14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

Rapid analysis of controlled substances using desorption electrospray ionization mass spectrometry.

PubMed

Rodriguez-Cruz, Sandra E

2006-01-01

The recently developed technique of desorption electrospray ionization (DESI) has been applied to the rapid analysis of controlled substances. Experiments have been performed using a commercial ThermoFinnigan LCQ Advantage MAX ion-trap mass spectrometer with limited modifications. Results from the ambient sampling of licit and illicit tablets demonstrate the ability of the DESI technique to detect the main active ingredient(s) or controlled substance(s), even in the presence of other higher-concentration components. Full-scan mass spectrometry data provide preliminary identification by molecular weight determination, while rapid analysis using the tandem mass spectrometry (MS/MS) mode provides fragmentation data which, when compared to the laboratory-generated ESI-MS/MS spectral library, provide structural information and final identification of the active ingredient(s). The consecutive analysis of tablets containing different active components indicates there is no cross-contamination or interference from tablet to tablet, demonstrating the reliability of the DESI technique for rapid sampling (one tablet/min or better). Active ingredients have been detected for tablets in which the active component represents less than 1% of the total tablet weight, demonstrating the sensitivity of the technique. The real-time sampling of cannabis plant material is also presented.

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

Yamanishi, Junsuke; Iwase, Shigeru; Ishida, Nobuyuki; Fujita, Daisuke

2018-01-01

We applied principal component analysis (PCA) to two-dimensional tunneling spectroscopy (2DTS) data obtained on a Si(111)-(7 × 7) surface to explore the effectiveness of multivariate analysis for interpreting 2DTS data. We demonstrated that several components that originated mainly from specific atoms at the Si(111)-(7 × 7) surface can be extracted by PCA. Furthermore, we showed that hidden components in the tunneling spectra can be decomposed (peak separation), which is difficult to achieve with normal 2DTS analysis without the support of theoretical calculations. Our analysis showed that multivariate analysis can be an additional powerful way to analyze 2DTS data and extract hidden information from a large amount of spectroscopic data.

A Bayesian Network Based Global Sensitivity Analysis Method for Identifying Dominant Processes in a Multi-physics Model

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2016-12-01

Sensitivity analysis has been an important tool in groundwater modeling to identify the influential parameters. Among various sensitivity analysis methods, the variance-based global sensitivity analysis has gained popularity for its model independence characteristic and capability of providing accurate sensitivity measurements. However, the conventional variance-based method only considers uncertainty contribution of single model parameters. In this research, we extended the variance-based method to consider more uncertainty sources and developed a new framework to allow flexible combinations of different uncertainty components. We decompose the uncertainty sources into a hierarchical three-layer structure: scenario, model and parametric. Furthermore, each layer of uncertainty source is capable of containing multiple components. An uncertainty and sensitivity analysis framework was then constructed following this three-layer structure using Bayesian network. Different uncertainty components are represented as uncertain nodes in this network. Through the framework, variance-based sensitivity analysis can be implemented with great flexibility of using different grouping strategies for uncertainty components. The variance-based sensitivity analysis thus is improved to be able to investigate the importance of an extended range of uncertainty sources: scenario, model, and other different combinations of uncertainty components which can represent certain key model system processes (e.g., groundwater recharge process, flow reactive transport process). For test and demonstration purposes, the developed methodology was implemented into a test case of real-world groundwater reactive transport modeling with various uncertainty sources. The results demonstrate that the new sensitivity analysis method is able to estimate accurate importance measurements for any uncertainty sources which were formed by different combinations of uncertainty components. The new methodology can provide useful information for environmental management and decision-makers to formulate policies and strategies.

Psychometric evaluation of the Persian version of the Templer's Death Anxiety Scale in cancer patients.

PubMed

Soleimani, Mohammad Ali; Yaghoobzadeh, Ameneh; Bahrami, Nasim; Sharif, Saeed Pahlevan; Sharif Nia, Hamid

2016-10-01

In this study, 398 Iranian cancer patients completed the 15-item Templer's Death Anxiety Scale (TDAS). Tests of internal consistency, principal components analysis, and confirmatory factor analysis were conducted to assess the internal consistency and factorial validity of the Persian TDAS. The construct reliability statistic and average variance extracted were also calculated to measure construct reliability, convergent validity, and discriminant validity. Principal components analysis indicated a 3-component solution, which was generally supported in the confirmatory analysis. However, acceptable cutoffs for construct reliability, convergent validity, and discriminant validity were not fulfilled for the three subscales that were derived from the principal component analysis. This study demonstrated both the advantages and potential limitations of using the TDAS with Persian-speaking cancer patients.

Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

NASA Astrophysics Data System (ADS)

Sun, Zhigang; Wang, Changxi; Niu, Xuming; Song, Yingdong

2017-08-01

In this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

Rotation of EOFs by the Independent Component Analysis: Towards A Solution of the Mixing Problem in the Decomposition of Geophysical Time Series

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Chedin, Alain; Hansen, James E. (Technical Monitor)

2001-01-01

The Independent Component Analysis is a recently developed technique for component extraction. This new method requires the statistical independence of the extracted components, a stronger constraint that uses higher-order statistics, instead of the classical decorrelation, a weaker constraint that uses only second-order statistics. This technique has been used recently for the analysis of geophysical time series with the goal of investigating the causes of variability in observed data (i.e. exploratory approach). We demonstrate with a data simulation experiment that, if initialized with a Principal Component Analysis, the Independent Component Analysis performs a rotation of the classical PCA (or EOF) solution. This rotation uses no localization criterion like other Rotation Techniques (RT), only the global generalization of decorrelation by statistical independence is used. This rotation of the PCA solution seems to be able to solve the tendency of PCA to mix several physical phenomena, even when the signal is just their linear sum.

[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.

Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

2008-06-01

Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Copyright 2007 Wiley-Liss, Inc.

Experimental Analysis of a Four-Component Procedure for Decreasing Noncompliance in a Preschool Child.

ERIC Educational Resources Information Center

Miller, Regina M.; And Others

In this study a 4-component procedure designed to decrease a 4-year-old child's noncompliance behaviors was experimentally analyzed as to the effectiveness of the separate components of the package. Once experimental control had been demonstrated and the subject's noncompliance behaviors had been decreased to an acceptable level, separate analyses…

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.

The economics of project analysis: Optimal investment criteria and methods of study

NASA Technical Reports Server (NTRS)

Scriven, M. C.

1979-01-01

Insight is provided toward the development of an optimal program for investment analysis of project proposals offering commercial potential and its components. This involves a critique of economic investment criteria viewed in relation to requirements of engineering economy analysis. An outline for a systems approach to project analysis is given Application of the Leontief input-output methodology to analysis of projects involving multiple processes and products is investigated. Effective application of elements of neoclassical economic theory to investment analysis of project components is demonstrated. Patterns of both static and dynamic activity levels are incorporated.

Face recognition using an enhanced independent component analysis approach.

PubMed

Kwak, Keun-Chang; Pedrycz, Witold

2007-03-01

This paper is concerned with an enhanced independent component analysis (ICA) and its application to face recognition. Typically, face representations obtained by ICA involve unsupervised learning and high-order statistics. In this paper, we develop an enhancement of the generic ICA by augmenting this method by the Fisher linear discriminant analysis (LDA); hence, its abbreviation, FICA. The FICA is systematically developed and presented along with its underlying architecture. A comparative analysis explores four distance metrics, as well as classification with support vector machines (SVMs). We demonstrate that the FICA approach leads to the formation of well-separated classes in low-dimension subspace and is endowed with a great deal of insensitivity to large variation in illumination and facial expression. The comprehensive experiments are completed for the facial-recognition technology (FERET) face database; a comparative analysis demonstrates that FICA comes with improved classification rates when compared with some other conventional approaches such as eigenface, fisherface, and the ICA itself.

Application of principal component analysis (PCA) as a sensory assessment tool for fermented food products.

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

The objective of the work was to use the method of quantitative descriptive analysis (QDA) to describe the sensory attributes of the fermented food products prepared with the incorporation of lactic cultures. Panellists were selected and trained to evaluate various attributes specially color and appearance, body texture, flavor, overall acceptability and acidity of the fermented food products like cow milk curd and soymilk curd, idli, sauerkraut and probiotic ice cream. Principal component analysis (PCA) identified the six significant principal components that accounted for more than 90% of the variance in the sensory attribute data. Overall product quality was modelled as a function of principal components using multiple least squares regression (R (2) = 0.8). The result from PCA was statistically analyzed by analysis of variance (ANOVA). These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring the fermented food product attributes that are important for consumer acceptability.

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.

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.

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

Vector magnetometer design study: Analysis of a triaxial fluxgate sensor design demonstrates that all MAGSAT Vector Magnetometer specifications can be met

NASA Technical Reports Server (NTRS)

Adams, D. F.; Hartmann, U. G.; Lazarow, L. L.; Maloy, J. O.; Mohler, G. W.

1976-01-01

The design of the vector magnetometer selected for analysis is capable of exceeding the required accuracy of 5 gamma per vector field component. The principal elements that assure this performance level are very low power dissipation triaxial feedback coils surrounding ring core flux-gates and temperature control of the critical components of two-loop feedback electronics. An analysis of the calibration problem points to the need for improved test facilities.

Facile hyphenation of gas chromatography and a microcantilever array sensor for enhanced selectivity.

PubMed

Chapman, Peter J; Vogt, Frank; Dutta, Pampa; Datskos, Panos G; Devault, Gerald L; Sepaniak, Michael J

2007-01-01

The very simple coupling of a standard, packed-column gas chromatograph with a microcantilever array (MCA) is demonstrated for enhanced selectivity and potential analyte identification in the analysis of volatile organic compounds (VOCs). The cantilevers in MCAs are differentially coated on one side with responsive phases (RPs) and produce bending responses of the cantilevers due to analyte-induced surface stresses. Generally, individual components are difficult to elucidate when introduced to MCA systems as mixtures, although pattern recognition techniques are helpful in identifying single components, binary mixtures, or composite responses of distinct mixtures (e.g., fragrances). In the present work, simple test VOC mixtures composed of acetone, ethanol, and trichloroethylene (TCE) in pentane and methanol and acetonitrile in pentane are first separated using a standard gas chromatograph and then introduced into a MCA flow cell. Significant amounts of response diversity to the analytes in the mixtures are demonstrated across the RP-coated cantilevers of the array. Principal component analysis is used to demonstrate that only three components of a four-component VOC mixture could be identified without mixture separation. Calibration studies are performed, demonstrating a good linear response over 2 orders of magnitude for each component in the primary study mixture. Studies of operational parameters including column temperature, column flow rate, and array cell temperature are conducted. Reproducibility studies of VOC peak areas and peak heights are also carried out showing RSDs of less than 4 and 3%, respectively, for intra-assay studies. Of practical significance is the facile manner by which the hyphenation of a mature separation technique and the burgeoning sensing approach is accomplished, and the potential to use pattern recognition techniques with MCAs as a new type of detector for chromatography with analyte-identifying capabilities.

Comparison of multivariate analysis methods for extracting the paraffin component from the paraffin-embedded cancer tissue spectra for Raman imaging

NASA Astrophysics Data System (ADS)

Meksiarun, Phiranuphon; Ishigaki, Mika; Huck-Pezzei, Verena A. C.; Huck, Christian W.; Wongravee, Kanet; Sato, Hidetoshi; Ozaki, Yukihiro

2017-03-01

This study aimed to extract the paraffin component from paraffin-embedded oral cancer tissue spectra using three multivariate analysis (MVA) methods; Independent Component Analysis (ICA), Partial Least Squares (PLS) and Independent Component - Partial Least Square (IC-PLS). The estimated paraffin components were used for removing the contribution of paraffin from the tissue spectra. These three methods were compared in terms of the efficiency of paraffin removal and the ability to retain the tissue information. It was found that ICA, PLS and IC-PLS could remove the paraffin component from the spectra at almost the same level while Principal Component Analysis (PCA) was incapable. In terms of retaining cancer tissue spectral integrity, effects of PLS and IC-PLS on the non-paraffin region were significantly less than that of ICA where cancer tissue spectral areas were deteriorated. The paraffin-removed spectra were used for constructing Raman images of oral cancer tissue and compared with Hematoxylin and Eosin (H&E) stained tissues for verification. This study has demonstrated the capability of Raman spectroscopy together with multivariate analysis methods as a diagnostic tool for the paraffin-embedded tissue section.

Enhancing the Impact of Quality Points in Interteaching

ERIC Educational Resources Information Center

Rosales, Rocío; Soldner, James L.; Crimando, William

2014-01-01

Interteaching is a classroom instruction approach based on behavioral principles that offers increased flexibility to instructors. There are several components of interteaching that may contribute to its demonstrated efficacy. In a prior analysis of one of these components, the quality points contingency, no significant difference was reported in…

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

PubMed

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

2014-01-01

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

Security Analysis of Smart Grid Cyber Physical Infrastructures Using Modeling and Game Theoretic Simulation

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

Abercrombie, Robert K; Sheldon, Frederick T.

Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, andmore » information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.« less

Assessing agro-environmental performance of dairy farms in northwest Italy based on aggregated results from indicators.

PubMed

Gaudino, Stefano; Goia, Irene; Grignani, Carlo; Monaco, Stefano; Sacco, Dario

2014-07-01

Dairy farms control an important share of the agricultural area of Northern Italy. Zero grazing, large maize-cropped areas, high stocking densities, and high milk production make them intensive and prone to impact the environment. Currently, few published studies have proposed indicator sets able to describe the entire dairy farm system and their internal components. This work had four aims: i) to propose a list of agro-environmental indicators to assess dairy farms; ii) to understand which indicators classify farms best; iii) to evaluate the dairy farms based on the proposed indicator list; iv) to link farmer decisions to the consequent environmental pressures. Forty agro-environmental indicators selected for this study are described. Northern Italy dairy systems were analysed considering both farmer decision indicators (farm management) and the resulting pressure indicators that demonstrate environmental stress on the entire farming system, and its components: cropping system, livestock system, and milk production. The correlations among single indicators identified redundant indicators. Principal Components Analysis distinguished which indicators provided meaningful information about each pressure indicator group. Analysis of the communalities and the correlations among indicators identified those that best represented farm variability: Farm Gate N Balance, Greenhouse Gas Emission, and Net Energy of the farm system; Net Energy and Gross P Balance of the cropping system component; Energy Use Efficiency and Purchased Feed N Input of the livestock system component; N Eco-Efficiency of the milk production component. Farm evaluation, based on the complete list of selected indicators demonstrated organic farming resulted in uniformly high values, while farms with low milk-producing herds resulted in uniformly low values. Yet on other farms, the environmental quality varied greatly when different groups of pressure indicators were considered, which highlighted the importance of expanding environmental analysis to effects within the farm. Statistical analysis demonstrated positive correlations between all farmer decision and pressure group indicators. Consumption of mineral fertiliser and pesticide negatively influenced the cropping system. Furthermore, stocking rate was found to correlate positively with the milk production component and negatively with the farm system. This study provides baseline references for ex ante policy evaluation, and monitoring tools for analysis both in itinere and ex post environment policy implementation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Contact Kinematics Correlates to Tibial Component Migration Following Single Radius Posterior Stabilized Knee Replacement.

PubMed

Teeter, Matthew G; Perry, Kevin I; Yuan, Xunhua; Howard, James L; Lanting, Brent A

2018-03-01

Contact kinematics between total knee arthroplasty components is thought to affect implant migration; however, the interaction between kinematics and tibial component migration has not been thoroughly examined in a modern implant system. A total of 24 knees from 23 patients undergoing total knee arthroplasty with a single radius, posterior stabilized implant were examined. Patients underwent radiostereometric analysis at 2 and 6 weeks, 3 and 6 months, and 1 and 2 years to measure migration of the tibial component in all planes. At 1 year, patients also had standing radiostereometric analysis examinations acquired in 0°, 20°, 40°, and 60° of flexion, and the location of contact and magnitude of any condylar liftoff was measured for each flexion angle. Regression analysis was performed between kinematic variables and migration at 1 year. The average magnitude of maximum total point motion across all patients was 0.671 ± 0.270 mm at 1 year and 0.608 ± 0.359 mm at 2 years (P = .327). Four implants demonstrated continuous migration of >0.2 mm between the first and second year of implantation. There were correlations between the location of contact and tibial component anterior-posterior tilt, varus-valgus tilt, and anterior-posterior translation. The patients with continuous migration demonstrated atypical kinematics and condylar liftoff in some instances. Kinematics can influence tibial component migration, likely through alterations of force transmission. Abnormal kinematics may play a role in long-term implant loosening. Copyright © 2017 Elsevier Inc. All rights reserved.

Quantitative analysis of NMR spectra with chemometrics

NASA Astrophysics Data System (ADS)

Winning, H.; Larsen, F. H.; Bro, R.; Engelsen, S. B.

2008-01-01

The number of applications of chemometrics to series of NMR spectra is rapidly increasing due to an emerging interest for quantitative NMR spectroscopy e.g. in the pharmaceutical and food industries. This paper gives an analysis of advantages and limitations of applying the two most common chemometric procedures, Principal Component Analysis (PCA) and Multivariate Curve Resolution (MCR), to a designed set of 231 simple alcohol mixture (propanol, butanol and pentanol) 1H 400 MHz spectra. The study clearly demonstrates that the major advantage of chemometrics is the visualisation of larger data structures which adds a new exploratory dimension to NMR research. While robustness and powerful data visualisation and exploration are the main qualities of the PCA method, the study demonstrates that the bilinear MCR method is an even more powerful method for resolving pure component NMR spectra from mixtures when certain conditions are met.

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.

Nonlinear structural analysis of a turbine airfoil using the Walker viscoplastic material model for B1900 + Hf

NASA Technical Reports Server (NTRS)

Meyer, T. G.; Hill, J. T.; Weber, R. M.

1988-01-01

A viscoplastic material model for the high temperature turbine airfoil material B1900 + Hf was developed and was demonstrated in a three dimensional finite element analysis of a typical turbine airfoil. The demonstration problem is a simulated flight cycle and includes the appropriate transient thermal and mechanical loads typically experienced by these components. The Walker viscoplastic material model was shown to be efficient, stable and easily used. The demonstration is summarized and the performance of the material model is evaluated.

A Fully Automated and Robust Method to Incorporate Stamping Data in Crash, NVH and Durability Analysis

NASA Astrophysics Data System (ADS)

Palaniswamy, Hariharasudhan; Kanthadai, Narayan; Roy, Subir; Beauchesne, Erwan

2011-08-01

Crash, NVH (Noise, Vibration, Harshness), and durability analysis are commonly deployed in structural CAE analysis for mechanical design of components especially in the automotive industry. Components manufactured by stamping constitute a major portion of the automotive structure. In CAE analysis they are modeled at a nominal state with uniform thickness and no residual stresses and strains. However, in reality the stamped components have non-uniformly distributed thickness and residual stresses and strains resulting from stamping. It is essential to consider the stamping information in CAE analysis to accurately model the behavior of the sheet metal structures under different loading conditions. Especially with the current emphasis on weight reduction by replacing conventional steels with aluminum and advanced high strength steels it is imperative to avoid over design. Considering this growing need in industry, a highly automated and robust method has been integrated within Altair Hyperworks® to initialize sheet metal components in CAE models with stamping data. This paper demonstrates this new feature and the influence of stamping data for a full car frontal crash analysis.

G2 Flywheel Module Design

NASA Technical Reports Server (NTRS)

Jensen, Ralph H.; Dever, Timothy P.

2006-01-01

Design of a flywheel module, designated the G2 module, is described. The G2 flywheel is a 60,000 RPM, 525 W-hr, 1 kW system designed for a laboratory environment; it will be used for component testing and system demonstrations, with the goal of applying flywheels to aerospace energy storage and integrated power and attitude control (IPACS) applications. G2 has a modular design, which allows for new motors, magnetic bearings, touchdown bearings, and rotors to be installed without a complete redesign of the system. This design process involves several engineering disciplines, and requirements are developed for the speed, energy storage, power level, and operating environment. The G2 rotor system consists of a multilayer carbon fiber rim with a titanium hub on which the other components mount, and rotordynamics analysis is conducted to ensure rigid and flexible rotor modes are controllable or outside of the operating speed range. Magnetic bearings are sized using 1-D magnetic circuit analysis and refined using 3-D finite element analysis. The G2 magnetic bearing system was designed by Texas A&M and has redundancy which allows derated operation after the loss of some components, and an existing liquid cooled two pole permanent magnet motor/generator is used. The touchdown bearing system is designed with a squeeze film damper system allowing spin down from full operating speed in case of a magnetic bearing failure. The G2 flywheel will enable module level demonstrations of component technology, and will be a key building block in system level attitude control and IPACS demonstrations.

Modeling of power electronic systems with EMTP

NASA Technical Reports Server (NTRS)

Tam, Kwa-Sur; Dravid, Narayan V.

1989-01-01

In view of the potential impact of power electronics on power systems, there is need for a computer modeling/analysis tool to perform simulation studies on power systems with power electronic components as well as to educate engineering students about such systems. The modeling of the major power electronic components of the NASA Space Station Freedom Electric Power System is described along with ElectroMagnetic Transients Program (EMTP) and it is demonstrated that EMTP can serve as a very useful tool for teaching, design, analysis, and research in the area of power systems with power electronic components. EMTP modeling of power electronic circuits is described and simulation results are presented.

Temporal evolution of financial-market correlations.

PubMed

Fenn, Daniel J; Porter, Mason A; Williams, Stacy; McDonald, Mark; Johnson, Neil F; Jones, Nick S

2011-08-01

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007-2008 credit and liquidity crisis.

Corolla Is a Novel Protein That Contributes to the Architecture of the Synaptonemal Complex of Drosophila

PubMed Central

Collins, Kimberly A.; Unruh, Jay R.; Slaughter, Brian D.; Yu, Zulin; Lake, Cathleen M.; Nielsen, Rachel J.; Box, Kimberly S.; Miller, Danny E.; Blumenstiel, Justin P.; Perera, Anoja G.; Malanowski, Kathryn E.; Hawley, R. Scott

2014-01-01

In most organisms the synaptonemal complex (SC) connects paired homologs along their entire length during much of meiotic prophase. To better understand the structure of the SC, we aim to identify its components and to determine how each of these components contributes to SC function. Here, we report the identification of a novel SC component in Drosophila melanogaster female oocytes, which we have named Corolla. Using structured illumination microscopy, we demonstrate that Corolla is a component of the central region of the SC. Consistent with its localization, we show by yeast two-hybrid analysis that Corolla strongly interacts with Cona, a central element protein, demonstrating the first direct interaction between two inner-synaptonemal complex proteins in Drosophila. These observations help provide a more complete model of SC structure and function in Drosophila females. PMID:24913682

Temporal evolution of financial-market correlations

NASA Astrophysics Data System (ADS)

Fenn, Daniel J.; Porter, Mason A.; Williams, Stacy; McDonald, Mark; Johnson, Neil F.; Jones, Nick S.

2011-08-01

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007-2008 credit and liquidity crisis.

Development of High vacuum facility for baking and cool down experiments for SST-1 Tokamak components

NASA Astrophysics Data System (ADS)

Khan, Ziauddin; Pathan, Firozkhan S.; Yuvakiran, Paravastu; George, Siju; Manthena, Himabindu; Raval, Dilip C.; Thankey, Prashant L.; Dhanani, Kalpesh R.; Gupta, Manoj Kumar; Pradhan, Subrata

2012-11-01

SST-1 Tokamak, a steady state super-conducting device, is under refurbishment to demonstrate the plasma discharge for the duration of 1000 second. The major fabricated components of SST-1 like vacuum vessel, thermal shields, superconducting magnets etc have to be tested for their functional parameters. During machine operation, vacuum vessel will be baked at 150 °C, thermal shields will be operated at 85 K and magnet system will be operated at 4.5 K. All these components must have helium leak tightness under these conditions so far as the machine operation is concerned. In order to validate the helium leak tightness of these components, in-house high vacuum chamber is fabricated. This paper describes the analysis, design and fabrication of high vacuum chamber to demonstrate these functionalities. Also some results will be presented.

Mandibular transformations in prepubertal patients following treatment for craniofacial microsomia: thin-plate spline analysis.

PubMed

Hay, A D; Singh, G D

2000-01-01

To analyze correction of mandibular deformity using an inverted L osteotomy and autogenous bone graft in patients exhibiting unilateral craniofacial microsomia (CFM), thin-plate spline analysis was undertaken. Preoperative, early postoperative, and approximately 3.5-year postoperative posteroanterior cephalographs of 15 children (age 10+/-3 years) with CFM were scanned, and eight homologous mandibular landmarks digitized. Average mandibular geometries, scaled to an equivalent size, were generated using Procrustes superimposition. Results indicated that the mean pre- and postoperative mandibular configurations differed statistically (P<0.05). Thin-plate spline analysis indicated that the total spline (Cartesian transformation grid) of the pre- to early postoperative configuration showed mandibular body elongation on the treated side and inferior symphyseal displacement. The affine component of the total spline revealed a clockwise rotation of the preoperative configuration, whereas the nonaffine component was responsible for ramus, body, and symphyseal displacements. The transformation grid for the early and late postoperative comparison showed bilateral ramus elongation. A superior symphyseal displacement contrasted with its earlier inferior displacement, the affine component had translocated the symphyseal landmarks towards the midline. The nonaffine component demonstrated bilateral ramus lengthening, and partial warps suggested that these elongations were slightly greater on the nontreated side. The affine component of the pre- and late postoperative comparison also demonstrated a clockwise rotation. The nonaffine component produced the bilateral ramus elongations-the nontreated side ramus lengthening slightly more than the treated side. It is concluded that an inverted L osteotomy improves mandibular morphology significantly in CFM patients and permits continued bilateral ramus growth. Copyright 2000 Wiley-Liss, Inc.

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.

Pattern Analysis of Dynamic Susceptibility Contrast-enhanced MR Imaging Demonstrates Peritumoral Tissue Heterogeneity

PubMed Central

Akbari, Hamed; Macyszyn, Luke; Da, Xiao; Wolf, Ronald L.; Bilello, Michel; Verma, Ragini; O’Rourke, Donald M.

2014-01-01

Purpose To augment the analysis of dynamic susceptibility contrast material–enhanced magnetic resonance (MR) images to uncover unique tissue characteristics that could potentially facilitate treatment planning through a better understanding of the peritumoral region in patients with glioblastoma. Materials and Methods Institutional review board approval was obtained for this study, with waiver of informed consent for retrospective review of medical records. Dynamic susceptibility contrast-enhanced MR imaging data were obtained for 79 patients, and principal component analysis was applied to the perfusion signal intensity. The first six principal components were sufficient to characterize more than 99% of variance in the temporal dynamics of blood perfusion in all regions of interest. The principal components were subsequently used in conjunction with a support vector machine classifier to create a map of heterogeneity within the peritumoral region, and the variance of this map served as the heterogeneity score. Results The calculated principal components allowed near-perfect separability of tissue that was likely highly infiltrated with tumor and tissue that was unlikely infiltrated with tumor. The heterogeneity map created by using the principal components showed a clear relationship between voxels judged by the support vector machine to be highly infiltrated and subsequent recurrence. The results demonstrated a significant correlation (r = 0.46, P < .0001) between the heterogeneity score and patient survival. The hazard ratio was 2.23 (95% confidence interval: 1.4, 3.6; P < .01) between patients with high and low heterogeneity scores on the basis of the median heterogeneity score. Conclusion Analysis of dynamic susceptibility contrast-enhanced MR imaging data by using principal component analysis can help identify imaging variables that can be subsequently used to evaluate the peritumoral region in glioblastoma. These variables are potentially indicative of tumor infiltration and may become useful tools in guiding therapy, as well as individualized prognostication. © RSNA, 2014 PMID:24955928

Respiratory motion correction in dynamic MRI using robust data decomposition registration - application to DCE-MRI.

PubMed

Hamy, Valentin; Dikaios, Nikolaos; Punwani, Shonit; Melbourne, Andrew; Latifoltojar, Arash; Makanyanga, Jesica; Chouhan, Manil; Helbren, Emma; Menys, Alex; Taylor, Stuart; Atkinson, David

2014-02-01

Motion correction in Dynamic Contrast Enhanced (DCE-) MRI is challenging because rapid intensity changes can compromise common (intensity based) registration algorithms. In this study we introduce a novel registration technique based on robust principal component analysis (RPCA) to decompose a given time-series into a low rank and a sparse component. This allows robust separation of motion components that can be registered, from intensity variations that are left unchanged. This Robust Data Decomposition Registration (RDDR) is demonstrated on both simulated and a wide range of clinical data. Robustness to different types of motion and breathing choices during acquisition is demonstrated for a variety of imaged organs including liver, small bowel and prostate. The analysis of clinically relevant regions of interest showed both a decrease of error (15-62% reduction following registration) in tissue time-intensity curves and improved areas under the curve (AUC60) at early enhancement. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Item-Level Psychometrics of the Glasgow Outcome Scale: Extended Structured Interviews.

PubMed

Hong, Ickpyo; Li, Chih-Ying; Velozo, Craig A

2016-04-01

The Glasgow Outcome Scale-Extended (GOSE) structured interview captures critical components of activities and participation, including home, shopping, work, leisure, and family/friend relationships. Eighty-nine community dwelling adults with mild-moderate traumatic brain injury (TBI) were recruited (average = 2.7 year post injury). Nine items of the 19 items were used for the psychometrics analysis purpose. Factor analysis and item-level psychometrics were investigated using the Rasch partial-credit model. Although the principal components analysis of residuals suggests that a single measurement factor dominates the measure, the instrument did not meet the factor analysis criteria. Five items met the rating scale criteria. Eight items fit the Rasch model. The instrument demonstrated low person reliability (0.63), low person strata (2.07), and a slight ceiling effect. The GOSE demonstrated limitations in precisely measuring activities/participation for individuals after TBI. Future studies should examine the impact of the low precision of the GOSE on effect size. © The Author(s) 2016.

Nonautonomous dark soliton solutions in two-component Bose—Einstein condensates with a linear time-dependent potential

NASA Astrophysics Data System (ADS)

Li, Qiu-Yan; Wang, Shuang-Jin; Li, Zai-Dong

2014-06-01

We report the analytical nonautonomous soliton solutions (NSSs) for two-component Bose—Einstein condensates with the presence of a time-dependent potential. These solutions show that the time-dependent potential can affect the velocity of NSS. The velocity shows the characteristic of both increasing and oscillation with time. A detailed analysis for the asymptotic behavior of NSSs demonstrates that the collision of two NSSs of each component is elastic.

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.

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

Huff, Kathryn D.

Component level and system level abstraction of detailed computational geologic repository models have resulted in four rapid computational models of hydrologic radionuclide transport at varying levels of detail. Those models are described, as is their implementation in Cyder, a software library of interchangeable radionuclide transport models appropriate for representing natural and engineered barrier components of generic geology repository concepts. A proof of principle demonstration was also conducted in which these models were used to represent the natural and engineered barrier components of a repository concept in a reducing, homogenous, generic geology. This base case demonstrates integration of the Cyder openmore » source library with the Cyclus computational fuel cycle systems analysis platform to facilitate calculation of repository performance metrics with respect to fuel cycle choices. (authors)« less

Hilbert-Huang Transform: A Spectral Analysis Tool Applied to Sunspot Number and Total Solar Irradiance Variations, as well as Near-Surface Atmospheric Variables

NASA Astrophysics Data System (ADS)

Barnhart, B. L.; Eichinger, W. E.; Prueger, J. H.

2010-12-01

Hilbert-Huang transform (HHT) is a relatively new data analysis tool which is used to analyze nonstationary and nonlinear time series data. It consists of an algorithm, called empirical mode decomposition (EMD), which extracts the cyclic components embedded within time series data, as well as Hilbert spectral analysis (HSA) which displays the time and frequency dependent energy contributions from each component in the form of a spectrogram. The method can be considered a generalized form of Fourier analysis which can describe the intrinsic cycles of data with basis functions whose amplitudes and phases may vary with time. The HHT will be introduced and compared to current spectral analysis tools such as Fourier analysis, short-time Fourier analysis, wavelet analysis and Wigner-Ville distributions. A number of applications are also presented which demonstrate the strengths and limitations of the tool, including analyzing sunspot number variability and total solar irradiance proxies as well as global averaged temperature and carbon dioxide concentration. Also, near-surface atmospheric quantities such as temperature and wind velocity are analyzed to demonstrate the nonstationarity of the atmosphere.

Selection of independent components based on cortical mapping of electromagnetic activity

NASA Astrophysics Data System (ADS)

Chan, Hui-Ling; Chen, Yong-Sheng; Chen, Li-Fen

2012-10-01

Independent component analysis (ICA) has been widely used to attenuate interference caused by noise components from the electromagnetic recordings of brain activity. However, the scalp topographies and associated temporal waveforms provided by ICA may be insufficient to distinguish functional components from artifactual ones. In this work, we proposed two component selection methods, both of which first estimate the cortical distribution of the brain activity for each component, and then determine the functional components based on the parcellation of brain activity mapped onto the cortical surface. Among all independent components, the first method can identify the dominant components, which have strong activity in the selected dominant brain regions, whereas the second method can identify those inter-regional associating components, which have similar component spectra between a pair of regions. For a targeted region, its component spectrum enumerates the amplitudes of its parceled brain activity across all components. The selected functional components can be remixed to reconstruct the focused electromagnetic signals for further analysis, such as source estimation. Moreover, the inter-regional associating components can be used to estimate the functional brain network. The accuracy of the cortical activation estimation was evaluated on the data from simulation studies, whereas the usefulness and feasibility of the component selection methods were demonstrated on the magnetoencephalography data recorded from a gender discrimination study.

Nuclear Forensics Applications of Principal Component Analysis on Micro X-ray Fluorescence Images

DTIC Science & Technology

analysis on quantified micro x-ray fluorescence intensity values. This method is then applied to address goals of nuclear forensics . Thefirst...researchers in the development and validation of nuclear forensics methods. A method for determining material homogeneity is developed and demonstrated

Energy Efficient Engine Low Pressure Subsystem Aerodynamic Analysis

NASA Technical Reports Server (NTRS)

Hall, Edward J.; Delaney, Robert A.; Lynn, Sean R.; Veres, Joseph P.

1998-01-01

The objective of this study was to demonstrate the capability to analyze the aerodynamic performance of the complete low pressure subsystem (LPS) of the Energy Efficient Engine (EEE). Detailed analyses were performed using three- dimensional Navier-Stokes numerical models employing advanced clustered processor computing platforms. The analysis evaluates the impact of steady aerodynamic interaction effects between the components of the LPS at design and off- design operating conditions. Mechanical coupling is provided by adjusting the rotational speed of common shaft-mounted components until a power balance is achieved. The Navier-Stokes modeling of the complete low pressure subsystem provides critical knowledge of component acro/mechanical interactions that previously were unknown to the designer until after hardware testing.

Exploring patterns enriched in a dataset with contrastive principal component analysis.

PubMed

Abid, Abubakar; Zhang, Martin J; Bagaria, Vivek K; Zou, James

2018-05-30

Visualization and exploration of high-dimensional data is a ubiquitous challenge across disciplines. Widely used techniques such as principal component analysis (PCA) aim to identify dominant trends in one dataset. However, in many settings we have datasets collected under different conditions, e.g., a treatment and a control experiment, and we are interested in visualizing and exploring patterns that are specific to one dataset. This paper proposes a method, contrastive principal component analysis (cPCA), which identifies low-dimensional structures that are enriched in a dataset relative to comparison data. In a wide variety of experiments, we demonstrate that cPCA with a background dataset enables us to visualize dataset-specific patterns missed by PCA and other standard methods. We further provide a geometric interpretation of cPCA and strong mathematical guarantees. An implementation of cPCA is publicly available, and can be used for exploratory data analysis in many applications where PCA is currently used.

14 CFR 417.301 - General.

Code of Federal Regulations, 2011 CFR

2011-01-01

... undergo analysis and testing that is comparable to that required by this part to demonstrate that the...) Functions, subsystems, and components. When initiated in the event of a launch vehicle failure, a flight...

14 CFR 417.301 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... undergo analysis and testing that is comparable to that required by this part to demonstrate that the...) Functions, subsystems, and components. When initiated in the event of a launch vehicle failure, a flight...

14 CFR 417.301 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... undergo analysis and testing that is comparable to that required by this part to demonstrate that the...) Functions, subsystems, and components. When initiated in the event of a launch vehicle failure, a flight...

14 CFR 417.301 - General.

Code of Federal Regulations, 2014 CFR

2014-01-01

... undergo analysis and testing that is comparable to that required by this part to demonstrate that the...) Functions, subsystems, and components. When initiated in the event of a launch vehicle failure, a flight...

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

PubMed Central

Amenabar, Iban; Poly, Simon; Goikoetxea, Monika; Nuansing, Wiwat; Lasch, Peter; Hillenbrand, Rainer

2017-01-01

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm−1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine. PMID:28198384

Hyperspectral infrared nanoimaging of organic samples based on Fourier transform infrared nanospectroscopy

NASA Astrophysics Data System (ADS)

Amenabar, Iban; Poly, Simon; Goikoetxea, Monika; Nuansing, Wiwat; Lasch, Peter; Hillenbrand, Rainer

2017-02-01

Infrared nanospectroscopy enables novel possibilities for chemical and structural analysis of nanocomposites, biomaterials or optoelectronic devices. Here we introduce hyperspectral infrared nanoimaging based on Fourier transform infrared nanospectroscopy with a tunable bandwidth-limited laser continuum. We describe the technical implementations and present hyperspectral infrared near-field images of about 5,000 pixel, each one covering the spectral range from 1,000 to 1,900 cm-1. To verify the technique and to demonstrate its application potential, we imaged a three-component polymer blend and a melanin granule in a human hair cross-section, and demonstrate that multivariate data analysis can be applied for extracting spatially resolved chemical information. Particularly, we demonstrate that distribution and chemical interaction between the polymer components can be mapped with a spatial resolution of about 30 nm. We foresee wide application potential of hyperspectral infrared nanoimaging for valuable chemical materials characterization and quality control in various fields ranging from materials sciences to biomedicine.

Respondent Techniques for Reduction of Emotions Limiting School Adjustment: A Quantitative Review and Methodological Critique.

ERIC Educational Resources Information Center

Misra, Anjali; Schloss, Patrick J.

1989-01-01

The critical analysis of 23 studies using respondent techniques for the reduction of excessive emotional reactions in school children focuses on research design, dependent variables, independent variables, component analysis, and demonstrations of generalization and maintenance. Results indicate widespread methodological flaws that limit the…

Isomorphisms between Petri nets and dataflow graphs

NASA Technical Reports Server (NTRS)

Kavi, Krishna M.; Buckles, Billy P.; Bhat, U. Narayan

1987-01-01

Dataflow graphs are a generalized model of computation. Uninterpreted dataflow graphs with nondeterminism resolved via probabilities are shown to be isomorphic to a class of Petri nets known as free choice nets. Petri net analysis methods are readily available in the literature and this result makes those methods accessible to dataflow research. Nevertheless, combinatorial explosion can render Petri net analysis inoperative. Using a previously known technique for decomposing free choice nets into smaller components, it is demonstrated that, in principle, it is possible to determine aspects of the overall behavior from the particular behavior of components.

High Temperature Transparent Furnace Development

NASA Technical Reports Server (NTRS)

Bates, Stephen C.

1997-01-01

This report describes the use of novel techniques for heat containment that could be used to build a high temperature transparent furnace. The primary objective of the work was to experimentally demonstrate transparent furnace operation at 1200 C. Secondary objectives were to understand furnace operation and furnace component specification to enable the design and construction of a low power prototype furnace for delivery to NASA in a follow-up project. The basic approach of the research was to couple high temperature component design with simple concept demonstration experiments that modify a commercially available transparent furnace rated at lower temperature. A detailed energy balance of the operating transparent furnace was performed, calculating heat losses through the furnace components as a result of conduction, radiation, and convection. The transparent furnace shells and furnace components were redesigned to permit furnace operation at at least 1200 C. Techniques were developed that are expected to lead to significantly improved heat containment compared with current transparent furnaces. The design of a thermal profile in a multizone high temperature transparent furnace design was also addressed. Experiments were performed to verify the energy balance analysis, to demonstrate some of the major furnace improvement techniques developed, and to demonstrate the overall feasibility of a high temperature transparent furnace. The important objective of the research was achieved: to demonstrate the feasibility of operating a transparent furnace at 1200 C.

Multiple Component Event-Related Potential (mcERP) Estimation

NASA Technical Reports Server (NTRS)

Knuth, K. H.; Clanton, S. T.; Shah, A. S.; Truccolo, W. A.; Ding, M.; Bressler, S. L.; Trejo, L. J.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

We show how model-based estimation of the neural sources responsible for transient neuroelectric signals can be improved by the analysis of single trial data. Previously, we showed that a multiple component event-related potential (mcERP) algorithm can extract the responses of individual sources from recordings of a mixture of multiple, possibly interacting, neural ensembles. McERP also estimated single-trial amplitudes and onset latencies, thus allowing more accurate estimation of ongoing neural activity during an experimental trial. The mcERP algorithm is related to informax independent component analysis (ICA); however, the underlying signal model is more physiologically realistic in that a component is modeled as a stereotypic waveshape varying both in amplitude and onset latency from trial to trial. The result is a model that reflects quantities of interest to the neuroscientist. Here we demonstrate that the mcERP algorithm provides more accurate results than more traditional methods such as factor analysis and the more recent ICA. Whereas factor analysis assumes the sources are orthogonal and ICA assumes the sources are statistically independent, the mcERP algorithm makes no such assumptions thus allowing investigators to examine interactions among components by estimating the properties of single-trial responses.

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.

A case study in nonconformance and performance trend analysis

NASA Technical Reports Server (NTRS)

Maloy, Joseph E.; Newton, Coy P.

1990-01-01

As part of NASA's effort to develop an agency-wide approach to trend analysis, a pilot nonconformance and performance trending analysis study was conducted on the Space Shuttle auxiliary power unit (APU). The purpose of the study was to (1) demonstrate that nonconformance analysis can be used to identify repeating failures of a specific item (and the associated failure modes and causes) and (2) determine whether performance parameters could be analyzed and monitored to provide an indication of component or system degradation prior to failure. The nonconformance analysis of the APU did identify repeating component failures, which possibly could be reduced if key performance parameters were monitored and analyzed. The performance-trending analysis verified that the characteristics of hardware parameters can be effective in detecting degradation of hardware performance prior to failure.

Comparison of the phenolic composition of fruit juices by single step gradient HPLC analysis of multiple components versus multiple chromatographic runs optimised for individual families.

PubMed

Bremner, P D; Blacklock, C J; Paganga, G; Mullen, W; Rice-Evans, C A; Crozier, A

2000-06-01

After minimal sample preparation, two different HPLC methodologies, one based on a single gradient reversed-phase HPLC step, the other on multiple HPLC runs each optimised for specific components, were used to investigate the composition of flavonoids and phenolic acids in apple and tomato juices. The principal components in apple juice were identified as chlorogenic acid, phloridzin, caffeic acid and p-coumaric acid. Tomato juice was found to contain chlorogenic acid, caffeic acid, p-coumaric acid, naringenin and rutin. The quantitative estimates of the levels of these compounds, obtained with the two HPLC procedures, were very similar, demonstrating that either method can be used to analyse accurately the phenolic components of apple and tomato juices. Chlorogenic acid in tomato juice was the only component not fully resolved in the single run study and the multiple run analysis prior to enzyme treatment. The single run system of analysis is recommended for the initial investigation of plant phenolics and the multiple run approach for analyses where chromatographic resolution requires improvement.

[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.

Visualizing Hyolaryngeal Mechanics in Swallowing Using Dynamic MRI

PubMed Central

Pearson, William G.; Zumwalt, Ann C.

2013-01-01

Introduction Coordinates of anatomical landmarks are captured using dynamic MRI to explore whether a proposed two-sling mechanism underlies hyolaryngeal elevation in pharyngeal swallowing. A principal components analysis (PCA) is applied to coordinates to determine the covariant function of the proposed mechanism. Methods Dynamic MRI (dMRI) data were acquired from eleven healthy subjects during a repeated swallows task. Coordinates mapping the proposed mechanism are collected from each dynamic (frame) of a dynamic MRI swallowing series of a randomly selected subject in order to demonstrate shape changes in a single subject. Coordinates representing minimum and maximum hyolaryngeal elevation of all 11 subjects were also mapped to demonstrate shape changes of the system among all subjects. MophoJ software was used to perform PCA and determine vectors of shape change (eigenvectors) for elements of the two-sling mechanism of hyolaryngeal elevation. Results For both single subject and group PCAs, hyolaryngeal elevation accounted for the first principal component of variation. For the single subject PCA, the first principal component accounted for 81.5% of the variance. For the between subjects PCA, the first principal component accounted for 58.5% of the variance. Eigenvectors and shape changes associated with this first principal component are reported. Discussion Eigenvectors indicate that two-muscle slings and associated skeletal elements function as components of a covariant mechanism to elevate the hyolaryngeal complex. Morphological analysis is useful to model shape changes in the two-sling mechanism of hyolaryngeal elevation. PMID:25090608

Demonstration of a Safety Analysis on a Complex System

NASA Technical Reports Server (NTRS)

Leveson, Nancy; Alfaro, Liliana; Alvarado, Christine; Brown, Molly; Hunt, Earl B.; Jaffe, Matt; Joslyn, Susan; Pinnell, Denise; Reese, Jon; Samarziya, Jeffrey;

Reliability analysis of component-level redundant topologies for solid-state fault current limiter

NASA Astrophysics Data System (ADS)

Farhadi, Masoud; Abapour, Mehdi; Mohammadi-Ivatloo, Behnam

2018-04-01

Experience shows that semiconductor switches in power electronics systems are the most vulnerable components. One of the most common ways to solve this reliability challenge is component-level redundant design. There are four possible configurations for the redundant design in component level. This article presents a comparative reliability analysis between different component-level redundant designs for solid-state fault current limiter. The aim of the proposed analysis is to determine the more reliable component-level redundant configuration. The mean time to failure (MTTF) is used as the reliability parameter. Considering both fault types (open circuit and short circuit), the MTTFs of different configurations are calculated. It is demonstrated that more reliable configuration depends on the junction temperature of the semiconductor switches in the steady state. That junction temperature is a function of (i) ambient temperature, (ii) power loss of the semiconductor switch and (iii) thermal resistance of heat sink. Also, results' sensitivity to each parameter is investigated. The results show that in different conditions, various configurations have higher reliability. The experimental results are presented to clarify the theory and feasibility of the proposed approaches. At last, levelised costs of different configurations are analysed for a fair comparison.

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.

Independent component analysis-based algorithm for automatic identification of Raman spectra applied to artistic pigments and pigment mixtures.

PubMed

González-Vidal, Juan José; Pérez-Pueyo, Rosanna; Soneira, María José; Ruiz-Moreno, Sergio

2015-03-01

A new method has been developed to automatically identify Raman spectra, whether they correspond to single- or multicomponent spectra. The method requires no user input or judgment. There are thus no parameters to be tweaked. Furthermore, it provides a reliability factor on the resulting identification, with the aim of becoming a useful support tool for the analyst in the decision-making process. The method relies on the multivariate techniques of principal component analysis (PCA) and independent component analysis (ICA), and on some metrics. It has been developed for the application of automated spectral analysis, where the analyzed spectrum is provided by a spectrometer that has no previous knowledge of the analyzed sample, meaning that the number of components in the sample is unknown. We describe the details of this method and demonstrate its efficiency by identifying both simulated spectra and real spectra. The method has been applied to artistic pigment identification. The reliable and consistent results that were obtained make the methodology a helpful tool suitable for the identification of pigments in artwork or in paint in general.

Principal component analysis of indocyanine green fluorescence dynamics for diagnosis of vascular diseases

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Choi, Chulhee

2015-03-01

Indocyanine green (ICG), a near-infrared fluorophore, has been used in visualization of vascular structure and non-invasive diagnosis of vascular disease. Although many imaging techniques have been developed, there are still limitations in diagnosis of vascular diseases. We have recently developed a minimally invasive diagnostics system based on ICG fluorescence imaging for sensitive detection of vascular insufficiency. In this study, we used principal component analysis (PCA) to examine ICG spatiotemporal profile and to obtain pathophysiological information from ICG dynamics. Here we demonstrated that principal components of ICG dynamics in both feet showed significant differences between normal control and diabetic patients with vascula complications. We extracted the PCA time courses of the first three components and found distinct pattern in diabetic patient. We propose that PCA of ICG dynamics reveal better classification performance compared to fluorescence intensity analysis. We anticipate that specific feature of spatiotemporal ICG dynamics can be useful in diagnosis of various vascular diseases.

Airborne electromagnetic data levelling using principal component analysis based on flight line difference

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Peng, Cong; Lu, Yiming; Wang, Hao; Zhu, Kaiguang

2018-04-01

A novel technique is developed to level airborne geophysical data using principal component analysis based on flight line difference. In the paper, flight line difference is introduced to enhance the features of levelling error for airborne electromagnetic (AEM) data and improve the correlation between pseudo tie lines. Thus we conduct levelling to the flight line difference data instead of to the original AEM data directly. Pseudo tie lines are selected distributively cross profile direction, avoiding the anomalous regions. Since the levelling errors of selective pseudo tie lines show high correlations, principal component analysis is applied to extract the local levelling errors by low-order principal components reconstruction. Furthermore, we can obtain the levelling errors of original AEM data through inverse difference after spatial interpolation. This levelling method does not need to fly tie lines and design the levelling fitting function. The effectiveness of this method is demonstrated by the levelling results of survey data, comparing with the results from tie-line levelling and flight-line correlation levelling.

Design, Analysis and Fabrication of Secondary Structural Components for the Habitat Demonstration Unit-Deep Space Habitat

NASA Technical Reports Server (NTRS)

Smith, Russell W.; Langford, William M.

2012-01-01

In support of NASA s Habitat Demonstration Unit - Deep Space Habitat Prototype, a number of evolved structural sections were designed, fabricated, analyzed and installed in the 5 meter diameter prototype. The hardware consisted of three principal structural sections, and included the development of novel fastener insert concepts. The articles developed consisted of: 1) 1/8th of the primary flooring section, 2) an inner radius floor beam support which interfaced with, and supported (1), 3) two upper hatch section prototypes, and 4) novel insert designs for mechanical fastener attachments. Advanced manufacturing approaches were utilized in the fabrication of the components. The structural components were developed using current commercial aircraft constructions as a baseline (for both the flooring components and their associated mechanical fastener inserts). The structural sections utilized honeycomb sandwich panels. The core section consisted of 1/8th inch cell size Nomex, at 9 lbs/cu ft, and which was 0.66 inches thick. The facesheets had 3 plys each, with a thickness of 0.010 inches per ply, made from woven E-glass with epoxy reinforcement. Analysis activities consisted of both analytical models, as well as initial closed form calculations. Testing was conducted to help verify analysis model inputs, as well as to facilitate correlation between testing and analysis. Test activities consisted of both 4 point bending tests as well as compressive core crush sequences. This paper presents an overview of this activity, and discusses issues encountered during the various phases of the applied research effort, and its relevance to future space based habitats.

Evaluation of Staining-Dependent Colour Changes in Resin Composites Using Principal Component Analysis

PubMed Central

Manojlovic, D.; Lenhardt, L.; Milićević, B.; Antonov, M.; Miletic, V.; Dramićanin, M. D.

2015-01-01

Colour changes in Gradia Direct™ composite after immersion in tea, coffee, red wine, Coca-Cola, Colgate mouthwash, and distilled water were evaluated using principal component analysis (PCA) and the CIELAB colour coordinates. The reflection spectra of the composites were used as input data for the PCA. The output data (scores and loadings) provided information about the magnitude and origin of the surface reflection changes after exposure to the staining solutions. The reflection spectra of the stained samples generally exhibited lower reflection in the blue spectral range, which was manifested in the lower content of the blue shade for the samples. Both analyses demonstrated the high staining abilities of tea, coffee, and red wine, which produced total colour changes of 4.31, 6.61, and 6.22, respectively, according to the CIELAB analysis. PCA revealed subtle changes in the reflection spectra of composites immersed in Coca-Cola, demonstrating Coca-Cola’s ability to stain the composite to a small degree. PMID:26450008

Evaluation of Staining-Dependent Colour Changes in Resin Composites Using Principal Component Analysis.

PubMed

Manojlovic, D; Lenhardt, L; Milićević, B; Antonov, M; Miletic, V; Dramićanin, M D

2015-10-09

Colour changes in Gradia Direct™ composite after immersion in tea, coffee, red wine, Coca-Cola, Colgate mouthwash, and distilled water were evaluated using principal component analysis (PCA) and the CIELAB colour coordinates. The reflection spectra of the composites were used as input data for the PCA. The output data (scores and loadings) provided information about the magnitude and origin of the surface reflection changes after exposure to the staining solutions. The reflection spectra of the stained samples generally exhibited lower reflection in the blue spectral range, which was manifested in the lower content of the blue shade for the samples. Both analyses demonstrated the high staining abilities of tea, coffee, and red wine, which produced total colour changes of 4.31, 6.61, and 6.22, respectively, according to the CIELAB analysis. PCA revealed subtle changes in the reflection spectra of composites immersed in Coca-Cola, demonstrating Coca-Cola's ability to stain the composite to a small degree.

The Contribution of Systems Analysis to Training Students in Cognitive Interdisciplinary Skills in Environmental Science Education

ERIC Educational Resources Information Center

Fortuin, K. P. J.; van Koppen, C. S. A.; Kroeze, C.

2013-01-01

Professionals in the environmental domain require cognitive interdisciplinary skills to be able to develop sustainable solutions to environmental problems. We demonstrate that education in environmental systems analysis allows for the development of these skills. We identify three components of cognitive interdisciplinary skills: (1) the ability…

Fast principal component analysis for stacking seismic data

NASA Astrophysics Data System (ADS)

Wu, Juan; Bai, Min

2018-04-01

Stacking seismic data plays an indispensable role in many steps of the seismic data processing and imaging workflow. Optimal stacking of seismic data can help mitigate seismic noise and enhance the principal components to a great extent. Traditional average-based seismic stacking methods cannot obtain optimal performance when the ambient noise is extremely strong. We propose a principal component analysis (PCA) algorithm for stacking seismic data without being sensitive to noise level. Considering the computational bottleneck of the classic PCA algorithm in processing massive seismic data, we propose an efficient PCA algorithm to make the proposed method readily applicable for industrial applications. Two numerically designed examples and one real seismic data are used to demonstrate the performance of the presented method.

Use of direct gradient analysis to uncover biological hypotheses in 16s survey data and beyond.

PubMed

Erb-Downward, John R; Sadighi Akha, Amir A; Wang, Juan; Shen, Ning; He, Bei; Martinez, Fernando J; Gyetko, Margaret R; Curtis, Jeffrey L; Huffnagle, Gary B

2012-01-01

This study investigated the use of direct gradient analysis of bacterial 16S pyrosequencing surveys to identify relevant bacterial community signals in the midst of a "noisy" background, and to facilitate hypothesis-testing both within and beyond the realm of ecological surveys. The results, utilizing 3 different real world data sets, demonstrate the utility of adding direct gradient analysis to any analysis that draws conclusions from indirect methods such as Principal Component Analysis (PCA) and Principal Coordinates Analysis (PCoA). Direct gradient analysis produces testable models, and can identify significant patterns in the midst of noisy data. Additionally, we demonstrate that direct gradient analysis can be used with other kinds of multivariate data sets, such as flow cytometric data, to identify differentially expressed populations. The results of this study demonstrate the utility of direct gradient analysis in microbial ecology and in other areas of research where large multivariate data sets are involved.

SCGICAR: Spatial concatenation based group ICA with reference for fMRI data analysis.

PubMed

Shi, Yuhu; Zeng, Weiming; Wang, Nizhuan

2017-09-01

With the rapid development of big data, the functional magnetic resonance imaging (fMRI) data analysis of multi-subject is becoming more and more important. As a kind of blind source separation technique, group independent component analysis (GICA) has been widely applied for the multi-subject fMRI data analysis. However, spatial concatenated GICA is rarely used compared with temporal concatenated GICA due to its disadvantages. In this paper, in order to overcome these issues and to consider that the ability of GICA for fMRI data analysis can be improved by adding a priori information, we propose a novel spatial concatenation based GICA with reference (SCGICAR) method to take advantage of the priori information extracted from the group subjects, and then the multi-objective optimization strategy is used to implement this method. Finally, the post-processing means of principal component analysis and anti-reconstruction are used to obtain group spatial component and individual temporal component in the group, respectively. The experimental results show that the proposed SCGICAR method has a better performance on both single-subject and multi-subject fMRI data analysis compared with classical methods. It not only can detect more accurate spatial and temporal component for each subject of the group, but also can obtain a better group component on both temporal and spatial domains. These results demonstrate that the proposed SCGICAR method has its own advantages in comparison with classical methods, and it can better reflect the commonness of subjects in the group. Copyright © 2017 Elsevier B.V. All rights reserved.

Correlation of ground tests and analyses of a dynamically scaled Space Station model configuration

NASA Technical Reports Server (NTRS)

Javeed, Mehzad; Edighoffer, Harold H.; Mcgowan, Paul E.

1993-01-01

Verification of analytical models through correlation with ground test results of a complex space truss structure is demonstrated. A multi-component, dynamically scaled space station model configuration is the focus structure for this work. Previously established test/analysis correlation procedures are used to develop improved component analytical models. Integrated system analytical models, consisting of updated component analytical models, are compared with modal test results to establish the accuracy of system-level dynamic predictions. Design sensitivity model updating methods are shown to be effective for providing improved component analytical models. Also, the effects of component model accuracy and interface modeling fidelity on the accuracy of integrated model predictions is examined.

Quantitative descriptive analysis and principal component analysis for sensory characterization of Indian milk product cham-cham.

PubMed

Puri, Ritika; Khamrui, Kaushik; Khetra, Yogesh; Malhotra, Ravinder; Devraja, H C

2016-02-01

Promising development and expansion in the market of cham-cham, a traditional Indian dairy product is expected in the coming future with the organized production of this milk product by some large dairies. The objective of this study was to document the extent of variation in sensory properties of market samples of cham-cham collected from four different locations known for their excellence in cham-cham production and to find out the attributes that govern much of variation in sensory scores of this product using quantitative descriptive analysis (QDA) and principal component analysis (PCA). QDA revealed significant (p < 0.05) difference in sensory attributes of cham-cham among the market samples. PCA identified four significant principal components that accounted for 72.4 % of the variation in the sensory data. Factor scores of each of the four principal components which primarily correspond to sweetness/shape/dryness of interior, surface appearance/surface dryness, rancid and firmness attributes specify the location of each market sample along each of the axes in 3-D graphs. These findings demonstrate the utility of quantitative descriptive analysis for identifying and measuring attributes of cham-cham that contribute most to its sensory acceptability.

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate the feasibility and power of the proposed DCA-based profile biomarker diagnosis in achieving high sensitivity and conquering the data reproducibility issue in serum proteomics. Furthermore, our proposed derivative component analysis suggests the subtle data characteristics gleaning and de-noising are essential in separating true signals from red herrings for high-dimensional proteomic profiles, which can be more important than the conventional feature selection or dimension reduction. In particular, our profile biomarker diagnosis can be generalized to other omics data for derivative component analysis (DCA)'s nature of generic data analysis.

Structure and content components of self-management interventions that improve health-related quality of life in people with inflammatory bowel disease: a systematic review, meta-analysis and meta-regression.

PubMed

Tu, Wenjing; Xu, Guihua; Du, Shizheng

2015-10-01

The purpose of this review was to identify and categorise the components of the content and structure of effective self-management interventions for patients with inflammatory bowel disease. Inflammatory bowel diseases are chronic gastrointestinal disorders impacting health-related quality of life. Although the efficacy of self-management interventions has been demonstrated in previous studies, the most effective components of the content and structure of these interventions remain unknown. A systematic review, meta-analysis and meta-regression of randomised controlled trials was used. A systematic search of six electronic databases, including Pubmed, Embase, Cochrane central register of controlled trials, Web of Science, Cumulative Index of Nursing and Allied Health Literature and Chinese Biomedical Literature Database, was conducted. Content analysis was used to categorise the components of the content and structure of effective self-management interventions for inflammatory bowel disease. Clinically important and statistically significant beneficial effects on health-related quality of life were explored, by comparing the association between effect sizes and various components of self-management interventions such as the presence or absence of specific content and different delivery methods. Fifteen randomised controlled trials were included in this review. Distance or remote self-management interventions demonstrated a larger effect size. However, there is no evidence for a positive effect associated with specific content component of self-management interventions in adult patients with inflammatory bowel disease in general. The results showed that self-management interventions have positive effects on health-related quality of life in patients with inflammatory bowel disease, and distance or remote self-management programmes had better outcomes than other types of interventions. This review provides useful information to clinician and researchers when determining components of effective self-management programmes for patients with inflammatory bowel disease. More high-quality randomised controlled trials are needed to test the results. © 2015 John Wiley & Sons Ltd.

6C polarization analysis - seismic direction finding in coherent noise, automated event identification, and wavefield separation

NASA Astrophysics Data System (ADS)

Schmelzbach, C.; Sollberger, D.; Greenhalgh, S.; Van Renterghem, C.; Robertsson, J. O. A.

2017-12-01

Polarization analysis of standard three-component (3C) seismic data is an established tool to determine the propagation directions of seismic waves recorded by a single station. A major limitation of seismic direction finding methods using 3C recordings, however, is that a correct propagation-direction determination is only possible if the wave mode is known. Furthermore, 3C polarization analysis techniques break down in the presence of coherent noise (i.e., when more than one event is present in the analysis time window). Recent advances in sensor technology (e.g., fibre-optical, magnetohydrodynamic angular rate sensors, and ring laser gyroscopes) have made it possible to accurately measure all three components of rotational ground motion exhibited by seismic waves, in addition to the conventionally recorded three components of translational motion. Here, we present an extension of the theory of single station 3C polarization analysis to six-component (6C) recordings of collocated translational and rotational ground motions. We demonstrate that the information contained in rotation measurements can help to overcome some of the main limitations of standard 3C seismic direction finding, such as handling multiple arrivals simultaneously. We show that the 6C polarisation of elastic waves measured at the Earth's free surface does not only depend on the seismic wave type and propagation direction, but also on the local P- and S-wave velocities just beneath the recording station. Using an adaptation of the multiple signal classification algorithm (MUSIC), we demonstrate how seismic events can univocally be identified and characterized in terms of their wave type. Furthermore, we show how the local velocities can be inferred from single-station 6C data, in addition to the direction angles (inclination and azimuth) of seismic arrivals. A major benefit of our proposed 6C method is that it also allows the accurate recovery of the wave type, propagation directions, and phase velocities of multiple, interfering arrivals in one time window. We demonstrate how this property can be exploited to separate the wavefield into its elastic wave-modes and to isolate or suppress waves arriving from specific directions (directional filtering), both in a fully automated fashion.

Comprehensive investigation into historical pipeline construction costs and engineering economic analysis of Alaska in-state gas pipeline

NASA Astrophysics Data System (ADS)

Rui, Zhenhua

This study analyzes historical cost data of 412 pipelines and 220 compressor stations. On the basis of this analysis, the study also evaluates the feasibility of an Alaska in-state gas pipeline using Monte Carlo simulation techniques. Analysis of pipeline construction costs shows that component costs, shares of cost components, and learning rates for material and labor costs vary by diameter, length, volume, year, and location. Overall average learning rates for pipeline material and labor costs are 6.1% and 12.4%, respectively. Overall average cost shares for pipeline material, labor, miscellaneous, and right of way (ROW) are 31%, 40%, 23%, and 7%, respectively. Regression models are developed to estimate pipeline component costs for different lengths, cross-sectional areas, and locations. An analysis of inaccuracy in pipeline cost estimation demonstrates that the cost estimation of pipeline cost components is biased except for in the case of total costs. Overall overrun rates for pipeline material, labor, miscellaneous, ROW, and total costs are 4.9%, 22.4%, -0.9%, 9.1%, and 6.5%, respectively, and project size, capacity, diameter, location, and year of completion have different degrees of impacts on cost overruns of pipeline cost components. Analysis of compressor station costs shows that component costs, shares of cost components, and learning rates for material and labor costs vary in terms of capacity, year, and location. Average learning rates for compressor station material and labor costs are 12.1% and 7.48%, respectively. Overall average cost shares of material, labor, miscellaneous, and ROW are 50.6%, 27.2%, 21.5%, and 0.8%, respectively. Regression models are developed to estimate compressor station component costs in different capacities and locations. An investigation into inaccuracies in compressor station cost estimation demonstrates that the cost estimation for compressor stations is biased except for in the case of material costs. Overall average overrun rates for compressor station material, labor, miscellaneous, land, and total costs are 3%, 60%, 2%, -14%, and 11%, respectively, and cost overruns for cost components are influenced by location and year of completion to different degrees. Monte Carlo models are developed and simulated to evaluate the feasibility of an Alaska in-state gas pipeline by assigning triangular distribution of the values of economic parameters. Simulated results show that the construction of an Alaska in-state natural gas pipeline is feasible at three scenarios: 500 million cubic feet per day (mmcfd), 750 mmcfd, and 1000 mmcfd.

Fast grasping of unknown objects using principal component analysis

NASA Astrophysics Data System (ADS)

Lei, Qujiang; Chen, Guangming; Wisse, Martijn

2017-09-01

Fast grasping of unknown objects has crucial impact on the efficiency of robot manipulation especially subjected to unfamiliar environments. In order to accelerate grasping speed of unknown objects, principal component analysis is utilized to direct the grasping process. In particular, a single-view partial point cloud is constructed and grasp candidates are allocated along the principal axis. Force balance optimization is employed to analyze possible graspable areas. The obtained graspable area with the minimal resultant force is the best zone for the final grasping execution. It is shown that an unknown object can be more quickly grasped provided that the component analysis principle axis is determined using single-view partial point cloud. To cope with the grasp uncertainty, robot motion is assisted to obtain a new viewpoint. Virtual exploration and experimental tests are carried out to verify this fast gasping algorithm. Both simulation and experimental tests demonstrated excellent performances based on the results of grasping a series of unknown objects. To minimize the grasping uncertainty, the merits of the robot hardware with two 3D cameras can be utilized to suffice the partial point cloud. As a result of utilizing the robot hardware, the grasping reliance is highly enhanced. Therefore, this research demonstrates practical significance for increasing grasping speed and thus increasing robot efficiency under unpredictable environments.

Usage of Parameterized Fatigue Spectra and Physics-Based Systems Engineering Models for Wind Turbine Component Sizing: Preprint

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

Parsons, Taylor; Guo, Yi; Veers, Paul

Software models that use design-level input variables and physics-based engineering analysis for estimating the mass and geometrical properties of components in large-scale machinery can be very useful for analyzing design trade-offs in complex systems. This study uses DriveSE, an OpenMDAO-based drivetrain model that uses stress and deflection criteria to size drivetrain components within a geared, upwind wind turbine. Because a full lifetime fatigue load spectrum can only be defined using computationally-expensive simulations in programs such as FAST, a parameterized fatigue loads spectrum that depends on wind conditions, rotor diameter, and turbine design life has been implemented. The parameterized fatigue spectrummore » is only used in this paper to demonstrate the proposed fatigue analysis approach. This paper details a three-part investigation of the parameterized approach and a comparison of the DriveSE model with and without fatigue analysis on the main shaft system. It compares loads from three turbines of varying size and determines if and when fatigue governs drivetrain sizing compared to extreme load-driven design. It also investigates the model's sensitivity to shaft material parameters. The intent of this paper is to demonstrate how fatigue considerations in addition to extreme loads can be brought into a system engineering optimization.« less

Radar fall detection using principal component analysis

NASA Astrophysics Data System (ADS)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Principal component analysis as a tool for library design: a case study investigating natural products, brand-name drugs, natural product-like libraries, and drug-like libraries.

PubMed

Wenderski, Todd A; Stratton, Christopher F; Bauer, Renato A; Kopp, Felix; Tan, Derek S

2015-01-01

Principal component analysis (PCA) is a useful tool in the design and planning of chemical libraries. PCA can be used to reveal differences in structural and physicochemical parameters between various classes of compounds by displaying them in a convenient graphical format. Herein, we demonstrate the use of PCA to gain insight into structural features that differentiate natural products, synthetic drugs, natural product-like libraries, and drug-like libraries, and show how the results can be used to guide library design.

Principal component analysis of bacteria using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Guicheteau, Jason; Christesen, Steven D.

2006-05-01

Surface-enhanced Raman scattering (SERS) provides rapid fingerprinting of biomaterial in a non-destructive manner. The problem of tissue fluorescence, which can overwhelm a normal Raman signal from biological samples, is largely overcome by treatment of biomaterials with colloidal silver. This work presents a study into the applicability of qualitative SER spectroscopy with principal component analysis (PCA) for the discrimination of four biological threat simulants; Bacillus globigii, Pantoea agglomerans, Brucella noetomae, and Yersinia rohdei. We also demonstrate differentiation of gram-negative and gram-positive species and as well as spores and vegetative cells of Bacillus globigii.

Principal Component Analysis as a Tool for Library Design: A Case Study Investigating Natural Products, Brand-Name Drugs, Natural Product-Like Libraries, and Drug-Like Libraries

PubMed Central

Wenderski, Todd A.; Stratton, Christopher F.; Bauer, Renato A.; Kopp, Felix; Tan, Derek S.

2015-01-01

Principal component analysis (PCA) is a useful tool in the design and planning of chemical libraries. PCA can be used to reveal differences in structural and physicochemical parameters between various classes of compounds by displaying them in a convenient graphical format. Herein, we demonstrate the use of PCA to gain insight into structural features that differentiate natural products, synthetic drugs, natural product-like libraries, and drug-like libraries, and show how the results can be used to guide library design. PMID:25618349

Psychometric properties of the Interpersonal Relationship Inventory-Short Form for active duty female service members.

PubMed

Nayback-Beebe, Ann M; Yoder, Linda H

2011-06-01

The Interpersonal Relationship Inventory-Short Form (IPRI-SF) has demonstrated psychometric consistency across several demographic and clinical populations; however, it has not been psychometrically tested in a military population. The purpose of this study was to psychometrically evaluate the reliability and component structure of the IPRI-SF in active duty United States Army female service members (FSMs). The reliability estimates were .93 for the social support subscale and .91 for the conflict subscale. Principal component analysis demonstrated an obliquely rotated three-component solution that accounted for 58.9% of the variance. The results of this study support the reliability and validity of the IPRI-SF for use in FSMs; however, a three-factor structure emerged in this sample of FSMs post-deployment that represents "cultural context." Copyright © 2011 Wiley Periodicals, Inc.

A practically unconditionally gradient stable scheme for the N-component Cahn-Hilliard system

NASA Astrophysics Data System (ADS)

Lee, Hyun Geun; Choi, Jeong-Whan; Kim, Junseok

2012-02-01

We present a practically unconditionally gradient stable conservative nonlinear numerical scheme for the N-component Cahn-Hilliard system modeling the phase separation of an N-component mixture. The scheme is based on a nonlinear splitting method and is solved by an efficient and accurate nonlinear multigrid method. The scheme allows us to convert the N-component Cahn-Hilliard system into a system of N-1 binary Cahn-Hilliard equations and significantly reduces the required computer memory and CPU time. We observe that our numerical solutions are consistent with the linear stability analysis results. We also demonstrate the efficiency of the proposed scheme with various numerical experiments.

Conversion of Component-Based Point Definition to VSP Model and Higher Order Meshing

NASA Technical Reports Server (NTRS)

Ordaz, Irian

2011-01-01

Vehicle Sketch Pad (VSP) has become a powerful conceptual and parametric geometry tool with numerous export capabilities for third-party analysis codes as well as robust surface meshing capabilities for computational fluid dynamics (CFD) analysis. However, a capability gap currently exists for reconstructing a fully parametric VSP model of a geometry generated by third-party software. A computer code called GEO2VSP has been developed to close this gap and to allow the integration of VSP into a closed-loop geometry design process with other third-party design tools. Furthermore, the automated CFD surface meshing capability of VSP are demonstrated for component-based point definition geometries in a conceptual analysis and design framework.

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.

[Spatial distribution characteristics of the physical and chemical properties of water in the Kunes River after the supply of snowmelt during spring].

PubMed

Liu, Xiang; Guo, Ling-Peng; Zhang, Fei-Yun; Ma, Jie; Mu, Shu-Yong; Zhao, Xin; Li, Lan-Hai

2015-02-01

Eight physical and chemical indicators related to water quality were monitored from nineteen sampling sites along the Kunes River at the end of snowmelt season in spring. To investigate the spatial distribution characteristics of water physical and chemical properties, cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA) are employed. The result of cluster analysis showed that the Kunes River could be divided into three reaches according to the similarities of water physical and chemical properties among sampling sites, representing the upstream, midstream and downstream of the river, respectively; The result of discriminant analysis demonstrated that the reliability of such a classification was high, and DO, Cl- and BOD5 were the significant indexes leading to this classification; Three principal components were extracted on the basis of the principal component analysis, in which accumulative variance contribution could reach 86.90%. The result of principal component analysis also indicated that water physical and chemical properties were mostly affected by EC, ORP, NO3(-) -N, NH4(+) -N, Cl- and BOD5. The sorted results of principal component scores in each sampling sites showed that the water quality was mainly influenced by DO in upstream, by pH in midstream, and by the rest of indicators in downstream. The order of comprehensive scores for principal components revealed that the water quality degraded from the upstream to downstream, i.e., the upstream had the best water quality, followed by the midstream, while the water quality at downstream was the worst. This result corresponded exactly to the three reaches classified using cluster analysis. Anthropogenic activity and the accumulation of pollutants along the river were probably the main reasons leading to this spatial difference.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

NASA Astrophysics Data System (ADS)

Tsouri, Gill R.; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K.

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

PubMed

Tsouri, Gill R; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Revealing the ultrafast outflow in IRAS 13224-3809 through spectral variability

NASA Astrophysics Data System (ADS)

Parker, M. L.; Alston, W. N.; Buisson, D. J. K.; Fabian, A. C.; Jiang, J.; Kara, E.; Lohfink, A.; Pinto, C.; Reynolds, C. S.

2017-08-01

We present an analysis of the long-term X-ray variability of the extreme narrow-line Seyfert 1 galaxy IRAS 13224-3809 using principal component analysis (PCA) and fractional excess variability (Fvar) spectra to identify model-independent spectral components. We identify a series of variability peaks in both the first PCA component and Fvar spectrum which correspond to the strongest predicted absorption lines from the ultrafast outflow (UFO) discovered by Parker et al. (2017). We also find higher order PCA components, which correspond to variability of the soft excess and reflection features. The subtle differences between RMS and PCA results argue that the observed flux-dependence of the absorption is due to increased ionization of the gas, rather than changes in column density or covering fraction. This result demonstrates that we can detect outflows from variability alone and that variability studies of UFOs are an extremely promising avenue for future research.

Components of Effective Cognitive-Behavioral Therapy for Pediatric Headache: A Mixed Methods Approach

PubMed Central

Law, Emily F.; Beals-Erickson, Sarah E.; Fisher, Emma; Lang, Emily A.; Palermo, Tonya M.

2017-01-01

Internet-delivered treatment has the potential to expand access to evidence-based cognitive-behavioral therapy (CBT) for pediatric headache, and has demonstrated efficacy in small trials for some youth with headache. We used a mixed methods approach to identify effective components of CBT for this population. In Study 1, component profile analysis identified common interventions delivered in published RCTs of effective CBT protocols for pediatric headache delivered face-to-face or via the Internet. We identified a core set of three treatment components that were common across face-to-face and Internet protocols: 1) headache education, 2) relaxation training, and 3) cognitive interventions. Biofeedback was identified as an additional core treatment component delivered in face-to-face protocols only. In Study 2, we conducted qualitative interviews to describe the perspectives of youth with headache and their parents on successful components of an Internet CBT intervention. Eleven themes emerged from the qualitative data analysis, which broadly focused on patient experiences using the treatment components and suggestions for new treatment components. In the Discussion, these mixed methods findings are integrated to inform the adaptation of an Internet CBT protocol for youth with headache. PMID:29503787

Components of Effective Cognitive-Behavioral Therapy for Pediatric Headache: A Mixed Methods Approach.

PubMed

Law, Emily F; Beals-Erickson, Sarah E; Fisher, Emma; Lang, Emily A; Palermo, Tonya M

2017-01-01

Internet-delivered treatment has the potential to expand access to evidence-based cognitive-behavioral therapy (CBT) for pediatric headache, and has demonstrated efficacy in small trials for some youth with headache. We used a mixed methods approach to identify effective components of CBT for this population. In Study 1, component profile analysis identified common interventions delivered in published RCTs of effective CBT protocols for pediatric headache delivered face-to-face or via the Internet. We identified a core set of three treatment components that were common across face-to-face and Internet protocols: 1) headache education, 2) relaxation training, and 3) cognitive interventions. Biofeedback was identified as an additional core treatment component delivered in face-to-face protocols only. In Study 2, we conducted qualitative interviews to describe the perspectives of youth with headache and their parents on successful components of an Internet CBT intervention. Eleven themes emerged from the qualitative data analysis, which broadly focused on patient experiences using the treatment components and suggestions for new treatment components. In the Discussion, these mixed methods findings are integrated to inform the adaptation of an Internet CBT protocol for youth with headache.

Simultaneous quantitation of 14 active components in Yinchenhao decoction by using ultra high performance liquid chromatography with diode array detection: Method development and ingredient analysis of different commonly prepared samples.

PubMed

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

2016-11-01

We developed a novel quantitative analysis method based on ultra high performance liquid chromatography coupled with diode array detection for the simultaneous determination of the 14 main active components in Yinchenhao decoction. All components were separated on an Agilent SB-C18 column by using a gradient solvent system of acetonitrile/0.1% phosphoric acid solution at a flow rate of 0.4 mL/min for 35 min. Subsequently, linearity, precision, repeatability, and accuracy tests were implemented to validate the method. Furthermore, the method has been applied for compositional difference analysis of 14 components in eight normal-extraction Yinchenhao decoction samples, accompanied by hierarchical clustering analysis and similarity analysis. The result that all samples were divided into three groups based on different contents of components demonstrated that extraction methods of decocting, refluxing, ultrasonication and extraction solvents of water or ethanol affected component differentiation, and should be related to its clinical applications. The results also indicated that the sample prepared by patients in the family by using water extraction employing a casserole was almost same to that prepared using a stainless-steel kettle, which is mostly used in pharmaceutical factories. This research would help patients to select the best and most convenient method for preparing Yinchenhao decoction. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enantiomer-specific analysis of multi-component mixtures by correlated electron imaging-ion mass spectrometry

NASA Astrophysics Data System (ADS)

Fanood, Mohammad M. Rafiee; Ram, N. Bhargava; Lehmann, C. Stefan; Powis, Ivan; Janssen, Maurice H. M.

2015-06-01

Simultaneous, enantiomer-specific identification of chiral molecules in multi-component mixtures is extremely challenging. Many established techniques for single-component analysis fail to provide selectivity in multi-component mixtures and lack sensitivity for dilute samples. Here we show how enantiomers may be differentiated by mass-selected photoelectron circular dichroism using an electron-ion coincidence imaging spectrometer. As proof of concept, vapours containing ~1% of two chiral monoterpene molecules, limonene and camphor, are irradiated by a circularly polarized femtosecond laser, resulting in multiphoton near-threshold ionization with little molecular fragmentation. Large chiral asymmetries (2-4%) are observed in the mass-tagged photoelectron angular distributions. These asymmetries switch sign according to the handedness (R- or S-) of the enantiomer in the mixture and scale with enantiomeric excess of a component. The results demonstrate that mass spectrometric identification of mixtures of chiral molecules and quantitative determination of enantiomeric excess can be achieved in a table-top instrument.

Enantiomer-specific analysis of multi-component mixtures by correlated electron imaging–ion mass spectrometry

PubMed Central

Fanood, Mohammad M Rafiee; Ram, N. Bhargava; Lehmann, C. Stefan; Powis, Ivan; Janssen, Maurice H. M.

2015-01-01

Simultaneous, enantiomer-specific identification of chiral molecules in multi-component mixtures is extremely challenging. Many established techniques for single-component analysis fail to provide selectivity in multi-component mixtures and lack sensitivity for dilute samples. Here we show how enantiomers may be differentiated by mass-selected photoelectron circular dichroism using an electron–ion coincidence imaging spectrometer. As proof of concept, vapours containing ∼1% of two chiral monoterpene molecules, limonene and camphor, are irradiated by a circularly polarized femtosecond laser, resulting in multiphoton near-threshold ionization with little molecular fragmentation. Large chiral asymmetries (2–4%) are observed in the mass-tagged photoelectron angular distributions. These asymmetries switch sign according to the handedness (R- or S-) of the enantiomer in the mixture and scale with enantiomeric excess of a component. The results demonstrate that mass spectrometric identification of mixtures of chiral molecules and quantitative determination of enantiomeric excess can be achieved in a table-top instrument. PMID:26104140

Group-level self-definition and self-investment: a hierarchical (multicomponent) model of in-group identification.

PubMed

Leach, Colin Wayne; van Zomeren, Martijn; Zebel, Sven; Vliek, Michael L W; Pennekamp, Sjoerd F; Doosje, Bertjan; Ouwerkerk, Jaap W; Spears, Russell

2008-07-01

Recent research shows individuals' identification with in-groups to be psychologically important and socially consequential. However, there is little agreement about how identification should be conceptualized or measured. On the basis of previous work, the authors identified 5 specific components of in-group identification and offered a hierarchical 2-dimensional model within which these components are organized. Studies 1 and 2 used confirmatory factor analysis to validate the proposed model of self-definition (individual self-stereotyping, in-group homogeneity) and self-investment (solidarity, satisfaction, and centrality) dimensions, across 3 different group identities. Studies 3 and 4 demonstrated the construct validity of the 5 components by examining their (concurrent) correlations with established measures of in-group identification. Studies 5-7 demonstrated the predictive and discriminant validity of the 5 components by examining their (prospective) prediction of individuals' orientation to, and emotions about, real intergroup relations. Together, these studies illustrate the conceptual and empirical value of a hierarchical multicomponent model of in-group identification.

Three-Dimensional Modeling of Aircraft High-Lift Components with Vehicle Sketch Pad

NASA Technical Reports Server (NTRS)

Olson, Erik D.

2016-01-01

Vehicle Sketch Pad (OpenVSP) is a parametric geometry modeler that has been used extensively for conceptual design studies of aircraft, including studies using higher-order analysis. OpenVSP can model flap and slat surfaces using simple shearing of the airfoil coordinates, which is an appropriate level of complexity for lower-order aerodynamic analysis methods. For three-dimensional analysis, however, there is not a built-in method for defining the high-lift components in OpenVSP in a realistic manner, or for controlling their complex motions in a parametric manner that is intuitive to the designer. This paper seeks instead to utilize OpenVSP's existing capabilities, and establish a set of best practices for modeling high-lift components at a level of complexity suitable for higher-order analysis methods. Techniques are described for modeling the flap and slat components as separate three-dimensional surfaces, and for controlling their motion using simple parameters defined in the local hinge-axis frame of reference. To demonstrate the methodology, an OpenVSP model for the Energy-Efficient Transport (EET) AR12 wind-tunnel model has been created, taking advantage of OpenVSP's Advanced Parameter Linking capability to translate the motions of the high-lift components from the hinge-axis coordinate system to a set of transformations in OpenVSP's frame of reference.

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.

Evaluation on the concentration change of paeoniflorin and glycyrrhizic acid in different formulations of Shaoyao-Gancao-Tang by the tri-level infrared macro-fingerprint spectroscopy and the whole analysis method

NASA Astrophysics Data System (ADS)

Liu, Aoxue; Wang, Jingjuan; Guo, Yizhen; Xiao, Yao; Wang, Yue; Sun, Suqin; Chen, Jianbo

2018-03-01

As a kind of common prescriptions, Shaoyao-Gancao-Tang (SGT) contains two Chinese herbs with four different proportions which have different clinical efficacy because of their various components. In order to investigate the herb-herb interaction mechanisms, we used the method of tri-level infrared macro-fingerprint spectroscopy to evaluate the concentration change of active components of four SGTs in this research. Fourier transform infrared spectroscopy (FT-IR) and Second derivative infrared spectroscopy (SD-IR) can recognize the multiple prescriptions directly and simultaneously. 2D-IR spectra enhance the spectral resolution and obtain much new information for discriminating the similar complicated samples of SGT. Furthermore, the whole analysis method from the analysis of the main components to the specific components and the relative content of the components may evaluate the quality of TCM better. Then we concluded that paeoniflorin and glycyrrhizic acid were the highest proportion in active ingredients in SGT-12:1 and the lowest one in SGT-12:12, which matched the HPLC-DAD results. It is demonstrated that the method composed by the tri-level infrared macro-fingerprint spectroscopy and the whole analysis can be applicable for effective, visual and accurate analysis and identification of very complicated and similar mixture systems of traditional Chinese medicine.

The application of near infrared (NIR) spectroscopy to inorganic preservative-treated wood

Treesearch

Chi-Leung So; Stan T. Lebow; Leslie H. Groom; Timothy G. Rials

2004-01-01

There is a growing need to find a rapid, inexpensive, and reliable method to distinguish between treated and untreated waste wood. This paper evaluates the ability of near infrared (NIR) spectroscopy with multivariate analysis (MVA) to distinguish preservative types and retentions. It is demonstrated that principal component analysis (PCA) can differentiate lumber...

Integrable multi-component generalization of a modified short pulse equation

NASA Astrophysics Data System (ADS)

Matsuno, Yoshimasa

2016-11-01

We propose a multi-component generalization of the modified short pulse (SP) equation which was derived recently as a reduction of Feng's two-component SP equation. Above all, we address the two-component system in depth. We obtain the Lax pair, an infinite number of conservation laws and multisoliton solutions for the system, demonstrating its integrability. Subsequently, we show that the two-component system exhibits cusp solitons and breathers for which the detailed analysis is performed. Specifically, we explore the interaction process of two cusp solitons and derive the formula for the phase shift. While cusp solitons are singular solutions, smooth breather solutions are shown to exist, provided that the parameters characterizing the solutions satisfy certain conditions. Last, we discuss the relation between the proposed system and existing two-component SP equations.

Technology verification phase. Dynamic isotope power system. Final report

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

Halsey, D.G.

1982-03-10

The Phase I requirements of the Kilowatt Isotope Power System (KIPS) program were to make a detailed Flight System Conceptual Design (FSCD) for an isotope fueled organic Rankine cycle power system and to build and test a Ground Demonstration System (GDS) which simulated as closely as possible the operational characteristics of the FSCD. The activities and results of Phase II, the Technology Verification Phase, of the program are reported. The objectives of this phase were to increase system efficiency to 18.1% by component development, to demonstrate system reliability by a 5000 h endurance test and to update the flight systemmore » design. During Phase II, system performance was improved from 15.1% to 16.6%, an endurance test of 2000 h was performed while the flight design analysis was limited to a study of the General Purpose Heat Source, a study of the regenerator manufacturing technique and analysis of the hardness of the system to a laser threat. It was concluded from these tests that the GDS is basically prototypic of a flight design; all components necessary for satisfactory operation were demonstrated successfully at the system level; over 11,000 total h of operation without any component failure attested to the inherent reliability of this type of system; and some further development is required, specifically in the area of performance. (LCL)« less

Time-dependent reliability analysis of ceramic engine components

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

1993-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing either the power or Paris law relations. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating proof testing and fatigue parameter estimation are given.

Neuroforecasting Aggregate Choice

PubMed Central

Knutson, Brian; Genevsky, Alexander

2018-01-01

Advances in brain-imaging design and analysis have allowed investigators to use neural activity to predict individual choice, while emerging Internet markets have opened up new opportunities for forecasting aggregate choice. Here, we review emerging research that bridges these levels of analysis by attempting to use group neural activity to forecast aggregate choice. A survey of initial findings suggests that components of group neural activity might forecast aggregate choice, in some cases even beyond traditional behavioral measures. In addition to demonstrating the plausibility of neuroforecasting, these findings raise the possibility that not all neural processes that predict individual choice forecast aggregate choice to the same degree. We propose that although integrative choice components may confer more consistency within individuals, affective choice components may generalize more broadly across individuals to forecast aggregate choice. PMID:29706726

Cognitive components of self esteem for individuals with severe mental illness.

PubMed

Blankertz, L

2001-10-01

In a sample of 182 individuals with severe mental illness, the applicability of reflected appraisals and self-enhancement theories as explanations for global self-esteem was examined at two time points on components of stigma, mastery, overall functioning, education, and job prestige. Path analysis demonstrated that the two theories work independently; and that stigma, mastery, and overall functioning are significant, persist over time, and have an enduring effect on self-esteem.

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

A Convective Vorticity Vector Associated With Tropical Convection: A 2D Cloud-Resolving Modeling Study

NASA Technical Reports Server (NTRS)

Gao, Shou-Ting; Ping, Fan; Li, Xiao-Fan; Tao, Wei-Kuo

2004-01-01

Although dry/moist potential vorticity is a useful physical quantity for meteorological analysis, it cannot be applied to the analysis of 2D simulations. A convective vorticity vector (CVV) is introduced in this study to analyze 2D cloud-resolving simulation data associated with 2D tropical convection. The cloud model is forced by the vertical velocity, zonal wind, horizontal advection, and sea surface temperature obtained from the TOGA COARE, and is integrated for a selected 10-day period. The CVV has zonal and vertical components in the 2D x-z frame. Analysis of zonally-averaged and mass-integrated quantities shows that the correlation coefficient between the vertical component of the CVV and the sum of the cloud hydrometeor mixing ratios is 0.81, whereas the correlation coefficient between the zonal component and the sum of the mixing ratios is only 0.18. This indicates that the vertical component of the CVV is closely associated with tropical convection. The tendency equation for the vertical component of the CVV is derived and the zonally-averaged and mass-integrated tendency budgets are analyzed. The tendency of the vertical component of the CVV is determined by the interaction between the vorticity and the zonal gradient of cloud heating. The results demonstrate that the vertical component of the CVV is a cloud-linked parameter and can be used to study tropical convection.

Determining the optimal number of independent components for reproducible transcriptomic data analysis.

PubMed

Kairov, Ulykbek; Cantini, Laura; Greco, Alessandro; Molkenov, Askhat; Czerwinska, Urszula; Barillot, Emmanuel; Zinovyev, Andrei

2017-09-11

Independent Component Analysis (ICA) is a method that models gene expression data as an action of a set of statistically independent hidden factors. The output of ICA depends on a fundamental parameter: the number of components (factors) to compute. The optimal choice of this parameter, related to determining the effective data dimension, remains an open question in the application of blind source separation techniques to transcriptomic data. Here we address the question of optimizing the number of statistically independent components in the analysis of transcriptomic data for reproducibility of the components in multiple runs of ICA (within the same or within varying effective dimensions) and in multiple independent datasets. To this end, we introduce ranking of independent components based on their stability in multiple ICA computation runs and define a distinguished number of components (Most Stable Transcriptome Dimension, MSTD) corresponding to the point of the qualitative change of the stability profile. Based on a large body of data, we demonstrate that a sufficient number of dimensions is required for biological interpretability of the ICA decomposition and that the most stable components with ranks below MSTD have more chances to be reproduced in independent studies compared to the less stable ones. At the same time, we show that a transcriptomics dataset can be reduced to a relatively high number of dimensions without losing the interpretability of ICA, even though higher dimensions give rise to components driven by small gene sets. We suggest a protocol of ICA application to transcriptomics data with a possibility of prioritizing components with respect to their reproducibility that strengthens the biological interpretation. Computing too few components (much less than MSTD) is not optimal for interpretability of the results. The components ranked within MSTD range have more chances to be reproduced in independent studies.

An inexpensive economical solar heating system for homes

NASA Technical Reports Server (NTRS)

Allred, J. W.; Shinn, J. M., Jr.; Kirby, C. E.; Barringer, S. R.

1976-01-01

A low-cost solar home heating system to supplement existing warm-air heating systems is described. The report is written in three parts: (1) a brief background on solar heating, (2) experience with a demonstration system, and (3) information for the homeowner who wishes to construct such a system. Instructions are given for a solar heating installation in which the homeowner supplies all labor necessary to install off-the-shelf components estimated to cost $2,000. These components, which include solar collector, heat exchanger, water pump, storage tank, piping, and controls to make the system completely automatic, are available at local lumber yards, hardware stores, and plumbing supply stores, and are relatively simple to install. Manufacturers and prices of each component used and a rough cost analysis based on these prices are included. This report also gives performance data obtained from a demonstration system which was built and tested at the Langley Research Center.

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Keller, Jonathan A.; Wade, Daniel R.

2008-01-01

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Signal Detection Theory Applied to Helicopter Transmission Diagnostic Thresholds

NASA Technical Reports Server (NTRS)

Dempsey, Paula J.; Keller, Jonathan A.; Wade, Daniel R.

2009-01-01

Helicopter Health Usage Monitoring Systems (HUMS) have potential for providing data to support increasing the service life of a dynamic mechanical component in the transmission of a helicopter. Data collected can demonstrate the HUMS condition indicator responds to a specific component fault with appropriate alert limits and minimal false alarms. Defining thresholds for specific faults requires a tradeoff between the sensitivity of the condition indicator (CI) limit to indicate damage and the number of false alarms. A method using Receiver Operating Characteristic (ROC) curves to assess CI performance was demonstrated using CI data collected from accelerometers installed on several UH60 Black Hawk and AH64 Apache helicopters and an AH64 helicopter component test stand. Results of the analysis indicate ROC curves can be used to reliably assess the performance of commercial HUMS condition indicators to detect damaged gears and bearings in a helicopter transmission.

Novel entries in a fungal biofilm matrix encyclopedia.

PubMed

Zarnowski, Robert; Westler, William M; Lacmbouh, Ghislain Ade; Marita, Jane M; Bothe, Jameson R; Bernhardt, Jörg; Lounes-Hadj Sahraoui, Anissa; Fontaine, Joël; Sanchez, Hiram; Hatfield, Ronald D; Ntambi, James M; Nett, Jeniel E; Mitchell, Aaron P; Andes, David R

2014-08-05

Virulence of Candida is linked with its ability to form biofilms. Once established, biofilm infections are nearly impossible to eradicate. Biofilm cells live immersed in a self-produced matrix, a blend of extracellular biopolymers, many of which are uncharacterized. In this study, we provide a comprehensive analysis of the matrix manufactured by Candida albicans both in vitro and in a clinical niche animal model. We further explore the function of matrix components, including the impact on drug resistance. We uncovered components from each of the macromolecular classes (55% protein, 25% carbohydrate, 15% lipid, and 5% nucleic acid) in the C. albicans biofilm matrix. Three individual polysaccharides were identified and were suggested to interact physically. Surprisingly, a previously identified polysaccharide of functional importance, β-1,3-glucan, comprised only a small portion of the total matrix carbohydrate. Newly described, more abundant polysaccharides included α-1,2 branched α-1,6-mannans (87%) associated with unbranched β-1,6-glucans (13%) in an apparent mannan-glucan complex (MGCx). Functional matrix proteomic analysis revealed 458 distinct activities. The matrix lipids consisted of neutral glycerolipids (89.1%), polar glycerolipids (10.4%), and sphingolipids (0.5%). Examination of matrix nucleic acid identified DNA, primarily noncoding sequences. Several of the in vitro matrix components, including proteins and each of the polysaccharides, were also present in the matrix of a clinically relevant in vivo biofilm. Nuclear magnetic resonance (NMR) analysis demonstrated interaction of aggregate matrix with the antifungal fluconazole, consistent with a role in drug impedance and contribution of multiple matrix components. Importance: This report is the first to decipher the complex and unique macromolecular composition of the Candida biofilm matrix, demonstrate the clinical relevance of matrix components, and show that multiple matrix components are needed for protection from antifungal drugs. The availability of these biochemical analyses provides a unique resource for further functional investigation of the biofilm matrix, a defining trait of this lifestyle. Copyright © 2014 Zarnowski et al.

Crack Detection with Lamb Wave Wavenumber Analysis

NASA Technical Reports Server (NTRS)

Tian, Zhenhua; Leckey, Cara; Rogge, Matt; Yu, Lingyu

2013-01-01

In this work, we present our study of Lamb wave crack detection using wavenumber analysis. The aim is to demonstrate the application of wavenumber analysis to 3D Lamb wave data to enable damage detection. The 3D wavefields (including vx, vy and vz components) in time-space domain contain a wealth of information regarding the propagating waves in a damaged plate. For crack detection, three wavenumber analysis techniques are used: (i) two dimensional Fourier transform (2D-FT) which can transform the time-space wavefield into frequency-wavenumber representation while losing the spatial information; (ii) short space 2D-FT which can obtain the frequency-wavenumber spectra at various spatial locations, resulting in a space-frequency-wavenumber representation; (iii) local wavenumber analysis which can provide the distribution of the effective wavenumbers at different locations. All of these concepts are demonstrated through a numerical simulation example of an aluminum plate with a crack. The 3D elastodynamic finite integration technique (EFIT) was used to obtain the 3D wavefields, of which the vz (out-of-plane) wave component is compared with the experimental measurement obtained from a scanning laser Doppler vibrometer (SLDV) for verification purposes. The experimental and simulated results are found to be in close agreement. The application of wavenumber analysis on 3D EFIT simulation data shows the effectiveness of the analysis for crack detection. Keywords: : Lamb wave, crack detection, wavenumber analysis, EFIT modeling

Modeling the missile-launch tube problem in DYSCO

NASA Technical Reports Server (NTRS)

Berman, Alex; Gustavson, Bruce A.

1989-01-01

DYSCO is a versatile, general purpose dynamic analysis program which assembles equations and solves dynamics problems. The executive manages a library of technology modules which contain routines that compute the matrix coefficients of the second order ordinary differential equations of the components. The executive performs the coupling of the equations of the components and manages the solution of the coupled equations. Any new component representation may be added to the library if, given the state vector, a FORTRAN program can be written to compute M, C, K, and F. The problem described demonstrates the generality of this statement.

Investigation of domain walls in PPLN by confocal raman microscopy and PCA analysis

NASA Astrophysics Data System (ADS)

Shur, Vladimir Ya.; Zelenovskiy, Pavel; Bourson, Patrice

2017-07-01

Confocal Raman microscopy (CRM) is a powerful tool for investigation of ferroelectric domains. Mechanical stresses and electric fields existed in the vicinity of neutral and charged domain walls modify frequency, intensity and width of spectral lines [1], thus allowing to visualize micro- and nanodomain structures both at the surface and in the bulk of the crystal [2,3]. Stresses and fields are naturally coupled in ferroelectrics due to inverse piezoelectric effect and hardly can be separated in Raman spectra. PCA is a powerful statistical method for analysis of large data matrix providing a set of orthogonal variables, called principal components (PCs). PCA is widely used for classification of experimental data, for example, in crystallization experiments, for detection of small amounts of components in solid mixtures etc. [4,5]. In Raman spectroscopy PCA was applied for analysis of phase transitions and provided critical pressure with good accuracy [6]. In the present work we for the first time applied Principal Component Analysis (PCA) method for analysis of Raman spectra measured in periodically poled lithium niobate (PPLN). We found that principal components demonstrate different sensitivity to mechanical stresses and electric fields in the vicinity of the domain walls. This allowed us to separately visualize spatial distribution of fields and electric fields at the surface and in the bulk of PPLN.

Computational model for the analysis of cartilage and cartilage tissue constructs

PubMed Central

Smith, David W.; Gardiner, Bruce S.; Davidson, John B.; Grodzinsky, Alan J.

2013-01-01

We propose a new non-linear poroelastic model that is suited to the analysis of soft tissues. In this paper the model is tailored to the analysis of cartilage and the engineering design of cartilage constructs. The proposed continuum formulation of the governing equations enables the strain of the individual material components within the extracellular matrix (ECM) to be followed over time, as the individual material components are synthesized, assembled and incorporated within the ECM or lost through passive transport or degradation. The material component analysis developed here naturally captures the effect of time-dependent changes of ECM composition on the deformation and internal stress states of the ECM. For example, it is shown that increased synthesis of aggrecan by chondrocytes embedded within a decellularized cartilage matrix initially devoid of aggrecan results in osmotic expansion of the newly synthesized proteoglycan matrix and tension within the structural collagen network. Specifically, we predict that the collagen network experiences a tensile strain, with a maximum of ~2% at the fixed base of the cartilage. The analysis of an example problem demonstrates the temporal and spatial evolution of the stresses and strains in each component of a self-equilibrating composite tissue construct, and the role played by the flux of water through the tissue. PMID:23784936

Incorporating principal component analysis into air quality model evaluation

EPA Science Inventory

The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Princi...

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

Moulin, D.; Chapuliot, S.; Drubay, B.

For structures like vessels or pipes containing a fluid, the Leak-Before-Break (LBB) assessment requires to demonstrate that it is possible, during the lifetime of the component, to detect a rate of leakage due to a possible defect, the growth of which would result in a leak before-break of the component. This LBB assessment could be an important contribution to the overall structural integrity argument for many components. The aim of this paper is to review some practices used for LBB assessment and to describe how some new R & D results have been used to provide a simplified approach ofmore » fracture mechanics analysis and especially the evaluation of crack shape and size during the lifetime of the component.« less

Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis.

PubMed

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner; Sakaguchi, Jun; Olmos, Juan José Vegas; Awaji, Yoshinari; Monroy, Idelfonso Tafur; Wada, Naoya

2017-09-18

This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel photonic lantern spatial multiplexer, coupled to a 36-core 3-mode fiber, is experimentally demonstrated, extracting the full impulse response and complex transfer function matrices as well as insertion loss (IL) and mode-dependent loss (MDL) data. Moreover, the mode-mixing behavior of fiber splices in the few-mode multi-core fiber and their impact on system IL and MDL are analyzed, finding splices to cause significant mode-mixing and to be non-negligible in system capacity analysis.

Principal Component Analysis for pulse-shape discrimination of scintillation radiation detectors

NASA Astrophysics Data System (ADS)

Alharbi, T.

2016-01-01

In this paper, we report on the application of Principal Component analysis (PCA) for pulse-shape discrimination (PSD) of scintillation radiation detectors. The details of the method are described and the performance of the method is experimentally examined by discriminating between neutrons and gamma-rays with a liquid scintillation detector in a mixed radiation field. The performance of the method is also compared against that of the conventional charge-comparison method, demonstrating the superior performance of the method particularly at low light output range. PCA analysis has the important advantage of automatic extraction of the pulse-shape characteristics which makes the PSD method directly applicable to various scintillation detectors without the need for the adjustment of a PSD parameter.

Independent component analysis based channel equalization for 6 × 6 MIMO-OFDM transmission over few-mode fiber.

PubMed

He, Zhixue; Li, Xiang; Luo, Ming; Hu, Rong; Li, Cai; Qiu, Ying; Fu, Songnian; Yang, Qi; Yu, Shaohua

2016-05-02

We propose and experimentally demonstrate two independent component analysis (ICA) based channel equalizers (CEs) for 6 × 6 MIMO-OFDM transmission over few-mode fiber. Compared with the conventional channel equalizer based on training symbols (TSs-CE), the proposed two ICA-based channel equalizers (ICA-CE-I and ICA-CE-II) can achieve comparable performances, while requiring much less training symbols. Consequently, the overheads for channel equalization can be substantially reduced from 13.7% to 0.4% and 2.6%, respectively. Meanwhile, we also experimentally investigate the convergence speed of the proposed ICA-based CEs.

Genetic diversity analysis of fruit characteristics of hawthorn germplasm.

PubMed

Su, K; Guo, Y S; Wang, G; Zhao, Y H; Dong, W X

2015-12-07

One hundred and six accessions of hawthorn intraspecific resources, from the National Germplasm Repository at Shenyang, were subjected to genetic diversity and principal component analysis based on evaluation data of 15 fruit traits. Results showed that the genetic diversity of hawthorn fruit traits varied. Among the 15 traits, the fruit shape variable coefficient had the most obvious evaluation, followed by fruit surface state, dot color, taste, weight of single fruit, sepal posture, peduncle form, and metula traits. These are the primary traits by which hawthorn could be classified in the future. The principal component demonstrated that these traits are the most influential factors of hawthorn fruit characteristics.

Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra.

PubMed

Mantini, Dante; Petrucci, Francesca; Del Boccio, Piero; Pieragostino, Damiana; Di Nicola, Marta; Lugaresi, Alessandra; Federici, Giorgio; Sacchetta, Paolo; Di Ilio, Carmine; Urbani, Andrea

2008-01-01

Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra. The comparison on peak detection with an open-source and two commercial methods shows its superior reliability in reducing the false discovery rate of protein peak masses. Moreover, the integration of ICA and statistical tests for detecting the differences in peak intensities between experimental groups allows to identify protein peaks that could be indicators of a diseased state. This data-driven approach demonstrates to be a promising tool for biomarker-discovery studies based on MALDI-TOF MS technology. The MATLAB implementation of the method described in the article and both simulated and experimental data are freely available at http://www.unich.it/proteomica/bioinf/.

Construction and Validation of the Career and Educational Decision Self-Efficacy Inventory for Secondary Students (CEDSIS)

ERIC Educational Resources Information Center

Ho, Esther Sui Chu; Sum, Kwok Wing

2018-01-01

This study aims to construct and validate the Career and Educational Decision Self-Efficacy Inventory for Secondary Students (CEDSIS) by using a sample of 2,631 students in Hong Kong. Principal component analysis yielded a three-factor structure, which demonstrated good model fit in confirmatory factor analysis. High reliability was found for the…

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

DTIC Science & Technology

2015-12-01

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

Extended Testability Analysis Tool

NASA Technical Reports Server (NTRS)

Melcher, Kevin; Maul, William A.; Fulton, Christopher

2012-01-01

The Extended Testability Analysis (ETA) Tool is a software application that supports fault management (FM) by performing testability analyses on the fault propagation model of a given system. Fault management includes the prevention of faults through robust design margins and quality assurance methods, or the mitigation of system failures. Fault management requires an understanding of the system design and operation, potential failure mechanisms within the system, and the propagation of those potential failures through the system. The purpose of the ETA Tool software is to process the testability analysis results from a commercial software program called TEAMS Designer in order to provide a detailed set of diagnostic assessment reports. The ETA Tool is a command-line process with several user-selectable report output options. The ETA Tool also extends the COTS testability analysis and enables variation studies with sensor sensitivity impacts on system diagnostics and component isolation using a single testability output. The ETA Tool can also provide extended analyses from a single set of testability output files. The following analysis reports are available to the user: (1) the Detectability Report provides a breakdown of how each tested failure mode was detected, (2) the Test Utilization Report identifies all the failure modes that each test detects, (3) the Failure Mode Isolation Report demonstrates the system s ability to discriminate between failure modes, (4) the Component Isolation Report demonstrates the system s ability to discriminate between failure modes relative to the components containing the failure modes, (5) the Sensor Sensor Sensitivity Analysis Report shows the diagnostic impact due to loss of sensor information, and (6) the Effect Mapping Report identifies failure modes that result in specified system-level effects.

Retest of a Principal Components Analysis of Two Household Environmental Risk Instruments.

PubMed

Oneal, Gail A; Postma, Julie; Odom-Maryon, Tamara; Butterfield, Patricia

2016-08-01

Household Risk Perception (HRP) and Self-Efficacy in Environmental Risk Reduction (SEERR) instruments were developed for a public health nurse-delivered intervention designed to reduce home-based, environmental health risks among rural, low-income families. The purpose of this study was to test both instruments in a second low-income population that differed geographically and economically from the original sample. Participants (N = 199) were recruited from the Women, Infants, and Children (WIC) program. Paper and pencil surveys were collected at WIC sites by research-trained student nurses. Exploratory principal components analysis (PCA) was conducted, and comparisons were made to the original PCA for the purpose of data reduction. Instruments showed satisfactory Cronbach alpha values for all components. HRP components were reduced from five to four, which explained 70% of variance. The components were labeled sensed risks, unseen risks, severity of risks, and knowledge. In contrast to the original testing, environmental tobacco smoke (ETS) items was not a separate component of the HRP. The SEERR analysis demonstrated four components explaining 71% of variance, with similar patterns of items as in the first study, including a component on ETS, but some differences in item location. Although low-income populations constituted both samples, differences in demographics and risk exposures may have played a role in component and item locations. Findings provided justification for changing or reducing items, and for tailoring the instruments to population-level risks and behaviors. Although analytic refinement will continue, both instruments advance the measurement of environmental health risk perception and self-efficacy. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Immunohistochemical, cytogenetic, and molecular cytogenetic characterization of both components of a dedifferentiated liposarcoma: implications for histogenesis.

PubMed

Nishio, Jun; Iwasaki, Hiroshi; Nabeshima, Kazuki; Naito, Masatoshi

2015-01-01

Dedifferentiated liposarcoma (DDLS) is a malignant adipocytic tumor showing transition from an atypical lipomatous tumor (ALT)/well-differentiated liposarcoma (WDLS) to a non-lipogenic sarcoma of variable histological grades. We present the immunohistochemical, cytogenetic, and molecular cytogenetic findings of DDLS arising in the right chest wall of a 76-year-old man. Magnetic resonance imaging exhibited a large mass composed of two components with heterogeneous signal intensities, suggesting the coexistence of a fatty area and another soft tissue component. The grossly heterogeneous mass was histologically composed of an ALT/WDLS component transitioning abruptly into a dedifferentiated component. Immunohistochemistry was positive for murine double-minute 2 (MDM2), cyclin-dependent kinase 4 (CDK4), and p16 in both components, although a more strong and diffuse staining was found in the dedifferentiated area. The MIB-1 labeling index was extremely higher in the dedifferentiated area compared to the ALT/WDLS area. Cytogenetic analysis of the ALT/WDLS component revealed the following karyotype: 46,X,-Y,+r. Notably, cytogenetic analysis of the dedifferentiated component revealed a similar but more complex karyotype. Spectral karyotyping demonstrated that the ring chromosome was entirely composed of material from chromosome 12. Interphase fluorescence in situ hybridization analysis revealed amplification of MDM2 and CDK4 in both components. These findings suggest that multiple abnormal clones derived from a single precursor cell would be present in DDLS, with one or more containing supernumerary rings or giant marker chromosomes. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Semiotic-conceptual analysis: a proposal

NASA Astrophysics Data System (ADS)

Priss, Uta

2017-07-01

This paper provides the basic definitions of Semiotic-conceptual analysis (SCA), which is a mathematical modelling of signs as elements of a triadic relation. FCA concept lattices are constructed for each of the three sign components. It is demonstrated how core linguistic and semiotic notions (such as synonymy and icon) can be represented with SCA. While the usefulness of SCA has already been demonstrated in a number of applications and several propositions are proven in this paper, there are still many open questions as to what to do next with SCA. Therefore, this paper is meant as a proposal and encouragement for further development.

Time-resolved scanning electron microscopy with polarization analysis

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

Frömter, Robert, E-mail: rfroemte@physik.uni-hamburg.de; Oepen, Hans Peter; The Hamburg Centre for Ultrafast Imaging, Luruper Chaussee 149, 22761 Hamburg

2016-04-04

We demonstrate the feasibility of investigating periodically driven magnetization dynamics in a scanning electron microscope with polarization analysis based on spin-polarized low-energy electron diffraction. With the present setup, analyzing the time structure of the scattering events, we obtain a temporal resolution of 700 ps, which is demonstrated by means of imaging the field-driven 100 MHz gyration of the vortex in a soft-magnetic FeCoSiB square. Owing to the efficient intrinsic timing scheme, high-quality movies, giving two components of the magnetization simultaneously, can be recorded on the time scale of hours.

REDARS 2 demonstration project for seismic risk analysis of highway systems.

DOT National Transportation Integrated Search

2006-06-01

Effects of earthquake damage to highway components such as bridges and roadways can go well beyond life-safety risks and costs to repair damaged structures. Such damage can also severely disrupt traffic flows that can : impact the regions economy ...

Traffic Profiling in Wireless Sensor Networks

DTIC Science & Technology

2006-12-01

components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.

Preservation of micro-architecture and angiogenic potential in a pulmonary acellular matrix obtained using intermittent intra-tracheal flow of detergent enzymatic treatment.

PubMed

Maghsoudlou, Panagiotis; Georgiades, Fanourios; Tyraskis, Athanasios; Totonelli, Giorgia; Loukogeorgakis, Stavros P; Orlando, Giuseppe; Shangaris, Panicos; Lange, Peggy; Delalande, Jean-Marie; Burns, Alan J; Cenedese, Angelo; Sebire, Neil J; Turmaine, Mark; Guest, Brogan N; Alcorn, John F; Atala, Anthony; Birchall, Martin A; Elliott, Martin J; Eaton, Simon; Pierro, Agostino; Gilbert, Thomas W; De Coppi, Paolo

2013-09-01

Tissue engineering of autologous lung tissue aims to become a therapeutic alternative to transplantation. Efforts published so far in creating scaffolds have used harsh decellularization techniques that damage the extracellular matrix (ECM), deplete its components and take up to 5 weeks to perform. The aim of this study was to create a lung natural acellular scaffold using a method that will reduce the time of production and better preserve scaffold architecture and ECM components. Decellularization of rat lungs via the intratracheal route removed most of the nuclear material when compared to the other entry points. An intermittent inflation approach that mimics lung respiration yielded an acellular scaffold in a shorter time with an improved preservation of pulmonary micro-architecture. Electron microscopy demonstrated the maintenance of an intact alveolar network, with no evidence of collapse or tearing. Pulsatile dye injection via the vasculature indicated an intact capillary network in the scaffold. Morphometry analysis demonstrated a significant increase in alveolar fractional volume, with alveolar size analysis confirming that alveolar dimensions were maintained. Biomechanical testing of the scaffolds indicated an increase in resistance and elastance when compared to fresh lungs. Staining and quantification for ECM components showed a presence of collagen, elastin, GAG and laminin. The intratracheal intermittent decellularization methodology could be translated to sheep lungs, demonstrating a preservation of ECM components, alveolar and vascular architecture. Decellularization treatment and methodology preserves lung architecture and ECM whilst reducing the production time to 3 h. Cell seeding and in vivo experiments are necessary to proceed towards clinical translation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of components of variance in multiple-reader studies of computer-aided diagnosis with different tasks

NASA Astrophysics Data System (ADS)

Beiden, Sergey V.; Wagner, Robert F.; Campbell, Gregory; Metz, Charles E.; Chan, Heang-Ping; Nishikawa, Robert M.; Schnall, Mitchell D.; Jiang, Yulei

2001-06-01

In recent years, the multiple-reader, multiple-case (MRMC) study paradigm has become widespread for receiver operating characteristic (ROC) assessment of systems for diagnostic imaging and computer-aided diagnosis. We review how MRMC data can be analyzed in terms of the multiple components of the variance (case, reader, interactions) observed in those studies. Such information is useful for the design of pivotal studies from results of a pilot study and also for studying the effects of reader training. Recently, several of the present authors have demonstrated methods to generalize the analysis of multiple variance components to the case where unaided readers of diagnostic images are compared with readers who receive the benefit of a computer assist (CAD). For this case it is necessary to model the possibility that several of the components of variance might be reduced when readers incorporate the computer assist, compared to the unaided reading condition. We review results of this kind of analysis on three previously published MRMC studies, two of which were applications of CAD to diagnostic mammography and one was an application of CAD to screening mammography. The results for the three cases are seen to differ, depending on the reader population sampled and the task of interest. Thus, it is not possible to generalize a particular analysis of variance components beyond the tasks and populations actually investigated.

Item response theory and factor analysis as a mean to characterize occurrence of response shift in a longitudinal quality of life study in breast cancer patients

PubMed Central

2014-01-01

Background The occurrence of response shift (RS) in longitudinal health-related quality of life (HRQoL) studies, reflecting patient adaptation to disease, has already been demonstrated. Several methods have been developed to detect the three different types of response shift (RS), i.e. recalibration RS, 2) reprioritization RS, and 3) reconceptualization RS. We investigated two complementary methods that characterize the occurrence of RS: factor analysis, comprising Principal Component Analysis (PCA) and Multiple Correspondence Analysis (MCA), and a method of Item Response Theory (IRT). Methods Breast cancer patients (n = 381) completed the EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires at baseline, immediately following surgery, and three and six months after surgery, according to the “then-test/post-test” design. Recalibration was explored using MCA and a model of IRT, called the Linear Logistic Model with Relaxed Assumptions (LLRA) using the then-test method. Principal Component Analysis (PCA) was used to explore reconceptualization and reprioritization. Results MCA highlighted the main profiles of recalibration: patients with high HRQoL level report a slightly worse HRQoL level retrospectively and vice versa. The LLRA model indicated a downward or upward recalibration for each dimension. At six months, the recalibration effect was statistically significant for 11/22 dimensions of the QLQ-C30 and BR23 according to the LLRA model (p ≤ 0.001). Regarding the QLQ-C30, PCA indicated a reprioritization of symptom scales and reconceptualization via an increased correlation between functional scales. Conclusions Our findings demonstrate the usefulness of these analyses in characterizing the occurrence of RS. MCA and IRT model had convergent results with then-test method to characterize recalibration component of RS. PCA is an indirect method in investigating the reprioritization and reconceptualization components of RS. PMID:24606836

A Case Study for Probabilistic Methods Validation (MSFC Center Director's Discretionary Fund, Project No. 94-26)

NASA Technical Reports Server (NTRS)

Price J. M.; Ortega, R.

1998-01-01

Probabilistic method is not a universally accepted approach for the design and analysis of aerospace structures. The validity of this approach must be demonstrated to encourage its acceptance as it viable design and analysis tool to estimate structural reliability. The objective of this Study is to develop a well characterized finite population of similar aerospace structures that can be used to (1) validate probabilistic codes, (2) demonstrate the basic principles behind probabilistic methods, (3) formulate general guidelines for characterization of material drivers (such as elastic modulus) when limited data is available, and (4) investigate how the drivers affect the results of sensitivity analysis at the component/failure mode level.

Subject order-independent group ICA (SOI-GICA) for functional MRI data analysis.

PubMed

Zhang, Han; Zuo, Xi-Nian; Ma, Shuang-Ye; Zang, Yu-Feng; Milham, Michael P; Zhu, Chao-Zhe

2010-07-15

Independent component analysis (ICA) is a data-driven approach to study functional magnetic resonance imaging (fMRI) data. Particularly, for group analysis on multiple subjects, temporally concatenation group ICA (TC-GICA) is intensively used. However, due to the usually limited computational capability, data reduction with principal component analysis (PCA: a standard preprocessing step of ICA decomposition) is difficult to achieve for a large dataset. To overcome this, TC-GICA employs multiple-stage PCA data reduction. Such multiple-stage PCA data reduction, however, leads to variable outputs due to different subject concatenation orders. Consequently, the ICA algorithm uses the variable multiple-stage PCA outputs and generates variable decompositions. In this study, a rigorous theoretical analysis was conducted to prove the existence of such variability. Simulated and real fMRI experiments were used to demonstrate the subject-order-induced variability of TC-GICA results using multiple PCA data reductions. To solve this problem, we propose a new subject order-independent group ICA (SOI-GICA). Both simulated and real fMRI data experiments demonstrated the high robustness and accuracy of the SOI-GICA results compared to those of traditional TC-GICA. Accordingly, we recommend SOI-GICA for group ICA-based fMRI studies, especially those with large data sets. Copyright 2010 Elsevier Inc. All rights reserved.

Differential principal component analysis of ChIP-seq.

PubMed

Ji, Hongkai; Li, Xia; Wang, Qian-fei; Ning, Yang

2013-04-23

We propose differential principal component analysis (dPCA) for analyzing multiple ChIP-sequencing datasets to identify differential protein-DNA interactions between two biological conditions. dPCA integrates unsupervised pattern discovery, dimension reduction, and statistical inference into a single framework. It uses a small number of principal components to summarize concisely the major multiprotein synergistic differential patterns between the two conditions. For each pattern, it detects and prioritizes differential genomic loci by comparing the between-condition differences with the within-condition variation among replicate samples. dPCA provides a unique tool for efficiently analyzing large amounts of ChIP-sequencing data to study dynamic changes of gene regulation across different biological conditions. We demonstrate this approach through analyses of differential chromatin patterns at transcription factor binding sites and promoters as well as allele-specific protein-DNA interactions.

Task analysis exemplified: the process of resolving unfinished business.

PubMed

Greenberg, L S; Foerster, F S

1996-06-01

The steps of a task-analytic research program designed to identify the in-session performances involved in resolving lingering bad feelings toward a significant other are described. A rational-empirical methodology of repeatedly cycling between rational conjecture and empirical observations is demonstrated as a method of developing an intervention manual and the components of client processes of resolution. A refined model of the change process developed by these procedures is validated by comparing 11 successful and 11 unsuccessful performances. Four performance components-intense expression of feeling, expression of need, shift in representation of other, and self-validation or understanding of the other-were found to discriminate between resolution and nonresolution performances. These components were measured on 4 process measures: the Structural Analysis of Social Behavior, the Experiencing Scale, the Client's Emotional Arousal Scale, and a need scale.

Principal component analysis and the locus of the Fréchet mean in the space of phylogenetic trees.

PubMed

Nye, Tom M W; Tang, Xiaoxian; Weyenberg, Grady; Yoshida, Ruriko

2017-12-01

Evolutionary relationships are represented by phylogenetic trees, and a phylogenetic analysis of gene sequences typically produces a collection of these trees, one for each gene in the analysis. Analysis of samples of trees is difficult due to the multi-dimensionality of the space of possible trees. In Euclidean spaces, principal component analysis is a popular method of reducing high-dimensional data to a low-dimensional representation that preserves much of the sample's structure. However, the space of all phylogenetic trees on a fixed set of species does not form a Euclidean vector space, and methods adapted to tree space are needed. Previous work introduced the notion of a principal geodesic in this space, analogous to the first principal component. Here we propose a geometric object for tree space similar to the [Formula: see text]th principal component in Euclidean space: the locus of the weighted Fréchet mean of [Formula: see text] vertex trees when the weights vary over the [Formula: see text]-simplex. We establish some basic properties of these objects, in particular showing that they have dimension [Formula: see text], and propose algorithms for projection onto these surfaces and for finding the principal locus associated with a sample of trees. Simulation studies demonstrate that these algorithms perform well, and analyses of two datasets, containing Apicomplexa and African coelacanth genomes respectively, reveal important structure from the second principal components.

Optimum Vehicle Component Integration with InVeST (Integrated Vehicle Simulation Testbed)

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

Ng, W; Paddack, E; Aceves, S

2001-12-27

We have developed an Integrated Vehicle Simulation Testbed (InVeST). InVeST is based on the concept of Co-simulation, and it allows the development of virtual vehicles that can be analyzed and optimized as an overall integrated system. The virtual vehicle is defined by selecting different vehicle components from a component library. Vehicle component models can be written in multiple programming languages running on different computer platforms. At the same time, InVeST provides full protection for proprietary models. Co-simulation is a cost-effective alternative to competing methodologies, such as developing a translator or selecting a single programming language for all vehicle components. InVeSTmore » has been recently demonstrated using a transmission model and a transmission controller model. The transmission model was written in SABER and ran on a Sun/Solaris workstation, while the transmission controller was written in MATRIXx and ran on a PC running Windows NT. The demonstration was successfully performed. Future plans include the applicability of Co-simulation and InVeST to analysis and optimization of multiple complex systems, including those of Intelligent Transportation Systems.« less

Identification of the isomers using principal component analysis (PCA) method

NASA Astrophysics Data System (ADS)

Kepceoǧlu, Abdullah; Gündoǧdu, Yasemin; Ledingham, Kenneth William David; Kilic, Hamdi Sukur

2016-03-01

In this work, we have carried out a detailed statistical analysis for experimental data of mass spectra from xylene isomers. Principle Component Analysis (PCA) was used to identify the isomers which cannot be distinguished using conventional statistical methods for interpretation of their mass spectra. Experiments have been carried out using a linear TOF-MS coupled to a femtosecond laser system as an energy source for the ionisation processes. We have performed experiments and collected data which has been analysed and interpreted using PCA as a multivariate analysis of these spectra. This demonstrates the strength of the method to get an insight for distinguishing the isomers which cannot be identified using conventional mass analysis obtained through dissociative ionisation processes on these molecules. The PCA results dependending on the laser pulse energy and the background pressure in the spectrometers have been presented in this work.

A hybrid spatial-spectral denoising method for infrared hyperspectral images using 2DPCA

NASA Astrophysics Data System (ADS)

Huang, Jun; Ma, Yong; Mei, Xiaoguang; Fan, Fan

2016-11-01

The traditional noise reduction methods for 3-D infrared hyperspectral images typically operate independently in either the spatial or spectral domain, and such methods overlook the relationship between the two domains. To address this issue, we propose a hybrid spatial-spectral method in this paper to link both domains. First, principal component analysis and bivariate wavelet shrinkage are performed in the 2-D spatial domain. Second, 2-D principal component analysis transformation is conducted in the 1-D spectral domain to separate the basic components from detail ones. The energy distribution of noise is unaffected by orthogonal transformation; therefore, the signal-to-noise ratio of each component is used as a criterion to determine whether a component should be protected from over-denoising or denoised with certain 1-D denoising methods. This study implements the 1-D wavelet shrinking threshold method based on Stein's unbiased risk estimator, and the quantitative results on publicly available datasets demonstrate that our method can improve denoising performance more effectively than other state-of-the-art methods can.

Utility of Metabolomics toward Assessing the Metabolic Basis of Quality Traits in Apple Fruit with an Emphasis on Antioxidants

PubMed Central

Cuthbertson, Daniel; Andrews, Preston K.; Reganold, John P.; Davies, Neal M.; Lange, B. Markus

2012-01-01

A gas chromatography–mass spectrometry approach was employed to evaluate the use of metabolite patterns to differentiate fruit from six commercially grown apple cultivars harvested in 2008. Principal component analysis (PCA) of apple fruit peel and flesh data indicated that individual cultivar replicates clustered together and were separated from all other cultivar samples. An independent metabolomics investigation with fruit harvested in 2003 confirmed the separate clustering of fruit from different cultivars. Further evidence for cultivar separation was obtained using a hierarchical clustering analysis. An evaluation of PCA component loadings revealed specific metabolite classes that contributed the most to each principal component, whereas a correlation analysis demonstrated that specific metabolites correlate directly with quality traits such as antioxidant activity, total phenolics, and total anthocyanins, which are important parameters in the selection of breeding germplasm. These data sets lay the foundation for elucidating the metabolic basis of commercially important fruit quality traits. PMID:22881116

Analysis of Free Modeling Predictions by RBO Aleph in CASP11

PubMed Central

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

2015-01-01

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

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.

Demonstrated Potential of Ion Mobility Spectrometry for Detection of Adulterated Perfumes and Plant Speciation

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

Clark, Jared Matthew; Daum, Keith Alvin; Kalival, J. H.

2003-01-01

This initial study evaluates the use of ion mobility spectrometry (IMS) as a rapid test procedure for potential detection of adulterated perfumes and speciation of plant life. Sample types measured consist of five genuine perfumes, two species of sagebrush, and four species of flowers. Each sample type is treated as a separate classification problem. It is shown that discrimination using principal component analysis with K-nearest neighbors can distinguish one class from another. Discriminatory models generated using principal component regressions are not as effective. Results from this examination are encouraging and represent an initial phase demonstrating that perfumes and plants possessmore » characteristic chemical signatures that can be used for reliable identification.« less

[Association between the use of blood components and the five-year mortality after liver transplant].

PubMed

de Morais, Bruno Salomé; Sanches, Marcelo Dias; Ribeiro, Daniel Dias; Lima, Agnaldo Soares; de Abreu Ferrari, Teresa Cristina; Duarte, Malvina Maria de Freitas; Cançado, Guilherme Henrique Gomes Moreira

2011-01-01

Liver transplant (LT) surgery is associated with significant bleeding in 20% of cases, and several authors have demonstrated the risks related to blood components. The objective of the present study was to evaluate the impact of using blood components during hospitalization in five-year survival of patients undergoing LT. One hundred and thirteen patients were evaluated retrospectively. Several variables, including the use of blood components intraoperatively and throughout hospitalization, were categorized and evaluated by univariate analysis using Fisher's test. A level of significance of 5% was adopted. Results with p < 0.2 underwent multivariate analysis using multinomial logistic regression. Parenchymal diseases, preoperative renal dysfunction, and longer stay in hospital and ICU are associated with greater five-year mortality after LT (p < 0.05). Unlike the intraoperative use of blood components, the accumulated transfusion of packed red blood cell, frozen fresh plasma, and platelets during the entire hospitalization was associated with greater five-year mortality after liver transplantation (p < 0.01). This study emphasizes the relationship between the use of blood components during hospitalization and increased mortality in five years after LT. 2011 Elsevier Editora Ltda. All rights reserved.

Classification of breast tissue in mammograms using efficient coding.

PubMed

Costa, Daniel D; Campos, Lúcio F; Barros, Allan K

2011-06-24

Female breast cancer is the major cause of death by cancer in western countries. Efforts in Computer Vision have been made in order to improve the diagnostic accuracy by radiologists. Some methods of lesion diagnosis in mammogram images were developed based in the technique of principal component analysis which has been used in efficient coding of signals and 2D Gabor wavelets used for computer vision applications and modeling biological vision. In this work, we present a methodology that uses efficient coding along with linear discriminant analysis to distinguish between mass and non-mass from 5090 region of interest from mammograms. The results show that the best rates of success reached with Gabor wavelets and principal component analysis were 85.28% and 87.28%, respectively. In comparison, the model of efficient coding presented here reached up to 90.07%. Altogether, the results presented demonstrate that independent component analysis performed successfully the efficient coding in order to discriminate mass from non-mass tissues. In addition, we have observed that LDA with ICA bases showed high predictive performance for some datasets and thus provide significant support for a more detailed clinical investigation.

A decomposition model and voxel selection framework for fMRI analysis to predict neural response of visual stimuli.

PubMed

Raut, Savita V; Yadav, Dinkar M

2018-03-28

This paper presents an fMRI signal analysis methodology using geometric mean curve decomposition (GMCD) and mutual information-based voxel selection framework. Previously, the fMRI signal analysis has been conducted using empirical mean curve decomposition (EMCD) model and voxel selection on raw fMRI signal. The erstwhile methodology loses frequency component, while the latter methodology suffers from signal redundancy. Both challenges are addressed by our methodology in which the frequency component is considered by decomposing the raw fMRI signal using geometric mean rather than arithmetic mean and the voxels are selected from EMCD signal using GMCD components, rather than raw fMRI signal. The proposed methodologies are adopted for predicting the neural response. Experimentations are conducted in the openly available fMRI data of six subjects, and comparisons are made with existing decomposition models and voxel selection frameworks. Subsequently, the effect of degree of selected voxels and the selection constraints are analyzed. The comparative results and the analysis demonstrate the superiority and the reliability of the proposed methodology.

Quality assessment of raw and processed Arctium lappa L. through multicomponent quantification, chromatographic fingerprint, and related chemometric analysis.

PubMed

Qin, Kunming; Wang, Bin; Li, Weidong; Cai, Hao; Chen, Danni; Liu, Xiao; Yin, Fangzhou; Cai, Baochang

2015-05-01

In traditional Chinese medicine, raw and processed herbs are used to treat different diseases. Suitable quality assessment methods are crucial for the discrimination between raw and processed herbs. The dried fruit of Arctium lappa L. and their processed products are widely used in traditional Chinese medicine, yet their therapeutic effects are different. In this study, a novel strategy using high-performance liquid chromatography and diode array detection coupled with multivariate statistical analysis to rapidly explore raw and processed Arctium lappa L. was proposed and validated. Four main components in a total of 30 batches of raw and processed Fructus Arctii samples were analyzed, and ten characteristic peaks were identified in the fingerprint common pattern. Furthermore, similarity evaluation, principal component analysis, and hierachical cluster analysis were applied to demonstrate the distinction. The results suggested that the relative amounts of the chemical components of raw and processed Fructus Arctii samples are different. This new method has been successfully applied to detect the raw and processed Fructus Arctii in marketed herbal medicinal products. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Single Event Analysis and Fault Injection Techniques Targeting Complex Designs Implemented in Xilinx-Virtex Family Field Programmable Gate Array (FPGA) Devices

NASA Technical Reports Server (NTRS)

Berg, Melanie D.; LaBel, Kenneth; Kim, Hak

2014-01-01

An informative session regarding SRAM FPGA basics. Presenting a framework for fault injection techniques applied to Xilinx Field Programmable Gate Arrays (FPGAs). Introduce an overlooked time component that illustrates fault injection is impractical for most real designs as a stand-alone characterization tool. Demonstrate procedures that benefit from fault injection error analysis.

Coupled structural/thermal/electromagnetic analysis/tailoring of graded composite structures

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Huang, H.; Hartle, M.

1992-01-01

Accomplishments are described for the fourth years effort of a 5-year program to develop a methodology for coupled structural/thermal/electromagnetic analysis/tailoring of graded component structures. These accomplishments include: (1) demonstration of coupled solution capability; (2) alternate CSTEM electromagnetic technology; (3) CSTEM acoustic capability; (4) CSTEM tailoring; (5) CSTEM composite micromechanics using ICAN; and (6) multiple layer elements in CSTEM.

Measuring Academic Library Efficiency and Alignment with Institutional Resource Utilization Priorities Using Data Envelopment Analysis: An Analysis of Institutions of Higher Education in Texas and Their Libraries

ERIC Educational Resources Information Center

Shupala, Christine M.

2012-01-01

Academic and library administrators are increasingly required to demonstrate efficiency in programs, services, and operations as well as effectiveness. An important component of efficiency measurement is identification of a relevant peer group against which to compare the administrative unit to determine relative efficiency. The two-fold purpose…

Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

PubMed

Williams, Alex H; Kim, Tony Hyun; Wang, Forea; Vyas, Saurabh; Ryu, Stephen I; Shenoy, Krishna V; Schnitzer, Mark; Kolda, Tamara G; Ganguli, Surya

2018-06-27

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights into diverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning. Copyright © 2018 Elsevier Inc. All rights reserved.

SDP_mharwit_1: Demonstration of HIFI Linear Polarization Analysis of Spectral Features

NASA Astrophysics Data System (ADS)

Harwit, M.

2010-03-01

We propose to observe the polarization of the 621 GHz water vapor maser in VY Canis Majoris to demonstrate the capability of HIFI to make polarization observations of Far-Infrared/Submillimeter spectral lines. The proposed Demonstration Phase would: - Show that HIFI is capable of interesting linear polarization measurements of spectral lines; - Test out the highest spectral resolving power to sort out closely spaced Doppler components; - Determine whether the relative intensities predicted by Neufeld and Melnick are correct; - Record the degree and direction of linear polarization for the closely-Doppler shifted peaks.

A distributed finite-element modeling and control approach for large flexible structures

NASA Technical Reports Server (NTRS)

Young, K. D.

1989-01-01

An unconventional framework is described for the design of decentralized controllers for large flexible structures. In contrast to conventional control system design practice which begins with a model of the open loop plant, the controlled plant is assembled from controlled components in which the modeling phase and the control design phase are integrated at the component level. The developed framework is called controlled component synthesis (CCS) to reflect that it is motivated by the well developed Component Mode Synthesis (CMS) methods which were demonstrated to be effective for solving large complex structural analysis problems for almost three decades. The design philosophy behind CCS is also closely related to that of the subsystem decomposition approach in decentralized control.

Rapid analysis of the main components of the total glycosides of Ranunculus japonicus by UPLC/Q-TOF-MS.

PubMed

Rui, Wen; Chen, Hongyuan; Tan, Yuzhi; Zhong, Yanmei; Feng, Yifan

2010-05-01

A rapid method for the analysis of the main components of the total glycosides of Ranunculus japonicus (TGOR) was developed using ultra-performance liquid chromatography with quadrupole-time-of-flight mass spectrometry (UPLC/Q-TOF-MS). The separation analysis was performed on a Waters Acquity UPLC system and the accurate mass of molecules and their fragment ions were determined by Q-TOF MS. Twenty compounds, including lactone glycosides, flavonoid glycosides and flavonoid aglycones, were identified and tentatively deduced on the basis of their elemental compositions, MS/MS data and relevant literature. The results demonstrated that lactone glycosides and flavonoids were the main constituents of TGOR. Furthermore, an effective and rapid pattern was established allowing for the comprehensive and systematic characterization of the complex samples.

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

Development and validation of a questionnaire to evaluate patient satisfaction with diabetes disease management.

PubMed

Paddock, L E; Veloski, J; Chatterton, M L; Gevirtz, F O; Nash, D B

2000-07-01

To develop a reliable and valid questionnaire to measure patient satisfaction with diabetes disease management programs. Questions related to structure, process, and outcomes were categorized into 14 domains defining the essential elements of diabetes disease management. Health professionals confirmed the content validity. Face validity was established by a patient focus group. The questionnaire was mailed to 711 patients with diabetes who participated in a disease management program. To reduce the number of questionnaire items, a principal components analysis was performed using a varimax rotation. The Scree test was used to select significant components. To further assess reliability and validity; Cronbach's alpha and product-moment correlations were calculated for components having > or =3 items with loadings >0.50. The validated 73-item mailed satisfaction survey had a 34.1% response rate. Principal components analysis yielded 13 components with eigenvalues > 1.0. The Scree test proposed a 6-component solution (39 items), which explained 59% of the total variation. Internal consistency reliabilities computed for the first 6 components (alpha = 0.79-0.95) were acceptable. The final questionnaire, the Diabetes Management Evaluation Tool (DMET), was designed to assess patient satisfaction with diabetes disease management programs. Although more extensive testing of the questionnaire is appropriate, preliminary reliability and validity of the DMET has been demonstrated.

Blood coagulation abnormalities in multibacillary leprosy patients.

PubMed

Silva, Débora Santos da; Teixeira, Lisandra Antonia Castro; Beghini, Daniela Gois; Ferreira, André Teixeira da Silva; Pinho, Márcia de Berredo Moreira; Rosa, Patricia Sammarco; Ribeiro, Marli Rambaldi; Freire, Monica Di Calafiori; Hacker, Mariana Andrea; Nery, José Augusto da Costa; Pessolani, Maria Cristina Vidal; Tovar, Ana Maria Freire; Sarno, Euzenir Nunes; Perales, Jonas; Bozza, Fernando Augusto; Esquenazi, Danuza; Monteiro, Robson Queiroz; Lara, Flavio Alves

2018-03-01

Leprosy is a chronic dermato-neurological disease caused by Mycobacterium leprae infection. In 2016, more than 200,000 new cases of leprosy were detected around the world, representing the most frequent cause of infectious irreversible deformities and disabilities. In the present work, we demonstrate a consistent procoagulant profile on 40 reactional and non-reactional multibacillary leprosy patients. A retrospective analysis in search of signs of coagulation abnormalities among 638 leprosy patients identified 35 leprosy patients (5.48%) which displayed a characteristic lipid-like clot formed between blood clot and serum during serum harvesting, herein named 'leprosum clot'. Most of these patients (n = 16, 45.7%) belonged to the lepromatous leprosy pole of the disease. In addition, formation of the leprosum clot was directly correlated with increased plasma levels of soluble tissue factor and von Willebrand factor. High performance thin layer chromatography demonstrated a high content of neutral lipids in the leprosum clot, and proteomic analysis demonstrated that the leprosum clot presented in these patients is highly enriched in fibrin. Remarkably, differential 2D-proteomics analysis between leprosum clots and control clots identified two proteins present only in leprosy patients clots: complement component 3 and 4 and inter-alpha-trypsin inhibitor family heavy chain-related protein (IHRP). In agreement with those observations we demonstrated that M. leprae induces hepatocytes release of IHRP in vitro. We demonstrated that leprosy MB patients develop a procoagulant status due to high levels of plasmatic fibrinogen, anti-cardiolipin antibodies, von Willebrand factor and soluble tissue factor. We propose that some of these components, fibrinogen for example, presents potential as predictive biomarkers of leprosy reactions, generating tools for earlier diagnosis and treatment of these events.

Thermoelastic stress analysis to validate tibial fixation technique in total ankle prostheses - a pilot study.

PubMed

Ficklscherer, Andreas; Wegener, Bernd; Niethammer, Thomas; Pietschmann, Matthias F; Müller, Peter E; Jansson, Volkmar; Trouillier, Hans-Heinrich

2013-03-01

Recent literature has shown a persistently high rate of aseptic loosening of the tibial component in total ankle prostheses. We analyzed the interface between the tibial bone and tibial component with a thermoelastic stress analysis to demonstrate load transmission onto the distal tibia. In this regard, we used two established ankle prostheses, which were implanted in two human cadaveric and in two third-generation composite tibia bones (Sawbones®, Sweden). Subsequently, the bones were attached to a hydropulser and a sinusoidal load of 700 N was applied. Both prostheses had an inhomogeneous load transmission onto the distal tibia. Instead of distributing load equally to the subarticular bone, forces were focused around the bolting stem, accumulating as stress maxima with forces up to 90 MPa. Furthermore, we were able to demonstrate load transmission into the metaphysis of the bone. As demonstrated in this study, anchoring systems with stems used in all established total ankle prostheses lead to an inhomogeneous load transmission onto the distal tibia, and furthermore, to a distribution of load into the weaker metaphyseal bone. For these reasons, we favor a prosthetic design with minimal bone resection and without any stem or stem-like anchoring system, which facilitates a homogeneous load transmission onto the distal tibia. Thermoelastic stress analysis proved to be a fast and easy-to-perform method to visualize load transmission.

Coupled multi-disciplinary composites behavior simulation

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Murthy, Pappu L. N.; Chamis, Christos C.

1993-01-01

The capabilities of the computer code CSTEM (Coupled Structural/Thermal/Electro-Magnetic Analysis) are discussed and demonstrated. CSTEM computationally simulates the coupled response of layered multi-material composite structures subjected to simultaneous thermal, structural, vibration, acoustic, and electromagnetic loads and includes the effect of aggressive environments. The composite material behavior and structural response is determined at its various inherent scales: constituents (fiber/matrix), ply, laminate, and structural component. The thermal and mechanical properties of the constituents are considered to be nonlinearly dependent on various parameters such as temperature and moisture. The acoustic and electromagnetic properties also include dependence on vibration and electromagnetic wave frequencies, respectively. The simulation is based on a three dimensional finite element analysis in conjunction with composite mechanics and with structural tailoring codes, and with acoustic and electromagnetic analysis methods. An aircraft engine composite fan blade is selected as a typical structural component to demonstrate the CSTEM capabilities. Results of various coupled multi-disciplinary heat transfer, structural, vibration, acoustic, and electromagnetic analyses for temperature distribution, stress and displacement response, deformed shape, vibration frequencies, mode shapes, acoustic noise, and electromagnetic reflection from the fan blade are discussed for their coupled effects in hot and humid environments. Collectively, these results demonstrate the effectiveness of the CSTEM code in capturing the coupled effects on the various responses of composite structures subjected to simultaneous multiple real-life loads.

Reconstruction of interatomic vectors by principle component analysis of nuclear magnetic resonance data in multiple alignments

NASA Astrophysics Data System (ADS)

Hus, Jean-Christophe; Bruschweiler, Rafael

2002-07-01

A general method is presented for the reconstruction of interatomic vector orientations from nuclear magnetic resonance (NMR) spectroscopic data of tensor interactions of rank 2, such as dipolar coupling and chemical shielding anisotropy interactions, in solids and partially aligned liquid-state systems. The method, called PRIMA, is based on a principal component analysis of the covariance matrix of the NMR parameters collected for multiple alignments. The five nonzero eigenvalues and their eigenvectors efficiently allow the approximate reconstruction of the vector orientations of the underlying interactions. The method is demonstrated for an isotropic distribution of sample orientations as well as for finite sets of orientations and internuclear vectors encountered in protein systems.

Probabilistic finite elements for fracture and fatigue analysis

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Lawrence, M.; Besterfield, G. H.

1989-01-01

The fusion of the probabilistic finite element method (PFEM) and reliability analysis for probabilistic fracture mechanics (PFM) is presented. A comprehensive method for determining the probability of fatigue failure for curved crack growth was developed. The criterion for failure or performance function is stated as: the fatigue life of a component must exceed the service life of the component; otherwise failure will occur. An enriched element that has the near-crack-tip singular strain field embedded in the element is used to formulate the equilibrium equation and solve for the stress intensity factors at the crack-tip. Performance and accuracy of the method is demonstrated on a classical mode 1 fatigue problem.

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

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.

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.

Demixed principal component analysis of neural population data.

PubMed

Kobak, Dmitry; Brendel, Wieland; Constantinidis, Christos; Feierstein, Claudia E; Kepecs, Adam; Mainen, Zachary F; Qi, Xue-Lian; Romo, Ranulfo; Uchida, Naoshige; Machens, Christian K

2016-04-12

Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information these areas represent and how it is represented. Here we demonstrate the advantages of a new dimensionality reduction technique, demixed principal component analysis (dPCA), that decomposes population activity into a few components. In addition to systematically capturing the majority of the variance of the data, dPCA also exposes the dependence of the neural representation on task parameters such as stimuli, decisions, or rewards. To illustrate our method we reanalyze population data from four datasets comprising different species, different cortical areas and different experimental tasks. In each case, dPCA provides a concise way of visualizing the data that summarizes the task-dependent features of the population response in a single figure.

A Genealogical Interpretation of Principal Components Analysis

PubMed Central

McVean, Gil

2009-01-01

Principal components analysis, PCA, is a statistical method commonly used in population genetics to identify structure in the distribution of genetic variation across geographical location and ethnic background. However, while the method is often used to inform about historical demographic processes, little is known about the relationship between fundamental demographic parameters and the projection of samples onto the primary axes. Here I show that for SNP data the projection of samples onto the principal components can be obtained directly from considering the average coalescent times between pairs of haploid genomes. The result provides a framework for interpreting PCA projections in terms of underlying processes, including migration, geographical isolation, and admixture. I also demonstrate a link between PCA and Wright's fst and show that SNP ascertainment has a largely simple and predictable effect on the projection of samples. Using examples from human genetics, I discuss the application of these results to empirical data and the implications for inference. PMID:19834557

Extending the accuracy of the SNAP interatomic potential form

NASA Astrophysics Data System (ADS)

Wood, Mitchell A.; Thompson, Aidan P.

2018-06-01

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functions in EAM. The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similar to artificial neural network potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting. The quality of this new potential form is measured through a robust cross-validation analysis.

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.

Lifetime Reliability Evaluation of Structural Ceramic Parts with the CARES/LIFE Computer Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

1993-01-01

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker equation. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), Weibull's normal stress averaging method (NSA), or Batdorf's theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating cyclic fatigue parameter estimation and component reliability analysis with proof testing are included.

Determination of Key Flavor Components in Methylene Chloride Extracts from Processed Grapefruit Juice.

PubMed

Jella; Rouseff; Goodner; Widmer

1998-01-19

The relative correlation of 52 aroma and 5 taste components in commercial not-from-concentrate grapefruit juices with flavor panel preference was determined. Methylene chloride extracts of juice were analyzed using GC/MS with a DB-5 column. Nonvolatiles determined included limonin and naringin by HPLC, degrees Brix, total acids, and degrees Brix/acid ratio. Juice samples were classified into low, medium, or high categories, based on average taste panel preference scores (nine-point hedonic scale). Principal component analysis demonstrated that highest quality juices were tightly clustered. Discriminant analysis indicated that 82% of the samples could be identified in the correct preference category using only myrcene, beta-caryophyllene, linalool, nootkatone, and degrees Brix. Nootkatone alone was not strongly associated with preference scores. The most preferred juices were strongly associated with low myrcene, low linalool, and intermediate levels of beta-caryophyllene.

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.

General multicomponent Yajima-Oikawa system: Painlevé analysis, soliton solutions, and energy-sharing collisions.

PubMed

Kanna, T; Sakkaravarthi, K; Tamilselvan, K

2013-12-01

We consider the multicomponent Yajima-Oikawa (YO) system and show that the two-component YO system can be derived in a physical setting of a three-coupled nonlinear Schrödinger (3-CNLS) type system by the asymptotic reduction method. The derivation is further generalized to the multicomponent case. This set of equations describes the dynamics of nonlinear resonant interaction between a one-dimensional long wave and multiple short waves. The Painlevé analysis of the general multicomponent YO system shows that the underlying set of evolution equations is integrable for arbitrary nonlinearity coefficients which will result in three different sets of equations corresponding to positive, negative, and mixed nonlinearity coefficients. We obtain the general bright N-soliton solution of the multicomponent YO system in the Gram determinant form by using Hirota's bilinearization method and explicitly analyze the one- and two-soliton solutions of the multicomponent YO system for the above mentioned three choices of nonlinearity coefficients. We also point out that the 3-CNLS system admits special asymptotic solitons of bright, dark, anti-dark, and gray types, when the long-wave-short-wave resonance takes place. The short-wave component solitons undergo two types of energy-sharing collisions. Specifically, in the two-component YO system, we demonstrate that two types of energy-sharing collisions-(i) energy switching with opposite nature for a particular soliton in two components and (ii) similar kind of energy switching for a given soliton in both components-result for two different choices of nonlinearity coefficients. The solitons appearing in the long-wave component always exhibit elastic collision whereas those of short-wave components exhibit standard elastic collisions only for a specific choice of parameters. We have also investigated the collision dynamics of asymptotic solitons in the original 3-CNLS system. For completeness, we explore the three-soliton interaction and demonstrate the pairwise nature of collisions and unravel the fascinating state restoration property.

Fault Tree Analysis Application for Safety and Reliability

NASA Technical Reports Server (NTRS)

Wallace, Dolores R.

2003-01-01

Many commercial software tools exist for fault tree analysis (FTA), an accepted method for mitigating risk in systems. The method embedded in the tools identifies a root as use in system components, but when software is identified as a root cause, it does not build trees into the software component. No commercial software tools have been built specifically for development and analysis of software fault trees. Research indicates that the methods of FTA could be applied to software, but the method is not practical without automated tool support. With appropriate automated tool support, software fault tree analysis (SFTA) may be a practical technique for identifying the underlying cause of software faults that may lead to critical system failures. We strive to demonstrate that existing commercial tools for FTA can be adapted for use with SFTA, and that applied to a safety-critical system, SFTA can be used to identify serious potential problems long before integrator and system testing.

Portable XRF and principal component analysis for bill characterization in forensic science.

PubMed

Appoloni, C R; Melquiades, F L

2014-02-01

Several modern techniques have been applied to prevent counterfeiting of money bills. The objective of this study was to demonstrate the potential of Portable X-ray Fluorescence (PXRF) technique and the multivariate analysis method of Principal Component Analysis (PCA) for classification of bills in order to use it in forensic science. Bills of Dollar, Euro and Real (Brazilian currency) were measured directly at different colored regions, without any previous preparation. Spectra interpretation allowed the identification of Ca, Ti, Fe, Cu, Sr, Y, Zr and Pb. PCA analysis separated the bills in three groups and subgroups among Brazilian currency. In conclusion, the samples were classified according to its origin identifying the elements responsible for differentiation and basic pigment composition. PXRF allied to multivariate discriminate methods is a promising technique for rapid and no destructive identification of false bills in forensic science. Copyright © 2013 Elsevier Ltd. All rights reserved.

Wavelength Selection Method Based on Differential Evolution for Precise Quantitative Analysis Using Terahertz Time-Domain Spectroscopy.

PubMed

Li, Zhi; Chen, Weidong; Lian, Feiyu; Ge, Hongyi; Guan, Aihong

2017-12-01

Quantitative analysis of component mixtures is an important application of terahertz time-domain spectroscopy (THz-TDS) and has attracted broad interest in recent research. Although the accuracy of quantitative analysis using THz-TDS is affected by a host of factors, wavelength selection from the sample's THz absorption spectrum is the most crucial component. The raw spectrum consists of signals from the sample and scattering and other random disturbances that can critically influence the quantitative accuracy. For precise quantitative analysis using THz-TDS, the signal from the sample needs to be retained while the scattering and other noise sources are eliminated. In this paper, a novel wavelength selection method based on differential evolution (DE) is investigated. By performing quantitative experiments on a series of binary amino acid mixtures using THz-TDS, we demonstrate the efficacy of the DE-based wavelength selection method, which yields an error rate below 5%.

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.

Comparison of conventional filtering and independent component analysis for artifact reduction in simultaneous gastric EMG and magnetogastrography from porcines.

PubMed

Irimia, Andrei; Richards, William O; Bradshaw, L Alan

2009-11-01

In this study, we perform a comparative study of independent component analysis (ICA) and conventional filtering (CF) for the purpose of artifact reduction from simultaneous gastric EMG and magnetogastrography (MGG). EMG/MGG data were acquired from ten anesthetized pigs by obtaining simultaneous recordings using serosal electrodes (EMG) as well as with a superconducting quantum interference device biomagnetometer (MGG). The analysis of MGG waveforms using ICA and CF indicates that ICA is superior to the CF method in its ability to extract respiration and cardiac artifacts from MGG recordings. A signal frequency analysis of ICA- and CF-processed data was also undertaken using waterfall plots, and it was determined that the two methods produce qualitatively comparable results. Through the use of simultaneous EMG/MGG, we were able to demonstrate the accuracy and trustworthiness of our results by comparison and cross-validation within the framework of a porcine model.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

Preliminary Geologic/spectral Analysis of LANDSAT-4 Thematic Mapper Data, Wind River/bighorn Basin Area, Wyoming

NASA Technical Reports Server (NTRS)

Lang, H. R.; Conel, J. E.; Paylor, E. D.

1984-01-01

A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.

Differentiation of essential oils in Atractylodes lancea and Atractylodes koreana by gas chromatography with mass spectrometry.

PubMed

Liu, Qiutao; Zhang, Shanshan; Yang, Xihui; Wang, Ruilin; Guo, Weiying; Kong, Weijun; Yang, Meihua

2016-12-01

Atractylodes rhizome is a valuable traditional Chinese medicinal herb that comprises complex several species whose essential oils are the primary pharmacologically active component. Essential oils of Atractylodes lancea and Atractylodes koreana were extracted by hydrodistillation, and the yield was determined. The average yield of essential oil obtained from A. lancea (2.91%) was higher than that from A. koreana (2.42%). The volatile components of the essential oils were then identified by a gas chromatography with mass spectrometry method that demonstrated good precision. The method showed clear differences in the numbers and contents of volatile components between the two species. 41 and 45 volatile components were identified in A. lancea and A. koreana, respectively. Atractylon (48.68%) was the primary volatile component in A. lancea, while eudesma-4(14)-en-11-ol (11.81%) was major in A. koreana. However, the most significant difference between A. lancea and A. koreana was the major component of atractylon and atractydin. Principal component analysis was utilized to reveal the correlation between volatile components and species, and the analysis was used to successfully discriminate between A. lancea and A. koreana samples. These results suggest that different species of Atractylodes rhizome may yield essential oils that differ significantly in content and composition. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Validation of a Scalable Solar Sailcraft

NASA Technical Reports Server (NTRS)

Murphy, D. M.

2006-01-01

The NASA In-Space Propulsion (ISP) program sponsored intensive solar sail technology and systems design, development, and hardware demonstration activities over the past 3 years. Efforts to validate a scalable solar sail system by functional demonstration in relevant environments, together with test-analysis correlation activities on a scalable solar sail system have recently been successfully completed. A review of the program, with descriptions of the design, results of testing, and analytical model validations of component and assembly functional, strength, stiffness, shape, and dynamic behavior are discussed. The scaled performance of the validated system is projected to demonstrate the applicability to flight demonstration and important NASA road-map missions.

X-45A in flight with F-18 #846 chase aircraft, during first GPS-guided weapon demonstration flight

NASA Image and Video Library

2002-12-19

The first X-45A Unmanned Combat Air Vehicle (UCAV) technology demonstrator completed its sixth flight on Dec. 19, 2002, raising its landing gear in flight for the first time. The X-45A flew for 40 minutes and reached an airspeed of 195 knots and an altitude of 7,500 feet. Dryden is supporting the DARPA/Boeing team in the design, development, integration, and demonstration of the critical technologies, processes, and system attributes leading to an operational UCAV system. Dryden support of the X-45A demonstrator system includes analysis, component development, simulations, ground and flight tests.

Principal component analysis and analysis of variance on the effects of Entellan New on the Raman spectra of fibers.

PubMed

Yu, Marcia M L; Sandercock, P Mark L

2012-01-01

During the forensic examination of textile fibers, fibers are usually mounted on glass slides for visual inspection and identification under the microscope. One method that has the capability to accurately identify single textile fibers without subsequent demounting is Raman microspectroscopy. The effect of the mountant Entellan New on the Raman spectra of fibers was investigated to determine if it is suitable for fiber analysis. Raman spectra of synthetic fibers mounted in three different ways were collected and subjected to multivariate analysis. Principal component analysis score plots revealed that while spectra from different fiber classes formed distinct groups, fibers of the same class formed a single group regardless of the mounting method. The spectra of bare fibers and those mounted in Entellan New were found to be statistically indistinguishable by analysis of variance calculations. These results demonstrate that fibers mounted in Entellan New may be identified directly by Raman microspectroscopy without further sample preparation. © 2011 American Academy of Forensic Sciences.

Determination and fingerprint analysis of steroidal saponins in roots of Liriope muscari (Decne.) L. H. Bailey by ultra high performance liquid chromatography coupled with ion trap time-of-flight mass spectrometry.

PubMed

Li, Yong-Wei; Qi, Jin; Wen-Zhang; Zhou, Shui-Ping; Yan-Wu; Yu, Bo-Yang

2014-07-01

Liriope muscari (Decne.) L. H. Bailey is a well-known traditional Chinese medicine used for treating cough and insomnia. There are few reports on the quality evaluation of this herb partly because the major steroid saponins are not readily identified by UV detectors and are not easily isolated due to the existence of many similar isomers. In this study, a qualitative and quantitative method was developed to analyze the major components in L. muscari (Decne.) L. H. Bailey roots. Sixteen components were deduced and identified primarily by the information obtained from ultra high performance liquid chromatography with ion-trap time-of-flight mass spectrometry. The method demonstrated the desired specificity, linearity, stability, precision, and accuracy for simultaneous determination of 15 constituents (13 steroidal glycosides, 25(R)-ruscogenin, and pentylbenzoate) in 26 samples from different origins. The fingerprint was established, and the evaluation was achieved using similarity analysis and principal component analysis of 15 fingerprint peaks from 26 samples by ultra high performance liquid chromatography. The results from similarity analysis were consistent with those of principal component analysis. All results suggest that the established method could be applied effectively to the determination of multi-ingredients and fingerprint analysis of steroid saponins for quality assessment and control of L. muscari (Decne.) L. H. Bailey. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion systems components

NASA Technical Reports Server (NTRS)

1991-01-01

Summarized here is the technical effort and computer code developed during the five year duration of the program for probabilistic structural analysis methods. The summary includes a brief description of the computer code manuals and a detailed description of code validation demonstration cases for random vibrations of a discharge duct, probabilistic material nonlinearities of a liquid oxygen post, and probabilistic buckling of a transfer tube liner.

Safety analysis report for packaging (onsite) steel drum

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

McCormick, W.A.

This Safety Analysis Report for Packaging (SARP) provides the analyses and evaluations necessary to demonstrate that the steel drum packaging system meets the transportation safety requirements of HNF-PRO-154, Responsibilities and Procedures for all Hazardous Material Shipments, for an onsite packaging containing Type B quantities of solid and liquid radioactive materials. The basic component of the steel drum packaging system is the 208 L (55-gal) steel drum.

Development and demonstration of manufacturing processes for fabricating graphite/LARC 160 polyimide structural elements

NASA Technical Reports Server (NTRS)

Frost, R. K.; Jones, J. S.; Dynes, P. J.; Wykes, D. H.

1981-01-01

The development and demonstration of manufacturing technologies for the structural application of Celion graphite/LARC-160 polyimide composite material is discussed. Process development and fabrication of demonstration components are discussed. Process development included establishing quality assurance of the basic composite material and processing, nondestructive inspection of fabricated components, developing processes for specific structural forms, and qualification of processes through mechanical testing. Demonstration components were fabricated. The demonstration components consisted of flat laminates, skin/stringer panels, honeycomb panels, chopped fiber compression moldings, and a technology demonstrator segment (TDS) representative of the space shuttle aft body flap.

Effect of high pressure treatment on the aging characteristics of Chinese liquor as evaluated by electronic nose and chemical analysis

NASA Astrophysics Data System (ADS)

Zhu, S. M.; Xu, M. L.; Ramaswamy, H. S.; Yang, M. Y.; Yu, Y.

2016-08-01

Several high pressure (HP) treatments (100-400 MPa 15 and 30 min) were applied to Chinese “Junchang” liquor, and aging characteristics of the liquor were evaluated. Results from the principal component analysis and the discriminant factor analysis of E-Nose demonstrated that HP treatment at 300 and 400 MPa resulted in significant (p < 0.05) changes in aroma components of the liquor. An increase in total ester content and a decrease in total acid content were observed for all treated samples (p < 0.05), which was verified by gas chromatography analysis. In addition, a slight decrease in alcohol content was found for HP treatment at 400 MPa for 30 min. These changes and trends were in accordance with the natural aging process of Chinese liquor. However, HP treatment caused a slight increase in solid content, which might be somewhat undesirable. Sensory evaluation results confirmed that favorable changes in color and flavor of Chinese liquor were induced by HP treatment; however, overall gaps still existed between the quality of treated and six-year aged samples. HP treatment demonstrated a potential to accelerate the natural aging process for Chinese liquor, but long term studies may be needed further to realize the full potential.

Inexpensive economical solar heating system for homes (un sistema economico de calefaccion solar para viviendas)

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

Alfred, J.W.; Shinn, J.M. Jr; Kirby, C.E.

1976-07-01

This report describes a low-cost solar home heating system to supplement the home-owner's present warm-air heating system. It has three parts: (1) A brief background on solar heating, (2) Langley's experience with a demonstration system, and (3) information for the home-owner who wishes to construct such a system. Instructions are given for a solar heating installation in which he supplies all labor needed to install off-the-shelf components estimated to cost $2000. These components, which include solar collector, heat exchanger, water pump, storage tank, piping, and controls to make the system completely automatic, are readily available at local lumber yards, hardwaremore » stores, and plumbing supply stores, and they are relatively simple to install. Manufacturers and prices of each component used and a rough cost analysis based on these prices are given for the owner's convenience. This report also gives performance data obtained from a demonstration system which has been built and tested at the Langley Research Center.« less

Describing patterns of weight changes using principal components analysis: results from the Action for Health in Diabetes (Look AHEAD) research group.

PubMed

Espeland, Mark A; Bray, George A; Neiberg, Rebecca; Rejeski, W Jack; Knowler, William C; Lang, Wei; Cheskin, Lawrence J; Williamson, Don; Lewis, C Beth; Wing, Rena

2009-10-01

To demonstrate how principal components analysis can be used to describe patterns of weight changes in response to an intensive lifestyle intervention. Principal components analysis was applied to monthly percent weight changes measured on 2,485 individuals enrolled in the lifestyle arm of the Action for Health in Diabetes (Look AHEAD) clinical trial. These individuals were 45 to 75 years of age, with type 2 diabetes and body mass indices greater than 25 kg/m(2). Associations between baseline characteristics and weight loss patterns were described using analyses of variance. Three components collectively accounted for 97.0% of total intrasubject variance: a gradually decelerating weight loss (88.8%), early versus late weight loss (6.6%), and a mid-year trough (1.6%). In agreement with previous reports, each of the baseline characteristics we examined had statistically significant relationships with weight loss patterns. As examples, males tended to have a steeper trajectory of percent weight loss and to lose weight more quickly than women. Individuals with higher hemoglobin A(1c) (glycosylated hemoglobin; HbA(1c)) tended to have a flatter trajectory of percent weight loss and to have mid-year troughs in weight loss compared to those with lower HbA(1c). Principal components analysis provided a coherent description of characteristic patterns of weight changes and is a useful vehicle for identifying their correlates and potentially for predicting weight control outcomes.

DISPLA: decision information system for procurement and logistics analysis

NASA Astrophysics Data System (ADS)

Calvo, Alberto B.; Danish, Alexander J.; Lamonakis, Gregory G.

2002-08-01

This paper describes an information-exchange system for Display systems acquisition and logistics support. DISPLA (Decision Information System for Procurement and Logistics Analysis) is an Internet-based system concept for bringing sellers (display system and component suppliers) and buyers (Government Program Offices and System Integrators) together in an electronic exchange to improve the acquisition and logistics analysis support of Flat Panel Displays for the military. A proof-of-concept demonstration is presented in this paper using sample data from vendor Web sites and Government data sources.

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.

Concept analysis of culture applied to nursing.

PubMed

Marzilli, Colleen

2014-01-01

Culture is an important concept, especially when applied to nursing. A concept analysis of culture is essential to understanding the meaning of the word. This article applies Rodgers' (2000) concept analysis template and provides a definition of the word culture as it applies to nursing practice. This article supplies examples of the concept of culture to aid the reader in understanding its application to nursing and includes a case study demonstrating components of culture that must be respected and included when providing health care.

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.

Atomic Force Microscopy Analysis of Nanocrystalline Patterns Fabricated Using Micromolding in Capillaries

ERIC Educational Resources Information Center

Lyman, Benjamin M.; Farmer, Orrin J.; Ramsey, Ryan D.; Lindsey, Samuel T.; Stout, Stephanie; Robison, Adam; Moore, Holly J.; Sanders, Wesley C.

2012-01-01

A cost-effective, hands-on laboratory exercise is described for demonstrating nanoscale fabrication at non-research-based educational institutions. The laboratory exercise also contains a component involving qualitative and quantitative surface characterization of student-fabricated nanoscale structures at institutions with on-site access to an…

Reconfigurable and responsive droplet-based compound micro-lenses.

PubMed

Nagelberg, Sara; Zarzar, Lauren D; Nicolas, Natalie; Subramanian, Kaushikaram; Kalow, Julia A; Sresht, Vishnu; Blankschtein, Daniel; Barbastathis, George; Kreysing, Moritz; Swager, Timothy M; Kolle, Mathias

2017-03-07

Micro-scale optical components play a crucial role in imaging and display technology, biosensing, beam shaping, optical switching, wavefront-analysis, and device miniaturization. Herein, we demonstrate liquid compound micro-lenses with dynamically tunable focal lengths. We employ bi-phase emulsion droplets fabricated from immiscible hydrocarbon and fluorocarbon liquids to form responsive micro-lenses that can be reconfigured to focus or scatter light, form real or virtual images, and display variable focal lengths. Experimental demonstrations of dynamic refractive control are complemented by theoretical analysis and wave-optical modelling. Additionally, we provide evidence of the micro-lenses' functionality for two potential applications-integral micro-scale imaging devices and light field display technology-thereby demonstrating both the fundamental characteristics and the promising opportunities for fluid-based dynamic refractive micro-scale compound lenses.

Reconfigurable and responsive droplet-based compound micro-lenses

PubMed Central

Nagelberg, Sara; Zarzar, Lauren D.; Nicolas, Natalie; Subramanian, Kaushikaram; Kalow, Julia A.; Sresht, Vishnu; Blankschtein, Daniel; Barbastathis, George; Kreysing, Moritz; Swager, Timothy M.; Kolle, Mathias

2017-01-01

Micro-scale optical components play a crucial role in imaging and display technology, biosensing, beam shaping, optical switching, wavefront-analysis, and device miniaturization. Herein, we demonstrate liquid compound micro-lenses with dynamically tunable focal lengths. We employ bi-phase emulsion droplets fabricated from immiscible hydrocarbon and fluorocarbon liquids to form responsive micro-lenses that can be reconfigured to focus or scatter light, form real or virtual images, and display variable focal lengths. Experimental demonstrations of dynamic refractive control are complemented by theoretical analysis and wave-optical modelling. Additionally, we provide evidence of the micro-lenses' functionality for two potential applications—integral micro-scale imaging devices and light field display technology—thereby demonstrating both the fundamental characteristics and the promising opportunities for fluid-based dynamic refractive micro-scale compound lenses. PMID:28266505

Applications of HPLC/MS in the analysis of traditional Chinese medicines

PubMed Central

Li, Miao; Hou, Xiao-Fang; Zhang, Jie; Wang, Si-Cen; Fu, Qiang; He, Lang-Chong

2012-01-01

In China, traditional Chinese medicines (TCMs) have been used in clinical applications for thousands of years. The successful hyphenation of high-Performance liquid chromatography (HPLC) and mass spectrometry (MS) has been applied widely in TCMs and biological samples analysis. Undoubtedly, HPLC/MS technique has facilitated the understanding of the treatment mechanism of TCMs. We reviewed more than 350 published papers within the last 5 years on HPLC/MS in the analysis of TCMs. The present review focused on the applications of HPLC/MS in the component analysis, metabolites analysis, and pharmacokinetics of TCMs etc. 50% of the literature is related to the component analysis of TCMs, which show that this field is the most populär type of research. In the metabolites analysis, HPLC coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry has been demonstrated to be the powerful tool for the characterization of structural features and fragmentation behavior patterns. This paper presented a brief overview of the applications of HPLC/MS in the analysis of TCMs. HPLC/MS in the fingerprint analysis is reviewed elsewhere. PMID:29403684

Application of fluorescence and PARAFAC to assess vertical distribution of subsurface hydrocarbons and dispersant during the Deepwater Horizon oil spill.

PubMed

Mendoza, Wilson G; Riemer, Daniel D; Zika, Rod G

2013-05-01

We evaluated the use of excitation and emission matrix (EEM) fluorescence and parallel factorial analysis (PARAFAC) modeling techniques for monitoring crude oil components in the water column. Four of the seven derived PARAFAC loadings were associated with the Macondo crude oil components. The other three components were associated with the dispersant, an unresolved component and colored dissolved organic matter (CDOM). The fluorescence of the associated benzene and naphthalene-like components of crude oil exhibited a maximum at ∼1200 m. The maximum fluorescence of the component associated with the dispersant (i.e., Corexit EC9500A) was observed at the same depth. The plume observed at this depth was attributed to the dispersed crude oil from the Deepwater Horizon oil spill. Results demonstrate the application of EEM and PARAFAC to simultaneously monitor selected PAH, dispersant-containing and humic-like fluorescence components in the oil spill region in the Gulf of Mexico.

Numerical and Experimental Study of Ti6Al4V Components Manufactured Using Powder Bed Fusion Additive Manufacturing

NASA Astrophysics Data System (ADS)

Zielinski, Jonas; Mindt, Hans-Wilfried; Düchting, Jan; Schleifenbaum, Johannes Henrich; Megahed, Mustafa

2017-12-01

Powder bed fusion additive manufacturing of titanium alloys is an interesting manufacturing route for many applications requiring high material strength combined with geometric complexity. Managing powder bed fusion challenges, including porosity, surface finish, distortions and residual stresses of as-built material, is the key to bringing the advantages of this process to production main stream. This paper discusses the application of experimental and numerical analysis towards optimizing the manufacturing process of a demonstration component. Powder characterization including assessment of the reusability, assessment of material consolidation and process window optimization is pursued prior to applying the identified optima to study the distortion and residual stresses of the demonstrator. Comparisons of numerical predictions with measurements show good correlations along the complete numerical chain.

General aviation crash safety program at Langley Research Center

NASA Technical Reports Server (NTRS)

Thomson, R. G.

1976-01-01

The purpose of the crash safety program is to support development of the technology to define and demonstrate new structural concepts for improved crash safety and occupant survivability in general aviation aircraft. The program involves three basic areas of research: full-scale crash simulation testing, nonlinear structural analyses necessary to predict failure modes and collapse mechanisms of the vehicle, and evaluation of energy absorption concepts for specific component design. Both analytical and experimental methods are being used to develop expertise in these areas. Analyses include both simplified procedures for estimating energy absorption capabilities and more complex computer programs for analysis of general airframe response. Full-scale tests of typical structures as well as tests on structural components are being used to verify the analyses and to demonstrate improved design concepts.

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.

The Distressed Brain: A Group Blind Source Separation Analysis on Tinnitus

PubMed Central

De Ridder, Dirk; Vanneste, Sven; Congedo, Marco

2011-01-01

Background Tinnitus, the perception of a sound without an external sound source, can lead to variable amounts of distress. Methodology In a group of tinnitus patients with variable amounts of tinnitus related distress, as measured by the Tinnitus Questionnaire (TQ), an electroencephalography (EEG) is performed, evaluating the patients' resting state electrical brain activity. This resting state electrical activity is compared with a control group and between patients with low (N = 30) and high distress (N = 25). The groups are homogeneous for tinnitus type, tinnitus duration or tinnitus laterality. A group blind source separation (BSS) analysis is performed using a large normative sample (N = 84), generating seven normative components to which high and low tinnitus patients are compared. A correlation analysis of the obtained normative components' relative power and distress is performed. Furthermore, the functional connectivity as reflected by lagged phase synchronization is analyzed between the brain areas defined by the components. Finally, a group BSS analysis on the Tinnitus group as a whole is performed. Conclusions Tinnitus can be characterized by at least four BSS components, two of which are posterior cingulate based, one based on the subgenual anterior cingulate and one based on the parahippocampus. Only the subgenual component correlates with distress. When performed on a normative sample, group BSS reveals that distress is characterized by two anterior cingulate based components. Spectral analysis of these components demonstrates that distress in tinnitus is related to alpha and beta changes in a network consisting of the subgenual anterior cingulate cortex extending to the pregenual and dorsal anterior cingulate cortex as well as the ventromedial prefrontal cortex/orbitofrontal cortex, insula, and parahippocampus. This network overlaps partially with brain areas implicated in distress in patients suffering from pain, functional somatic syndromes and posttraumatic stress disorder, and might therefore represent a specific distress network. PMID:21998628

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.

Full waveform inversion using a decomposed single frequency component from a spectrogram

NASA Astrophysics Data System (ADS)

Ha, Jiho; Kim, Seongpil; Koo, Namhyung; Kim, Young-Ju; Woo, Nam-Sub; Han, Sang-Mok; Chung, Wookeen; Shin, Sungryul; Shin, Changsoo; Lee, Jaejoon

2018-06-01

Although many full waveform inversion methods have been developed to construct velocity models of subsurface, various approaches have been presented to obtain an inversion result with long-wavelength features even though seismic data lacking low-frequency components were used. In this study, a new full waveform inversion algorithm was proposed to recover a long-wavelength velocity model that reflects the inherent characteristics of each frequency component of seismic data using a single-frequency component decomposed from the spectrogram. We utilized the wavelet transform method to obtain the spectrogram, and the decomposed signal from the spectrogram was used as transformed data. The Gauss-Newton method with the diagonal elements of an approximate Hessian matrix was used to update the model parameters at each iteration. Based on the results of time-frequency analysis in the spectrogram, numerical tests with some decomposed frequency components were performed using a modified SEG/EAGE salt dome (A-A‧) line to demonstrate the feasibility of the proposed inversion algorithm. This demonstrated that a reasonable inverted velocity model with long-wavelength structures can be obtained using a single frequency component. It was also confirmed that when strong noise occurs in part of the frequency band, it is feasible to obtain a long-wavelength velocity model from the noise data with a frequency component that is less affected by the noise. Finally, it was confirmed that the results obtained from the spectrogram inversion can be used as an initial velocity model in conventional inversion methods.

Structural damage continuous monitoring by using a data driven approach based on principal component analysis and cross-correlation analysis

NASA Astrophysics Data System (ADS)

Camacho-Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Moreno-Beltrán, Gustavo; Quiroga, Jabid

2017-05-01

Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross-correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in the structural response when damages occur. Two types of damage cases are studied: crack and leak for each structure, respectively. Experimental results show that the methodology is promising in the continuous monitoring of real structures.

Principal variance component analysis of crop composition data: a case study on herbicide-tolerant cotton.

PubMed

Harrison, Jay M; Howard, Delia; Malven, Marianne; Halls, Steven C; Culler, Angela H; Harrigan, George G; Wolfinger, Russell D

2013-07-03

Compositional studies on genetically modified (GM) and non-GM crops have consistently demonstrated that their respective levels of key nutrients and antinutrients are remarkably similar and that other factors such as germplasm and environment contribute more to compositional variability than transgenic breeding. We propose that graphical and statistical approaches that can provide meaningful evaluations of the relative impact of different factors to compositional variability may offer advantages over traditional frequentist testing. A case study on the novel application of principal variance component analysis (PVCA) in a compositional assessment of herbicide-tolerant GM cotton is presented. Results of the traditional analysis of variance approach confirmed the compositional equivalence of the GM and non-GM cotton. The multivariate approach of PVCA provided further information on the impact of location and germplasm on compositional variability relative to GM.

Laser-induced breakdown spectroscopy is a reliable method for urinary stone analysis

PubMed Central

Mutlu, Nazım; Çiftçi, Seyfettin; Gülecen, Turgay; Öztoprak, Belgin Genç; Demir, Arif

2016-01-01

Objective We compared laser-induced breakdown spectroscopy (LIBS) with the traditionally used and recommended X-ray diffraction technique (XRD) for urinary stone analysis. Material and methods In total, 65 patients with urinary calculi were enrolled in this prospective study. Stones were obtained after surgical or extracorporeal shockwave lithotripsy procedures. All stones were divided into two equal pieces. One sample was analyzed by XRD and the other by LIBS. The results were compared by the kappa (κ) and Spearman’s correlation coefficient (rho) tests. Results Using LIBS, 95 components were identified from 65 stones, while XRD identified 88 components. LIBS identified 40 stones with a single pure component, 20 stones with two different components, and 5 stones with three components. XRD demonstrated 42 stones with a single component, 22 stones with two different components, and only 1 stone with three different components. There was a strong relationship in the detection of stone types between LIBS and XRD for stones components (Spearman rho, 0.866; p<0.001). There was excellent agreement between the two techniques among 38 patients with pure stones (κ index, 0.910; Spearman rho, 0.916; p<0.001). Conclusion Our study indicates that LIBS is a valid and reliable technique for determining urinary stone composition. Moreover, it is a simple, low-cost, and nondestructive technique. LIBS can be safely used in routine daily practice if our results are supported by studies with larger numbers of patients. PMID:27011877

Scaling Analysis Techniques to Establish Experimental Infrastructure for Component, Subsystem, and Integrated System Testing

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

Sabharwall, Piyush; O'Brien, James E.; McKellar, Michael G.

2015-03-01

Hybrid energy system research has the potential to expand the application for nuclear reactor technology beyond electricity. The purpose of this research is to reduce both technical and economic risks associated with energy systems of the future. Nuclear hybrid energy systems (NHES) mitigate the variability of renewable energy sources, provide opportunities to produce revenue from different product streams, and avoid capital inefficiencies by matching electrical output to demand by using excess generation capacity for other purposes when it is available. An essential step in the commercialization and deployment of this advanced technology is scaled testing to demonstrate integrated dynamic performancemore » of advanced systems and components when risks cannot be mitigated adequately by analysis or simulation. Further testing in a prototypical environment is needed for validation and higher confidence. This research supports the development of advanced nuclear reactor technology and NHES, and their adaptation to commercial industrial applications that will potentially advance U.S. energy security, economy, and reliability and further reduce carbon emissions. Experimental infrastructure development for testing and feasibility studies of coupled systems can similarly support other projects having similar developmental needs and can generate data required for validation of models in thermal energy storage and transport, energy, and conversion process development. Experiments performed in the Systems Integration Laboratory will acquire performance data, identify scalability issues, and quantify technology gaps and needs for various hybrid or other energy systems. This report discusses detailed scaling (component and integrated system) and heat transfer figures of merit that will establish the experimental infrastructure for component, subsystem, and integrated system testing to advance the technology readiness of components and systems to the level required for commercial application and demonstration under NHES.« less

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.

Measuring research influence on drug policy: a case example of two epidemiological monitoring systems.

PubMed

Ritter, Alison; Lancaster, Kari

2013-01-01

Assessing the extent to which drug research influences and impacts upon policy decision-making needs to go beyond bibliometric analysis of academic citations. Policy makers do not necessarily access the academic literature, and policy processes are largely iterative and rely on interactions and relationships. Furthermore, media representation of research contributes to public opinion and can influence policy uptake. In this context, assessing research influence involves examining the extent to which a research project is taken up in policy documents, used within policy processes, and disseminated via the media. This three component approach is demonstrated using a case example of two ongoing illicit drug monitoring systems: the Illicit Drug Reporting System (IDRS) and the Ecstasy and related Drugs Reporting System (EDRS). Systematic searches for reference to the IDRS and/or EDRS within policy documents, across multiple policy processes (such as parliamentary inquiries) and in the media, in conjunction with analysis of the types of mentions in these three sources, enables an analysis of policy influence. The context for the research is also described as the foundation for the approach. The application of the three component approach to the case study demonstrates a practical and systematic retrospective approach to measure drug research influence. For example, the ways in which the IDRS and EDRS were mentioned in policy documents demonstrated research utilisation. Policy processes were inclusive of IDRS and EDRS findings, while the media analysis revealed only a small contribution in the context of wider media reporting. Consistent with theories of policy processes, assessing the extent of research influence requires a systematic analysis of policy documents and processes. Development of such analyses and associated methods will better equip researchers to evaluate the impact of research. Copyright © 2012 Elsevier B.V. All rights reserved.

Air-coupled laser vibrometry: analysis and applications.

PubMed

Solodov, Igor; Döring, Daniel; Busse, Gerd

2009-03-01

Acousto-optic interaction between a narrow laser beam and acoustic waves in air is analyzed theoretically. The photoelastic relation in air is used to derive the phase modulation of laser light in air-coupled reflection vibrometry induced by angular spatial spectral components comprising the acoustic beam. Maximum interaction was found for the zero spatial acoustic component propagating normal to the laser beam. The angular dependence of the imaging efficiency is determined for the axial and nonaxial acoustic components with the regard for the laser beam steering in the scanning mode. The sensitivity of air-coupled vibrometry is compared with conventional "Doppler" reflection vibrometry. Applications of the methodology for visualization of linear and nonlinear air-coupled fields are demonstrated.

Program for plasma-sprayed self-lubricating coatings

NASA Technical Reports Server (NTRS)

Walther, G. C.

1979-01-01

A method for preparing composite powders of the three coating components was developed and a procedure that can be used in applying uniform coatings of the composite powders was demonstrated. Composite powders were prepared by adjusting particle sizes of the components and employing a small amount of monoaluminum phosphate as an inorganic binder. Quantitative microscopy (image analysis) was found to be a convenient method of characterizing the composition of the multiphase plasma-sprayed coatings. Area percentages and distribution of the components were readily obtained by this method. The adhesive strength of the coating to a nickel-chromium alloy substrate was increased by about 40 percent by a heat treatment of 20 hours at 650 C.

A novel principal component analysis for spatially misaligned multivariate air pollution data.

PubMed

Jandarov, Roman A; Sheppard, Lianne A; Sampson, Paul D; Szpiro, Adam A

2017-01-01

We propose novel methods for predictive (sparse) PCA with spatially misaligned data. These methods identify principal component loading vectors that explain as much variability in the observed data as possible, while also ensuring the corresponding principal component scores can be predicted accurately by means of spatial statistics at locations where air pollution measurements are not available. This will make it possible to identify important mixtures of air pollutants and to quantify their health effects in cohort studies, where currently available methods cannot be used. We demonstrate the utility of predictive (sparse) PCA in simulated data and apply the approach to annual averages of particulate matter speciation data from national Environmental Protection Agency (EPA) regulatory monitors.

The approximation of anomalous magnetic field by array of magnetized rods

NASA Astrophysics Data System (ADS)

Denis, Byzov; Lev, Muravyev; Natalia, Fedorova

2017-07-01

The method for calculation the vertical component of an anomalous magnetic field from its absolute value is presented. Conversion is based on the approximation of magnetic induction module anomalies by the set of singular sources and the subsequent calculation for the vertical component of the field with the chosen distribution. The rods that are uniformly magnetized along their axis were used as a set of singular sources. Applicability analysis of different methods of nonlinear optimization for solving the given task was carried out. The algorithm is implemented using the parallel computing technology on the NVidia GPU. The approximation and calculation of vertical component is demonstrated for regional magnetic field of North Eurasia territories.

Successful Completion of FY18/Q1 ASC L2 Milestone 6355: Electrical Analysis Calibration Workflow Capability Demonstration.

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

Copps, Kevin D.

The Sandia Analysis Workbench (SAW) project has developed and deployed a production capability for SIERRA computational mechanics analysis workflows. However, the electrical analysis workflow capability requirements have only been demonstrated in early prototype states, with no real capability deployed for analysts’ use. This milestone aims to improve the electrical analysis workflow capability (via SAW and related tools) and deploy it for ongoing use. We propose to focus on a QASPR electrical analysis calibration workflow use case. We will include a number of new capabilities (versus today’s SAW), such as: 1) support for the XYCE code workflow component, 2) data managementmore » coupled to electrical workflow, 3) human-in-theloop workflow capability, and 4) electrical analysis workflow capability deployed on the restricted (and possibly classified) network at Sandia. While far from the complete set of capabilities required for electrical analysis workflow over the long term, this is a substantial first step toward full production support for the electrical analysts.« less

Chandra Interactive Analysis of Observations (CIAO)

NASA Technical Reports Server (NTRS)

Dobrzycki, Adam

2000-01-01

The Chandra (formerly AXAF) telescope, launched on July 23, 1999, provides X-rays data with unprecedented spatial and spectral resolution. As part of the Chandra scientific support, the Chandra X-ray Observatory Center provides a new data analysis system, CIAO ("Chandra Interactive Analysis of Observations"). We will present the main components of the system: "First Look" analysis; SHERPA: a multi-dimensional, multi-mission modeling and fitting application; Chandra Imaging and Plotting System; Detect package-source detection algorithms; and DM package generic data manipulation tools, We will set up a demonstration of the portable version of the system and show examples of Chandra Data Analysis.

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.

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.

Identifying fluorescent pulp mill effluent in the Gulf of Maine and its watershed

USGS Publications Warehouse

Cawley, Kaelin M.; Butler, Kenna D.; Aiken, George R.; Larsen, Laurel G.; Huntington, Thomas G.; McKnight, Diane M.

2012-01-01

Using fluorescence spectroscopy and parallel factor analysis (PARAFAC) we characterized and modeled the fluorescence properties of dissolved organic matter (DOM) in samples from the Penobscot River, Androscoggin River, Penobscot Bay, and the Gulf of Maine (GoM). We analyzed excitation-emission matrices (EEMs) using an existing PARAFAC model (Cory and McKnight, 2005) and created a system-specific model with seven components (GoM PARAFAC). The GoM PARAFAC model contained six components similar to those in other PARAFAC models and one unique component with a spectrum similar to a residual found using the Cory and McKnight (2005) model. The unique component was abundant in samples from the Androscoggin River immediately downstream of a pulp mill effluent release site. The detection of a PARAFAC component associated with an anthropogenic source of DOM, such as pulp mill effluent, demonstrates the importance for rigorously analyzing PARAFAC residuals and developing system-specific models.

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

PVD TBC experience on GE aircraft engines

NASA Technical Reports Server (NTRS)

Bartz, A.; Mariocchi, A.; Wortman, D. J.

1995-01-01

The higher performance levels of modern gas turbine engines present significant challenges in the reliability of materials in the turbine. The increased engine temperatures required to achieve the higher performance levels reduce the strength of the materials used in the turbine sections of the engine. Various forms of Thermal Barrier Coatings (TBC's) have been used for many years to increase the reliability of gas turbine engine components. Recent experience with the Physical Vapor Deposition (PVD) process using ceramic material has demonstrated success in extending the service life of turbine blades and nozzles. Engine test results of turbine components with a 125 micrometer (0.005 in) PVD TBC have demonstrated component operating temperatures of 56-83 C (100-150 F) lower than uncoated components. Engine testing has also revealed the TBC is susceptible to high angle particle impact damage. Sand particles and other engine debris impact the TBC surface at the leading edge of airfoils and fracture the PVD columns. As the impacting continues the TBC erodes away in local areas. Analysis of the eroded areas has shown a slight increase in temperature over a fully coated area, however, a significant temperature reduction was realized over an airfoil without any TBC.

PVD TBC experience on GE aircraft engines

NASA Technical Reports Server (NTRS)

Maricocchi, Antonio; Bartz, Andi; Wortman, David

1995-01-01

The higher performance levels of modern gas turbine engines present significant challenges in the reliability of materials in the turbine. The increased engine temperatures required to achieve the higher performance levels reduce the strength of the materials used in the turbine sections of the engine. Various forms of thermal barrier coatings (TBC's) have been used for many years to increase the reliability of gas turbine engine components. Recent experience with the physical vapor deposition (PVD) process using ceramic material has demonstrated success in extending the service life of turbine blades and nozzles. Engine test results of turbine components with a 125 micron (0.005 in) PVD TBC have demonstrated component operating temperatures of 56-83 C (100-150 F) lower than non-PVD TBC components. Engine testing has also revealed the TBC is susceptible to high angle particle impact damage. Sand particles and other engine debris impact the TBC surface at the leading edge of airfoils and fracture the PVD columns. As the impacting continues, the TBC erodes away in local areas. Analysis of the eroded areas has shown a slight increase in temperature over a fully coated area, however a significant temperature reduction was realized over an airfoil without TBC.

PVD TBC experience on GE aircraft engines

NASA Astrophysics Data System (ADS)

Maricocchi, A.; Bartz, A.; Wortman, D.

1997-06-01

The higher performance levels of modern gas turbine engines present significant challenges in the reli-ability of materials in the turbine. The increased engine temperatures required to achieve the higher per-formance levels reduce the strength of the materials used in the turbine sections of the engine. Various forms of thermal barrier coatings have been used for many years to increase the reliability of gas turbine engine components. Recent experience with the physical vapor deposition process using ceramic material has demonstrated success in extending the service life of turbine blades and nozzles. Engine test results of turbine components with a 125 μm (0.005 in.) PVD TBC have demonstrated component operating tem-peratures of 56 to 83 °C (100 to 150 °F) lower than non-PVD TBC components. Engine testing has also revealed that TBCs are susceptible to high angle particle impact damage. Sand particles and other engine debris impact the TBC surface at the leading edge of airfoils and fracture the PVD columns. As the impacting continues, the TBC erodes in local areas. Analysis of the eroded areas has shown a slight increase in temperature over a fully coated area ; however, a significant temperature reduc-tion was realized over an airfoil without TBC.

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

Symplectic geometry spectrum regression for prediction of noisy time series

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates; Sivakumar, Bellie; Mengersen, Kerrie

2016-05-01

We present the symplectic geometry spectrum regression (SGSR) technique as well as a regularized method based on SGSR for prediction of nonlinear time series. The main tool of analysis is the symplectic geometry spectrum analysis, which decomposes a time series into the sum of a small number of independent and interpretable components. The key to successful regularization is to damp higher order symplectic geometry spectrum components. The effectiveness of SGSR and its superiority over local approximation using ordinary least squares are demonstrated through prediction of two noisy synthetic chaotic time series (Lorenz and Rössler series), and then tested for prediction of three real-world data sets (Mississippi River flow data and electromyographic and mechanomyographic signal recorded from human body).

Ceramic component reliability with the restructured NASA/CARES computer program

NASA Technical Reports Server (NTRS)

Powers, Lynn M.; Starlinger, Alois; Gyekenyesi, John P.

1992-01-01

The Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design program on statistical fast fracture reliability and monolithic ceramic components is enhanced to include the use of a neutral data base, two-dimensional modeling, and variable problem size. The data base allows for the efficient transfer of element stresses, temperatures, and volumes/areas from the finite element output to the reliability analysis program. Elements are divided to insure a direct correspondence between the subelements and the Gaussian integration points. Two-dimensional modeling is accomplished by assessing the volume flaw reliability with shell elements. To demonstrate the improvements in the algorithm, example problems are selected from a round-robin conducted by WELFEP (WEakest Link failure probability prediction by Finite Element Postprocessors).

CARES/LIFE Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Janosik, Lesley A.; Gyekenyesi, John P.

2003-01-01

This manual describes the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction (CARES/LIFE) computer program. The program calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. CARES/LIFE is an extension of the CARES (Ceramic Analysis and Reliability Evaluation of Structures) computer program. The program uses results from MSC/NASTRAN, ABAQUS, and ANSYS finite element analysis programs to evaluate component reliability due to inherent surface and/or volume type flaws. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing the power law, Paris law, or Walker law. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled by using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. The probabilistic time-dependent theories used in CARES/LIFE, along with the input and output for CARES/LIFE, are described. Example problems to demonstrate various features of the program are also included.

Design, Analysis and R&D of the EAST In-Vessel Components

NASA Astrophysics Data System (ADS)

Yao, Damao; Bao, Liman; Li, Jiangang; Song, Yuntao; Chen, Wenge; Du, Shijun; Hu, Qingsheng; Wei, Jing; Xie, Han; Liu, Xufeng; Cao, Lei; Zhou, Zibo; Chen, Junling; Mao, Xinqiao; Wang, Shengming; Zhu, Ning; Weng, Peide; Wan, Yuanxi

2008-06-01

In-vessel components are important parts of the EAST superconducting tokamak. They include the plasma facing components, passive plates, cryo-pumps, in-vessel coils, etc. The structural design, analysis and related R&D have been completed. The divertor is designed in an up-down symmetric configuration to accommodate both double null and single null plasma operation. Passive plates are used for plasma movement control. In-vessel coils are used for the active control of plasma vertical movements. Each cryo-pump can provide an approximately 45 m3/s pumping rate at a pressure of 10-1 Pa for particle exhaust. Analysis shows that, when a plasma current of 1 MA disrupts in 3 ms, the EM loads caused by the eddy current and the halo current in a vertical displacement event (VDE) will not generate an unacceptable stress on the divertor structure. The bolted divertor thermal structure with an active cooling system can sustain a load of 2 MW/m2 up to a 60 s operation if the plasma facing surface temperature is limited to 1500 °C. Thermal testing and structural optimization testing were conducted to demonstrate the analysis results.

Adiabatic diesel engine component development: Reference engine for on-highway applications

NASA Technical Reports Server (NTRS)

Hakim, Nabil S.

1986-01-01

The main objectives were to select an advanced low heat rejection diesel reference engine (ADRE) and to carry out systems analysis and design. The ADRE concept selection consisted of: (1) rated point performance optimization; (2) study of various exhaust energy recovery scenarios; (3) components, systems and engine configuration studies; and (4) life cycle cost estimates of the ADRE economic worth. The resulting ADRE design proposed a reciprocator with many advanced features for the 1995 technology demonstration time frame. These included ceramic air gap insulated hot section structural components, high temperature tribology treatments, nonmechanical (camless) valve actuation systems, and elimination of the cylinder head gasket. ADRE system analysis and design resulted in more definition of the engine systems. These systems include: (1) electro-hydraulic valve actuation, (2) electronic common rail injection system; (3) engine electronic control; (4) power transfer for accessory drives and exhaust energy recovery systems; and (5) truck installation. Tribology and performance assessments were also carried out. Finite element and probability of survival analyses were undertaken for the ceramic low heat rejection component.

Hybrid computational and experimental approach for the study and optimization of mechanical components

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1998-05-01

Increased demands on the performance and efficiency of mechanical components impose challenges on their engineering design and optimization, especially when new and more demanding applications must be developed in relatively short periods of time while satisfying design objectives, as well as cost and manufacturability. In addition, reliability and durability must be taken into consideration. As a consequence, effective quantitative methodologies, computational and experimental, should be applied in the study and optimization of mechanical components. Computational investigations enable parametric studies and the determination of critical engineering design conditions, while experimental investigations, especially those using optical techniques, provide qualitative and quantitative information on the actual response of the structure of interest to the applied load and boundary conditions. We discuss a hybrid experimental and computational approach for investigation and optimization of mechanical components. The approach is based on analytical, computational, and experimental resolutions methodologies in the form of computational, noninvasive optical techniques, and fringe prediction analysis tools. Practical application of the hybrid approach is illustrated with representative examples that demonstrate the viability of the approach as an effective engineering tool for analysis and optimization.

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.

Selective One-Dimensional Total Correlation Spectroscopy Nuclear Magnetic Resonance Experiments for a Rapid Identification of Minor Components in the Lipid Fraction of Milk and Dairy Products: Toward Spin Chromatography?

PubMed

Papaemmanouil, Christina; Tsiafoulis, Constantinos G; Alivertis, Dimitrios; Tzamaloukas, Ouranios; Miltiadou, Despoina; Tzakos, Andreas G; Gerothanassis, Ioannis P

2015-06-10

We report a rapid, direct, and unequivocal spin-chromatographic separation and identification of minor components in the lipid fraction of milk and common dairy products with the use of selective one-dimensional (1D) total correlation spectroscopy (TOCSY) nuclear magnetic resonance (NMR) experiments. The method allows for the complete backbone spin-coupling network to be elucidated even in strongly overlapped regions and in the presence of major components from 4 × 10(2) to 3 × 10(3) stronger NMR signal intensities. The proposed spin-chromatography method does not require any derivatization steps for the lipid fraction, is selective with excellent resolution, is sensitive with quantitation capability, and compares favorably to two-dimensional (2D) TOCSY and gas chromatography-mass spectrometry (GC-MS) methods of analysis. The results of the present study demonstrated that the 1D TOCSY NMR spin-chromatography method can become a procedure of primary interest in food analysis and generally in complex mixture analysis.

Analysis of free modeling predictions by RBO aleph in CASP11.

PubMed

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

2016-09-01

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

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

PubMed

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

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.

Incorporating principal component analysis into air quality ...

EPA Pesticide Factsheets

The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Principal Component Analysis (PCA) with the intent of motivating its use by the evaluation community. One of the main objectives of PCA is to identify, through data reduction, the recurring and independent modes of variations (or signals) within a very large dataset, thereby summarizing the essential information of that dataset so that meaningful and descriptive conclusions can be made. In this demonstration, PCA is applied to a simple evaluation metric – the model bias associated with EPA's Community Multi-scale Air Quality (CMAQ) model when compared to weekly observations of sulfate (SO42−) and ammonium (NH4+) ambient air concentrations measured by the Clean Air Status and Trends Network (CASTNet). The advantages of using this technique are demonstrated as it identifies strong and systematic patterns of CMAQ model bias across a myriad of spatial and temporal scales that are neither constrained to geopolitical boundaries nor monthly/seasonal time periods (a limitation of many current studies). The technique also identifies locations (station–grid cell pairs) that are used as indicators for a more thorough diagnostic evaluation thereby hastening and facilitating understanding of the prob

Systems Engineering Provides Successful High Temperature Steam Electrolysis Project

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

Charles V. Park; Emmanuel Ohene Opare, Jr.

2011-06-01

This paper describes two Systems Engineering Studies completed at the Idaho National Laboratory (INL) to support development of the High Temperature Stream Electrolysis (HTSE) process. HTSE produces hydrogen from water using nuclear power and was selected by the Department of Energy (DOE) for integration with the Next Generation Nuclear Plant (NGNP). The first study was a reliability, availability and maintainability (RAM) analysis to identify critical areas for technology development based on available information regarding expected component performance. An HTSE process baseline flowsheet at commercial scale was used as a basis. The NGNP project also established a process and capability tomore » perform future RAM analyses. The analysis identified which components had the greatest impact on HTSE process availability and indicated that the HTSE process could achieve over 90% availability. The second study developed a series of life-cycle cost estimates for the various scale-ups required to demonstrate the HTSE process. Both studies were useful in identifying near- and long-term efforts necessary for successful HTSE process deployment. The size of demonstrations to support scale-up was refined, which is essential to estimate near- and long-term cost and schedule. The life-cycle funding profile, with high-level allocations, was identified as the program transitions from experiment scale R&D to engineering scale demonstration.« less

[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.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

A hybrid symplectic principal component analysis and central tendency measure method for detection of determinism in noisy time series with application to mechanomyography.

PubMed

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

We present a hybrid symplectic geometry and central tendency measure (CTM) method for detection of determinism in noisy time series. CTM is effective for detecting determinism in short time series and has been applied in many areas of nonlinear analysis. However, its performance significantly degrades in the presence of strong noise. In order to circumvent this difficulty, we propose to use symplectic principal component analysis (SPCA), a new chaotic signal de-noising method, as the first step to recover the system dynamics. CTM is then applied to determine whether the time series arises from a stochastic process or has a deterministic component. Results from numerical experiments, ranging from six benchmark deterministic models to 1/f noise, suggest that the hybrid method can significantly improve detection of determinism in noisy time series by about 20 dB when the data are contaminated by Gaussian noise. Furthermore, we apply our algorithm to study the mechanomyographic (MMG) signals arising from contraction of human skeletal muscle. Results obtained from the hybrid symplectic principal component analysis and central tendency measure demonstrate that the skeletal muscle motor unit dynamics can indeed be deterministic, in agreement with previous studies. However, the conventional CTM method was not able to definitely detect the underlying deterministic dynamics. This result on MMG signal analysis is helpful in understanding neuromuscular control mechanisms and developing MMG-based engineering control applications.

Automatic classification of artifactual ICA-components for artifact removal in EEG signals.

PubMed

Winkler, Irene; Haufe, Stefan; Tangermann, Michael

2011-08-02

Artifacts contained in EEG recordings hamper both, the visual interpretation by experts as well as the algorithmic processing and analysis (e.g. for Brain-Computer Interfaces (BCI) or for Mental State Monitoring). While hand-optimized selection of source components derived from Independent Component Analysis (ICA) to clean EEG data is widespread, the field could greatly profit from automated solutions based on Machine Learning methods. Existing ICA-based removal strategies depend on explicit recordings of an individual's artifacts or have not been shown to reliably identify muscle artifacts. We propose an automatic method for the classification of general artifactual source components. They are estimated by TDSEP, an ICA method that takes temporal correlations into account. The linear classifier is based on an optimized feature subset determined by a Linear Programming Machine (LPM). The subset is composed of features from the frequency-, the spatial- and temporal domain. A subject independent classifier was trained on 640 TDSEP components (reaction time (RT) study, n = 12) that were hand labeled by experts as artifactual or brain sources and tested on 1080 new components of RT data of the same study. Generalization was tested on new data from two studies (auditory Event Related Potential (ERP) paradigm, n = 18; motor imagery BCI paradigm, n = 80) that used data with different channel setups and from new subjects. Based on six features only, the optimized linear classifier performed on level with the inter-expert disagreement (<10% Mean Squared Error (MSE)) on the RT data. On data of the auditory ERP study, the same pre-calculated classifier generalized well and achieved 15% MSE. On data of the motor imagery paradigm, we demonstrate that the discriminant information used for BCI is preserved when removing up to 60% of the most artifactual source components. We propose a universal and efficient classifier of ICA components for the subject independent removal of artifacts from EEG data. Based on linear methods, it is applicable for different electrode placements and supports the introspection of results. Trained on expert ratings of large data sets, it is not restricted to the detection of eye- and muscle artifacts. Its performance and generalization ability is demonstrated on data of different EEG studies.

A Comprehensive Two-Dimensional Retention Time Alignment Algorithm To Enhance Chemometric Analysis of Comprehensive Two-Dimensional Separation Data

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

Pierce, Karisa M.; Wood, Lianna F.; Wright, Bob W.

2005-12-01

A comprehensive two-dimensional (2D) retention time alignment algorithm was developed using a novel indexing scheme. The algorithm is termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the separation information in both dimensions. Although the algorithm is demonstrated by correcting comprehensive two-dimensional gas chromatography (GC x GC) data, the algorithm is designed to correct shifting in all forms of 2D separations, such as LC x LC, LC x CE, CE x CE, and LC x GC. This 2D alignment algorithm was applied to three different data sets composed of replicate GC x GCmore » separations of (1) three 22-component control mixtures, (2) three gasoline samples, and (3) three diesel samples. The three data sets were collected using slightly different temperature or pressure programs to engender significant retention time shifting in the raw data and then demonstrate subsequent corrections of that shifting upon comprehensive 2D alignment of the data sets. Thirty 12-min GC x GC separations from three 22-component control mixtures were used to evaluate the 2D alignment performance (10 runs/mixture). The average standard deviation of the first column retention time improved 5-fold from 0.020 min (before alignment) to 0.004 min (after alignment). Concurrently, the average standard deviation of second column retention time improved 4-fold from 3.5 ms (before alignment) to 0.8 ms (after alignment). Alignment of the 30 control mixture chromatograms took 20 min. The quantitative integrity of the GC x GC data following 2D alignment was also investigated. The mean integrated signal was determined for all components in the three 22-component mixtures for all 30 replicates. The average percent difference in the integrated signal for each component before and after alignment was 2.6%. Singular value decomposition (SVD) was applied to the 22-component control mixture data before and after alignment to show the restoration of trilinearity to the data, since trilinearity benefits chemometric analysis. By applying comprehensive 2D retention time alignment to all three data sets (control mixtures, gasoline samples, and diesel samples), classification by principal component analysis (PCA) substantially improved, resulting in 100% accurate scores clustering.« less

14 CFR 415.129 - Flight safety system test data.

Code of Federal Regulations, 2012 CFR

2012-01-01

..., acceptance, age surveillance, and preflight testing of a flight safety system and its subsystems and..., subsystem, and component testing requirements of part 417 of this chapter and appendix E to part 417 of this... demonstrate similarity by performing the analysis required by appendix E of part 417 of this chapter. The...

14 CFR 415.129 - Flight safety system test data.

Code of Federal Regulations, 2011 CFR

2011-01-01

..., acceptance, age surveillance, and preflight testing of a flight safety system and its subsystems and..., subsystem, and component testing requirements of part 417 of this chapter and appendix E to part 417 of this... demonstrate similarity by performing the analysis required by appendix E of part 417 of this chapter. The...

14 CFR 415.129 - Flight safety system test data.

Code of Federal Regulations, 2013 CFR

2013-01-01

..., acceptance, age surveillance, and preflight testing of a flight safety system and its subsystems and..., subsystem, and component testing requirements of part 417 of this chapter and appendix E to part 417 of this... demonstrate similarity by performing the analysis required by appendix E of part 417 of this chapter. The...

14 CFR 415.129 - Flight safety system test data.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., acceptance, age surveillance, and preflight testing of a flight safety system and its subsystems and..., subsystem, and component testing requirements of part 417 of this chapter and appendix E to part 417 of this... demonstrate similarity by performing the analysis required by appendix E of part 417 of this chapter. The...

14 CFR 415.129 - Flight safety system test data.

Code of Federal Regulations, 2014 CFR

2014-01-01

..., acceptance, age surveillance, and preflight testing of a flight safety system and its subsystems and..., subsystem, and component testing requirements of part 417 of this chapter and appendix E to part 417 of this... demonstrate similarity by performing the analysis required by appendix E of part 417 of this chapter. The...

The Three Domains of Disgust Scale: Factor Structure, Psychometric Properties, and Conceptual Limitations

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Adams, Thomas; Ciesielski, Bethany; David, Bieke; Sarawgi, Shivali; Broman-Fulks, Joshua

2012-01-01

This investigation examined the measurement properties of the Three Domains of Disgust Scale (TDDS). Principal components analysis in Study 1 (n = 206) revealed three factors of Pathogen, Sexual, and Moral Disgust that demonstrated excellent reliability, including test-retest over 12 weeks. Confirmatory factor analyses in Study 2 (n = 406)…

Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method

NASA Technical Reports Server (NTRS)

Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.

2014-01-01

A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.

DOE-FG02-00ER62797 Final Report

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

Sweedler, J.V.

2004-12-01

Specific Aims The overall goal of this proposal has been to develop and interface a new technology, molecular gates, with microfabricated systems to add an important capability to microfabricated DNA measurement systems. This project specifically focused on demonstrating how molecular gates could be used to capture a single analyte band, among a stream of bands from a separation or a flow injection analysis experiment, and release it for later measurement, thus allowing further manipulations on the selected analyte. Since the original proposal, the molecular gate concept has been greatly expanded to allow the gates to be used as externally controllablemore » intelligent interconnects in multilayer microfluidic networks. We have demonstrated: (1) the ability of the molecular gates to work with a much wider range of biological molecules including DNA, proteins and small metabolites; and (2) the capability of performing an electrophoretic separation and sequestering individual picoliter volume components (or even classes of components) into separate channels for further analysis. Both capabilities will enable characterization of small mass amounts of complex mixtures of DNA, proteins and even small molecules--allowing them to be further separated and chemically characterized.« less

Development, Demonstration, and Analysis of an Integrated Iodine Hall Thruster Feed System

NASA Technical Reports Server (NTRS)

Polzin, Kurt A.; Peeples, Steven R.; Burt, Adam O.; Martin, Adam K.; Martinez, Armando; Seixal, Joao F.; Mauro, Stephanie

2016-01-01

The design of an in-space iodine-vapor-fed Hall effect thruster propellant management system is described. The solid-iodine propellant tank has unique issues associated with the microgravity environment, requiring a solution where the iodine is maintained in intimate thermal contact with the heated tank walls. The flow control valves required alterations from earlier iterations to survive for extended periods of time in the corrosive iodine-vapor environment. Materials have been selected for the entire feed system that can chemically resist the iodine vapor, with the design now featuring Hastelloy or Inconel for almost all the wetted components. An integrated iodine feed system/Hall thruster demonstration unit was fabricated and tested, with all control being handled by an onboard electronics card specifically designed to operate the feed system. Structural analysis shows that the feed system can survive launch loads after the implementation of some minor reinforcement. Flow modeling, while still requiring significant additional validation, is presented to show its potential in capturing the behavior of components in this low-flow, low-pressure system.

Reliability considerations for the total strain range version of strainrange partitioning

NASA Technical Reports Server (NTRS)

Wirsching, P. H.; Wu, Y. T.

1984-01-01

A proposed total strainrange version of strainrange partitioning (SRP) to enhance the manner in which SRP is applied to life prediction is considered with emphasis on how advanced reliability technology can be applied to perform risk analysis and to derive safety check expressions. Uncertainties existing in the design factors associated with life prediction of a component which experiences the combined effects of creep and fatigue can be identified. Examples illustrate how reliability analyses of such a component can be performed when all design factors in the SRP model are random variables reflecting these uncertainties. The Rackwitz-Fiessler and Wu algorithms are used and estimates of the safety index and the probablity of failure are demonstrated for a SRP problem. Methods of analysis of creep-fatigue data with emphasis on procedures for producing synoptic statistics are presented. An attempt to demonstrate the importance of the contribution of the uncertainties associated with small sample sizes (fatique data) to risk estimates is discussed. The procedure for deriving a safety check expression for possible use in a design criteria document is presented.

Seasonal characterization of CDOM for lakes in semiarid regions of Northeast China using excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC)

NASA Astrophysics Data System (ADS)

Zhao, Ying; Song, Kaishan; Wen, Zhidan; Li, Lin; Zang, Shuying; Shao, Tiantian; Li, Sijia; Du, Jia

2016-03-01

The seasonal characteristics of fluorescent components in chromophoric dissolved organic matter (CDOM) for lakes in the semiarid region of Northeast China were examined by excitation-emission matrix (EEM) spectra and parallel factor analysis (PARAFAC). Two humic-like (C1 and C2) and protein-like (C3 and C4) components were identified using PARAFAC. The average fluorescence intensity of the four components differed under seasonal variation from June and August 2013 to February and April 2014. Components 1 and 2 exhibited a strong linear correlation (R2 = 0.628). Significantly positive linear relationships between CDOM absorption coefficients a(254) (R2 = 0.72, 0.46, p < 0.01), a(280) (R2 = 0.77, 0.47, p < 0.01), a(350) (R2 = 0.76, 0.78, p < 0.01) and Fmax for two humic-like components (C1 and C2) were exhibited, respectively. A significant relationship (R2 = 0.930) was found between salinity and dissolved organic carbon (DOC). However, almost no obvious correlation was found between salinity and EEM-PARAFAC-extracted components except for C3 (R2 = 0.469). Results from this investigation demonstrate that the EEM-PARAFAC technique can be used to evaluate the seasonal dynamics of CDOM fluorescent components for inland waters in the semiarid regions of Northeast China, and to quantify CDOM components for other waters with similar environmental conditions.

Six components observations of local earthquakes during the 2016 Central Italy seismic sequence

NASA Astrophysics Data System (ADS)

Simonelli, A.; Bernauer, F.; Chow, B.; Braun, T.; Wassermann, J. M.; Igel, H.

2017-12-01

For many years the seismological community has looked for a reliable, sensitive, broadband three-component portable rotational sensor. In this preliminary study, we show the possibility of measuring and extracting relevant seismological information from local earthquakes. We employ portable three-component rotational sensors, insensitive to translations, which operate on optical interferometry principles (Sagnac effect). Multiple sensors recording redundantly add significance to the measurements.During the Central Italy seismic sequence in November 2016, we deployed two portable fiber-optic gyroscopes (BlueSeis3A from iXBlue and LCG demonstrator from LITEF) and a broadband seismometer in Colfiorito, Italy. We present here the six-component observations, with analysis of rotational (three redundant components) and translational (three components) ground motions, generated by earthquakes at local distances. For each seismic event, we compare coherence between rotational sensors and estimate a back azimuth consistent with theoretical values. We also estimate Love and Rayleigh wave phase velocities in the 5 to 10 Hz frequency range.

Identification of trace additives in polymer materials by attenuated total reflection Fourier transform infrared mapping coupled with multivariate curve resolution

NASA Astrophysics Data System (ADS)

Li, Qian; Tang, Yongjiao; Yan, Zhiwei; Zhang, Pudun

2017-06-01

Although multivariate curve resolution (MCR) has been applied to the analysis of Fourier transform infrared (FTIR) imaging, it is still problematic to determine the number of components. The reported methods at present tend to cause the components of low concentration missed. In this paper a new idea was proposed to resolve this problem. First, MCR calculation was repeated by increasing the number of components sequentially, then each retrieved pure spectrum of as-resulted MCR component was directly compared with a real-world pixel spectrum of the local high concentration in the corresponding MCR map. One component was affirmed only if the characteristic bands of the MCR component had been included in its pixel spectrum. This idea was applied to attenuated total reflection (ATR)/FTIR mapping for identifying the trace additives in blind polymer materials and satisfactory results were acquired. The successful demonstration of this novel approach opens up new possibilities for analyzing additives in polymer materials.

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.

Resting State Functional Connectivity in Mild Traumatic Brain Injury at the Acute Stage: Independent Component and Seed-Based Analyses

PubMed Central

Iraji, Armin; Benson, Randall R.; Welch, Robert D.; O'Neil, Brian J.; Woodard, John L.; Imran Ayaz, Syed; Kulek, Andrew; Mika, Valerie; Medado, Patrick; Soltanian-Zadeh, Hamid; Liu, Tianming; Haacke, E. Mark

2015-01-01

Abstract Mild traumatic brain injury (mTBI) accounts for more than 1 million emergency visits each year. Most of the injured stay in the emergency department for a few hours and are discharged home without a specific follow-up plan because of their negative clinical structural imaging. Advanced magnetic resonance imaging (MRI), particularly functional MRI (fMRI), has been reported as being sensitive to functional disturbances after brain injury. In this study, a cohort of 12 patients with mTBI were prospectively recruited from the emergency department of our local Level-1 trauma center for an advanced MRI scan at the acute stage. Sixteen age- and sex-matched controls were also recruited for comparison. Both group-based and individual-based independent component analysis of resting-state fMRI (rsfMRI) demonstrated reduced functional connectivity in both posterior cingulate cortex (PCC) and precuneus regions in comparison with controls, which is part of the default mode network (DMN). Further seed-based analysis confirmed reduced functional connectivity in these two regions and also demonstrated increased connectivity between these regions and other regions of the brain in mTBI. Seed-based analysis using the thalamus, hippocampus, and amygdala regions further demonstrated increased functional connectivity between these regions and other regions of the brain, particularly in the frontal lobe, in mTBI. Our data demonstrate alterations of multiple brain networks at the resting state, particularly increased functional connectivity in the frontal lobe, in response to brain concussion at the acute stage. Resting-state functional connectivity of the DMN could serve as a potential biomarker for improved detection of mTBI in the acute setting. PMID:25285363

Transactive System: Part II: Analysis of Two Pilot Transactive Systems using Foundational Theory and Metrics

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

Lian, Jianming; Sun, Y.; Kalsi, Karanjit

This document is the second of a two-part report. Part 1 reviewed several demonstrations of transactive control and compared them in terms of their payoff functions, control decisions, information privacy, and mathematical solution concepts. It was suggested in Part 1 that these four listed components should be adopted for meaningful comparison and design of future transactive systems. Part 2 proposes qualitative and quantitative metrics that will be needed to compare alternative transactive systems. It then uses the analysis and design principles from Part 1 while conducting more in-depth analysis of two transactive demonstrations: the American Electric Power (AEP) gridSMART Demonstration,more » which used a double –auction market mechanism, and a consensus method like that used in the Pacific Northwest Smart Grid Demonstration. Ultimately, metrics must be devised and used to meaningfully compare alternative transactive systems. One significant contribution of this report is an observation that the decision function used for thermostat control in the AEP gridSMART Demonstration has superior performance if its decision function is recast to more accurately reflect the power that will be used under for thermostatic control under alternative market outcomes.« less

Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

PubMed Central

Lin, Nan; Jiang, Junhai; Guo, Shicheng; Xiong, Momiao

2015-01-01

Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

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.

Fluorescence characterization of fractionated dissolved organic matter in the five tributaries of Poyang Lake, China.

PubMed

Yan, Caixia; Liu, Huihui; Sheng, Yanru; Huang, Xian; Nie, Minghua; Huang, Qi; Baalousha, Mohammed

2018-10-01

Characterization of natural colloids is the key to understand pollutant fate and transport in the environment. The present study investigates the relationship between size and fluorescence properties of colloidal organic matter (COM) from five tributaries of Poyang Lake. Colloids were size-fractionated using cross-flow ultrafiltration and their fluorescence properties were measured by three-dimensional excitation-emission matrix fluorescence spectroscopy (3D-EEM). Parallel factor analysis (PARAFAC) and/or Self-organizing map (SOM) were applied to assess fluorescence properties as proxy indicators for the different size of colloids. PARAFAC analysis identified four fluorescence components including three humic-like components (C1-C3) and a protein-like component (C4). These four fluorescence components, and in particular the protein-like component, are primarily present in <1 kDa phase. For the colloidal fractions (1-10 kDa, 10-100 kDa, and 100 kDa-0.7 μm), the majority of fluorophores are associated with the smallest size fraction. SOM analysis demonstrated that relatively high fluorescence intensity and aromaticity occur primarily in <1 kDa phase, followed by 1-10 kDa colloids. Coupling PARAFAC and SOM facilitate the visualization and interpretation of the relationship between colloidal size and fluorescence properties with fewer input variables, shorter running time, higher reliability, and nondestructive results. Fluorescence indices analysis reveals that the smallest colloidal fraction (1-10 kDa) was dominated by higher humified and less autochthonous COM. Copyright © 2018 Elsevier B.V. All rights reserved.

Ultraviolet photography of the in vivo human cornea unmasks the Hudson-Stähli line and physiologic vortex patterns.

PubMed

Every, Sean G; Leader, John P; Molteno, Anthony C B; Bevin, Tui H; Sanderson, Gordon

2005-10-01

To perform ultraviolet (UV) macrophotography of the normal in vivo human cornea, establishing biometric data of the major component of UV absorption for comparison with the Hudson-Stähli (HS) line, the distribution of iron demonstrated by Perl stain, and cases of typical amiodarone keratopathy. Nonrandomized comparative case series of UV photographs of 76 normal corneas (group 1) and 16 corneas with typical amiodarone keratopathy (group 2). Image-analysis software was used to grade the major component of UV absorption for slope and the coordinates of its points of intersection with the vertical corneal meridian and inflection. In group 1 the major component had a mean slope of 5.8 degrees, sloping down from nasal to temporal cornea. The mean coordinates of points of intersection with the vertical corneal meridian and inflection were (0, 0.30) and (0.02, 0.31), respectively. No significant differences between groups 1 and 2 were found for slope (P = 0.155), intersection with the vertical corneal meridian (P = 0.517), and point of inflection (P = 0.344). The major component of UV absorption was consistent with published characteristics of the HS line, and coincidence of UV absorption and Perl-stained iron was demonstrated in one corneal button. A vortex pattern of UV absorption was observed in all corneas. UV photography demonstrates subclinical corneal iron, confirming its deposition in an integrated HS line/vortex pattern. Coincident iron and amiodarone deposition occurs in amiodarone keratopathy.

Proton transfer reaction mass spectrometry: on-line trace gas analysis at the ppb level

NASA Astrophysics Data System (ADS)

Hansel, A.; Jordan, A.; Holzinger, R.; Prazeller, P.; Vogel, W.; Lindinger, W.

1995-11-01

A system for trace gas analysis using proton transfer reaction mass spectrometry (PTR-MS) has been developed which allows for on-line measurements of components with concentrations as low as 1 ppb. The method is based on reactions of H3O+ ions, which perform non-dissociative proton transfer to most of the common organic trace constituents but do not react with any of the components present in clean air. Examples of analysis of breath taken from smokers and non-smokers as well as from patients suffering from cirrhosis of the liver, and of air in buildings as well as of ambient air taken at a road crossing demonstrate the wide range of applicability of this method. An enhanced level of acetonitrile in the breath is a most suitable indicator that a person is a smoker. Enhanced levels of propanol strongly indicate that a person has a severe liver deficiency.

Analysis of stress fields and elastic energies in the vicinity of nanograin boundaries using the disclination approach

NASA Astrophysics Data System (ADS)

Sukhanov, Ivan I.; Ditenberg, Ivan A.

2017-12-01

The paper provides a theoretical analysis of elastic stresses and elastic energy distribution in nanostructured metal materials in the vicinity of nanograin boundaries with a high partial disclination density. The analysis demonstrates the stress field distribution in disclination grain boundary configurations as a function of nanograin size, taking into account the superposition of these stresses in screening the disclination pile-ups. It is found that the principal stress tensor components reach maximum values only in disclination planes P ≈ E/25 and that the stress gradients peak at nodal points ∂P/∂x ≈ 0.08E nm-1. The shear stress components are localized within the physical grain size, and the specific elastic energy distribution for such configurations reveals characteristic local maxima which can be the cause for physical broadening of nanograin boundaries.

19F DOSY NMR analysis for spin systems with nJFF couplings.

PubMed

Dal Poggetto, Guilherme; Favaro, Denize C; Nilsson, Mathias; Morris, Gareth A; Tormena, Cláudio F

2014-04-01

NMR is a powerful method for identification and quantification of drug components and contaminations. These problems present themselves as mixtures, and here, one of the most powerful tools is DOSY. DOSY works best when there is no spectral overlap between components, so drugs containing fluorine substituents are well-suited for DOSY analysis as (19)F spectra are typically very sparse. Here, we demonstrate the use of a modified (19)F DOSY experiment (on the basis of the Oneshot sequences) for various fluorinated benzenes. For compounds with significant (n) JFF coupling constants, as is common, the undesirable J-modulation can be efficiently suppressed using the Oneshot45 pulse sequence. This investigation highlights (19)F DOSY as a valuable and robust method for analysis of molecular systems containing fluorine atoms even where there are large fluorine-fluorine couplings. Copyright © 2014 John Wiley & Sons, Ltd.

Across-task priming revisited: response and task conflicts disentangled using ex-Gaussian distribution analysis.

PubMed

Moutsopoulou, Karolina; Waszak, Florian

2012-04-01

The differential effects of task and response conflict in priming paradigms where associations are strengthened between a stimulus, a task, and a response have been demonstrated in recent years with neuroimaging methods. However, such effects are not easily disentangled with only measurements of behavior, such as reaction times (RTs). Here, we report the application of ex-Gaussian distribution analysis on task-switching RT data and show that conflict related to stimulus-response associations retrieved after a switch of tasks is reflected in the Gaussian component. By contrast, conflict related to the retrieval of stimulus-task associations is reflected in the exponential component. Our data confirm that the retrieval of stimulus-task and -response associations affects behavior differently. Ex-Gaussian distribution analysis is a useful tool for pulling apart these different levels of associative priming that are not distinguishable in analyses of RT means.

Multiaxial Cyclic Thermoplasticity Analysis with Besseling's Subvolume Method

NASA Technical Reports Server (NTRS)

Mcknight, R. L.

1983-01-01

A modification was formulated to Besseling's Subvolume Method to allow it to use multilinear stress-strain curves which are temperature dependent to perform cyclic thermoplasticity analyses. This method automotically reproduces certain aspects of real material behavior important in the analysis of Aircraft Gas Turbine Engine (AGTE) components. These include the Bauschinger effect, cross-hardening, and memory. This constitutive equation was implemented in a finite element computer program called CYANIDE. Subsequently, classical time dependent plasticity (creep) was added to the program. Since its inception, this program was assessed against laboratory and component testing and engine experience. The ability of this program to simulate AGTE material response characteristics was verified by this experience and its utility in providing data for life analyses was demonstrated. In this area of life analysis, the multiaxial thermoplasticity capabilities of the method have proved a match for the actual AGTE life experience.

Granger causality for state-space models

NASA Astrophysics Data System (ADS)

Barnett, Lionel; Seth, Anil K.

2015-04-01

Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations—commonplace in application domains as diverse as climate science, econometrics, and the neurosciences—induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

[The analytical reliability of clinical laboratory information and role of the standards in its support].

PubMed

Men'shikov, V V

2012-12-01

The article deals with the factors impacting the reliability of clinical laboratory information. The differences of qualities of laboratory analysis tools produced by various manufacturers are discussed. These characteristics are the causes of discrepancy of the results of laboratory analyses of the same analite. The role of the reference system in supporting the comparability of laboratory analysis results is demonstrated. The project of national standard is presented to regulate the requirements to standards and calibrators for analysis of qualitative and non-metrical characteristics of components of biomaterials.

Hyper-X Hot Structures Comparison of Thermal Analysis and Flight Data

NASA Technical Reports Server (NTRS)

Amundsen, Ruth M.; Leonard, Charles P.; Bruce, Walter E., III

2004-01-01

The Hyper-X (X-43A) program is a flight experiment to demonstrate scramjet performance and operability under controlled powered free-flight conditions at Mach 7 and 10. The Mach 7 flight was successfully completed on March 27, 2004. Thermocouple instrumentation in the hot structures (nose, horizontal tail, and vertical tail) recorded the flight thermal response of these components. Preflight thermal analysis was performed for design and risk assessment purposes. This paper will present a comparison of the preflight thermal analysis and the recorded flight data.

Using Machine Learning Techniques in the Analysis of Oceanographic Data

NASA Astrophysics Data System (ADS)

Falcinelli, K. E.; Abuomar, S.

2017-12-01

Acoustic Doppler Current Profilers (ADCPs) are oceanographic tools capable of collecting large amounts of current profile data. Using unsupervised machine learning techniques such as principal component analysis, fuzzy c-means clustering, and self-organizing maps, patterns and trends in an ADCP dataset are found. Cluster validity algorithms such as visual assessment of cluster tendency and clustering index are used to determine the optimal number of clusters in the ADCP dataset. These techniques prove to be useful in analysis of ADCP data and demonstrate potential for future use in other oceanographic applications.

Classification using NMR-based metabolomics of Sophora flavescens grown in Japan and China.

PubMed

Suzuki, Ryuichiro; Ikeda, Yuriko; Yamamoto, Akari; Saima, Toyoe; Fujita, Tatsuya; Fukuda, Tatsuo; Fukuda, Eriko; Baba, Masaki; Okada, Yoshihito; Shirataki, Yoshiaki

2012-11-01

We demonstrate that NMR-based metabolomics can be used to identify the country of growth (Japan or China) of Sophora flavescens plants. Principle Component Analysis (PCA) conducted on extracts of S. flavescens grown in China provided data distinct from that of extracts of plants grown in Japan. Loading plot analysis showed signals characteristic of Japanese S. flavescens. NMR analyses showed these signals to be due to kurarinol (1) and kushenol H (2). These compounds were confirmed by HPLC analysis to be distinctive markers for Japanese S. flavescens.

Effect of high pressure treatment on the aging characteristics of Chinese liquor as evaluated by electronic nose and chemical analysis

PubMed Central

Zhu, S. M.; Xu, M. L.; Ramaswamy, H. S.; Yang, M. Y.; Yu, Y.

2016-01-01

Several high pressure (HP) treatments (100–400 MPa; 15 and 30 min) were applied to Chinese “Junchang” liquor, and aging characteristics of the liquor were evaluated. Results from the principal component analysis and the discriminant factor analysis of E-Nose demonstrated that HP treatment at 300 and 400 MPa resulted in significant (p < 0.05) changes in aroma components of the liquor. An increase in total ester content and a decrease in total acid content were observed for all treated samples (p < 0.05), which was verified by gas chromatography analysis. In addition, a slight decrease in alcohol content was found for HP treatment at 400 MPa for 30 min. These changes and trends were in accordance with the natural aging process of Chinese liquor. However, HP treatment caused a slight increase in solid content, which might be somewhat undesirable. Sensory evaluation results confirmed that favorable changes in color and flavor of Chinese liquor were induced by HP treatment; however, overall gaps still existed between the quality of treated and six-year aged samples. HP treatment demonstrated a potential to accelerate the natural aging process for Chinese liquor, but long term studies may be needed further to realize the full potential. PMID:27484292

Comprehensive two-dimensional liquid chromatography separations of pharmaceutical samples using dual Fused-Core columns in the 2nd dimension.

PubMed

Alexander, Anthony J; Ma, Lianjia

2009-02-27

This paper focuses on the application of RPLC x RPLC to pharmaceutical analysis and addresses the specific problem of separating co-eluting impurities/degradation products that maybe "hidden" within the peak envelope of the active pharmaceutical ingredient (API) and thus may escape detection by conventional methods. A comprehensive two-dimensional liquid chromatograph (LC x LC) was constructed from commercially available HPLC equipment. This system utilizes two independently configurable 2nd dimension binary pumping systems to deliver independent flow rates, gradient profiles and mobile phase compositions to dual Fused-Core secondary columns. Very fast gradient separations (30s total cycle time) were achieved at ambient temperature without excessive backpressure and without compromising optimal 1st dimension sampling rates. The operation of the interface is demonstrated for the analysis of a 1mg/ml standard mixture containing 0.05% of a minor component. The practicality of using RPLC x RPLC for the analysis of actual co-eluting pharmaceutical degradation products, by exploiting pH-induced changes in selectivity, is also demonstrated using a three component mixture. This mixture (an API, an oxidation product of the API at 1.0%, w/w, and a photo degradant of the API at 0.5%, w/w) was used to assess the stability indicating nature of an established LC method for analysis of the API.

Percolator: Scalable Pattern Discovery in Dynamic Graphs

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

Choudhury, Sutanay; Purohit, Sumit; Lin, Peng

We demonstrate Percolator, a distributed system for graph pattern discovery in dynamic graphs. In contrast to conventional mining systems, Percolator advocates efficient pattern mining schemes that (1) support pattern detection with keywords; (2) integrate incremental and parallel pattern mining; and (3) support analytical queries such as trend analysis. The core idea of Percolator is to dynamically decide and verify a small fraction of patterns and their in- stances that must be inspected in response to buffered updates in dynamic graphs, with a total mining cost independent of graph size. We demonstrate a) the feasibility of incremental pattern mining by walkingmore » through each component of Percolator, b) the efficiency and scalability of Percolator over the sheer size of real-world dynamic graphs, and c) how the user-friendly GUI of Percolator inter- acts with users to support keyword-based queries that detect, browse and inspect trending patterns. We also demonstrate two user cases of Percolator, in social media trend analysis and academic collaboration analysis, respectively.« less

Effects of cumulative illness severity on hippocampal gray matter volume in major depression: a voxel-based morphometry study.

PubMed

Zaremba, Dario; Enneking, Verena; Meinert, Susanne; Förster, Katharina; Bürger, Christian; Dohm, Katharina; Grotegerd, Dominik; Redlich, Ronny; Dietsche, Bruno; Krug, Axel; Kircher, Tilo; Kugel, Harald; Heindel, Walter; Baune, Bernhard T; Arolt, Volker; Dannlowski, Udo

2018-02-08

Patients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients' cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression. We estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients' cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients' individual component scores on hippocampal volume. Principal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients' Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores. Variables associated with patients' history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients' cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.

[Fluorescence excitation-emission matrix spectroscopy of CDOM from Yundang Lagoon and its indication for organic pollution].

PubMed

Zhuo, Jian-Fu; Guo, Wei-Dong; Deng, Xun; Zhang, Zhi-Ying; Xu, Jing; Huang, Ling-Feng

2010-06-01

Fluorescence excitation-emission matrix spectroscopy (EEMs) combined with absorption spectroscopy were applied to study the optical properties of CDOM samples from highly-polluted Yundang Lagoon in Xiamen in order to demonstrate the feasibility of using these spectral properties as a tracer of the degree of organic pollution in similar polluted coastal waters. Surface water samples were collected from 13 stations 4 times during April and May, 2008. Parallel factor analysis (PARAFAC) model was used to resolve the EEMs of CDOM. Five separate fluorescent components were identified, including two humic-like components (C1: 240, 325/422 nm; C5: 260, 380/474 nm), two protein-like components (C2: 225, 275/350 nm; C4: 240, 300/354 nm) and one xenobiotic-like component (C3: 225/342 nm), which could be used as a good tracer for the input of the anthropogenic organic, pollutants. The concentrations of component C3 and dissolved organic carbon (DOC) are much higher near the inlet of sewage discharge, demonstrating that the discharge of surrounding sewage is a major source of organic pollutants in Yundang Lagoon. CDOM absorption coefficient alpha (280) and the score of humic-like component C1 showed significant linear relationships with COD(Mn), and a strong positive correlation was also found between the score of protein-like component C2 and BOD5. This suggested that the optical properties of CDOM may provide a fast in-situ way to monitor the variation of the water quality in Yundang Lagoon and that of similar polluted coastal waters.

Thermal Analysis of Iodine Satellite (iSAT)

NASA Technical Reports Server (NTRS)

Mauro, Stephanie

2015-01-01

This paper presents the progress of the thermal analysis and design of the Iodine Satellite (iSAT). The purpose of the iSAT spacecraft (SC) is to demonstrate the ability of the iodine Hall Thruster propulsion system throughout a one year mission in an effort to mature the system for use on future satellites. The benefit of this propulsion system is that it uses a propellant, iodine, that is easy to store and provides a high thrust-to-mass ratio. The spacecraft will also act as a bus for an earth observation payload, the Long Wave Infrared (LWIR) Camera. Four phases of the mission, determined to either be critical to achieving requirements or phases of thermal concern, are modeled. The phases are the Right Ascension of the Ascending Node (RAAN) Change, Altitude Reduction, De-Orbit, and Science Phases. Each phase was modeled in a worst case hot environment and the coldest phase, the Science Phase, was also modeled in a worst case cold environment. The thermal environments of the spacecraft are especially important to model because iSAT has a very high power density. The satellite is the size of a 12 unit cubesat, and dissipates slightly more than 75 Watts of power as heat at times. The maximum temperatures for several components are above their maximum operational limit for one or more cases. The analysis done for the first Design and Analysis Cycle (DAC1) showed that many components were above or within 5 degrees Centigrade of their maximum operation limit. The battery is a component of concern because although it is not over its operational temperature limit, efficiency greatly decreases if it operates at the currently predicted temperatures. In the second Design and Analysis Cycle (DAC2), many steps were taken to mitigate the overheating of components, including isolating several high temperature components, removal of components, and rearrangement of systems. These changes have greatly increased the thermal margin available.

Independent component analysis-based source-level hyperlink analysis for two-person neuroscience studies

NASA Astrophysics Data System (ADS)

Zhao, Yang; Dai, Rui-Na; Xiao, Xiang; Zhang, Zong; Duan, Lian; Li, Zheng; Zhu, Chao-Zhe

2017-02-01

Two-person neuroscience, a perspective in understanding human social cognition and interaction, involves designing immersive social interaction experiments as well as simultaneously recording brain activity of two or more subjects, a process termed "hyperscanning." Using newly developed imaging techniques, the interbrain connectivity or hyperlink of various types of social interaction has been revealed. Functional near-infrared spectroscopy (fNIRS)-hyperscanning provides a more naturalistic environment for experimental paradigms of social interaction and has recently drawn much attention. However, most fNIRS-hyperscanning studies have computed hyperlinks using sensor data directly while ignoring the fact that the sensor-level signals contain confounding noises, which may lead to a loss of sensitivity and specificity in hyperlink analysis. In this study, on the basis of independent component analysis (ICA), a source-level analysis framework is proposed to investigate the hyperlinks in a fNIRS two-person neuroscience study. The performance of five widely used ICA algorithms in extracting sources of interaction was compared in simulative datasets, and increased sensitivity and specificity of hyperlink analysis by our proposed method were demonstrated in both simulative and real two-person experiments.

Time-dependent inertia analysis of vehicle mechanisms

NASA Astrophysics Data System (ADS)

Salmon, James Lee

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

Development of a Dynamically Configurable,Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation

NASA Technical Reports Server (NTRS)

Afjeh, Abdollah A.; Reed, John A.

2003-01-01

This research is aimed at developing a neiv and advanced simulation framework that will significantly improve the overall efficiency of aerospace systems design and development. This objective will be accomplished through an innovative integration of object-oriented and Web-based technologies ivith both new and proven simulation methodologies. The basic approach involves Ihree major areas of research: Aerospace system and component representation using a hierarchical object-oriented component model which enables the use of multimodels and enforces component interoperability. Collaborative software environment that streamlines the process of developing, sharing and integrating aerospace design and analysis models. . Development of a distributed infrastructure which enables Web-based exchange of models to simplify the collaborative design process, and to support computationally intensive aerospace design and analysis processes. Research for the first year dealt with the design of the basic architecture and supporting infrastructure, an initial implementation of that design, and a demonstration of its application to an example aircraft engine system simulation.

Design and optimization of the CFRP mirror components

NASA Astrophysics Data System (ADS)

Wei, Lei; Zhang, Lei; Gong, Xiaoxue

2017-09-01

As carbon fiber reinforced polymer (CFRP) material has been developed and demonstrated as an effective material in lightweight telescope reflector manufacturing recently, the authors of this article have extended to apply this material on the lightweight space camera mirror design and fabrication. By CFRP composite laminate design and optimization using finite element method (FEM) analysis, a spherical mirror with φ316 mm diameter whose core cell reinforcement is an isogrid configuration is fabricated. Compared with traditional ways of applying ultra-low-expansion glass (ULE) on the CFRP mirror surface, the method of nickel electroplating on the surface effectively reduces the processing cost and difficulty of the CFRP mirror. Through the FEM analysis, the first order resonance frequency of the CFRP mirror components reaches up to 652.3 Hz. Under gravity affection coupling with +5°C temperature rising, the mirror surface shape root-mean-square values (RMS) at the optical axis horizontal state is 5.74 nm, which meets mechanical and optical requirements of the mirror components on space camera.

Antimycobacterial action of a new glycolipid-peptide complex obtained from extracellular metabolites of Raoultella ornithinolytica.

PubMed

Fiołka, Marta J; Grzywnowicz, Krzysztof; Mendyk, Ewaryst; Zagaja, Mirosław; Szewczyk, Rafał; Rawski, Michał; Keller, Radosław; Rzymowska, Jolanta; Wydrych, Jerzy

2015-12-01

In this paper, an antimycobacterial component of extracellular metabolites of a gut bacterium Raoultella ornithinolytica from D. veneta earthworms was isolated and its antimycobacterial action was tested using Mycobacterium smegmatis. After incubation with the complex obtained, formation of pores and furrows in cell walls was observed using microscopic techniques. The cells lost their shape, stuck together and formed clusters. Surface-enhanced Raman spectroscopy analysis showed that, after incubation, the complex was attached to the cell walls of the Mycobacterium. Analyses of the component performed with Fourier transform infrared spectroscopy demonstrated high similarity to a bacteriocin nisin, but energy dispersive X-ray spectroscopy analysis revealed differences in the elemental composition of this antimicrobial peptide. The component with antimycobacterial activity was identified using mass spectrometry techniques as a glycolipid-peptide complex. As it exhibits no cytotoxicity on normal human fibroblasts, the glycolipid-peptide complex appears to be a promising compound for investigations of its activity against pathogenic mycobacteria. © 2015 APMIS. Published by John Wiley & Sons Ltd.

Demixed principal component analysis of neural population data

PubMed Central

Kobak, Dmitry; Brendel, Wieland; Constantinidis, Christos; Feierstein, Claudia E; Kepecs, Adam; Mainen, Zachary F; Qi, Xue-Lian; Romo, Ranulfo; Uchida, Naoshige; Machens, Christian K

2016-01-01

Neurons in higher cortical areas, such as the prefrontal cortex, are often tuned to a variety of sensory and motor variables, and are therefore said to display mixed selectivity. This complexity of single neuron responses can obscure what information these areas represent and how it is represented. Here we demonstrate the advantages of a new dimensionality reduction technique, demixed principal component analysis (dPCA), that decomposes population activity into a few components. In addition to systematically capturing the majority of the variance of the data, dPCA also exposes the dependence of the neural representation on task parameters such as stimuli, decisions, or rewards. To illustrate our method we reanalyze population data from four datasets comprising different species, different cortical areas and different experimental tasks. In each case, dPCA provides a concise way of visualizing the data that summarizes the task-dependent features of the population response in a single figure. DOI: http://dx.doi.org/10.7554/eLife.10989.001 PMID:27067378

Calculating system reliability with SRFYDO

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

Morzinski, Jerome; Anderson - Cook, Christine M; Klamann, Richard M

2010-01-01

SRFYDO is a process for estimating reliability of complex systems. Using information from all applicable sources, including full-system (flight) data, component test data, and expert (engineering) judgment, SRFYDO produces reliability estimates and predictions. It is appropriate for series systems with possibly several versions of the system which share some common components. It models reliability as a function of age and up to 2 other lifecycle (usage) covariates. Initial output from its Exploratory Data Analysis mode consists of plots and numerical summaries so that the user can check data entry and model assumptions, and help determine a final form for themore » system model. The System Reliability mode runs a complete reliability calculation using Bayesian methodology. This mode produces results that estimate reliability at the component, sub-system, and system level. The results include estimates of uncertainty, and can predict reliability at some not-too-distant time in the future. This paper presents an overview of the underlying statistical model for the analysis, discusses model assumptions, and demonstrates usage of SRFYDO.« less

Extending the accuracy of the SNAP interatomic potential form

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

Wood, Mitchell A.; Thompson, Aidan P.

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functionsmore » in EAM. It is also argued that the quadratic SNAP form is a special case of an artificial neural network (ANN). The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similarly to ANN potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting, as measured by cross-validation analysis.« less

Noise deconvolution based on the L1-metric and decomposition of discrete distributions of postsynaptic responses.

PubMed

Astrelin, A V; Sokolov, M V; Behnisch, T; Reymann, K G; Voronin, L L

1997-04-25

A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.

Extending the accuracy of the SNAP interatomic potential form

DOE PAGES

Wood, Mitchell A.; Thompson, Aidan P.

2018-03-28

The Spectral Neighbor Analysis Potential (SNAP) is a classical interatomic potential that expresses the energy of each atom as a linear function of selected bispectrum components of the neighbor atoms. An extension of the SNAP form is proposed that includes quadratic terms in the bispectrum components. The extension is shown to provide a large increase in accuracy relative to the linear form, while incurring only a modest increase in computational cost. The mathematical structure of the quadratic SNAP form is similar to the embedded atom method (EAM), with the SNAP bispectrum components serving as counterparts to the two-body density functionsmore » in EAM. It is also argued that the quadratic SNAP form is a special case of an artificial neural network (ANN). The effectiveness of the new form is demonstrated using an extensive set of training data for tantalum structures. Similarly to ANN potentials, the quadratic SNAP form requires substantially more training data in order to prevent overfitting, as measured by cross-validation analysis.« less

A Fast and Sensitive New Satellite SO2 Retrieval Algorithm based on Principal Component Analysis: Application to the Ozone Monitoring Instrument

NASA Technical Reports Server (NTRS)

Li, Can; Joiner, Joanna; Krotkov, A.; Bhartia, Pawan K.

2013-01-01

We describe a new algorithm to retrieve SO2 from satellite-measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO2 Jacobians calculated with a radiative transfer model to directly estimate SO2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5-340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing longterm, consistent SO2 records for air quality and climate research.

Embedding Dimension Selection for Adaptive Singular Spectrum Analysis of EEG Signal.

PubMed

Xu, Shanzhi; Hu, Hai; Ji, Linhong; Wang, Peng

2018-02-26

The recorded electroencephalography (EEG) signal is often contaminated with different kinds of artifacts and noise. Singular spectrum analysis (SSA) is a powerful tool for extracting the brain rhythm from a noisy EEG signal. By analyzing the frequency characteristics of the reconstructed component (RC) and the change rate in the trace of the Toeplitz matrix, it is demonstrated that the embedding dimension is related to the frequency bandwidth of each reconstructed component, in consistence with the component mixing in the singular value decomposition step. A method for selecting the embedding dimension is thereby proposed and verified by simulated EEG signal based on the Markov Process Amplitude (MPA) EEG Model. Real EEG signal is also collected from the experimental subjects under both eyes-open and eyes-closed conditions. The experimental results show that based on the embedding dimension selection method, the alpha rhythm can be extracted from the real EEG signal by the adaptive SSA, which can be effectively utilized to distinguish between the eyes-open and eyes-closed states.

Advanced oxide dispersion strengthened sheet alloys for improved combustor durability

NASA Technical Reports Server (NTRS)

Henricks, R. J.

1981-01-01

Burner design modifications that will take advantage of the improved creep and cyclic oxidation resistance of oxide dispersion strengthened (ODS) alloys while accommodating the reduced fatigue properties of these materials were evaluated based on preliminary analysis and life predictions, on construction and repair feasibility, and on maintenance and direct operating costs. Two designs - the film cooled, segmented louver and the transpiration cooled, segmented twin Wall - were selected for low cycle fatigue (LCF) component testing. Detailed thermal and structural analysis of these designs established the strain range and temprature at critical locations resulting in predicted lives of 10,000 cycles for MA 956 alloy. The ODs alloys, MA 956 and HDA 8077, demonstrated a 167 C (300 F) temperature advantage over Hastelloy X alloy in creep strength and oxidation resistance. The MA 956 alloy was selected for mechanical property and component test evaluations. The MA 956 alloy was superior to Hastelloy X in LCF component testing of the film cooled, segmented louver design.

Independent component analysis for onset detection in piano trills

NASA Astrophysics Data System (ADS)

Brown, Judith C.; Todd, Jeremy G.; Smaragdis, Paris

2002-05-01

The detection of onsets in piano music is difficult due to the presence of many notes simultaneously and their long decay times from pedaling. This is even more difficult for trills where the rapid note changes make it difficult to observe a decrease in amplitude for individual notes in either the temporal wave form or the time dependent Fourier components. Occasionally one note of the trill has a much lower amplitude than the other making an unambiguous determination of its onset virtually impossible. We have analyzed a number of trills from CD's of performances by Horowitz, Ashkenazy, and Goode, choosing the same trill and different performances where possible. The Fourier transform was calculated as a function of time, and the magnitude coefficients served as input for a calculation using the method of independent component analysis. In most cases this gave a more definitive determination of the onset times, as can be demonstrated graphically. For comparison identical calculations have been carried out on recordings of midi generated performances on a Yamaha Disclavier piano.

Development of an Aeroelastic Modeling Capability for Transient Nozzle Side Load Analysis

NASA Technical Reports Server (NTRS)

Wang, Ten-See; Zhao, Xiang; Zhang, Sijun; Chen, Yen-Sen

2013-01-01

Lateral nozzle forces are known to cause severe structural damage to any new rocket engine in development during test. While three-dimensional, transient, turbulent, chemically reacting computational fluid dynamics methodology has been demonstrated to capture major side load physics with rigid nozzles, hot-fire tests often show nozzle structure deformation during major side load events, leading to structural damages if structural strengthening measures were not taken. The modeling picture is incomplete without the capability to address the two-way responses between the structure and fluid. The objective of this study is to develop a coupled aeroelastic modeling capability by implementing the necessary structural dynamics component into an anchored computational fluid dynamics methodology. The computational fluid dynamics component is based on an unstructured-grid, pressure-based computational fluid dynamics formulation, while the computational structural dynamics component is developed in the framework of modal analysis. Transient aeroelastic nozzle startup analyses of the Block I Space Shuttle Main Engine at sea level were performed. The computed results from the aeroelastic nozzle modeling are presented.

The structure of temperament and personality in Russian children.

PubMed

Digman, J M; Shmelyov, A G

1996-08-01

Russian schoolchildren (N = 480) 8-10 years old were rated by their teachers on 60 scales drawn from 3 sources: the temperament literature, studies of child personality, and Russian educators. Analysis of 21 temperament scales produced 4 meaningful components: sociability, anger, impulsivity, and fear. Component scores formed from these scales were then analyzed in the context of the remaining scales, leading to a solution that demonstrated the usefulness of the Big Five for the organization of personality characteristics in the Russian language and culture. The high degree of relation between the temperament dimensions and 4 of the 5 personality dimensions supports the view of many developmentalists that temperament not only is a major component of personality but may be the foundation of personality.

Identification of Pulmonary Edema in Forensic Autopsy Cases of Sudden Cardiac Death Using Fourier Transform Infrared Microspectroscopy: A Pilot Study.

PubMed

Lin, Hancheng; Luo, Yiwen; Sun, Qiran; Zhang, Ji; Tuo, Ya; Zhang, Zhong; Wang, Lei; Deng, Kaifei; Chen, Yijiu; Huang, Ping; Wang, Zhenyuan

2018-02-20

Many studies have proven the usefulness of biofluid-based infrared spectroscopy in the clinical domain for diagnosis and monitoring the progression of diseases. Here we present a state-of-the-art study in the forensic field that employed Fourier transform infrared microspectroscopy for postmortem diagnosis of sudden cardiac death (SCD) by in situ biochemical investigation of alveolar edema fluid in lung tissue sections. The results of amide-related spectral absorbance analysis demonstrated that the pulmonary edema fluid of the SCD group was richer in protein components than that of the neurologic catastrophe (NC) and lethal multiple injuries (LMI) groups. The complementary results of unsupervised principle component analysis (PCA) and genetic algorithm-guided partial least-squares discriminant analysis (GA-PLS-DA) further indicated different global spectral band patterns of pulmonary edema fluids between these three groups. Ultimately, a random forest (RF) classification model for postmortem diagnosis of SCD was built and achieved good sensitivity and specificity scores of 97.3% and 95.5%, respectively. Classification predictions of unknown pulmonary edema fluid collected from 16 cases were also performed by the model, resulting in 100% correct discrimination. This pilot study demonstrates that FTIR microspectroscopy in combination with chemometrics has the potential to be an effective aid for postmortem diagnosis of SCD.

Comparative Analysis of a Principal Component Analysis-Based and an Artificial Neural Network-Based Method for Baseline Removal.

PubMed

Carvajal, Roberto C; Arias, Luis E; Garces, Hugo O; Sbarbaro, Daniel G

2016-04-01

This work presents a non-parametric method based on a principal component analysis (PCA) and a parametric one based on artificial neural networks (ANN) to remove continuous baseline features from spectra. The non-parametric method estimates the baseline based on a set of sampled basis vectors obtained from PCA applied over a previously composed continuous spectra learning matrix. The parametric method, however, uses an ANN to filter out the baseline. Previous studies have demonstrated that this method is one of the most effective for baseline removal. The evaluation of both methods was carried out by using a synthetic database designed for benchmarking baseline removal algorithms, containing 100 synthetic composed spectra at different signal-to-baseline ratio (SBR), signal-to-noise ratio (SNR), and baseline slopes. In addition to deomonstrating the utility of the proposed methods and to compare them in a real application, a spectral data set measured from a flame radiation process was used. Several performance metrics such as correlation coefficient, chi-square value, and goodness-of-fit coefficient were calculated to quantify and compare both algorithms. Results demonstrate that the PCA-based method outperforms the one based on ANN both in terms of performance and simplicity. © The Author(s) 2016.

Hyperspectral and differential CARS microscopy for quantitative chemical imaging in human adipocytes

PubMed Central

Di Napoli, Claudia; Pope, Iestyn; Masia, Francesco; Watson, Peter; Langbein, Wolfgang; Borri, Paola

2014-01-01

In this work, we demonstrate the applicability of coherent anti-Stokes Raman scattering (CARS) micro-spectroscopy for quantitative chemical imaging of saturated and unsaturated lipids in human stem-cell derived adipocytes. We compare dual-frequency/differential CARS (D-CARS), which enables rapid imaging and simple data analysis, with broadband hyperspectral CARS microscopy analyzed using an unsupervised phase-retrieval and factorization method recently developed by us for quantitative chemical image analysis. Measurements were taken in the vibrational fingerprint region (1200–2000/cm) and in the CH stretch region (2600–3300/cm) using a home-built CARS set-up which enables hyperspectral imaging with 10/cm resolution via spectral focussing from a single broadband 5 fs Ti:Sa laser source. Through a ratiometric analysis, both D-CARS and phase-retrieved hyperspectral CARS determine the concentration of unsaturated lipids with comparable accuracy in the fingerprint region, while in the CH stretch region D-CARS provides only a qualitative contrast owing to its non-linear behavior. When analyzing hyperspectral CARS images using the blind factorization into susceptibilities and concentrations of chemical components recently demonstrated by us, we are able to determine vol:vol concentrations of different lipid components and spatially resolve inhomogeneities in lipid composition with superior accuracy compared to state-of-the art ratiometric methods. PMID:24877002

A comparison of spectral magnitude and phase-locking value analyses of the frequency-following response to complex tones

PubMed Central

Zhu, Li; Bharadwaj, Hari; Xia, Jing; Shinn-Cunningham, Barbara

2013-01-01

Two experiments, both presenting diotic, harmonic tone complexes (100 Hz fundamental), were conducted to explore the envelope-related component of the frequency-following response (FFRENV), a measure of synchronous, subcortical neural activity evoked by a periodic acoustic input. Experiment 1 directly compared two common analysis methods, computing the magnitude spectrum and the phase-locking value (PLV). Bootstrapping identified which FFRENV frequency components were statistically above the noise floor for each metric and quantified the statistical power of the approaches. Across listeners and conditions, the two methods produced highly correlated results. However, PLV analysis required fewer processing stages to produce readily interpretable results. Moreover, at the fundamental frequency of the input, PLVs were farther above the metric's noise floor than spectral magnitudes. Having established the advantages of PLV analysis, the efficacy of the approach was further demonstrated by investigating how different acoustic frequencies contribute to FFRENV, analyzing responses to complex tones composed of different acoustic harmonics of 100 Hz (Experiment 2). Results show that the FFRENV response is dominated by peripheral auditory channels responding to unresolved harmonics, although low-frequency channels driven by resolved harmonics also contribute. These results demonstrate the utility of the PLV for quantifying the strength of FFRENV across conditions. PMID:23862815

Identification of proteins derived from Listeria monocytogenes inducing human dendritic cell maturation.

PubMed

Mirzaei, Reza; Saei, Azad; Torkashvand, Fatemeh; Azarian, Bahareh; Jalili, Ahmad; Noorbakhsh, Farshid; Vaziri, Behrouz; Hadjati, Jamshid

2016-08-01

Dendritic cells (DCs) are potent antigen-presenting cells (APCs) that can promote antitumor immunity when pulsed with tumor antigens and then matured by stimulatory agents. Despite apparent progress in DC-based cancer immunotherapy, some discrepancies were reported in generating potent DCs. Listeria monocytogenes as an intracellular microorganism is able to effectively activate DCs through engaging pattern-recognition receptors (PRRs). This study aimed to find the most potent components derived from L. monocytogenes inducing DC maturation. The preliminary results demonstrated that the ability of protein components is higher than DNA components to promote DC maturation and activation. Protein lysate fractionation demonstrated that fraction 2 HIC (obtained by hydrophobic interaction chromatography) was able to efficiently mature DCs. F2HIC-matured DCs are able to induce allogeneic CD8(+) T cells proliferation better than LPS-matured DCs and induce IFN-γ producing CD8(+) T cells. Mass spectrometry results showed that F2HIC contains 109 proteins. Based on the bioinformatics analysis for these 109 proteins, elongation factor Tu (EF-Tu) could be considered as a PRR ligand for stimulating DC maturation.

Specific binding of a Pop6/Pop7 heterodimer to the P3 stem of the yeast RNase MRP and RNase P RNAs.

PubMed

Perederina, Anna; Esakova, Olga; Koc, Hasan; Schmitt, Mark E; Krasilnikov, Andrey S

2007-10-01

Pop6 and Pop7 are protein subunits of Saccharomyces cerevisiae RNase MRP and RNase P. Here we show that bacterially expressed Pop6 and Pop7 form a soluble heterodimer that binds the RNA components of both RNase MRP and RNase P. Footprint analysis of the interaction between the Pop6/7 heterodimer and the RNase MRP RNA, combined with gel mobility assays, demonstrates that the Pop6/7 complex binds to a conserved region of the P3 domain. Binding of these proteins to the MRP RNA leads to local rearrangement in the structure of the P3 loop and suggests that direct interaction of the Pop6/7 complex with the P3 domain of the RNA components of RNases MRP and P may mediate binding of other protein components. These results suggest a role for a key element in the RNase MRP and RNase P RNAs in protein binding, and demonstrate the feasibility of directly studying RNA-protein interactions in the eukaryotic RNases MRP and P complexes.

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.

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.

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

Student Gains in Self-Efficacy in an Advanced MSW Curriculum: A Customized Model for Outcomes Assessment

ERIC Educational Resources Information Center

Rishel, Carrie W.; Majewski, Virginia

2009-01-01

The new Educational Policy and Accreditation Standards (EPAS) identify assessment as "an integral component of competency-based education." It is not new, however, that programs must demonstrate plans to assess attainment of competencies or expected program outcomes and show how data collection and analysis inform curriculum decisions. Previous…

Summer Enrichment Workshop (SEW): A Quality Component of the University of Alabama's Gifted Education Preservice Training Program

ERIC Educational Resources Information Center

Newman, Jane L.; Gregg, Madeleine; Dantzler, John

2009-01-01

Summer Enrichment Workshop (SEW) is a clinical experience in the teacher preservice training program for gifted and talented (GT) master's degree interns at the University of Alabama. This mixed design study investigated the effects of the SEW clinical experience on interns' preparation to teach. Quantitative analysis demonstrated a statistically…

Air Force Manufacturing Technology. Year 2000 Project Book

DTIC Science & Technology

2000-01-01

Electronic Warfare Component Manufacturing 13 National Center for Manufacturing Science 14 Product Research Market Analysis System 15 Electronics Acoustic...other agile organizations that can respond to rapidly changing market demands. Approach This program demonstrated and evaluated the advanced design...production worker contact with customers and suppliers; shopfloor identification of new technologies, markets , and products; and strategic planning to assure

Leucoreduction of blood components: an effective way to increase blood safety?

PubMed Central

Bianchi, Maria; Vaglio, Stefania; Pupella, Simonetta; Marano, Giuseppe; Facco, Giuseppina; Liumbruno, Giancarlo M.; Grazzini, Giuliano

2016-01-01

Over the past 30 years, it has been demonstrated that removal of white blood cells from blood components is effective in preventing some adverse reactions such as febrile non-haemolytic transfusion reactions, immunisation against human leucocyte antigens and human platelet antigens, and transmission of cytomegalovirus. In this review we discuss indications for leucoreduction and classify them into three categories: evidence-based indications for which the clinical efficacy is proven, indications based on the analysis of observational clinical studies with very consistent results and indications for which the clinical efficacy is partial or unproven. PMID:26710353

On the adequacy of modeling the concentration dependences of the activity coefficients for the components of solutions

NASA Astrophysics Data System (ADS)

Sergievskii, V. V.; Rudakov, A. M.

2006-11-01

An analysis of the accepted methods for calculating the activity coefficients for the components of binary aqueous solutions was performed. It was demonstrated that the use of the osmotic coefficients in auxiliary calculations decreases the accuracy of estimates of the activity coefficients. The possibility of calculating the activity coefficient of the solute from the concentration dependence of the water activity was examined. It was established that, for weak electrolytes, the interpretation of data on heterogeneous equilibria within the framework of the standard assumption that the dissociation is complete encounters serious difficulties.

Energy Efficient Engine: Combustor component performance program

NASA Technical Reports Server (NTRS)

Dubiel, D. J.

1986-01-01

The results of the Combustor Component Performance analysis as developed under the Energy Efficient Engine (EEE) program are presented. This study was conducted to demonstrate the aerothermal and environmental goals established for the EEE program and to identify areas where refinements might be made to meet future combustor requirements. In this study, a full annular combustor test rig was used to establish emission levels and combustor performance for comparison with those indicated by the supporting technology program. In addition, a combustor sector test rig was employed to examine differences in emissions and liner temperatures obtained during the full annular performance and supporting technology tests.

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.

Evolution of JAK-STAT Pathway Components: Mechanisms and Role in Immune System Development

PubMed Central

Liongue, Clifford; O'Sullivan, Lynda A.; Trengove, Monique C.; Ward, Alister C.

2012-01-01

Background Lying downstream of a myriad of cytokine receptors, the Janus kinase (JAK) – Signal transducer and activator of transcription (STAT) pathway is pivotal for the development and function of the immune system, with additional important roles in other biological systems. To gain further insight into immune system evolution, we have performed a comprehensive bioinformatic analysis of the JAK-STAT pathway components, including the key negative regulators of this pathway, the SH2-domain containing tyrosine phosphatase (SHP), Protein inhibitors against Stats (PIAS), and Suppressor of cytokine signaling (SOCS) proteins across a diverse range of organisms. Results Our analysis has demonstrated significant expansion of JAK-STAT pathway components co-incident with the emergence of adaptive immunity, with whole genome duplication being the principal mechanism for generating this additional diversity. In contrast, expansion of upstream cytokine receptors appears to be a pivotal driver for the differential diversification of specific pathway components. Conclusion Diversification of JAK-STAT pathway components during early vertebrate development occurred concurrently with a major expansion of upstream cytokine receptors and two rounds of whole genome duplications. This produced an intricate cell-cell communication system that has made a significant contribution to the evolution of the immune system, particularly the emergence of adaptive immunity. PMID:22412924

Dimension reduction: additional benefit of an optimal filter for independent component analysis to extract event-related potentials.

PubMed

Cong, Fengyu; Leppänen, Paavo H T; Astikainen, Piia; Hämäläinen, Jarmo; Hietanen, Jari K; Ristaniemi, Tapani

2011-09-30

The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the number of sources) simultaneously. We demonstrated these effects using two datasets, one containing visual and the other auditory ERPs. The results showed that the method including OF and ICA extracted much more reliable components than the sole ICA without OF did, and that OF removed some non-targeted sources and made the underdetermined model of EEG recordings approach to the determined one. Thus, we suggest designing an OF based on the properties of an ERP to filter recordings before using ICA decomposition to extract the targeted ERP component. Copyright © 2011 Elsevier B.V. All rights reserved.

Geochemical differentiation processes for arc magma of the Sengan volcanic cluster, Northeastern Japan, constrained from principal component analysis

NASA Astrophysics Data System (ADS)

Ueki, Kenta; Iwamori, Hikaru

2017-10-01

In this study, with a view of understanding the structure of high-dimensional geochemical data and discussing the chemical processes at work in the evolution of arc magmas, we employed principal component analysis (PCA) to evaluate the compositional variations of volcanic rocks from the Sengan volcanic cluster of the Northeastern Japan Arc. We analyzed the trace element compositions of various arc volcanic rocks, sampled from 17 different volcanoes in a volcanic cluster. The PCA results demonstrated that the first three principal components accounted for 86% of the geochemical variation in the magma of the Sengan region. Based on the relationships between the principal components and the major elements, the mass-balance relationships with respect to the contributions of minerals, the composition of plagioclase phenocrysts, geothermal gradient, and seismic velocity structure in the crust, the first, the second, and the third principal components appear to represent magma mixing, crystallizations of olivine/pyroxene, and crystallizations of plagioclase, respectively. These represented 59%, 20%, and 6%, respectively, of the variance in the entire compositional range, indicating that magma mixing accounted for the largest variance in the geochemical variation of the arc magma. Our result indicated that crustal processes dominate the geochemical variation of magma in the Sengan volcanic cluster.

Characterization of CDOM from urban waters in Northern-Northeastern China using excitation-emission matrix fluorescence and parallel factor analysis.

PubMed

Zhao, Ying; Song, Kaishan; Li, Sijia; Ma, Jianhang; Wen, Zhidan

2016-08-01

Chromophoric dissolved organic matter (CDOM) plays an important role in aquatic systems, but high concentrations of organic materials are considered pollutants. The fluorescent component characteristics of CDOM in urban waters sampled from Northern and Northeastern China were examined by excitation-emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC) to investigate the source and compositional changes of CDOM on both space and pollution levels. One humic-like (C1), one tryptophan-like component (C2), and one tyrosine-like component (C3) were identified by PARAFAC. Mean fluorescence intensities of the three CDOM components varied spatially and by pollution level in cities of Northern and Northeastern China during July-August, 2013 and 2014. Principal components analysis (PCA) was conducted to identify the relative distribution of all water samples. Cluster analysis (CA) was also used to categorize the samples into groups of similar pollution levels within a study area. Strong positive linear relationships were revealed between the CDOM absorption coefficients a(254) (R (2) = 0.89, p < 0.01); a(355) (R (2) = 0.94, p < 0.01); and the fluorescence intensity (F max) for the humic-like C1 component. A positive linear relationship (R (2) = 0.77) was also exhibited between dissolved organic carbon (DOC) and the F max for the humic-like C1 component, but a relatively weak correlation (R (2) = 0.56) was detected between DOC and the F max for the tryptophan-like component (C2). A strong positive correlation was observed between the F max for the tryptophan-like component (C2) and total nitrogen (TN) (R (2) = 0.78), but moderate correlations were observed with ammonium-N (NH4-N) (R (2) = 0.68), and chemical oxygen demand (CODMn) (R (2) = 0.52). Therefore, the fluorescence intensities of CDOM components can be applied to monitor water quality in real time compared to that of traditional approaches. These results demonstrate that EEM-PARAFAC is useful to evaluate the dynamics of CDOM fluorescent components in urban waters from Northern and Northeastern China and this method has potential applications for monitoring urban water quality in different regions with various hydrological conditions and pollution levels.

A systematic study on the influencing parameters and improvement of quantitative analysis of multi-component with single marker method using notoginseng as research subject.

PubMed

Wang, Chao-Qun; Jia, Xiu-Hong; Zhu, Shu; Komatsu, Katsuko; Wang, Xuan; Cai, Shao-Qing

2015-03-01

A new quantitative analysis of multi-component with single marker (QAMS) method for 11 saponins (ginsenosides Rg1, Rb1, Rg2, Rh1, Rf, Re and Rd; notoginsenosides R1, R4, Fa and K) in notoginseng was established, when 6 of these saponins were individually used as internal referring substances to investigate the influences of chemical structure, concentrations of quantitative components, and purities of the standard substances on the accuracy of the QAMS method. The results showed that the concentration of the analyte in sample solution was the major influencing parameter, whereas the other parameters had minimal influence on the accuracy of the QAMS method. A new method for calculating the relative correction factors by linear regression was established (linear regression method), which demonstrated to decrease standard method differences of the QAMS method from 1.20%±0.02% - 23.29%±3.23% to 0.10%±0.09% - 8.84%±2.85% in comparison with the previous method. And the differences between external standard method and the QAMS method using relative correction factors calculated by linear regression method were below 5% in the quantitative determination of Rg1, Re, R1, Rd and Fa in 24 notoginseng samples and Rb1 in 21 notoginseng samples. And the differences were mostly below 10% in the quantitative determination of Rf, Rg2, R4 and N-K (the differences of these 4 constituents bigger because their contents lower) in all the 24 notoginseng samples. The results indicated that the contents assayed by the new QAMS method could be considered as accurate as those assayed by external standard method. In addition, a method for determining applicable concentration ranges of the quantitative components assayed by QAMS method was established for the first time, which could ensure its high accuracy and could be applied to QAMS methods of other TCMs. The present study demonstrated the practicability of the application of the QAMS method for the quantitative analysis of multi-component and the quality control of TCMs and TCM prescriptions. Copyright © 2014 Elsevier B.V. All rights reserved.

Fast and Accurate Radiative Transfer Calculations Using Principal Component Analysis for (Exo-)Planetary Retrieval Models

NASA Astrophysics Data System (ADS)

Kopparla, P.; Natraj, V.; Shia, R. L.; Spurr, R. J. D.; Crisp, D.; Yung, Y. L.

2015-12-01

Radiative transfer (RT) computations form the engine of atmospheric retrieval codes. However, full treatment of RT processes is computationally expensive, prompting usage of two-stream approximations in current exoplanetary atmospheric retrieval codes [Line et al., 2013]. Natraj et al. [2005, 2010] and Spurr and Natraj [2013] demonstrated the ability of a technique using principal component analysis (PCA) to speed up RT computations. In the PCA method for RT performance enhancement, empirical orthogonal functions are developed for binned sets of inherent optical properties that possess some redundancy; costly multiple-scattering RT calculations are only done for those few optical states corresponding to the most important principal components, and correction factors are applied to approximate radiation fields. Kopparla et al. [2015, in preparation] extended the PCA method to a broadband spectral region from the ultraviolet to the shortwave infrared (0.3-3 micron), accounting for major gas absorptions in this region. Here, we apply the PCA method to a some typical (exo-)planetary retrieval problems. Comparisons between the new model, called Universal Principal Component Analysis Radiative Transfer (UPCART) model, two-stream models and line-by-line RT models are performed, for spectral radiances, spectral fluxes and broadband fluxes. Each of these are calculated at the top of the atmosphere for several scenarios with varying aerosol types, extinction and scattering optical depth profiles, and stellar and viewing geometries. We demonstrate that very accurate radiance and flux estimates can be obtained, with better than 1% accuracy in all spectral regions and better than 0.1% in most cases, as compared to a numerically exact line-by-line RT model. The accuracy is enhanced when the results are convolved to typical instrument resolutions. The operational speed and accuracy of UPCART can be further improved by optimizing binning schemes and parallelizing the codes, work on which is under way.

40 CFR 59.506 - How do I demonstrate compliance if I manufacture multi-component kits?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false How do I demonstrate compliance if I manufacture multi-component kits? 59.506 Section 59.506 Protection of Environment ENVIRONMENTAL PROTECTION... § 59.506 How do I demonstrate compliance if I manufacture multi-component kits? (a) If you manufacture...

RP-HPLC method using 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate incorporated with normalization technique in principal component analysis to differentiate the bovine, porcine and fish gelatins.

PubMed

Azilawati, M I; Hashim, D M; Jamilah, B; Amin, I

2015-04-01

The amino acid compositions of bovine, porcine and fish gelatin were determined by amino acid analysis using 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate as derivatization reagent. Sixteen amino acids were identified with similar spectral chromatograms. Data pre-treatment via centering and transformation of data by normalization were performed to provide data that are more suitable for analysis and easier to be interpreted. Principal component analysis (PCA) transformed the original data matrix into a number of principal components (PCs). Three principal components (PCs) described 96.5% of the total variance, and 2 PCs (91%) explained the highest variances. The PCA model demonstrated the relationships among amino acids in the correlation loadings plot to the group of gelatins in the scores plot. Fish gelatin was correlated to threonine, serine and methionine on the positive side of PC1; bovine gelatin was correlated to the non-polar side chains amino acids that were proline, hydroxyproline, leucine, isoleucine and valine on the negative side of PC1 and porcine gelatin was correlated to the polar side chains amino acids that were aspartate, glutamic acid, lysine and tyrosine on the negative side of PC2. Verification on the database using 12 samples from commercial products gelatin-based had confirmed the grouping patterns and the variables correlations. Therefore, this quantitative method is very useful as a screening method to determine gelatin from various sources. Copyright © 2014 Elsevier Ltd. All rights reserved.

Precise measurement of volume of eccrine sweat gland in mental sweating by optical coherence tomography

NASA Astrophysics Data System (ADS)

Sugawa, Yoshihiko; Fukuda, Akihiro; Ohmi, Masato

2015-04-01

We have demonstrated dynamic analysis of the physiological function of eccrine sweat glands underneath skin surface by optical coherence tomography (OCT). In this paper, we propose a method for extraction of the specific eccrine sweat gland by means of the connected component extraction process and the adaptive threshold method, where the en face OCT images are constructed by the swept-source OCT. In the experiment, we demonstrate precise measurement of the volume of the sweat gland in response to the external stimulus.

Identification of a xanthine oxidase-inhibitory component from Sophora flavescens using NMR-based metabolomics.

PubMed

Suzuki, Ryuichiro; Hasuike, Yuka; Hirabayashi, Moeka; Fukuda, Tatsuo; Okada, Yoshihito; Shirataki, Yoshiaki

2013-10-01

We demonstrate that NMR-based metabolomics studies can be used to identify xanthine oxidase-inhibitory compounds in the diethyl ether soluble fraction prepared from a methanolic extract of Sophora flavescens. Loading plot analysis, accompanied by direct comparison of 1H NMR spectraexhibiting characteristic signals, identified compounds exhibiting inhibitory activity. NMR analysis indicated that these characteristic signals were attributed to flavanones such as sophoraflavanone G and kurarinone. Sophoraflavanone G showed inhibitory activity towards xanthine oxidase in an in vitro assay.

Classification of alloys using laser induced breakdown spectroscopy with principle component analysis

NASA Astrophysics Data System (ADS)

Syuhada Mangsor, Aneez; Haider Rizvi, Zuhaib; Chaudhary, Kashif; Safwan Aziz, Muhammad

2018-05-01

The study of atomic spectroscopy has contributed to a wide range of scientific applications. In principle, laser induced breakdown spectroscopy (LIBS) method has been used to analyse various types of matter regardless of its physical state, either it is solid, liquid or gas because all elements emit light of characteristic frequencies when it is excited to sufficiently high energy. The aim of this work was to analyse the signature spectrums of each element contained in three different types of samples. Metal alloys of Aluminium, Titanium and Brass with the purities of 75%, 80%, 85%, 90% and 95% were used as the manipulated variable and their LIBS spectra were recorded. The characteristic emission lines of main elements were identified from the spectra as well as its corresponding contents. Principal component analysis (PCA) was carried out using the data from LIBS spectra. Three obvious clusters were observed in 3-dimensional PCA plot which corresponding to the different group of alloys. Findings from this study showed that LIBS technology with the help of principle component analysis could conduct the variety discrimination of alloys demonstrating the capability of LIBS-PCA method in field of spectro-analysis. Thus, LIBS-PCA method is believed to be an effective method for classifying alloys with different percentage of purifications, which was high-cost and time-consuming before.

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

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.

Measuring the immune system: a comprehensive approach for the analysis of immune functions in humans.

PubMed

Claus, Maren; Dychus, Nicole; Ebel, Melanie; Damaschke, Jürgen; Maydych, Viktoriya; Wolf, Oliver T; Kleinsorge, Thomas; Watzl, Carsten

2016-10-01

The immune system is essential to provide protection from infections and cancer. Disturbances in immune function can therefore directly affect the health of the affected individual. Many extrinsic and intrinsic factors such as exposure to chemicals, stress, nutrition and age have been reported to influence the immune system. These influences can affect various components of the immune system, and we are just beginning to understand the causalities of these changes. To investigate such disturbances, it is therefore essential to analyze the different components of the immune system in a comprehensive fashion. Here, we demonstrate such an approach which provides information about total number of leukocytes, detailed quantitative and qualitative changes in the composition of lymphocyte subsets, cytokine levels in serum and functional properties of T cells, NK cells and monocytes. Using samples from a cohort of 24 healthy volunteers, we demonstrate the feasibility of our approach to detect changes in immune functions.

Skill Analysis of the Wrist Release in the Golf Swings Utilizing Shaft Elasticity

NASA Astrophysics Data System (ADS)

Suzuki, Soichiro; Hoshino, Yohei; Kobayashi, Yukinori

This study analyzes the skill component of the wrist release in the golf swing by employing a three-dimensional dynamic model considering vibration of the club shaft. It is observed that professional and expert golfers relax their wrists in the swing motion as a "natural" or "late" release. Thus, the relationship between the timing of the wrist release and the shaft vibration is examined in this study. First, it is demonstrated that "natural release" at the zero-crossing point of the bending vibration of the shaft efficiently increases the head speed at impact. In the next step, the "late hitting" condition is imposed upon the model. It is demonstrated that "late hitting" could further improve the efficiency of the swing motion. Finally, the skill component in the wrist release for the long drive is experimentally verified by measuring the movement of the wrist and the dynamic deformation of the shaft during the downswing.

Numerical Simulation of the RTA Combustion Rig

NASA Technical Reports Server (NTRS)

Davoudzadeh, Farhad; Buehrle, Robert; Liu, Nan-Suey; Winslow, Ralph

2005-01-01

The Revolutionary Turbine Accelerator (RTA)/Turbine Based Combined Cycle (TBCC) project is investigating turbine-based propulsion systems for access to space. NASA Glenn Research Center and GE Aircraft Engines (GEAE) planned to develop a ground demonstrator engine for validation testing. The demonstrator (RTA-1) is a variable cycle, turbofan ramjet designed to transition from an augmented turbofan to a ramjet that produces the thrust required to accelerate the vehicle from Sea Level Static (SLS) to Mach 4. The RTA-1 is designed to accommodate a large variation in bypass ratios from sea level static to Mach 4 conditions. Key components of this engine are new, such as a nickel alloy fan, advanced trapped vortex combustor, a Variable Area Bypass Injector (VABI), radial flameholders, and multiple fueling zones. A means to mitigate risks to the RTA development program was the use of extensive component rig tests and computational fluid dynamics (CFD) analysis.

Analysis of migration of press-fit porous-coated acetabular components with medial lucencies using Ein-Bild-Roentegen-Analyse.

PubMed

Sadeghi, Cameron; Gibson, Anthony G; Ries, Michael D

2012-08-01

A total of 136 patients who underwent total hip arthroplasty (154 hips) with press-fit acetabular components were evaluated for the presence of medial radiographic lucencies. Thirty patients (22.1%) demonstrated radiolucencies greater than 1 mm in zone 2 on initial postoperative films. Ein-Bild-Roentegen-Analyse (EBRA) was used to evaluate component migration over a 5-year follow-up period. Migration, measured by EBRA, was not observed during the first 6 months when the radiolucencies were noted to disappear. After 2 years, the mean total migration was 0.8 mm, and at 5 years, it was 1.6 mm. Our results indicate that disappearance of a medial radiolucency seen on early postoperative radiographs is not associated with component migration, which supports the concept that the medial radiolucency fills in with bone or represents bony remodeling around a stable implant. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

Self-criticism interacts with the affective component of pain to predict depressive symptoms in female patients.

PubMed

Lerman, S F; Shahar, G; Rudich, Z

2012-01-01

This longitudinal study examined the role of the trait of self-criticism as a moderator of the relationship between the affective and sensory components of pain, and depression. One hundred and sixty-three chronic pain patients treated at a specialty pain clinic completed self-report questionnaires at two time points assessing affective and sensory components of pain, depression, and self-criticism. Hierarchical linear regression analysis revealed a significant 3-way interaction between self-criticism, affective pain and gender, whereby women with high affective pain and high self-criticism demonstrated elevated levels of depression. Our findings are the first to show within a broad, comprehensive model, that selfcriticism is activated by the affective, but not sensory component of pain in leading to depressive symptoms, and highlight the need to assess patients' personality as part of an effective treatment plan. © 2011 European Federation of International Association for the Study of Pain Chapters.

Development and initial validation of an instrument to assess stressors among South African sports coaches.

PubMed

Kubayi, Alliance; Toriola, Abel; Didymus, Faye

2018-06-01

The aim of this series of studies was to develop and initially validate an instrument to assess stressors among South African sports coaches. In study one, a preliminary pool of 45 items was developed based on existing literature and an expert panel was employed to assess the content validity and applicability of these items. In study two, the 32 items that were retained after study one were analysed using principal component analysis (PCA). The resultant factorial structure comprised four components: environmental stressors, performance stressors, task-related stressors, and athlete stressors. These four components were made up of 26 items and, together, the components and items comprised the provisional Stressors in Sports Coaching Questionnaire (SSCQ). The results show that the SSCQ demonstrates acceptable internal consistency (.73-.89). The findings provide preliminary evidence that SSCQ is a valid tool to assess stressors among South African sports coaches.

New evidence and impact of electron transport non-linearities based on new perturbative inter-modulation analysis

NASA Astrophysics Data System (ADS)

van Berkel, M.; Kobayashi, T.; Igami, H.; Vandersteen, G.; Hogeweij, G. M. D.; Tanaka, K.; Tamura, N.; Zwart, H. J.; Kubo, S.; Ito, S.; Tsuchiya, H.; de Baar, M. R.; LHD Experiment Group

2017-12-01

A new methodology to analyze non-linear components in perturbative transport experiments is introduced. The methodology has been experimentally validated in the Large Helical Device for the electron heat transport channel. Electron cyclotron resonance heating with different modulation frequencies by two gyrotrons has been used to directly quantify the amplitude of the non-linear component at the inter-modulation frequencies. The measurements show significant quadratic non-linear contributions and also the absence of cubic and higher order components. The non-linear component is analyzed using the Volterra series, which is the non-linear generalization of transfer functions. This allows us to study the radial distribution of the non-linearity of the plasma and to reconstruct linear profiles where the measurements were not distorted by non-linearities. The reconstructed linear profiles are significantly different from the measured profiles, demonstrating the significant impact that non-linearity can have.

Automatic single-image-based rain streaks removal via image decomposition.

PubMed

Kang, Li-Wei; Lin, Chia-Wen; Fu, Yu-Hsiang

2012-04-01

Rain removal from a video is a challenging problem and has been recently investigated extensively. Nevertheless, the problem of rain removal from a single image was rarely studied in the literature, where no temporal information among successive images can be exploited, making the problem very challenging. In this paper, we propose a single-image-based rain removal framework via properly formulating rain removal as an image decomposition problem based on morphological component analysis. Instead of directly applying a conventional image decomposition technique, the proposed method first decomposes an image into the low- and high-frequency (HF) parts using a bilateral filter. The HF part is then decomposed into a "rain component" and a "nonrain component" by performing dictionary learning and sparse coding. As a result, the rain component can be successfully removed from the image while preserving most original image details. Experimental results demonstrate the efficacy of the proposed algorithm.

Atomic Force Microscope Mediated Chromatography

NASA Technical Reports Server (NTRS)

Anderson, Mark S.

2013-01-01

The atomic force microscope (AFM) is used to inject a sample, provide shear-driven liquid flow over a functionalized substrate, and detect separated components. This is demonstrated using lipophilic dyes and normal phase chromatography. A significant reduction in both size and separation time scales is achieved with a 25-micron-length column scale, and one-second separation times. The approach has general applications to trace chemical and microfluidic analysis. The AFM is now a common tool for ultra-microscopy and nanotechnology. It has also been demonstrated to provide a number of microfluidic functions necessary for miniaturized chromatography. These include injection of sub-femtoliter samples, fluidic switching, and sheardriven pumping. The AFM probe tip can be used to selectively remove surface layers for subsequent microchemical analysis using infrared and tip-enhanced Raman spectroscopy. With its ability to image individual atoms, the AFM is a remarkably sensitive detector that can be used to detect separated components. These diverse functional components of microfluidic manipulation have been combined in this work to demonstrate AFM mediated chromatography. AFM mediated chromatography uses channel-less, shear-driven pumping. This is demonstrated with a thin, aluminum oxide substrate and a non-polar solvent system to separate a mixture of lipophilic dyes. In conventional chromatographic terms, this is analogous to thin-layer chromatography using normal phase alumina substrate with sheardriven pumping provided by the AFM tip-cantilever mechanism. The AFM detection of separated components is accomplished by exploiting the variation in the localized friction of the separated components. The AFM tip-cantilever provides the mechanism for producing shear-induced flows and rapid pumping. Shear-driven chromatography (SDC) is a relatively new concept that overcomes the speed and miniaturization limitations of conventional liquid chromatography. SDC is based on a sliding plate system, consisting of two flat surfaces, one of which has a recessed channel. A fluid flow is produced by axially sliding one plate past another, where the fluid has mechanical shear forces imposed at each point along the channel length. The shear-induced flow rates are very reproducible, and do not have pressure or voltage gradient limitations. SDC opens up a new range of enhanced separation kinetics by permitting the sample confinement with submicron dimensions. Small, highly confined liquid is advantageous for chromatographic separation because the separation rate is known to scale according to the square of the confined sample diameter. In addition, because shear-driven flows are not limited by fluid velocity, shear-driven liquid chromatography may provide up to 100,000 plate efficiency.

Shade avoidance components and pathways in adult plants revealed by phenotypic profiling.

PubMed

Nozue, Kazunari; Tat, An V; Kumar Devisetty, Upendra; Robinson, Matthew; Mumbach, Maxwell R; Ichihashi, Yasunori; Lekkala, Saradadevi; Maloof, Julin N

2015-04-01

Shade from neighboring plants limits light for photosynthesis; as a consequence, plants have a variety of strategies to avoid canopy shade and compete with their neighbors for light. Collectively the response to foliar shade is called the shade avoidance syndrome (SAS). The SAS includes elongation of a variety of organs, acceleration of flowering time, and additional physiological responses, which are seen throughout the plant life cycle. However, current mechanistic knowledge is mainly limited to shade-induced elongation of seedlings. Here we use phenotypic profiling of seedling, leaf, and flowering time traits to untangle complex SAS networks. We used over-representation analysis (ORA) of shade-responsive genes, combined with previous annotation, to logically select 59 known and candidate novel mutants for phenotyping. Our analysis reveals shared and separate pathways for each shade avoidance response. In particular, auxin pathway components were required for shade avoidance responses in hypocotyl, petiole, and flowering time, whereas jasmonic acid pathway components were only required for petiole and flowering time responses. Our phenotypic profiling allowed discovery of seventeen novel shade avoidance mutants. Our results demonstrate that logical selection of mutants increased success of phenotypic profiling to dissect complex traits and discover novel components.

A probabilistic seismic risk assessment procedure for nuclear power plants: (I) Methodology

USGS Publications Warehouse

Huang, Y.-N.; Whittaker, A.S.; Luco, N.

2011-01-01

A new procedure for probabilistic seismic risk assessment of nuclear power plants (NPPs) is proposed. This procedure modifies the current procedures using tools developed recently for performance-based earthquake engineering of buildings. The proposed procedure uses (a) response-based fragility curves to represent the capacity of structural and nonstructural components of NPPs, (b) nonlinear response-history analysis to characterize the demands on those components, and (c) Monte Carlo simulations to determine the damage state of the components. The use of response-rather than ground-motion-based fragility curves enables the curves to be independent of seismic hazard and closely related to component capacity. The use of Monte Carlo procedure enables the correlation in the responses of components to be directly included in the risk assessment. An example of the methodology is presented in a companion paper to demonstrate its use and provide the technical basis for aspects of the methodology. ?? 2011 Published by Elsevier B.V.

Directional connectivity of resting state human fMRI data using cascaded ICA-PDC analysis.

PubMed

Silfverhuth, Minna J; Remes, Jukka; Starck, Tuomo; Nikkinen, Juha; Veijola, Juha; Tervonen, Osmo; Kiviniemi, Vesa

2011-11-01

Directional connectivity measures, such as partial directed coherence (PDC), give us means to explore effective connectivity in the human brain. By utilizing independent component analysis (ICA), the original data-set reduction was performed for further PDC analysis. To test this cascaded ICA-PDC approach in causality studies of human functional magnetic resonance imaging (fMRI) data. Resting state group data was imaged from 55 subjects using a 1.5 T scanner (TR 1800 ms, 250 volumes). Temporal concatenation group ICA in a probabilistic ICA and further repeatability runs (n = 200) were overtaken. The reduced data-set included the time series presentation of the following nine ICA components: secondary somatosensory cortex, inferior temporal gyrus, intracalcarine cortex, primary auditory cortex, amygdala, putamen and the frontal medial cortex, posterior cingulate cortex and precuneus, comprising the default mode network components. Re-normalized PDC (rPDC) values were computed to determine directional connectivity at the group level at each frequency. The integrative role was suggested for precuneus while the role of major divergence region may be proposed to primary auditory cortex and amygdala. This study demonstrates the potential of the cascaded ICA-PDC approach in directional connectivity studies of human fMRI.

Non-stationary signal analysis based on general parameterized time-frequency transform and its application in the feature extraction of a rotary machine

NASA Astrophysics Data System (ADS)

Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming

2018-06-01

With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.

Subacute casemix classification for stroke rehabilitation in Australia. How well does AN-SNAP v2 explain variance in outcomes?

PubMed

Kohler, Friedbert; Renton, Roger; Dickson, Hugh G; Estell, John; Connolly, Carol E

2011-02-01

We sought the best predictors for length of stay, discharge destination and functional improvement for inpatients undergoing rehabilitation following a stroke and compared these predictors against AN-SNAP v2. The Oxfordshire classification subgroup, sociodemographic data and functional data were collected for patients admitted between 1997 and 2007, with a diagnosis of recent stroke. The data were factor analysed using Principal Components Analysis for categorical data (CATPCA). Categorical regression analyses was performed to determine the best predictors of length of stay, discharge destination, and functional improvement. A total of 1154 patients were included in the study. Principal components analysis indicated that the data were effectively unidimensional, with length of stay being the most important component. Regression analysis demonstrated that the best predictor was the admission motor FIM score, explaining 38.9% of variance for length of stay, 37.4%.of variance for functional improvement and 16% of variance for discharge destination. The best explanatory variable in our inpatient rehabilitation service is the admission motor FIM. AN- SNAP v2 classification is a less effective explanatory variable. This needs to be taken into account when using AN-SNAP v2 classification for clinical or funding purposes.

Semantic point cloud interpretation based on optimal neighborhoods, relevant features and efficient classifiers

NASA Astrophysics Data System (ADS)

Weinmann, Martin; Jutzi, Boris; Hinz, Stefan; Mallet, Clément

2015-07-01

3D scene analysis in terms of automatically assigning 3D points a respective semantic label has become a topic of great importance in photogrammetry, remote sensing, computer vision and robotics. In this paper, we address the issue of how to increase the distinctiveness of geometric features and select the most relevant ones among these for 3D scene analysis. We present a new, fully automated and versatile framework composed of four components: (i) neighborhood selection, (ii) feature extraction, (iii) feature selection and (iv) classification. For each component, we consider a variety of approaches which allow applicability in terms of simplicity, efficiency and reproducibility, so that end-users can easily apply the different components and do not require expert knowledge in the respective domains. In a detailed evaluation involving 7 neighborhood definitions, 21 geometric features, 7 approaches for feature selection, 10 classifiers and 2 benchmark datasets, we demonstrate that the selection of optimal neighborhoods for individual 3D points significantly improves the results of 3D scene analysis. Additionally, we show that the selection of adequate feature subsets may even further increase the quality of the derived results while significantly reducing both processing time and memory consumption.

Breast Shape Analysis With Curvature Estimates and Principal Component Analysis for Cosmetic and Reconstructive Breast Surgery.

PubMed

Catanuto, Giuseppe; Taher, Wafa; Rocco, Nicola; Catalano, Francesca; Allegra, Dario; Milotta, Filippo Luigi Maria; Stanco, Filippo; Gallo, Giovanni; Nava, Maurizio Bruno

2018-03-20

Breast shape is defined utilizing mainly qualitative assessment (full, flat, ptotic) or estimates, such as volume or distances between reference points, that cannot describe it reliably. We will quantitatively describe breast shape with two parameters derived from a statistical methodology denominated principal component analysis (PCA). We created a heterogeneous dataset of breast shapes acquired with a commercial infrared 3-dimensional scanner on which PCA was performed. We plotted on a Cartesian plane the two highest values of PCA for each breast (principal components 1 and 2). Testing of the methodology on a preoperative and postoperative surgical case and test-retest was performed by two operators. The first two principal components derived from PCA are able to characterize the shape of the breast included in the dataset. The test-retest demonstrated that different operators are able to obtain very similar values of PCA. The system is also able to identify major changes in the preoperative and postoperative stages of a two-stage reconstruction. Even minor changes were correctly detected by the system. This methodology can reliably describe the shape of a breast. An expert operator and a newly trained operator can reach similar results in a test/re-testing validation. Once developed and after further validation, this methodology could be employed as a good tool for outcome evaluation, auditing, and benchmarking.

Slow Crack Growth and Fatigue Life Prediction of Ceramic Components Subjected to Variable Load History

NASA Technical Reports Server (NTRS)

Jadaan, Osama

2001-01-01

Present capabilities of the NASA CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code include probabilistic life prediction of ceramic components subjected to fast fracture, slow crack growth (stress corrosion), and cyclic fatigue failure modes. Currently, this code has the capability to compute the time-dependent reliability of ceramic structures subjected to simple time-dependent loading. For example, in slow crack growth (SCG) type failure conditions CARES/Life can handle the cases of sustained and linearly increasing time-dependent loads, while for cyclic fatigue applications various types of repetitive constant amplitude loads can be accounted for. In real applications applied loads are rarely that simple, but rather vary with time in more complex ways such as, for example, engine start up, shut down, and dynamic and vibrational loads. In addition, when a given component is subjected to transient environmental and or thermal conditions, the material properties also vary with time. The objective of this paper is to demonstrate a methodology capable of predicting the time-dependent reliability of components subjected to transient thermomechanical loads that takes into account the change in material response with time. In this paper, the dominant delayed failure mechanism is assumed to be SCG. This capability has been added to the NASA CARES/Life (Ceramic Analysis and Reliability Evaluation of Structures/Life) code, which has also been modified to have the ability of interfacing with commercially available FEA codes executed for transient load histories. An example involving a ceramic exhaust valve subjected to combustion cycle loads is presented to demonstrate the viability of this methodology and the CARES/Life program.

Demonstration of fully coupled simplified extended station black-out accident simulation with RELAP-7

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

Zhao, Haihua; Zhang, Hongbin; Zou, Ling

2014-10-01

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The RELAP-7 code develop-ment effort started in October of 2011 and by the end of the second development year, a number of physical components with simplified two phase flow capability have been de-veloped to support the simplified boiling water reactor (BWR) extended station blackout (SBO) analyses. The demonstration case includes the major components for the primary system of a BWR, as well as the safety system components for the safety relief valve (SRV), the reactor core isolation cooling (RCIC)more » system, and the wet well. Three scenar-ios for the SBO simulations have been considered. Since RELAP-7 is not a severe acci-dent analysis code, the simulation stops when fuel clad temperature reaches damage point. Scenario I represents an extreme station blackout accident without any external cooling and cooling water injection. The system pressure is controlled by automatically releasing steam through SRVs. Scenario II includes the RCIC system but without SRV. The RCIC system is fully coupled with the reactor primary system and all the major components are dynamically simulated. The third scenario includes both the RCIC system and the SRV to provide a more realistic simulation. This paper will describe the major models and dis-cuss the results for the three scenarios. The RELAP-7 simulations for the three simplified SBO scenarios show the importance of dynamically simulating the SRVs, the RCIC sys-tem, and the wet well system to the reactor safety during extended SBO accidents.« less

Demonstration of Critical Systems for Propellant Production on Mars for Science and Exploration Missions

NASA Technical Reports Server (NTRS)

Linne, Diane L.; Gaier, James R.; Zoeckler, Joseph G.; Kolacz, John S.; Wegeng, Robert S.; Rassat, Scot D.; Clark, D. Larry

2013-01-01

A Mars hopper has been proposed as a Mars mobility concept that will also demonstrate and advance in-situ resource utilization. The components needed in a Mars propellant production plant have been developed to various levels of technology maturity, but there is little experience with the systems in a Mars environment. Two systems for the acquisition and compression of the thin carbon dioxide atmosphere were designed, assembled, and tested in a Mars environment chamber. A microchannel sorption pump system was able to raise the pressure from 7 Torr to 450 Torr or from 12 Torr to over 700 Torr in two stages. This data now provides information needed to make additional improvements in the sorption pump technology to increase performance, although a system-level analysis might prove that some amount of pre- or post-compression may be a preferred solution. A mini cryofreezer system was also evaluated as an alternative method for carbon dioxide acquisition and compression. Finally, an electrolysis system was tested and successfully demonstrated start-up operation and thermal stability of all components during long-term operation in the chamber.

Cementitious Barriers Partnership FY2013 End-Year Report

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

Flach, G. P.; Langton, C. A.; Burns, H. H.

2013-11-01

In FY2013, the Cementitious Barriers Partnership (CBP) demonstrated continued tangible progress toward fulfilling the objective of developing a set of software tools to improve understanding and prediction of the long-term structural, hydraulic and chemical performance of cementitious barriers used in nuclear applications. In November 2012, the CBP released “Version 1.0” of the CBP Software Toolbox, a suite of software for simulating reactive transport in cementitious materials and important degradation phenomena. In addition, the CBP completed development of new software for the “Version 2.0” Toolbox to be released in early FY2014 and demonstrated use of the Version 1.0 Toolbox on DOEmore » applications. The current primary software components in both Versions 1.0 and 2.0 are LeachXS/ORCHESTRA, STADIUM, and a GoldSim interface for probabilistic analysis of selected degradation scenarios. The CBP Software Toolbox Version 1.0 supports analysis of external sulfate attack (including damage mechanics), carbonation, and primary constituent leaching. Version 2.0 includes the additional analysis of chloride attack and dual regime flow and contaminant migration in fractured and non-fractured cementitious material. The LeachXS component embodies an extensive material property measurements database along with chemical speciation and reactive mass transport simulation cases with emphasis on leaching of major, trace and radionuclide constituents from cementitious materials used in DOE facilities, such as Saltstone (Savannah River) and Cast Stone (Hanford), tank closure grouts, and barrier concretes. STADIUM focuses on the physical and structural service life of materials and components based on chemical speciation and reactive mass transport of major cement constituents and aggressive species (e.g., chloride, sulfate, etc.). THAMES is a planned future CBP Toolbox component focused on simulation of the microstructure of cementitious materials and calculation of resultant hydraulic and constituent mass transfer parameters needed in modeling. Two CBP software demonstrations were conducted in FY2013, one to support the Saltstone Disposal Facility (SDF) at SRS and the other on a representative Hanford high-level waste tank. The CBP Toolbox demonstration on the SDF provided analysis on the most probable degradation mechanisms to the cementitious vault enclosure caused by sulfate and carbonation ingress. This analysis was documented and resulted in the issuance of a SDF Performance Assessment Special Analysis by Liquid Waste Operations this fiscal year. The two new software tools supporting chloride attack and dual-regime flow will provide additional degradation tools to better evaluate performance of DOE and commercial cementitious barriers. The CBP SRNL experimental program produced two patent applications and field data that will be used in the development and calibration of CBP software tools being developed in FY2014. The CBP software and simulation tools varies from other efforts in that all the tools are based upon specific and relevant experimental research of cementitious materials utilized in DOE applications. The CBP FY2013 program involved continuing research to improve and enhance the simulation tools as well as developing new tools that model other key degradation phenomena not addressed in Version 1.0. Also efforts to continue to verify the various simulation tools through laboratory experiments and analysis of field specimens are ongoing and will continue into FY2014 to quantify and reduce the uncertainty associated with performance assessments. This end-year report summarizes FY2013 software development efforts and the various experimental programs that are providing data for calibration and validation of the CBP developed software.« less

Spatiotemporal Distribution, Sources, and Photobleaching Imprint of Dissolved Organic Matter in the Yangtze Estuary and Its Adjacent Sea Using Fluorescence and Parallel Factor Analysis

PubMed Central

Li, Penghui; Chen, Ling; Zhang, Wen; Huang, Qinghui

2015-01-01

To investigate the seasonal and interannual dynamics of dissolved organic matter (DOM) in the Yangtze Estuary, surface and bottom water samples in the Yangtze Estuary and its adjacent sea were collected and characterized using fluorescence excitation-emission matrices (EEMs) and parallel factor analysis (PARAFAC) in both dry and wet seasons in 2012 and 2013. Two protein-like components and three humic-like components were identified. Three humic-like components decreased linearly with increasing salinity (r>0.90, p<0.001), suggesting their distribution could primarily be controlled by physical mixing. By contrast, two protein-like components fell below the theoretical mixing line, largely due to microbial degradation and removal during mixing. Higher concentrations of humic-like components found in 2012 could be attributed to higher freshwater discharge relative to 2013. There was a lack of systematic patterns for three humic-like components between seasons and years, probably due to variations of other factors such as sources and characteristics. Highest concentrations of fluorescent components, observed in estuarine turbidity maximum (ETM) region, could be attributed to sediment resuspension and subsequent release of DOM, supported by higher concentrations of fluorescent components in bottom water than in surface water at two stations where sediments probably resuspended. Meanwhile, photobleaching could be reflected from the changes in the ratios between fluorescence intensity (Fmax) of humic-like components and chromophoric DOM (CDOM) absorption coefficient (a355) along the salinity gradient. This study demonstrates the abundance and composition of DOM in estuaries are controlled not only by hydrological conditions, but also by its sources, characteristics and related estuarine biogeochemical processes. PMID:26107640

Design of Computer-aided Instruction for Radiology Interpretation: The Role of Cognitive Task Analysis

PubMed Central

Pusic, Martin V.; LeBlanc, Vicki; Patel, Vimla L.

2001-01-01

Traditional task analysis for instructional design has emphasized the importance of precisely defining behavioral educational objectives and working back to select objective-appropriate instructional strategies. However, this approach may miss effective strategies. Cognitive task analysis, on the other hand, breaks a process down into its component knowledge representations. Selection of instructional strategies based on all such representations in a domain is likely to lead to optimal instructional design. In this demonstration, using the interpretation of cervical spine x-rays as an educational example, we show how a detailed cognitive task analysis can guide the development of computer-aided instruction.

Demonstration of Wavelet Techniques in the Spectral Analysis of Bypass Transition Data

NASA Technical Reports Server (NTRS)

Lewalle, Jacques; Ashpis, David E.; Sohn, Ki-Hyeon

1997-01-01

A number of wavelet-based techniques for the analysis of experimental data are developed and illustrated. A multiscale analysis based on the Mexican hat wavelet is demonstrated as a tool for acquiring physical and quantitative information not obtainable by standard signal analysis methods. Experimental data for the analysis came from simultaneous hot-wire velocity traces in a bypass transition of the boundary layer on a heated flat plate. A pair of traces (two components of velocity) at one location was excerpted. A number of ensemble and conditional statistics related to dominant time scales for energy and momentum transport were calculated. The analysis revealed a lack of energy-dominant time scales inside turbulent spots but identified transport-dominant scales inside spots that account for the largest part of the Reynolds stress. Momentum transport was much more intermittent than were energetic fluctuations. This work is the first step in a continuing study of the spatial evolution of these scale-related statistics, the goal being to apply the multiscale analysis results to improve the modeling of transitional and turbulent industrial flows.

A three-way parallel ICA approach to analyze links among genetics, brain structure and brain function.

PubMed

Vergara, Victor M; Ulloa, Alvaro; Calhoun, Vince D; Boutte, David; Chen, Jiayu; Liu, Jingyu

2014-09-01

Multi-modal data analysis techniques, such as the Parallel Independent Component Analysis (pICA), are essential in neuroscience, medical imaging and genetic studies. The pICA algorithm allows the simultaneous decomposition of up to two data modalities achieving better performance than separate ICA decompositions and enabling the discovery of links between modalities. However, advances in data acquisition techniques facilitate the collection of more than two data modalities from each subject. Examples of commonly measured modalities include genetic information, structural magnetic resonance imaging (MRI) and functional MRI. In order to take full advantage of the available data, this work extends the pICA approach to incorporate three modalities in one comprehensive analysis. Simulations demonstrate the three-way pICA performance in identifying pairwise links between modalities and estimating independent components which more closely resemble the true sources than components found by pICA or separate ICA analyses. In addition, the three-way pICA algorithm is applied to real experimental data obtained from a study that investigate genetic effects on alcohol dependence. Considered data modalities include functional MRI (contrast images during alcohol exposure paradigm), gray matter concentration images from structural MRI and genetic single nucleotide polymorphism (SNP). The three-way pICA approach identified links between a SNP component (pointing to brain function and mental disorder associated genes, including BDNF, GRIN2B and NRG1), a functional component related to increased activation in the precuneus area, and a gray matter component comprising part of the default mode network and the caudate. Although such findings need further verification, the simulation and in-vivo results validate the three-way pICA algorithm presented here as a useful tool in biomedical data fusion applications. Copyright © 2014 Elsevier Inc. All rights reserved.

X-ray and neutron total scattering analysis of Hy·(Bi0.2Ca0.55Sr0.25)(Ag0.25Na0.75)Nb3O10·xH2O perovskite nanosheet booklets with stacking disorder

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

Metz, Peter; Koch, Robert; Cladek, Bernadette

Ion-exchanged Aurivillius materials form perovskite nanosheet booklets wherein well-defined bi-periodic sheets, with ~11.5 Å thickness, exhibit extensive stacking disorder. The perovskite layer contents were defined initially using combined synchrotron X-ray and neutron Rietveld refinement of the parent Aurivillius structure. The structure of the subsequently ion-exchanged material, which is disordered in its stacking sequence, is analyzed using both pair distribution function (PDF) analysis and recursive method simulations of the scattered intensity. Combined X-ray and neutron PDF refinement of supercell stacking models demonstrates sensitivity of the PDF to both perpendicular and transverse stacking vector components. Further, hierarchical ensembles of stacking models weightedmore » by a standard normal distribution are demonstrated to improve PDF fit over 1–25 Å. Recursive method simulations of the X-ray scattering profile demonstrate agreement between the real space stacking analysis and more conventional reciprocal space methods. The local structure of the perovskite sheet is demonstrated to relax only slightly from the Aurivillius structure after ion exchange.« less

Automatic and Direct Identification of Blink Components from Scalp EEG

PubMed Central

Kong, Wanzeng; Zhou, Zhanpeng; Hu, Sanqing; Zhang, Jianhai; Babiloni, Fabio; Dai, Guojun

2013-01-01

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to both its location and significant amplitude, in this paper, we proposed a method based on correlation index and the feature of power distribution to automatically detect eye blink components. Furthermore, we prove mathematically that the correlation between independent components and scalp EEG channels can be translating directly from the mixing matrix of ICA. This helps to simplify calculations and understand the implications of the correlation. The proposed method doesn't need to select a template or thresholds in advance, and it works without simultaneously recording an electrooculography (EOG) reference. The experimental results demonstrate that the proposed method can automatically recognize eye blink components with a high accuracy on entire datasets from 15 subjects. PMID:23959240

Intercomparison of air quality data using principal component analysis, and forecasting of PM₁₀ and PM₂.₅ concentrations using artificial neural networks, in Thessaloniki and Helsinki.

PubMed

Voukantsis, Dimitris; Karatzas, Kostas; Kukkonen, Jaakko; Räsänen, Teemu; Karppinen, Ari; Kolehmainen, Mikko

2011-03-01

In this paper we propose a methodology consisting of specific computational intelligence methods, i.e. principal component analysis and artificial neural networks, in order to inter-compare air quality and meteorological data, and to forecast the concentration levels for environmental parameters of interest (air pollutants). We demonstrate these methods to data monitored in the urban areas of Thessaloniki and Helsinki in Greece and Finland, respectively. For this purpose, we applied the principal component analysis method in order to inter-compare the patterns of air pollution in the two selected cities. Then, we proceeded with the development of air quality forecasting models for both studied areas. On this basis, we formulated and employed a novel hybrid scheme in the selection process of input variables for the forecasting models, involving a combination of linear regression and artificial neural networks (multi-layer perceptron) models. The latter ones were used for the forecasting of the daily mean concentrations of PM₁₀ and PM₂.₅ for the next day. Results demonstrated an index of agreement between measured and modelled daily averaged PM₁₀ concentrations, between 0.80 and 0.85, while the kappa index for the forecasting of the daily averaged PM₁₀ concentrations reached 60% for both cities. Compared with previous corresponding studies, these statistical parameters indicate an improved performance of air quality parameters forecasting. It was also found that the performance of the models for the forecasting of the daily mean concentrations of PM₁₀ was not substantially different for both cities, despite the major differences of the two urban environments under consideration. Copyright © 2011 Elsevier B.V. All rights reserved.

Proteome-metabolome profiling of ovarian cancer ascites reveals novel components involved in intercellular communication.

PubMed

Shender, Victoria O; Pavlyukov, Marat S; Ziganshin, Rustam H; Arapidi, Georgij P; Kovalchuk, Sergey I; Anikanov, Nikolay A; Altukhov, Ilya A; Alexeev, Dmitry G; Butenko, Ivan O; Shavarda, Alexey L; Khomyakova, Elena B; Evtushenko, Evgeniy; Ashrafyan, Lev A; Antonova, Irina B; Kuznetcov, Igor N; Gorbachev, Alexey Yu; Shakhparonov, Mikhail I; Govorun, Vadim M

2014-12-01

Ovarian cancer ascites is a native medium for cancer cells that allows investigation of their secretome in a natural environment. This medium is of interest as a promising source of potential biomarkers, and also as a medium for cell-cell communication. The aim of this study was to elucidate specific features of the malignant ascites metabolome and proteome. In order to omit components of the systemic response to ascites formation, we compared malignant ascites with cirrhosis ascites. Metabolome analysis revealed 41 components that differed significantly between malignant and cirrhosis ascites. Most of the identified cancer-specific metabolites are known to be important signaling molecules. Proteomic analysis identified 2096 and 1855 proteins in the ovarian cancer and cirrhosis ascites, respectively; 424 proteins were specific for the malignant ascites. Functional analysis of the proteome demonstrated that the major differences between cirrhosis and malignant ascites were observed for the cluster of spliceosomal proteins. Additionally, we demonstrate that several splicing RNAs were exclusively detected in malignant ascites, where they probably existed within protein complexes. This result was confirmed in vitro using an ovarian cancer cell line. Identification of spliceosomal proteins and RNAs in an extracellular medium is of particular interest; the finding suggests that they might play a role in the communication between cancer cells. In addition, malignant ascites contains a high number of exosomes that are known to play an important role in signal transduction. Thus our study reveals the specific features of malignant ascites that are associated with its function as a medium of intercellular communication. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Structured functional additive regression in reproducing kernel Hilbert spaces.

PubMed

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2014-06-01

Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application.

Design and Production of the Injection Mould with a Cax Assistance

NASA Astrophysics Data System (ADS)

Likavčan, Lukáš; Frnčík, Martin; Zaujec, Rudolf; Satin, Lukáš; Martinkovič, Maroš

2016-09-01

This paper is focused on the process of designing the desired plastic component and injection mould by using the 3D CAD systems. The subsequent FEM analysis of the injection mould process was carried out in order to define shrinkage and deformation of the plastic material by CAE system. The dimensions of the mould were then modified to compensate the shrinkage effect. Machining process (milling and the laser texturing) of the mould was performed by using CAM systems. Finally, after the production of the plastic components by the injection mould technology, the inspection of the plastic component dimensions was carried out by CAQ in order to define the accuracy of the whole CAx chain. It was also demonstrated that CAx systems are an integral part of pre-production and production process.

Fossil Energy Program

NASA Astrophysics Data System (ADS)

McNeese, L. E.

1981-01-01

Increased utilization of coal and other fossil fuel alternatives as sources of clean energy is reported. The following topics are discussed: coal conversion development, chemical research and development, materials technology, component development and process evaluation studies, technical support to major liquefaction projects, process analysis and engineering evaluations, fossil energy environmental analysis, flue gas desulfurization, solid waste disposal, coal preparation waste utilization, plant control development, atmospheric fluidized bed coal combustor for cogeneration, TVA FBC demonstration plant program technical support, PFBC systems analysis, fossil fuel applications assessments, performance assurance system support for fossil energy projects, international energy technology assessment, and general equilibrium models of liquid and gaseous fuel supplies.

Carbon charge exchange analysis in the ITER-like wall environment.

PubMed

Menmuir, S; Giroud, C; Biewer, T M; Coffey, I H; Delabie, E; Hawkes, N C; Sertoli, M

2014-11-01

Charge exchange spectroscopy has long been a key diagnostic tool for fusion plasmas and is well developed in devices with Carbon Plasma-Facing Components. Operation with the ITER-like wall at JET has resulted in changes to the spectrum in the region of the Carbon charge exchange line at 529.06 nm and demonstrates the need to revise the core charge exchange analysis for this line. An investigation has been made of this spectral region in different plasma conditions and the revised description of the spectral lines to be included in the analysis is presented.

Typing Local Control and State Using Flow Analysis

NASA Astrophysics Data System (ADS)

Guha, Arjun; Saftoiu, Claudiu; Krishnamurthi, Shriram

Programs written in scripting languages employ idioms that confound conventional type systems. In this paper, we highlight one important set of related idioms: the use of local control and state to reason informally about types. To address these idioms, we formalize run-time tags and their relationship to types, and use these to present a novel strategy to integrate typing with flow analysis in a modular way. We demonstrate that in our separation of typing and flow analysis, each component remains conventional, their composition is simple, but the result can handle these idioms better than either one alone.

An approximate methods approach to probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.

1989-01-01

A probabilistic structural analysis method (PSAM) is described which makes an approximate calculation of the structural response of a system, including the associated probabilistic distributions, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The method employs the fast probability integration (FPI) algorithm of Wu and Wirsching. Typical solution strategies are illustrated by formulations for a representative critical component chosen from the Space Shuttle Main Engine (SSME) as part of a major NASA-sponsored program on PSAM. Typical results are presented to demonstrate the role of the methodology in engineering design and analysis.

Science Alert Demonstration with a Rover Traverse Science Data Analysis System

NASA Technical Reports Server (NTRS)

Castano, R.; Estlin, T.; Gaines, D.; Castano, A.; Bornstein, B.; Anderson, R. C.; Judd, M.; Stough, T.; Wagstaff, K.

2005-01-01

The Onboard Autonomous Science Investigation System (OASIS) evaluates geologic data gathered by a planetary rover. This analysis is used to prioritize the data for transmission, so that the data with the highest science value is transmitted to Earth. In addition, the onboard analysis results are used to identify science opportunities. A planning and scheduling component of the system enables the rover to take advantage of the identified science opportunity. OASIS is a NASA-funded research project that is currently being tested on the FIDO rover at JPL for the use on future missions.

PRMS Data Warehousing Prototype

NASA Technical Reports Server (NTRS)

Guruvadoo, Eranna K.

2001-01-01

Project and Resource Management System (PRMS) is a web-based, mid-level management tool developed at KSC to provide a unified enterprise framework for Project and Mission management. The addition of a data warehouse as a strategic component to the PRMS is investigated through the analysis design and implementation processes of a data warehouse prototype. As a proof of concept, a demonstration of the prototype with its OLAP's technology for multidimensional data analysis is made. The results of the data analysis and the design constraints are discussed. The prototype can be used to motivate interest and support for an operational data warehouse.

PRMS Data Warehousing Prototype

NASA Technical Reports Server (NTRS)

Guruvadoo, Eranna K.

2002-01-01

Project and Resource Management System (PRMS) is a web-based, mid-level management tool developed at KSC to provide a unified enterprise framework for Project and Mission management. The addition of a data warehouse as a strategic component to the PRMS is investigated through the analysis, design and implementation processes of a data warehouse prototype. As a proof of concept, a demonstration of the prototype with its OLAP's technology for multidimensional data analysis is made. The results of the data analysis and the design constraints are discussed. The prototype can be used to motivate interest and support for an operational data warehouse.

Simulation investigation of multipactor in metal components for space application with an improved secondary emission model

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

Li, Yun, E-mail: genliyun@126.com, E-mail: cuiwanzhao@126.com; Cui, Wan-Zhao, E-mail: genliyun@126.com, E-mail: cuiwanzhao@126.com; Wang, Hong-Guang

2015-05-15

Effects of the secondary electron emission (SEE) phenomenon of metal surface on the multipactor analysis of microwave components are investigated numerically and experimentally in this paper. Both the secondary electron yield (SEY) and the emitted energy spectrum measurements are performed on silver plated samples for accurate description of the SEE phenomenon. A phenomenological probabilistic model based on SEE physics is utilized and fitted accurately to the measured SEY and emitted energy spectrum of the conditioned surface material of microwave components. Specially, the phenomenological probabilistic model is extended to the low primary energy end lower than 20 eV mathematically, since no accuratemore » measurement data can be obtained. Embedding the phenomenological probabilistic model into the Electromagnetic Particle-In-Cell (EM-PIC) method, the electronic resonant multipacting in microwave components can be tracked and hence the multipactor threshold can be predicted. The threshold prediction error of the transformer and the coaxial filter is 0.12 dB and 1.5 dB, respectively. Simulation results demonstrate that the discharge threshold is strongly dependent on the SEYs and its energy spectrum in the low energy end (lower than 50 eV). Multipacting simulation results agree quite well with experiments in practical components, while the phenomenological probabilistic model fit both the SEY and the emission energy spectrum better than the traditionally used model and distribution. The EM-PIC simulation method with the phenomenological probabilistic model for the surface collision simulation has been demonstrated for predicting the multipactor threshold in metal components for space application.« less

Applicability of the "Emotiv EEG Neuroheadset" as a user-friendly input interface.

PubMed

Boutani, Hidenori; Ohsuga, Mieko

2013-01-01

We aimed to develop an input interface by using the P3 component of visual event-related potentials (ERPs). When using electroencephalography (EEG) in daily applications, coping with ocular-motor artifacts and ensuring that the equipment is user-friendly are both important. To address the first issue, we applied a previously proposed method that applies an unmixing matrix to acquire independent components (ICs) obtained from another dataset. For the second issue, we introduced a 14-channel EEG commercial headset called the "Emotiv EEG Neuroheadset". An advantage of the Emotiv headset is that users can put it on by themselves within 1 min without any specific skills. However, only a few studies have investigated whether EEG and ERP signals are accurately measured by Emotiv. Additionally, no electrodes of the Emotiv headset are located over the centroparietal area of the head where P3 components are reported to show large amplitudes. Therefore, we first demonstrated that the P3 components obtained by the headset and by commercial plate electrodes and a multipurpose bioelectric amplifier during an oddball task were comparable. Next, we confirmed that eye-blink and ocular movement components could be decomposed by independent component analysis (ICA) using the 14-channel signals measured by the headset. We also demonstrated that artifacts could be removed with an unmixing matrix, as long as the matrix was obtained from the same person, even if they were measured on different days. Finally, we confirmed that the fluctuation of the sampling frequency of the Emotiv headset was not a major problem.

Demonstrating Principles of Spectrophotometry by Constructing a Simple, Low-Cost, Functional Spectrophotometer Utilizing the Light Sensor on a Smartphone

ERIC Educational Resources Information Center

Hosker, Bill S.

2018-01-01

A highly simplified variation on the do-it-yourself spectrophotometer using a smartphone's light sensor as a detector and an app to calculate and display absorbance values was constructed and tested. This simple version requires no need for electronic components or postmeasurement spectral analysis. Calibration graphs constructed from two…

Accounting for Poverty in Infrastructure Reform: Learning from Latin America's Experience. WBI Development Studies.

ERIC Educational Resources Information Center

Estache, Antonio; Foster, Vivien; Wodon, Quentin

This book explores the connections between infrastructure reform and poverty alleviation in Latin America based on a detailed analysis of the effects of a decade of reforms. The book demonstrates that because the access to, and affordability of, basic services is still a major problem, infrastructure investment will be a core component of poverty…

A Comparative Analysis of Competency Frameworks for Youth Workers in the Out-of-School Time Field

ERIC Educational Resources Information Center

Vance, Femi

2010-01-01

Research suggests that the quality of out-of-school time (OST) programs is related to positive youth outcomes and skilled staff are a critical component of high quality programming. This descriptive case study of competency frameworks for youth workers in the OST field demonstrates how experts and practitioners characterize a skilled youth worker.…

Automatic Classification of Artifactual ICA-Components for Artifact Removal in EEG Signals

PubMed Central

2011-01-01

Background Artifacts contained in EEG recordings hamper both, the visual interpretation by experts as well as the algorithmic processing and analysis (e.g. for Brain-Computer Interfaces (BCI) or for Mental State Monitoring). While hand-optimized selection of source components derived from Independent Component Analysis (ICA) to clean EEG data is widespread, the field could greatly profit from automated solutions based on Machine Learning methods. Existing ICA-based removal strategies depend on explicit recordings of an individual's artifacts or have not been shown to reliably identify muscle artifacts. Methods We propose an automatic method for the classification of general artifactual source components. They are estimated by TDSEP, an ICA method that takes temporal correlations into account. The linear classifier is based on an optimized feature subset determined by a Linear Programming Machine (LPM). The subset is composed of features from the frequency-, the spatial- and temporal domain. A subject independent classifier was trained on 640 TDSEP components (reaction time (RT) study, n = 12) that were hand labeled by experts as artifactual or brain sources and tested on 1080 new components of RT data of the same study. Generalization was tested on new data from two studies (auditory Event Related Potential (ERP) paradigm, n = 18; motor imagery BCI paradigm, n = 80) that used data with different channel setups and from new subjects. Results Based on six features only, the optimized linear classifier performed on level with the inter-expert disagreement (<10% Mean Squared Error (MSE)) on the RT data. On data of the auditory ERP study, the same pre-calculated classifier generalized well and achieved 15% MSE. On data of the motor imagery paradigm, we demonstrate that the discriminant information used for BCI is preserved when removing up to 60% of the most artifactual source components. Conclusions We propose a universal and efficient classifier of ICA components for the subject independent removal of artifacts from EEG data. Based on linear methods, it is applicable for different electrode placements and supports the introspection of results. Trained on expert ratings of large data sets, it is not restricted to the detection of eye- and muscle artifacts. Its performance and generalization ability is demonstrated on data of different EEG studies. PMID:21810266

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

Teaching evidence-based medicine: Impact on students' literature use and inpatient clinical documentation.

PubMed

Sastre, Elizabeth Ann; Denny, Joshua C; McCoy, Jacob A; McCoy, Allison B; Spickard, Anderson

2011-01-01

Effective teaching of evidence-based medicine (EBM) to medical students is important for lifelong self-directed learning. We implemented a brief workshop designed to teach literature searching skills to third-year medical students. We assessed its impact on students' utilization of EBM resources during their clinical rotation and the quality of EBM integration in inpatient notes. We developed a physician-led, hands-on workshop to introduce EBM resources to all internal medicine clerks. Pre- and post-workshop measures included student's attitudes to EBM, citations of EBM resources in their clinical notes, and quality of the EBM component of the discussion in the note. Computer log analysis recorded students' online search attempts. After the workshop, students reported improved comfort using EBM and increased utilization of EBM resources. EBM integration into the discussion component of the notes also showed significant improvement. Computer log analysis of students' searches demonstrated increased utilization of EBM resources following the workshop. We describe the successful implementation of a workshop designed to teach third-year medical students how to perform an efficient EBM literature search. We demonstrated improvements in students' confidence regarding EBM, increased utilization of EBM resources, and improved integration of EBM into inpatient notes.

Independent component analysis separates spikes of different origin in the EEG.

PubMed

Urrestarazu, Elena; Iriarte, Jorge; Artieda, Julio; Alegre, Manuel; Valencia, Miguel; Viteri, César

2006-02-01

Independent component analysis (ICA) is a novel system that finds independent sources in recorded signals. Its usefulness in separating epileptiform activity of different origin has not been determined. The goal of this study was to demonstrate that ICA is useful for separating different spikes using samples of EEG of patients with focal epilepsy. Digital EEG samples from four patients with focal epilepsy were included. The patients had temporal (n = 2), centrotemporal (n = 1) or frontal spikes (n = 1). Twenty-six samples with two (or more) spikes from two different patients were created. The selection of the two spikes for each mixed EEG was performed randomly, trying to have all the different combinations and rejecting the mixture of two spikes from the same patient. Two different examiners studied the EEGs using ICA with JADE paradigm in Matlab platform, trying to separate and to identify the spikes. They agreed in the correct separation of the spikes in 24 of the 26 samples, classifying the spikes as frontal, temporal or centrotemporal, left or right sided. The demonstration of the possibility of detecting different artificially mixed spikes confirms that ICA may be useful in separating spikes or other elements in real EEGs.

Micropower Mixed-signal VLSI Independent Component Analysis for Gradient Flow Acoustic Source Separation.

PubMed

Stanaćević, Milutin; Li, Shuo; Cauwenberghs, Gert

2016-07-01

A parallel micro-power mixed-signal VLSI implementation of independent component analysis (ICA) with reconfigurable outer-product learning rules is presented. With the gradient sensing of the acoustic field over a miniature microphone array as a pre-processing method, the proposed ICA implementation can separate and localize up to 3 sources in mild reverberant environment. The ICA processor is implemented in 0.5 µm CMOS technology and occupies 3 mm × 3 mm area. At 16 kHz sampling rate, ASIC consumes 195 µW power from a 3 V supply. The outer-product implementation of natural gradient and Herault-Jutten ICA update rules demonstrates comparable performance to benchmark FastICA algorithm in ideal conditions and more robust performance in noisy and reverberant environment. Experiments demonstrate perceptually clear separation and precise localization over wide range of separation angles of two speech sources presented through speakers positioned at 1.5 m from the array on a conference room table. The presented ASIC leads to a extreme small form factor and low power consumption microsystem for source separation and localization required in applications like intelligent hearing aids and wireless distributed acoustic sensor arrays.

The challenge of measuring emergency preparedness: integrating component metrics to build system-level measures for strategic national stockpile operations.

PubMed

Jackson, Brian A; Faith, Kay Sullivan

2013-02-01

Although significant progress has been made in measuring public health emergency preparedness, system-level performance measures are lacking. This report examines a potential approach to such measures for Strategic National Stockpile (SNS) operations. We adapted an engineering analytic technique used to assess the reliability of technological systems-failure mode and effects analysis-to assess preparedness. That technique, which includes systematic mapping of the response system and identification of possible breakdowns that affect performance, provides a path to use data from existing SNS assessment tools to estimate likely future performance of the system overall. Systems models of SNS operations were constructed and failure mode analyses were performed for each component. Linking data from existing assessments, including the technical assistance review and functional drills, to reliability assessment was demonstrated using publicly available information. The use of failure mode and effects estimates to assess overall response system reliability was demonstrated with a simple simulation example. Reliability analysis appears an attractive way to integrate information from the substantial investment in detailed assessments for stockpile delivery and dispensing to provide a view of likely future response performance.

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.

Topological image texture analysis for quality assessment

NASA Astrophysics Data System (ADS)

Asaad, Aras T.; Rashid, Rasber Dh.; Jassim, Sabah A.

2017-05-01

Image quality is a major factor influencing pattern recognition accuracy and help detect image tampering for forensics. We are concerned with investigating topological image texture analysis techniques to assess different type of degradation. We use Local Binary Pattern (LBP) as a texture feature descriptor. For any image construct simplicial complexes for selected groups of uniform LBP bins and calculate persistent homology invariants (e.g. number of connected components). We investigated image quality discriminating characteristics of these simplicial complexes by computing these models for a large dataset of face images that are affected by the presence of shadows as a result of variation in illumination conditions. Our tests demonstrate that for specific uniform LBP patterns, the number of connected component not only distinguish between different levels of shadow effects but also help detect the infected regions as well.

Assessing rumination in eating disorders: principal component analysis of a minimally modified ruminative response scale.

PubMed

Cowdrey, Felicity A; Park, Rebecca J

2011-12-01

A process account of eating disorders (EDs) (Park et al., in press-a) proposes that preoccupation with ruminative themes of eating, weight and shape may be important in ED maintenance. No self-report measure exists to capture disorder-specific rumination in EDs. 275 healthy participants rated rumination items and completed self-report measures of ED symptoms, depression and anxiety. Principal component analysis revealed two factors, reflection and brooding. The final nine-item Ruminative Response Scale for Eating Disorders (RRS-ED) demonstrated good convergent and discriminant validity and test-retest reliability. The psychometric properties were replicated in an anorexia nervosa sample. The findings support the notion that rumination in EDs is distinct from rumination in depression and is not adequately captured by existing measures. Copyright © 2011 Elsevier Ltd. All rights reserved.

Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm

NASA Astrophysics Data System (ADS)

Silveira, Landulfo, Jr.; Silveira, Fabrício L.; Bodanese, Benito; Pacheco, Marcos Tadeu T.; Zângaro, Renato A.

2012-02-01

This work demonstrated the discrimination among basal cell carcinoma (BCC) and normal human skin in vivo using near-infrared Raman spectroscopy. Spectra were obtained in the suspected lesion prior resectional surgery. After tissue withdrawn, biopsy fragments were submitted to histopathology. Spectra were also obtained in the adjacent, clinically normal skin. Raman spectra were measured using a Raman spectrometer (830 nm) with a fiber Raman probe. By comparing the mean spectra of BCC with the normal skin, it has been found important differences in the 800-1000 cm-1 and 1250-1350 cm-1 (vibrations of C-C and amide III, respectively, from lipids and proteins). A discrimination algorithm based on Principal Components Analysis and Mahalanobis distance (PCA/MD) could discriminate the spectra of both tissues with high sensitivity and specificity.

Quantification of acidic compounds in complex biomass-derived streams

DOE PAGES

Karp, Eric M.; Nimlos, Claire T.; Deutch, Steve; ...

2016-05-10

Biomass-derived streams that contain acidic compounds from the degradation of lignin and polysaccharides (e.g. black liquor, pyrolysis oil, pyrolytic lignin, etc.) are chemically complex solutions prone to instability and degradation during analysis, making quantification of compounds within them challenging. Here we present a robust analytical method to quantify acidic compounds in complex biomass-derived mixtures using ion exchange, sample reconstitution in pyridine and derivatization with BSTFA. The procedure is based on an earlier method originally reported for kraft black liquors and, in this work, is applied to identify and quantify a large slate of acidic compounds in corn stover derived alkalinemore » pretreatment liquor (APL) as a function of pretreatment severity. Analysis of the samples is conducted with GCxGC-TOFMS to achieve good resolution of the components within the complex mixture. The results reveal the dominant low molecular weight components and their concentrations as a function of pretreatment severity. Application of this method is also demonstrated in the context of lignin conversion technologies by applying it to track the microbial conversion of an APL substrate. Here as well excellent results are achieved, and the appearance and disappearance of compounds is observed in agreement with the known metabolic pathways of two bacteria, indicating the sample integrity was maintained throughout analysis. Finally, it is shown that this method applies more generally to lignin-rich materials by demonstrating its usefulness in analysis of pyrolysis oil and pyrolytic lignin.« less

Air Data Boom System Development for the Max Launch Abort System (MLAS) Flight Experiment

NASA Technical Reports Server (NTRS)

Woods-Vedeler, Jessica A.; Cox, Jeff; Bondurant, Robert; Dupont, Ron; ODonnell, Louise; Vellines, Wesley, IV; Johnston, William M.; Cagle, Christopher M.; Schuster, David M.; Elliott, Kenny B.;

[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.

Argo: an integrative, interactive, text mining-based workbench supporting curation

PubMed Central

Rak, Rafal; Rowley, Andrew; Black, William; Ananiadou, Sophia

2012-01-01

Curation of biomedical literature is often supported by the automatic analysis of textual content that generally involves a sequence of individual processing components. Text mining (TM) has been used to enhance the process of manual biocuration, but has been focused on specific databases and tasks rather than an environment integrating TM tools into the curation pipeline, catering for a variety of tasks, types of information and applications. Processing components usually come from different sources and often lack interoperability. The well established Unstructured Information Management Architecture is a framework that addresses interoperability by defining common data structures and interfaces. However, most of the efforts are targeted towards software developers and are not suitable for curators, or are otherwise inconvenient to use on a higher level of abstraction. To overcome these issues we introduce Argo, an interoperable, integrative, interactive and collaborative system for text analysis with a convenient graphic user interface to ease the development of processing workflows and boost productivity in labour-intensive manual curation. Robust, scalable text analytics follow a modular approach, adopting component modules for distinct levels of text analysis. The user interface is available entirely through a web browser that saves the user from going through often complicated and platform-dependent installation procedures. Argo comes with a predefined set of processing components commonly used in text analysis, while giving the users the ability to deposit their own components. The system accommodates various areas and levels of user expertise, from TM and computational linguistics to ontology-based curation. One of the key functionalities of Argo is its ability to seamlessly incorporate user-interactive components, such as manual annotation editors, into otherwise completely automatic pipelines. As a use case, we demonstrate the functionality of an in-built manual annotation editor that is well suited for in-text corpus annotation tasks. Database URL: http://www.nactem.ac.uk/Argo PMID:22434844

Structural analyses of the JPL Mars Pathfinder impact

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

Gwinn, K.W.

1994-12-31

The purpose of this paper is to demonstrate that finite element analysis can be used in the design process for high performance fabric structures. These structures exhibit extreme geometric nonlinearity; specifically, the contact and interaction of fabric surfaces with the large deformation which necessarily results from membrane structures introduces great complexity to analyses of this type. All of these features are demonstrated here in the analysis of the Jet Propulsion Laboratory (JPL) Mars Pathfinder impact onto Mars. This lander system uses airbags to envelope the lander experiment package, protecting it with large deformation upon contact. Results from the analysis showmore » the stress in the fabric airbags, forces in the internal tendon support system, forces in the latches and hinges which allow the lander to deploy after impact, and deceleration of the lander components. All of these results provide the JPL engineers with design guidance for the success of this novel lander system.« less

Structural analyses of the JPL Mars Pathfinder impact

NASA Astrophysics Data System (ADS)

Gwinn, Kenneth W.

The purpose of this paper is to demonstrate that finite element analysis can be used in the design process for high performance fabric structures. These structures exhibit extreme geometric nonlinearity; specifically, the contact and interaction of fabric surfaces with the large deformation which necessarily results from membrane structures introduces great complexity to analyses of this type. All of these features are demonstrated here in the analysis of the Jet Propulsion Laboratory (JPL) Mars Pathfinder impact onto Mars. This lander system uses airbags to envelope the lander experiment package, protecting it with large deformation upon contact. Results from the analysis show the stress in the fabric airbags, forces in the internal tendon support system, forces in the latches and hinges which allow the lander to deploy after impact, and deceleration of the lander components. All of these results provide the JPL engineers with design guidance for the success of this novel lander system.

Flow Injection Mass Spectral Fingerprints Demonstrate Chemical Differences in Rio Red Grapefruit with Respect to Year, Harvest Time, and Conventional versus Organic Farming

PubMed Central

Chen, Pei; Harnly, James M.; Lester, Gene E.

2013-01-01

Spectral fingerprints were acquired for Rio Red grapefruit using flow injection electrospray ionization with ion trap and time-of-flight mass spectrometry (FI-ESI-IT-MS and FI-ESI-TOF-MS). Rio Red grapefruits were harvested 3 times a year (early, mid, and late harvests) in 2005 and 2006 from conventionally and organically grown trees. Data analysis using analysis of variance principal component analysis (ANOVA-PCA) demonstrated that, for both MS systems, the chemical patterns were different as a function of farming mode (conventional vs organic), as well as growing year and time of harvest. This was visually obvious with PCA and was shown to be statistically significant using ANOVA. The spectral fingerprints provided a more inclusive view of the chemical composition of the grapefruit and extended previous conclusions regarding the chemical differences between conventionally and organically grown Rio Red grapefruit. PMID:20337420

Design and analysis of compact MMIC switches utilising GaAs pHEMTs in 3D multilayer technology

NASA Astrophysics Data System (ADS)

Haris, Norshakila; Kyabaggu, Peter B. K.; Alim, Mohammad A.; Rezazadeh, Ali A.

2017-05-01

In this paper, we demonstrate for the first time the implementation of three-dimensional multilayer technology on GaAs-based pseudomorphic high electron mobility transistor (pHEMT) switches. Two types of pHEMT switches are considered, namely single-pole single-throw (SPST) and single-pole double-throw (SPDT). The design and analysis of the devices are demonstrated first through a simulation of the industry-recognised standard model, TriQuint’s Own Model—Level 3, developed by TriQuint Semiconductor, Inc. From the simulation analysis, three optimised SPST and SPDT pHEMT switches which can address applications ranging from L to X bands, are fabricated and tested. The performance of the pHEMT switches using multilayer technology are comparable to those of the current state-of-the-art pHEMT switches, while simultaneously offering compact circuits with the advantages of integration with other MMIC components.

Two Components of the RNA-Directed DNA Methylation Pathway Associate with MORC6 and Silence Loci Targeted by MORC6 in Arabidopsis

PubMed Central

Liu, Zhang-Wei; Zhou, Jin-Xing; Huang, Huan-Wei; Li, Yong-Qiang; Shao, Chang-Rong; Li, Lin; Cai, Tao; Chen, She

2016-01-01

The SU(VAR)3-9 homolog SUVH9 and the double-stranded RNA-binding protein IDN2 were thought to be components of an RNA-directed DNA methylation (RdDM) pathway in Arabidopsis. We previously found that SUVH9 interacts with MORC6 but how the interaction contributes to transcriptional silencing remains elusive. Here, our genetic analysis indicates that SUVH2 and SUVH9 can either act in the same pathway as MORC6 or act synergistically with MORC6 to mediate transcriptional silencing. Moreover, we demonstrate that IDN2 interacts with MORC6 and mediates the silencing of a subset of MORC6 target loci. Like SUVH2, SUVH9, and IDN2, other RdDM components including Pol IV, Pol V, RDR2, and DRM2 are also required for transcriptional silencing at a subset of MORC6 target loci. MORC6 was previously shown to mediate transcriptional silencing through heterochromatin condensation. We demonstrate that the SWI/SNF chromatin-remodeling complex components SWI3B, SWI3C, and SWI3D interact with MORC6 as well as with SUVH9 and then mediate transcriptional silencing. These results suggest that the RdDM components are involved not only in DNA methylation but also in MORC6-mediated heterochromatin condensation. This study illustrates how DNA methylation is linked to heterochromatin condensation and thereby enhances transcriptional silencing at methylated genomic regions. PMID:27171427

Variation in the Humification Degree of Dissolved Organic Matter from Cattle Manure during Composting as Analyzed by Ultraviolet-Visible and Fluorescence Spectroscopy.

PubMed

Chen, Yukun; Jiang, Zhao; Zhang, Xiuyuan; Cao, Bo; Yang, Fan; Wang, Ziyi; Zhang, Ying

2017-11-01

This study investigated the degree of humification of dissolved organic matter (DOM) during different periods of cattle manure composting using ultraviolet-visible (UV-vis) and fluorescence spectroscopy (emission, synchronous scan, and excitation-emission matrix) and determined which method is more suitable for analysis of the humification degree of DOM. Two composting piles were prepared by mixing manure and corn straw. One pile (Pile A [PA]) contained inoculated exogenous composite agents at a ratio of 2% (v/v), and a pile without the addition of inoculants (PNA) served as the control treatment. The results showed that ultraviolet integrated absorption intensities in the range of 226 to 400 nm and 260 to 280 nm and specific ultraviolet absorbances at 254 and 280 nm of both PA and PNA gradually increased with composting time. Based on the fluorescence regional integration analysis and parallel factor analysis, the humic-like substances became the main components of the DOM after composting. Our study demonstrated that the humification degree of DOM was enhanced during composting and that the inoculation composite agent was beneficial for the humification of DOM at the mesophilic and thermophilic phases of the composting process. Moreover, the results of correlation analysis and principal component analysis demonstrated that the fluorescence spectral parameters evaluated the humification degree of DOM during the whole cattle manure composting process better than the UV-vis spectral parameters. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Nonlinear transient chirp signal modeling of the aortic and pulmonary components of the second heart sound.

PubMed

Xu, J; Durand, L G; Pibarot, P

2000-10-01

This paper describes a new approach based on the time-frequency representation of transient nonlinear chirp signals for modeling the aortic (A2) and the pulmonary (P2) components of the second heart sound (S2). It is demonstrated that each component is a narrow-band signal with decreasing instantaneous frequency defined by its instantaneous amplitude and its instantaneous phase. Each component is also a polynomial phase signal, the instantaneous phase of which can be accurately represented by a polynomial having an order of thirty. A dechirping approach is used to obtain the instantaneous amplitude of each component while reducing the effect of the background noise. The analysis-synthesis procedure is applied to 32 isolated A2 and 32 isolated P2 components recorded in four pigs with pulmonary hypertension. The mean +/- standard deviation of the normalized root-mean-squared error (NRMSE) and the correlation coefficient (rho) between the original and the synthesized signal components were: NRMSE = 2.1 +/- 0.3% and rho = 0.97 +/- 0.02 for A2 and NRMSE = 2.52 +/- 0.5% and rho = 0.96 +/- 0.02 for P2. These results confirm that each component can be modeled as mono-component nonlinear chirp signals of short duration with energy distributions concentrated along its decreasing instantaneous frequency.

Study of polarization properties of fiber-optics probes with use of a binary phase plate.

PubMed

Alferov, S V; Khonina, S N; Karpeev, S V

2014-04-01

We conduct a theoretical and experimental study of the distribution of the electric field components in the sharp focal domain when rotating a zone plate with a π-phase jump placed in the focused beam. Comparing the theoretical and experimental results for several kinds of near-field probes, an analysis of the polarization sensitivity of different types of metal-coated aperture probes is conducted. It is demonstrated that with increasing diameter of the non-metal-coated tip part there occurs an essential redistribution of sensitivity in favor of the transverse electric field components and an increase of the probe's energy throughput.

Evidence of tampering in watermark identification

NASA Astrophysics Data System (ADS)

McLauchlan, Lifford; Mehrübeoglu, Mehrübe

2009-08-01

In this work, watermarks are embedded in digital images in the discrete wavelet transform (DWT) domain. Principal component analysis (PCA) is performed on the DWT coefficients. Next higher order statistics based on the principal components and the eigenvalues are determined for different sets of images. Feature sets are analyzed for different types of attacks in m dimensional space. The results demonstrate the separability of the features for the tampered digital copies. Different feature sets are studied to determine more effective tamper evident feature sets. The digital forensics, the probable manipulation(s) or modification(s) performed on the digital information can be identified using the described technique.

The first X-45A Unmanned Combat Air Vehicle (UCAV) technology demonstrator completed its sixth flight on Dec. 19, 2002, raising its landing gear in flight for the first time. The X-45A flew for 40 minutes and reached an airspeed of 195 knots

NASA Image and Video Library

2002-12-19

The first X-45A Unmanned Combat Air Vehicle (UCAV) technology demonstrator completed its sixth flight on Dec. 19, 2002, raising its landing gear in flight for the first time. The X-45A flew for 40 minutes and reached an airspeed of 195 knots and an altitude of 7,500 feet. Dryden is supporting the DARPA/Boeing team in the design, development, integration, and demonstration of the critical technologies, processes, and system attributes leading to an operational UCAV system. Dryden support of the X-45A demonstrator system includes analysis, component development, simulations, ground and flight tests.

Characterization of Chinese liquor aroma components during aging process and liquor age discrimination using gas chromatography combined with multivariable statistics

NASA Astrophysics Data System (ADS)

Xu, M. L.; Yu, Y.; Ramaswamy, H. S.; Zhu, S. M.

2017-01-01

Chinese liquor aroma components were characterized during the aging process using gas chromatography (GC). Principal component and cluster analysis (PCA, CA) were used to discriminate the Chinese liquor age which has a great economic value. Of a total of 21 major aroma components identified and quantified, 13 components which included several acids, alcohols, esters, aldehydes and furans decreased significantly in the first year of aging, maintained the same levels (p > 0.05) for next three years and decreased again (p < 0.05) in the fifth year. On the contrary, a significant increase was observed in propionic acid, furfural and phenylethanol. Ethyl lactate was found to be the most stable aroma component during aging process. Results of PCA and CA demonstrated that young liquor (fresh) and aged liquors were well separated from each other, which is in consistent with the evolution of aroma components along with the aging process. These findings provide a quantitative basis for discriminating the Chinese liquor age and a scientific basis for further research on elucidating the liquor aging process, and a possible tool to guard against counterfeit and defective products.

Chemometric Data Analysis for Deconvolution of Overlapped Ion Mobility Profiles

NASA Astrophysics Data System (ADS)

Zekavat, Behrooz; Solouki, Touradj

2012-11-01

We present the details of a data analysis approach for deconvolution of the ion mobility (IM) overlapped or unresolved species. This approach takes advantage of the ion fragmentation variations as a function of the IM arrival time. The data analysis involves the use of an in-house developed data preprocessing platform for the conversion of the original post-IM/collision-induced dissociation mass spectrometry (post-IM/CID MS) data to a Matlab compatible format for chemometric analysis. We show that principle component analysis (PCA) can be used to examine the post-IM/CID MS profiles for the presence of mobility-overlapped species. Subsequently, using an interactive self-modeling mixture analysis technique, we show how to calculate the total IM spectrum (TIMS) and CID mass spectrum for each component of the IM overlapped mixtures. Moreover, we show that PCA and IM deconvolution techniques provide complementary results to evaluate the validity of the calculated TIMS profiles. We use two binary mixtures with overlapping IM profiles, including (1) a mixture of two non-isobaric peptides (neurotensin (RRPYIL) and a hexapeptide (WHWLQL)), and (2) an isobaric sugar isomer mixture of raffinose and maltotriose, to demonstrate the applicability of the IM deconvolution.

Modality-Spanning Deficits in Attention-Deficit/Hyperactivity Disorder in Functional Networks, Gray Matter, and White Matter

PubMed Central

Kessler, Daniel; Angstadt, Michael; Welsh, Robert C.

2014-01-01

Previous neuroimaging investigations in attention-deficit/hyperactivity disorder (ADHD) have separately identified distributed structural and functional deficits, but interconnections between these deficits have not been explored. To unite these modalities in a common model, we used joint independent component analysis, a multivariate, multimodal method that identifies cohesive components that span modalities. Based on recent network models of ADHD, we hypothesized that altered relationships between large-scale networks, in particular, default mode network (DMN) and task-positive networks (TPNs), would co-occur with structural abnormalities in cognitive regulation regions. For 756 human participants in the ADHD-200 sample, we produced gray and white matter volume maps with voxel-based morphometry, as well as whole-brain functional connectomes. Joint independent component analysis was performed, and the resulting transmodal components were tested for differential expression in ADHD versus healthy controls. Four components showed greater expression in ADHD. Consistent with our a priori hypothesis, we observed reduced DMN-TPN segregation co-occurring with structural abnormalities in dorsolateral prefrontal cortex and anterior cingulate cortex, two important cognitive control regions. We also observed altered intranetwork connectivity in DMN, dorsal attention network, and visual network, with co-occurring distributed structural deficits. There was strong evidence of spatial correspondence across modalities: For all four components, the impact of the respective component on gray matter at a region strongly predicted the impact on functional connectivity at that region. Overall, our results demonstrate that ADHD involves multiple, cohesive modality spanning deficits, each one of which exhibits strong spatial overlap in the pattern of structural and functional alterations. PMID:25505309

COMPUTATIONAL ANALYSIS OF SWALLOWING MECHANICS UNDERLYING IMPAIRED EPIGLOTTIC INVERSION

PubMed Central

Pearson, William G.; Taylor, Brandon K; Blair, Julie; Martin-Harris, Bonnie

2015-01-01

Objective Determine swallowing mechanics associated with the first and second epiglottic movements, that is, movement to horizontal and full inversion respectively, in order to provide a clinical interpretation of impaired epiglottic function. Study Design Retrospective cohort study. Methods A heterogeneous cohort of patients with swallowing difficulties was identified (n=92). Two speech-language pathologists reviewed 5ml thin and 5ml pudding videofluoroscopic swallow studies per subject, and assigned epiglottic component scores of 0=complete inversion, 1=partial inversion, and 2=no inversion forming three groups of videos for comparison. Coordinates mapping minimum and maximum excursion of the hyoid, pharynx, larynx, and tongue base during pharyngeal swallowing were recorded using ImageJ software. A canonical variate analysis with post-hoc discriminant function analysis of coordinates was performed using MorphoJ software to evaluate mechanical differences between groups. Eigenvectors characterizing swallowing mechanics underlying impaired epiglottic movements were visualized. Results Nineteen of 184 video-swallows were rejected for poor quality (n=165). A Goodman-Kruskal index of predictive association showed no correlation between epiglottic component scores and etiologies of dysphagia (λ=.04). A two-way analysis of variance by epiglottic component scores showed no significant interaction effects between sex and age (f=1.4, p=.25). Discriminant function analysis demonstrated statistically significant mechanical differences between epiglottic component scores: 1&2, representing the first epiglottic movement (Mahalanobis distance=1.13, p=.0007); and, 0&1, representing the second epiglottic movement (Mahalanobis distance=0.83, p=.003). Eigenvectors indicate that laryngeal elevation and tongue base retraction underlie both epiglottic movements. Conclusion Results suggest that reduced tongue base retraction and laryngeal elevation underlie impaired first and second epiglottic movements. The styloglossus, hyoglossus and long pharyngeal muscles are implicated as targets for rehabilitation in dysphagic patients with impaired epiglottic inversion. PMID:27426940

A novel improved method for analysis of 2D diffusion relaxation data—2D PARAFAC-Laplace decomposition

NASA Astrophysics Data System (ADS)

Tønning, Erik; Polders, Daniel; Callaghan, Paul T.; Engelsen, Søren B.

2007-09-01

This paper demonstrates how the multi-linear PARAFAC model can with advantage be used to decompose 2D diffusion-relaxation correlation NMR spectra prior to 2D-Laplace inversion to the T2- D domain. The decomposition is advantageous for better interpretation of the complex correlation maps as well as for the quantification of extracted T2- D components. To demonstrate the new method seventeen mixtures of wheat flour, starch, gluten, oil and water were prepared and measured with a 300 MHz nuclear magnetic resonance (NMR) spectrometer using a pulsed gradient stimulated echo (PGSTE) pulse sequence followed by a Carr-Purcell-Meiboom-Gill (CPMG) pulse echo train. By varying the gradient strength, 2D diffusion-relaxation data were recorded for each sample. From these double exponentially decaying relaxation data the PARAFAC algorithm extracted two unique diffusion-relaxation components, explaining 99.8% of the variation in the data set. These two components were subsequently transformed to the T2- D domain using 2D-inverse Laplace transformation and quantitatively assigned to the oil and water components of the samples. The oil component was one distinct distribution with peak intensity at D = 3 × 10 -12 m 2 s -1 and T2 = 180 ms. The water component consisted of two broad populations of water molecules with diffusion coefficients and relaxation times centered around correlation pairs: D = 10 -9 m 2 s -1, T2 = 10 ms and D = 3 × 10 -13 m 2 s -1, T2 = 13 ms. Small spurious peaks observed in the inverse Laplace transformation of original complex data were effectively filtered by the PARAFAC decomposition and thus considered artefacts from the complex Laplace transformation. The oil-to-water ratio determined by PARAFAC followed by 2D-Laplace inversion was perfectly correlated with known oil-to-water ratio of the samples. The new method of using PARAFAC prior to the 2D-Laplace inversion proved to have superior potential in analysis of diffusion-relaxation spectra, as it improves not only the interpretation, but also the quantification.

Comparative Proteomic and Nutritional Composition Analysis of Independent Transgenic Pigeon Pea Seeds Harboring cry1AcF and cry2Aa Genes and Their Nontransgenic Counterparts.

PubMed

Mishra, Pragya; Singh, Shweta; Rathinam, Maniraj; Nandiganti, Muralimohan; Ram Kumar, Nikhil; Thangaraj, Arulprakash; Thimmegowda, Vinutha; Krishnan, Veda; Mishra, Vagish; Jain, Neha; Rai, Vandna; Pattanayak, Debasis; Sreevathsa, Rohini

2017-02-22

Safety assessment of genetically modified plants is an important aspect prior to deregulation. Demonstration of substantial equivalence of the transgenics compared to their nontransgenic counterparts can be performed using different techniques at various molecular levels. The present study is a first-ever comprehensive evaluation of pigeon pea transgenics harboring two independent cry genes, cry2Aa and cry1AcF. The absence of unintended effects in the transgenic seed components was demonstrated by proteome and nutritional composition profiling. Analysis revealed that no significant differences were found in the various nutritional compositional analyses performed. Additionally, 2-DGE-based proteome analysis of the transgenic and nontransgenic seed protein revealed that there were no major changes in the protein profile, although a minor fold change in the expression of a few proteins was observed. Furthermore, the study also demonstrated that neither the integration of T-DNA nor the expression of the cry genes resulted in the production of unintended effects in the form of new toxins or allergens.

Revealing the microstructure of the giant component in random graph ensembles

NASA Astrophysics Data System (ADS)

Tishby, Ido; Biham, Ofer; Katzav, Eytan; Kühn, Reimer

2018-04-01

The microstructure of the giant component of the Erdős-Rényi network and other configuration model networks is analyzed using generating function methods. While configuration model networks are uncorrelated, the giant component exhibits a degree distribution which is different from the overall degree distribution of the network and includes degree-degree correlations of all orders. We present exact analytical results for the degree distributions as well as higher-order degree-degree correlations on the giant components of configuration model networks. We show that the degree-degree correlations are essential for the integrity of the giant component, in the sense that the degree distribution alone cannot guarantee that it will consist of a single connected component. To demonstrate the importance and broad applicability of these results, we apply them to the study of the distribution of shortest path lengths on the giant component, percolation on the giant component, and spectra of sparse matrices defined on the giant component. We show that by using the degree distribution on the giant component one obtains high quality results for these properties, which can be further improved by taking the degree-degree correlations into account. This suggests that many existing methods, currently used for the analysis of the whole network, can be adapted in a straightforward fashion to yield results conditioned on the giant component.

A CAD Approach to Integrating NDE With Finite Element

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Downey, James; Ghosn, Louis J.; Baaklini, George Y.

2004-01-01

Nondestructive evaluation (NDE) is one of several technologies applied at NASA Glenn Research Center to determine atypical deformities, cracks, and other anomalies experienced by structural components. NDE consists of applying high-quality imaging techniques (such as x-ray imaging and computed tomography (CT)) to discover hidden manufactured flaws in a structure. Efforts are in progress to integrate NDE with the finite element (FE) computational method to perform detailed structural analysis of a given component. This report presents the core outlines for an in-house technical procedure that incorporates this combined NDE-FE interrelation. An example is presented to demonstrate the applicability of this analytical procedure. FE analysis of a test specimen is performed, and the resulting von Mises stresses and the stress concentrations near the anomalies are observed, which indicates the fidelity of the procedure. Additional information elaborating on the steps needed to perform such an analysis is clearly presented in the form of mini step-by-step guidelines.

Thermal Inspection of a Composite Fuselage Section Using a Fixed Eigenvector Principal Component Analysis Method

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Bolduc, Sean; Harman, Rebecca

2017-01-01

A composite fuselage aircraft forward section was inspected with flash thermography. The fuselage section is 24 feet long and approximately 8 feet in diameter. The structure is primarily configured with a composite sandwich structure of carbon fiber face sheets with a Nomex(Trademark) honeycomb core. The outer surface area was inspected. The thermal data consisted of 477 data sets totaling in size of over 227 Gigabytes. Principal component analysis (PCA) was used to process the data sets for substructure and defect detection. A fixed eigenvector approach using a global covariance matrix was used and compared to a varying eigenvector approach. The fixed eigenvector approach was demonstrated to be a practical analysis method for the detection and interpretation of various defects such as paint thickness variation, possible water intrusion damage, and delamination damage. In addition, inspection considerations are discussed including coordinate system layout, manipulation of the fuselage section, and the manual scanning technique used for full coverage.

Effect of Gender on the Knowledge of Medicinal Plants: Systematic Review and Meta-Analysis

PubMed Central

Torres-Avilez, Wendy; de Medeiros, Patrícia Muniz

2016-01-01

Knowledge of medicinal plants is not only one of the main components in the structure of knowledge in local medical systems but also one of the most studied resources. This study uses a systematic review and meta-analysis of a compilation of ethnobiological studies with a medicinal plant component and the variable of gender to evaluate whether there is a gender-based pattern in medicinal plant knowledge on different scales (national, continental, and global). In this study, three types of meta-analysis are conducted on different scales. We detect no significant differences on the global level; women and men have the same rich knowledge. On the national and continental levels, significant differences are observed in both directions (significant for men and for women), and a lack of significant differences in the knowledge of the genders is also observed. This finding demonstrates that there is no gender-based pattern for knowledge on different scales. PMID:27795730

Big Data in Reciprocal Space: Sliding Fast Fourier Transforms for Determining Periodicity

DOE PAGES

Vasudevan, Rama K.; Belianinov, Alex; Gianfrancesco, Anthony G.; ...

2015-03-03

Significant advances in atomically resolved imaging of crystals and surfaces have occurred in the last decade allowing unprecedented insight into local crystal structures and periodicity. Yet, the analysis of the long-range periodicity from the local imaging data, critical to correlation of functional properties and chemistry to the local crystallography, remains a challenge. Here, we introduce a Sliding Fast Fourier Transform (FFT) filter to analyze atomically resolved images of in-situ grown La5/8Ca3/8MnO3 films. We demonstrate the ability of sliding FFT algorithm to differentiate two sub-lattices, resulting from a mixed-terminated surface. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) of themore » Sliding FFT dataset reveal the distinct changes in crystallography, step edges and boundaries between the multiple sub-lattices. The method is universal for images with any periodicity, and is especially amenable to atomically resolved probe and electron-microscopy data for rapid identification of the sub-lattices present.« less

Big Data in Reciprocal Space: Sliding Fast Fourier Transforms for Determining Periodicity

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

Vasudevan, Rama K.; Belianinov, Alex; Gianfrancesco, Anthony G.

Significant advances in atomically resolved imaging of crystals and surfaces have occurred in the last decade allowing unprecedented insight into local crystal structures and periodicity. Yet, the analysis of the long-range periodicity from the local imaging data, critical to correlation of functional properties and chemistry to the local crystallography, remains a challenge. Here, we introduce a Sliding Fast Fourier Transform (FFT) filter to analyze atomically resolved images of in-situ grown La5/8Ca3/8MnO3 films. We demonstrate the ability of sliding FFT algorithm to differentiate two sub-lattices, resulting from a mixed-terminated surface. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) of themore » Sliding FFT dataset reveal the distinct changes in crystallography, step edges and boundaries between the multiple sub-lattices. The method is universal for images with any periodicity, and is especially amenable to atomically resolved probe and electron-microscopy data for rapid identification of the sub-lattices present.« less

Partitioning the relative contributions of inorganic plant composition and soil characteristics to the quality of Helichrysum italicum subsp. italicum (Roth) G. Don fil. essential oil.

PubMed

Bianchini, Ange; Santoni, François; Paolini, Julien; Bernardini, Antoine-François; Mouillot, David; Costa, Jean

2009-07-01

Composition of Helichrysum italicum subsp. italicum essential oil showed chemical variability according to vegetation cycle, environment, and geographic origins. In the present work, 48 individuals of this plant at different development stages and the corresponding root soils were sampled: i) 28 volatile components were identified and measured in essential oil by using GC and GC/MS; ii) ten elements from plants and soils have been estimated using colorimetry in continuous flux, flame atomic absorption spectrometry, or emission spectrometry (FAAS/FAES); iii) texture and acidity (real and potential) of soil samples were also reported. Relationships between the essential-oil composition, the inorganic plant composition, and the soil characteristics (inorganic composition, texture, and acidity) have been established using multivariate analysis such as Principal Component Analysis (PCA) and partial Redundancy Analysis (RDA). This study demonstrates a high level of intraspecific differences in oil composition due to environmental factors and, more particularly, soil characteristics.

Macro-fingerprint analysis-through-separation of licorice based on FT-IR and 2DCOS-IR

NASA Astrophysics Data System (ADS)

Wang, Yang; Wang, Ping; Xu, Changhua; Yang, Yan; Li, Jin; Chen, Tao; Li, Zheng; Cui, Weili; Zhou, Qun; Sun, Suqin; Li, Huifen

2014-07-01

In this paper, a step-by-step analysis-through-separation method under the navigation of multi-step IR macro-fingerprint (FT-IR integrated with second derivative IR (SD-IR) and 2DCOS-IR) was developed for comprehensively characterizing the hierarchical chemical fingerprints of licorice from entirety to single active components. Subsequently, the chemical profile variation rules of three parts (flavonoids, saponins and saccharides) in the separation process were holistically revealed and the number of matching peaks and correlation coefficients with standards of pure compounds was increasing along the extracting directions. The findings were supported by UPLC results and a verification experiment of aqueous separation process. It has been demonstrated that the developed multi-step IR macro-fingerprint analysis-through-separation approach could be a rapid, effective and integrated method not only for objectively providing comprehensive chemical characterization of licorice and all its separated parts, but also for rapidly revealing the global enrichment trend of the active components in licorice separation process.

Short wavelength Raman spectroscopy applied to the discrimination and characterization of three cultivars of extra virgin olive oils in different maturation stages.

PubMed

Gouvinhas, Irene; Machado, Nelson; Carvalho, Teresa; de Almeida, José M M M; Barros, Ana I R N A

2015-01-01

Extra virgin olive oils produced from three cultivars on different maturation stages were characterized using Raman spectroscopy. Chemometric methods (principal component analysis, discriminant analysis, principal component regression and partial least squares regression) applied to Raman spectral data were utilized to evaluate and quantify the statistical differences between cultivars and their ripening process. The models for predicting the peroxide value and free acidity of olive oils showed good calibration and prediction values and presented high coefficients of determination (>0.933). Both the R(2), and the correlation equations between the measured chemical parameters, and the values predicted by each approach are presented; these comprehend both PCR and PLS, used to assess SNV normalized Raman data, as well as first and second derivative of the spectra. This study demonstrates that a combination of Raman spectroscopy with multivariate analysis methods can be useful to predict rapidly olive oil chemical characteristics during the maturation process. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of neural network techniques for finger-vein pattern classification

NASA Astrophysics Data System (ADS)

Wu, Jian-Da; Liu, Chiung-Tsiung; Tsai, Yi-Jang; Liu, Jun-Ching; Chang, Ya-Wen

2010-02-01

A personal identification system using finger-vein patterns and neural network techniques is proposed in the present study. In the proposed system, the finger-vein patterns are captured by a device that can transmit near infrared through the finger and record the patterns for signal analysis and classification. The biometric system for verification consists of a combination of feature extraction using principal component analysis and pattern classification using both back-propagation network and adaptive neuro-fuzzy inference systems. Finger-vein features are first extracted by principal component analysis method to reduce the computational burden and removes noise residing in the discarded dimensions. The features are then used in pattern classification and identification. To verify the effect of the proposed adaptive neuro-fuzzy inference system in the pattern classification, the back-propagation network is compared with the proposed system. The experimental results indicated the proposed system using adaptive neuro-fuzzy inference system demonstrated a better performance than the back-propagation network for personal identification using the finger-vein patterns.

Risk and Vulnerability Analysis of Satellites Due to MM/SD with PIRAT

NASA Astrophysics Data System (ADS)

Kempf, Scott; Schafer, Frank Rudolph, Martin; Welty, Nathan; Donath, Therese; Destefanis, Roberto; Grassi, Lilith; Janovsky, Rolf; Evans, Leanne; Winterboer, Arne

2013-08-01

Until recently, the state-of-the-art assessment of the threat posed to spacecraft by micrometeoroids and space debris was limited to the application of ballistic limit equations to the outer hull of a spacecraft. The probability of no penetration (PNP) is acceptable for assessing the risk and vulnerability of manned space mission, however, for unmanned missions, whereby penetrations of the spacecraft exterior do not necessarily constitute satellite or mission failure, these values are overly conservative. The newly developed software tool PIRAT (Particle Impact Risk and Vulnerability Analysis Tool) has been developed based on the Schäfer-Ryan-Lambert (SRL) triple-wall ballistic limit equation (BLE), applicable for various satellite components. As a result, it has become possible to assess the individual failure rates of satellite components. This paper demonstrates the modeling of an example satellite, the performance of a PIRAT analysis and the potential for subsequent design optimizations with respect of micrometeoroid and space debris (MM/SD) impact risk.

Strategies and Approaches to TPS Design

NASA Technical Reports Server (NTRS)

Kolodziej, Paul

2005-01-01

Thermal protection systems (TPS) insulate planetary probes and Earth re-entry vehicles from the aerothermal heating experienced during hypersonic deceleration to the planet s surface. The systems are typically designed with some additional capability to compensate for both variations in the TPS material and for uncertainties in the heating environment. This additional capability, or robustness, also provides a surge capability for operating under abnormal severe conditions for a short period of time, and for unexpected events, such as meteoroid impact damage, that would detract from the nominal performance. Strategies and approaches to developing robust designs must also minimize mass because an extra kilogram of TPS displaces one kilogram of payload. Because aircraft structures must be optimized for minimum mass, reliability-based design approaches for mechanical components exist that minimize mass. Adapting these existing approaches to TPS component design takes advantage of the extensive work, knowledge, and experience from nearly fifty years of reliability-based design of mechanical components. A Non-Dimensional Load Interference (NDLI) method for calculating the thermal reliability of TPS components is presented in this lecture and applied to several examples. A sensitivity analysis from an existing numerical simulation of a carbon phenolic TPS provides insight into the effects of the various design parameters, and is used to demonstrate how sensitivity analysis may be used with NDLI to develop reliability-based designs of TPS components.

Response Time Analysis and Test of Protection System Instrument Channels for APR1400 and OPR1000

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

Lee, Chang Jae; Han, Seung; Yun, Jae Hee

2015-07-01

Safety limits are required to maintain the integrity of physical barriers designed to prevent the uncontrolled release of radioactive materials in nuclear power plants. The safety analysis establishes two critical constraints that include an analytical limit in terms of a measured or calculated variable, and a specific time after the analytical limit is reached to begin protective action. Keeping with the nuclear regulations and industry standards, satisfying these two requirements will ensure that the safety limit will not be exceeded during the design basis event, either an anticipated operational occurrence or a postulated accident. Various studies on the setpoint determinationmore » methodology for the safety-related instrumentation have been actively performed to ensure that the requirement of the analytical limit is satisfied. In particular, the protection setpoint methodology for the advanced power reactor 1400 (APP1400) and the optimized power reactor 1000 (OPR1000) has been recently developed to cover both the design basis event and the beyond design basis event. The developed setpoint methodology has also been quantitatively validated using specific computer programs and setpoint calculations. However, the safety of nuclear power plants cannot be fully guaranteed by satisfying the requirement of the analytical limit. In spite of the response time verification requirements of nuclear regulations and industry standards, it is hard to find the studies on the systematically integrated methodology regarding the response time evaluation. In cases of APR1400 and OPR1000, the response time analysis for the plant protection system is partially included in the setpoint calculation and the response time test is separately performed via the specific plant procedure. The test technique has a drawback which is the difficulty to demonstrate completeness of timing test. The analysis technique has also a demerit of resulting in extreme times that not actually possible. Thus, the establishment of the systematic response time evaluation methodology is needed to justify the conformance to the response time requirement used in the safety analysis. This paper proposes the response time evaluation methodology for APR1400 and OPR1000 using the combined analysis and test technique to confirm that the plant protection system can meet the analytical response time assumed in the safety analysis. In addition, the results of the quantitative evaluation performed for APR1400 and OPR1000 are presented in this paper. The proposed response time analysis technique consists of defining the response time requirement, determining the critical signal path for the trip parameter, allocating individual response time to each component on the signal path, and analyzing the total response time for the trip parameter, and demonstrates that the total analyzed response time does not exceed the response time requirement. The proposed response time test technique is composed of defining the response time requirement, determining the critical signal path for the trip parameter, determining the test method for each component on the signal path, performing the response time test, and demonstrates that the total test result does not exceed the response time requirement. The total response time should be tested in a single test that covers from the sensor to the final actuation device on the instrument channel. When the total channel is not tested in a single test, separate tests on groups of components or single components including the total instrument channel shall be combined to verify the total channel response. For APR1400 and OPR1000, the ramp test technique is used for the pressure and differential pressure transmitters and the step function testing technique is applied to the signal processing equipment and final actuation device. As a result, it can be demonstrated that the response time requirement is satisfied by the combined analysis and test technique. Therefore, the proposed methodology in this paper plays a crucial role in guaranteeing the safety of the nuclear power plants systematically satisfying one of two critical requirements from the safety analysis. (authors)« less

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

PubMed

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

Coupled electromechanical response of composite beams with embedded piezoelectric sensors and actuators

NASA Technical Reports Server (NTRS)

Saravanos, D. A.; Heyliger, P. R.

1994-01-01

Unified mechanics are developed with the capability to model both sensory and active composite laminates with embedded piezoelectric layers. A discrete-layer formulation enables analysis of both global and local electromechanical response. The mechanics include the contributions from elastic, piezoelectric, and dielectric components. The incorporation of electric potential into the state variables permits representation of general electromechanical boundary conditions. Approximate finite element solutions for the static and free-vibration analysis of beams are presented. Applications on composite beams demonstrate the capability to represent either sensory or active structures and to model the complicated stress-strain fields, the interactions between passive/active layers, interfacial phenomena between sensors and composite plies, and critical damage modes in the material. The capability to predict the dynamic characteristics under various electrical boundary conditions is also demonstrated.

Probabilistic Structures Analysis Methods (PSAM) for select space propulsion system components

NASA Technical Reports Server (NTRS)

1991-01-01

The basic formulation for probabilistic finite element analysis is described and demonstrated on a few sample problems. This formulation is based on iterative perturbation that uses the factorized stiffness on the unperturbed system as the iteration preconditioner for obtaining the solution to the perturbed problem. This approach eliminates the need to compute, store and manipulate explicit partial derivatives of the element matrices and force vector, which not only reduces memory usage considerably, but also greatly simplifies the coding and validation tasks. All aspects for the proposed formulation were combined in a demonstration problem using a simplified model of a curved turbine blade discretized with 48 shell elements, and having random pressure and temperature fields with partial correlation, random uniform thickness, and random stiffness at the root.

Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes

PubMed Central

Liang, Qiaokang; Zhang, Dan; Coppola, Gianmarc; Mao, Jianxu; Sun, Wei; Wang, Yaonan; Ge, Yunjian

2016-01-01

Multi-component force sensors have infiltrated a wide variety of automation products since the 1970s. However, one seldom finds full-component sensor systems available in the market for cutting force measurement in machine processes. In this paper, a new six-component sensor system with a compact monolithic elastic element (EE) is designed and developed to detect the tangential cutting forces Fx, Fy and Fz (i.e., forces along x-, y-, and z-axis) as well as the cutting moments Mx, My and Mz (i.e., moments about x-, y-, and z-axis) simultaneously. Optimal structural parameters of the EE are carefully designed via simulation-driven optimization. Moreover, a prototype sensor system is fabricated, which is applied to a 5-axis parallel kinematic machining center. Calibration experimental results demonstrate that the system is capable of measuring cutting forces and moments with good linearity while minimizing coupling error. Both the Finite Element Analysis (FEA) and calibration experimental studies validate the high performance of the proposed sensor system that is expected to be adopted into machining processes. PMID:26751451

Interpretable functional principal component analysis.

PubMed

Lin, Zhenhua; Wang, Liangliang; Cao, Jiguo

2016-09-01

Functional principal component analysis (FPCA) is a popular approach to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). The intervals where the values of FPCs are significant are interpreted as where sample curves have major variations. However, these intervals are often hard for naïve users to identify, because of the vague definition of "significant values". In this article, we develop a novel penalty-based method to derive FPCs that are only nonzero precisely in the intervals where the values of FPCs are significant, whence the derived FPCs possess better interpretability than the FPCs derived from existing methods. To compute the proposed FPCs, we devise an efficient algorithm based on projection deflation techniques. We show that the proposed interpretable FPCs are strongly consistent and asymptotically normal under mild conditions. Simulation studies confirm that with a competitive performance in explaining variations of sample curves, the proposed FPCs are more interpretable than the traditional counterparts. This advantage is demonstrated by analyzing two real datasets, namely, electroencephalography data and Canadian weather data. © 2015, The International Biometric Society.

Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis

NASA Astrophysics Data System (ADS)

Li, D.; Xu, L.; Peng, J.; Ma, J.

2018-04-01

Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.

Speckle noise reduction technique for Lidar echo signal based on self-adaptive pulse-matching independent component analysis

NASA Astrophysics Data System (ADS)

Xu, Fan; Wang, Jiaxing; Zhu, Daiyin; Tu, Qi

2018-04-01

Speckle noise has always been a particularly tricky problem in improving the ranging capability and accuracy of Lidar system especially in harsh environment. Currently, effective speckle de-noising techniques are extremely scarce and should be further developed. In this study, a speckle noise reduction technique has been proposed based on independent component analysis (ICA). Since normally few changes happen in the shape of laser pulse itself, the authors employed the laser source as a reference pulse and executed the ICA decomposition to find the optimal matching position. In order to achieve the self-adaptability of algorithm, local Mean Square Error (MSE) has been defined as an appropriate criterion for investigating the iteration results. The obtained experimental results demonstrated that the self-adaptive pulse-matching ICA (PM-ICA) method could effectively decrease the speckle noise and recover the useful Lidar echo signal component with high quality. Especially, the proposed method achieves 4 dB more improvement of signal-to-noise ratio (SNR) than a traditional homomorphic wavelet method.

Finger crease pattern recognition using Legendre moments and principal component analysis

NASA Astrophysics Data System (ADS)

Luo, Rongfang; Lin, Tusheng

2007-03-01

The finger joint lines defined as finger creases and its distribution can identify a person. In this paper, we propose a new finger crease pattern recognition method based on Legendre moments and principal component analysis (PCA). After obtaining the region of interest (ROI) for each finger image in the pre-processing stage, Legendre moments under Radon transform are applied to construct a moment feature matrix from the ROI, which greatly decreases the dimensionality of ROI and can represent principal components of the finger creases quite well. Then, an approach to finger crease pattern recognition is designed based on Karhunen-Loeve (K-L) transform. The method applies PCA to a moment feature matrix rather than the original image matrix to achieve the feature vector. The proposed method has been tested on a database of 824 images from 103 individuals using the nearest neighbor classifier. The accuracy up to 98.584% has been obtained when using 4 samples per class for training. The experimental results demonstrate that our proposed approach is feasible and effective in biometrics.

The effect of pomegranate seed oil and grapeseed oil on cis-9, trans-11 CLA (rumenic acid), n-3 and n-6 fatty acids deposition in selected tissues of chickens.

PubMed

Białek, A; Białek, M; Lepionka, T; Kaszperuk, K; Banaszkiewicz, T; Tokarz, A

2018-04-23

The aim of this study was to determine whether diet modification with different doses of grapeseed oil or pomegranate seed oil will improve the nutritive value of poultry meat in terms of n-3 and n-6 fatty acids, as well as rumenic acid (cis-9, trans-11 conjugated linoleic acid) content in tissues diversified in lipid composition and roles in lipid metabolism. To evaluate the influence of applied diet modification comprehensively, two chemometric methods were used. Results of cluster analysis demonstrated that pomegranate seed oil modifies fatty acids profile in the most potent way, mainly by an increase in rumenic acid content. Principal component analysis showed that regardless of type of tissue first principal component is strongly associated with type of deposited fatty acid, while second principal component enables identification of place of deposition-type of tissue. Pomegranate seed oil seems to be a valuable feed additive in chickens' feeding. © 2018 Blackwell Verlag GmbH.

Design and Analysis of a Sensor System for Cutting Force Measurement in Machining Processes.

PubMed

Liang, Qiaokang; Zhang, Dan; Coppola, Gianmarc; Mao, Jianxu; Sun, Wei; Wang, Yaonan; Ge, Yunjian

2016-01-07

Multi-component force sensors have infiltrated a wide variety of automation products since the 1970s. However, one seldom finds full-component sensor systems available in the market for cutting force measurement in machine processes. In this paper, a new six-component sensor system with a compact monolithic elastic element (EE) is designed and developed to detect the tangential cutting forces Fx, Fy and Fz (i.e., forces along x-, y-, and z-axis) as well as the cutting moments Mx, My and Mz (i.e., moments about x-, y-, and z-axis) simultaneously. Optimal structural parameters of the EE are carefully designed via simulation-driven optimization. Moreover, a prototype sensor system is fabricated, which is applied to a 5-axis parallel kinematic machining center. Calibration experimental results demonstrate that the system is capable of measuring cutting forces and moments with good linearity while minimizing coupling error. Both the Finite Element Analysis (FEA) and calibration experimental studies validate the high performance of the proposed sensor system that is expected to be adopted into machining processes.

Hemiclonal analysis reveals significant genetic, environmental and genotype x environment effects on sperm size in Drosophila melanogaster.

PubMed

Morrow, E H; Leijon, A; Meerupati, A

2008-11-01

Spermatozoa are the most diverse of all animal cells. Variation in size alone is enormous and yet there are still no clear evolutionary explanations that can account for such diversity. The basic genetics of sperm form is also poorly understood, although sperm size is known to have a strong genetic component. Here, using hemiclonal analysis of Drosophila melanogaster, we demonstrate that there is not only a significant additive genetic component contributing to phenotypic variation in sperm length but also a significant environmental effect. Furthermore, the plasticity of sperm size has a significant genetic component to it (a genotype x environment interaction). A genotype x environment interaction could contribute to the maintenance of the substantial genetic variation in this trait and thereby explain the persistent inter-male differences in sperm size seen in numerous taxa. We suggest that the low conditional dependence and high heritability but low evolvability (the coefficient of additive genetic variation) of sperm length is more consistent with a history of stabilizing selection rather than either sexual selection or strong directional selection.

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.

Conductive polymer sensor arrays for smart orthopaedic implants

NASA Astrophysics Data System (ADS)

Micolini, Carolina; Holness, F. B.; Johnson, James A.; Price, Aaron D.

2017-04-01

This study proposes and demonstrates the design, implementation, and characterization of a 3D-printed smartpolymer sensor array using conductive polyaniline (PANI) structures embedded in a polymeric substrate. The piezoresistive characteristics of PANI were studied to evaluate the efficacy of the manufacturing of an embedded pressure sensor. PANI's stability throughout loading and unloading cycles together with the response to incremental loading cycles was investigated. It is demonstrated that this specially developed multi-material additive manufacturing process for polyaniline is a good candidate for the manufacture of implant components with smart-polymer sensors embedded for the analysis of joint loads in orthopaedic implants.

Quantifying the economic importance of irrigation water reuse in a Chilean watershed using an integrated agent-based model

NASA Astrophysics Data System (ADS)

Arnold, R. T.; Troost, Christian; Berger, Thomas

2015-01-01

Irrigation with surface water enables Chilean agricultural producers to generate one of the country's most important economic exports. The Chilean water code established tradable water rights as a mechanism to allocate water amongst farmers and other water-use sectors. It remains contested whether this mechanism is effective and many authors have raised equity concerns regarding its impact on water users. For example, speculative hoarding of water rights in expectations of their increasing value has been described. This paper demonstrates how farmers can hoard water rights as a risk management strategy for variable water supply, for example, due to the cycles of El Niño or as consequence of climate change. While farmers with insufficient water rights can rely on unclaimed water during conditions of normal water availability, drought years overproportionally impact on their supply of irrigation water and thereby farm profitability. This study uses a simulation model that consists of a hydrological balance model component and a multiagent farm decision and production component. Both model components are parameterized with empirical data, while uncertain parameters are calibrated. The study demonstrates a thorough quantification of parameter uncertainty, using global sensitivity analysis and multiple behavioral parameter scenarios.

Systems-wide analysis of BCR signalosomes and downstream phosphorylation and ubiquitylation

PubMed Central

Satpathy, Shankha; Wagner, Sebastian A; Beli, Petra; Gupta, Rajat; Kristiansen, Trine A; Malinova, Dessislava; Francavilla, Chiara; Tolar, Pavel; Bishop, Gail A; Hostager, Bruce S; Choudhary, Chunaram

2015-01-01

B-cell receptor (BCR) signaling is essential for the development and function of B cells; however, the spectrum of proteins involved in BCR signaling is not fully known. Here we used quantitative mass spectrometry-based proteomics to monitor the dynamics of BCR signaling complexes (signalosomes) and to investigate the dynamics of downstream phosphorylation and ubiquitylation signaling. We identify most of the previously known components of BCR signaling, as well as many proteins that have not yet been implicated in this system. BCR activation leads to rapid tyrosine phosphorylation and ubiquitylation of the receptor-proximal signaling components, many of which are co-regulated by both the modifications. We illustrate the power of multilayered proteomic analyses for discovering novel BCR signaling components by demonstrating that BCR-induced phosphorylation of RAB7A at S72 prevents its association with effector proteins and with endo-lysosomal compartments. In addition, we show that BCL10 is modified by LUBAC-mediated linear ubiquitylation, and demonstrate an important function of LUBAC in BCR-induced NF-κB signaling. Our results offer a global and integrated view of BCR signaling, and the provided datasets can serve as a valuable resource for further understanding BCR signaling networks. PMID:26038114

Systems biology approaches to understand the effects of nutrition and promote health.

PubMed

Badimon, Lina; Vilahur, Gemma; Padro, Teresa

2017-01-01

Within the last years the implementation of systems biology in nutritional research has emerged as a powerful tool to understand the mechanisms by which dietary components promote health and prevent disease as well as to identify the biologically active molecules involved in such effects. Systems biology, by combining several '-omics' disciplines (mainly genomics/transcriptomics, proteomics and metabolomics), creates large data sets that upon computational integration provide in silico predictive networks that allow a more extensive analysis of the individual response to a nutritional intervention and provide a more global comprehensive understanding of how diet may influence health and disease. Numerous studies have demonstrated that diet and particularly bioactive food components play a pivotal role in helping to counteract environmental-related oxidative damage. Oxidative stress is considered to be strongly implicated in ageing and the pathophysiology of numerous diseases including neurodegenerative disease, cancers, metabolic disorders and cardiovascular diseases. In the following review we will provide insights into the role of systems biology in nutritional research and focus on transcriptomic, proteomic and metabolomics studies that have demonstrated the ability of functional foods and their bioactive components to fight against oxidative damage and contribute to health benefits. © 2016 The British Pharmacological Society.

``Low-cost Electronic nose evaluated on Thai-herb of Northern-Thailand samples using multivariate analysis methods''

NASA Astrophysics Data System (ADS)

na ayudhaya, Paisarn Daungjak; Klinbumrung, Arrak; Jaroensutasinee, Krisanadej; Pratontep, Sirapat; Kerdcharoen, Teerakiat

2009-05-01

In case of species of natural and aromatic plant originated from the northern Thailand, sensory characteristics, especially odours, have unique identifiers of herbs. The instruments sensory analysis have performed by several of differential of sensing, so call `electronic nose', to be a significantly and rapidly for chemometrics. The signal responses of the low cost electronic nose were evaluated by principal component analysis (PCA). The aims of this paper evaluated various of Thai-herbs grown in Northern of Thailand as data preprocessing tools of the Low-cost electronic nose (enNU-PYO1). The essential oil groups of Thai herbs such as Garlic, Lemongrass, Shallot (potato onion), Onion, Zanthoxylum limonella (Dennst.) Alston (Thai name is Makaen), and Kaffir lime leaf were compared volatilized from selected fresh herbs. Principal component analysis of the original sensor responses did clearly distinguish either all samples. In all cases more than 97% for cross-validated group were classified correctly. The results demonstrated that it was possible to develop in a model to construct a low-cost electronic nose to provide measurement of odoriferous herbs.

The Contributions of Primary and Secondary Memory to Working Memory Capacity: An Individual Differences Analysis of Immediate Free Recall

ERIC Educational Resources Information Center

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

2010-01-01

The present study tested the dual-component model of working memory capacity (WMC) by examining estimates of primary memory and secondary memory from an immediate free recall task. Participants completed multiple measures of WMC and general intellectual ability as well as multiple trials of an immediate free recall task. It was demonstrated that…

Forest growth of Mississippi's north unit - A case study of the Southern Forest surveys growth estimation procedures

Treesearch

Dennis M. May

1988-01-01

This report presents the procedures by which the Southern Forest Inventory and Analysis unit estimates forest growth from permanent horizontal point samples. Inventory data from the 1977-87 survey of Mississippi's north unit were used to demonstrate how trees on the horizontal point samples are classified into one of eight components of growth and, in turn, how...

Improved analysis and visualization of friction loop data: unraveling the energy dissipation of meso-scale stick-slip motion

NASA Astrophysics Data System (ADS)

Kokorian, Jaap; Merlijn van Spengen, W.

2017-11-01

In this paper we demonstrate a new method for analyzing and visualizing friction force measurements of meso-scale stick-slip motion, and introduce a method for extracting two separate dissipative energy components. Using a microelectromechanical system tribometer, we execute 2 million reciprocating sliding cycles, during which we measure the static friction force with a resolution of \

Design and demonstrate the performance of cryogenic components representative of space vehicles: Start basket liquid acquisition device performance analysis

NASA Technical Reports Server (NTRS)

1987-01-01

The objective was to design, fabricate and test an integrated cryogenic test article incorporating both fluid and thermal propellant management subsystems. A 2.2 m (87 in) diameter aluminum test tank was outfitted with multilayer insulation, helium purge system, low-conductive tank supports, thermodynamic vent system, liquid acquisition device and immersed outflow pump. Tests and analysis performed on the start basket liquid acquisition device and studies of the liquid retention characteristics of fine mesh screens are discussed.

Kernel PLS-SVC for Linear and Nonlinear Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Matthews, Bryan

2003-01-01

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.

DOSY Analysis of Micromolar Analytes: Resolving Dilute Mixtures by SABRE Hyperpolarization.

PubMed

Reile, Indrek; Aspers, Ruud L E G; Tyburn, Jean-Max; Kempf, James G; Feiters, Martin C; Rutjes, Floris P J T; Tessari, Marco

2017-07-24

DOSY is an NMR spectroscopy technique that resolves resonances according to the analytes' diffusion coefficients. It has found use in correlating NMR signals and estimating the number of components in mixtures. Applications of DOSY in dilute mixtures are, however, held back by excessively long measurement times. We demonstrate herein, how the enhanced NMR sensitivity provided by SABRE hyperpolarization allows DOSY analysis of low-micromolar mixtures, thus reducing the concentration requirements by at least 100-fold. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Asano, Keiji G; Ford, Michael J; Tomkins, Bruce A

A self-aspirating heated nebulizer probe is described and demonstrated for use in the direct analysis of analytes on surfaces and in liquid samples by atmospheric pressure chemical ionization (APCI) mass spectrometry. Functionality and performance of the probe as a self-aspirating APCI source is demonstrated using reserpine and progesterone as test compounds. The utility of the probe to sample analytes directly from surfaces was demonstrated first by scanning development lanes of a reversed-phase thin-layer chromatography plate in which a three-component dye mixture, viz., Fat Red 7B, Solvent Green 3, and Solvent Blue 35, was spotted and the components were separated. Developmentmore » lanes were scanned by the sampling probe operated under computer control (x, y plane) while full-scan mass spectra were recorded using a quadrupole ion trap mass spectrometer. In addition, the ability to sample the surface of pharmaceutical tablets (viz., Extra Strength Tylenol(reg. sign) and Evista(reg. sign) tablets) and to detect the active ingredients (acetaminophen and raloxifene, respectively) selectively was demonstrated using tandem mass spectrometry (MS/MS). Finally, the capability to sample analyte solutions from the wells of a 384-well microtiter plate and to perform quantitative analyses using MS/MS detection was illustrated with cotinine standards spiked with cotinine-d{sub 3} as an internal standard.« less

Quantitative and qualitative analysis of naphthenic acids in natural waters surrounding the Canadian oil sands industry.

PubMed

Ross, Matthew S; Pereira, Alberto dos Santos; Fennell, Jon; Davies, Martin; Johnson, James; Sliva, Lucie; Martin, Jonathan W

2012-12-04

The Canadian oil sands industry stores toxic oil sands process-affected water (OSPW) in large tailings ponds adjacent to the Athabasca River or its tributaries, raising concerns over potential seepage. Naphthenic acids (NAs; C(n)H(2n-Z)O(2)) are toxic components of OSPW, but are also natural components of bitumen and regional groundwaters, and may enter surface waters through anthropogenic or natural sources. This study used a selective high-resolution mass spectrometry method to examine total NA concentrations and NA profiles in OSPW (n = 2), Athabasca River pore water (n = 6, representing groundwater contributions) and surface waters (n = 58) from the Lower Athabasca Region. NA concentrations in surface water (< 2-80.8 μg/L) were 100-fold lower than previously estimated. Principal components analysis (PCA) distinguished sample types based on NA profile, and correlations to water quality variables identified two sources of NAs: natural fatty acids, and bitumen-derived NAs. Analysis of NA data with water quality variables highlighted two tributaries to the Athabasca River-Beaver River and McLean Creek-as possibly receiving OSPW seepage. This study is the first comprehensive analysis of NA profiles in surface waters of the region, and demonstrates the need for highly selective analytical methods for source identification and in monitoring for potential effects of development on ambient water quality.

Finite Element Model Calibration Approach for Area I-X

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.; Buehrle, Ralph D.; Templeton, Justin D.; Gaspar, James L.; Lazor, Daniel R.; Parks, Russell A.; Bartolotta, Paul A.

2010-01-01

Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of non-conventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pretest predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.

Finite Element Model Calibration Approach for Ares I-X

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.; Buehrle, Ralph D.; Templeton, Justin D.; Lazor, Daniel R.; Gaspar, James L.; Parks, Russel A.; Bartolotta, Paul A.

2010-01-01

Ares I-X is a pathfinder vehicle concept under development by NASA to demonstrate a new class of launch vehicles. Although this vehicle is essentially a shell of what the Ares I vehicle will be, efforts are underway to model and calibrate the analytical models before its maiden flight. Work reported in this document will summarize the model calibration approach used including uncertainty quantification of vehicle responses and the use of nonconventional boundary conditions during component testing. Since finite element modeling is the primary modeling tool, the calibration process uses these models, often developed by different groups, to assess model deficiencies and to update parameters to reconcile test with predictions. Data for two major component tests and the flight vehicle are presented along with the calibration results. For calibration, sensitivity analysis is conducted using Analysis of Variance (ANOVA). To reduce the computational burden associated with ANOVA calculations, response surface models are used in lieu of computationally intensive finite element solutions. From the sensitivity studies, parameter importance is assessed as a function of frequency. In addition, the work presents an approach to evaluate the probability that a parameter set exists to reconcile test with analysis. Comparisons of pre-test predictions of frequency response uncertainty bounds with measured data, results from the variance-based sensitivity analysis, and results from component test models with calibrated boundary stiffness models are all presented.

Wind Variability in Intermediate Luminosity B Supergiants

NASA Technical Reports Server (NTRS)

Massa, Derck

1996-01-01

This study used the unique spectroscopic diagnostics of intermediate luminosity B supergiants to determine the ubiquity and nature of wind variability. Specifically, (1) A detailed analysis of HD 64760 demonstrated massive ejections into its wind, provided the first clear demonstration of a 'photospheric connection' and ionization shifts in a stellar wind; (2) The international 'IUE MEGA campaign' obtained unprecedented temporal coverage of wind variability in rapidly rotating stars and demonstrated regularly repeating wind features originating in the photosphere; (3) A detailed analysis of wind variability in the rapidly rotating B1 Ib, gamma Ara demonstrated a two component wind with distinctly different mean states at different epochs; (4) A follow-on campaign to the MEGA project to study slowly rotating stars was organized and deemed a key project by ESA/NASA, and will obtain 30 days of IUE observations in May-June 1996; and (5) A global survey of archival IUE time series identified recurring spectroscopic signatures, identified with different physical phenomena. Items 4 and 5 above are still in progress and will be completed this summer in collaboration with Raman Prinja at University College, London.

Analysis of dewar and transfer line cooldown in Superfluid Helium On-Orbit Transfer Flight Experiment (SHOOT)

NASA Technical Reports Server (NTRS)

Ng, Y. S.; Lee, J. H.

1989-01-01

The Superfluid Helium On-Orbit Transfer Flight Experiment (SHOOT) is designed to demonstrate the techniques and components required for orbital superfluid (He II) replenishment of observatories and satellites. One of the tasks planned in the experiment is to cool a warm cryogen tank and a warm transfer line to liquid helium temperature. A math model, based on single-phase vapor flow heat transfer, has been developed to predict the cooldown time, component temperature histories, and helium consumption rate, for various initial conditions of the components and for the thermomechanical pump heater powers of 2 W and 0.5 W. This paper discusses the model and the analytical results, which can be used for planning the experiment operations and determining the pump heater power required for the cooldown operation.

Structured functional additive regression in reproducing kernel Hilbert spaces

PubMed Central

Zhu, Hongxiao; Yao, Fang; Zhang, Hao Helen

2013-01-01

Summary Functional additive models (FAMs) provide a flexible yet simple framework for regressions involving functional predictors. The utilization of data-driven basis in an additive rather than linear structure naturally extends the classical functional linear model. However, the critical issue of selecting nonlinear additive components has been less studied. In this work, we propose a new regularization framework for the structure estimation in the context of Reproducing Kernel Hilbert Spaces. The proposed approach takes advantage of the functional principal components which greatly facilitates the implementation and the theoretical analysis. The selection and estimation are achieved by penalized least squares using a penalty which encourages the sparse structure of the additive components. Theoretical properties such as the rate of convergence are investigated. The empirical performance is demonstrated through simulation studies and a real data application. PMID:25013362

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Description of data on the Nimbus 7 LIMS map archive tape: Water vapor and nitrogen dioxide

NASA Technical Reports Server (NTRS)

Haggard, Kenneth V.; Marshall, B. T.; Kurzeja, Robert J.; Remsberg, Ellis E.; Russell, James M., III

1988-01-01

Described is the process by which the analysis of the Limb Infrared Monitor of the Stratosphere (LIMS) experiment data were used to produce estimates of synoptic maps of water vapor and nitrogen dioxide. In addition to a detailed description of the analysis procedure, also discussed are several interesting features in the data which are used to demonstrate how the analysis procedure produced the final maps and how one can estimate the uncertainties in the maps. In addition, features in the analysis are noted that would influence how one might use, or interpret, the results. These include subjects such as smoothing and the interpretation of wave components.

Wavelet-Bayesian inference of cosmic strings embedded in the cosmic microwave background

NASA Astrophysics Data System (ADS)

McEwen, J. D.; Feeney, S. M.; Peiris, H. V.; Wiaux, Y.; Ringeval, C.; Bouchet, F. R.

2017-12-01

Cosmic strings are a well-motivated extension to the standard cosmological model and could induce a subdominant component in the anisotropies of the cosmic microwave background (CMB), in addition to the standard inflationary component. The detection of strings, while observationally challenging, would provide a direct probe of physics at very high-energy scales. We develop a framework for cosmic string inference from observations of the CMB made over the celestial sphere, performing a Bayesian analysis in wavelet space where the string-induced CMB component has distinct statistical properties to the standard inflationary component. Our wavelet-Bayesian framework provides a principled approach to compute the posterior distribution of the string tension Gμ and the Bayesian evidence ratio comparing the string model to the standard inflationary model. Furthermore, we present a technique to recover an estimate of any string-induced CMB map embedded in observational data. Using Planck-like simulations, we demonstrate the application of our framework and evaluate its performance. The method is sensitive to Gμ ∼ 5 × 10-7 for Nambu-Goto string simulations that include an integrated Sachs-Wolfe contribution only and do not include any recombination effects, before any parameters of the analysis are optimized. The sensitivity of the method compares favourably with other techniques applied to the same simulations.

Uncovering the Mechanisms of Chinese Herbal Medicine (MaZiRenWan) for Functional Constipation by Focused Network Pharmacology Approach.

PubMed

Huang, Tao; Ning, Ziwan; Hu, Dongdong; Zhang, Man; Zhao, Ling; Lin, Chengyuan; Zhong, Linda L D; Yang, Zhijun; Xu, Hongxi; Bian, Zhaoxiang

2018-01-01

MaZiRenWan (MZRW, also known as Hemp Seed Pill) is a Chinese Herbal Medicine which has been demonstrated to safely and effectively alleviate functional constipation (FC) in a randomized, placebo-controlled clinical study with 120 subjects. However, the underlying pharmacological actions of MZRW for FC, are still largely unknown. We systematically analyzed the bioactive compounds of MZRW and mechanism-of-action biological targets through a novel approach called "focused network pharmacology." Among the 97 compounds identified by UPLC-QTOF-MS/MS in MZRW extract, 34 were found in rat plasma, while 10 were found in rat feces. Hierarchical clustering analysis suggest that these compounds can be classified into component groups, in which compounds are highly similar to each other and most of them are from the same herb. Emodin, amygdalin, albiflorin, honokiol, and naringin were selected as representative compounds of corresponding component groups. All of them were shown to induce spontaneous contractions of rat colonic smooth muscle in vitro . Network analysis revealed that biological targets in acetylcholine-, estrogen-, prostaglandin-, cannabinoid-, and purine signaling pathways are able to explain the prokinetic effects of representative compounds and corresponding component groups. In conclusion, MZRW active components enhance colonic motility, possibly by acting on multiple targets and pathways.

Uncovering the Mechanisms of Chinese Herbal Medicine (MaZiRenWan) for Functional Constipation by Focused Network Pharmacology Approach

PubMed Central

Huang, Tao; Ning, Ziwan; Hu, Dongdong; Zhang, Man; Zhao, Ling; Lin, Chengyuan; Zhong, Linda L. D.; Yang, Zhijun; Xu, Hongxi; Bian, Zhaoxiang

2018-01-01

MaZiRenWan (MZRW, also known as Hemp Seed Pill) is a Chinese Herbal Medicine which has been demonstrated to safely and effectively alleviate functional constipation (FC) in a randomized, placebo-controlled clinical study with 120 subjects. However, the underlying pharmacological actions of MZRW for FC, are still largely unknown. We systematically analyzed the bioactive compounds of MZRW and mechanism-of-action biological targets through a novel approach called “focused network pharmacology.” Among the 97 compounds identified by UPLC-QTOF-MS/MS in MZRW extract, 34 were found in rat plasma, while 10 were found in rat feces. Hierarchical clustering analysis suggest that these compounds can be classified into component groups, in which compounds are highly similar to each other and most of them are from the same herb. Emodin, amygdalin, albiflorin, honokiol, and naringin were selected as representative compounds of corresponding component groups. All of them were shown to induce spontaneous contractions of rat colonic smooth muscle in vitro. Network analysis revealed that biological targets in acetylcholine-, estrogen-, prostaglandin-, cannabinoid-, and purine signaling pathways are able to explain the prokinetic effects of representative compounds and corresponding component groups. In conclusion, MZRW active components enhance colonic motility, possibly by acting on multiple targets and pathways. PMID:29632490

Comparison of cemented and uncemented fixation in total knee arthroplasty.

PubMed

Brown, Thomas E; Harper, Benjamin L; Bjorgul, Kristian

2013-05-01

As a result of reading this article, physicians should be able to :1. Understand the rationale behind using uncemented fixation in total knee arthroplasty.2.Discuss the current literature comparing cemented and uncemented total knee arthroplasty3. Describe the value of radiostereographic analysis in assessing implant stability.4. Appreciate the limitations in the available literature advocating 1 mode of fixation in total knee arthroplasty. Total knee arthroplasty performed worldwide uses either cemented, cementless, or hybrid (cementless femur with a cemented tibia) fixation of the components. No recent literature review concerning the outcomes of cemented vs noncemented components has been performed. Noncemented components offer the potential advantage of a biologic interface between the bone and implants, which could demonstrate the greatest advantage in long-term durable fixation in the follow-up of young patients undergoing arthroplasty. Several advances have been made in the backing of the tibial components that have not been available long enough to yield long-term comparative follow-up studies. Short-term radiostereographic analysis studies have yielded differing results. Although long-term, high-quality studies are still needed, material advances in biologic fixation surfaces, such as trabecular metal and hydroxyapatite, may offer promising results for young and active patients undergoing total knee arthroplasty when compared with traditional cemented options. Copyright 2013, SLACK Incorporated.

Assessing trihalomethanes (THMs) and N-nitrosodimethylamine (NDMA) formation potentials in drinking water treatment plants using fluorescence spectroscopy and parallel factor analysis.

PubMed

Yang, Liyang; Kim, Daekyun; Uzun, Habibullah; Karanfil, Tanju; Hur, Jin

2015-02-01

The formation of disinfection byproducts (DBPs) is a major challenge in drinking water treatments. This study explored the applicability of fluorescence excitation-emission matrices and parallel factor analysis (EEM-PARAFAC) for assessing the formation potentials (FPs) of trihalomethanes (THMs) and N-nitrosodimethylamine (NDMA), and the treatability of THM and NDMA precursors in nine drinking water treatment plants. Two humic-like and one tryptophan-like components were identified for the samples using PARAFAC. The total THM FP (TTHM FP) correlated strongly with humic-like component C2 (r=0.874), while NDMA FP showed a moderate and significant correlation with the tryptophan-like component C3 (r=0.628). The reduction by conventional treatment was more effective for C2 than C3, and for TTHM FP than NDMA FP. The treatability of DOM and TTHM FP correlated negatively with the absorption spectral slope (S275-295) and biological index (BIX) of the raw water, but it correlated positively with humification index (HIX). Our results demonstrated that PARAFAC components were valuable for assessing DBPs FP in drinking water treatments, and also that the raw water quality could affect the treatment efficiency. Copyright © 2014 Elsevier Ltd. All rights reserved.

UMAMI: A Recipe for Generating Meaningful Metrics through Holistic I/O Performance Analysis

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

Lockwood, Glenn K.; Yoo, Wucherl; Byna, Suren

I/O efficiency is essential to productivity in scientific computing, especially as many scientific domains become more data-intensive. Many characterization tools have been used to elucidate specific aspects of parallel I/O performance, but analyzing components of complex I/O subsystems in isolation fails to provide insight into critical questions: how do the I/O components interact, what are reasonable expectations for application performance, and what are the underlying causes of I/O performance problems? To address these questions while capitalizing on existing component-level characterization tools, we propose an approach that combines on-demand, modular synthesis of I/O characterization data into a unified monitoring and metricsmore » interface (UMAMI) to provide a normalized, holistic view of I/O behavior. We evaluate the feasibility of this approach by applying it to a month-long benchmarking study on two distinct largescale computing platforms. We present three case studies that highlight the importance of analyzing application I/O performance in context with both contemporaneous and historical component metrics, and we provide new insights into the factors affecting I/O performance. By demonstrating the generality of our approach, we lay the groundwork for a production-grade framework for holistic I/O analysis.« less

Pain sensitivity profiles in patients with advanced knee osteoarthritis

PubMed Central

Frey-Law, Laura A.; Bohr, Nicole L.; Sluka, Kathleen A.; Herr, Keela; Clark, Charles R.; Noiseux, Nicolas O.; Callaghan, John J; Zimmerman, M Bridget; Rakel, Barbara A.

2016-01-01

The development of patient profiles to subgroup individuals on a variety of variables has gained attention as a potential means to better inform clinical decision-making. Patterns of pain sensitivity response specific to quantitative sensory testing (QST) modality have been demonstrated in healthy subjects. It has not been determined if these patterns persist in a knee osteoarthritis population. In a sample of 218 participants, 19 QST measures along with pain, psychological factors, self-reported function, and quality of life were assessed prior to total knee arthroplasty. Component analysis was used to identify commonalities across the 19 QST assessments to produce standardized pain sensitivity factors. Cluster analysis then grouped individuals that exhibited similar patterns of standardized pain sensitivity component scores. The QST resulted in four pain sensitivity components: heat, punctate, temporal summation, and pressure. Cluster analysis resulted in five pain sensitivity profiles: a “low pressure pain” group, an “average pain” group, and three “high pain” sensitivity groups who were sensitive to different modalities (punctate, heat, and temporal summation). Pain and function differed between pain sensitivity profiles, along with sex distribution; however no differences in OA grade, medication use, or psychological traits were found. Residualizing QST data by age and sex resulted in similar components and pain sensitivity profiles. Further, these profiles are surprisingly similar to those reported in healthy populations suggesting that individual differences in pain sensitivity are a robust finding even in an older population with significant disease. PMID:27152688

Intrinsic Connectivity Provides the Baseline Framework for Variability in Motor Performance: A Multivariate Fusion Analysis of Low- and High-Frequency Resting-State Oscillations and Antisaccade Performance.

PubMed

Jamadar, Sharna D; Egan, Gary F; Calhoun, Vince D; Johnson, Beth; Fielding, Joanne

2016-07-01

Intrinsic brain activity provides the functional framework for the brain's full repertoire of behavioral responses; that is, a common mechanism underlies intrinsic and extrinsic neural activity, with extrinsic activity building upon the underlying baseline intrinsic activity. The generation of a motor movement in response to sensory stimulation is one of the most fundamental functions of the central nervous system. Since saccadic eye movements are among our most stereotyped motor responses, we hypothesized that individual variability in the ability to inhibit a prepotent saccade and make a voluntary antisaccade would be related to individual variability in intrinsic connectivity. Twenty-three individuals completed the antisaccade task and resting-state functional magnetic resonance imaging (fMRI). A multivariate analysis of covariance identified relationships between fMRI oscillations (0.01-0.2 Hz) of resting-state networks determined using high-dimensional independent component analysis and antisaccade performance (latency, error rate). Significant multivariate relationships between antisaccade latency and directional error rate were obtained in independent components across the entire brain. Some of the relationships were obtained in components that overlapped substantially with the task; however, many were obtained in components that showed little overlap with the task. The current results demonstrate that even in the absence of a task, spectral power in regions showing little overlap with task activity predicts an individual's performance on a saccade task.

Label-free observation of tissues by high-speed stimulated Raman spectral microscopy and independent component analysis

NASA Astrophysics Data System (ADS)

Ozeki, Yasuyuki; Otsuka, Yoichi; Sato, Shuya; Hashimoto, Hiroyuki; Umemura, Wataru; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi

2013-02-01

We have developed a video-rate stimulated Raman scattering (SRS) microscope with frame-by-frame wavenumber tunability. The system uses a 76-MHz picosecond Ti:sapphire laser and a subharmonically synchronized, 38-MHz Yb fiber laser. The Yb fiber laser pulses are spectrally sliced by a fast wavelength-tunable filter, which consists of a galvanometer scanner, a 4-f optical system and a reflective grating. The spectral resolution of the filter is ~ 3 cm-1. The wavenumber was scanned from 2800 to 3100 cm-1 with an arbitrary waveform synchronized to the frame trigger. For imaging, we introduced a 8-kHz resonant scanner and a galvanometer scanner. We were able to acquire SRS images of 500 x 480 pixels at a frame rate of 30.8 frames/s. Then these images were processed by principal component analysis followed by a modified algorithm of independent component analysis. This algorithm allows blind separation of constituents with overlapping Raman bands from SRS spectral images. The independent component (IC) spectra give spectroscopic information, and IC images can be used to produce pseudo-color images. We demonstrate various label-free imaging modalities such as 2D spectral imaging of the rat liver, two-color 3D imaging of a vessel in the rat liver, and spectral imaging of several sections of intestinal villi in the mouse. Various structures in the tissues such as lipid droplets, cytoplasm, fibrous texture, nucleus, and water-rich region were successfully visualized.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

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

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Stabilizing bidirectional associative memory with Principles in Independent Component Analysis and Null Space (PICANS)

NASA Astrophysics Data System (ADS)

LaRue, James P.; Luzanov, Yuriy

2013-05-01

A new extension to the way in which the Bidirectional Associative Memory (BAM) algorithms are implemented is presented here. We will show that by utilizing the singular value decomposition (SVD) and integrating principles of independent component analysis (ICA) into the nullspace (NS) we have created a novel approach to mitigating spurious attractors. We demonstrate this with two applications. The first application utilizes a one-layer association while the second application is modeled after the several hierarchal associations of ventral pathways. The first application will detail the way in which we manage the associations in terms of matrices. The second application will take what we have learned from the first example and apply it to a cascade of a convolutional neural network (CNN) and perceptron this being our signal processing model of the ventral pathways, i.e., visual systems.

The perception of coherent and non-coherent auditory objects: a signature in gamma frequency band.

PubMed

Knief, A; Schulte, M; Bertran, O; Pantev, C

2000-07-01

The pertinence of gamma band activity in magnetoencephalographic and electroencephalographic recordings for the performance of a gestalt recognition process is a question at issue. We investigated the functional relevance of gamma band activity for the perception of auditory objects. An auditory experiment was performed as an analog to the Kanizsa experiment in the visual modality, comprising four different coherent and non-coherent stimuli. For the first time functional differences of evoked gamma band activity due to the perception of these stimuli were demonstrated by various methods (localization of sources, wavelet analysis and independent component analysis, ICA). Responses to coherent stimuli were found to have more features in common compared to non-coherent stimuli (e.g. closer located sources and smaller number of ICA components). The results point to the existence of a pitch processor in the auditory pathway.

A Genome-Wide RNAi Screen for Modifiers of the Circadian Clock in Human Cells

PubMed Central

Zhang, Eric E.; Liu, Andrew C.; Hirota, Tsuyoshi; Miraglia, Loren J.; Welch, Genevieve; Pongsawakul, Pagkapol Y.; Liu, Xianzhong; Atwood, Ann; Huss, Jon W.; Janes, Jeff; Su, Andrew I.; Hogenesch, John B.; Kay, Steve A.

2009-01-01

Summary Two decades of research identified more than a dozen clock genes and defined a biochemical feedback mechanism of circadian oscillator function. To identify additional clock genes and modifiers, we conducted a genome-wide siRNA screen in a human cellular clock model. Knockdown of nearly a thousand genes reduced rhythm amplitude. Potent effects on period length or increased amplitude were less frequent; we found hundreds of these and confirmed them in secondary screens. Characterization of a subset of these genes demonstrated a dosage-dependent effect on oscillator function. Protein interaction network analysis showed that dozens of gene products directly or indirectly associate with known clock components. Pathway analysis revealed these genes are overrepresented for components of insulin and hedgehog signaling, the cell cycle, and the folate metabolism. Coupled with data showing many of these pathways are clock-regulated, we conclude the clock is interconnected with many aspects of cellular function. PMID:19765810

The Baptist Health Nurse Retention Questionnaire: A Methodological Study, Part 1.

PubMed

Lengerich, Alexander; Bugajski, Andrew; Marchese, Matthew; Hall, Brittany; Yackzan, Susan; Davies, Claire; Brockopp, Dorothy

2017-05-01

The purposes of this study were to develop and test the Baptist Health Nurse Retention Questionnaire (BHNRQ) and examine the importance of nurse retention factors. Multiple factors, including increasing patient acuity levels, have led to concerns regarding nurse retention. An understanding of current factors related to retention is limited. To establish the psychometric properties of the BHNRQ, data were collected from 279 bedside nurses at a 391-bed, Magnet® redesignated community hospital. A principal component analysis was conducted to determine the subscale structure of the BHNRQ. Additional analyses were conducted related to content validity and test-retest reliability. The results of the principal components analysis revealed 3 subscales: nursing practice, management, and staffing. Analyses demonstrate that the BHNRQ is a reliable and valid instrument for measuring nurse retention factors. The BHNRQ was found to be a clinically useful instrument for measuring important factors related to nurse retention.

Automatic classification of retinal three-dimensional optical coherence tomography images using principal component analysis network with composite kernels

NASA Astrophysics Data System (ADS)

Fang, Leyuan; Wang, Chong; Li, Shutao; Yan, Jun; Chen, Xiangdong; Rabbani, Hossein

2017-11-01

We present an automatic method, termed as the principal component analysis network with composite kernel (PCANet-CK), for the classification of three-dimensional (3-D) retinal optical coherence tomography (OCT) images. Specifically, the proposed PCANet-CK method first utilizes the PCANet to automatically learn features from each B-scan of the 3-D retinal OCT images. Then, multiple kernels are separately applied to a set of very important features of the B-scans and these kernels are fused together, which can jointly exploit the correlations among features of the 3-D OCT images. Finally, the fused (composite) kernel is incorporated into an extreme learning machine for the OCT image classification. We tested our proposed algorithm on two real 3-D spectral domain OCT (SD-OCT) datasets (of normal subjects and subjects with the macular edema and age-related macular degeneration), which demonstrated its effectiveness.

The structure of cross-cultural musical diversity.

PubMed

Rzeszutek, Tom; Savage, Patrick E; Brown, Steven

2012-04-22

Human cultural traits, such as languages, musics, rituals and material objects, vary widely across cultures. However, the majority of comparative analyses of human cultural diversity focus on between-culture variation without consideration for within-culture variation. In contrast, biological approaches to genetic diversity, such as the analysis of molecular variance (AMOVA) framework, partition genetic diversity into both within- and between-population components. We attempt here for the first time to quantify both components of cultural diversity by applying the AMOVA model to music. By employing this approach with 421 traditional songs from 16 Austronesian-speaking populations, we show that the vast majority of musical variability is due to differences within populations rather than differences between. This demonstrates a striking parallel to the structure of genetic diversity in humans. A neighbour-net analysis of pairwise population musical divergence shows a large amount of reticulation, indicating the pervasive occurrence of borrowing and/or convergent evolution of musical features across populations.

The Recalled Childhood Gender Questionnaire-Revised: a psychometric analysis in a sample of women with congenital adrenal hyperplasia.

PubMed

Meyer-Bahlburg, Heino F L; Dolezal, Curtis; Zucker, Kenneth J; Kessler, Suzanna J; Schober, Justine M; New, Maria I

2006-11-01

We administered the 18-item Recalled Childhood Gender Questionnaire-Revised (RCGQ-R), female version, to 147 adult women with congenital adrenal hyperplasia (CAH) representing three different degrees of prenatal androgenization due to 21-hydroxylase deficiency and to non-CAH controls. A principal components analysis generated three components accounting for 46%, 9%, and 6% of the variance, respectively. Corresponding unit-weighted scales (high scores = feminine) were labeled Gender Role (13 items; Cronbach alpha = .91), Physical Activity (3 items; alpha = .64), and Cross-Gender Desire (2 items; alpha = .47). Discriminant validity was demonstrated in terms of highly significant comparisons across the four groups. We conclude that the first 2 RCGQ-R scales show good psychometric qualities, but that the third scale needs to be further evaluated in a sample that includes women with gender identity disorder.

SVD-aided pseudo principal-component analysis: A new method to speed up and improve determination of the optimum kinetic model from time-resolved data

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

Oang, Key Young; Yang, Cheolhee; Muniyappan, Srinivasan

Determination of the optimum kinetic model is an essential prerequisite for characterizing dynamics and mechanism of a reaction. Here, we propose a simple method, termed as singular value decomposition-aided pseudo principal-component analysis (SAPPA), to facilitate determination of the optimum kinetic model from time-resolved data by bypassing any need to examine candidate kinetic models. We demonstrate the wide applicability of SAPPA by examining three different sets of experimental time-resolved data and show that SAPPA can efficiently determine the optimum kinetic model. In addition, the results of SAPPA for both time-resolved X-ray solution scattering (TRXSS) and transient absorption (TA) data of themore » same protein reveal that global structural changes of protein, which is probed by TRXSS, may occur more slowly than local structural changes around the chromophore, which is probed by TA spectroscopy.« less

The structure of cross-cultural musical diversity

PubMed Central

Rzeszutek, Tom; Savage, Patrick E.; Brown, Steven

2012-01-01

Human cultural traits, such as languages, musics, rituals and material objects, vary widely across cultures. However, the majority of comparative analyses of human cultural diversity focus on between-culture variation without consideration for within-culture variation. In contrast, biological approaches to genetic diversity, such as the analysis of molecular variance (AMOVA) framework, partition genetic diversity into both within- and between-population components. We attempt here for the first time to quantify both components of cultural diversity by applying the AMOVA model to music. By employing this approach with 421 traditional songs from 16 Austronesian-speaking populations, we show that the vast majority of musical variability is due to differences within populations rather than differences between. This demonstrates a striking parallel to the structure of genetic diversity in humans. A neighbour-net analysis of pairwise population musical divergence shows a large amount of reticulation, indicating the pervasive occurrence of borrowing and/or convergent evolution of musical features across populations. PMID:22072606

Bioenergy Feedstock Development Program Status Report

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

Kszos, L.A.

2001-02-09

The U.S. Department of Energy's (DOE's) Bioenergy Feedstock Development Program (BFDP) at Oak Ridge National Laboratory (ORNL) is a mission-oriented program of research and analysis whose goal is to develop and demonstrate cropping systems for producing large quantities of low-cost, high-quality biomass feedstocks for use as liquid biofuels, biomass electric power, and/or bioproducts. The program specifically supports the missions and goals of DOE's Office of Fuels Development and DOE's Office of Power Technologies. ORNL has provided technical leadership and field management for the BFDP since DOE began energy crop research in 1978. The major components of the BFDP include energymore » crop selection and breeding; crop management research; environmental assessment and monitoring; crop production and supply logistics operational research; integrated resource analysis and assessment; and communications and outreach. Research into feedstock supply logistics has recently been added and will become an integral component of the program.« less

An improved principal component analysis based region matching method for fringe direction estimation

NASA Astrophysics Data System (ADS)

He, A.; Quan, C.

2018-04-01

The principal component analysis (PCA) and region matching combined method is effective for fringe direction estimation. However, its mask construction algorithm for region matching fails in some circumstances, and the algorithm for conversion of orientation to direction in mask areas is computationally-heavy and non-optimized. We propose an improved PCA based region matching method for the fringe direction estimation, which includes an improved and robust mask construction scheme, and a fast and optimized orientation-direction conversion algorithm for the mask areas. Along with the estimated fringe direction map, filtered fringe pattern by automatic selective reconstruction modification and enhanced fast empirical mode decomposition (ASRm-EFEMD) is used for Hilbert spiral transform (HST) to demodulate the phase. Subsequently, windowed Fourier ridge (WFR) method is used for the refinement of the phase. The robustness and effectiveness of proposed method are demonstrated by both simulated and experimental fringe patterns.