

PubMed

Cebi, Nur; Yilmaz, Mustafa Tahsin; Sagdic, Osman

2017-08-15

Sibutramine may be illicitly included in herbal slimming foods and supplements marketed as "100% natural" to enhance weight loss. Considering public health and legal regulations, there is an urgent need for effective, rapid and reliable techniques to detect sibutramine in dietetic herbal foods, teas and dietary supplements. This research comprehensively explored, for the first time, detection of sibutramine in green tea, green coffee and mixed herbal tea using ATR-FTIR spectroscopic technique combined with chemometrics. Hierarchical cluster analysis and PCA principle component analysis techniques were employed in spectral range (2746-2656cm -1 ) for classification and discrimination through Euclidian distance and Ward's algorithm. Unadulterated and adulterated samples were classified and discriminated with respect to their sibutramine contents with perfect accuracy without any false prediction. The results suggest that existence of the active substance could be successfully determined at the levels in the range of 0.375-12mg in totally 1.75g of green tea, green coffee and mixed herbal tea by using FTIR-ATR technique combined with chemometrics. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of Chuanxiong Rhizoma and its active components by Fourier transform infrared spectroscopy combined with two-dimensional correlation infrared spectroscopy.

PubMed

Guo, Yizhen; Lv, Beiran; Wang, Jingjuan; Liu, Yang; Sun, Suqin; Xiao, Yao; Lu, Lina; Xiang, Li; Yang, Yanfang; Qu, Lei; Meng, Qinghong

2016-01-15

As complicated mixture systems, active components of Chuanxiong Rhizoma are very difficult to identify and discriminate. In this paper, the macroscopic IR fingerprint method including Fourier transform infrared spectroscopy (FT-IR), the second derivative infrared spectroscopy (SD-IR) and two-dimensional correlation infrared spectroscopy (2DCOS-IR), was applied to study and identify Chuanxiong raw materials and its different segmented production of HPD-100 macroporous resin. Chuanxiong Rhizoma is rich in sucrose. In the FT-IR spectra, water eluate is more similar to sucrose than the powder and the decoction. Their second derivative spectra amplified the differences and revealed the potentially characteristic IR absorption bands and combined with the correlation coefficient, concluding that 50% ethanol eluate had more ligustilide than other eluates. Finally, it can be found from 2DCOS-IR spectra that proteins were extracted by ethanol from Chuanxiong decoction by HPD-100 macroporous resin. It was demonstrated that the above three-step infrared spectroscopy could be applicable for quick, non-destructive and effective analysis and identification of very complicated and similar mixture systems of traditional Chinese medicines. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of Multi-tRNA Synthetase Complex by Multiple Reaction Monitoring Mass Spectrometry Coupled with Size Exclusion Chromatography.

PubMed

Park, Seong-Jun; Ahn, Hee-Sung; Kim, Jun Seok; Lee, Cheolju

2015-01-01

Eight aminoacyl-tRNA synthetases (M, K, Q, D, R, I, EP and LARS) and three auxiliary proteins (AIMP1, 2 and 3) are known to form a multi-tRNA synthetase complex (MSC) in mammalian cells. We combined size exclusion chromatography (SEC) with reversed-phase liquid chromatography multiple reaction monitoring mass spectrometry (RPLC-MRM-MS) to characterize MSC components and free ARS proteins in human embryonic kidney (HEK 293T) cells. Crude cell extract and affinity-purified proteins were fractionated by SEC in non-denaturing state and ARSs were monitored in each fraction by MRM-MS. The eleven MSC components appeared mostly in earlier SEC fractions demonstrating their participation in complex formation. TARSL2 and AIMP2-DX2, despite their low abundance, were co-purified with KARS and detected in the SEC fractions, where MSC appeared. Moreover, other large complex-forming ARS proteins, such as VARS and FARS, were detected in earlier fractions. The MRM-MS results were further confirmed by western blot analysis. Our study demonstrates usefulness of combined SEC-MRM analysis for the characterization of protein complexes and in understanding the behavior of minor isoforms or variant proteins.

Screening of the key volatile organic compounds of Tuber melanosporum fermentation by aroma sensory evaluation combination with principle component analysis

PubMed Central

Liu, Rui-Sang; Jin, Guang-Huai; Xiao, Deng-Rong; Li, Hong-Mei; Bai, Feng-Wu; Tang, Ya-Jie

2015-01-01

Aroma results from the interplay of volatile organic compounds (VOCs) and the attributes of microbial-producing aromas are significantly affected by fermentation conditions. Among the VOCs, only a few of them contribute to aroma. Thus, screening and identification of the key VOCs is critical for microbial-producing aroma. The traditional method is based on gas chromatography-olfactometry (GC-O), which is time-consuming and laborious. Considering the Tuber melanosporum fermentation system as an example, a new method to screen and identify the key VOCs by combining the aroma evaluation method with principle component analysis (PCA) was developed in this work. First, an aroma sensory evaluation method was developed to screen 34 potential favorite aroma samples from 504 fermentation samples. Second, PCA was employed to screen nine common key VOCs from these 34 samples. Third, seven key VOCs were identified by the traditional method. Finally, all of the seven key VOCs identified by the traditional method were also identified, along with four others, by the new strategy. These results indicate the reliability of the new method and demonstrate it to be a viable alternative to the traditional method. PMID:26655663

Analysis strategies for combining continuous and episodic GNSS for studies of neo-tectonics in Northern-Norway

NASA Astrophysics Data System (ADS)

Kierulf, Halfdan Pascal

2017-09-01

Crustal deformation in the seismically active Nordland area in Northern Norway is estimated based on a combination of data from local episodic epGNSS campaigns (three 5-day campaigns in 1999, 2008 and 2015) and continuously operating cGNSS stations in the area that were mainly established in 2008 and in 2009. To establish a local long-term stable reference frame, which is consistent both with the epGNSS network and the network of newer cGNSS, a three-step procedure for reference frame realization is used to get consistent results from all the stations in the area. Analysis of the main error sources shows that uncertainties for the episodic epGNSS stations are around 0.2 mm/yr in the horizontal components and 0.5 mm/yr in the vertical component. The results support earlier findings that Ranafjord area of the Nordland is undergoing crustal spreading with horizontal displacement velocities of ca. 1.0 ± 0.2 mm/yr, predominantly in the east-west direction. The results also show a gradient in the uplift along the coast of Nordland that is larger than predicted by existing glacial isostatic adjustment models.

Identification of pesticide varieties by testing microalgae using Visible/Near Infrared Hyperspectral Imaging technology

NASA Astrophysics Data System (ADS)

Shao, Yongni; Jiang, Linjun; Zhou, Hong; Pan, Jian; He, Yong

2016-04-01

In our study, the feasibility of using visible/near infrared hyperspectral imaging technology to detect the changes of the internal components of Chlorella pyrenoidosa so as to determine the varieties of pesticides (such as butachlor, atrazine and glyphosate) at three concentrations (0.6 mg/L, 3 mg/L, 15 mg/L) was investigated. Three models (partial least squares discriminant analysis combined with full wavelengths, FW-PLSDA; partial least squares discriminant analysis combined with competitive adaptive reweighted sampling algorithm, CARS-PLSDA; linear discrimination analysis combined with regression coefficients, RC-LDA) were built by the hyperspectral data of Chlorella pyrenoidosa to find which model can produce the most optimal result. The RC-LDA model, which achieved an average correct classification rate of 97.0% was more superior than FW-PLSDA (72.2%) and CARS-PLSDA (84.0%), and it proved that visible/near infrared hyperspectral imaging could be a rapid and reliable technique to identify pesticide varieties. It also proved that microalgae can be a very promising medium to indicate characteristics of pesticides.

ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features.

PubMed

Mognon, Andrea; Jovicich, Jorge; Bruzzone, Lorenzo; Buiatti, Marco

2011-02-01

A successful method for removing artifacts from electroencephalogram (EEG) recordings is Independent Component Analysis (ICA), but its implementation remains largely user-dependent. Here, we propose a completely automatic algorithm (ADJUST) that identifies artifacted independent components by combining stereotyped artifact-specific spatial and temporal features. Features were optimized to capture blinks, eye movements, and generic discontinuities on a feature selection dataset. Validation on a totally different EEG dataset shows that (1) ADJUST's classification of independent components largely matches a manual one by experts (agreement on 95.2% of the data variance), and (2) Removal of the artifacted components detected by ADJUST leads to neat reconstruction of visual and auditory event-related potentials from heavily artifacted data. These results demonstrate that ADJUST provides a fast, efficient, and automatic way to use ICA for artifact removal. Copyright © 2010 Society for Psychophysiological Research.

KIC 9451096: Magnetic Activity, Flares and Differential Rotation

NASA Astrophysics Data System (ADS)

Özdarcan, O.; Yoldaş, E.; Dal, H. A.

2018-04-01

We present a spectroscopic and photometric analysis of KIC 9451096. The combined spectroscopic and photometric modelling shows that the system is a detached eclipsing binary in a circular orbit and composed of F5V + K2V components. Subtracting the best-fitting light curve model from the whole long cadence data reveals additional low (mmag) amplitude light variations in time and occasional flares, suggesting a low, but still remarkable level of magnetic spot activity on the K2V component. Analyzing the rotational modulation of the light curve residuals enables us to estimate the differential rotation coefficient of the K2V component as k = 0.069 ± 0.008, which is 3 times weaker compared with the solar value of k = 0.19, assuming a solar type differential rotation. We find the stellar flare activity frequency for the K2V component as 0.000368411 h-1 indicating a low magnetic activity level.

Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2016-01-01

A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

Adherence to an (n-3) Fatty Acid/Fish Intake Pattern Is Inversely Associated with Metabolic Syndrome among Puerto Rican Adults in the Greater Boston Area123

PubMed Central

Noel, Sabrina E.; Newby, P. K.; Ordovas, Jose M.; Tucker, Katherine L.

2010-01-01

Combinations of fatty acids may affect risk of metabolic syndrome. Puerto Ricans have a disproportionate number of chronic conditions compared with other Hispanic groups. We aimed to characterize fatty acid intake patterns of Puerto Rican adults aged 45–75 y and living in the Greater Boston area (n = 1207) and to examine associations between these patterns and metabolic syndrome. Dietary fatty acids, as a percentage of total fat, were entered into principle components analysis. Spearman correlation coefficients were used to examine associations between fatty acid intake patterns, nutrients, and food groups. Associations with metabolic syndrome were analyzed by using logistic regression and general linear models with quintiles of principal component scores. Four principal components (factors) emerged: factor 1, short- and medium-chain SFA/dairy; factor 2, (n-3) fatty acid/fish; factor 3, very long-chain (VLC) SFA and PUFA/oils; and factor 4, monounsaturated fatty acid/trans fat. The SFA/dairy factor was inversely associated with fasting serum glucose concentrations (P = 0.02) and the VLC SFA/oils factor was negatively related to waist circumference (P = 0.008). However, these associations were no longer significant after additional adjustment for BMI. The (n-3) fatty acid/fish factor was associated with a lower likelihood of metabolic syndrome (Q5 vs. Q1: odds ratio: 0.54, 95% CI: 0.34, 0.86). In summary, principal components analysis of fatty acid intakes revealed 4 dietary fatty acid patterns in this population. Identifying optimal combinations of fatty acids may be beneficial for understanding relationships with health outcomes given their diverse effects on metabolism. PMID:20702744

Combination of near infrared spectroscopy and chemometrics for authentication of taro flour from wheat and sago flour

NASA Astrophysics Data System (ADS)

Rachmawati; Rohaeti, E.; Rafi, M.

2017-05-01

Taro flour on the market is usually sold at higher price than wheat and sago flour. This situation could be a cause for adulteration of taro flour from wheat and sago flour. For this reason, we will need an identification and authentication. Combination of near infrared (NIR) spectrum with multivariate analysis was used in this study to identify and authenticate taro flour from wheat and sago flour. The authentication model of taro flour was developed by using a mixture of 5%, 25%, and 50% of adulterated taro flour from wheat and sago flour. Before subjected to multivariate analysis, an initial preprocessing signal was used namely normalization and standard normal variate to the NIR spectrum. We used principal component analysis followed by discriminant analysis to make an identification and authentication model of taro flour. From the result obtained, about 90.48% of the taro flour mixed with wheat flour and 85% of taro flour mixed with sago flour were successfully classified into their groups. So the combination of NIR spectrum with chemometrics could be used for identification and authentication of taro flour from wheat and sago flour.

Extracting Independent Local Oscillatory Geophysical Signals by Geodetic Tropospheric Delay

NASA Technical Reports Server (NTRS)

Botai, O. J.; Combrinck, L.; Sivakumar, V.; Schuh, H.; Bohm, J.

2010-01-01

Zenith Tropospheric Delay (ZTD) due to water vapor derived from space geodetic techniques and numerical weather prediction simulated-reanalysis data exhibits non-linear and non-stationary properties akin to those in the crucial geophysical signals of interest to the research community. These time series, once decomposed into additive (and stochastic) components, have information about the long term global change (the trend) and other interpretable (quasi-) periodic components such as seasonal cycles and noise. Such stochastic component(s) could be a function that exhibits at most one extremum within a data span or a monotonic function within a certain temporal span. In this contribution, we examine the use of the combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis (ICA): the EEMD-ICA algorithm to extract the independent local oscillatory stochastic components in the tropospheric delay derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) over six geodetic sites (HartRAO, Hobart26, Wettzell, Gilcreek, Westford, and Tsukub32). The proposed methodology allows independent geophysical processes to be extracted and assessed. Analysis of the quality index of the Independent Components (ICs) derived for each cluster of local oscillatory components (also called the Intrinsic Mode Functions (IMFs)) for all the geodetic stations considered in the study demonstrate that they are strongly site dependent. Such strong dependency seems to suggest that the localized geophysical signals embedded in the ZTD over the geodetic sites are not correlated. Further, from the viewpoint of non-linear dynamical systems, four geophysical signals the Quasi-Biennial Oscillation (QBO) index derived from the NCEP/NCAR reanalysis, the Southern Oscillation Index (SOI) anomaly from NCEP, the SIDC monthly Sun Spot Number (SSN), and the Length of Day (LoD) are linked to the extracted signal components from ZTD. Results from the synchronization analysis show that ZTD and the geophysical signals exhibit (albeit subtle) site dependent phase synchronization index.

Enhanced catalyst for converting synthesis gas to liquid motor fuels

DOEpatents

Coughlin, Peter K.

1986-01-01

The conversion of synthesis gas to liquid molar fuels by means of a cobalt Fischer-Tropsch catalyst composition is enhanced by the addition of molybdenum, tungsten or a combination thereof as an additional component of said composition. The presence of the additive component increases the olefinic content of the hydrocarbon products produced. The catalyst composition can advantageously include a support component, such as a molecular sieve, co-catalyst/support component or a combination of such support components.

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.

PubMed

Boyd, Joseph S; Cheng, Ryan R; Paddock, Mark L; Sancar, Cigdem; Morcos, Faruck; Golden, Susan S

2016-09-15

Two-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems. Signaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Revealing the Structural Complexity of Component Interactions of Topic-Specific PCK when Planning to Teach

NASA Astrophysics Data System (ADS)

Mavhunga, Elizabeth

2018-04-01

Teaching pedagogical content knowledge (PCK) at a topic-specific level requires clarity on the content-specific nature of the components employed, as well as the specific features that bring about the desirable depth in teacher explanations. Such understanding is often hazy; yet, it influences the nature of teacher tasks and learning opportunities afforded to pre-service teachers in a teaching program. The purpose of this study was twofold: firstly, to illuminate the emerging complexity when content-specific components of PCK interact when planning to teach a chemistry topic; and secondly, to identify the kinds of teacher tasks that promote the emergence of such complexity. Data collected were content representations (CoRes) in chemical equilibrium accompanied by expanded lesson outlines from 15 pre-service teachers in their final year of study towards a first degree in teaching (B Ed). The analysis involved extraction of episodes that exhibited component interaction by using a qualitative in-depth analysis method. The results revealed the structure in which the components of PCK in a topic interact among each other to be linear, interwoven, or a combination of the two. The interwoven interactions contained multiple components that connected explanations on different aspects of a concept, all working in a complementary manner. The most sophisticated component interactions emerged from teacher tasks on descriptions of a lesson sequence and a summary of a lesson. Recommendations in this study highlight core practices for making pedagogical transformation of topic content knowledge more accessible.

Analysis of lithology: Vegetation mixes in multispectral images

NASA Technical Reports Server (NTRS)

Adams, J. B.; Smith, M.; Adams, J. D.

1982-01-01

Discrimination and identification of lithologies from multispectral images is discussed. Rock/soil identification can be facilitated by removing the component of the signal in the images that is contributed by the vegetation. Mixing models were developed to predict the spectra of combinations of pure end members, and those models were refined using laboratory measurements of real mixtures. Models in use include a simple linear (checkerboard) mix, granular mixing, semi-transparent coatings, and combinations of the above. The use of interactive computer techniques that allow quick comparison of the spectrum of a pixel stack (in a multiband set) with laboratory spectra is discussed.

Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA.

PubMed

Javed, Ehtasham; Faye, Ibrahima; Malik, Aamir Saeed; Abdullah, Jafri Malin

2017-11-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance image (fMRI) acquisitions provide better insight into brain dynamics. Some artefacts due to simultaneous acquisition pose a threat to the quality of the data. One such problematic artefact is the ballistocardiogram (BCG) artefact. We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. The algorithm does not require extra electrocardiogram (ECG) or electrooculogram (EOG) recordings to extract the BCG artefact. The method was tested with both simulated and real EEG data of 11 participants. From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. On the other hand, real data were recorded with two conditions, i.e. resting state (eyes closed dataset) and task influenced (event-related potentials (ERPs) dataset). Using qualitative (visual inspection) and quantitative (similarity index, improved normalized power spectrum (INPS) ratio, power spectrum, sample entropy (SE)) evaluation parameters, the assessment results showed that the proposed method can efficiently reduce the BCG artefact while preserving the neuronal signals. Compared with conventional methods, namely, average artefact subtraction (AAS), optimal basis set (OBS) and combined independent component analysis and principal component analysis (ICA-PCA), the statistical analyses of the results showed that the proposed method has better performance, and the differences were significant for all quantitative parameters except for the power and sample entropy. The proposed method does not require any reference signal, prior information or assumption to extract the BCG artefact. It will be very useful in circumstances where the reference signal is not available. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of the chemical components of Saussurea involucrata by high-resolution mass spectrometry and the mass spectral trees similarity filter technique.

PubMed

Jia, Zhixin; Wu, Caisheng; Jin, Hongtao; Zhang, Jinlan

2014-11-15

Saussurea involucrata is a rare traditional Chinese medicine (TCM) that displays anti-fatigue, anti-inflammatory and anti-tumor effects. In this paper, the different chemical components of Saussurea involucrata were characterized and identified over a wide dynamic range by high-performance liquid chromatography coupled with high-resolution hybrid mass spectrometry (HPLC/HRMS/MS(n)) and the mass spectral trees similarity filter (MTSF) technique. The aerial parts of Saussurea involucrata were extracted with 75% ethanol. The partial extract was separated on a chromatography column to concentrate the low-concentration compounds. Mass data were acquired using full-scan mass analysis (resolving power 50,000) with data-dependent incorporation of dynamic exclusion analysis. The identified compounds were used as templates to construct a database of mass spectral trees. Data for the unknown compounds were matched with those templates and matching candidate structures were obtained. The detected compounds were characterized based on matching to candidate structures by the MTSF technique and were further identified by their accurate mass weight, multiple-stage analysis and fragmentation patterns and through comparison with literature data. A total of 38 compounds were identified including 19 flavones, 11 phenylpropanoids and 8 sphingolipids. Among them, 7 flavonoids, 8 phenylpropanoids and 8 sphingolipids were identified for the first time in Saussurea involucrata. HPLC/HRMS/MS(n) combined with MTSF was successfully used to discover and identify the chemical compounds in Saussurea involucrata. The results indicated that this combined technique was extremely useful for the rapid detection and identification of the chemical components in TCMs. Copyright © 2014 John Wiley & Sons, Ltd.

BA3b and BA1 activate in a serial fashion after median nerve stimulation: direct evidence from combining source analysis of evoked fields and cytoarchitectonic probabilistic maps.

PubMed

Papadelis, Christos; Eickhoff, Simon B; Zilles, Karl; Ioannides, Andreas A

2011-01-01

This study combines source analysis imaging data for early somatosensory processing and the probabilistic cytoarchitectonic maps (PCMs). Human somatosensory evoked fields (SEFs) were recorded by stimulating left and right median nerves. Filtering the recorded responses in different frequency ranges identified the most responsive frequency band. The short-latency averaged SEFs were analyzed using a single equivalent current dipole (ECD) model and magnetic field tomography (MFT). The identified foci of activity were superimposed with PCMs. Two major components of opposite polarity were prominent around 21 and 31 ms. A weak component around 25 ms was also identified. For the most responsive frequency band (50-150 Hz) ECD and MFT revealed one focal source at the contralateral Brodmann area 3b (BA3b) at the peak of N20. The component ~25 ms was localised in Brodmann area 1 (BA1) in 50-150 Hz. By using ECD, focal generators around 28-30 ms located initially in BA3b and 2 ms later to BA1. MFT also revealed two focal sources - one in BA3b and one in BA1 for these latencies. Our results provide direct evidence that the earliest cortical response after median nerve stimulation is generated within the contralateral BA3b. BA1 activation few milliseconds later indicates a serial mode of somatosensory processing within cytoarchitectonic SI subdivisions. Analysis of non-invasive magnetoencephalography (MEG) data and the use of PCMs allow unambiguous and quantitative (probabilistic) interpretation of cytoarchitectonic identity of activated areas following median nerve stimulation, even with the simple ECD model, but only when the model fits the data extremely well. Copyright © 2010 Elsevier Inc. All rights reserved.

Use of principal component analysis in the evaluation of adherence to statin treatment: a method to determine a potential target population for public health intervention.

PubMed

Latry, Philippe; Martin-Latry, Karin; Labat, Anne; Molimard, Mathieu; Peter, Claude

2011-08-01

The prevalence of statin use is high but adherence low. For public health intervention to be rational, subpopulations of nonadherent subjects must be defined. To categorise statin users with respect to patterns of reimbursement, this study was performed using the main French health reimbursement database for the Aquitaine region of south-western France. The cohort included subjects who submitted a reimbursement for at least one delivery of a statin (index) during the inclusion period (1st of September 2004-31st of December 2004). Indicators of adherence from reimbursement data were considered for principal component analysis. The 119,570 subjects included and analysed had a sex ratio of 1.1, mean (SD) age of 65.9 (11.9), and 13% were considered incident statin users. Principal component analysis found three dimensions that explained 67% of the variance. Using a K-means classification combined with a hierarchical ascendant classification, six groups were characterised. One group was considered nonadherent (10% of study population) and one group least adherent (1%). This novel application of principal component analysis identified groups that may be potential targets for intervention. The least adherent group appears to be one of the most appropriate because of both its relatively small size for case review with prescribing physicians and its very poor adherence. © 2010 The Authors Fundamental and Clinical Pharmacology © 2010 Société Française de Pharmacologie et de Thérapeutique.

Quality Evaluation and Chemical Markers Screening of Salvia miltiorrhiza Bge. (Danshen) Based on HPLC Fingerprints and HPLC-MSn Coupled with Chemometrics.

PubMed

Liang, Wenyi; Chen, Wenjing; Wu, Lingfang; Li, Shi; Qi, Qi; Cui, Yaping; Liang, Linjin; Ye, Ting; Zhang, Lanzhen

2017-03-17

Danshen, the dried root of Salvia miltiorrhiza Bge., is a widely used commercially available herbal drug, and unstable quality of different samples is a current issue. This study focused on a comprehensive and systematic method combining fingerprints and chemical identification with chemometrics for discrimination and quality assessment of Danshen samples. Twenty-five samples were analyzed by HPLC-PAD and HPLC-MS n . Forty-nine components were identified and characteristic fragmentation regularities were summarized for further interpretation of bioactive components. Chemometric analysis was employed to differentiate samples and clarify the quality differences of Danshen including hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis. Consistent results were that the samples were divided into three categories which reflected the difference in quality of Danshen samples. By analyzing the reasons for sample classification, it was revealed that the processing method had a more obvious impact on sample classification than the geographical origin, it induced the different content of bioactive compounds and finally lead to different qualities. Cryptotanshinone, trijuganone B, and 15,16-dihydrotanshinone I were screened out as markers to distinguish samples by different processing methods. The developed strategy could provide a reference for evaluation and discrimination of other traditional herbal medicines.

Model Performance Evaluation and Scenario Analysis ...

EPA Pesticide Factsheets

This tool consists of two parts: model performance evaluation and scenario analysis (MPESA). The model performance evaluation consists of two components: model performance evaluation metrics and model diagnostics. These metrics provides modelers with statistical goodness-of-fit measures that capture magnitude only, sequence only, and combined magnitude and sequence errors. The performance measures include error analysis, coefficient of determination, Nash-Sutcliffe efficiency, and a new weighted rank method. These performance metrics only provide useful information about the overall model performance. Note that MPESA is based on the separation of observed and simulated time series into magnitude and sequence components. The separation of time series into magnitude and sequence components and the reconstruction back to time series provides diagnostic insights to modelers. For example, traditional approaches lack the capability to identify if the source of uncertainty in the simulated data is due to the quality of the input data or the way the analyst adjusted the model parameters. This report presents a suite of model diagnostics that identify if mismatches between observed and simulated data result from magnitude or sequence related errors. MPESA offers graphical and statistical options that allow HSPF users to compare observed and simulated time series and identify the parameter values to adjust or the input data to modify. The scenario analysis part of the too

Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test.

PubMed

Palmerini, Luca; Mellone, Sabato; Rocchi, Laura; Chiari, Lorenzo

2011-01-01

The Timed Up and Go is a clinical test to assess mobility in the elderly and in Parkinson's disease. Lately instrumented versions of the test are being considered, where inertial sensors assess motion. To improve the pervasiveness, ease of use, and cost, we consider a smartphone's accelerometer as the measurement system. Several parameters (usually highly correlated) can be computed from the signals recorded during the test. To avoid redundancy and obtain the features that are most sensitive to the locomotor performance, a dimensionality reduction was performed through principal component analysis (PCA). Forty-nine healthy subjects of different ages were tested. PCA was performed to extract new features (principal components) which are not redundant combinations of the original parameters and account for most of the data variability. They can be useful for exploratory analysis and outlier detection. Then, a reduced set of the original parameters was selected through correlation analysis with the principal components. This set could be recommended for studies based on healthy adults. The proposed procedure could be used as a first-level feature selection in classification studies (i.e. healthy-Parkinson's disease, fallers-non fallers) and could allow, in the future, a complete system for movement analysis to be incorporated in a smartphone.

Bayes-Turchin analysis of x-ray absorption data above the Fe L{sub 2,3}-edges

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

Rossner, H. H.; Schmitz, D.; Imperia, P.

2006-10-01

Extended x-ray absorption fine structure (EXAFS) data and magnetic EXAFS (MEXAFS) data were measured at two temperatures (180 and 296 K) in the energy region of the overlapping L-edges of bcc Fe grown on a V(110) crystal surface. In combination with a Bayes-Turchin data analysis procedure these measurements enable the exploration of local crystallographic and magnetic structures. The analysis determined the atomic-like background together with the EXAFS parameters which consisted of ten shell radii, the Debye-Waller parameters, separated into structural and vibrational components, and the third cumulant of the first scattering path. The vibrational components for 97 different scattering pathsmore » were determined by a two parameter force-field model using a priori values adjusted to Born-von Karman parameters of inelastic neutron scattering data. The investigations of the system Fe/V(110) demonstrate that the simultaneous fitting of atomic background parameters and EXAFS parameters can be performed reliably. Using the L{sub 2}- and L{sub 3}-components extracted from the EXAFS analysis and the rigid-band model, the MEXAFS oscillations can only be described when the sign of the exchange energy is changed compared to the predictions of the Hedin Lundquist exchange and correlation functional.« less

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

Bonamigo, M.; Grillo, C.; Ettori, S.

We present a novel approach for a combined analysis of X-ray and gravitational lensing data and apply this technique to the merging galaxy cluster MACS J0416.1–2403. The method exploits the information on the intracluster gas distribution that comes from a fit of the X-ray surface brightness and then includes the hot gas as a fixed mass component in the strong-lensing analysis. With our new technique, we can separate the collisional from the collision-less diffuse mass components, thus obtaining a more accurate reconstruction of the dark matter distribution in the core of a cluster. We introduce an analytical description of themore » X-ray emission coming from a set of dual pseudo-isothermal elliptical mass distributions, which can be directly used in most lensing softwares. By combining Chandra observations with Hubble Frontier Fields imaging and Multi Unit Spectroscopic Explorer spectroscopy in MACS J0416.1–2403, we measure a projected gas-to-total mass fraction of approximately 10% at 350 kpc from the cluster center. Compared to the results of a more traditional cluster mass model (diffuse halos plus member galaxies), we find a significant difference in the cumulative projected mass profile of the dark matter component and that the dark matter over total mass fraction is almost constant, out to more than 350 kpc. In the coming era of large surveys, these results show the need of multiprobe analyses for detailed dark matter studies in galaxy clusters.« less

[Adaptation to hypoxia and hyperoxia improves physical endurance: the role of reactive oxygen species and redox-signaling].

PubMed

Sazontova, T G; Glazachev, O S; Bolotova, A V; Dudnik, E N; Striapko, N V; Bedareva, I V; Anchishkina, N A; Arkhipenko, Iu V

2012-06-01

We have conducted theoretical foundation, experimental analysis and a pilot study of a new method of adaptation to hypoxia and hyperoxia in the prevention of hypoxic and stress-induced disorders and improving the body's tolerance to physical stress. It has been shown in the experimental part that a combination of physical exercise with adaptation to hypoxia-hyperoxia significantly increased tolerance to acute physical load (APL) and its active phase. Analysis of lipid peroxidation processes, antioxidant enzymes and HSPs showed that short-term training for physical exercise by itself compensates the stressor, but not the hypoxic component of the APL, the combination of training with adaptation to hypoxia-hyperoxia completely normalizes the stressor and hypoxic components of APL. The pilot study has been performed to evaluate the effectiveness of hypoxic-hyperoxic training course in qualified young athletes with over-training syndrome. After completing the course of hypoxia-hyperoxia adaptation, 14 sessions, accompanied by light mode sports training, the athletes set the normalization of autonomic balance, increased resistance to acute hypoxia in hypoxic test, increased physical performance--increased PWC170, maximal oxygen consumption (VO2max) parameters, their relative values to body mass, diminished shift of rate pressure product in the load. Thus, we confirmed experimental findings that hypoxic-hyperoxic training optimizes hypoxic (increased athletes resistance to proper hypoxia) and stress (myocardium economy in acute physical stress testing) components in systemic adaptation and restoration of athletes' with over-training syndrome.

Assessment of annoyance due to urban road traffic noise combined with tramway noise.

PubMed

Klein, A; Marquis-Favre, C; Champelovier, P

2017-01-01

Due to the expansion of urban areas, an increasing number of residents are exposed to combined community noise sources. Studies show that the exposure to transportation noise significantly affects health and well-being. Noise annoyance is one of these adverse health effects. Up to now, annoyance due to transportation noise is mostly assessed considering single noise exposure situations neglecting the effects of potential interactions between noise sources. In this study, perceptual phenomena involved in noise annoyance due to combined urban road traffic and tramway noises are assessed in laboratory conditions with imaginary and simulated contexts. The urban road traffic was composed of light vehicles, heavy vehicles, buses, and powered-two-wheelers in different driving conditions. The tramway traffic corresponded to tramways in in-curve operating configurations. It could be shown that the road traffic and tramway traffic partial annoyance responses were influenced by each other. Throughout the experiments the strongest component effect prevailed but secondary phenomena could also be observed. Considering the perceptual phenomena highlighted in the analysis, it is shown that total noise annoyance due to the combined noises can be most adequately predicted by the strongest component model. This result was obtained by calculating partial annoyance responses due to urban road and tramway traffic.

Process management using component thermal-hydraulic function classes

DOEpatents

Morman, James A.; Wei, Thomas Y. C.; Reifman, Jaques

1999-01-01

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced.

Process management using component thermal-hydraulic function classes

DOEpatents

Morman, J.A.; Wei, T.Y.C.; Reifman, J.

1999-07-27

A process management expert system where following malfunctioning of a component, such as a pump, for determining system realignment procedures such as for by-passing the malfunctioning component with on-line speeds to maintain operation of the process at full or partial capacity or to provide safe shut down of the system while isolating the malfunctioning component. The expert system uses thermal-hydraulic function classes at the component level for analyzing unanticipated as well as anticipated component malfunctions to provide recommended sequences of operator actions. Each component is classified according to its thermal-hydraulic function, and the generic and component-specific characteristics for that function. Using the diagnosis of the malfunctioning component and its thermal hydraulic class, the expert system analysis is carried out using generic thermal-hydraulic first principles. One aspect of the invention employs a qualitative physics-based forward search directed primarily downstream from the malfunctioning component in combination with a subsequent backward search directed primarily upstream from the serviced component. Generic classes of components are defined in the knowledge base according to the three thermal-hydraulic functions of mass, momentum and energy transfer and are used to determine possible realignment of component configurations in response to thermal-hydraulic function imbalance caused by the malfunctioning component. Each realignment to a new configuration produces the accompanying sequence of recommended operator actions. All possible new configurations are examined and a prioritized list of acceptable solutions is produced. 5 figs.

Using auditory pre-information to solve the cocktail-party problem: electrophysiological evidence for age-specific differences.

PubMed

Getzmann, Stephan; Lewald, Jörg; Falkenstein, Michael

2014-01-01

Speech understanding in complex and dynamic listening environments requires (a) auditory scene analysis, namely auditory object formation and segregation, and (b) allocation of the attentional focus to the talker of interest. There is evidence that pre-information is actively used to facilitate these two aspects of the so-called "cocktail-party" problem. Here, a simulated multi-talker scenario was combined with electroencephalography to study scene analysis and allocation of attention in young and middle-aged adults. Sequences of short words (combinations of brief company names and stock-price values) from four talkers at different locations were simultaneously presented, and the detection of target names and the discrimination between critical target values were assessed. Immediately prior to speech sequences, auditory pre-information was provided via cues that either prepared auditory scene analysis or attentional focusing, or non-specific pre-information was given. While performance was generally better in younger than older participants, both age groups benefited from auditory pre-information. The analysis of the cue-related event-related potentials revealed age-specific differences in the use of pre-cues: Younger adults showed a pronounced N2 component, suggesting early inhibition of concurrent speech stimuli; older adults exhibited a stronger late P3 component, suggesting increased resource allocation to process the pre-information. In sum, the results argue for an age-specific utilization of auditory pre-information to improve listening in complex dynamic auditory environments.

Using auditory pre-information to solve the cocktail-party problem: electrophysiological evidence for age-specific differences

PubMed Central

Getzmann, Stephan; Lewald, Jörg; Falkenstein, Michael

2014-01-01

Speech understanding in complex and dynamic listening environments requires (a) auditory scene analysis, namely auditory object formation and segregation, and (b) allocation of the attentional focus to the talker of interest. There is evidence that pre-information is actively used to facilitate these two aspects of the so-called “cocktail-party” problem. Here, a simulated multi-talker scenario was combined with electroencephalography to study scene analysis and allocation of attention in young and middle-aged adults. Sequences of short words (combinations of brief company names and stock-price values) from four talkers at different locations were simultaneously presented, and the detection of target names and the discrimination between critical target values were assessed. Immediately prior to speech sequences, auditory pre-information was provided via cues that either prepared auditory scene analysis or attentional focusing, or non-specific pre-information was given. While performance was generally better in younger than older participants, both age groups benefited from auditory pre-information. The analysis of the cue-related event-related potentials revealed age-specific differences in the use of pre-cues: Younger adults showed a pronounced N2 component, suggesting early inhibition of concurrent speech stimuli; older adults exhibited a stronger late P3 component, suggesting increased resource allocation to process the pre-information. In sum, the results argue for an age-specific utilization of auditory pre-information to improve listening in complex dynamic auditory environments. PMID:25540608

A custom-made temporomandibular joint prosthesis for fabrication by selective laser melting: Finite element analysis.

PubMed

Xu, Xiangliang; Luo, Danmei; Guo, Chuanbin; Rong, Qiguo

2017-08-01

A novel and custom-made selective laser melting (SLM) 3D-printed alloplastic temporomandibular joint (TMJ) prosthesis is proposed. The titanium-6aluminium-4vanadium (Ti-6Al-4V) condyle component and ultra-high molecular weight polyethylene (UHMWPE) fossa component comprised the total alloplastic TMJ replacement prosthesis. For the condyle component, an optimized tetrahedral open-porous scaffold with combined connection structures, i.e. an inlay rod and an onlay plate, between the prosthesis and remaining mandible was designed. The trajectory of movement of the intact condyle was assessed via kinematic analysis to facilitate the design of the fossa component. The behaviours of the intact mandible and mandible with the prosthesis were compared. The biomechanical behaviour was analysed by assessing the stress distribution on the prosthesis and strain distribution on the mandible. After muscle force was applied, the magnitude of the compressive strain on the condyle neck of the mandible with the prosthesis was lower than that on the condyle neck of the intact mandible, with the exception of the area about the screws; additionally, the magnitude of the strain at the scaffold-bone interface was relatively high. Copyright © 2017. Published by Elsevier Ltd.