[Analysis on component difference in Citrus reticulata before and after being processed with salt by UPLC-Q-TOF/MS].

PubMed

Zeng, Rui; Fu, Juan; Wu, La-Bin; Huang, Lin-Fang

2013-07-01

To analyze components of Citrus reticulata and salt-processed C. reticulata by ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF/MS), and compared the changes in components before and after being processed with salt. Principal component analysis (PCA) and partial least squares discriminant analysis (OPLS-DA) were adopted to analyze the difference in fingerprint between crude and processed C. reticulata, showing increased content of eriocitrin, limonin, nomilin and obacunone increase in salt-processed C. reticulata. Potential chemical markers were identified as limonin, obacunone and nomilin, which could be used for distinguishing index components of crude and processed C. reticulata.

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

PubMed

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

2010-07-15

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

Component isolation for multi-component signal analysis using a non-parametric gaussian latent feature model

NASA Astrophysics Data System (ADS)

Yang, Yang; Peng, Zhike; Dong, Xingjian; Zhang, Wenming; Clifton, David A.

2018-03-01

A challenge in analysing non-stationary multi-component signals is to isolate nonlinearly time-varying signals especially when they are overlapped in time and frequency plane. In this paper, a framework integrating time-frequency analysis-based demodulation and a non-parametric Gaussian latent feature model is proposed to isolate and recover components of such signals. The former aims to remove high-order frequency modulation (FM) such that the latter is able to infer demodulated components while simultaneously discovering the number of the target components. The proposed method is effective in isolating multiple components that have the same FM behavior. In addition, the results show that the proposed method is superior to generalised demodulation with singular-value decomposition-based method, parametric time-frequency analysis with filter-based method and empirical model decomposition base method, in recovering the amplitude and phase of superimposed components.

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.

Extracting functional components of neural dynamics with Independent Component Analysis and inverse Current Source Density.

PubMed

Lęski, Szymon; Kublik, Ewa; Swiejkowski, Daniel A; Wróbel, Andrzej; Wójcik, Daniel K

2010-12-01

Local field potentials have good temporal resolution but are blurred due to the slow spatial decay of the electric field. For simultaneous recordings on regular grids one can reconstruct efficiently the current sources (CSD) using the inverse Current Source Density method (iCSD). It is possible to decompose the resultant spatiotemporal information about the current dynamics into functional components using Independent Component Analysis (ICA). We show on test data modeling recordings of evoked potentials on a grid of 4 × 5 × 7 points that meaningful results are obtained with spatial ICA decomposition of reconstructed CSD. The components obtained through decomposition of CSD are better defined and allow easier physiological interpretation than the results of similar analysis of corresponding evoked potentials in the thalamus. We show that spatiotemporal ICA decompositions can perform better for certain types of sources but it does not seem to be the case for the experimental data studied. Having found the appropriate approach to decomposing neural dynamics into functional components we use the technique to study the somatosensory evoked potentials recorded on a grid spanning a large part of the forebrain. We discuss two example components associated with the first waves of activation of the somatosensory thalamus. We show that the proposed method brings up new, more detailed information on the time and spatial location of specific activity conveyed through various parts of the somatosensory thalamus in the rat.

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.

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

PubMed

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

2013-08-01

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

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

PubMed

Mitsutake, Ayori; Iijima, Hiromitsu; Takano, Hiroshi

2011-10-28

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

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.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D

2008-05-12

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component's discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies.

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulhee

2016-04-01

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

[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.

Survey to Identify Substandard and Falsified Tablets in Several Asian Countries with Pharmacopeial Quality Control Tests and Principal Component Analysis of Handheld Raman Spectroscopy.

PubMed

Kakio, Tomoko; Nagase, Hitomi; Takaoka, Takashi; Yoshida, Naoko; Hirakawa, Junichi; Macha, Susan; Hiroshima, Takashi; Ikeda, Yukihiro; Tsuboi, Hirohito; Kimura, Kazuko

2018-06-01

The World Health Organization has warned that substandard and falsified medical products (SFs) can harm patients and fail to treat the diseases for which they were intended, and they affect every region of the world, leading to loss of confidence in medicines, health-care providers, and health systems. Therefore, development of analytical procedures to detect SFs is extremely important. In this study, we investigated the quality of pharmaceutical tablets containing the antihypertensive candesartan cilexetil, collected in China, Indonesia, Japan, and Myanmar, using the Japanese pharmacopeial analytical procedures for quality control, together with principal component analysis (PCA) of Raman spectrum obtained with handheld Raman spectrometer. Some samples showed delayed dissolution and failed to meet the pharmacopeial specification, whereas others failed the assay test. These products appeared to be substandard. Principal component analysis showed that all Raman spectra could be explained in terms of two components: the amount of the active pharmaceutical ingredient and the kinds of excipients. Principal component analysis score plot indicated one substandard, and the falsified tablets have similar principal components in Raman spectra, in contrast to authentic products. The locations of samples within the PCA score plot varied according to the source country, suggesting that manufacturers in different countries use different excipients. Our results indicate that the handheld Raman device will be useful for detection of SFs in the field. Principal component analysis of that Raman data clarify the difference in chemical properties between good quality products and SFs that circulate in the Asian market.

Learning Principal Component Analysis by Using Data from Air Quality Networks

ERIC Educational Resources Information Center

Perez-Arribas, Luis Vicente; Leon-González, María Eugenia; Rosales-Conrado, Noelia

2017-01-01

With the final objective of using computational and chemometrics tools in the chemistry studies, this paper shows the methodology and interpretation of the Principal Component Analysis (PCA) using pollution data from different cities. This paper describes how students can obtain data on air quality and process such data for additional information…

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Weighted Components of i-Government Enterprise Architecture

NASA Astrophysics Data System (ADS)

Budiardjo, E. K.; Firmansyah, G.; Hasibuan, Z. A.

2017-01-01

Lack of government performance, among others due to the lack of coordination and communication among government agencies. Whilst, Enterprise Architecture (EA) in the government can be use as a strategic planning tool to improve productivity, efficiency, and effectivity. However, the existence components of Government Enterprise Architecture (GEA) do not show level of importance, that cause difficulty in implementing good e-government for good governance. This study is to explore the weight of GEA components using Principal Component Analysis (PCA) in order to discovered an inherent structure of e-government. The results show that IT governance component of GEA play a major role in the GEA. The rest of components that consist of e-government system, e-government regulation, e-government management, and application key operational, contributed more or less the same. Beside that GEA from other countries analyzes using comparative base on comon enterprise architecture component. These weighted components use to construct i-Government enterprise architecture. and show the relative importance of component in order to established priorities in developing e-government.

Rosacea assessment by erythema index and principal component analysis segmentation maps

NASA Astrophysics Data System (ADS)

Kuzmina, Ilona; Rubins, Uldis; Saknite, Inga; Spigulis, Janis

2017-12-01

RGB images of rosacea were analyzed using segmentation maps of principal component analysis (PCA) and erythema index (EI). Areas of segmented clusters were compared to Clinician's Erythema Assessment (CEA) values given by two dermatologists. The results show that visible blood vessels are segmented more precisely on maps of the erythema index and the third principal component (PC3). In many cases, a distribution of clusters on EI and PC3 maps are very similar. Mean values of clusters' areas on these maps show a decrease of the area of blood vessels and erythema and an increase of lighter skin area after the therapy for the patients with diagnosis CEA = 2 on the first visit and CEA=1 on the second visit. This study shows that EI and PC3 maps are more useful than the maps of the first (PC1) and second (PC2) principal components for indicating vascular structures and erythema on the skin of rosacea patients and therapy monitoring.

Combination of PCA and LORETA for sources analysis of ERP data: an emotional processing study

NASA Astrophysics Data System (ADS)

Hu, Jin; Tian, Jie; Yang, Lei; Pan, Xiaohong; Liu, Jiangang

2006-03-01

The purpose of this paper is to study spatiotemporal patterns of neuronal activity in emotional processing by analysis of ERP data. 108 pictures (categorized as positive, negative and neutral) were presented to 24 healthy, right-handed subjects while 128-channel EEG data were recorded. An analysis of two steps was applied to the ERP data. First, principal component analysis was performed to obtain significant ERP components. Then LORETA was applied to each component to localize their brain sources. The first six principal components were extracted, each of which showed different spatiotemporal patterns of neuronal activity. The results agree with other emotional study by fMRI or PET. The combination of PCA and LORETA can be used to analyze spatiotemporal patterns of ERP data in emotional processing.

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.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D.

2009-01-01

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component’s discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies. PMID:20582334

Independent Component Analysis of Textures

NASA Technical Reports Server (NTRS)

Manduchi, Roberto; Portilla, Javier

2000-01-01

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.

Rotordynamic Characteristics of the HPOTP (High Pressure Oxygen Turbopump) of the SSME (Space Shuttle Main Engine)

NASA Technical Reports Server (NTRS)

Childs, D. W.

1984-01-01

Rotational stability of turbopump components in the space shuttle main engine was studied via analysis of component and structural dynamic models. Subsynchronous vibration caused unacceptable migration of the rotor/housing unit with unequal load sharing of the synchronous bearings that resulted in the failure of the High Pressure Oxygen Turbopump. Linear analysis shows that a shrouded inducer eliminates the second critical speed and the stability problem, a stiffened rotor improves the rotordynamic characteristics of the turbopump, and installing damper boost/impeller seals reduces bearing loads. Nonlinear analysis shows that by increasing the "dead band' clearances, a marked reduction in peak bearing loads occurs.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

A comparison of independent component analysis algorithms and measures to discriminate between EEG and artifact components.

PubMed

Dharmaprani, Dhani; Nguyen, Hoang K; Lewis, Trent W; DeLosAngeles, Dylan; Willoughby, John O; Pope, Kenneth J

2016-08-01

Independent Component Analysis (ICA) is a powerful statistical tool capable of separating multivariate scalp electrical signals into their additive independent or source components, specifically EEG or electroencephalogram and artifacts. Although ICA is a widely accepted EEG signal processing technique, classification of the recovered independent components (ICs) is still flawed, as current practice still requires subjective human decisions. Here we build on the results from Fitzgibbon et al. [1] to compare three measures and three ICA algorithms. Using EEG data acquired during neuromuscular paralysis, we tested the ability of the measures (spectral slope, peripherality and spatial smoothness) and algorithms (FastICA, Infomax and JADE) to identify components containing EMG. Spatial smoothness showed differentiation between paralysis and pre-paralysis ICs comparable to spectral slope, whereas peripherality showed less differentiation. A combination of the measures showed better differentiation than any measure alone. Furthermore, FastICA provided the best discrimination between muscle-free and muscle-contaminated recordings in the shortest time, suggesting it may be the most suited to EEG applications of the considered algorithms. Spatial smoothness results suggest that a significant number of ICs are mixed, i.e. contain signals from more than one biological source, and so the development of an ICA algorithm that is optimised to produce ICs that are easily classifiable is warranted.

Hyperspectral functional imaging of the human brain

NASA Astrophysics Data System (ADS)

Toronov, Vladislav; Schelkanova, Irina

2013-03-01

We performed the independent component analysis of the hyperspectral functional near-infrared data acquired on humans during exercise and rest. We found that the hyperspectral functional data acquired on the human brain requires only two physiologically meaningful components to cover more than 50% o the temporal variance in hundreds of wavelengths. The analysis of the spectra of independent components showed that these components could be interpreted as results of changes in the cerebral blood volume and blood flow. Also, we found significant contributions of water and cytochrome c oxydase into changes associated with the independent components. Another remarkable effect of ICA was its good performance in terms of the filtering of the data noise.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Regional assessment of trends in vegetation change dynamics using principal component analysis

NASA Astrophysics Data System (ADS)

Osunmadewa, B. A.; Csaplovics, E.; R. A., Majdaldin; Adeofun, C. O.; Aralova, D.

2016-10-01

Vegetation forms the basis for the existence of animal and human. Due to changes in climate and human perturbation, most of the natural vegetation of the world has undergone some form of transformation both in composition and structure. Increased anthropogenic activities over the last decades had pose serious threat on the natural vegetation in Nigeria, many vegetated areas are either transformed to other land use such as deforestation for agricultural purpose or completely lost due to indiscriminate removal of trees for charcoal, fuelwood and timber production. This study therefore aims at examining the rate of change in vegetation cover, the degree of change and the application of Principal Component Analysis (PCA) in the dry sub-humid region of Nigeria using Normalized Difference Vegetation Index (NDVI) data spanning from 1983-2011. The method used for the analysis is the T-mode orientation approach also known as standardized PCA, while trends are examined using ordinary least square, median trend (Theil-Sen) and monotonic trend. The result of the trend analysis shows both positive and negative trend in vegetation change dynamics over the 29 years period examined. Five components were used for the Principal Component Analysis. The results of the first component explains about 98 % of the total variance of the vegetation (NDVI) while components 2-5 have lower variance percentage (< 1%). Two ancillary land use land cover data of 2000 and 2009 from European Space Agency (ESA) were used to further explain changes observed in the Normalized Difference Vegetation Index. The result of the land use data shows changes in land use pattern which can be attributed to anthropogenic activities such as cutting of trees for charcoal production, fuelwood and agricultural practices. The result of this study shows the ability of remote sensing data for monitoring vegetation change in the dry-sub humid region of Nigeria.

Make or buy decision model with multi-stage manufacturing process and supplier imperfect quality

NASA Astrophysics Data System (ADS)

Pratama, Mega Aria; Rosyidi, Cucuk Nur

2017-11-01

This research develops an make or buy decision model considering supplier imperfect quality. This model can be used to help companies make the right decision in case of make or buy component with the best quality and the least cost in multistage manufacturing process. The imperfect quality is one of the cost component that must be minimizing in this model. Component with imperfect quality, not necessarily defective. It still can be rework and used for assembly. This research also provide a numerical example and sensitivity analysis to show how the model work. We use simulation and help by crystal ball to solve the numerical problem. The sensitivity analysis result show that percentage of imperfect generally not affect to the model significantly, and the model is not sensitive to changes in these parameters. This is because the imperfect cost are smaller than overall total cost components.

The Use of Principal Components in Long-Range Forecasting

NASA Astrophysics Data System (ADS)

Chern, Jonq-Gong

Large-scale modes of the global sea surface temperatures and the Northern Hemisphere tropospheric circulation are described by principal component analysis. The first and the second SST components well describe the El Nino episodes, and the El Nino index (ENI), suggested in this study, is consistent with the winter Southern Oscillation index (SOI), where this ENI is a composite component of the weighted first and second SST components. The large-scale interactive modes of the coupling ocean-atmosphere system are identified by cross-correlation analysis The result shows that the first SST component is strongly correlated with the first component of geopotential height in lead time of 6 months. In the El Nino-Southern Oscillation (ENSO) evolution, the El Nino mode strongly influences the winter tropospheric circulation in the mid -latitudes for up to three leading seasons. The regional long-range variation of climate is investigated with these major components of the SST and the tropospheric circulation. In the mid-latitude, the climate of the central United States shows a weak linkage with these large-scale circulations, and the climate of the western United States appears to be consistently associated with the ENSO modes. These El Nino modes also show a dominant influence on Eastern Asia as evidenced in Taiwan Mei-Yu patterns. Possible regional long-range forecasting schemes, utilizing the complementary characteristics of the winter El Nino mode and SST anomalies, are examined with the Taiwan Mei-Yu.

Integrated fluorescence analysis system

DOEpatents

Buican, Tudor N.; Yoshida, Thomas M.

1992-01-01

An integrated fluorescence analysis system enables a component part of a sample to be virtually sorted within a sample volume after a spectrum of the component part has been identified from a fluorescence spectrum of the entire sample in a flow cytometer. Birefringent optics enables the entire spectrum to be resolved into a set of numbers representing the intensity of spectral components of the spectrum. One or more spectral components are selected to program a scanning laser microscope, preferably a confocal microscope, whereby the spectrum from individual pixels or voxels in the sample can be compared. Individual pixels or voxels containing the selected spectral components are identified and an image may be formed to show the morphology of the sample with respect to only those components having the selected spectral components. There is no need for any physical sorting of the sample components to obtain the morphological information.

Lattice Independent Component Analysis for Mobile Robot Localization

NASA Astrophysics Data System (ADS)

Villaverde, Ivan; Fernandez-Gauna, Borja; Zulueta, Ekaitz

This paper introduces an approach to appearance based mobile robot localization using Lattice Independent Component Analysis (LICA). The Endmember Induction Heuristic Algorithm (EIHA) is used to select a set of Strong Lattice Independent (SLI) vectors, which can be assumed to be Affine Independent, and therefore candidates to be the endmembers of the data. Selected endmembers are used to compute the linear unmixing of the robot's acquired images. The resulting mixing coefficients are used as feature vectors for view recognition through classification. We show on a sample path experiment that our approach can recognise the localization of the robot and we compare the results with the Independent Component Analysis (ICA).

Principal components analysis of the photoresponse nonuniformity of a matrix detector.

PubMed

Ferrero, Alejandro; Alda, Javier; Campos, Joaquín; López-Alonso, Jose Manuel; Pons, Alicia

2007-01-01

The principal component analysis is used to identify and quantify spatial distributions of relative photoresponse as a function of the exposure time for a visible CCD array. The analysis shows a simple way to define an invariant photoresponse nonuniformity and compare it with the definition of this invariant pattern as the one obtained for long exposure times. Experimental data of radiant exposure from levels of irradiance obtained in a stable and well-controlled environment are used.

[Discrimination of Red Tide algae by fluorescence spectra and principle component analysis].

PubMed

Su, Rong-guo; Hu, Xu-peng; Zhang, Chuan-song; Wang, Xiu-lin

2007-07-01

Fluorescence discrimination technology for 11 species of the Red Tide algae at genus level was constructed by principle component analysis and non-negative least squares. Rayleigh and Raman scattering peaks of 3D fluorescence spectra were eliminated by Delaunay triangulation method. According to the results of Fisher linear discrimination, the first principle component score and the second component score of 3D fluorescence spectra were chosen as discriminant feature and the feature base was established. The 11 algae species were tested, and more than 85% samples were accurately determinated, especially for Prorocentrum donghaiense, Skeletonema costatum, Gymnodinium sp., which have frequently brought Red tide in the East China Sea. More than 95% samples were right discriminated. The results showed that the genus discriminant feature of 3D fluorescence spectra of Red Tide algae given by principle component analysis could work well.

Characterization of Strombolian events by using independent component analysis

NASA Astrophysics Data System (ADS)

Ciaramella, A.; de Lauro, E.; de Martino, S.; di Lieto, B.; Falanga, M.; Tagliaferri, R.

2004-10-01

We apply Independent Component Analysis (ICA) to seismic signals recorded at Stromboli volcano. Firstly, we show how ICA works considering synthetic signals, which are generated by dynamical systems. We prove that Strombolian signals, both tremor and explosions, in the high frequency band (>0.5 Hz), are similar in time domain. This seems to give some insights to the organ pipe model generation for the source of these events. Moreover, we are able to recognize in the tremor signals a low frequency component (<0.5 Hz), with a well defined peak corresponding to 30s.

δ Scuti-type pulsation in the hot component of the Algol-type binary system BG Peg

NASA Astrophysics Data System (ADS)

Şenyüz, T.; Soydugan, E.

2014-02-01

In this study, 23 Algol-type binary systems, which were selected as candidate binaries with pulsating components, were observed at the Çanakkale Onsekiz Mart University Observatory. One of these systems was BG Peg. Its hotter component shows δ Scuti-type light variations. Physical parameters of BG Peg were derived from modelling the V light curve using the Wilson-Devinney code. The frequency analysis shows that the pulsational component of the BG Peg system pulsates in two modes with periods of 0.039 and 0.047 d. Mode identification indicates that both modes are most likely non-radial l = 2 modes.

[Identification of two varieties of Citri Fructus by fingerprint and chemometrics].

PubMed

Su, Jing-hua; Zhang, Chao; Sun, Lei; Gu, Bing-ren; Ma, Shuang-cheng

2015-06-01

Citri Fructus identification by fingerprint and chemometrics was investigated in this paper. Twenty-three Citri Fructus samples were collected which referred to two varieties as Cirtus wilsonii and C. medica recorded in Chinese Pharmacopoeia. HPLC chromatograms were obtained. The components were partly identified by reference substances, and then common pattern was established for chemometrics analysis. Similarity analysis, principal component analysis (PCA) , partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis heatmap were applied. The results indicated that C. wilsonii and C. medica could be ideally classified with common pattern contained twenty-five characteristic peaks. Besides, preliminary pattern recognition had verified the chemometrics analytical results. Absolute peak area (APA) was used for relevant quantitative analysis, results showed the differences between two varieties and it was valuable for further quality control as selection of characteristic components.

Detection of increase in corneal irregularity due to pterygium using Fourier series harmonic analyses with multiple diameters.

PubMed

Minami, Keiichiro; Miyata, Kazunori; Otani, Atsushi; Tokunaga, Tadatoshi; Tokuda, Shouta; Amano, Shiro

2018-05-01

To determine steep increase of corneal irregularity induced by advancement of pterygium. A total of 456 eyes from 456 consecutive patients with primary pterygia were examined for corneal topography and advancement of pterygium with respect to the corneal diameter. Corneal irregularity induced by the pterygium advancement was evaluated by Fourier harmonic analyses of the topographic data that were modified for a series of analysis diameters from 1 mm to 6 mm. Incidences of steep increases in the asymmetry or higher-order irregularity components (inflection points) were determined by using segmented regression analysis for each analysis diameter. The pterygium advancement ranged from 2% to 57%, with a mean of 22.0%. Both components showed steep increases from the inflection points. The inflection points in the higher-order irregularity component altered with the analysis diameter (14.0%-30.6%), while there was no alternation in the asymmetry components (35.5%-36.8%). For the former component, the values at the inflection points were obtained in a range of 0.16 to 0.25 D. The Fourier harmonic analyses for a series of analysis diameters revealed that the higher-order irregularity component increased with the pterygium advancement. The analysis results confirmed the precedence of corneal irregularity due to pterygium advancement.

Data analysis using a combination of independent component analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lin, Shih-Lin; Tung, Pi-Cheng; Huang, Norden E.

2009-06-01

A combination of independent component analysis and empirical mode decomposition (ICA-EMD) is proposed in this paper to analyze low signal-to-noise ratio data. The advantages of ICA-EMD combination are these: ICA needs few sensory clues to separate the original source from unwanted noise and EMD can effectively separate the data into its constituting parts. The case studies reported here involve original sources contaminated by white Gaussian noise. The simulation results show that the ICA-EMD combination is an effective data analysis tool.

Global Analysis Reveals the Complexity of the Human Glomerular Extracellular Matrix

PubMed Central

Byron, Adam; Humphries, Jonathan D.; Randles, Michael J.; Carisey, Alex; Murphy, Stephanie; Knight, David; Brenchley, Paul E.; Zent, Roy; Humphries, Martin J.

2014-01-01

The glomerulus contains unique cellular and extracellular matrix (ECM) components, which are required for intact barrier function. Studies of the cellular components have helped to build understanding of glomerular disease; however, the full composition and regulation of glomerular ECM remains poorly understood. We used mass spectrometry-based proteomics of enriched ECM extracts for a global analysis of human glomerular ECM in vivo and identified a tissue-specific proteome of 144 structural and regulatory ECM proteins. This catalog includes all previously identified glomerular components plus many new and abundant components. Relative protein quantification showed a dominance of collagen IV, collagen I, and laminin isoforms in the glomerular ECM together with abundant collagen VI and TINAGL1. Protein network analysis enabled the creation of a glomerular ECM interactome, which revealed a core of highly connected structural components. More than one half of the glomerular ECM proteome was validated using colocalization studies and data from the Human Protein Atlas. This study yields the greatest number of ECM proteins relative to previous investigations of whole glomerular extracts, highlighting the importance of sample enrichment. It also shows that the composition of glomerular ECM is far more complex than previously appreciated and suggests that many more ECM components may contribute to glomerular development and disease processes. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000456. PMID:24436468

A summary of phase analysis on Apollo 14 samples

NASA Technical Reports Server (NTRS)

Fredriksson, K.; Nelen, J.; Noonan, A.; Kraut, F.

1971-01-01

The results of an analysis of lunar samples from Apollo 14 are presented. The large number of breccias returned from the Fra Mauro formation show that impact events are an important rock forming mechanism on the moon. Larger rocks as well as micro breccias bear structural resemblance to brecciated chondrites and terrestrial impactites. Many show evidence of repetitious events of break-up and accumulation welding. The surface of the regolith has become thoroughly mixed by this process. Most components however appear locally derived from basalts rich in feldspar and Kreep components, similar to rocks such as 14310.

Spectral components in electromyograms from four regions of the human masseter, in natural dentate and edentulous subjects with removable prostheses and implants.

PubMed

Guzmán-Venegas, Rodrigo A; Palma, Felipe H; Biotti P, Jorge L; de la Rosa, Francisco J Berral

2018-06-01

To compare the frequency or spectral components between different regions of the superficial masseter in young natural dentate and total edentulous older adults rehabilitated with removable prostheses and fixed-implant support. A secondary objective was to compare these components between the three groups. 21 young natural dentate and 28 edentulous (14 with removable prostheses and 14 with fixed-implant support) were assessed. High-density surface electromyography (sEMG) was recorded in four portions of the superficial masseter during submaximal isometric bites. Spectral components were obtained through a spectral analysis of the sEMG signals. An analysis of mixed models was used to compare the spectral components. In all groups, the spectral components of the anterior portion were lower than in the posterior region (p < 0.05). Both edentulous groups showed lower spectral components and median frequency slope than the natural dentate group (p < 0.05). The removable prostheses group showed the greatest differences with natural dentate group. There were significant differences in the spectral components recorded in the different regions of the superficial masseter. The lower spectral components and fatigability of older adults rehabilitated with prostheses could be a cause of a greater loss of type II fibers, especially in the removable prostheses group. Copyright © 2018 Elsevier Ltd. All rights reserved.

Larvicidal effect of Eucalyptus grandis essential oil and turpentine and their major components on Aedes aegypti larvae.

PubMed

Lucia, Alejandro; Gonzalez Audino, Paola; Seccacini, Emilia; Licastro, Susana; Zerba, Eduardo; Masuh, Hector

2007-09-01

In the search for new alternatives for the control of Aedes aegypti the larvicidal activity of Eucalyptus grandis essential oil and pine resin essential oil (turpentine) and their major components (alpha- and beta-pinene and 1,8-cineole) was determined. Gas chromatography-mass spectroscopy analysis of E. grandis essential oil revealed that its major components are alpha-pinene and 1,8-cineole. Similar analysis of turpentine obtained by distillation of the resin pitch of conifers showed that alpha- and beta-pinene are the only major components. Third and early 4th instars of the CIPEIN-susceptible strain of Ae. aegypti were exposed to acetonic solutions of E. grandis essential oil, turpentine, and their major components for 24 h. Turpentine, with an LC50 of 14.7 ppm, was more active than the essential oil of E. grandis (LC50: 32.4 ppm). Larvicidal activity of the essential oil components showed that alpha- and beta-pinene present low LC50 values (15.4 and 12.1 ppm, respectively), whereas pure 1,8-cineole showed an LC50 of 57.2 ppm. These results suggest that alpha-pinene in E. grandis and alpha- and beta-pinene in turpentine serve as the principal larvicidal components of both oils. Results obtained on larvicidal effects of essential oil of Eucalyptus grandis and turpentine could be considered a contribution to the search for new biodegradable larvicides of natural origin.

Time-of-flight expansion of binary Bose–Einstein condensates at finite temperature

NASA Astrophysics Data System (ADS)

Lee, K. L.; Jørgensen, N. B.; Wacker, L. J.; Skou, M. G.; Skalmstang, K. T.; Arlt, J. J.; Proukakis, N. P.

2018-05-01

Ultracold quantum gases provide a unique setting for studying and understanding the properties of interacting quantum systems. Here, we investigate a multi-component system of 87Rb–39K Bose–Einstein condensates (BECs) with tunable interactions both theoretically and experimentally. Such multi-component systems can be characterized by their miscibility, where miscible components lead to a mixed ground state and immiscible components form a phase-separated state. Here we perform the first full simulation of the dynamical expansion of this system including both BECs and thermal clouds, which allows for a detailed comparison with experimental results. In particular we show that striking features emerge in time-of-flight (TOF) for BECs with strong interspecies repulsion, even for systems which were separated in situ by a large gravitational sag. An analysis of the centre of mass positions of the BECs after expansion yields qualitative agreement with the homogeneous criterion for phase-separation, but reveals no clear transition point between the mixed and the separated phases. Instead one can identify a transition region, for which the presence of a gravitational sag is found to be advantageous. Moreover, we analyse the situation where only one component is condensed and show that the density distribution of the thermal component also shows some distinct features. Our work sheds new light on the analysis of multi-component systems after TOF and will guide future experiments on the detection of miscibility in these systems.

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

Non-Newtonian Liquid Flow through Small Diameter Piping Components: CFD Analysis

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Tarun Kanti; Das, Sudip Kumar

2016-10-01

Computational Fluid Dynamics (CFD) analysis have been carried out to evaluate the frictional pressure drop across the horizontal pipeline and different piping components, like elbows, orifices, gate and globe valves for non-Newtonian liquid through 0.0127 m pipe line. The mesh generation is done using GAMBIT 6.3 and FLUENT 6.3 is used for CFD analysis. The CFD results are verified with our earlier published experimental data. The CFD results show the very good agreement with the experimental values.

Preserved cognitive functions with age are determined by domain-dependent shifts in network responsivity

PubMed Central

Samu, Dávid; Campbell, Karen L.; Tsvetanov, Kamen A.; Shafto, Meredith A.; Brayne, Carol; Bullmore, Edward T.; Calder, Andrew C.; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Henson, Richard N.; Matthews, Fiona E.; Marslen-Wilson, William D.; Rowe, James B.; Cheung, Teresa; Davis, Simon; Geerligs, Linda; Kievit, Rogier; McCarrey, Anna; Mustafa, Abdur; Price, Darren; Taylor, Jason R.; Treder, Matthias; van Belle, Janna; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Henriques, Rafael; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Barnes, Dan; Dixon, Marie; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Tyler, Lorraine K.

2017-01-01

Healthy ageing has disparate effects on different cognitive domains. The neural basis of these differences, however, is largely unknown. We investigated this question by using Independent Components Analysis to obtain functional brain components from 98 healthy participants aged 23–87 years from the population-based Cam-CAN cohort. Participants performed two cognitive tasks that show age-related decrease (fluid intelligence and object naming) and a syntactic comprehension task that shows age-related preservation. We report that activation of task-positive neural components predicts inter-individual differences in performance in each task across the adult lifespan. Furthermore, only the two tasks that show performance declines with age show age-related decreases in task-positive activation of neural components and decreasing default mode (DM) suppression. Our results suggest that distributed, multi-component brain responsivity supports cognition across the adult lifespan, and the maintenance of this, along with maintained DM deactivation, characterizes successful ageing and may explain differential ageing trajectories across cognitive domains. PMID:28480894

Preserved cognitive functions with age are determined by domain-dependent shifts in network responsivity.

PubMed

Samu, Dávid; Campbell, Karen L; Tsvetanov, Kamen A; Shafto, Meredith A; Tyler, Lorraine K

2017-05-08

Healthy ageing has disparate effects on different cognitive domains. The neural basis of these differences, however, is largely unknown. We investigated this question by using Independent Components Analysis to obtain functional brain components from 98 healthy participants aged 23-87 years from the population-based Cam-CAN cohort. Participants performed two cognitive tasks that show age-related decrease (fluid intelligence and object naming) and a syntactic comprehension task that shows age-related preservation. We report that activation of task-positive neural components predicts inter-individual differences in performance in each task across the adult lifespan. Furthermore, only the two tasks that show performance declines with age show age-related decreases in task-positive activation of neural components and decreasing default mode (DM) suppression. Our results suggest that distributed, multi-component brain responsivity supports cognition across the adult lifespan, and the maintenance of this, along with maintained DM deactivation, characterizes successful ageing and may explain differential ageing trajectories across cognitive domains.

Audio-visual speech perception in adult readers with dyslexia: an fMRI study.

PubMed

Rüsseler, Jascha; Ye, Zheng; Gerth, Ivonne; Szycik, Gregor R; Münte, Thomas F

2018-04-01

Developmental dyslexia is a specific deficit in reading and spelling that often persists into adulthood. In the present study, we used slow event-related fMRI and independent component analysis to identify brain networks involved in perception of audio-visual speech in a group of adult readers with dyslexia (RD) and a group of fluent readers (FR). Participants saw a video of a female speaker saying a disyllabic word. In the congruent condition, audio and video input were identical whereas in the incongruent condition, the two inputs differed. Participants had to respond to occasionally occurring animal names. The independent components analysis (ICA) identified several components that were differently modulated in FR and RD. Two of these components including fusiform gyrus and occipital gyrus showed less activation in RD compared to FR possibly indicating a deficit to extract face information that is needed to integrate auditory and visual information in natural speech perception. A further component centered on the superior temporal sulcus (STS) also exhibited less activation in RD compared to FR. This finding is corroborated in the univariate analysis that shows less activation in STS for RD compared to FR. These findings suggest a general impairment in recruitment of audiovisual processing areas in dyslexia during the perception of natural speech.

Artifact suppression and analysis of brain activities with electroencephalography signals.

PubMed

Rashed-Al-Mahfuz, Md; Islam, Md Rabiul; Hirose, Keikichi; Molla, Md Khademul Islam

2013-06-05

Brain-computer interface is a communication system that connects the brain with computer (or other devices) but is not dependent on the normal output of the brain (i.e., peripheral nerve and muscle). Electro-oculogram is a dominant artifact which has a significant negative influence on further analysis of real electroencephalography data. This paper presented a data adaptive technique for artifact suppression and brain wave extraction from electroencephalography signals to detect regional brain activities. Empirical mode decomposition based adaptive thresholding approach was employed here to suppress the electro-oculogram artifact. Fractional Gaussian noise was used to determine the threshold level derived from the analysis data without any training. The purified electroencephalography signal was composed of the brain waves also called rhythmic components which represent the brain activities. The rhythmic components were extracted from each electroencephalography channel using adaptive wiener filter with the original scale. The regional brain activities were mapped on the basis of the spatial distribution of rhythmic components, and the results showed that different regions of the brain are activated in response to different stimuli. This research analyzed the activities of a single rhythmic component, alpha with respect to different motor imaginations. The experimental results showed that the proposed method is very efficient in artifact suppression and identifying individual motor imagery based on the activities of alpha component.

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Development of a software tool to support chemical and biological terrorism intelligence analysis

NASA Astrophysics Data System (ADS)

Hunt, Allen R.; Foreman, William

1997-01-01

AKELA has developed a software tool which uses a systems analytic approach to model the critical processes which support the acquisition of biological and chemical weapons by terrorist organizations. This tool has four major components. The first is a procedural expert system which describes the weapon acquisition process. It shows the relationship between the stages a group goes through to acquire and use a weapon, and the activities in each stage required to be successful. It applies to both state sponsored and small group acquisition. An important part of this expert system is an analysis of the acquisition process which is embodied in a list of observables of weapon acquisition activity. These observables are cues for intelligence collection The second component is a detailed glossary of technical terms which helps analysts with a non- technical background understand the potential relevance of collected information. The third component is a linking capability which shows where technical terms apply to the parts of the acquisition process. The final component is a simple, intuitive user interface which shows a picture of the entire process at a glance and lets the user move quickly to get more detailed information. This paper explains e each of these five model components.

Loss of switch/sucrose non-fermenting complex protein expression is associated with dedifferentiation in endometrial carcinomas

PubMed Central

Karnezis, Anthony N.; Hoang, Lien N.; Coatham, Mackenzie; Ravn, Sarah; Almadani, Noorah; Cloutier, Basile; Irving, Julie; Meng, Bo; Li, Xiaodong; Chow, Christine; McAlpine, Jessica; Kuo, Kuan-Ting; Mao, Tsui-Lien; Djordjevic, Bojana; Soslow, Robert A.; Huntsman, David G.; Gilks, C. Blake; Köbel, Martin; Lee, Cheng-Han

2016-01-01

Dedifferentiated endometrial carcinoma is an aggressive type of endometrial cancer that contains a mix of low grade endometrioid and undifferentiated carcinoma components. We performed targeted sequencing of 8 dedifferentiated endometrial carcinomas and identified somatic frameshift/nonsense mutations in SMARCA4, a core member of the switch/sucrose non-fermenting (SWI/SNF) complex, in the undifferentiated components of 4 tumors. Immunohistochemical analysis confirmed the loss of SMARCA4 in the undifferentiated component of these 4 SMARCA4-mutated cases while the corresponding low grade endometrioid component showed retained SMARCA4 expression. An expanded survey of another member of the SWI/SNF complex showed SMARCB1 loss in the undifferentiated component of 2 SMARCA4-intact tumors. Subsequent immunohistochemical analysis of SMARCA4 and SMARCB1 was done in an additional set of 22 centrally reviewed dedifferentiated endometrial carcinomas and 31 grade 3 endometrioid carcinomas. Combining the results from the index and the expansion set, 15 of 30 (50%) of the dedifferentiated endometrial carcinomas examined showed either SMARCA4 loss (37%) or SMARCB1 loss (13%). The loss of SMARCA4 or SMARCB1 was mutually exclusive and occurred only in the undifferentiated component. All 31 grade 3 endometrioid carcinomas showed intact SMARCA4/SMARCB1 expression. The majority (73%) of the SMARCA4-deficient and half of SMARCB1-deficient undifferentiated component developed in a mismatch repair protein (MMR)-deficient molecular context. The observed spatial association between SMARCA4/SMARCB1 loss and histologic dedifferentiation suggests that loss of these SWI/SNF complex proteins may contribute to the development of dedifferentiated endometrial carcinoma. PMID:26743474

Visualization and Semiquantitative Study of the Distribution of Major Components in Wheat Straw in Mesoscopic Scale using Fourier Transform Infrared Microspectroscopic Imaging.

PubMed

Yang, Zengling; Mei, Jiaqi; Liu, Zhiqiang; Huang, Guangqun; Huang, Guan; Han, Lujia

2018-06-19

Understanding the biochemical heterogeneity of plant tissue linked to crop straw anatomy is attractive to plant researchers and researchers in the field of biomass refinery. This study provides an in situ analysis and semiquantitative visualization of major components distribution in internodal transverse sections of wheat straw based on Fourier transform infrared (FTIR) microspectroscopic imaging, with a fast non-negativity-constrained least squares (fast NNLS) fitting. This paper investigates changes in biochemical components of tissue during stages of elongation, booting, heading, flowering, grain-filling, milk-ripening, dough, and full-ripening. Visualization analysis was carried out with reference spectra for five components (microcrystalline cellulose, xylan, lignin, pectin, and starch) of wheat straw. Our result showed that (a) the cellulose and lignin distribution is consistent with that from tissue-dyeing with safranin O-fast green and (b) the distribution of cellulose, lignin, and starch is consistent with chemical images for characteristic wavelength at 1432, 1507, and 987 cm -1 , respectively, showing no interference from the other components analyzed. With the validation from biochemical images using characteristic wavelength and tissue-dyeing techniques, further semiquantitative analysis in local tissues based on fast NNLS was carried out, and the result showed that (a) the contents of cellulose in various tissues are very different, with most in parenchyma tissue and least in the epidermis and (b) during plant development, the fluctuation of each component in tissues follows nearly the same trend, especially within vascular bundles and parenchyma tissue. Thus, FTIR microspectroscopic imaging combined with suitable chemometric methods can be successfully applied to study chemical distributions within the internodes transverse sections of wheat straw, providing semiquantitative chemical information.

[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.

Research on distributed heterogeneous data PCA algorithm based on cloud platform

NASA Astrophysics Data System (ADS)

Zhang, Jin; Huang, Gang

2018-05-01

Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

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.

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.

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Scaling analysis of bilateral hand tremor movements in essential tremor patients.

PubMed

Blesic, S; Maric, J; Dragasevic, N; Milanovic, S; Kostic, V; Ljubisavljevic, Milos

2011-08-01

Recent evidence suggests that the dynamic-scaling behavior of the time-series of signals extracted from separate peaks of tremor spectra may reveal existence of multiple independent sources of tremor. Here, we have studied dynamic characteristics of the time-series of hand tremor movements in essential tremor (ET) patients using the detrended fluctuation analysis method. Hand accelerometry was recorded with (500 g) and without weight loading under postural conditions in 25 ET patients and 20 normal subjects. The time-series comprising peak-to-peak (PtP) intervals were extracted from regions around the first three main frequency components of power spectra (PwS) of the recorded tremors. The data were compared between the load and no-load condition on dominant (related to tremor severity) and non-dominant tremor side and with the normal (physiological) oscillations in healthy subjects. Our analysis shows that, in ET, the dynamic characteristics of the main frequency component of recorded tremors exhibit scaling behavior. Furthermore, they show that the two main components of ET tremor frequency spectra, otherwise indistinguishable without load, become significantly different after inertial loading and that they differ between the tremor sides (related to tremor severity). These results show that scaling, a time-domain analysis, helps revealing tremor features previously not revealed by frequency-domain analysis and suggest that distinct oscillatory central circuits may generate the tremor in ET patients.

Artifacts and noise removal in electrocardiograms using independent component analysis.

PubMed

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

2008-09-26

Independent component analysis (ICA) is a novel technique capable of separating independent components from electrocardiogram (ECG) complex signals. The purpose of this analysis is to evaluate the effectiveness of ICA in removing artifacts and noise from ECG recordings. ICA is applied to remove artifacts and noise in ECG segments of either an individual ECG CSE data base file or all files. The reconstructed ECGs are compared with the original ECG signal. For the four special cases discussed, the R-Peak magnitudes of the CSE data base ECG waveforms before and after applying ICA are also found. In the results, it is shown that in most of the cases, the percentage error in reconstruction is very small. The results show that there is a significant improvement in signal quality, i.e. SNR. All the ECG recording cases dealt showed an improved ECG appearance after the use of ICA. This establishes the efficacy of ICA in elimination of noise and artifacts in electrocardiograms.

The Development and Validation of the Empathy Components Questionnaire (ECQ).

PubMed

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

Key research suggests that empathy is a multidimensional construct comprising of both cognitive and affective components. More recent theories and research suggest even further factors within these components of empathy, including the ability to empathize with others versus the drive towards empathizing with others. While numerous self-report measures have been developed to examine empathy, none of them currently index all of these wider components together. The aim of the present research was to develop and validate the Empathy Components Questionnaire (ECQ) to measure cognitive and affective components, as well as ability and drive components within each. Study one utilized items measuring cognitive and affective empathy taken from various established questionnaires to create an initial version of the ECQ. Principal component analysis (PCA) was used to examine the underlying components of empathy within the ECQ in a sample of 101 typical adults. Results revealed a five-component model consisting of cognitive ability, cognitive drive, affective ability, affective drive, and a fifth factor assessing affective reactivity. This five-component structure was then validated and confirmed using confirmatory factor analysis (CFA) in an independent sample of 211 typical adults. Results also showed that females scored higher than males overall on the ECQ, and on specific components, which is consistent with previous findings of a female advantage on self-reported empathy. Findings also showed certain components predicted scores on an independent measure of social behavior, which provided good convergent validity of the ECQ. Together, these findings validate the newly developed ECQ as a multidimensional measure of empathy more in-line with current theories of empathy. The ECQ provides a useful new tool for quick and easy measurement of empathy and its components for research with both healthy and clinical populations.

The Development and Validation of the Empathy Components Questionnaire (ECQ)

PubMed Central

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

Key research suggests that empathy is a multidimensional construct comprising of both cognitive and affective components. More recent theories and research suggest even further factors within these components of empathy, including the ability to empathize with others versus the drive towards empathizing with others. While numerous self-report measures have been developed to examine empathy, none of them currently index all of these wider components together. The aim of the present research was to develop and validate the Empathy Components Questionnaire (ECQ) to measure cognitive and affective components, as well as ability and drive components within each. Study one utilized items measuring cognitive and affective empathy taken from various established questionnaires to create an initial version of the ECQ. Principal component analysis (PCA) was used to examine the underlying components of empathy within the ECQ in a sample of 101 typical adults. Results revealed a five-component model consisting of cognitive ability, cognitive drive, affective ability, affective drive, and a fifth factor assessing affective reactivity. This five-component structure was then validated and confirmed using confirmatory factor analysis (CFA) in an independent sample of 211 typical adults. Results also showed that females scored higher than males overall on the ECQ, and on specific components, which is consistent with previous findings of a female advantage on self-reported empathy. Findings also showed certain components predicted scores on an independent measure of social behavior, which provided good convergent validity of the ECQ. Together, these findings validate the newly developed ECQ as a multidimensional measure of empathy more in-line with current theories of empathy. The ECQ provides a useful new tool for quick and easy measurement of empathy and its components for research with both healthy and clinical populations. PMID:28076406

Non-linear Min protein interactions generate harmonics that signal mid-cell division in Escherichia coli

PubMed Central

Walsh, James C.; Angstmann, Christopher N.; Duggin, Iain G.

2017-01-01

The Min protein system creates a dynamic spatial pattern in Escherichia coli cells where the proteins MinD and MinE oscillate from pole to pole. MinD positions MinC, an inhibitor of FtsZ ring formation, contributing to the mid-cell localization of cell division. In this paper, Fourier analysis is used to decompose experimental and model MinD spatial distributions into time-dependent harmonic components. In both experiment and model, the second harmonic component is responsible for producing a mid-cell minimum in MinD concentration. The features of this harmonic are robust in both experiment and model. Fourier analysis reveals a close correspondence between the time-dependent behaviour of the harmonic components in the experimental data and model. Given this, each molecular species in the model was analysed individually. This analysis revealed that membrane-bound MinD dimer shows the mid-cell minimum with the highest contrast when averaged over time, carrying the strongest signal for positioning the cell division ring. This concurs with previous data showing that the MinD dimer binds to MinC inhibiting FtsZ ring formation. These results show that non-linear interactions of Min proteins are essential for producing the mid-cell positioning signal via the generation of second-order harmonic components in the time-dependent spatial protein distribution. PMID:29040283

Effects of frying oils' fatty acids profile on the formation of polar lipids components and their retention in French fries over deep-frying process.

PubMed

Li, Xiaodan; Li, Jinwei; Wang, Yong; Cao, Peirang; Liu, Yuanfa

2017-12-15

The effects of frying oils' fatty acids profile on the formation of polar components and their retention in French fries and corresponding deep-fried oils were investigated in the present study, using oils with different fatty acids composition. Our analysis showed that the total polar compounds (TPCs) content in French fries was only slightly lower than that in deep-fried oils, indicating that there was no significant difference considering the amounts of TPCs in French fries and deep-fried oils. Our further analysis showed that different polar components in TPCs distributed differently in deep-fried oils and oils extracted from French fries. Specifically, the level of oligomeric and dimeric triacylglycerols was higher in French fries while oxidized triacylglycerols and diacylglycerols content was higher in deep-fried oils. The different retention of TPCs components in French fries may be explained by their interactions with carbohydrates, which are shown to enhance with the increase of hydrophobic property. Chemometric analysis showed that no correlation between the polar compounds level and saturated fatty acids profile was observed. Meanwhile, the polar compounds content was highly correlated with the formation of trans-C18:1, and a highly positive association between polar compounds and C18:2 content was also observed in palm oil. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

Roopwani, Rahul; Buckner, Ira S

2011-10-14

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

Multiband Photometric and Spectroscopic Analysis of HV Cnc

NASA Astrophysics Data System (ADS)

Gökay, G.; Gürol, B.; Derman, E.

2013-11-01

In this paper, radial velocity and VI- and JHKS - (Two Micron All Sky Survey) band photometric data of the detached system HV Cnc have been analyzed. The primary component of HV Cnc, which is a member of the M67 cluster, is suspected to be either a blue straggler or turn-off star. The system is a single-lined spectroscopic binary and its light curve shows a total eclipse. Spectroscopic observations of the system revealed the third component, which shows contribution to the total light of the system. Light curve and radial velocity data have been analyzed using the Wilson-Devinney (W-D) code and JHKS filter definitions computed for the W-D code in this work. Our analysis shows that the mass and radius of the primary and secondary components are 1.31 M ⊙, 0.52 M ⊙, 1.87 R ⊙, and 0.48 R ⊙, respectively. All results are compared with previously published literature values and discussed.

MULTIBAND PHOTOMETRIC AND SPECTROSCOPIC ANALYSIS OF HV Cnc

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

Gökay, G.; Gürol, B.; Derman, E., E-mail: ggokay@science.ankara.edu.tr

2013-11-01

In this paper, radial velocity and VI- and JHK{sub S} - (Two Micron All Sky Survey) band photometric data of the detached system HV Cnc have been analyzed. The primary component of HV Cnc, which is a member of the M67 cluster, is suspected to be either a blue straggler or turn-off star. The system is a single-lined spectroscopic binary and its light curve shows a total eclipse. Spectroscopic observations of the system revealed the third component, which shows contribution to the total light of the system. Light curve and radial velocity data have been analyzed using the Wilson-Devinney (W-D)more » code and JHK{sub S} filter definitions computed for the W-D code in this work. Our analysis shows that the mass and radius of the primary and secondary components are 1.31 M {sub ☉}, 0.52 M {sub ☉}, 1.87 R {sub ☉}, and 0.48 R {sub ☉}, respectively. All results are compared with previously published literature values and discussed.« less

Schematic of Sample Analysis at Mars SAM Instrument

NASA Image and Video Library

2011-01-18

This schematic illustration for NASA Mars Science Laboratory Sample Analysis at Mars SAM instrument shows major components of the microwave-oven-size instrument, which will examine samples of Martian rocks, soil and atmosphere.

Regional prioritisation of flood risk in mountainous areas

NASA Astrophysics Data System (ADS)

Rogelis, M. C.; Werner, M.; Obregón, N.; Wright, G.

2015-07-01

A regional analysis of flood risk was carried out in the mountainous area surrounding the city of Bogotá (Colombia). Vulnerability at regional level was assessed on the basis of a principal component analysis carried out with variables recognised in literature to contribute to vulnerability; using watersheds as the unit of analysis. The area exposed was obtained from a simplified flood analysis at regional level to provide a mask where vulnerability variables were extracted. The vulnerability indicator obtained from the principal component analysis was combined with an existing susceptibility indicator, thus providing an index that allows the watersheds to be prioritised in support of flood risk management at regional level. Results show that the components of vulnerability can be expressed in terms of four constituent indicators; socio-economic fragility, which is composed of demography and lack of well-being; lack of resilience, which is composed of education, preparedness and response capacity, rescue capacity, social cohesion and participation; and physical exposure is composed of exposed infrastructure and exposed population. A sensitivity analysis shows that the classification of vulnerability is robust for watersheds with low and high values of the vulnerability indicator, while some watersheds with intermediate values of the indicator are sensitive to shifting between medium and high vulnerability. The complex interaction between vulnerability and hazard is evidenced in the case study. Environmental degradation in vulnerable watersheds shows the influence that vulnerability exerts on hazard and vice versa, thus establishing a cycle that builds up risk conditions.

A comparison of the usefulness of canonical analysis, principal components analysis, and band selection for extraction of features from TMS data for landcover analysis

NASA Technical Reports Server (NTRS)

Boyd, R. K.; Brumfield, J. O.; Campbell, W. J.

1984-01-01

Three feature extraction methods, canonical analysis (CA), principal component analysis (PCA), and band selection, have been applied to Thematic Mapper Simulator (TMS) data in order to evaluate the relative performance of the methods. The results obtained show that CA is capable of providing a transformation of TMS data which leads to better classification results than provided by all seven bands, by PCA, or by band selection. A second conclusion drawn from the study is that TMS bands 2, 3, 4, and 7 (thermal) are most important for landcover classification.

Lead isotope systematics of some Apollo 17 soils and some separated components from 76501

NASA Technical Reports Server (NTRS)

Church, S. E.; Tilton, G. R.

1974-01-01

Isotopic lead data from bulk samples of Apollo 17 soils were analyzed, and they define a chord in a concordia diagram, showing the presence of a component or components containing excess radiogenic lead with Pb-207/Pb-206 equal to about 1.32. The chord is distinctly different from the cataclysm chord, for which Pb-207/Pb-206 is approximately 1.45. Nitric acid analysis of plagioclase indicates lead ages of around 4.35 AE, in agreement with previous findings. Agglutinates from soil 76501,34 show loss of approximately 15% of lead.

Relationships between NIR spectra and sensory attributes of Thai commercial fish sauces.

PubMed

Ritthiruangdej, Pitiporn; Suwonsichon, Thongchai

2007-07-01

Twenty Thai commercial fish sauces were characterized by sensory descriptive analysis and near-infrared (NIR) spectroscopy. The main objectives were i) to investigate the relationships between sensory attributes and NIR spectra of samples and ii) to characterize the sensory characteristics of fish sauces based on NIR data. A generic descriptive analysis with 12 trained panels was used to characterize the sensory attributes. These attributes consisted of 15 descriptors: brown color, 5 aromatics (sweet, caramelized, fermented, fishy, and musty), 4 tastes (sweet, salty, bitter, and umami), 3 aftertastes (sweet, salty and bitter) and 2 flavors (caramelized and fishy). The results showed that Thai fish sauce samples exhibited significant differences in all of sensory attribute values (p < 0.05). NIR transflectance spectra were obtained from 1100 to 2500 nm. Prior to investigation of the relationships between sensory attributes and NIR spectra, principal component analysis (PCA) was applied to reduce the dimensionality of the spectral data from 622 wavelengths to two uncorrelated components (NIR1 and NIR2) which explained 92 and 7% of the total variation, respectively. NIR1 was highly correlated with the wavelength regions of 1100 - 1544, 1774 - 2062, 2092 - 2308, and 2358 - 2440 nm, while NIR2 was highly correlated with the wavelength regions of 1742 - 1764, 2066 - 2088, and 2312 - 2354 nm. Subsequently, the relationships among these two components and all sensory attributes were also investigated by PCA. The results showed that the first three principal components (PCs) named as fishy flavor component (PC1), sweet component (PC2) and bitterness component (PC3), respectively, explained a total of 66.86% of the variation. NIR1 was mainly correlated to the sensory attributes of fishy aromatic, fishy flavor and sweet aftertaste on PC1. In addition, the PCA using only the factor loadings of NIR1 and NIR2 could be used to classify samples into three groups which showed high, medium and low degrees of fishy aromatic, fishy flavor and sweet aftertaste.

Comparing sugar components of cereal and pseudocereal flour by GC-MS analysis.

PubMed

Ačanski, Marijana M; Vujić, Djura N

2014-02-15

Gas chromatography with mass spectrometry was used for carrying out a qualitative analysis of the ethanol soluble flour extract of different types of cereals bread wheat and spelt and pseudocereals (amaranth and buckwheat). TMSI (trimethylsilylimidazole) was used as a reagent for the derivatisation of carbohydrates into trimethylsilyl ethers. All samples were first defatted with hexane. (In our earlier investigations, hexane extracts were used for the analysis of fatty acid of lipid components.) Many components of pentoses, hexoses and disaccharides were identified using 73 and 217 Da mass and the Wiley Online Library search. The aim of this paper is not to identify and find new components, but to compare sugar components of tested samples of flour of cereals bread wheat and spelt and pseudocereals (amarnath and buckwheat). Results were analysed using descriptive statistics (dendrograms and PCA). The results show that this method can be used for making a distinction among different types of flour. Copyright © 2013 Elsevier Ltd. All rights reserved.

Orbital transfer rocket engine technology 7.5K-LB thrust rocket engine preliminary design

NASA Technical Reports Server (NTRS)

Harmon, T. J.; Roschak, E.

1993-01-01

A preliminary design of an advanced LOX/LH2 expander cycle rocket engine producing 7,500 lbf thrust for Orbital Transfer vehicle missions was completed. Engine system, component and turbomachinery analysis at both on design and off design conditions were completed. The preliminary design analysis results showed engine requirements and performance goals were met. Computer models are described and model outputs are presented. Engine system assembly layouts, component layouts and valve and control system analysis are presented. Major design technologies were identified and remaining issues and concerns were listed.

Use of multivariate statistics to identify unreliable data obtained using CASA.

PubMed

Martínez, Luis Becerril; Crispín, Rubén Huerta; Mendoza, Maximino Méndez; Gallegos, Oswaldo Hernández; Martínez, Andrés Aragón

2013-06-01

In order to identify unreliable data in a dataset of motility parameters obtained from a pilot study acquired by a veterinarian with experience in boar semen handling, but without experience in the operation of a computer assisted sperm analysis (CASA) system, a multivariate graphical and statistical analysis was performed. Sixteen boar semen samples were aliquoted then incubated with varying concentrations of progesterone from 0 to 3.33 µg/ml and analyzed in a CASA system. After standardization of the data, Chernoff faces were pictured for each measurement, and a principal component analysis (PCA) was used to reduce the dimensionality and pre-process the data before hierarchical clustering. The first twelve individual measurements showed abnormal features when Chernoff faces were drawn. PCA revealed that principal components 1 and 2 explained 63.08% of the variance in the dataset. Values of principal components for each individual measurement of semen samples were mapped to identify differences among treatment or among boars. Twelve individual measurements presented low values of principal component 1. Confidence ellipses on the map of principal components showed no statistically significant effects for treatment or boar. Hierarchical clustering realized on two first principal components produced three clusters. Cluster 1 contained evaluations of the two first samples in each treatment, each one of a different boar. With the exception of one individual measurement, all other measurements in cluster 1 were the same as observed in abnormal Chernoff faces. Unreliable data in cluster 1 are probably related to the operator inexperience with a CASA system. These findings could be used to objectively evaluate the skill level of an operator of a CASA system. This may be particularly useful in the quality control of semen analysis using CASA systems.

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

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

Ceulemans, R.; Impens, I.

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

Personality in domestic cats.

PubMed

Lee, Christina M; Ryan, Joseph J; Kreiner, David S

2007-02-01

Personality ratings of 196 cats were made by their owners using a 5-point Likert scale anchored by 1: not at all and 5: a great deal with 12 items: timid, friendly, curious, sociable, obedient, clever, protective, active, independent, aggressive, bad-tempered, and emotional. A principal components analysis with varimax rotation identified three intepretable components. Component I had high loadings by active, clever, curious, and sociable. Component II had high loadings by emotional, friendly, and protective, Component III by aggressive and bad-tempered, and Component IV by timid. Sex was not associated with any component, but age showed a weak negative correlation with Component I. Older animals were rated less social and curious than younger animals.

New insights into the folding of a β-sheet miniprotein in a reduced space of collective hydrogen bond variables: application to a hydrodynamic analysis of the folding flow.

PubMed

Kalgin, Igor V; Caflisch, Amedeo; Chekmarev, Sergei F; Karplus, Martin

2013-05-23

A new analysis of the 20 μs equilibrium folding/unfolding molecular dynamics simulations of the three-stranded antiparallel β-sheet miniprotein (beta3s) in implicit solvent is presented. The conformation space is reduced in dimensionality by introduction of linear combinations of hydrogen bond distances as the collective variables making use of a specially adapted principal component analysis (PCA); i.e., to make structured conformations more pronounced, only the formed bonds are included in determining the principal components. It is shown that a three-dimensional (3D) subspace gives a meaningful representation of the folding behavior. The first component, to which eight native hydrogen bonds make the major contribution (four in each beta hairpin), is found to play the role of the reaction coordinate for the overall folding process, while the second and third components distinguish the structured conformations. The representative points of the trajectory in the 3D space are grouped into conformational clusters that correspond to locally stable conformations of beta3s identified in earlier work. A simplified kinetic network based on the three components is constructed, and it is complemented by a hydrodynamic analysis. The latter, making use of "passive tracers" in 3D space, indicates that the folding flow is much more complex than suggested by the kinetic network. A 2D representation of streamlines shows there are vortices which correspond to repeated local rearrangement, not only around minima of the free energy surface but also in flat regions between minima. The vortices revealed by the hydrodynamic analysis are apparently not evident in folding pathways generated by transition-path sampling. Making use of the fact that the values of the collective hydrogen bond variables are linearly related to the Cartesian coordinate space, the RMSD between clusters is determined. Interestingly, the transition rates show an approximate exponential correlation with distance in the hydrogen bond subspace. Comparison with the many published studies shows good agreement with the present analysis for the parts that can be compared, supporting the robust character of our understanding of this "hydrogen atom" of protein folding.

Quantitative Evaluation for Differentiating Malignant and Benign Thyroid Nodules Using Histogram Analysis of Grayscale Sonograms.

PubMed

Nam, Se Jin; Yoo, Jaeheung; Lee, Hye Sun; Kim, Eun-Kyung; Moon, Hee Jung; Yoon, Jung Hyun; Kwak, Jin Young

2016-04-01

To evaluate the diagnostic value of histogram analysis using grayscale sonograms for differentiation of malignant and benign thyroid nodules. From July 2013 through October 2013, 579 nodules in 563 patients who had undergone ultrasound-guided fine-needle aspiration were included. For the grayscale histogram analysis, pixel echogenicity values in regions of interest were measured as 0 to 255 (0, black; 255, white) with in-house software. Five parameters (mean, skewness, kurtosis, standard deviation, and entropy) were obtained for each thyroid nodule. With principal component analysis, an index was derived. Diagnostic performance rates for the 5 histogram parameters and the principal component analysis index were calculated. A total of 563 patients were included in the study (mean age ± SD, 50.3 ± 12.3 years;range, 15-79 years). Of the 579 nodules, 431 were benign, and 148 were malignant. Among the 5 parameters and the principal component analysis index, the standard deviation (75.546 ± 14.153 versus 62.761 ± 16.01; P < .001), kurtosis (3.898 ± 2.652 versus 6.251 ± 9.102; P < .001), entropy (0.16 ± 0.135 versus 0.239 ± 0.185; P < .001), and principal component analysis index (-0.386±0.774 versus 0.134 ± 0.889; P < .001) were significantly different between the malignant and benign nodules. With the calculated cutoff values, the areas under the curve were 0.681 (95% confidence interval, 0.643-0.721) for standard deviation, 0.661 (0.620-0.703) for principal component analysis index, 0.651 (0.607-0.691) for kurtosis, 0.638 (0.596-0.681) for entropy, and 0.606 (0.563-0.647) for skewness. The subjective analysis of grayscale sonograms by radiologists alone showed an area under the curve of 0.861 (0.833-0.888). Grayscale histogram analysis was feasible for differentiating malignant and benign thyroid nodules but did not show better diagnostic performance than subjective analysis performed by radiologists. Further technical advances will be needed to objectify interpretations of thyroid grayscale sonograms. © 2016 by the American Institute of Ultrasound in Medicine.

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

Just a fad? Gamification in health and fitness apps.

PubMed

Lister, Cameron; West, Joshua H; Cannon, Ben; Sax, Tyler; Brodegard, David

2014-08-04

Gamification has been a predominant focus of the health app industry in recent years. However, to our knowledge, there has yet to be a review of gamification elements in relation to health behavior constructs, or insight into the true proliferation of gamification in health apps. The objective of this study was to identify the extent to which gamification is used in health apps, and analyze gamification of health and fitness apps as a potential component of influence on a consumer's health behavior. An analysis of health and fitness apps related to physical activity and diet was conducted among apps in the Apple App Store in the winter of 2014. This analysis reviewed a sample of 132 apps for the 10 effective game elements, the 6 core components of health gamification, and 13 core health behavior constructs. A regression analysis was conducted in order to measure the correlation between health behavior constructs, gamification components, and effective game elements. This review of the most popular apps showed widespread use of gamification principles, but low adherence to any professional guidelines or industry standard. Regression analysis showed that game elements were associated with gamification (P<.001). Behavioral theory was associated with gamification (P<.05), but not game elements, and upon further analysis gamification was only associated with composite motivational behavior scores (P<.001), and not capacity or opportunity/trigger. This research, to our knowledge, represents the first comprehensive review of gamification use in health and fitness apps, and the potential to impact health behavior. The results show that use of gamification in health and fitness apps has become immensely popular, as evidenced by the number of apps found in the Apple App Store containing at least some components of gamification. This shows a lack of integrating important elements of behavioral theory from the app industry, which can potentially impact the efficacy of gamification apps to change behavior. Apps represent a very promising, burgeoning market and landscape in which to disseminate health behavior change interventions. Initial results show an abundant use of gamification in health and fitness apps, which necessitates the in-depth study and evaluation of the potential of gamification to change health behaviors.

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.

[Does carbonate originate from carbonate-calcium crystal component of the human urinary calculus?].

PubMed

Yuzawa, Masayuki; Nakano, Kazuhiko; Kumamaru, Takatoshi; Nukui, Akinori; Ikeda, Hitoshi; Suzuki, Kazumi; Kobayashi, Minoru; Sugaya, Yasuhiro; Morita, Tatsuo

2008-09-01

It gives important information in selecting the appropriate treatment for urolithiasis to confirm the component of urinary calculus. Presently component analysis of the urinary calculus is generally performed by infrared spectroscopy which is employed by companies providing laboratory testing services in Japan. The infrared spectroscopy determines the molecular components from the absorption spectra in consequence of atomic vibrations. It has the drawback that an accurate crystal structure cannot be analyzed compared with the X-ray diffraction method which analyzes the crystal constituent based on the diffraction of X-rays on crystal lattice. The components of the urinary calculus including carbonate are carbonate apatite and calcium carbonate such as calcite. Although the latter is reported to be very rare component in human urinary calculus, the results by infrared spectroscopy often show that calcium carbonate is included in calculus. The infrared spectroscopy can confirm the existence of carbonate but cannot determine whether carbonate is originated from carbonate apatite or calcium carbonate. Thus, it is not clear whether calcium carbonate is included in human urinary calculus component in Japan. In this study, we examined human urinary calculus including carbonate by use of X-ray structural analysis in order to elucidate the origin of carbonate in human urinary calculus. We examined 17 human calculi which were reported to contain calcium carbonate by infrared spectroscopy performed in the clinical laboratory. Fifteen calculi were obtained from urinary tract, and two were from gall bladder. The stones were analyzed by X-ray powder method after crushed finely. The reports from the clinical laboratory showed that all urinary culculi consisted of calcium carbonate and calcium phosphate, while the gallstones consisted of calcium carbonate. But the components of all urinary calculi were revealed to be carbonate apatite by X-ray diffraction. The components of gallstones were shown to be calcium carbonate (one calcite and the other aragonite) not only by infrared spectroscopy but by X-ray diffraction. It was shown that component analysis of the calculus could be more accurately performed by adding X-ray diffraction method to infrared spectroscopy. It was shown that calcium carbonate existed in a gallstone. As for the carbonate in human urinary calculi, present study showed that it was not calcium carbonate origin but carbonate apatite origin.

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.

Rapid Characterization of Components in Bolbostemma paniculatum by UPLC/LTQ-Orbitrap MSn Analysis and Multivariate Statistical Analysis for Herb Discrimination.

PubMed

Zeng, Yanling; Lu, Yang; Chen, Zhao; Tan, Jiawei; Bai, Jie; Li, Pengyue; Wang, Zhixin; Du, Shouying

2018-05-11

Bolbostemma paniculatum is a traditional Chinese medicine (TCM) showed various therapeutic effects. Owing to its complex chemical composition, few investigations have acquired a comprehensive cognition for the chemical profiles of this herb and explicated the differences between samples collected from different places. In this study, a strategy based on UPLC tandem LTQ-Orbitrap MS n was established for characterizing chemical components of B. paniculatum . Through a systematic identification strategy, a total of 60 components in B. paniculatum were rapidly separated in 30 min and identified. Then based on peak intensities of all the characterized components, principle component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to classify 18 batches of B. paniculatum into four groups, which were highly consistent with the four climate types of their original places. And five compounds were finally screened out as chemical markers to discriminate the internal quality of B. paniculatum . As the first study to systematically characterize the chemical components of B. paniculatum by UPLC-MS n , the above results could offer essential data for its pharmacological research. And the current strategy could provide useful reference for future investigations on discovery of important chemical constituents in TCM, as well as establishment of quality control and evaluation method.

Application of principal component analysis to distinguish patients with schizophrenia from healthy controls based on fractional anisotropy measurements.

PubMed

Caprihan, A; Pearlson, G D; Calhoun, V D

2008-08-15

Principal component analysis (PCA) is often used to reduce the dimension of data before applying more sophisticated data analysis methods such as non-linear classification algorithms or independent component analysis. This practice is based on selecting components corresponding to the largest eigenvalues. If the ultimate goal is separation of data in two groups, then these set of components need not have the most discriminatory power. We measured the distance between two such populations using Mahalanobis distance and chose the eigenvectors to maximize it, a modified PCA method, which we call the discriminant PCA (DPCA). DPCA was applied to diffusion tensor-based fractional anisotropy images to distinguish age-matched schizophrenia subjects from healthy controls. The performance of the proposed method was evaluated by the one-leave-out method. We show that for this fractional anisotropy data set, the classification error with 60 components was close to the minimum error and that the Mahalanobis distance was twice as large with DPCA, than with PCA. Finally, by masking the discriminant function with the white matter tracts of the Johns Hopkins University atlas, we identified left superior longitudinal fasciculus as the tract which gave the least classification error. In addition, with six optimally chosen tracts the classification error was zero.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults.

PubMed

Azcárate, T; Mendoza, B

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.

2017-09-01

We performed a study of the systolic and diastolic arterial blood pressure behavior under natural variables such as the atmospheric pressure and the horizontal geomagnetic field component. We worked with a group of eight adult hypertensive volunteers, four men and four women, with ages between 18 and 27 years in Mexico City during a geomagnetic storm in 2014. The data was divided by gender, age, and day/night cycle. We studied the time series using three methods: correlations, bivariate analysis, and superposed epoch (within a window of 2 days around the day of occurrence of a geomagnetic storm) analysis, between the systolic and diastolic blood pressure and the natural variables. The correlation analysis indicated a correlation between the systolic and diastolic blood pressure and the atmospheric pressure and the horizontal geomagnetic field component, being the largest during the night. Furthermore, the correlation and bivariate analyses showed that the largest correlations are between the systolic and diastolic blood pressure and the horizontal geomagnetic field component. Finally, the superposed epoch analysis showed that the largest number of significant changes in the blood pressure under the influence of geomagnetic field occurred in the systolic blood pressure for men.

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Efficient principal component analysis for multivariate 3D voxel-based mapping of brain functional imaging data sets as applied to FDG-PET and normal aging.

PubMed

Zuendorf, Gerhard; Kerrouche, Nacer; Herholz, Karl; Baron, Jean-Claude

2003-01-01

Principal component analysis (PCA) is a well-known technique for reduction of dimensionality of functional imaging data. PCA can be looked at as the projection of the original images onto a new orthogonal coordinate system with lower dimensions. The new axes explain the variance in the images in decreasing order of importance, showing correlations between brain regions. We used an efficient, stable and analytical method to work out the PCA of Positron Emission Tomography (PET) images of 74 normal subjects using [(18)F]fluoro-2-deoxy-D-glucose (FDG) as a tracer. Principal components (PCs) and their relation to age effects were investigated. Correlations between the projections of the images on the new axes and the age of the subjects were carried out. The first two PCs could be identified as being the only PCs significantly correlated to age. The first principal component, which explained 10% of the data set variance, was reduced only in subjects of age 55 or older and was related to loss of signal in and adjacent to ventricles and basal cisterns, reflecting expected age-related brain atrophy with enlarging CSF spaces. The second principal component, which accounted for 8% of the total variance, had high loadings from prefrontal, posterior parietal and posterior cingulate cortices and showed the strongest correlation with age (r = -0.56), entirely consistent with previously documented age-related declines in brain glucose utilization. Thus, our method showed that the effect of aging on brain metabolism has at least two independent dimensions. This method should have widespread applications in multivariate analysis of brain functional images. Copyright 2002 Wiley-Liss, Inc.

Computational Fatigue Life Analysis of Carbon Fiber Laminate

NASA Astrophysics Data System (ADS)

Shastry, Shrimukhi G.; Chandrashekara, C. V., Dr.

2018-02-01

In the present scenario, many traditional materials are being replaced by composite materials for its light weight and high strength properties. Industries like automotive industry, aerospace industry etc., are some of the examples which uses composite materials for most of its components. Replacing of components which are subjected to static load or impact load are less challenging compared to components which are subjected to dynamic loading. Replacing the components made up of composite materials demands many stages of parametric study. One such parametric study is the fatigue analysis of composite material. This paper focuses on the fatigue life analysis of the composite material by using computational techniques. A composite plate is considered for the study which has a hole at the center. The analysis is carried on (0°/90°/90°/90°/90°)s laminate sequence and (45°/-45°)2s laminate sequence by using a computer script. The life cycles for both the lay-up sequence are compared with each other. It is observed that, for the same material and geometry of the component, cross ply laminates show better fatigue life than that of angled ply laminates.

Sensory characteristics and consumer preference for chicken meat in Guinea.

PubMed

Sow, T M A; Grongnet, J F

2010-10-01

This study identified the sensory characteristics and consumer preference for chicken meat in Guinea. Five chicken samples [live village chicken, live broiler, live spent laying hen, ready-to-cook broiler, and ready-to-cook broiler (imported)] bought from different locations were assessed by 10 trained panelists using 19 sensory attributes. The ANOVA results showed that 3 chicken appearance attributes (brown, yellow, and white), 5 chicken odor attributes (oily, intense, medicine smell, roasted, and mouth persistent), 3 chicken flavor attributes (sweet, bitter, and astringent), and 8 chicken texture attributes (firm, tender, juicy, chew, smooth, springy, hard, and fibrous) were significantly discriminating between the chicken samples (P<0.05). Principal component analysis of the sensory data showed that the first 2 principal components explained 84% of the sensory data variance. The principal component analysis results showed that the live village chicken, the live spent laying hen, and the ready-to-cook broiler (imported) were very well represented and clearly distinguished from the live broiler and the ready-to-cook broiler. One hundred twenty consumers expressed their preferences for the chicken samples using a 5-point Likert scale. The hierarchical cluster analysis of the preference data identified 4 homogenous consumer clusters. The hierarchical cluster analysis results showed that the live village chicken was the most preferred chicken sample, whereas the ready-to-cook broiler was the least preferred one. The partial least squares regression (PLSR) type 1 showed that 72% of the sensory data for the first 2 principal components explained 83% of the chicken preference. The PLSR1 identified that the sensory characteristics juicy, oily, sweet, hard, mouth persistent, and yellow were the most relevant sensory drivers of the Guinean chicken preference. The PLSR2 (with multiple responses) identified the relationship between the chicken samples, their sensory attributes, and the consumer clusters. Our results showed that there was not a chicken category that was exclusively preferred from the other chicken samples and therefore highlight the existence of place for development of all chicken categories in the local market.

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.

Continuous inventories and the components of change

Treesearch

Frnacis A. Roesch

2004-01-01

The consequences of conducting a continuous inventory that utilizes measurements on overlapping temporal intervals of varying length on compatible estimation systems for the components of growth are explored. The time interpenetrating sample design of the USDA Forest Service Forest Inventory and Analysis Program is used as an example. I show why estimation of the...

Response of the small hive beetle (Aethina tumida) to a blend of chemicals identified from honeybee (Apis mellifera) volatiles

USDA-ARS?s Scientific Manuscript database

Coupled gas chromatographic-electroantennographic detection (GC-EAD) analyses of Super Q collected worker honey bee volatiles revealed several components that elicited antennal responses by the small hive beetle Aethina tumida. However, GC-MS analysis showed that eight of these EAD-active components...

Proteome comparison for discrimination between honeydew and floral honeys from botanical species Mimosa scabrella Bentham by principal component analysis.

PubMed

Azevedo, Mônia Stremel; Valentim-Neto, Pedro Alexandre; Seraglio, Siluana Katia Tischer; da Luz, Cynthia Fernandes Pinto; Arisi, Ana Carolina Maisonnave; Costa, Ana Carolina Oliveira

2017-10-01

Due to the increasing valuation and appreciation of honeydew honey in many European countries and also to existing contamination among different types of honeys, authentication is an important aspect of quality control with regard to guaranteeing the origin in terms of source (honeydew or floral) and needs to be determined. Furthermore, proteins are minor components of the honey, despite the importance of their physiological effects, and can differ according to the source of the honey. In this context, the aims of this study were to carry out protein extraction from honeydew and floral honeys and to discriminate these honeys from the same botanical species, Mimosa scabrella Bentham, through proteome comparison using two-dimensional gel electrophoresis and principal component analysis. The results showed that the proteome profile and principal component analysis can be a useful tool for discrimination between these types of honey using matched proteins (45 matched spots). Also, the proteome profile showed 160 protein spots in honeydew honey and 84 spots in the floral honey. The protein profile can be a differential characteristic of this type of honey, in view of the importance of proteins as bioactive compounds in honey. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Component-/structure-dependent elasticity of solid electrolyte interphase layer in Li-ion batteries: Experimental and computational studies

NASA Astrophysics Data System (ADS)

Shin, Hosop; Park, Jonghyun; Han, Sangwoo; Sastry, Ann Marie; Lu, Wei

2015-03-01

The mechanical instability of the Solid Electrolyte Interphase (SEI) layer in lithium ion (Li-ion) batteries causes significant side reactions resulting in Li-ion consumption and cell impedance rise by forming further SEI layers, which eventually leads to battery capacity fade and power fade. In this paper, the composition-/structure-dependent elasticity of the SEI layer is investigated via Atomic Force Microscopy (AFM) measurements coupled with X-ray Photoelectron Spectroscopy (XPS) analysis, and atomistic calculations. It is observed that the inner layer is stiffer than the outer layer. The measured Young's moduli are mostly in the range of 0.2-4.5 GPa, while some values above 80 GPa are also observed. This wide variation of the observed elastic modulus is elucidated by atomistic calculations with a focus on chemical and structural analysis. The numerical analysis shows the Young's moduli range from 2.4 GPa to 58.1 GPa in the order of the polymeric, organic, and amorphous inorganic components. The crystalline inorganic component (LiF) shows the highest value (135.3 GPa) among the SEI species. This quantitative observation on the elasticity of individual components of the SEI layer must be essential to analyzing the mechanical behavior of the SEI layer and to optimizing and controlling it.

[Determination and principal component analysis of mineral elements based on ICP-OES in Nitraria roborowskii fruits from different regions].

PubMed

Yuan, Yuan-Yuan; Zhou, Yu-Bi; Sun, Jing; Deng, Juan; Bai, Ying; Wang, Jie; Lu, Xue-Feng

2017-06-01

The content of elements in fifteen different regions of Nitraria roborowskii samples were determined by inductively coupled plasma-atomic emission spectrometry(ICP-OES), and its elemental characteristics were analyzed by principal component analysis. The results indicated that 18 mineral elements were detected in N. roborowskii of which V cannot be detected. In addition, contents of Na, K and Ca showed high concentration. Ti showed maximum content variance, while K is minimum. Four principal components were gained from the original data. The cumulative variance contribution rate is 81.542% and the variance contribution of the first principal component was 44.997%, indicating that Cr, Fe, P and Ca were the characteristic elements of N. roborowskii.Thus, the established method was simple, precise and can be used for determination of mineral elements in N.roborowskii Kom. fruits. The elemental distribution characteristics among N.roborowskii fruits are related to geographical origins which were clearly revealed by PCA. All the results will provide good basis for comprehensive utilization of N.roborowskii. Copyright© by the Chinese Pharmaceutical Association.

Factor structure of DSM-IV criteria for obsessive compulsive personality disorder in patients with binge eating disorder.

PubMed

Grilo, C M

2004-01-01

To examine the factor structure of DSM-IV criteria for obsessive compulsive personality disorder (OCPD) in patients with binge eating disorder (BED). Two hundred and eleven consecutive out-patients with axis I diagnoses of BED were reliably assessed with semi-structured diagnostic interviews. The eight criteria for the OCPD diagnosis were examined with reliability and correlational analyses. Exploratory factor analysis was performed to identify potential components. Cronbach's coefficient alpha for the OCPD criteria was 0.77. Principal components factor analysis with varimax rotation revealed a three-factor solution (rigidity, perfectionism, and miserliness), which accounted for 65% of variance. The DSM-IV criteria for OCPD showed good internal consistency. Exploratory factor analysis, however, revealed three components that may reflect distinct interpersonal, intrapersonal (cognitive), and behavioral features.

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.

Dynamic competitive probabilistic principal components analysis.

PubMed

López-Rubio, Ezequiel; Ortiz-DE-Lazcano-Lobato, Juan Miguel

2009-04-01

We present a new neural model which extends the classical competitive learning (CL) by performing a Probabilistic Principal Components Analysis (PPCA) at each neuron. The model also has the ability to learn the number of basis vectors required to represent the principal directions of each cluster, so it overcomes a drawback of most local PCA models, where the dimensionality of a cluster must be fixed a priori. Experimental results are presented to show the performance of the network with multispectral image data.

Source Analysis of the Crandall Canyon, Utah, Mine Collapse

DOE PAGES

Dreger, D. S.; Ford, S. R.; Walter, W. R.

2008-07-11

Analysis of seismograms from a magnitude 3.9 seismic event on August 6, 2007 in central Utah reveals an anomalous radiation pattern that is contrary to that expected for a tectonic earthquake, and which is dominated by an implosive component. The results show the seismic event is best modeled as a shallow underground collapse. Interestingly, large transverse surface waves require a smaller additional non-collapse source component that represents either faulting in the rocks above the mine workings or deformation of the medium surrounding the mine.

CARES/Life Software for Designing More Reliable Ceramic Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Baker, Eric H.

1997-01-01

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion, and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CAPES/Life software eases this task by providing a tool to optimize the design and manufacture of brittle material components using probabilistic reliability analysis techniques. Probabilistic component design involves predicting the probability of failure for a thermomechanically loaded component from specimen rupture data. Typically, these experiments are performed using many simple geometry flexural or tensile test specimens. A static, dynamic, or cyclic load is applied to each specimen until fracture. Statistical strength and SCG (fatigue) parameters are then determined from these data. Using these parameters and the results obtained from a finite element analysis, the time-dependent reliability for a complex component geometry and loading is then predicted. Appropriate design changes are made until an acceptable probability of failure has been reached.

Analysis of amyloid fibrils in the cheetah (Acinonyx jubatus).

PubMed

Bergström, Joakim; Ueda, Mitsuharu; Une, Yumi; Sun, Xuguo; Misumi, Shogo; Shoji, Shozo; Ando, Yukio

2006-06-01

Recently, a high prevalence of amyloid A (AA) amyloidosis has been documented among captive cheetahs worldwide. Biochemical analysis of amyloid fibrils extracted from the liver of a Japanese captive cheetah unequivocally showed that protein AA was the main fibril constituent. Further characterization of the AA fibril components by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blot analysis revealed three main protein AA bands with approximate molecular weights of 8, 10 and 12 kDa. Mass spectrometry analysis of the 12-kDa component observed in SDS-PAGE and Western blotting confirmed the molecular weight of a 12,381-Da peak. Our finding of a 12-kDa protein AA component provides evidence that the cheetah SAA sequence is longer than the previously reported 90 amino acid residues (approximately 10 kDa), and hence SAA is part of the amyloid fibril.

Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures.

PubMed

Bouhlel, Jihéne; Jouan-Rimbaud Bouveresse, Delphine; Abouelkaram, Said; Baéza, Elisabeth; Jondreville, Catherine; Travel, Angélique; Ratel, Jérémy; Engel, Erwan; Rutledge, Douglas N

2018-02-01

The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not highlight the most influencing variables for each separation, whereas the ICA Loadings highlighted the same variables as did CCA. This study shows the potential of CCA for the extraction of pertinent information from a data matrix, using a procedure based on an original optimisation criterion, to produce results that are complementary, and in some cases may be superior, to those of PCA and ICA. Copyright © 2017 Elsevier B.V. All rights reserved.

Natural selection among Kinnaura of the Himalayan highland: A comparative analysis with other Indian and Himalayan populations

PubMed Central

Gautam, Rajesh K.; Kapoor, Anup K.; Kshatriya, G. K.

2009-01-01

The present investigation on fertility and mortality differential among Kinnaura of the Himalayan highland is based on data collected from 160 post-menopausal women belonging to the middle and high altitude region of Kinnaur district of Himachal Pradesh (Indian Himalayas). Selection potential based on differential fertility and mortality was computed for middle-and high-altitude women. Irrespective of the methodology, the total index of selection was found to be highest among middle-altitude women (0.386) as compared with high-altitude (0.370) women, whereas for the total population it is estimated to be 0.384. It was found that the Kinnaura of the Himalayan highland showing moderate index of total selection and relative contribution of the mortality component (Im) to the index of total selection is higher than the corresponding fertility component (If). The analysis of embryonic and post-natal mortality components shows that the post-natal mortality components are higher in comparison with the embryonic mortality components among highlanders and needs special intervention and health care. The present findings are compared with other Indian tribes as well as non-tribes of the Himalayan region and other parts of the country. It reveals that this index among Kinnaura is moderate than the other population groups; among the Himalayan population, the highest was reported for Galong (It = 1.07) of Arunachal, whereas the lowest was reported from Ahom (It = 0.218) of Manipur. The correlation and regression analysis between total index of selection (It) and fertility (If) and mortality (Im) components for pooled data of populations of the Indian Himalayan states show that If and Im account for 21.6 and 29.1% variability, respectively. In Crow's total index of selection (It) along with strong association, which is significant at the 1% level, this indicates that mortality plays a greater role in natural selection in comparison with fertility among populations of the Indian Himalayas. PMID:21088718

Combinations of NIR, Raman spectroscopy and physicochemical measurements for improved monitoring of solvent extraction processes using hierarchical multivariate analysis models

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

Nee, K.; Bryan, S.; Levitskaia, T.

The reliability of chemical processes can be greatly improved by implementing inline monitoring systems. Combining multivariate analysis with non-destructive sensors can enhance the process without interfering with the operation. Here, we present here hierarchical models using both principal component analysis and partial least square analysis developed for different chemical components representative of solvent extraction process streams. A training set of 380 samples and an external validation set of 95 samples were prepared and Near infrared and Raman spectral data as well as conductivity under variable temperature conditions were collected. The results from the models indicate that careful selection of themore » spectral range is important. By compressing the data through Principal Component Analysis (PCA), we lower the rank of the data set to its most dominant features while maintaining the key principal components to be used in the regression analysis. Within the studied data set, concentration of five chemical components were modeled; total nitrate (NO 3 -), total acid (H +), neodymium (Nd 3+), sodium (Na +), and ionic strength (I.S.). The best overall model prediction for each of the species studied used a combined data set comprised of complementary techniques including NIR, Raman, and conductivity. Finally, our study shows that chemometric models are powerful but requires significant amount of carefully analyzed data to capture variations in the chemistry.« less

Combinations of NIR, Raman spectroscopy and physicochemical measurements for improved monitoring of solvent extraction processes using hierarchical multivariate analysis models

DOE PAGES

Nee, K.; Bryan, S.; Levitskaia, T.; ...

2017-12-28

The reliability of chemical processes can be greatly improved by implementing inline monitoring systems. Combining multivariate analysis with non-destructive sensors can enhance the process without interfering with the operation. Here, we present here hierarchical models using both principal component analysis and partial least square analysis developed for different chemical components representative of solvent extraction process streams. A training set of 380 samples and an external validation set of 95 samples were prepared and Near infrared and Raman spectral data as well as conductivity under variable temperature conditions were collected. The results from the models indicate that careful selection of themore » spectral range is important. By compressing the data through Principal Component Analysis (PCA), we lower the rank of the data set to its most dominant features while maintaining the key principal components to be used in the regression analysis. Within the studied data set, concentration of five chemical components were modeled; total nitrate (NO 3 -), total acid (H +), neodymium (Nd 3+), sodium (Na +), and ionic strength (I.S.). The best overall model prediction for each of the species studied used a combined data set comprised of complementary techniques including NIR, Raman, and conductivity. Finally, our study shows that chemometric models are powerful but requires significant amount of carefully analyzed data to capture variations in the chemistry.« less

Identification of faulty sensor using relative partial decomposition via independent component analysis

NASA Astrophysics Data System (ADS)

Wang, Z.; Quek, S. T.

2015-07-01

Performance of any structural health monitoring algorithm relies heavily on good measurement data. Hence, it is necessary to employ robust faulty sensor detection approaches to isolate sensors with abnormal behaviour and exclude the highly inaccurate data in the subsequent analysis. The independent component analysis (ICA) is implemented to detect the presence of sensors showing abnormal behaviour. A normalized form of the relative partial decomposition contribution (rPDC) is proposed to identify the faulty sensor. Both additive and multiplicative types of faults are addressed and the detectability illustrated using a numerical and an experimental example. An empirical method to establish control limits for detecting and identifying the type of fault is also proposed. The results show the effectiveness of the ICA and rPDC method in identifying faulty sensor assuming that baseline cases are available.

A first application of independent component analysis to extracting structure from stock returns.

PubMed

Back, A D; Weigend, A S

1997-08-01

This paper explores the application of a signal processing technique known as independent component analysis (ICA) or blind source separation to multivariate financial time series such as a portfolio of stocks. The key idea of ICA is to linearly map the observed multivariate time series into a new space of statistically independent components (ICs). We apply ICA to three years of daily returns of the 28 largest Japanese stocks and compare the results with those obtained using principal component analysis. The results indicate that the estimated ICs fall into two categories, (i) infrequent large shocks (responsible for the major changes in the stock prices), and (ii) frequent smaller fluctuations (contributing little to the overall level of the stocks). We show that the overall stock price can be reconstructed surprisingly well by using a small number of thresholded weighted ICs. In contrast, when using shocks derived from principal components instead of independent components, the reconstructed price is less similar to the original one. ICA is shown to be a potentially powerful method of analyzing and understanding driving mechanisms in financial time series. The application to portfolio optimization is described in Chin and Weigend (1998).

Quality of life improvements among cancer patients in remission following the consumption of Agaricus blazei Murill mushroom extract.

PubMed

Ohno, Satoshi; Sumiyoshi, Yoshiteru; Hashine, Katsuyoshi; Shirato, Akitomi; Kyo, Satoru; Inoue, Masaki

2013-10-01

The aim of this preliminary clinical study was to assess if the daily intake of Agaricus blazei Murill (ABM) granulated powder (SSI Co., Ltd., Tokyo, Japan) for 6 months improved the quality of life (QOL) in cancer patients in remission. Open study. Subjects diurnally took 1 (1.8 g; N=23), 2 (3.6 g; N=22), or 3 (5.4 g; N=22) packs/day orally for 6 months. The SF-8 Health Survey questionnaire was used to evaluate the QOL. The differences between the SF-8 baseline scores at the time of entry and 6-months after ABM treatment were evaluated. The results showed a significant improvement in QOL in both physical and mental components. More specifically, QOL effects of ABM in different genders showed males improved physical components, while females improved only mental components. QOL effects in the different age groups showed that ages 65 and under improved mental components, while ages 66 and older improved physical components. Furthermore, with respect to optimal dose effects of ABM with respect to QOL improvement, two packs per day for 6 months showed improvements in both physical and mental components. This preliminary longitudinal clinical study demonstrated that daily intake of ABM appears to improve both physical and mental components based on SF-8 qualimetric analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Sterols as biomarkers in the surface microlayer of the estuarine areas.

PubMed

Alsalahi, Murad Ali; Latif, Mohd Talib; Ali, Masni Mohd; Dominick, Doreena; Khan, Md Firoz; Mustaffa, Nur Ili Hamizah; Nadzir, Mohd Shahrul Mohd; Nasher, Essam; Zakaria, Mohamad Pauzi

2015-04-15

This study aims to determine the concentration of sterols used as biomarkers in the surface microlayer (SML) in estuarine areas of the Selangor River, Malaysia. Samples were collected during different seasons through the use of a rotation drum. The analysis of sterols was performed using gas chromatography equipped with a flame ionisation detector (GC-FID). The results showed that the concentrations of total sterols in the SML ranged from 107.06 to 505.55 ng L(-1). The total sterol concentration was found to be higher in the wet season. Cholesterol was found to be the most abundant sterols component in the SML. The diagnostic ratios of sterols show the influence of natural sources and waste on the contribution of sterols in the SML. Further analysis, using principal component analysis (PCA), showed distinct inputs of sterols derived from human activity (40.58%), terrigenous and plant inputs (22.59%) as well as phytoplankton and marine inputs (17.35%). Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Estimation of low back moments from video analysis: a validation study.

PubMed

Coenen, Pieter; Kingma, Idsart; Boot, Cécile R L; Faber, Gert S; Xu, Xu; Bongers, Paulien M; van Dieën, Jaap H

2011-09-02

This study aimed to develop, compare and validate two versions of a video analysis method for assessment of low back moments during occupational lifting tasks since for epidemiological studies and ergonomic practice relatively cheap and easily applicable methods to assess low back loads are needed. Ten healthy subjects participated in a protocol comprising 12 lifting conditions. Low back moments were assessed using two variants of a video analysis method and a lab-based reference method. Repeated measures ANOVAs showed no overall differences in peak moments between the two versions of the video analysis method and the reference method. However, two conditions showed a minor overestimation of one of the video analysis method moments. Standard deviations were considerable suggesting that errors in the video analysis were random. Furthermore, there was a small underestimation of dynamic components and overestimation of the static components of the moments. Intraclass correlations coefficients for peak moments showed high correspondence (>0.85) of the video analyses with the reference method. It is concluded that, when a sufficient number of measurements can be taken, the video analysis method for assessment of low back loads during lifting tasks provides valid estimates of low back moments in ergonomic practice and epidemiological studies for lifts up to a moderate level of asymmetry. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

Nguyen, Phuong H

2007-05-15

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

My Body Looks Like That Girl’s: Body Mass Index Modulates Brain Activity during Body Image Self-Reflection among Young Women

PubMed Central

Wen, Xin; She, Ying; Vinke, Petra Corianne; Chen, Hong

2016-01-01

Body image distress or body dissatisfaction is one of the most common consequences of obesity and overweight. We investigated the neural bases of body image processing in overweight and average weight young women to understand whether brain regions that were previously found to be involved in processing self-reflective, perspective and affective components of body image would show different activation between two groups. Thirteen overweight (O-W group, age = 20.31±1.70 years) and thirteen average weight (A-W group, age = 20.15±1.62 years) young women underwent functional magnetic resonance imaging while performing a body image self-reflection task. Among both groups, whole-brain analysis revealed activations of a brain network related to perceptive and affective components of body image processing. ROI analysis showed a main effect of group in ACC as well as a group by condition interaction within bilateral EBA, bilateral FBA, right IPL, bilateral DLPFC, left amygdala and left MPFC. For the A-W group, simple effect analysis revealed stronger activations in Thin-Control compared to Fat-Control condition within regions related to perceptive (including bilateral EBA, bilateral FBA, right IPL) and affective components of body image processing (including bilateral DLPFC, left amygdala), as well as self-reference (left MPFC). The O-W group only showed stronger activations in Fat-Control than in Thin-Control condition within regions related to the perceptive component of body image processing (including left EBA and left FBA). Path analysis showed that in the Fat-Thin contrast, body dissatisfaction completely mediated the group difference in brain response in left amygdala across the whole sample. Our data are the first to demonstrate differences in brain response to body pictures between average weight and overweight young females involved in a body image self-reflection task. These results provide insights for understanding the vulnerability to body image distress among overweight or obese young females. PMID:27764116

My Body Looks Like That Girl's: Body Mass Index Modulates Brain Activity during Body Image Self-Reflection among Young Women.

PubMed

Gao, Xiao; Deng, Xiao; Wen, Xin; She, Ying; Vinke, Petra Corianne; Chen, Hong

2016-01-01

Body image distress or body dissatisfaction is one of the most common consequences of obesity and overweight. We investigated the neural bases of body image processing in overweight and average weight young women to understand whether brain regions that were previously found to be involved in processing self-reflective, perspective and affective components of body image would show different activation between two groups. Thirteen overweight (O-W group, age = 20.31±1.70 years) and thirteen average weight (A-W group, age = 20.15±1.62 years) young women underwent functional magnetic resonance imaging while performing a body image self-reflection task. Among both groups, whole-brain analysis revealed activations of a brain network related to perceptive and affective components of body image processing. ROI analysis showed a main effect of group in ACC as well as a group by condition interaction within bilateral EBA, bilateral FBA, right IPL, bilateral DLPFC, left amygdala and left MPFC. For the A-W group, simple effect analysis revealed stronger activations in Thin-Control compared to Fat-Control condition within regions related to perceptive (including bilateral EBA, bilateral FBA, right IPL) and affective components of body image processing (including bilateral DLPFC, left amygdala), as well as self-reference (left MPFC). The O-W group only showed stronger activations in Fat-Control than in Thin-Control condition within regions related to the perceptive component of body image processing (including left EBA and left FBA). Path analysis showed that in the Fat-Thin contrast, body dissatisfaction completely mediated the group difference in brain response in left amygdala across the whole sample. Our data are the first to demonstrate differences in brain response to body pictures between average weight and overweight young females involved in a body image self-reflection task. These results provide insights for understanding the vulnerability to body image distress among overweight or obese young females.

Application of principal component regression and partial least squares regression in ultraviolet spectrum water quality detection

NASA Astrophysics Data System (ADS)

Li, Jiangtong; Luo, Yongdao; Dai, Honglin

2018-01-01

Water is the source of life and the essential foundation of all life. With the development of industrialization, the phenomenon of water pollution is becoming more and more frequent, which directly affects the survival and development of human. Water quality detection is one of the necessary measures to protect water resources. Ultraviolet (UV) spectral analysis is an important research method in the field of water quality detection, which partial least squares regression (PLSR) analysis method is becoming predominant technology, however, in some special cases, PLSR's analysis produce considerable errors. In order to solve this problem, the traditional principal component regression (PCR) analysis method was improved by using the principle of PLSR in this paper. The experimental results show that for some special experimental data set, improved PCR analysis method performance is better than PLSR. The PCR and PLSR is the focus of this paper. Firstly, the principal component analysis (PCA) is performed by MATLAB to reduce the dimensionality of the spectral data; on the basis of a large number of experiments, the optimized principal component is extracted by using the principle of PLSR, which carries most of the original data information. Secondly, the linear regression analysis of the principal component is carried out with statistic package for social science (SPSS), which the coefficients and relations of principal components can be obtained. Finally, calculating a same water spectral data set by PLSR and improved PCR, analyzing and comparing two results, improved PCR and PLSR is similar for most data, but improved PCR is better than PLSR for data near the detection limit. Both PLSR and improved PCR can be used in Ultraviolet spectral analysis of water, but for data near the detection limit, improved PCR's result better than PLSR.

A Method for Accurate Group Difference Detection by Constraining the Mixing Coefficients in an ICA Framework

PubMed Central

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

2009-01-01

Independent component analysis (ICA) is a promising method that is increasingly used to analyze brain imaging data such as functional magnetic resonance imaging (fMRI), structural MRI, and electroencephalography and has also proved useful for group comparison, e.g., differentiating healthy controls from patients. An advantage of ICA is its ability to identify components that are mixed in an unknown manner. However, ICA is not necessarily robust and optimal in identifying between-group effects, especially in highly noisy situations. Here, we propose a modified ICA framework for multi-group data analysis that incorporates prior information regarding group membership as a constraint into the mixing coefficients. Our approach, called coefficient-constrained ICA (CC-ICA), prioritizes identification of components that show a significant group difference. The performance of CC-ICA via synthetic and hybrid data simulations is evaluated under different hypothesis testing assumptions and signal to noise ratios (SNRs). Group analysis is also conducted on real multitask fMRI data. Results show that CC-ICA improves the estimation accuracy of the independent components greatly, especially those that have different patterns for different groups (e.g., patients vs. controls); In addition, it enhances the data extraction sensitivity to group differences by ranking components with P value or J-divergence more consistently with the ground truth. The proposed algorithm performs quite well for both group-difference detection and multitask fMRI data fusion, which may prove especially important for the identification of relevant disease biomarkers. PMID:19172631

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

NASA Technical Reports Server (NTRS)

Somani, Arun K.

1996-01-01

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

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

PubMed

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

2011-01-01

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

[New method of mixed gas infrared spectrum analysis based on SVM].

PubMed

Bai, Peng; Xie, Wen-Jun; Liu, Jun-Hua

2007-07-01

A new method of infrared spectrum analysis based on support vector machine (SVM) for mixture gas was proposed. The kernel function in SVM was used to map the seriously overlapping absorption spectrum into high-dimensional space, and after transformation, the high-dimensional data could be processed in the original space, so the regression calibration model was established, then the regression calibration model with was applied to analyze the concentration of component gas. Meanwhile it was proved that the regression calibration model with SVM also could be used for component recognition of mixture gas. The method was applied to the analysis of different data samples. Some factors such as scan interval, range of the wavelength, kernel function and penalty coefficient C that affect the model were discussed. Experimental results show that the component concentration maximal Mean AE is 0.132%, and the component recognition accuracy is higher than 94%. The problems of overlapping absorption spectrum, using the same method for qualitative and quantitative analysis, and limit number of training sample, were solved. The method could be used in other mixture gas infrared spectrum analyses, promising theoretic and application values.

Testing for Non-Random Mating: Evidence for Ancestry-Related Assortative Mating in the Framingham Heart Study

PubMed Central

Sebro, Ronnie; Hoffman, Thomas J.; Lange, Christoph; Rogus, John J.; Risch, Neil J.

2013-01-01

Population stratification leads to a predictable phenomenon—a reduction in the number of heterozygotes compared to that calculated assuming Hardy-Weinberg Equilibrium (HWE). We show that population stratification results in another phenomenon—an excess in the proportion of spouse-pairs with the same genotypes at all ancestrally informative markers, resulting in ancestrally related positive assortative mating. We use principal components analysis to show that there is evidence of population stratification within the Framingham Heart Study, and show that the first principal component correlates with a North-South European cline. We then show that the first principal component is highly correlated between spouses (r=0.58, p=0.0013), demonstrating that there is ancestrally related positive assortative mating among the Framingham Caucasian population. We also show that the single nucleotide polymorphisms loading most heavily on the first principal component show an excess of homozygotes within the spouses, consistent with similar ancestry-related assortative mating in the previous generation. This nonrandom mating likely affects genetic structure seen more generally in the North American population of European descent today, and decreases the rate of decay of linkage disequilibrium for ancestrally informative markers. PMID:20842694

A photometric study of the eclipsing binary RX Hercules

NASA Technical Reports Server (NTRS)

Jeffreys, K. W.

1980-01-01

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

The Motivational Salience of Faces Is Related to Both Their Valence and Dominance.

PubMed

Wang, Hongyi; Hahn, Amanda C; DeBruine, Lisa M; Jones, Benedict C

2016-01-01

Both behavioral and neural measures of the motivational salience of faces are positively correlated with their physical attractiveness. Whether physical characteristics other than attractiveness contribute to the motivational salience of faces is not known, however. Research with male macaques recently showed that more dominant macaques' faces hold greater motivational salience. Here we investigated whether dominance also contributes to the motivational salience of faces in human participants. Principal component analysis of third-party ratings of faces for multiple traits revealed two orthogonal components. The first component ("valence") was highly correlated with rated trustworthiness and attractiveness. The second component ("dominance") was highly correlated with rated dominance and aggressiveness. Importantly, both components were positively and independently related to the motivational salience of faces, as assessed from responses on a standard key-press task. These results show that at least two dissociable components underpin the motivational salience of faces in humans and present new evidence for similarities in how humans and non-human primates respond to facial cues of dominance.

[Infrared spectroscopic study on the component and vigor analysis of Cistanche deserticola seeds].

PubMed

Xu, Rong; Sun, Su-Qin; Chen, Jun; Chen, Shi-Lin; Zhou, Feng

2009-01-01

Comparative study of the different parts of cistanche deserticola seeds and their changes after different processing were examined by Fourier transform infrared spectroscopy spectra (FTIR). The results of the analysis showed that components in the cistanche deserticola seeds were abundant, which contained characteristic absorption peaks of protein, fat and carbohydrate. As well, pectin and aromatic compound can be also found in the seeds. However, the components were different in different parts of cistanche deserticola seeds. The characteristic absorption peak intensities of fat at 2,926, 1,746, 1,161 and 721 cm(-1) were the strongest in the seed kernels. However, the seed coats mainly consisted of carbohydrate and pectin, which were showed at 1,054 cm(-1). The contents of protein and carbohydrate were decreased distinctly in the moldy and dead seeds after processing. The characteristic absorption peak intensity ratio of protein to fat (I1,630/I1,745 ) was all higher than 1.05 in the live seeds. The characteristic absorption peak intensity ratio of amido link I of protein to fat (11,653/I1,745) in the dead seed kernels of the cistanche deserticola was decreased from 0.31 to 0. 23, which was 25.8% less than that in vital seed kernels. The results suggest that FTIR not only can be used in fast comprehensive analysis of seed components, but also can be used in the seed vigor analysis, seed longevity determination and seed quality evaluation.

Visual target modulation of functional connectivity networks revealed by self-organizing group ICA.

PubMed

van de Ven, Vincent; Bledowski, Christoph; Prvulovic, David; Goebel, Rainer; Formisano, Elia; Di Salle, Francesco; Linden, David E J; Esposito, Fabrizio

2008-12-01

We applied a data-driven analysis based on self-organizing group independent component analysis (sogICA) to fMRI data from a three-stimulus visual oddball task. SogICA is particularly suited to the investigation of the underlying functional connectivity and does not rely on a predefined model of the experiment, which overcomes some of the limitations of hypothesis-driven analysis. Unlike most previous applications of ICA in functional imaging, our approach allows the analysis of the data at the group level, which is of particular interest in high order cognitive studies. SogICA is based on the hierarchical clustering of spatially similar independent components, derived from single subject decompositions. We identified four main clusters of components, centered on the posterior cingulate, bilateral insula, bilateral prefrontal cortex, and right posterior parietal and prefrontal cortex, consistently across all participants. Post hoc comparison of time courses revealed that insula, prefrontal cortex and right fronto-parietal components showed higher activity for targets than for distractors. Activation for distractors was higher in the posterior cingulate cortex, where deactivation was observed for targets. While our results conform to previous neuroimaging studies, they also complement conventional results by showing functional connectivity networks with unique contributions to the task that were consistent across subjects. SogICA can thus be used to probe functional networks of active cognitive tasks at the group-level and can provide additional insights to generate new hypotheses for further study. Copyright 2007 Wiley-Liss, Inc.

An ICT Adoption Framework for Education: A Case Study in Public Secondary School of Indonesia

NASA Astrophysics Data System (ADS)

Nurjanah, S.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

This paper presents preliminary research findings on the ICT adoption framework for education. Despite many studies have been conducted on ICT adoption framework in education at various countries, they are lack of analysis on the degree of component contribution to the success to the framework. In this paper a set of components that link to ICT adoption in education is observed based on literatures and explorative analysis. The components are Infrastructure, Application, User Skills, Utilization, Finance, and Policy. The components are used as a basis to develop a questionnaire to capture the current ICT adoption condition in schools. The data from questionnaire are processed using Structured Equation Model (SEM). The results show that each component contributes differently to the ICT adoption framework. Finance provides the strongest affect to Infrastructure readiness, whilst User Skills provides the strongest affect to Utilization. The study concludes that development of ICT adoption framework should consider components contribution weights among the components that can be used to guide the implementation of ICT adoption in education.

Genome-wide selection components analysis in a fish with male pregnancy.

PubMed

Flanagan, Sarah P; Jones, Adam G

2017-04-01

A major goal of evolutionary biology is to identify the genome-level targets of natural and sexual selection. With the advent of next-generation sequencing, whole-genome selection components analysis provides a promising avenue in the search for loci affected by selection in nature. Here, we implement a genome-wide selection components analysis in the sex role reversed Gulf pipefish, Syngnathus scovelli. Our approach involves a double-digest restriction-site associated DNA sequencing (ddRAD-seq) technique, applied to adult females, nonpregnant males, pregnant males, and their offspring. An F ST comparison of allele frequencies among these groups reveals 47 genomic regions putatively experiencing sexual selection, as well as 468 regions showing a signature of differential viability selection between males and females. A complementary likelihood ratio test identifies similar patterns in the data as the F ST analysis. Sexual selection and viability selection both tend to favor the rare alleles in the population. Ultimately, we conclude that genome-wide selection components analysis can be a useful tool to complement other approaches in the effort to pinpoint genome-level targets of selection in the wild. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Molecular characterization of banana bunchy top virus isolate from Sri Lanka and its genetic relationship with other isolates.

PubMed

Wickramaarachchi, W A R T; Shankarappa, K S; Rangaswamy, K T; Maruthi, M N; Rajapakse, R G A S; Ghosh, Saptarshi

2016-06-01

Bunchy top disease of banana caused by Banana bunchy top virus (BBTV, genus Babuvirus family Nanoviridae) is one of the most important constraints in production of banana in the different parts of the world. Six genomic DNA components of BBTV isolate from Kandy, Sri Lanka (BBTV-K) were amplified by polymerase chain reaction (PCR) with specific primers using total DNA extracted from banana tissues showing typical symptoms of bunchy top disease. The amplicons were of expected size of 1.0-1.1 kb, which were cloned and sequenced. Analysis of sequence data revealed the presence of six DNA components; DNA-R, DNA-U3, DNA-S, DNA-N, DNA-M and DNA-C for Sri Lanka isolate. Comparisons of sequence data of DNA components followed by the phylogenetic analysis, grouped Sri Lanka-(Kandy) isolate in the Pacific Indian Oceans (PIO) group. Sri Lanka-(Kandy) isolate of BBTV is classified a new member of PIO group based on analysis of six components of the virus.

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.

Integrative sparse principal component analysis of gene expression data.

PubMed

Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

2017-12-01

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

Analysis on Sealing Reliability of Bolted Joint Ball Head Component of Satellite Propulsion System

NASA Astrophysics Data System (ADS)

Guo, Tao; Fan, Yougao; Gao, Feng; Gu, Shixin; Wang, Wei

2018-01-01

Propulsion system is one of the important subsystems of satellite, and its performance directly affects the service life, attitude control and reliability of the satellite. The Paper analyzes the sealing principle of bolted joint ball head component of satellite propulsion system and discuss from the compatibility of hydrazine anhydrous and bolted joint ball head component, influence of ground environment on the sealing performance of bolted joint ball heads, and material failure caused by environment, showing that the sealing reliability of bolted joint ball head component is good and the influence of above three aspects on sealing of bolted joint ball head component can be ignored.

[Identification of antler powder components based on DNA barcoding technology].

PubMed

Jia, Jing; Shi, Lin-chun; Xu, Zhi-chao; Xin, Tian-yi; Song, Jing-yuan; Chen Shi, Lin

2015-10-01

In order to authenticate the components of antler powder in the market, DNA barcoding technology coupled with cloning method were used. Cytochrome c oxidase subunit I (COI) sequences were obtained according to the DNA barcoding standard operation procedure (SOP). For antler powder with possible mixed components, the cloning method was used to get each COI sequence. 65 COI sequences were successfully obtained from commercial antler powders via sequencing PCR products. The results indicates that only 38% of these samples were derived from Cervus nippon Temminck or Cervus elaphus Linnaeus which is recorded in the 2010 edition of "Chinese Pharmacopoeia", while 62% of them were derived from other species. Rangifer tarandus Linnaeus was the most frequent species among the adulterants. Further analysis showed that some samples collected from different regions, companies and prices, contained adulterants. Analysis of 36 COI sequences obtained by the cloning method showed that C. elaphus and C. nippon were main components. In addition, some samples were marked clearly as antler powder on the label, however, C. elaphus or R. tarandus were their main components. In summary, DNA barcoding can accurately and efficiently distinguish the exact content in the commercial antler powder, which provides a new technique to ensure clinical safety and improve quality control of Chinese traditional medicine

Comparative cost-effectiveness of the components of a behavior change communication campaign on HIV/AIDS in North India.

PubMed

Sood, Suruchi; Nambiar, Devaki

2006-01-01

Numerous studies show that exposure to entertainment-education-based mass media campaigns is associated with reduction in risk behaviors. Concurrently, there is a growing interest in comparing the cost-effectiveness of HIV prevention interventions taking into account infrastructural and programmatic costs. In such analyses, though few in number, mass media campaigns have fared well. Using data from a mass media communication campaign in the low HIV prevalence states of Uttar Pradesh, Rajasthan, and Delhi in Northern India, in this article we examine the following: (1) factors that mediate behavior change in different components of the campaign, comprising a TV drama, reality show for youth audiences, and TV spots; (2) the relative impact of campaign components on the behavioral outcome: condom use; and (3) the cost-effectiveness calculations arising from this analysis. Results suggest that recall of the TV spots and the TV drama influences behavior change and is strongly associated with interpersonal communication and positive gender attitudes. The TV drama, in spite of being the costliest, emerges as the most cost-effective component when considering the behavioral outcome of interest. The analysis of the comparative cost-effectiveness of individual campaign components provides insights into the planning of resources for communication interventions globally.

[Autoantibody formation against the antigens of the synaptonemal complex in the syngeneic immunization of male Mus musculus].

PubMed

Dadashev, S Ia; Gorach, G G; Kolomiets, O L

1994-01-01

Male mice were immunized with the suspension of synaptonemal complexes (SC) isolated from mouse spermatocytes nuclei. The indirect immunofluorescent analysis showed the active binding of sera obtained from immunized mice to SC of mouse spermatocyte spreads. At early and mid-pachytene, SC can be clearly identified in 19 autosome bivalents and in sex chromosome bivalent. According to the electron microscopic analysis, all structural elements of SC bind antibodies. Metaphase chromosomes were not stained with the immune sera. Specificity of interaction between SC components and antibodies was confirmed in a series of control experiments. Analysis of sera obtained from mice after their syngeneic immunization with isolated SC fraction suggested that certain mouse SC components induce the formation of autoantibodies. This, in turn, suggests that these SC components are meiosis-specific.

Addressing the identification problem in age-period-cohort analysis: a tutorial on the use of partial least squares and principal components analysis.

PubMed

Tu, Yu-Kang; Krämer, Nicole; Lee, Wen-Chung

2012-07-01

In the analysis of trends in health outcomes, an ongoing issue is how to separate and estimate the effects of age, period, and cohort. As these 3 variables are perfectly collinear by definition, regression coefficients in a general linear model are not unique. In this tutorial, we review why identification is a problem, and how this problem may be tackled using partial least squares and principal components regression analyses. Both methods produce regression coefficients that fulfill the same collinearity constraint as the variables age, period, and cohort. We show that, because the constraint imposed by partial least squares and principal components regression is inherent in the mathematical relation among the 3 variables, this leads to more interpretable results. We use one dataset from a Taiwanese health-screening program to illustrate how to use partial least squares regression to analyze the trends in body heights with 3 continuous variables for age, period, and cohort. We then use another dataset of hepatocellular carcinoma mortality rates for Taiwanese men to illustrate how to use partial least squares regression to analyze tables with aggregated data. We use the second dataset to show the relation between the intrinsic estimator, a recently proposed method for the age-period-cohort analysis, and partial least squares regression. We also show that the inclusion of all indicator variables provides a more consistent approach. R code for our analyses is provided in the eAppendix.

Analysis of indoor air pollutants checklist using environmetric technique for health risk assessment of sick building complaint in nonindustrial workplace

PubMed Central

Syazwan, AI; Rafee, B Mohd; Juahir, Hafizan; Azman, AZF; Nizar, AM; Izwyn, Z; Syahidatussyakirah, K; Muhaimin, AA; Yunos, MA Syafiq; Anita, AR; Hanafiah, J Muhamad; Shaharuddin, MS; Ibthisham, A Mohd; Hasmadi, I Mohd; Azhar, MN Mohamad; Azizan, HS; Zulfadhli, I; Othman, J; Rozalini, M; Kamarul, FT

2012-01-01

Purpose To analyze and characterize a multidisciplinary, integrated indoor air quality checklist for evaluating the health risk of building occupants in a nonindustrial workplace setting. Design A cross-sectional study based on a participatory occupational health program conducted by the National Institute of Occupational Safety and Health (Malaysia) and Universiti Putra Malaysia. Method A modified version of the indoor environmental checklist published by the Department of Occupational Health and Safety, based on the literature and discussion with occupational health and safety professionals, was used in the evaluation process. Summated scores were given according to the cluster analysis and principal component analysis in the characterization of risk. Environmetric techniques was used to classify the risk of variables in the checklist. Identification of the possible source of item pollutants was also evaluated from a semiquantitative approach. Result Hierarchical agglomerative cluster analysis resulted in the grouping of factorial components into three clusters (high complaint, moderate-high complaint, moderate complaint), which were further analyzed by discriminant analysis. From this, 15 major variables that influence indoor air quality were determined. Principal component analysis of each cluster revealed that the main factors influencing the high complaint group were fungal-related problems, chemical indoor dispersion, detergent, renovation, thermal comfort, and location of fresh air intake. The moderate-high complaint group showed significant high loading on ventilation, air filters, and smoking-related activities. The moderate complaint group showed high loading on dampness, odor, and thermal comfort. Conclusion This semiquantitative assessment, which graded risk from low to high based on the intensity of the problem, shows promising and reliable results. It should be used as an important tool in the preliminary assessment of indoor air quality and as a categorizing method for further IAQ investigations and complaints procedures. PMID:23055779

Analysis of indoor air pollutants checklist using environmetric technique for health risk assessment of sick building complaint in nonindustrial workplace.

PubMed

Syazwan, Ai; Rafee, B Mohd; Juahir, Hafizan; Azman, Azf; Nizar, Am; Izwyn, Z; Syahidatussyakirah, K; Muhaimin, Aa; Yunos, Ma Syafiq; Anita, Ar; Hanafiah, J Muhamad; Shaharuddin, Ms; Ibthisham, A Mohd; Hasmadi, I Mohd; Azhar, Mn Mohamad; Azizan, Hs; Zulfadhli, I; Othman, J; Rozalini, M; Kamarul, Ft

2012-01-01

To analyze and characterize a multidisciplinary, integrated indoor air quality checklist for evaluating the health risk of building occupants in a nonindustrial workplace setting. A cross-sectional study based on a participatory occupational health program conducted by the National Institute of Occupational Safety and Health (Malaysia) and Universiti Putra Malaysia. A modified version of the indoor environmental checklist published by the Department of Occupational Health and Safety, based on the literature and discussion with occupational health and safety professionals, was used in the evaluation process. Summated scores were given according to the cluster analysis and principal component analysis in the characterization of risk. Environmetric techniques was used to classify the risk of variables in the checklist. Identification of the possible source of item pollutants was also evaluated from a semiquantitative approach. Hierarchical agglomerative cluster analysis resulted in the grouping of factorial components into three clusters (high complaint, moderate-high complaint, moderate complaint), which were further analyzed by discriminant analysis. From this, 15 major variables that influence indoor air quality were determined. Principal component analysis of each cluster revealed that the main factors influencing the high complaint group were fungal-related problems, chemical indoor dispersion, detergent, renovation, thermal comfort, and location of fresh air intake. The moderate-high complaint group showed significant high loading on ventilation, air filters, and smoking-related activities. The moderate complaint group showed high loading on dampness, odor, and thermal comfort. This semiquantitative assessment, which graded risk from low to high based on the intensity of the problem, shows promising and reliable results. It should be used as an important tool in the preliminary assessment of indoor air quality and as a categorizing method for further IAQ investigations and complaints procedures.

Different brain activations between own- and other-race face categorization: an fMRI study using group independent component analysis

NASA Astrophysics Data System (ADS)

Wei, Wenjuan; Liu, Jiangang; Dai, Ruwei; Feng, Lu; Li, Ling; Tian, Jie

2014-03-01

Previous behavioral research has proved that individuals process own- and other-race faces differently. One well-known effect is the other-race effect (ORE), which indicates that individuals categorize other-race faces more accurately and faster than own-race faces. The existed functional magnetic resonance imaging (fMRI) studies of the other-race effect mainly focused on the racial prejudice and the socio-affective differences towards own- and other-race face. In the present fMRI study, we adopted a race-categorization task to determine the activation level differences between categorizing own- and other-race faces. Thirty one Chinese participants who live in China with Chinese as the majority and who had no direct contact with Caucasian individual were recruited in the present study. We used the group independent component analysis (ICA), which is a method of blind source signal separation that has proven to be promising for analysis of fMRI data. We separated the entail data into 56 components which is estimated based on one subject using the Minimal Description Length (MDL) criteria. The components sorted based on the multiple linear regression temporal sorting criteria, and the fit regression parameters were used in performing statistical test to evaluate the task-relatedness of the components. The one way anova was performed to test the significance of the component time course in different conditions. Our result showed that the areas, which coordinates is similar to the right FFA coordinates that previous studies reported, were greater activated for own-race faces than other-race faces, while the precuneus showed greater activation for other-race faces than own-race faces.

Analysis on unevenness of skin color using the melanin and hemoglobin components separated by independent component analysis of skin color image

NASA Astrophysics Data System (ADS)

Ojima, Nobutoshi; Fujiwara, Izumi; Inoue, Yayoi; Tsumura, Norimichi; Nakaguchi, Toshiya; Iwata, Kayoko

2011-03-01

Uneven distribution of skin color is one of the biggest concerns about facial skin appearance. Recently several techniques to analyze skin color have been introduced by separating skin color information into chromophore components, such as melanin and hemoglobin. However, there are not many reports on quantitative analysis of unevenness of skin color by considering type of chromophore, clusters of different sizes and concentration of the each chromophore. We propose a new image analysis and simulation method based on chromophore analysis and spatial frequency analysis. This method is mainly composed of three techniques: independent component analysis (ICA) to extract hemoglobin and melanin chromophores from a single skin color image, an image pyramid technique which decomposes each chromophore into multi-resolution images, which can be used for identifying different sizes of clusters or spatial frequencies, and analysis of the histogram obtained from each multi-resolution image to extract unevenness parameters. As the application of the method, we also introduce an image processing technique to change unevenness of melanin component. As the result, the method showed high capabilities to analyze unevenness of each skin chromophore: 1) Vague unevenness on skin could be discriminated from noticeable pigmentation such as freckles or acne. 2) By analyzing the unevenness parameters obtained from each multi-resolution image for Japanese ladies, agerelated changes were observed in the parameters of middle spatial frequency. 3) An image processing system modulating the parameters was proposed to change unevenness of skin images along the axis of the obtained age-related change in real time.

New Insights into the Folding of a β-Sheet Miniprotein in a Reduced Space of Collective Hydrogen Bond Variables: Application to a Hydrodynamic Analysis of the Folding Flow

PubMed Central

Kalgin, Igor V.; Caflisch, Amedeo; Chekmarev, Sergei F.; Karplus, Martin

2013-01-01

A new analysis of the 20 μs equilibrium folding/unfolding molecular dynamics simulations of the three-stranded antiparallel β-sheet miniprotein (beta3s) in implicit solvent is presented. The conformation space is reduced in dimensionality by introduction of linear combinations of hydrogen bond distances as the collective variables making use of a specially adapted Principal Component Analysis (PCA); i.e., to make structured conformations more pronounced, only the formed bonds are included in determining the principal components. It is shown that a three-dimensional (3D) subspace gives a meaningful representation of the folding behavior. The first component, to which eight native hydrogen bonds make the major contribution (four in each beta hairpin), is found to play the role of the reaction coordinate for the overall folding process, while the second and third components distinguish the structured conformations. The representative points of the trajectory in the 3D space are grouped into conformational clusters that correspond to locally stable conformations of beta3s identified in earlier work. A simplified kinetic network based on the three components is constructed and it is complemented by a hydrodynamic analysis. The latter, making use of “passive tracers” in 3D space, indicates that the folding flow is much more complex than suggested by the kinetic network. A 2D representation of streamlines shows there are vortices which correspond to repeated local rearrangement, not only around minima of the free energy surface, but also in flat regions between minima. The vortices revealed by the hydrodynamic analysis are apparently not evident in folding pathways generated by transition-path sampling. Making use of the fact that the values of the collective hydrogen bond variables are linearly related to the Cartesian coordinate space, the RMSD between clusters is determined. Interestingly, the transition rates show an approximate exponential correlation with distance in the hydrogen bond subspace. Comparison with the many published studies shows good agreement with the present analysis for the parts that can be compared, supporting the robust character of our understanding of this “hydrogen atom” of protein folding. PMID:23621790

Predicting athletic success motivation using mental skin and emotional intelligence and its components in male athletes.

PubMed

Kajbafnezhad, H; Ahadi, H; Heidarie, A; Askari, P; Enayati, M

2012-10-01

The aim of this study was to predict athletic success motivation by mental skills, emotional intelligence and its components. The research sample consisted of 153 male athletes who were selected through random multistage sampling. The subjects completed the Mental Skills Questionnaire, Bar-On Emotional Intelligence questionnaire and the perception of sport success questionnaire. Data were analyzed using Pearson correlation coefficient and multiple regressions. Regression analysis shows that between the two variables of mental skill and emotional intelligence, mental skill is the best predictor for athletic success motivation and has a better ability to predict the success rate of the participants. Regression analysis results showed that among all the components of emotional intelligence, self-respect had a significantly higher ability to predict athletic success motivation. The use of psychological skills and emotional intelligence as an mediating and regulating factor and organizer cause leads to improved performance and can not only can to help athletes in making suitable and effective decisions for reaching a desired goal.

Brewing and volatiles analysis of three tea beers indicate a potential interaction between tea components and lager yeast.

PubMed

Rong, Lei; Peng, Li-Juan; Ho, Chi-Tang; Yan, Shou-He; Meurens, Marc; Zhang, Zheng-Zhu; Li, Da-Xiang; Wan, Xiao-Chun; Bao, Guan-Hu; Gao, Xue-Ling; Ling, Tie-Jun

2016-04-15

Green tea, oolong tea and black tea were separately introduced to brew three kinds of tea beers. A model was designed to investigate the tea beer flavour character. Comparison of the volatiles between the sample of tea beer plus water mixture (TBW) and the sample of combination of tea infusion and normal beer (CTB) was accomplished by triangular sensory test and HS-SPME GC-MS analysis. The PCA of GC-MS data not only showed a significant difference between volatile features of each TBW and CTB group, but also suggested some key compounds to distinguish TBW from CTB. The results of GC-MS showed that the relative concentrations of many typical tea volatiles were significantly changed after the brewing process. More interestingly, the behaviour of yeast fermentation was influenced by tea components. A potential interaction between tea components and lager yeast could be suggested. Copyright © 2015 Elsevier Ltd. All rights reserved.

Urban air-quality assessment and source apportionment studies for Bhubaneshwar, Odisha

NASA Astrophysics Data System (ADS)

Mahapatra, Parth Sarathi; Ray, Sanak; Das, Namrata; Mohanty, Ayusman; Ramulu, T. S.; Das, Trupti; Chaudhury, G. Roy; Das, S. N.

2013-04-01

Acid- and water-soluble component of suspended particulate matter was studied from January 2009 to December 2009 at Bhubaneshwar, an urban coastal location of eastern India, by high-volume sampler, environmental dust monitor using GRIMM®, and scanning electron microscope and energy dispersive X-ray spectrometer. The water-soluble components accounted for 30-45 % of the total suspended particulate matter, and the major elements were observed to be ammonium and nitrate as the cationic and anionic species, respectively. The acid-soluble component like copper, nickel, cobalt, iron, and lead accounted for 5-15 % of the total particulate matter concentration. The composition of particulate matter shows a clear seasonal variation in relation to wind speed, wind direction, and trajectories of the air mass movement. The GRIMM spectrometer analysis shows higher concentration of fine particulate matter. Source apportionment and enrichment factor analysis indicated that except sodium and chloride, all other elements have emerged from different sources such as crustal as well as anthropogenic.

Debonding of porous coating of a threaded acetabular component: retrieval analysis.

PubMed

Łapaj, Łukasz; Markuszewski, Jacek; Rybak, Tomasz; Wierusz-Kozłowska, Małgorzata

2013-01-01

This report presents a case of debonding of plasma sprayed porous titanium coating from a threaded acetabular component which caused aseptic loosening of the implant. Weight bearing after delamination caused abrasive damage of the acetabular shell, and particles of the coating embedded in the acetabular liner. Microscopic examination of periprosthetic tissues showed presence of metal particles and macrophage infiltration. Despite microscopic examination of the retrieved component the cause of debonding remains unclear. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ambient Field Analysis at Groningen Gas Field

NASA Astrophysics Data System (ADS)

Spica, Z.; Nakata, N.; Beroza, G. C.

2016-12-01

We analyze continuous ambient-field data at Groningen gas field (Netherlands) through cross-correlation processing. The Groningen array is composed of 75 shallow boreholes with 6 km spacing, which contain a 3C surface accelerometer and four 5-Hz 3C borehole geophones spaced at 50 m depth intervals. We successfully retrieve coherent waves from ambient seismic field on the 9 components between stations. Results show high SNR signal in the frequency range of 0.125-1 Hz, and the ZZ, ZR, RZ, RR and TT components show much stronger wave energy than other components as expected. This poster discuss the different type of waves retrieved, the utility of the combination of borehole and surface observations, future development as well as the importance to compute the 9 components of the Green's tensor to better understand the wave field propriety with ambient noise.

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.

Just a Fad? Gamification in Health and Fitness Apps

PubMed Central

2014-01-01

Background Gamification has been a predominant focus of the health app industry in recent years. However, to our knowledge, there has yet to be a review of gamification elements in relation to health behavior constructs, or insight into the true proliferation of gamification in health apps. Objective The objective of this study was to identify the extent to which gamification is used in health apps, and analyze gamification of health and fitness apps as a potential component of influence on a consumer’s health behavior. Methods An analysis of health and fitness apps related to physical activity and diet was conducted among apps in the Apple App Store in the winter of 2014. This analysis reviewed a sample of 132 apps for the 10 effective game elements, the 6 core components of health gamification, and 13 core health behavior constructs. A regression analysis was conducted in order to measure the correlation between health behavior constructs, gamification components, and effective game elements. Results This review of the most popular apps showed widespread use of gamification principles, but low adherence to any professional guidelines or industry standard. Regression analysis showed that game elements were associated with gamification (P<.001). Behavioral theory was associated with gamification (P<.05), but not game elements, and upon further analysis gamification was only associated with composite motivational behavior scores (P<.001), and not capacity or opportunity/trigger. Conclusions This research, to our knowledge, represents the first comprehensive review of gamification use in health and fitness apps, and the potential to impact health behavior. The results show that use of gamification in health and fitness apps has become immensely popular, as evidenced by the number of apps found in the Apple App Store containing at least some components of gamification. This shows a lack of integrating important elements of behavioral theory from the app industry, which can potentially impact the efficacy of gamification apps to change behavior. Apps represent a very promising, burgeoning market and landscape in which to disseminate health behavior change interventions. Initial results show an abundant use of gamification in health and fitness apps, which necessitates the in-depth study and evaluation of the potential of gamification to change health behaviors. PMID:25654660

Non-linear principal component analysis applied to Lorenz models and to North Atlantic SLP

NASA Astrophysics Data System (ADS)

Russo, A.; Trigo, R. M.

2003-04-01

A non-linear generalisation of Principal Component Analysis (PCA), denoted Non-Linear Principal Component Analysis (NLPCA), is introduced and applied to the analysis of three data sets. Non-Linear Principal Component Analysis allows for the detection and characterisation of low-dimensional non-linear structure in multivariate data sets. This method is implemented using a 5-layer feed-forward neural network introduced originally in the chemical engineering literature (Kramer, 1991). The method is described and details of its implementation are addressed. Non-Linear Principal Component Analysis is first applied to a data set sampled from the Lorenz attractor (1963). It is found that the NLPCA approximations are more representative of the data than are the corresponding PCA approximations. The same methodology was applied to the less known Lorenz attractor (1984). However, the results obtained weren't as good as those attained with the famous 'Butterfly' attractor. Further work with this model is underway in order to assess if NLPCA techniques can be more representative of the data characteristics than are the corresponding PCA approximations. The application of NLPCA to relatively 'simple' dynamical systems, such as those proposed by Lorenz, is well understood. However, the application of NLPCA to a large climatic data set is much more challenging. Here, we have applied NLPCA to the sea level pressure (SLP) field for the entire North Atlantic area and the results show a slight imcrement of explained variance associated. Finally, directions for future work are presented.%}

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

An experimental study to investigate the effects of a motion tracking electromagnetic sensor during EEG data acquisition.

PubMed

Bashashati, Ali; Noureddin, Borna; Ward, Rabab K; Lawrence, Peter D; Birch, Gary E

2006-03-01

A power spectral analysis study was conducted to investigate the effects of using an electromagnetic motion tracking sensor on an electroencephalogram (EEG) recording system. The results showed that the sensors do not generate any consistent frequency component(s) in the power spectrum of the EEG in the frequencies of interest (0.1-55 Hz).

Study on fast discrimination of varieties of yogurt using Vis/NIR-spectroscopy

NASA Astrophysics Data System (ADS)

He, Yong; Feng, Shuijuan; Deng, Xunfei; Li, Xiaoli

2006-09-01

A new approach for discrimination of varieties of yogurt by means of VisINTR-spectroscopy was present in this paper. Firstly, through the principal component analysis (PCA) of spectroscopy curves of 5 typical kinds of yogurt, the clustering of yogurt varieties was processed. The analysis results showed that the cumulate reliabilities of PC1 and PC2 (the first two principle components) were more than 98.956%, and the cumulate reliabilities from PC1 to PC7 (the first seven principle components) was 99.97%. Secondly, a discrimination model of Artificial Neural Network (ANN-BP) was set up. The first seven principles components of the samples were applied as ANN-BP inputs, and the value of type of yogurt were applied as outputs, then the three-layer ANN-BP model was build. In this model, every variety yogurt includes 27 samples, the total number of sample is 135, and the rest 25 samples were used as prediction set. The results showed the distinguishing rate of the five yogurt varieties was 100%. It presented that this model was reliable and practicable. So a new approach for the rapid and lossless discrimination of varieties of yogurt was put forward.

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

PubMed Central

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

2016-01-01

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

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

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

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

1995-07-01

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

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

PubMed

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

2016-03-20

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

Inversion of gravity gradient tensor data: does it provide better resolution?

NASA Astrophysics Data System (ADS)

Paoletti, V.; Fedi, M.; Italiano, F.; Florio, G.; Ialongo, S.

2016-04-01

The gravity gradient tensor (GGT) has been increasingly used in practical applications, but the advantages and the disadvantages of the analysis of GGT components versus the analysis of the vertical component of the gravity field are still debated. We analyse the performance of joint inversion of GGT components versus separate inversion of the gravity field alone, or of one tensor component. We perform our analysis by inspection of the Picard Plot, a Singular Value Decomposition tool, and analyse both synthetic data and gradiometer measurements carried out at the Vredefort structure, South Africa. We show that the main factors controlling the reliability of the inversion are algebraic ambiguity (the difference between the number of unknowns and the number of available data points) and signal-to-noise ratio. Provided that algebraic ambiguity is kept low and the noise level is small enough so that a sufficient number of SVD components can be included in the regularized solution, we find that: (i) the choice of tensor components involved in the inversion is not crucial to the overall reliability of the reconstructions; (ii) GGT inversion can yield the same resolution as inversion with a denser distribution of gravity data points, but with the advantage of using fewer measurement stations.

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.

[Detection of quadratic phase coupling between EEG signal components by nonparamatric and parametric methods of bispectral analysis].

PubMed

Schmidt, K; Witte, H

1999-11-01

Recently the assumption of the independence of individual frequency components in a signal has been rejected, for example, for the EEG during defined physiological states such as sleep or sedation [9, 10]. Thus, the use of higher-order spectral analysis capable of detecting interrelations between individual signal components has proved useful. The aim of the present study was to investigate the quality of various non-parametric and parametric estimation algorithms using simulated as well as true physiological data. We employed standard algorithms available for the MATLAB. The results clearly show that parametric bispectral estimation is superior to non-parametric estimation in terms of the quality of peak localisation and the discrimination from other peaks.

The role of event water, a rapid shallow flow component, and catchment size in summer stormflow

USGS Publications Warehouse

Brown, V.A.; McDonnell, Jeffery J.; Burns, Douglas A.; Kendall, C.

1999-01-01

Seven nested headwater catchments (8 to 161 ha) were monitored during five summer rain events to evaluate storm runoff components and the effect of catchment size on water sources. Two-component isotopic hydrograph separation showed that event-water contributions near the time of peakflow ranged from 49% to 62% in the 7 catchments during the highest intensity event. The proportion of event water in stormflow was greater than could be accounted for by direct precipitation onto saturated areas. DOC concentrations in stormflow were strongly correlated with stream 18O composition. Bivariate mixing diagrams indicated that the large event water contributions were likely derived from flow through the soil O-horizon. Results from two-tracer, three-component hydrograph separations showed that the throughfall and O-horizon soil-water components together could account for the estimated contributions of event water to stormflow. End-member mixing analysis confirmed these results. Estimated event-water contributions were inversely related to catchment size, but the relation was significant for only the event with greatest rainfall intensity. Our results suggest that perched, shallow subsurface flow provides a substantial contribution to summer stormflow in these small catchments, but the relative contribution of this component decreases with catchment size.Seven nested headwater catchments (8 to 161 ha) were monitored during five summer rain events to evaluate storm runoff components and the effect of catchment size on water sources. Two-component isotopic hydrograph separation showed that event-water contributions near the time of peakflow ranged from 49% to 62% in the 7 catchments during the highest intensity event. The proportion of event water in stormflow was greater than could be accounted for by direct precipitation onto saturated areas. DOC concentrations in stormflow were strongly correlated with stream 18O composition. Bivariate mixing diagrams indicated that the large event water contributions were likely derived from flow through the soil O-horizon. Results from two-tracer, three-component hydrograph separations showed that the throughfall and O-horizon soil-water components together could account for the estimated contributions of event water to stormflow. End-member mixing analysis confirmed these results. Estimated event-water contributions were inversely related to catchment size, but the relation was significant for only the event with greatest rainfall intensity. Our results suggest that perched, shallow subsurface flow provides a substantial contribution to summer stormflow in these small catchments, but the relative contribution of this component decreases with catchment size.

Use of principal-component, correlation, and stepwise multiple-regression analyses to investigate selected physical and hydraulic properties of carbonate-rock aquifers

USGS Publications Warehouse

Brown, C. Erwin

1993-01-01

Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.

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

Evolution of the symbiotic binary system AG Pegasi - The slowest classical nova eruption ever recorded

NASA Technical Reports Server (NTRS)

Kenyon, Scott J.; Mikolajewska, Joanna; Mikolajewski, Maciej; Polidan, Ronald S.; Slovak, Mark H.

1993-01-01

We present an analysis of new and existing photometric and spectroscopic observations of the ongoing eruption in the symbiotic star AG Pegasi, showing that this binary has evolved considerably since the turn of the century. Recent dramatic changes in both the UV continuum and the wind from the hot component allow a more detailed analysis than in previous papers. AG Peg is composed of a normal M3 giant and a hot, compact star embedded in a dense, ionized nebula. The hot component powers the activity observed in this system, including a dense wind and a photoionized region within the outer atmosphere of the red giant. The hot component contracted in radius at roughly constant luminosity from 1850 to 1985. Its bolometric luminosity declined by a factor of about 4 during the past 5 yr. Both the mass loss rate from the hot component and the emission activity decreased in step with the hot component's total luminosity, while photospheric radiation from the red giant companion remained essentially constant.

Assessing School Work Culture: A Higher-Order Analysis and Strategy.

ERIC Educational Resources Information Center

Johnson, William L.; Johnson, Annabel M.; Zimmerman, Kurt J.

This paper reviews a work culture productivity model and reports the development of a work culture instrument based on the culture productivity model. Higher order principal components analysis was used to assess work culture, and a third-order factor analysis shows how the first-order factors group into higher-order factors. The school work…

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

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

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

NASA Astrophysics Data System (ADS)

Ritchie, Alexa J.; Brouwer, Jacob

2018-04-01

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

Time-frequency analysis of stimulus frequency otoacoustic emissions and their changes with efferent stimulation in guinea pigs

NASA Astrophysics Data System (ADS)

Berezina-Greene, Maria A.; Guinan, John J.

2015-12-01

To aid in understanding their origin, stimulus frequency otoacoustic emissions (SFOAEs) were measured at a series of tone frequencies using the suppression method, both with and without stimulation of medial olivocochlear (MOC) efferents, in anesthetized guinea pigs. Time-frequency analysis showed SFOAE energy peaks in 1-3 delay components throughout the measured frequency range (0.5-12 kHz). One component's delay usually coincided with the phase-gradient delay. When multiple delay components were present, they were usually near SFOAE dips. Below 2 kHz, SFOAE delays were shorter than predicted from mechanical measurements. With MOC stimulation, SFOAE amplitude was decreased at most frequencies, but was sometimes enhanced, and all SFOAE delay components were affected. The MOC effects and an analysis of model data suggest that the multiple SFOAE delay components arise at the edges of the traveling-wave peak, not far basal of the peak. Comparisons with published guinea-pig neural data suggest that the short latencies of low-frequency SFOAEs may arise from coherent reflection from an organ-of-Corti motion that has a shorter group delay than the traveling wave.

Using recurrence plot analysis for software execution interpretation and fault detection

NASA Astrophysics Data System (ADS)

Mosdorf, M.

2015-09-01

This paper shows a method targeted at software execution interpretation and fault detection using recurrence plot analysis. In in the proposed approach recurrence plot analysis is applied to software execution trace that contains executed assembly instructions. Results of this analysis are subject to further processing with PCA (Principal Component Analysis) method that simplifies number coefficients used for software execution classification. This method was used for the analysis of five algorithms: Bubble Sort, Quick Sort, Median Filter, FIR, SHA-1. Results show that some of the collected traces could be easily assigned to particular algorithms (logs from Bubble Sort and FIR algorithms) while others are more difficult to distinguish.

[Relationship between four components of assertiveness and mental health among high school students].

PubMed

Watanabe, Asami

2009-04-01

This study examines the relationship between four components of assertiveness ("open expression", "control of emotion", "consideration for others" and "self-direction") and mental health. In Study 1, the analysis of interviews with thirteen high school students suggested that some components did not have a positive relationship with mental health. In Study 2, 176 high school students completed a questionnaire which included the UCLA isolation scale, the General Health Questionnaire (GHQ) and a scale to measure the four components of assertiveness. The results showed that an excessively high score for "consideration for others" was associated with mental unhealthiness. This component probably has an optimum level to maintain mental health.

Chemical Mapping of Essential Oils, Flavonoids and Carotenoids in Citrus Peels by Raman Microscopy.

PubMed

Yang, Ying; Wang, Xiaohe; Zhao, Chengying; Tian, Guifang; Zhang, Hua; Xiao, Hang; He, Lili; Zheng, Jinkai

2017-12-01

Citrus peels, by-products in large quantity, are rich in various functional and beneficial components which have wide applications. Chemical analysis of these components in citrus peels is an important step to determine the usefulness of the by-products for further applications. In this study, we explored Raman microscopy for rapid, nondestructive, and in situ chemical mapping of multiple main functional components from citrus peels. The relative amount and distribution in different locations (flavedo, albedo, and longitudinal section) of 3 main functional components (essential oils, carotenoids, and flavonoids) in citrus peels were systematically investigated. The distribution profiles of these components were heterogeneous on the peels and varied between different species of citrus peels. Essential oil was found mainly existed in the oil glands, while carotenoids were in the complementary location. Some flavonoids were observed in the oil glands. This study showed the capability of Raman microscopy for rapid and nondestructive analysis of multiple bio-components without extraction from plants. The information obtained from this study would assist the better production and application of the functional and beneficial components from citrus by products in an effective and sustainable manner. This study indicated the capability of Raman microscopy for rapid and nondestructive analysis of multiple bioactive components in plant tissues. The information obtained from the study would be valuable for developing effective and sustainable strategy of utilization of citrus peels for further applications. © 2017 Institute of Food Technologists®.

Fetal source extraction from magnetocardiographic recordings by dependent component analysis

NASA Astrophysics Data System (ADS)

de Araujo, Draulio B.; Kardec Barros, Allan; Estombelo-Montesco, Carlos; Zhao, Hui; Roque da Silva Filho, A. C.; Baffa, Oswaldo; Wakai, Ronald; Ohnishi, Noboru

2005-10-01

Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

Mental and physical health-related quality of life in obese patients before and after bariatric surgery: a meta-analysis.

PubMed

Magallares, Alejandro; Schomerus, Georg

2015-01-01

In this meta-analysis, we review studies that compare mental and physical health-related quality of life measured with the Short-Form 36 of obese patients before and after bariatric surgery with a follow-up measure until one year. Twenty-one studies were selected to conduct the meta-analysis about the relationship between quality of life in obesity before (2680 subjects) and after (2251 subjects) bariatric surgery. Results reveal that obese patients scored less in the mental health component of the Short-Form 36 before bariatric surgery than after (d = -9.00). The same pattern could be observed in the case of the physical health component of the Short-Form 36 (d = -22.84). The results show the strong improvement that obese patients experience in both mental and physical components of the Short-Form 36 after receiving bariatric surgery.

[Extraction of evoked related potentials by using the combination of independent component analysis and wavelet analysis].

PubMed

Zou, Ling; Chen, Shuyue; Sun, Yuqiang; Ma, Zhenghua

2010-08-01

In this paper we present a new method of combining Independent Component Analysis (ICA) and Wavelet de-noising algorithm to extract Evoked Related Potentials (ERPs). First, the extended Infomax-ICA algorithm is used to analyze EEG signals and obtain the independent components (Ics); Then, the Wave Shrink (WS) method is applied to the demixed Ics as an intermediate step; the EEG data were rebuilt by using the inverse ICA based on the new Ics; the ERPs were extracted by using de-noised EEG data after being averaged several trials. The experimental results showed that the combined method and ICA method could remove eye artifacts and muscle artifacts mixed in the ERPs, while the combined method could retain the brain neural activity mixed in the noise Ics and could extract the weak ERPs efficiently from strong background artifacts.

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

NASA Astrophysics Data System (ADS)

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

2004-10-01

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

Principal Components Analysis of a JWST NIRSpec Detector Subsystem

NASA Technical Reports Server (NTRS)

Arendt, Richard G.; Fixsen, D. J.; Greenhouse, Matthew A.; Lander, Matthew; Lindler, Don; Loose, Markus; Moseley, S. H.; Mott, D. Brent; Rauscher, Bernard J.; Wen, Yiting;

Factor analysis of the Foreign Language Classroom Anxiety Scale in Korean learners of English as a foreign language.

PubMed

Park, Gi-Pyo

2014-08-01

This study examined the latent constructs of the Foreign Language Classroom Anxiety Scale (FLCAS) using two different groups of Korean English as a foreign language (EFL) university students. Maximum likelihood exploratory factor analysis with direct oblimin rotation was performed among the first group of 217 participants and produced two meaningful latent components in the FLCAS. The two components of the FLCAS were closely examined among the second group of 244 participants to find the extent to which the two components of the FLCAS fit the data. The model fit indexes showed that the two-factor model in general adequately fit the data. Findings of this study were discussed with the focus on the two components of the FLCAS, followed by future study areas to be undertaken to shed further light on the role of foreign language anxiety in L2 acquisition.

Evaluation of the split cantilever beam for Mode 3 delamination testing

NASA Technical Reports Server (NTRS)

Martin, Roderick H.

1989-01-01

A test rig for testing a thick split cantilever beam for scissoring delamination (mode 3) fracture toughness was developed. A 3-D finite element analysis was conducted on the test specimen to determine the strain energy release rate, G, distribution along the delamination front. The virtual crack closure technique was used to calculate the G components resulting from interlaminar tension, GI, interlaminar sliding shear, GII, and interlaminar tearing shear, GIII. The finite element analysis showed that at the delamination front no GI component existed, but a GII component was present in addition to a GIII component. Furthermore, near the free edges, the GII component was significantly higher than the GIII component. The GII/GIII ratio was found to increase with delamination length but was insensitive to the beam depth. The presence of GII at the delamination front was verified experimentally by examination of the failure surfaces. At the center of the beam, where the failure was in mode 3, there was significant fiber bridging. However, at the edges of the beam where the failure was in mode 3, there was no fiber bridging and mode 2 shear hackles were observed. Therefore, it was concluded that the split cantilever beam configuration does not represent a pure mode 3 test. The experimental work showed that the mode 2 fracture toughness, GIIc, must be less than the mode 3 fracture toughness, GIIIc. Therefore, a conservative approach to characterizing mode 3 delamination is to equate GIIIc to GIIc.

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.

Mass fingerprinting of the venom and transcriptome of venom gland of scorpion Centruroides tecomanus.

PubMed

Valdez-Velázquez, Laura L; Quintero-Hernández, Verónica; Romero-Gutiérrez, Maria Teresa; Coronas, Fredy I V; Possani, Lourival D

2013-01-01

Centruroides tecomanus is a Mexican scorpion endemic of the State of Colima, that causes human fatalities. This communication describes a proteome analysis obtained from milked venom and a transcriptome analysis from a cDNA library constructed from two pairs of venom glands of this scorpion. High perfomance liquid chromatography separation of soluble venom produced 80 fractions, from which at least 104 individual components were identified by mass spectrometry analysis, showing to contain molecular masses from 259 to 44,392 Da. Most of these components are within the expected molecular masses for Na(+)- and K(+)-channel specific toxic peptides, supporting the clinical findings of intoxication, when humans are stung by this scorpion. From the cDNA library 162 clones were randomly chosen, from which 130 sequences of good quality were identified and were clustered in 28 contigs containing, each, two or more expressed sequence tags (EST) and 49 singlets with only one EST. Deduced amino acid sequence analysis from 53% of the total ESTs showed that 81% (24 sequences) are similar to known toxic peptides that affect Na(+)-channel activity, and 19% (7 unique sequences) are similar to K(+)-channel especific toxins. Out of the 31 sequences, at least 8 peptides were confirmed by direct Edman degradation, using components isolated directly from the venom. The remaining 19%, 4%, 4%, 15% and 5% of the ESTs correspond respectively to proteins involved in cellular processes, antimicrobial peptides, venom components, proteins without defined function and sequences without similarity in databases. Among the cloned genes are those similar to metalloproteinases.

Noise characteristics in DORIS station positions time series derived from IGN-JPL, INASAN and CNES-CLS analysis centres

NASA Astrophysics Data System (ADS)

Khelifa, S.

2014-12-01

Using wavelet transform and Allan variance, we have analysed the solutions of weekly position residuals of 09 high latitude DORIS stations in STCD (STation Coordinate Difference) format provided from the three Analysis Centres : IGN-JPL (solution ign11wd01), INASAN (solution ina10wd01) and CNES-CLS (solution lca11wd02), in order to compare the spectral characteristics of their residual noise. The temporal correlations between the three solutions, two by two and station by station, for each component (North, East and Vertical) reveal a high correlation in the horizontal components (North and East). For the North component, the correlation average is about 0.88, 0.81 and 0.79 between, respectively, IGN-INA, IGN-LCA and INA-LCA solutions, then for the East component it is about 0.84, 0.82 and 0.76, respectively. However, the correlations for the Vertical component are moderate with an average of 0.64, 0.57 and 0.58 in, respectively, IGN-INA, IGN-LCA and INA-LCA solutions. After removing the trends and seasonal components from the analysed time series, the Allan variance analysis shows that the three solutions are dominated by a white noise in the all three components (North, East and Vertical). The wavelet transform analysis, using the VisuShrink method with soft thresholding, reveals that the noise level in the LCA solution is less important compared to IGN and INA solutions. Indeed, the standard deviation of the noise for the three components is in the range of 5-11, 5-12 and 4-9mm in the IGN, INA, and LCA solutions, respectively.

Effects of growing location on the production of main active components and antioxidant activity of Dasiphora fruticosa (L.) Rydb. by chemometric methods.

PubMed

Liu, Wei; Wang, Dongmei; Hou, Xiaogai; Yang, Yueqin; Xue, Xian; Jia, Qishi; Zhang, Lixia; Zhao, Wei; Yin, Dongxue

2018-05-17

Traditional Chinese medicine (TCM) plays a very important role in the health system of China. The content and activity of active component are main indexes that evaluate the quality of TCM, however they may vary with environmental factors in their growing locations. In this study, effects of environmental factors on the contents of active components and antioxidant activity of Dasiphora fruticosa from the five main production areas of China were investigated. The contents of tannin, total flavonoid and rutin were determined and varied within the range of 7.65-10.69%, 2.30-5.39% and 0.18-0.81%, respectively. Antioxidant activity was determined by DPPH assay, with the DPPH IC 50 values ranged from 8.791 to 32.534μg mL -1 . In order to further explore the cause of these significant geographical variations, the chemometric methods including correlation analysis, principal component analysis, gray correlation analysis, and path analysis were conducted. The results showed environmental factors had significant effect on the active component contents and antioxidant activity. Rapidly available phosphorus (RAP) and rapidly available nitrogen (RAN) were common dominant factors, and a significant positive correlation was observed between RAP and active components and antioxidant activity (P<0.05). Contributed by their high active components and strong antioxidant activity, Bange in Tibet and Geermu in Qinghai Province was selected as a favorable growing location, respectively. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

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

PubMed

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

2015-06-01

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

Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data.

PubMed

Excoffier, L; Smouse, P E; Quattro, J M

1992-06-01

We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-distances among all pairs of haplotypes. This analysis of molecular variance (AMOVA) produces estimates of variance components and F-statistic analogs, designated here as phi-statistics, reflecting the correlation of haplotypic diversity at different levels of hierarchical subdivision. The method is flexible enough to accommodate several alternative input matrices, corresponding to different types of molecular data, as well as different types of evolutionary assumptions, without modifying the basic structure of the analysis. The significance of the variance components and phi-statistics is tested using a permutational approach, eliminating the normality assumption that is conventional for analysis of variance but inappropriate for molecular data. Application of AMOVA to human mitochondrial DNA haplotype data shows that population subdivisions are better resolved when some measure of molecular differences among haplotypes is introduced into the analysis. At the intraspecific level, however, the additional information provided by knowing the exact phylogenetic relations among haplotypes or by a nonlinear translation of restriction-site change into nucleotide diversity does not significantly modify the inferred population genetic structure. Monte Carlo studies show that site sampling does not fundamentally affect the significance of the molecular variance components. The AMOVA treatment is easily extended in several different directions and it constitutes a coherent and flexible framework for the statistical analysis of molecular data.

The effect of hydraulic retention time on the performance and fouling characteristics of membrane sequencing batch reactors used for the treatment of synthetic petroleum refinery wastewater.

PubMed

Shariati, Seyed Ramin Pajoum; Bonakdarpour, Babak; Zare, Nasim; Ashtiani, Farzin Zokaee

2011-09-01

The use of membrane sequencing batch reactors, operated at HRT of 8, 16 and 24h, was considered for the treatment of a synthetic petroleum wastewater. Increase in HRT resulted in statistically significant decrease in MLSS. Removal efficiencies higher than 97% were found for the three model hydrocarbon pollutants at all HRTs, with air stripping making a small contribution to overall removal. Particle size distribution (PSD) and microscopic analysis showed reduction in the protozoan populations in the activated sludge with decreasing HRT. PSD analysis also showed a higher proportion of larger and smaller sized particles at the lowest HRT. The rate of membrane fouling was found to increase with decreasing HRT; SMP, especially carbohydrate SMP, and mixed liquor apparent viscosity also showed a pronounced increase with decreasing HRT, whereas the concentration of EPS and its components decreased. FTIR analysis identified organic compounds as the main component of membrane pore fouling. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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.

Characterization of atrazine binding to dissolved organic matter of soil under different types of land use.

PubMed

Zhu, Long-Ji; Zhao, Yue; Chen, Yan-Ni; Cui, Hong-Yang; Wei, Yu-Quan; Liu, Hai-Long; Chen, Xiao-Meng; Wei, Zi-Min

2018-01-01

Atrazine is widely used in agriculture. In this study, dissolved organic matter (DOM) from soils under four types of land use (forest (F), meadow (M), cropland (C) and wetland (W)) was used to investigate the binding characteristics of atrazine. Fluorescence excitation-emission matrix-parallel factor (EEM-PARAFAC) analysis, two-dimensional correlation spectroscopy (2D-COS) and Stern-Volmer model were combined to explore the complexation between DOM and atrazine. The EEM-PARAFAC indicated that DOM from different sources had different structures, and humic-like components had more obvious quenching effects than protein-like components. The Stern-Volmer model combined with correlation analysis showed that log K values of PARAFAC components had a significant correlation with the humification of DOM, especially for C3 component, and they were all in the same order as follows: meadow soil (5.68)>wetland soil (5.44)>cropland soil (5.35)>forest soil (5.04). The 2D-COS further confirmed that humic-like components firstly combined with atrazine followed by protein-like components. These findings suggest that DOM components can significantly influence the bioavailability, mobility and migration of atrazine in different land uses. Copyright © 2016 Elsevier Inc. All rights reserved.

The Circumplex Pattern of the Life Styles Inventory: A Reanalysis.

ERIC Educational Resources Information Center

Levin, Joseph

1991-01-01

A reanalysis of the intercorrelation matrix from a principal components analysis of the Life Styles Inventory was conducted using a Canadian sample. Using nonmetric multidimensional scaling, analyses show an almost perfect circumplex pattern. Results illustrate the inadequacy of factor analytic procedures for the analysis and representation of a…

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.

Explosive percolation on directed networks due to monotonic flow of activity

NASA Astrophysics Data System (ADS)

Waagen, Alex; D'Souza, Raissa M.; Lu, Tsai-Ching

2017-07-01

An important class of real-world networks has directed edges, and in addition, some rank ordering on the nodes, for instance the popularity of users in online social networks. Yet, nearly all research related to explosive percolation has been restricted to undirected networks. Furthermore, information on such rank-ordered networks typically flows from higher-ranked to lower-ranked individuals, such as follower relations, replies, and retweets on Twitter. Here we introduce a simple percolation process on an ordered, directed network where edges are added monotonically with respect to the rank ordering. We show with a numerical approach that the emergence of a dominant strongly connected component appears to be discontinuous. Large-scale connectivity occurs at very high density compared with most percolation processes, and this holds not just for the strongly connected component structure but for the weakly connected component structure as well. We present analysis with branching processes, which explains this unusual behavior and gives basic intuition for the underlying mechanisms. We also show that before the emergence of a dominant strongly connected component, multiple giant strongly connected components may exist simultaneously. By adding a competitive percolation rule with a small bias to link uses of similar rank, we show this leads to formation of two distinct components, one of high-ranked users, and one of low-ranked users, with little flow between the two components.

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

Using principal components analysis to explore competence and confidence in student nurses as users of information and communication technologies.

PubMed

Todhunter, Fern

2015-07-01

To report on the relationship between competence and confidence in nursing students as users of information and communication technologies, using principal components analysis. In nurse education, learning about and learning using information and communication technologies is well established. Nursing students are one of the undergraduate populations in higher education required to use these resources for academic work and practice learning. Previous studies showing mixed experiences influenced the choice of an exploratory study to find out about information and communication technologies competence and confidence. A 48-item survey questionnaire was administered to a volunteer sample of first- and second-year nursing students between July 2008-April 2009. The cohort ( N  =   375) represented 18·75% of first- and second-year undergraduates. A comparison between this work and subsequent studies reveal some similar ongoing issues and ways to address them. A principal components analysis (PCA) was carried out to determine the strength of the correlation between information and communication technologies competence and confidence. The aim was to show the presence of any underlying dimensions in the transformed data that would explain any variations in information and communication technologies competence and confidence. Cronbach's alpha values showed fair to good internal consistency. The five component structure gave medium to high results and explained 44·7% of the variance in the original data. Confidence had a high representation. The findings emphasized the shift towards social learning approaches for information and communication technologies. Informal social collaboration found favour with nursing students. Learning through talking, watching and listening all play a crucial role in the development of computing skills.

Cradle-to-Gate Impact Assessment of a High-Pressure Die-Casting Safety-Relevant Automotive Component

NASA Astrophysics Data System (ADS)

Cecchel, Silvia; Cornacchia, Giovanna; Panvini, Andrea

2016-09-01

The mass of automotive components has a direct influence on several aspects of vehicle performance, including both fuel consumption and tailpipe emissions, but the real environmental benefit has to be evaluated considering the entire life of the products with a proper life cycle assessment. In this context, the present paper analyzes the environmental burden connected to the production of a safety-relevant aluminum high-pressure die-casting component for commercial vehicles (a suspension cross-beam) considering all the phases connected to its manufacture. The focus on aluminum high-pressure die casting reflects the current trend of the industry and its high energy consumption. This work shows a new method that deeply analyzes every single step of the component's production through the implementation of a wide database of primary data collected thanks to collaborations of some automotive supplier companies. This energy analysis shows significant environmental benefits of aluminum recycling.

Effect of noise in principal component analysis with an application to ozone pollution

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

This thesis analyzes the effect of independent noise in principal components of k normally distributed random variables defined by a covariance matrix. We prove that the principal components as well as the canonical variate pairs determined from joint distribution of original sample affected by noise can be essentially different in comparison with those determined from the original sample. However when the differences between the eigenvalues of the original covariance matrix are sufficiently large compared to the level of the noise, the effect of noise in principal components and canonical variate pairs proved to be negligible. The theoretical results are supported by simulation study and examples. Moreover, we compare our results about the eigenvalues and eigenvectors in the two dimensional case with other models examined before. This theory can be applied in any field for the decomposition of the components in multivariate analysis. One application is the detection and prediction of the main atmospheric factor of ozone concentrations on the example of Albany, New York. Using daily ozone, solar radiation, temperature, wind speed and precipitation data, we determine the main atmospheric factor for the explanation and prediction of ozone concentrations. A methodology is described for the decomposition of the time series of ozone and other atmospheric variables into the global term component which describes the long term trend and the seasonal variations, and the synoptic scale component which describes the short term variations. By using the Canonical Correlation Analysis, we show that solar radiation is the only main factor between the atmospheric variables considered here for the explanation and prediction of the global and synoptic scale component of ozone. The global term components are modeled by a linear regression model, while the synoptic scale components by a vector autoregressive model and the Kalman filter. The coefficient of determination, R2, for the prediction of the synoptic scale ozone component was found to be the highest when we consider the synoptic scale component of the time series for solar radiation and temperature. KEY WORDS: multivariate analysis; principal component; canonical variate pairs; eigenvalue; eigenvector; ozone; solar radiation; spectral decomposition; Kalman filter; time series prediction

In Vivo Tibial Fit and Rotational Analysis of a Customized, Patient-Specific TKA versus Off-the-Shelf TKA.

PubMed

Schroeder, Lennart; Martin, Gregory

2018-05-25

In total knee arthroplasty (TKA), surgeons often face the decision of maximizing tibial component fit and achieving correct rotational alignment at the same time. Customized implants (CIMs) address this difficulty by aiming to replicate the anatomical joint structure, utilizing data from patient-specific knee geometry during the manufacturing. We intraoperatively compared component fit in four tibial zones of a CIM to that of three different off-the-shelf (OTS) TKA designs in 44 knees. Additionally, we assessed the rotational alignment of the tibia using computed tomography (CT)-based computer aided design model analysis. Overall the CIM device showed significantly better component fit than the OTS TKAs. While 18% of OTS designs presented an implant overhang of 3 mm or more, none of the CIM components did ( p  < 0.05). There was a larger percentage of CIMs seen with optimal fit (≤1 mm implant overhang to ≤1 mm tibial bone undercoverage) than in OTS TKAs. Also, OTS implants showed significantly more component underhang of ≥3 mm than the CIM design (37 vs. 18%). The rotational analysis revealed that 45% of the OTS tibial components showed a rotational deviation of more than 5 degrees and 4% of more than 10 degrees to a tibial rotational axis described by Cobb et al. No deviation was seen for the CIM, as the device is designed along this axis. Using the medial one-third of the tibial tubercle as the rotational landmark, 95% of the OTS trays demonstrated a rotational deviation of more than 5 degrees and 73% of more than 10 degrees compared with 73% of CIM tibial trays with more than 5 degrees and 27% with more than 10 degrees. Based on our findings, we believe that the CIM TKA provides both better rotational alignment and tibial fit without causing overhang of the tibial tray than the three examined OTS implants. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Multilayer neural networks for reduced-rank approximation.

PubMed

Diamantaras, K I; Kung, S Y

1994-01-01

This paper is developed in two parts. First, the authors formulate the solution to the general reduced-rank linear approximation problem relaxing the invertibility assumption of the input autocorrelation matrix used by previous authors. The authors' treatment unifies linear regression, Wiener filtering, full rank approximation, auto-association networks, SVD and principal component analysis (PCA) as special cases. The authors' analysis also shows that two-layer linear neural networks with reduced number of hidden units, trained with the least-squares error criterion, produce weights that correspond to the generalized singular value decomposition of the input-teacher cross-correlation matrix and the input data matrix. As a corollary the linear two-layer backpropagation model with reduced hidden layer extracts an arbitrary linear combination of the generalized singular vector components. Second, the authors investigate artificial neural network models for the solution of the related generalized eigenvalue problem. By introducing and utilizing the extended concept of deflation (originally proposed for the standard eigenvalue problem) the authors are able to find that a sequential version of linear BP can extract the exact generalized eigenvector components. The advantage of this approach is that it's easier to update the model structure by adding one more unit or pruning one or more units when the application requires it. An alternative approach for extracting the exact components is to use a set of lateral connections among the hidden units trained in such a way as to enforce orthogonality among the upper- and lower-layer weights. The authors call this the lateral orthogonalization network (LON) and show via theoretical analysis-and verify via simulation-that the network extracts the desired components. The advantage of the LON-based model is that it can be applied in a parallel fashion so that the components are extracted concurrently. Finally, the authors show the application of their results to the solution of the identification problem of systems whose excitation has a non-invertible autocorrelation matrix. Previous identification methods usually rely on the invertibility assumption of the input autocorrelation, therefore they can not be applied to this case.

DREEM on: validation of the Dundee Ready Education Environment Measure in Pakistan.

PubMed

Khan, Junaid Sarfraz; Tabasum, Saima; Yousafzai, Usman Khalil; Fatima, Mehreen

2011-09-01

To validate DREEM in medical education environment of Punjab, Pakistan. The DREEM questionnaire was anonymously collected from Final year Baccalaureate of Medicine; Baccalaureate of Surgery students in the private and public medical colleges affiliated with the University of Health Sciences, Lahore. Data was analyzed using Principal Component Analysis with Varimax Rotation. The response rate was 84.14 %. The average DREEM score was 125. Confirmatory and Exploratory Factor Analysis was applied under the conditions of eigenvalues >1 and loadings > or = 0.3. In CONFIRMATORY FACTOR ANALYSIS, Five components were extracted accounting for 40.10% of variance and in EXPLORATORY FACTOR ANALYSIS, Ten components were extracted accounting for 52.33% of variance. Total 50 items had internal consistency reliability of 0.91 (Cronbach's Alpha). The value of Spearman-Brown was 0.868 showing the reliability of the analysis. In both analyses the subscales produced were sensible but the mismatch from the original was largely due to the English-Pakistan contextual and cultural differences. DREEM is a generic instrument that will do well with regional modifications to suit individual, contextual and cultural settings.

Loss of switch/sucrose non-fermenting complex protein expression is associated with dedifferentiation in endometrial carcinomas.

PubMed

Karnezis, Anthony N; Hoang, Lien N; Coatham, Mackenzie; Ravn, Sarah; Almadani, Noorah; Tessier-Cloutier, Basile; Irving, Julie; Meng, Bo; Li, Xiaodong; Chow, Christine; McAlpine, Jessica; Kuo, Kuan-Ting; Mao, Tsui-Lien; Djordjevic, Bojana; Soslow, Robert A; Huntsman, David G; Blake Gilks, C; Köbel, Martin; Lee, Cheng-Han

2016-03-01

Dedifferentiated endometrial carcinoma is an aggressive type of endometrial cancer that contains a mix of low-grade endometrioid and undifferentiated carcinoma components. We performed targeted sequencing of eight dedifferentiated carcinomas and identified somatic frameshift/nonsense mutations in SMARCA4, a core ATPase of the switch/sucrose non-fermenting (SWI/SNF) complex, in the undifferentiated components of four tumors. Immunohistochemical analysis confirmed the loss of SMARCA4 in the undifferentiated component of these four SMARCA4-mutated cases, whereas the corresponding low-grade endometrioid component showed retained SMARCA4 expression. An expanded survey of other members of the SWI/SNF complex showed SMARCB1 loss in the undifferentiated component of two SMARCA4-intact tumors, and all SMARCA4- or SMARCB1-deficient tumors showed concomitant loss of expression of SMARCA2. We subsequently examined the expression of SMARCA2, SMARCA4, and SMARCB1 in an additional set of 22 centrally reviewed dedifferentiated carcinomas and 31 grade 3 endometrioid carcinomas. Combining the results from the index and the expansion set, 15 of 30 (50%) of the dedifferentiated carcinomas examined showed either concurrent SMARCA4 and SMARCA2 loss (37%) or concurrent SMARCB1 and SMARCA2 loss (13%) in the undifferentiated component. The loss of SMARCA4 or SMARCB1 was mutually exclusive. All 31 grade 3 endometrioid carcinomas showed intact expression of these core SWI/SNF proteins. The majority (73%) of the SMARCA4/SMARCA2-deficient and half of SMARCB1/SMARCA2-deficient undifferentiated component developed in a mismatch repair-deficient molecular context. The observed spatial association between SWI/SNF protein loss and histologic dedifferentiation suggests that inactivation of these core SWI/SNF proteins may contribute to the development of dedifferentiated endometrial carcinoma.

Machine learning of frustrated classical spin models. I. Principal component analysis

NASA Astrophysics Data System (ADS)

Wang, Ce; Zhai, Hui

2017-10-01

This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.

Clustering of immunological, metabolic and genetic features in latent autoimmune diabetes in adults: evidence from principal component analysis.

PubMed

Pes, Giovanni Mario; Delitala, Alessandro Palmerio; Errigo, Alessandra; Delitala, Giuseppe; Dore, Maria Pina

2016-06-01

Latent autoimmune diabetes in adults (LADA) which accounts for more than 10 % of all cases of diabetes is characterized by onset after age 30, absence of ketoacidosis, insulin independence for at least 6 months, and presence of circulating islet-cell antibodies. Its marked heterogeneity in clinical features and immunological markers suggests the existence of multiple mechanisms underlying its pathogenesis. The principal component (PC) analysis is a statistical approach used for finding patterns in data of high dimension. In this study the PC analysis was applied to a set of variables from a cohort of Sardinian LADA patients to identify a smaller number of latent patterns. A list of 11 variables including clinical (gender, BMI, lipid profile, systolic and diastolic blood pressure and insulin-free time period), immunological (anti-GAD65, anti-IA-2 and anti-TPO antibody titers) and genetic features (predisposing gene variants previously identified as risk factors for autoimmune diabetes) retrieved from clinical records of 238 LADA patients referred to the Internal Medicine Unit of University of Sassari, Italy, were analyzed by PC analysis. The predictive value of each PC on the further development of insulin dependence was evaluated using Kaplan-Meier curves. Overall 4 clusters were identified by PC analysis. In component PC-1, the dominant variables were: BMI, triglycerides, systolic and diastolic blood pressure and duration of insulin-free time period; in PC-2: genetic variables such as Class II HLA, CTLA-4 as well as anti-GAD65, anti-IA-2 and anti-TPO antibody titers, and the insulin-free time period predominated; in PC-3: gender and triglycerides; and in PC-4: total cholesterol. These components explained 18, 15, 12, and 12 %, respectively, of the total variance in the LADA cohort. The predictive power of insulin dependence of the four components was different. PC-2 (characterized mostly by high antibody titers and presence of predisposing genetic markers) showed a faster beta-cells failure and PC-3 (characterized mostly by gender and high triglycerides) and PC-4 (high cholesterol) showed a slower beta-cells failure. PC-1 (including dislipidemia and other metabolic dysfunctions), showed a mild beta-cells failure. In conclusion variable clustering might be consistent with different pathogenic pathways and/or distinct immune mechanisms in LADA and could potentially help physicians improve the clinical management of these patients.

Synthesis and characterization of a new photoluminescent material, tris-[1-10 phenanthroline] aluminium

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

Kumar, Rahul, E-mail: id-kumarrahul003@gmail.com; Bhargava, Parag; Dvivedi, Avanish

A new photoluminescent material namely tris-[1-10 Phenanthroline] Aluminium Al(Phen){sub 3} has been synthesized and characterized. This material was characterized by fourier transform infrared spectroscopy (FTIR),nuclear magnetic resonance (NMR),mass spectroscopy, thermal gravimetric analysis (TGA),ultraviolet-visible spectroscopy(UV) and photoluminescence (PL). This material shows thermal stability up to 300°C. This material showed absorption maxima at 352nm which may be attributed to the moderate energy (π–π{sup *}) transition. Photoluminescence spectra for this material showed the most intense peak at 423 nm and the time resolved photoluminescence spectra showed two life time components. The decay times of the first and second component were 1.4ns and 4.8 ns respectively.

Identification of periodical components in a signal. Role of the chronological arrangement of observations (French Title: Recherche des composantes périodiques dans un signal. Importance de la répartition chronologique des observations)

NASA Astrophysics Data System (ADS)

Hoynant, G.

2007-12-01

Fourier analysis allows to identify periodical components in a time series of measurements under the form of a spectrum of the periodical components mathematically included in the series. The reading of a spectrum is often delicate and contradictory interpretations can be presented in some cases as for the luminosity of Seyfert galaxy NGC 4151 despite the very large number of observations since 1968. The present study identifies the causes of these difficulties thanks to an experimental approach based on analysis of synthetic series with one periodic component only. The total duration of the campaign must be long as compared to the periods to be identified: this ratio governs the separation capability of the spectral analysis. A large number of observations is obviously favourable but the intervals between measurements are not critical : the analysis can accommodate intervals significantly longer than the periods to be identified. But interruptions along the campaign, with separate sessions of observations, make the physical understanding of the analysis difficult and sometimes impossible. An analysis performed on an imperfect series shows peaks which are not significant of the signal itself but of the chronological distribution of the measurements. These chronological peaks are becoming numerous and important when there are vacancy periods in the campaign. A method for authentication of a peak as a peak of the signal is to cut the chronological series in pieces with the same length than the period to identify and to superpose all these pieces. The present study shows that some chronological peaks can exhibit superposition graphics almost as clear as those for the signal peaks. Practically, the search for periodical components necessitates to organise the campaign specifically with a neutral chronological distribution of measurements without vacancies and the authentication of a peak as a peak of the signal requires a dominating amplitude or a graphic of periodical superposition significantly clearer than for any peak with a comparable or bigger amplitude.

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.

Ad hoc Laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Ma, Zongfeng; Shen, Jingshi

2016-03-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Ad hoc laser networks component technology for modular spacecraft

NASA Astrophysics Data System (ADS)

Huang, Xiujun; Shi, Dele; Shen, Jingshi

2017-10-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Multivariate Statistical Analysis: a tool for groundwater quality assessment in the hidrogeologic region of the Ring of Cenotes, Yucatan, Mexico.

NASA Astrophysics Data System (ADS)

Ye, M.; Pacheco Castro, R. B.; Pacheco Avila, J.; Cabrera Sansores, A.

2014-12-01

The karstic aquifer of Yucatan is a vulnerable and complex system. The first fifteen meters of this aquifer have been polluted, due to this the protection of this resource is important because is the only source of potable water of the entire State. Through the assessment of groundwater quality we can gain some knowledge about the main processes governing water chemistry as well as spatial patterns which are important to establish protection zones. In this work multivariate statistical techniques are used to assess the groundwater quality of the supply wells (30 to 40 meters deep) in the hidrogeologic region of the Ring of Cenotes, located in Yucatan, Mexico. Cluster analysis and principal component analysis are applied in groundwater chemistry data of the study area. Results of principal component analysis show that the main sources of variation in the data are due sea water intrusion and the interaction of the water with the carbonate rocks of the system and some pollution processes. The cluster analysis shows that the data can be divided in four clusters. The spatial distribution of the clusters seems to be random, but is consistent with sea water intrusion and pollution with nitrates. The overall results show that multivariate statistical analysis can be successfully applied in the groundwater quality assessment of this karstic aquifer.

Variation of gunshot injury patterns in mortality associated with human rights abuses and armed conflict: an exploratory study.

PubMed

Baraybar, Jose Pablo

2015-09-01

The analysis of the distribution of gunshot injuries in a sample of 777 sets of human remains of proven human rights abuse from Somaliland, the Balkans and Peru is compared to frequencies of injuries sustained by combatants in contemporary conflicts reported in the literature. Principal Component Analysis (PCA) reduced the data to three components accounting for 82.94% of the variance. The first component with 38.31% of variance shows segments Arms and thorax/abdomen to be positively correlated (0.887 and 0.662, respectively); the segment head/neck is strongly correlated (0.951) to the second component while the segment thorax/abdomen shows a low, negative correlation (-0.388). Finally in the third component only the legs are strongly correlated (0.991). Data was further subjected to a K-means cluster analysis to determine the likely groupings combining the four types of injuries. Each of the three clusters reproduced similar patterns observed in the PCA: Cluster 1 shows the prevalence of injuries to the thorax/abdomen and extremities in addition to injuries to the head/neck; Cluster 2 shows injuries to the head/neck and Cluster 3 injuries to the thorax/abdomen and a lower representation of the arms and legs. Most of the cases (70.5%), irrespective of geography and type of site (attack or detention), were grouped into Cluster 2. Such comparison shows that in human rights abuse, irrespective of their geography, gunshot injuries tend to follow a pattern favouring the head/neck and thorax/abdomen areas over the extremities, the reverse pattern observed in contemporary combat operations. In those settings gunshot wound trauma is the second cause of mortality/morbidity (after fragmenting ammunition) and its distribution concentrates on the extremities, thorax/abdomen and head; following the pattern of protective armour when it is used. Considering that human rights abuses are often presented as encounters between two armed groups in the context of counter-insurgency operations, a careful analysis of gunshot injury patterns could serve as an indicator that in fact murder, rather than combat, took place and the intention was to kill rather than to maim or render people unfit for battle. To compare the variation of gunshot injury patterns between mortality associated with human rights abuses and armed conflict in selected samples from different countries. Literature review and case analysis. Original statistical analysis of gunshot injuries on human remains (n=777) recovered from mass or clandestine graves associated with human rights abuses in countries in Somaliland, the Balkans and Peru (1983-1995) and literature review of mortality caused by armed conflicts. Mechanism of gunshot injury and wound distribution pattern in geographically diverse samples of human rights abuse. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

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.

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.

Major and trace element chemistry of Luna 24 samples from Mare Crisium

NASA Technical Reports Server (NTRS)

Blanchard, D. P.; Brannon, J. C.; Aaboe, E.; Budahn, J. R.

1978-01-01

Atomic absorption spectrometry and instrumental neutron activation analysis were employed to analyze six Luna 24 soils for major and trace elements. The analysis revealed well-mixed soils, though size fractions of each of the soils showed quite dissimilar compositions. Thus the regolith apparently has not been extensively reworked. Noritic breccia admixed preferentially to the finest size fractions and differential comminution of one or more other soil components accounted for the observed elemental distributions as a function of grain size. The ferrobasalt composition and one or more components with higher MgO contents have been identified in the samples.

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 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

Fetal ECG extraction using independent component analysis by Jade approach

NASA Astrophysics Data System (ADS)

Giraldo-Guzmán, Jader; Contreras-Ortiz, Sonia H.; Lasprilla, Gloria Isabel Bautista; Kotas, Marian

2017-11-01

Fetal ECG monitoring is a useful method to assess the fetus health and detect abnormal conditions. In this paper we propose an approach to extract fetal ECG from abdomen and chest signals using independent component analysis based on the joint approximate diagonalization of eigenmatrices approach. The JADE approach avoids redundancy, what reduces matrix dimension and computational costs. Signals were filtered with a high pass filter to eliminate low frequency noise. Several levels of decomposition were tested until the fetal ECG was recognized in one of the separated sources output. The proposed method shows fast and good performance.

Molecular Analysis of Mixed Endometrial Carcinomas Shows Clonality in Most Cases.

PubMed

Köbel, Martin; Meng, Bo; Hoang, Lien N; Almadani, Noorah; Li, Xiaodong; Soslow, Robert A; Gilks, C Blake; Lee, Cheng-Han

2016-02-01

Mixed endometrial carcinoma refers to a tumor that comprises 2 or more distinct histotypes. We studied 18 mixed-type endometrial carcinomas-11 mixed serous and low-grade endometrioid carcinomas (SC/EC), 5 mixed clear cell and low-grade ECs (CCC/EC), and 2 mixed CCC and SCs (CCC/SC), using targeted next-generation sequencing and immunohistochemistry to compare the molecular profiles of the different histotypes present in each case. In 16 of 18 cases there was molecular evidence that both components shared a clonal origin. Eight cases (6 EC/SC, 1 EC/CCC, and 1 SC/CCC) showed an SC molecular profile that was the same in both components. Five cases (3 CCC/EC and 2 SC/EC) showed a shared endometrioid molecular profile and identical mismatch-repair protein deficiency in both components. A single SC/EC case harbored the same POLE exonuclease domain mutation in both components. One SC/CCC and 1 EC/CCC case showed both shared and unique molecular features in the 2 histotype components, suggesting early molecular divergence from a common clonal origin. In 2 cases, there were no shared molecular features, and these appear to be biologically unrelated synchronous tumors. Overall, these results show that the different histologic components in mixed endometrial carcinomas typically share the same molecular aberrations. Mixed endometrial carcinomas most commonly occur through morphologic mimicry, whereby tumors with serous-type molecular profile show morphologic features of EC or CCC, or through underlying deficiency in DNA nucleotide repair, with resulting rapid accrual of mutations and intratumoral phenotypic heterogeneity. Less commonly, mixed endometrial carcinomas are the result of early molecular divergence from a common progenitor clone or are synchronous biologically unrelated tumors (collision tumors).

Molecular analysis of mixed endometrial carcinomas shows clonality in most cases

PubMed Central

Hoang, Lien N.; Almadani, Noorah; Li, Xiaodong; Soslow, Robert A; Gilks, C. Blake; Lee, Cheng-Han

2016-01-01

Mixed endometrial carcinoma refers to a tumor that is comprised of two or more distinct histotypes. We studied 18 mixed-type endometrial carcinomas - 11 mixed serous and low-grade endometrioid carcinomas (SC/EC), 5 mixed clear cell and low-grade endometrioid carcinomas (CCC/EC), and 2 mixed clear cell and serous carcinoma (CCC/SC), using targeted next generation sequencing and immunohistochemistry to compare the molecular profiles of the different histotypes present in each case. In 16 of 18 cases there was molecular evidence that both components shared a clonal origin. Eight cases (6 EC/SC, 1 EC/CCC and 1 SC/CCC) showed a serous carcinoma molecular profile that was the same in both components. Five cases (3 CCC/EC and 2 SC/EC) showed a shared endometrioid molecular profile and identical mismatch repair protein (MMR) deficiency in both components. A single SC/EC case harbored the same POLE exonuclease domain mutation in both components. One SC/CCC and one EC/CCC case showed both shared and unique molecular features in the two histotype components, suggesting early molecular divergence from a common clonal origin. In two cases, there were no shared molecular features and these appear to be biologically unrelated synchronous tumors. Overall, these results show that the different histologic components in mixed endometrial carcinomas typically share the same molecular aberrations. Mixed endometrial carcinomas most commonly occur through morphological mimicry, whereby tumors with serous-type molecular profile show morphological features of endometrioid or clear cell carcinoma, or through underlying deficiency in DNA nucleotide repair, with resulting rapid accrual of mutations and intratumoral phenotypic heterogeneity. Less commonly, mixed endometrial carcinomas are the result of early molecular divergence from a common progenitor clone or are synchronous biologically unrelated tumors (collision tumors). PMID:26492180

Resolving the variability of CDOM fluorescence to differentiate the sources and fate of DOM in Lake Taihu and its tributaries.

PubMed

Yao, Xin; Zhang, Yunlin; Zhu, Guangwei; Qin, Boqiang; Feng, Longqing; Cai, Linlin; Gao, Guang

2011-01-01

Taihu Basin is the most developed area in China, which economic development has resulted in pollutants being produced and discharged into rivers and the lake. Lake Taihu is located in the center of the basin, which is characterized by a complex network of rivers and channels. To assess the sources and fate of dissolved organic matter (DOM) in surface waters, we determined the components and abundance of chromophoric dissolved organic matter (CDOM) within Lake Taihu and 66 of its tributaries, and 22 sites along transects from two main rivers. In Lake Taihu, there was a relative less spatial variation in CDOM absorption a(CDOM)(355) with a mean of 2.46 ± 0.69 m⁻¹ compared to the mean of 3.36 ± 1.77 m⁻¹ in the rivers. Two autochthonous tryptophan-like components (C1 and C5), two humic-like components (C2 and C3), and one autochthonous tyrosine-like component (C4) were identified using the parallel factor analysis (PARAFAC) model. The C2 and C3 had a direct relationship with a(CDOM)(355), dissolved organic carbon (DOC), and chemical oxygen demand (COD). The separation of lake samples from river samples, on both axes of the Principal Component Analysis (PCA), showed the difference in DOM fluorophores between these various environments. Components C1 and C5 concurrently showed positive factor 1 loadings, while C4 was close to the negative factor 1 axis. Components C2 and C3 showed positive second factor loadings. The major contribution of autochthonous tryptophan-like components to lake samples is due to the autochthonous production of CDOM in the lake ecosystems. The results also showed that the differences in geology and associated land use control CDOM dynamics, such as the high levels of CDOM with terrestrial characteristics in the northwestern upstream rivers and low levels of CDOM with increased microbial characteristics in the southwestern upstream rivers. Most of river samples from the downstream regions in the eastern and southeastern plains had a similar relative abundance of humic-like fluorescence, with less of the tryptophan-like and more of the tyrosine-like contributions than did samples from upstream regions. Copyright © 2010 Elsevier Ltd. All rights reserved.

Craniometric relationships among medieval Central European populations: implications for Croat migration and expansion.

PubMed

Slaus, Mario; Tomicić, Zeljko; Uglesić, Ante; Jurić, Radomir

2004-08-01

To determine the ethnic composition of the early medieval Croats, the location from which they migrated to the east coast of the Adriatic, and to separate early medieval Croats from Bijelo brdo culture members, using principal components analysis and discriminant function analysis of craniometric data from Central and South-East European medieval archaeological sites. Mean male values for 8 cranial measurements from 39 European and 5 Iranian sites were analyzed by principal components analysis. Raw data for 17 cranial measurements for 103 female and 112 male skulls were used to develop discriminant functions. The scatter-plot of the analyzed sites on the first 2 principal components showed a pattern of intergroup relationships consistent with geographical and archaeological information not included in the data set. The first 2 principal components separated the sites into 4 distinct clusters: Avaroslav sites west of the Danube, Avaroslav sites east of the Danube, Bijelo brdo sites, and Polish sites. All early medieval Croat sites were located in the cluster of Polish sites. Two discriminant functions successfully differentiated between early medieval Croats and Bijelo brdo members. Overall accuracies were high -- 89.3% for males, and 97.1% for females. Early medieval Croats seem to be of Slavic ancestry, and at one time shared a common homeland with medieval Poles. Application of unstandardized discriminant function coefficients to unclassified crania from 18 sites showed an expansion of early medieval Croats into continental Croatia during the 10th to 13th century.

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.

Effect of scene illumination conditions on digital enhancement techniques of multispectral scanner LANDSAT images

NASA Technical Reports Server (NTRS)

Parada, N. D. J.; Novo, E. M. L. M.

1983-01-01

Two sets of MSS/LANDSAT data with solar elevation ranging from 22 deg to 41 deg were used at the Image-100 System to implement the Eliason et alii technique for extracting the topographic modulation component. An unsupervised cluster analysis was used to obtain an average brightness image for each channel. Analysis of the enhanced imaged shows that the technique for extracting topographic modulation component is more appropriated to MSS data obtained under high sun elevation ngles. Low sun elevation increases the variance of each cluster so that the average brightness doesn't represent its albedo proprties. The topographic modulation component applied to low sun elevation angle damages rather than enhance topographic information. Better results were produced for channels 4 and 5 than for channels 6 and 7.

Generation mechanisms of fundamental rogue wave spatial-temporal structure.

PubMed

Ling, Liming; Zhao, Li-Chen; Yang, Zhan-Ying; Guo, Boling

2017-08-01

We discuss the generation mechanism of fundamental rogue wave structures in N-component coupled systems, based on analytical solutions of the nonlinear Schrödinger equation and modulational instability analysis. Our analysis discloses that the pattern of a fundamental rogue wave is determined by the evolution energy and growth rate of the resonant perturbation that is responsible for forming the rogue wave. This finding allows one to predict the rogue wave pattern without the need to solve the N-component coupled nonlinear Schrödinger equation. Furthermore, our results show that N-component coupled nonlinear Schrödinger systems may possess N different fundamental rogue wave patterns at most. These results can be extended to evaluate the type and number of fundamental rogue wave structure in other coupled nonlinear systems.

An efficient classification method based on principal component and sparse representation.

PubMed

Zhai, Lin; Fu, Shujun; Zhang, Caiming; Liu, Yunxian; Wang, Lu; Liu, Guohua; Yang, Mingqiang

2016-01-01

As an important application in optical imaging, palmprint recognition is interfered by many unfavorable factors. An effective fusion of blockwise bi-directional two-dimensional principal component analysis and grouping sparse classification is presented. The dimension reduction and normalizing are implemented by the blockwise bi-directional two-dimensional principal component analysis for palmprint images to extract feature matrixes, which are assembled into an overcomplete dictionary in sparse classification. A subspace orthogonal matching pursuit algorithm is designed to solve the grouping sparse representation. Finally, the classification result is gained by comparing the residual between testing and reconstructed images. Experiments are carried out on a palmprint database, and the results show that this method has better robustness against position and illumination changes of palmprint images, and can get higher rate of palmprint recognition.

A stable systemic risk ranking in China's banking sector: Based on principal component analysis

NASA Astrophysics Data System (ADS)

Fang, Libing; Xiao, Binqing; Yu, Honghai; You, Qixing

2018-02-01

In this paper, we compare five popular systemic risk rankings, and apply principal component analysis (PCA) model to provide a stable systemic risk ranking for the Chinese banking sector. Our empirical results indicate that five methods suggest vastly different systemic risk rankings for the same bank, while the combined systemic risk measure based on PCA provides a reliable ranking. Furthermore, according to factor loadings of the first component, PCA combined ranking is mainly based on fundamentals instead of market price data. We clearly find that price-based rankings are not as practical a method as fundamentals-based ones. This PCA combined ranking directly shows systemic risk contributions of each bank for banking supervision purpose and reminds banks to prevent and cope with the financial crisis in advance.

Online signature recognition using principal component analysis and artificial neural network

NASA Astrophysics Data System (ADS)

Hwang, Seung-Jun; Park, Seung-Je; Baek, Joong-Hwan

2016-12-01

In this paper, we propose an algorithm for on-line signature recognition using fingertip point in the air from the depth image acquired by Kinect. We extract 10 statistical features from X, Y, Z axis, which are invariant to changes in shifting and scaling of the signature trajectories in three-dimensional space. Artificial neural network is adopted to solve the complex signature classification problem. 30 dimensional features are converted into 10 principal components using principal component analysis, which is 99.02% of total variances. We implement the proposed algorithm and test to actual on-line signatures. In experiment, we verify the proposed method is successful to classify 15 different on-line signatures. Experimental result shows 98.47% of recognition rate when using only 10 feature vectors.

Analysis of near-field components of a plasmonic optical antenna and their contribution to quantum dot infrared photodetector enhancement.

PubMed

Gu, Guiru; Vaillancourt, Jarrod; Lu, Xuejun

2014-10-20

In this paper, we analyze near-field vector components of a metallic circular disk array (MCDA) plasmonic optical antenna and their contribution to quantum dot infrared photodetector (QDIP) enhancement. The near-field vector components of the MCDA optical antenna and their distribution in the QD active region are simulated. The near-field overlap integral with the QD active region is calculated at different wavelengths and compared with the QDIP enhancement spectrum. The x-component (E(x)) of the near-field vector shows a larger intensity overlap integral and stronger correlation with the QDIP enhancement than E(z) and thus is determined to be the major near-field component to the QDIP enhancement.

Rapid Elemental Analysis and Provenance Study of Blumea balsamifera DC Using Laser-Induced Breakdown Spectroscopy

PubMed Central

Liu, Xiaona; Zhang, Qiao; Wu, Zhisheng; Shi, Xinyuan; Zhao, Na; Qiao, Yanjiang

2015-01-01

Laser-induced breakdown spectroscopy (LIBS) was applied to perform a rapid elemental analysis and provenance study of Blumea balsamifera DC. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were implemented to exploit the multivariate nature of the LIBS data. Scores and loadings of computed principal components visually illustrated the differing spectral data. The PLS-DA algorithm showed good classification performance. The PLS-DA model using complete spectra as input variables had similar discrimination performance to using selected spectral lines as input variables. The down-selection of spectral lines was specifically focused on the major elements of B. balsamifera samples. Results indicated that LIBS could be used to rapidly analyze elements and to perform provenance study of B. balsamifera. PMID:25558999

Early Literacy and Numeracy Skills in Bilingual Minority Children: Toward a Relative Independence of Linguistic and Numerical Processing

PubMed Central

Bonifacci, Paola; Tobia, Valentina; Bernabini, Luca; Marzocchi, Gian Marco

2016-01-01

Many studies have suggested that the concept of “number” is relatively independent from linguistic skills, although an increasing number of studies suggest that language abilities may play a pivotal role in the development of arithmetic skills. The condition of bilingualism can offer a unique perspective into the role of linguistic competence in numerical development. The present study was aimed at evaluating the relationship between language skills and early numeracy through a multilevel investigation in monolingual and bilingual minority children attending preschool. The sample included 156 preschool children. Of these, 77 were bilingual minority children (mean age = 58.27 ± 5.90), and 79 were monolinguals (mean age = 58.45 ± 6.03). The study focused on three levels of analysis: group differences in language and number skills, concurrent linguistic predictors of early numeracy and, finally, profile analysis of linguistic skills in children with impaired vs. adequate numeracy skills. The results showed that, apart from the expected differences in linguistic measures, bilinguals differed from monolinguals in numerical skills with a verbal component, such as semantic knowledge of digits, but they did not differ in a pure non-verbal component such as quantity comparison. The multigroup structural equation model indicated that letter knowledge was a significant predictor of the verbal component of numeracy for both groups. Phonological awareness was a significant predictor of numeracy skills only in the monolingual group. Profile analysis showed that children with a selective weakness in the non-verbal component of numeracy had fully adequate verbal skills. Results from the present study suggest that only some specific components of language competence predict numerical processing, although linguistic proficiency may not be a prerequisite for developing adequate early numeracy skills. PMID:27458413

Macrophage biospecific extraction and HPLC-ESI-MSn analysis for screening immunological active components in Smilacis Glabrae Rhizoma.

PubMed

Zheng, Zhao-Guang; Duan, Ting-Ting; He, Bao; Tang, Dan; Jia, Xiao-Bin; Wang, Ru-Shang; Zhu, Jia-Xiao; Xu, You-Hua; Zhu, Quan; Feng, Liang

2013-04-15

A cell-permeable membrane, as typified by Transwell insert Permeable Supports, permit accurate repeatable invasion assays, has been developed as a tool for screening immunological active components in Smilacis Glabrae Rhizoma (SGR). In this research, components in the water extract of SGR (ESGR) might conjugate with the receptors or other targets on macrophages which invaded Transwell inserts, and then the eluate which contained components biospecific binding to macrophages was identified by HPLC-ESI-MS(n) analysis. Six compounds, which could interact with macrophages, were detected and identified. Among these compounds, taxifolin (2) and astilbin (4) were identified by comparing with the chromatography of standards, while the four others including 5-O-caffeoylshikimic acid (1), neoastilbin (3), neoisoastilbin (5) and isoastilbin (6), were elucidated by their structure clearage characterizations of tandem mass spectrometry. Then compound 1 was isolated and purified from SGR, along with 2 and 4, was applied to the macrophage migration and adhesion assay in HUVEC (Human Umbilical Vein Endothelial Cells) -macrophages co-incultured Transwell system for immunological activity assessment. The results showed that compounds 1, 2 and 4 with concentration of 5μM (H), 500nM (M) and 50nM (L) could remarkably inhibit the macrophage migration and adhesion (Vs AGEs (Advanced Glycation End Produces) group, 1-L, 2-H and 4-L groups: p<0.05; other groups: p<0.01). Moreover, 1 and 4 showed satisfactory dose-effect relationship. In conclusion, the application of macrophage biospecific extraction coupled with HPLC-ESI-MS(n) analysis is a rapid, simple and reliable method for screening immunological active components from Traditional Chinese Medicine. Copyright © 2013 Elsevier B.V. All rights reserved.

Early Literacy and Numeracy Skills in Bilingual Minority Children: Toward a Relative Independence of Linguistic and Numerical Processing.

PubMed

Bonifacci, Paola; Tobia, Valentina; Bernabini, Luca; Marzocchi, Gian Marco

2016-01-01

Many studies have suggested that the concept of "number" is relatively independent from linguistic skills, although an increasing number of studies suggest that language abilities may play a pivotal role in the development of arithmetic skills. The condition of bilingualism can offer a unique perspective into the role of linguistic competence in numerical development. The present study was aimed at evaluating the relationship between language skills and early numeracy through a multilevel investigation in monolingual and bilingual minority children attending preschool. The sample included 156 preschool children. Of these, 77 were bilingual minority children (mean age = 58.27 ± 5.90), and 79 were monolinguals (mean age = 58.45 ± 6.03). The study focused on three levels of analysis: group differences in language and number skills, concurrent linguistic predictors of early numeracy and, finally, profile analysis of linguistic skills in children with impaired vs. adequate numeracy skills. The results showed that, apart from the expected differences in linguistic measures, bilinguals differed from monolinguals in numerical skills with a verbal component, such as semantic knowledge of digits, but they did not differ in a pure non-verbal component such as quantity comparison. The multigroup structural equation model indicated that letter knowledge was a significant predictor of the verbal component of numeracy for both groups. Phonological awareness was a significant predictor of numeracy skills only in the monolingual group. Profile analysis showed that children with a selective weakness in the non-verbal component of numeracy had fully adequate verbal skills. Results from the present study suggest that only some specific components of language competence predict numerical processing, although linguistic proficiency may not be a prerequisite for developing adequate early numeracy skills.

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.

Analysis of Floral Volatile Components and Antioxidant Activity of Different Varieties of Chrysanthemum morifolium.

PubMed

Yang, Lu; Cheng, Ping; Wang, Jin-Hui; Li, Hong

2017-10-23

This study investigated the volatile flavor compounds and antioxidant properties of the essential oil of chrysanthemums that was extracted from the fresh flowers of 10 taxa of Chrysanthemum morifolium from three species; namely Dendranthema morifolium (Ramat.) Yellow, Dendranthema morifolium (Ramat.) Red, Dendranthema morifolium (Ramat.) Pink, Dendranthema morifolium (Ramat.) White, Pericallis hybrid Blue, Pericallis hybrid Pink, Pericallis hybrid Purple, Bellis perennis Pink, Bellis perennis Yellow, and Bellis perennis White. The antioxidant capacity of the essential oil was assayed by spectrophotometric analysis. The volatile flavor compounds from the fresh flowers were collected using dynamic headspace collection, analyzed using auto thermal desorber-gas chromatography/mass spectrometry, and identified with quantification using the external standard method. The antioxidant activities of Chrysanthemum morifolium were evaluated by DPPH and FRAP assays, and the results showed that the antioxidant activity of each sample was not the same. The different varieties of fresh Chrysanthemum morifolium flowers were distinguished and classified by fingerprint similarity evaluation, principle component analysis (PCA), and cluster analysis. The results showed that the floral volatile component profiles were significantly different among the different Chrysanthemum morifolium varieties. A total of 36 volatile flavor compounds were identified with eight functional groups: hydrocarbons, terpenoids, aromatic compounds, alcohols, ketones, ethers, aldehydes, and esters. Moreover, the variability among Chrysanthemum morifolium in basis to the data, and the first three principal components (PC1, PC2, and PC3) accounted for 96.509% of the total variance (55.802%, 30.599%, and 10.108%, respectively). PCA indicated that there were marked differences among Chrysanthemum morifolium varieties. The cluster analysis confirmed the results of the PCA analysis. In conclusion, the results of this study provide a basis for breeding Chrysanthemum cultivars with desirable floral scents, and they further support the view that some plants are promising sources of natural antioxidants.

Somatotype of the individuals with lower extremity amputation and its association with cardiovascular risk.

PubMed

Mozumdar, Arupendra; Roy, Subrata K

2008-03-01

Anthropometric somatotyping is one of the methods to describe the shape of the human body, which shows some associations with an individual's health and disease condition, especially with cardiovascular diseases (CVD). Individuals with lower extremity amputation (LEA) are known to be more vulnerable to the cardiovascular risk. The objectives of the present study are to report the somatotype of the individuals having lower extremity amputation, to study the possible variation in somatotype between two groups of amputated individuals, and to study the association between cardiovascular disease risk factor and somatotype components among individuals with locomotor disability. 102 adult male individuals with unilateral lower-extremity amputation residing in Calcutta and adjoining areas were investigated. The anthropometric data for somatotyping and data on cardiovascular risk traits (such as body mass index, blood pressure measurements, blood lipids) have been collected. The somatotyping technique of Carter & Heath (1990) has been followed. The result shows high mean values of endomorphy and mesomorphy components and a low mean value of the ectomorphy component among the amputated individuals having cardiovascular risks. The results of both discriminant analysis and logistic regression analysis show a significant relationship between somatotype components and CVD risk among the individuals with LEA. The findings of the present study support the findings of similar studies conducted on the normal population. Diagnosis of CVD risk condition through somatotyping can be utilized in prevention/treatment management for the individuals with LEA.

Chloroplast two-component systems: evolution of the link between photosynthesis and gene expression

PubMed Central

Puthiyaveetil, Sujith; Allen, John F.

2009-01-01

Two-component signal transduction, consisting of sensor kinases and response regulators, is the predominant signalling mechanism in bacteria. This signalling system originated in prokaryotes and has spread throughout the eukaryotic domain of life through endosymbiotic, lateral gene transfer from the bacterial ancestors and early evolutionary precursors of eukaryotic, cytoplasmic, bioenergetic organelles—chloroplasts and mitochondria. Until recently, it was thought that two-component systems inherited from an ancestral cyanobacterial symbiont are no longer present in chloroplasts. Recent research now shows that two-component systems have survived in chloroplasts as products of both chloroplast and nuclear genes. Comparative genomic analysis of photosynthetic eukaryotes shows a lineage-specific distribution of chloroplast two-component systems. The components and the systems they comprise have homologues in extant cyanobacterial lineages, indicating their ancient cyanobacterial origin. Sequence and functional characteristics of chloroplast two-component systems point to their fundamental role in linking photosynthesis with gene expression. We propose that two-component systems provide a coupling between photosynthesis and gene expression that serves to retain genes in chloroplasts, thus providing the basis of cytoplasmic, non-Mendelian inheritance of plastid-associated characters. We discuss the role of this coupling in the chronobiology of cells and in the dialogue between nuclear and cytoplasmic genetic systems. PMID:19324807

Chloroplast two-component systems: evolution of the link between photosynthesis and gene expression.

PubMed

Puthiyaveetil, Sujith; Allen, John F

2009-06-22

Two-component signal transduction, consisting of sensor kinases and response regulators, is the predominant signalling mechanism in bacteria. This signalling system originated in prokaryotes and has spread throughout the eukaryotic domain of life through endosymbiotic, lateral gene transfer from the bacterial ancestors and early evolutionary precursors of eukaryotic, cytoplasmic, bioenergetic organelles-chloroplasts and mitochondria. Until recently, it was thought that two-component systems inherited from an ancestral cyanobacterial symbiont are no longer present in chloroplasts. Recent research now shows that two-component systems have survived in chloroplasts as products of both chloroplast and nuclear genes. Comparative genomic analysis of photosynthetic eukaryotes shows a lineage-specific distribution of chloroplast two-component systems. The components and the systems they comprise have homologues in extant cyanobacterial lineages, indicating their ancient cyanobacterial origin. Sequence and functional characteristics of chloroplast two-component systems point to their fundamental role in linking photosynthesis with gene expression. We propose that two-component systems provide a coupling between photosynthesis and gene expression that serves to retain genes in chloroplasts, thus providing the basis of cytoplasmic, non-Mendelian inheritance of plastid-associated characters. We discuss the role of this coupling in the chronobiology of cells and in the dialogue between nuclear and cytoplasmic genetic systems.

Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data.

PubMed

Pagani, Marco; Giuliani, Alessandro; Öberg, Johanna; De Carli, Fabrizio; Morbelli, Silvia; Girtler, Nicola; Arnaldi, Dario; Accardo, Jennifer; Bauckneht, Matteo; Bongioanni, Francesca; Chincarini, Andrea; Sambuceti, Gianmario; Jonsson, Cathrine; Nobili, Flavio

2017-07-01

Brain connectivity has been assessed in several neurodegenerative disorders investigating the mutual correlations between predetermined regions or nodes. Selective breakdown of brain networks during progression from normal aging to Alzheimer disease dementia (AD) has also been observed. Methods: We implemented independent-component analysis of 18 F-FDG PET data in 5 groups of subjects with cognitive states ranging from normal aging to AD-including mild cognitive impairment (MCI) not converting or converting to AD-to disclose the spatial distribution of the independent components in each cognitive state and their accuracy in discriminating the groups. Results: We could identify spatially distinct independent components in each group, with generation of local circuits increasing proportionally to the severity of the disease. AD-specific independent components first appeared in the late-MCI stage and could discriminate converting MCI and AD from nonconverting MCI with an accuracy of 83.5%. Progressive disintegration of the intrinsic networks from normal aging to MCI to AD was inversely proportional to the conversion time. Conclusion: Independent-component analysis of 18 F-FDG PET data showed a gradual disruption of functional brain connectivity with progression of cognitive decline in AD. This information might be useful as a prognostic aid for individual patients and as a surrogate biomarker in intervention trials. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

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.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Distribution and Taxonomic Significance of Secondary Metabolites Occurring in the Methanol Extracts of the Stonecrops (Sedum L., Crassulaceae) from the Central Balkan Peninsula.

PubMed

Stojanovic, Gordana S; Jovanović, Snežana C; Zlatković, Bojan K

2015-06-01

The present study is engaged in the chemical composition of methanol extracts of Sedum taxa from the central part of the Balkan Peninsula, and representatives from other genera of Crassulaceae (Crassula, Echeveria and Kalanchoe) considered as out-groups. The chemical composition of extracts was determined by HPLC analysis, according to retention time of standards and characteristic absorption spectra of components. Identified components were considered as original variables with possible chemotaxonomic significance. Relationships of examined plant samples were investigated by agglomerative hierarchical cluster analysis (AHC). The obtained results showed how the distribution of methanol extract components (mostly phenolics) affected grouping of the examined samples. The obtained clustering showed satisfactory grouping of the examined samples, among which some representatives of the Sedum series, Rupestria and Magellensia, are the most remote. The out-group samples were not clearly singled out with regard to Sedum samples as expected; this especially applies to samples of Crassula ovata and Echeveria lilacina, while Kalanchoe daigremontiana was more separated from most of the Sedum samples.

Enhancing high-order harmonic generation by sculpting waveforms with chirp

NASA Astrophysics Data System (ADS)

Peng, Dian; Frolov, M. V.; Pi, Liang-Wen; Starace, Anthony F.

2018-05-01

We present a theoretical analysis showing how chirp can be used to sculpt two-color driving laser field waveforms in order to enhance high-order harmonic generation (HHG) and/or extend HHG cutoff energies. Specifically, we consider driving laser field waveforms composed of two ultrashort pulses having different carrier frequencies in each of which a linear chirp is introduced. Two pairs of carrier frequencies of the component pulses are considered: (ω , 2 ω ) and (ω , 3 ω ). Our results show how changing the signs of the chirps in each of the two component pulses leads to drastic changes in the HHG spectra. Our theoretical analysis is based on numerical solutions of the time-dependent Schrödinger equation and on a semiclassical analytical approach that affords a clear physical interpretation of how our optimized waveforms lead to enhanced HHG spectra.

Analysis of genetic effects of nuclear-cytoplasmic interaction on quantitative traits: genetic model for diploid plants.

PubMed

Han, Lide; Yang, Jian; Zhu, Jun

2007-06-01

A genetic model was proposed for simultaneously analyzing genetic effects of nuclear, cytoplasm, and nuclear-cytoplasmic interaction (NCI) as well as their genotype by environment (GE) interaction for quantitative traits of diploid plants. In the model, the NCI effects were further partitioned into additive and dominance nuclear-cytoplasmic interaction components. Mixed linear model approaches were used for statistical analysis. On the basis of diallel cross designs, Monte Carlo simulations showed that the genetic model was robust for estimating variance components under several situations without specific effects. Random genetic effects were predicted by an adjusted unbiased prediction (AUP) method. Data on four quantitative traits (boll number, lint percentage, fiber length, and micronaire) in Upland cotton (Gossypium hirsutum L.) were analyzed as a worked example to show the effectiveness of the model.

Fast noise level estimation algorithm based on principal component analysis transform and nonlinear rectification

NASA Astrophysics Data System (ADS)

Xu, Shaoping; Zeng, Xiaoxia; Jiang, Yinnan; Tang, Yiling

2018-01-01

We proposed a noniterative principal component analysis (PCA)-based noise level estimation (NLE) algorithm that addresses the problem of estimating the noise level with a two-step scheme. First, we randomly extracted a number of raw patches from a given noisy image and took the smallest eigenvalue of the covariance matrix of the raw patches as the preliminary estimation of the noise level. Next, the final estimation was directly obtained with a nonlinear mapping (rectification) function that was trained on some representative noisy images corrupted with different known noise levels. Compared with the state-of-art NLE algorithms, the experiment results show that the proposed NLE algorithm can reliably infer the noise level and has robust performance over a wide range of image contents and noise levels, showing a good compromise between speed and accuracy in general.

[Application of ICP-MS to Identify the Botanic Source of Characteristic Honey in South Yunnan].

PubMed

Wei, Yue; Chen, Fang; Wang, Yong; Chen, Lan-zhen; Zhang, Xue-wen; Wang, Yan-hui; Wu, Li-ming; Zhou, Qun

2016-01-01

By adopting inductively coupled plasma mass spectrometry (ICP-MS) combined with chemometric analysis technology, 23 kinds of minerals in four kinds of characteristic honey derived from Yunnan province were analyzed. The result showed that 21 kinds of mineral elements, namely Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sb, Ba, Tl and Pb, have significant differences among different varieties of honey. The results of principal component analysis (PCA) showed that the cumulative variance contribution rate of the first four main components reached 77.74%, seven kinds of elements (Mg, Ca, Mn, Co, Sr, Cd, Ba) from the first main component contained most of the honey information. Through the stepwise discriminant analysis, seven kinds of elements (Mg, K, Ca, Cr, Mn, Sr, Pb) were filtered. out and used to establish the discriminant function model, and the correct classification rates of the proposed model reached 90% and 86.7%, respectively, which showed elements contents could be effectively indicators to discriminate the four kinds characteristic honey in southern Yunnan Province. In view of all the honey samples were harvested from apiaries located at south Yunnan Province where have similar climate, soil and other environment conditions, the differences of the mineral elements contents for the honey samples mainly due to their corresponding nectariferous plant. Therefore, it is feasible to identify honey botanical source through the differences of mineral elements.

Relationship between regional population and healthcare delivery in Japan.

PubMed

Niga, Takeo; Mori, Maiko; Kawahara, Kazuo

2016-01-01

In order to address regional inequality in healthcare delivery in Japan, healthcare districts were established in 1985. However, regional healthcare delivery has now become a national issue because of population migration and the aging population. In this study, the state of healthcare delivery at the district level is examined by analyzing population, the number of physicians, and the number of hospital beds. The results indicate a continuing disparity in healthcare delivery among districts. We find that the rate of change in population has a strong positive correlation with that in the number of physicians and a weak positive correlation with that in the number of hospital beds. In addition, principal component analysis is performed on three variables: the rate of change in population, the number of physicians per capita, and the number of hospital beds per capita. This analysis suggests that the two principal components contribute 90.1% of the information. The first principal component is thought to show the effect of the regulations on hospital beds. The second principal component is thought to show the capacity to recruit physicians. This study indicates that an adjustment to the regulations on hospital beds as well as physician allocation by public funds may be key to resolving the impending issue of regionally disproportionate healthcare delivery.

Moisture Forecast Bias Correction in GEOS DAS

NASA Technical Reports Server (NTRS)

Dee, D.

1999-01-01

Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

Suzaku Observations of the Broad-Line Radio Galaxy 3C390.3

NASA Technical Reports Server (NTRS)

Sambruna, rita

2007-01-01

We present the results of a 100ks Suzaku observation of the BLRG 3C390.3. The observations were performed to attempt to disentangle the contributions to the X-ray emission of this galaxy from an AGN and a jet component, via variability and/or the spectrum. The source was detected at high energies up to 80 keV, with a complex 0.3--80keV spectrum. Preliminary analysis of the data shows significant flux variability, with the largest amplitudes at higher energies. Deconvolution of the spectrum shows that, besides a standard Seyfert-like spectrum dominating the 0.3--8keV emission, an additional, hard power law component is required, dominating the emission above 10 keV. We attribute this component to a variable jet.

Analysis of seismic patterns observed at Nevado del Ruiz volcano, Colombia during August September 1985

NASA Astrophysics Data System (ADS)

Martinelli, Bruno

1990-07-01

The seismic activity of the Nevado del Ruiz volcano was monitored during August-September 1985 using a three-component portable seismograph station placed on the upper part of the volcano. The objective was to investigate the frequency content of the seismic signals and the possible sources of the volcanic tremor. The seismicity showed a wide spectrum of signals, especially at the beginning of September. Some relevant patterns from the collected records, which have been analyzed by spectrum analysis, are presented. For the purpose of analysis, the records have been divided into several categories such as long-period events, tremor, cyclic tremor episodes, and strong seismic activity on September 8, 1985. The origin of the seismic signals must be considered in relation to the dynamical and acoustical properties of fluids and the shape and dimensions of the volcano's conduits. The main results of the present experiment and analysis show that the sources of the seismic signals are within the volcanic edifice. The signal characteristics indicate that the sources lie in fluid-phase interactions rather than in brittle fracturing of solid components.

Analysis of Resistant Starches in Rat Cecal Contents Using Fourier Transform Infrared Photoacoustic Spectroscopy

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

Anderson, Timothy J.; Ai, Yongfeng; Jones, Roger W.

Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) qualitatively and quantitatively measured resistant starch (RS) in rat cecal contents. Fisher 344 rats were fed diets of 55% (w/w, dry basis) starch for 8 weeks. Cecal contents were collected from sacrificed rats. A corn starch control was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. To calibrate the FTIR-PAS analysis, samples from each diet were analyzed using an enzymatic assay. A partial least-squares cross-validation plot generated from the enzymatic assay and FTIR-PAS spectral results for starch fitmore » the ideal curve with a R2 of 0.997. A principal component analysis plot of components 1 and 2 showed that spectra from diets clustered significantly from each other. This study clearly showed that FTIR-PAS can accurately quantify starch content and identify the form of starch in complex matrices.« less

Analysis and modification of theory for impact of seaplanes on water

NASA Technical Reports Server (NTRS)

Mayo, Wilbur L

1945-01-01

An analysis of available theory on seaplane impact and a proposed modification thereto are presented. In previous methods the overall momentum of the float and virtual mass has been assumed to remain constant during the impact but the present analysis shows that this assumption is rigorously correct only when the resultant velocity of the float is normal to the keel. The proposed modification chiefly involves consideration of the fact that forward velocity of the seaplane float causes momentum to be passed into the hydrodynamic downwash (an action that is the entire consideration in the case of the planing float) and consideration of the fact that, for an impact with trim, the rate of penetration is determined not only by the velocity component normal to the keel but also by the velocity component parallel to the keel, which tends to reduce the penetration. Experimental data for planing, oblique impact, and vertical drop are used to show that the accuracy of the proposed theory is good.

Micro friction stir lap welding of AISI 430 ferritic stainless steel: a study on the mechanical properties, microstructure, texture and magnetic properties

NASA Astrophysics Data System (ADS)

Mostaan, Hossein; Safari, Mehdi; Bakhtiari, Arash

2018-04-01

In this study, the effect of friction stir welding of AISI 430 (X6Cr17, material number 1.4016) ferritic stainless steel is examined. Two thin sheets with dimensions of 0.4 × 50 × 200 mm3 are joined in lap configuration. Optical microscopy and field emission electron microscopy were used in order to microstructural evaluations and fracture analysis, respectively. Tensile test and microhardness measurements are employed in order to study the mechanical behaviors of welds. Also, vibrational sample magnetometry (VSM) is employed for characterizing magnetic properties of welded samples. Texture analysis is carried out in order to clarify the change mechanism of magnetic properties in the welded area. The results show that AISI 430 sheets are successfully joined considering both, the appearance of the welding bead and the strength of the welded joint. It is found that by friction stir welding of AISI 430 sheets, texture components with easy axes magnetization have been replaced by texture components with harder magnetization axes. VSM analysis showed that friction stir welding leads to increase in residual induction (Br) and coercivity (Hc). This increase is attributed to the grain refining due the friction stir welding and formation of texture components with harder axes of magnetizations.

Boundary layer noise subtraction in hydrodynamic tunnel using robust principal component analysis.

PubMed

Amailland, Sylvain; Thomas, Jean-Hugh; Pézerat, Charles; Boucheron, Romuald

2018-04-01

The acoustic study of propellers in a hydrodynamic tunnel is of paramount importance during the design process, but can involve significant difficulties due to the boundary layer noise (BLN). Indeed, advanced denoising methods are needed to recover the acoustic signal in case of poor signal-to-noise ratio. The technique proposed in this paper is based on the decomposition of the wall-pressure cross-spectral matrix (CSM) by taking advantage of both the low-rank property of the acoustic CSM and the sparse property of the BLN CSM. Thus, the algorithm belongs to the class of robust principal component analysis (RPCA), which derives from the widely used principal component analysis. If the BLN is spatially decorrelated, the proposed RPCA algorithm can blindly recover the acoustical signals even for negative signal-to-noise ratio. Unfortunately, in a realistic case, acoustic signals recorded in a hydrodynamic tunnel show that the noise may be partially correlated. A prewhitening strategy is then considered in order to take into account the spatially coherent background noise. Numerical simulations and experimental results show an improvement in terms of BLN reduction in the large hydrodynamic tunnel. The effectiveness of the denoising method is also investigated in the context of acoustic source localization.

An innovative approach for characteristic analysis and state-of-health diagnosis for a Li-ion cell based on the discrete wavelet transform

NASA Astrophysics Data System (ADS)

Kim, Jonghoon; Cho, B. H.

2014-08-01

This paper introduces an innovative approach to analyze electrochemical characteristics and state-of-health (SOH) diagnosis of a Li-ion cell based on the discrete wavelet transform (DWT). In this approach, the DWT has been applied as a powerful tool in the analysis of the discharging/charging voltage signal (DCVS) with non-stationary and transient phenomena for a Li-ion cell. Specifically, DWT-based multi-resolution analysis (MRA) is used for extracting information on the electrochemical characteristics in both time and frequency domain simultaneously. Through using the MRA with implementation of the wavelet decomposition, the information on the electrochemical characteristics of a Li-ion cell can be extracted from the DCVS over a wide frequency range. Wavelet decomposition based on the selection of the order 3 Daubechies wavelet (dB3) and scale 5 as the best wavelet function and the optimal decomposition scale is implemented. In particular, this present approach develops these investigations one step further by showing low and high frequency components (approximation component An and detail component Dn, respectively) extracted from variable Li-ion cells with different electrochemical characteristics caused by aging effect. Experimental results show the clearness of the DWT-based approach for the reliable diagnosis of the SOH for a Li-ion cell.

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

PubMed

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

2016-07-01

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

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

[Quantitative analysis of nucleotide mixtures with terahertz time domain spectroscopy].

PubMed

Zhang, Zeng-yan; Xiao, Ti-qiao; Zhao, Hong-wei; Yu, Xiao-han; Xi, Zai-jun; Xu, Hong-jie

2008-09-01

Adenosine, thymidine, guanosine, cytidine and uridine form the building blocks of ribose nucleic acid (RNA) and deoxyribose nucleic acid (DNA). Nucleosides and their derivants are all have biological activities. Some of them can be used as medicine directly or as materials to synthesize other medicines. It is meaningful to detect the component and content in nucleosides mixtures. In the present paper, components and contents of the mixtures of adenosine, thymidine, guanosine, cytidine and uridine were analyzed. THz absorption spectra of pure nucleosides were set as standard spectra. The mixture's absorption spectra were analyzed by linear regression with non-negative constraint to identify the components and their relative content in the mixtures. The experimental and analyzing results show that it is simple and effective to get the components and their relative percentage in the mixtures by terahertz time domain spectroscopy with a relative error less than 10%. Component which is absent could be excluded exactly by this method, and the error sources were also analyzed. All the experiments and analysis confirms that this method is of no damage or contamination to the sample. This means that it will be a simple, effective and new method in biochemical materials analysis, which extends the application field of THz-TDS.

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

Water characterization and seasonal heavy metal distribution in the Odiel River (Huelva, Spain) by means of principal component analysis.

PubMed

Montes-Botella, C; Tenorio, M D

2003-11-01

The Iberian Pyrite Belt is the largest mass of sulfide and manganese ores in Western Europe. Its sulfide oxidation is the origin of a heavily acidic drainage that affects the Odiel River in southwestern Huelva (Spain). To assess physicochemical, contamination parameters, heavy metal distribution and its seasonal variation in the upper Odiel River and in El Lomero mines, three water samplings were undertaken and analyzed between July 1998 and November 1999. Water from the Odiel River in the polluted zone showed low pH values (2.76-3.51), high heavy metal content, and high values of conductivity (1410-3648 microS/cm) and dissolved solids (1484-5602 mg/L). Principal Component Analysis (PCA) showed that variables related with the products of the pyrite oxidation and the salts that are solubilized by the high acidity generated in the oxidation of sulfides, grouped in the first component, accounted for 40.88% of total variance, and were the main influential factor in physicochemical water sample properties. The second influential factor was minority metals (nickel, cobalt, cadmium). Heavy metals showed three different seasonal patterns, closely related with saline efflorescences formed next to the river bed: majority metals (iron, copper, manganese, zinc); minority metals (lead, nickel, cobalt, cadmium); and chromium, which had a distinctive behavior.

A new crank arm based load cell, with built-in conditioning circuit and strain gages, to measure the components of the force applied by a cyclist.

PubMed

Pigatto, Andre V; Moura, Karina O A; Favieiro, Gabriela W; Balbinot, Alexandre

2016-08-01

This report describes the development of a force platform based on instrumented load cells with built-in conditioning circuit and strain gages to measure and acquire the components of the force that is applied to the bike crank arm during pedaling in real conditions, and save them on a SD Card. To accomplish that, a complete new crank arm 3D solid model was developed in the SolidWorks, with dimensions equivalent to a commercial crank set and compatible with a conventional road bike, but with a compartment to support all the electronics necessary to measure 3 components of the force applied to the pedal during pedaling. After that, a 6082 T6 Aluminum Crankset based on the solid model was made and instrumented with three Wheatstone bridges each. The signals were conditioned on a printed circuit board, made on SMD technology, and acquired using a microcontroller with a DAC. Static deformation analysis showed a linearity error below 0.6% for all six channels. Dynamic analysis showed a natural frequency above 136Hz. A one-factor experiment design was performed with 5 amateur cyclists. ANOVA showed that the cyclist weight causes significant variation on the force applied to the bicycle pedal and its bilateral symmetry.

Scalable Robust Principal Component Analysis Using Grassmann Averages.

PubMed

Hauberg, Sren; Feragen, Aasa; Enficiaud, Raffi; Black, Michael J

2016-11-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA are not scalable. We note that in a zero-mean dataset, each observation spans a one-dimensional subspace, giving a point on the Grassmann manifold. We show that the average subspace corresponds to the leading principal component for Gaussian data. We provide a simple algorithm for computing this Grassmann Average ( GA), and show that the subspace estimate is less sensitive to outliers than PCA for general distributions. Because averages can be efficiently computed, we immediately gain scalability. We exploit robust averaging to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. The resulting Trimmed Grassmann Average ( TGA) is appropriate for computer vision because it is robust to pixel outliers. The algorithm has linear computational complexity and minimal memory requirements. We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie; a task beyond any current method. Source code is available online.

Adhesive properties and adhesive joints strength of graphite/epoxy composites

NASA Astrophysics Data System (ADS)

Rudawska, Anna; Stančeková, Dana; Cubonova, Nadezda; Vitenko, Tetiana; Müller, Miroslav; Valášek, Petr

2017-05-01

The article presents the results of experimental research of the adhesive joints strength of graphite/epoxy composites and the results of the surface free energy of the composite surfaces. Two types of graphite/epoxy composites with different thickness were tested which are used to aircraft structure. The single-lap adhesive joints of epoxy composites were considered. Adhesive properties were described by surface free energy. Owens-Wendt method was used to determine surface free energy. The epoxy two-component adhesive was used to preparing the adhesive joints. Zwick/Roell 100 strength device were used to determination the shear strength of adhesive joints of epoxy composites. The strength test results showed that the highest value was obtained for adhesive joints of graphite-epoxy composite of smaller material thickness (0.48 mm). Statistical analysis of the results obtained, the study showed statistically significant differences between the values of the strength of the confidence level of 0.95. The statistical analysis of the results also showed that there are no statistical significant differences in average values of surface free energy (0.95 confidence level). It was noted that in each of the results the dispersion component of surface free energy was much greater than polar component of surface free energy.

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.

Token Economy: A Systematic Review of Procedural Descriptions.

PubMed

Ivy, Jonathan W; Meindl, James N; Overley, Eric; Robson, Kristen M

2017-09-01

The token economy is a well-established and widely used behavioral intervention. A token economy is comprised of six procedural components: the target response(s), a token that functions as a conditioned reinforcer, backup reinforcers, and three interconnected schedules of reinforcement. Despite decades of applied research, the extent to which the procedures of a token economy are described in complete and replicable detail has not been evaluated. Given the inherent complexity of a token economy, an analysis of the procedural descriptions may benefit future token economy research and practice. Articles published between 2000 and 2015 that included implementation of a token economy within an applied setting were identified and reviewed with a focus on evaluating the thoroughness of procedural descriptions. The results show that token economy components are regularly omitted or described in vague terms. Of the articles included in this analysis, only 19% (18 of 96 articles reviewed) included replicable and complete descriptions of all primary components. Missing or vague component descriptions could negatively affect future research or applied practice. Recommendations are provided to improve component descriptions.

A Principle Component Analysis of Galaxy Properties from a Large, Gas-Selected Sample

DOE PAGES

Chang, Yu-Yen; Chao, Rikon; Wang, Wei-Hao; ...

2012-01-01

Disney emore » t al. (2008) have found a striking correlation among global parameters of H i -selected galaxies and concluded that this is in conflict with the CDM model. Considering the importance of the issue, we reinvestigate the problem using the principal component analysis on a fivefold larger sample and additional near-infrared data. We use databases from the Arecibo Legacy Fast Arecibo L -band Feed Array Survey for the gas properties, the Sloan Digital Sky Survey for the optical properties, and the Two Micron All Sky Survey for the near-infrared properties. We confirm that the parameters are indeed correlated where a single physical parameter can explain 83% of the variations. When color ( g - i ) is included, the first component still dominates but it develops a second principal component. In addition, the near-infrared color ( i - J ) shows an obvious second principal component that might provide evidence of the complex old star formation. Based on our data, we suggest that it is premature to pronounce the failure of the CDM model and it motivates more theoretical work.« less

A Filtering of Incomplete GNSS Position Time Series with Probabilistic Principal Component Analysis

NASA Astrophysics Data System (ADS)

Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

2018-04-01

For the first time, we introduced the probabilistic principal component analysis (pPCA) regarding the spatio-temporal filtering of Global Navigation Satellite System (GNSS) position time series to estimate and remove Common Mode Error (CME) without the interpolation of missing values. We used data from the International GNSS Service (IGS) stations which contributed to the latest International Terrestrial Reference Frame (ITRF2014). The efficiency of the proposed algorithm was tested on the simulated incomplete time series, then CME was estimated for a set of 25 stations located in Central Europe. The newly applied pPCA was compared with previously used algorithms, which showed that this method is capable of resolving the problem of proper spatio-temporal filtering of GNSS time series characterized by different observation time span. We showed, that filtering can be carried out with pPCA method when there exist two time series in the dataset having less than 100 common epoch of observations. The 1st Principal Component (PC) explained more than 36% of the total variance represented by time series residuals' (series with deterministic model removed), what compared to the other PCs variances (less than 8%) means that common signals are significant in GNSS residuals. A clear improvement in the spectral indices of the power-law noise was noticed for the Up component, which is reflected by an average shift towards white noise from - 0.98 to - 0.67 (30%). We observed a significant average reduction in the accuracy of stations' velocity estimated for filtered residuals by 35, 28 and 69% for the North, East, and Up components, respectively. CME series were also subjected to analysis in the context of environmental mass loading influences of the filtering results. Subtraction of the environmental loading models from GNSS residuals provides to reduction of the estimated CME variance by 20 and 65% for horizontal and vertical components, respectively.

Multivariate Analysis of Fruit Antioxidant Activities of Blackberry Treated with 1-Methylcyclopropene or Vacuum Precooling

PubMed Central

Li, Jian; Ma, Guowei; Ma, Lin; Bao, Xiaolin; Li, Liping; Zhao, Qian

2018-01-01

Effects of 1-methylcyclopropene (1-MCP) and vacuum precooling on quality and antioxidant properties of blackberries (Rubus spp.) were evaluated using one-way analysis of variance, principal component analysis (PCA), partial least squares (PLS), and path analysis. Results showed that the activities of antioxidant enzymes were enhanced by both 1-MCP treatment and vacuum precooling. PCA could discriminate 1-MCP treated fruit and the vacuum precooled fruit and showed that the radical-scavenging activities in vacuum precooled fruit were higher than those in 1-MCP treated fruit. The scores of PCA showed that H2O2 content was the most important variables of blackberry fruit. PLSR results showed that peroxidase (POD) activity negatively correlated with H2O2 content. The results of path coefficient analysis indicated that glutathione (GSH) also had an indirect effect on H2O2 content. PMID:29487622

AE Source Orientation by Plate Wave Analysis

NASA Technical Reports Server (NTRS)

Gorman, Michael R.; Prosser, William H.

1991-01-01

Lead breaks (Hsu-Neilsen source) were used to generate simulated acoustic emission signals in an aluminum plate at angles of 0, 30, 60, and 90 degrees with respect to the plane of the plate. This was accomplished by breaking the lead on slots cut into the plate at the respective angles. The out-of-plane and in-plane displacement components of the resulting signals were detected by broad band transducers and digitized. Analysis of the waveforms showed them to consist of the extensional and flexural plate modes. The amplitude of both components of the two modes was dependent on the source orientation angle. This suggests that plate wave analysis may be used to determine the source orientation of acoustic emission sources.

Numerical Analysis of the Bending Properties of Cathay Poplar Glulam

PubMed Central

Gao, Ying; Wu, Yuxuan; Zhu, Xudong; Zhu, Lei; Yu, Zhiming; Wu, Yong

2015-01-01

This paper presents the formulae and finite element analysis models for predicting the Modulus of Elastic (MOE) and Modulus of Rupture (MOR) of Cathay poplar finger-jointed glulam. The formula of the MOE predicts the MOE of Cathay poplar glulam glued with one-component polyurethane precisely. Three formulae are used to predict the MOR, and Equation (12) predicts the MOR of Cathay poplar glulam precisely. The finite element analysis simulation results of both the MOE and MOR are similar to the experimental results. The predicted results of the finite element analysis are shown to be more accurate than those of the formulae, because the finite element analysis considers the glue layers, but the formulae do not. Three types of typical failure modes due to bending were summarized. The bending properties of Cathay poplar glulam were compared to those of Douglas fir glulam. The results show that Cathay poplar glulam has a lower stiffness, but a marginally higher strength. One-component polyurethane adhesive is shown to be more effective than resorcinol formaldehyde resin adhesive for Cathay poplar glulam. This study shows that Cathay poplar has the potential to be a glulam material in China. PMID:28793619

FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases

NASA Astrophysics Data System (ADS)

Ogruc Ildiz, G.; Arslan, M.; Unsalan, O.; Araujo-Andrade, C.; Kurt, E.; Karatepe, H. T.; Yilmaz, A.; Yalcinkaya, O. B.; Herken, H.

2016-01-01

In this study, a methodology based on Fourier-transform infrared spectroscopy and principal component analysis and partial least square methods is proposed for the analysis of blood plasma samples in order to identify spectral changes correlated with some biomarkers associated with schizophrenia and bipolarity. Our main goal was to use the spectral information for the calibration of statistical models to discriminate and classify blood plasma samples belonging to bipolar and schizophrenic patients. IR spectra of 30 samples of blood plasma obtained from each, bipolar and schizophrenic patients and healthy control group were collected. The results obtained from principal component analysis (PCA) show a clear discrimination between the bipolar (BP), schizophrenic (SZ) and control group' (CG) blood samples that also give possibility to identify three main regions that show the major differences correlated with both mental disorders (biomarkers). Furthermore, a model for the classification of the blood samples was calibrated using partial least square discriminant analysis (PLS-DA), allowing the correct classification of BP, SZ and CG samples. The results obtained applying this methodology suggest that it can be used as a complimentary diagnostic tool for the detection and discrimination of these mental diseases.

Assessment on the leakage hazard of landfill leachate using three-dimensional excitation-emission fluorescence and parallel factor analysis method.

PubMed

Pan, Hongwei; Lei, Hongjun; Liu, Xin; Wei, Huaibin; Liu, Shufang

2017-09-01

A large number of simple and informal landfills exist in developing countries, which pose as tremendous soil and groundwater pollution threats. Early warning and monitoring of landfill leachate pollution status is of great importance. However, there is a shortage of affordable and effective tools and methods. In this study, a soil column experiment was performed to simulate the pollution status of leachate using three-dimensional excitation-emission fluorescence (3D-EEMF) and parallel factor analysis (PARAFAC) models. Sum of squared residuals (SSR) and principal component analysis (PCA) were used to determine the optimal components for PARAFAC. A one-way analysis of variance showed that the component scores of the soil column leachate were significant influenced by landfill leachate (p<0.05). Therefore, the ratio of the component scores of the soil under the landfill to that of natural soil could be used to evaluate the leakage status of landfill leachate. Furthermore, a hazard index (HI) and a hazard evaluation standard were established. A case study of Kaifeng landfill indicated a low hazard (level 5) by the use of HI. In summation, HI is presented as a tool to evaluate landfill pollution status and for the guidance of municipal solid waste management. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-11-22

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

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

PubMed Central

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

2016-01-01

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

Statistical analysis of Stromboli VLP tremor in the band (0.1-0.5)Hz: Some consequences for geometrical vibrating structure

NASA Astrophysics Data System (ADS)

Palo, M.; de Lauro, E.; de Martino, S.; Falanga, M.

2006-12-01

We analyze time series of strombolian volcanic tremor recorded during the experiment performed in 1997 by using 21 three-component broadband seismometers. This work is devoted to the careful analysis of the frequency band [0.1-0.5] Hz in order to obtain information about the properties of volcanic tremor and the microseismic noise. In fact, although this frequency band is largely affected by noise, we infer the possibility of simpler hidden structures. We evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of about 0.2 and 0.4 Hz. We show that these components display wavefield features similar to those of the high frequency strombolian signals (greater than 0.5 Hz). In fact they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case the presence of microseismic noise becomes relevant. Investigating the entire large data- set available, we determine how microseismic noise influences the signals. We ascribed the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to affirm that the strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.

Reliability Centred Maintenance (RCM) Analysis of Laser Machine in Filling Lithos at PT X

NASA Astrophysics Data System (ADS)

Suryono, M. A. E.; Rosyidi, C. N.

2018-03-01

PT. X used automated machines which work for sixteen hours per day. Therefore, the machines should be maintained to keep the availability of the machines. The aim of this research is to determine maintenance tasks according to the cause of component’s failure using Reliability Centred Maintenance (RCM) and determine the amount of optimal inspection frequency which must be performed to the machine at filling lithos process. In this research, RCM is used as an analysis tool to determine the critical component and find optimal inspection frequencies to maximize machine’s reliability. From the analysis, we found that the critical machine in filling lithos process is laser machine in Line 2. Then we proceed to determine the cause of machine’s failure. Lastube component has the highest Risk Priority Number (RPN) among other components such as power supply, lens, chiller, laser siren, encoder, conveyor, and mirror galvo. Most of the components have operational consequences and the others have hidden failure consequences and safety consequences. Time-directed life-renewal task, failure finding task, and servicing task can be used to overcome these consequences. The results of data analysis show that the inspection must be performed once a month for laser machine in the form of preventive maintenance to lowering the downtime.

Content Analysis of the Concept of Addiction in High School Textbooks of Iran.

PubMed

Mirzamohammadi, Mohammad Hasan; Mousavi, Sayedeh Zainab; Massah, Omid; Farhoudian, Ali

2017-01-01

This research sought to determine how well the causes of addiction, addiction harms, and prevention of addiction have been noticed in high school textbooks. We used descriptive method to select the main related components of the addiction concept and content analysis method for analyzing the content of textbooks. The study population comprised 61 secondary school curriculum textbooks and study sample consisted of 14 secondary school textbooks selected by purposeful sampling method. The tools for collecting data were "content analysis inventory" which its validity was confirmed by educational and social sciences experts and its reliability has been found to be 91%. About 67 components were prepared for content analysis and were divided to 3 categories of causes, harms, and prevention of addiction. The analysis units in this study comprised phrases, topics, examples, course topics, words, poems, images, questions, tables, and exercises. Results of the study showed that the components of the addiction concept have presented with 212 remarks in the textbooks. Also, the degree of attention given to any of the 3 main components of the addiction concept were presented as follows: causes with 52 (24.52%) remarks, harm with 89 (41.98%) remarks, and prevention with 71 (33.49%) remarks. In high school textbooks, little attention has been paid to the concept of addiction and mostly its biological dimension were addressed while social, personal, familial, and religious dimensions of addiction have been neglected.

Automated analysis of blood pressure measurements (Korotkov sound)

NASA Technical Reports Server (NTRS)

Golden, D. P.; Hoffler, G. W.; Wolthuis, R. A.

1972-01-01

Automatic system for noninvasive measurements of arterial blood pressure is described. System uses Korotkov sound processor logic ratios to identify Korotkov sounds. Schematic diagram of system is provided to show components and method of operation.

Improving KPCA Online Extraction by Orthonormalization in the Feature Space.

PubMed

Souza Filho, Joao B O; Diniz, Paulo S R

2018-04-01

Recently, some online kernel principal component analysis (KPCA) techniques based on the generalized Hebbian algorithm (GHA) were proposed for use in large data sets, defining kernel components using concise dictionaries automatically extracted from data. This brief proposes two new online KPCA extraction algorithms, exploiting orthogonalized versions of the GHA rule. In both the cases, the orthogonalization of kernel components is achieved by the inclusion of some low complexity additional steps to the kernel Hebbian algorithm, thus not substantially affecting the computational cost of the algorithm. Results show improved convergence speed and accuracy of components extracted by the proposed methods, as compared with the state-of-the-art online KPCA extraction algorithms.

Principal component similarity analysis of Raman spectra to study the effects of pH, heating, and kappa-carrageenan on whey protein structure.

PubMed

Alizadeh-Pasdar, Nooshin; Nakai, Shuryo; Li-Chan, Eunice C Y

2002-10-09

Raman spectroscopy was used to elucidate structural changes of beta-lactoglobulin (BLG), whey protein isolate (WPI), and bovine serum albumin (BSA), at 15% concentration, as a function of pH (5.0, 7.0, and 9.0), heating (80 degrees C, 30 min), and presence of 0.24% kappa-carrageenan. Three data-processing techniques were used to assist in identifying significant changes in Raman spectral data. Analysis of variance showed that of 12 characteristics examined in the Raman spectra, only a few were significantly affected by pH, heating, kappa-carrageenan, and their interactions. These included amide I (1658 cm(-1)) for WPI and BLG, alpha-helix for BLG and BSA, beta-sheet for BSA, CH stretching (2880 cm(-1)) for BLG and BSA, and CH stretching (2930 cm(-1)) for BSA. Principal component analysis reduced dimensionality of the characteristics. Heating and its interaction with kappa-carrageenan were identified as the most influential in overall structure of the whey proteins, using principal component similarity analysis.

Analyzing the development of Indonesia shrimp industry

NASA Astrophysics Data System (ADS)

Wati, L. A.

2018-04-01

This research aimed to analyze the development of shrimp industry in Indonesia. Porter’s Diamond Theory was used for analysis. The Porter’s Diamond theory is one of framework for industry analysis and business strategy development. The Porter’s Diamond theory has five forces that determine the competitive intensity in an industry, namely (1) the threat of substitute products, (2) the threat of competition, (3) the threat of new entrants, (4) bargaining power of suppliers, and (5) bargaining power of consumers. The development of Indonesian shrimp industry pretty good, explained by Porter Diamond Theory analysis. Analysis of Porter Diamond Theory through four main components namely factor conditions; demand condition; related and supporting industries; and firm strategy, structure and rivalry coupled with a two-component supporting (regulatory the government and the factor of chance). Based on the result of this research show that two-component supporting (regulatory the government and the factor of chance) have positive. Related and supporting industries have negative, firm and structure strategy have negative, rivalry has positive, factor condition have positive (except science and technology resources).

Order-crossing removal in Gabor order tracking by independent component analysis

NASA Astrophysics Data System (ADS)

Guo, Yu; Tan, Kok Kiong

2009-08-01

Order-crossing problems in Gabor order tracking (GOT) of rotating machinery often occur when noise due to power-frequency interference, local structure resonance, etc., is prominent in applications. They can render the analysis results and the waveform-reconstruction tasks in GOT inaccurate or even meaningless. An approach is proposed in this paper to address the order-crossing problem by independent component analysis (ICA). With the approach, accurate order analysis results can be obtained and the waveforms of the order components of interest can be reconstructed or extracted from the recorded noisy data series. In addition, the ambiguities (permutation and scaling) of ICA results are also solved with the approach. The approach is amenable to applications in condition monitoring and fault diagnosis of rotating machinery. The evaluation of the approach is presented in detail based on simulations and an experiment on a rotor test rig. The results obtained using the proposed approach are compared with those obtained using the standard GOT. The comparison shows that the presented approach is more effective to solve order-crossing problems in GOT.

Evaluating filterability of different types of sludge by statistical analysis: The role of key organic compounds in extracellular polymeric substances.

PubMed

Xiao, Keke; Chen, Yun; Jiang, Xie; Zhou, Yan

2017-03-01

An investigation was conducted for 20 different types of sludge in order to identify the key organic compounds in extracellular polymeric substances (EPS) that are important in assessing variations of sludge filterability. The different types of sludge varied in initial total solids (TS) content, organic composition and pre-treatment methods. For instance, some of the sludges were pre-treated by acid, ultrasonic, thermal, alkaline, or advanced oxidation technique. The Pearson's correlation results showed significant correlations between sludge filterability and zeta potential, pH, dissolved organic carbon, protein and polysaccharide in soluble EPS (SB EPS), loosely bound EPS (LB EPS) and tightly bound EPS (TB EPS). The principal component analysis (PCA) method was used to further explore correlations between variables and similarities among EPS fractions of different types of sludge. Two principal components were extracted: principal component 1 accounted for 59.24% of total EPS variations, while principal component 2 accounted for 25.46% of total EPS variations. Dissolved organic carbon, protein and polysaccharide in LB EPS showed higher eigenvector projection values than the corresponding compounds in SB EPS and TB EPS in principal component 1. Further characterization of fractionized key organic compounds in LB EPS was conducted with size-exclusion chromatography-organic carbon detection-organic nitrogen detection (LC-OCD-OND). A numerical multiple linear regression model was established to describe relationship between organic compounds in LB EPS and sludge filterability. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Principal component analysis and cluster analysis of inorganic elements in sea cucumber Apostichopus japonicus].

PubMed

Liu, Xiao-Fang; Xue, Chang-Hu; Wang, Yu-Ming; Li, Zhao-Jie; Xue, Yong; Xu, Jie

2011-11-01

The present study is to investigate the feasibility of multi-elements analysis in determination of the geographical origin of sea cucumber Apostichopus japonicus, and to make choice of the effective tracers in sea cucumber Apostichopus japonicus geographical origin assessment. The content of the elements such as Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb in sea cucumber Apostichopus japonicus samples from seven places of geographical origin were determined by means of ICP-MS. The results were used for the development of elements database. Cluster analysis(CA) and principal component analysis (PCA) were applied to differentiate the sea cucumber Apostichopus japonicus geographical origin. Three principal components which accounted for over 89% of the total variance were extracted from the standardized data. The results of Q-type cluster analysis showed that the 26 samples could be clustered reasonably into five groups, the classification results were significantly associated with the marine distribution of the sea cucumber Apostichopus japonicus samples. The CA and PCA were the effective methods for elements analysis of sea cucumber Apostichopus japonicus samples. The content of the mineral elements in sea cucumber Apostichopus japonicus samples was good chemical descriptors for differentiating their geographical origins.

Chemistry and in vitro antioxidant activity of volatile oil and oleoresins of black pepper (Piper nigrum).

PubMed

Kapoor, I P S; Singh, Bandana; Singh, Gurdip; De Heluani, Carola S; De Lampasona, M P; Catalan, Cesar A N

2009-06-24

Essential oil and oleoresins (ethanol and ethyl acetate) of Piper nigrum were extracted by using Clevenger and Soxhlet apparatus, respectively. GC-MS analysis of pepper essential oil showed the presence of 54 components representing about 96.6% of the total weight. beta-Caryophylline (29.9%) was found as the major component along with limonene (13.2%), beta-pinene (7.9%), sabinene (5.9%), and several other minor components. The major component of both ethanol and ethyl acetate oleoresins was found to contain piperine (63.9 and 39.0%), with many other components in lesser amounts. The antioxidant activities of essential oil and oleoresins were evaluated against mustard oil by peroxide, p-anisidine, and thiobarbituric acid. Both the oil and oleoresins showed strong antioxidant activity in comparison with butylated hydroxyanisole (BHA) and butylated hydroxytoluene (BHT) but lower than that of propyl gallate (PG). In addition, their inhibitory action by FTC method, scavenging capacity by DPPH (2,2'-diphenyl-1-picrylhydrazyl radical), and reducing power were also determined, proving the strong antioxidant capacity of both the essential oil and oleoresins of pepper.

Restoration of recto-verso colour documents using correlated component analysis

NASA Astrophysics Data System (ADS)

Tonazzini, Anna; Bedini, Luigi

2013-12-01

In this article, we consider the problem of removing see-through interferences from pairs of recto-verso documents acquired either in grayscale or RGB modality. The see-through effect is a typical degradation of historical and archival documents or manuscripts, and is caused by transparency or seeping of ink from the reverse side of the page. We formulate the problem as one of separating two individual texts, overlapped in the recto and verso maps of the colour channels through a linear convolutional mixing operator, where the mixing coefficients are unknown, while the blur kernels are assumed known a priori or estimated off-line. We exploit statistical techniques of blind source separation to estimate both the unknown model parameters and the ideal, uncorrupted images of the two document sides. We show that recently proposed correlated component analysis techniques overcome the already satisfactory performance of independent component analysis techniques and colour decorrelation, when the two texts are even sensibly correlated.

New insights into comparison between synthetic and practical municipal wastewater in cake layer characteristic analysis of membrane bioreactor.

PubMed

Zhou, Lijie; Zhuang, Wei-Qin; Wang, Xin; Yu, Ke; Yang, Shufang; Xia, Siqing

2017-11-01

In previous studies, cake layer analysis in membrane bioreactor (MBR) was both carried out with synthetic and practical municipal wastewater (SMW and PMW), leading to different results. This study aimed to identify the comparison between SMW and PMW in cake layer characteristic analysis of MBR. Two laboratory-scale anoxic/oxic MBRs were operated for over 90days with SMW and PMW, respectively. Results showed that PMW led to rough cake layer surface with particles, and the aggravation of cake layer formation with thinner and denser cake layer. Additionally, inorganic components, especially Si and Al, in PMW accumulated into cake layer and strengthened the cake layer structure, inducing severer biofouling. However, SMW promoted bacterial metabolism during cake layer formation, thus aggravated the accumulation of organic components into cake layer. Therefore, SMW highlighted the organic components in cake layer, but weakened the inorganic functions in practical MBR operation. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Ionospheric total electron content anomalies due to Typhoon Nakri on 29 May 2008: A nonlinear principal component analysis

NASA Astrophysics Data System (ADS)

Lin, Jyh-Woei

2012-09-01

This paper uses Nonlinear Principal Component Analysis (NLPCA) and Principal Component Analysis (PCA) to determine Total Electron Content (TEC) anomalies in the ionosphere for the Nakri Typhoon on 29 May, 2008 (UTC). NLPCA, PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00-14:00 UT on 29 May 2008 when the wind was most intense. Results show that at a height of approximately 150-200 km the TEC anomaly using NLPCA is more localized; however its intensity increases with height and becomes more widespread. The TEC anomalies are not found by PCA. Potential causes of the results are discussed with emphasis given to vertical acoustic gravity waves. The approximate position of the typhoon's eye can be detected if the GIM is divided into fine enough maps with adequate spatial-resolution at GPS-TEC receivers. This implies that the trace of the typhoon in the regional GIM is caught using NLPCA.

Statistical analysis of Stromboli VLP tremor in the band [0.1-0.5] Hz: some consequences for vibrating structures

NASA Astrophysics Data System (ADS)

de Lauro, E.; de Martino, S.; Falanga, M.; Palo, M.

2006-08-01

We analyze time series of Strombolian volcanic tremor, focusing our attention on the frequency band [0.1-0.5] Hz (very long period (VLP) tremor). Although this frequency band is largely affected by noise, we evidence two significant components by using Independent Component Analysis with the frequencies, respectively, of ~0.2 and ~0.4 Hz. We show that these components display wavefield features similar to those of the high frequency Strombolian signals (>0.5 Hz). In fact, they are radially polarised and located within the crater area. This characterization is lost when an enhancement of energy appears. In this case, the presence of microseismic noise becomes relevant. Investigating the entire large data set available, we determine how microseismic noise influences the signals. We ascribe the microseismic noise source to Scirocco wind. Moreover, our analysis allows one to evidence that the Strombolian conduit vibrates like the asymmetric cavity associated with musical instruments generating self-sustained tones.

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

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

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

Equivalent water height extracted from GRACE gravity field model with robust independent component analysis

NASA Astrophysics Data System (ADS)

Guo, Jinyun; Mu, Dapeng; Liu, Xin; Yan, Haoming; Dai, Honglei

2014-08-01

The Level-2 monthly GRACE gravity field models issued by Center for Space Research (CSR), GeoForschungs Zentrum (GFZ), and Jet Propulsion Laboratory (JPL) are treated as observations used to extract the equivalent water height (EWH) with the robust independent component analysis (RICA). The smoothing radii of 300, 400, and 500 km are tested, respectively, in the Gaussian smoothing kernel function to reduce the observation Gaussianity. Three independent components are obtained by RICA in the spatial domain; the first component matches the geophysical signal, and the other two match the north-south strip and the other noises. The first mode is used to estimate EWHs of CSR, JPL, and GFZ, and compared with the classical empirical decorrelation method (EDM). The EWH STDs for 12 months in 2010 extracted by RICA and EDM show the obvious fluctuation. The results indicate that the sharp EWH changes in some areas have an important global effect, like in Amazon, Mekong, and Zambezi basins.

Simultaneous quantitative analysis of main components in linderae reflexae radix with one single marker.

PubMed

Wang, Li-Li; Zhang, Yun-Bin; Sun, Xiao-Ya; Chen, Sui-Qing

2016-05-08

Establish a quantitative analysis of multi-components by the single marker (QAMS) method for quality evaluation and validate its feasibilities by the simultaneous quantitative assay of four main components in Linderae Reflexae Radix. Four main components of pinostrobin, pinosylvin, pinocembrin, and 3,5-dihydroxy-2-(1- p -mentheneyl)- trans -stilbene were selected as analytes to evaluate the quality by RP-HPLC coupled with a UV-detector. The method was evaluated by a comparison of the quantitative results between the external standard method and QAMS with a different HPLC system. The results showed that no significant differences were found in the quantitative results of the four contents of Linderae Reflexae Radix determined by the external standard method and QAMS (RSD <3%). The contents of four analytes (pinosylvin, pinocembrin, pinostrobin, and Reflexanbene I) in Linderae Reflexae Radix were determined by the single marker of pinosylvin. This fingerprint was the spectra determined by Shimadzu LC-20AT and Waters e2695 HPLC that were equipped with three different columns.

Using independent component analysis for electrical impedance tomography

NASA Astrophysics Data System (ADS)

Yan, Peimin; Mo, Yulong

2004-05-01

Independent component analysis (ICA) is a way to resolve signals into independent components based on the statistical characteristics of the signals. It is a method for factoring probability densities of measured signals into a set of densities that are as statistically independent as possible under the assumptions of a linear model. Electrical impedance tomography (EIT) is used to detect variations of the electric conductivity of the human body. Because there are variations of the conductivity distributions inside the body, EIT presents multi-channel data. In order to get all information contained in different location of tissue it is necessary to image the individual conductivity distribution. In this paper we consider to apply ICA to EIT on the signal subspace (individual conductivity distribution). Using ICA the signal subspace will then be decomposed into statistically independent components. The individual conductivity distribution can be reconstructed by the sensitivity theorem in this paper. Compute simulations show that the full information contained in the multi-conductivity distribution will be obtained by this method.

Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis.

PubMed

Wahle, Fabian; Bollhalder, Lea; Kowatsch, Tobias; Fleisch, Elgar

2017-05-31

Existing research postulates a variety of components that show an impact on utilization of technology-mediated mental health information systems (MHIS) and treatment outcome. Although researchers assessed the effect of isolated design elements on the results of Web-based interventions and the associations between symptom reduction and use of components across computer and mobile phone platforms, there remains uncertainty with regard to which components of technology-mediated interventions for mental health exert the greatest therapeutic gain. Until now, no studies have presented results on the therapeutic benefit associated with specific service components of technology-mediated MHIS for depression. This systematic review aims at identifying components of technology-mediated MHIS for patients with depression. Consequently, all randomized controlled trials comparing technology-mediated treatments for depression to either waiting-list control, treatment as usual, or any other form of treatment for depression were reviewed. Updating prior reviews, this study aims to (1) assess the effectiveness of technology-supported interventions for the treatment of depression and (2) add to the debate on what components in technology-mediated MHIS for the treatment of depression should be standard of care. Systematic searches in MEDLINE, PsycINFO, and the Cochrane Library were conducted. Effect sizes for each comparison between a technology-enabled intervention and a control condition were computed using the standard mean difference (SMD). Chi-square tests were used to test for heterogeneity. Using subgroup analysis, potential sources of heterogeneity were analyzed. Publication bias was examined using visual inspection of funnel plots and Begg's test. Qualitative data analysis was also used. In an explorative approach, a list of relevant components was extracted from the body of literature by consensus between two researchers. Of 6387 studies initially identified, 45 met all inclusion criteria. Programs analyzed showed a significant trend toward reduced depressive symptoms (SMD -0.58, 95% CI -0.71 to -0.45, P<.001). Heterogeneity was large (I2≥76). A total of 15 components were identified. Technology-mediated MHIS for the treatment of depression has a consistent positive overall effect compared to controls. A total of 15 components have been identified. Further studies are needed to quantify the impact of individual components on treatment effects and to identify further components that are relevant for the design of future technology-mediated interventions for the treatment of depression and other mental disorders. ©Fabian Wahle, Lea Bollhalder, Tobias Kowatsch, Elgar Fleisch. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 31.05.2017.

Toward the Design of Evidence-Based Mental Health Information Systems for People With Depression: A Systematic Literature Review and Meta-Analysis

PubMed Central

Fleisch, Elgar

2017-01-01

Background Existing research postulates a variety of components that show an impact on utilization of technology-mediated mental health information systems (MHIS) and treatment outcome. Although researchers assessed the effect of isolated design elements on the results of Web-based interventions and the associations between symptom reduction and use of components across computer and mobile phone platforms, there remains uncertainty with regard to which components of technology-mediated interventions for mental health exert the greatest therapeutic gain. Until now, no studies have presented results on the therapeutic benefit associated with specific service components of technology-mediated MHIS for depression. Objective This systematic review aims at identifying components of technology-mediated MHIS for patients with depression. Consequently, all randomized controlled trials comparing technology-mediated treatments for depression to either waiting-list control, treatment as usual, or any other form of treatment for depression were reviewed. Updating prior reviews, this study aims to (1) assess the effectiveness of technology-supported interventions for the treatment of depression and (2) add to the debate on what components in technology-mediated MHIS for the treatment of depression should be standard of care. Methods Systematic searches in MEDLINE, PsycINFO, and the Cochrane Library were conducted. Effect sizes for each comparison between a technology-enabled intervention and a control condition were computed using the standard mean difference (SMD). Chi-square tests were used to test for heterogeneity. Using subgroup analysis, potential sources of heterogeneity were analyzed. Publication bias was examined using visual inspection of funnel plots and Begg’s test. Qualitative data analysis was also used. In an explorative approach, a list of relevant components was extracted from the body of literature by consensus between two researchers. Results Of 6387 studies initially identified, 45 met all inclusion criteria. Programs analyzed showed a significant trend toward reduced depressive symptoms (SMD –0.58, 95% CI –0.71 to –0.45, P<.001). Heterogeneity was large (I2≥76). A total of 15 components were identified. Conclusions Technology-mediated MHIS for the treatment of depression has a consistent positive overall effect compared to controls. A total of 15 components have been identified. Further studies are needed to quantify the impact of individual components on treatment effects and to identify further components that are relevant for the design of future technology-mediated interventions for the treatment of depression and other mental disorders. PMID:28566267

Viscoplastic analysis of an experimental cylindrical thrust chamber liner

NASA Technical Reports Server (NTRS)

Arya, Vinod K.; Arnold, Steven M.

1991-01-01

A viscoplastic stress-strain analysis of an experimental cylindrical thrust chamber is presented. A viscoelastic constitutive model incorporating a single internal state variable that represents kinematic hardening was employed to investigate whether such a viscoplastic model could predict the experimentally observed behavior of the thrust chamber. Two types of loading cycles were considered: a short cycle of 3.5 sec. duration that corresponded to the experiments, and an extended loading cycle of 485.1 sec. duration that is typical of the Space Shuttle Main Engine (SSME) operating cycle. The analysis qualitatively replicated the deformation behavior of the component as observed in experiments designed to simulate SSME operating conditions. The analysis also showed that the mode and location in the component may depend on the loading cycle. The results indicate that using viscoplastic models for structural analysis can lead to a more realistic life assessment of thrust chambers.

Development and Validation of the Work-Related Well-Being Index: Analysis of the Federal Employee Viewpoint Survey.

PubMed

Eaton, Jennifer L; Mohr, David C; Hodgson, Michael J; McPhaul, Kathleen M

2018-02-01

To describe development and validation of the work-related well-being (WRWB) index. Principal components analysis was performed using Federal Employee Viewpoint Survey (FEVS) data (N = 392,752) to extract variables representing worker well-being constructs. Confirmatory factor analysis was performed to verify factor structure. To validate the WRWB index, we used multiple regression analysis to examine relationships with burnout associated outcomes. Principal Components Analysis identified three positive psychology constructs: "Work Positivity", "Co-worker Relationships", and "Work Mastery". An 11 item index explaining 63.5% of variance was achieved. The structural equation model provided a very good fit to the data. Higher WRWB scores were positively associated with all three employee experience measures examined in regression models. The new WRWB index shows promise as a valid and widely accessible instrument to assess worker well-being.

A morphospace for reef fishes: elongation is the dominant axis of body shape evolution.

PubMed

Claverie, Thomas; Wainwright, Peter C

2014-01-01

Tropical reef fishes are widely regarded as being perhaps the most morphologically diverse vertebrate assemblage on earth, yet much remains to be discovered about the scope and patterns of this diversity. We created a morphospace of 2,939 species spanning 56 families of tropical Indo-Pacific reef fishes and established the primary axes of body shape variation, the phylogenetic consistency of these patterns, and whether dominant patterns of shape change can be accomplished by diverse underlying changes. Principal component analysis showed a major axis of shape variation that contrasts deep-bodied species with slender, elongate forms. Furthermore, using custom methods to compare the elongation vector (axis that maximizes elongation deformation) and the main vector of shape variation (first principal component) for each family in the morphospace, we showed that two thirds of the families diversify along an axis of body elongation. Finally, a comparative analysis using a principal coordinate analysis based on the angles among first principal component vectors of each family shape showed that families accomplish changes in elongation with a wide range of underlying modifications. Some groups such as Pomacentridae and Lethrinidae undergo decreases in body depth with proportional increases in all body regions, while other families show disproportionate changes in the length of the head (e.g., Labridae), the trunk or caudal region in all combinations (e.g., Pempheridae and Pinguipedidae). In conclusion, we found that evolutionary changes in body shape along an axis of elongation dominates diversification in reef fishes. Changes in shape on this axis are thought to have immediate implications for swimming performance, defense from gape limited predators, suction feeding performance and access to some highly specialized habitats. The morphological modifications that underlie changes in elongation are highly diverse, suggesting a role for a range of developmental processes and functional consequences.

Analysis of aroma compounds of pitaya fruit wine

NASA Astrophysics Data System (ADS)

Gong, Xiao; Ma, Lina; Li, Liuji; Yuan, Yuan; Peng, Shaodan; Lin, Mao

2017-12-01

In order to analyze the volatile components in red pitaya fruit wine, the study using headspace solid phase microextractionand gas chromatography-mass spectrometry technology of pitaya fruit juice and wine aroma composition analysis comparison. Results showed that 55 volatile components were detected in red pitaya fruit wine, including 12 kinds of alcohol (18.16%), 18 kinds of esters (66.17%), 7 kinds of acids (5.94%), 11 kinds of alkanes (4.32%), one kind of aldehyde (0.09%), 2 kinds of olefins (0.09%) and 3 kinds of other volatile substances (0.23%). Relative contents among them bigger have 11 species, such as decanoic acid, ethyl ester (22.92%), respectively, diisoamylene (20.75%), octanoic acid, ethyl ester (17.73%), etc. The red pitaya fruit wine contained a lot of aroma components, which offer the products special aroma like brandy, rose and fruit.

Comparative Study of the Volatile Components of Fresh and Fermented Flowers of Alnus sieboldiana (Betulaceae).

PubMed

Ab Ghani, Nurunajah; Ismail, Nor Hadiani; Asakawa, Yoshinori

2016-02-01

Analysis of the volatile components present in the fresh male and female flowers and young leaves shows that 2-phenylethanol is the major component in all these three organs, which play a significant role in the strong resinous aromatic odor. The male flowers contained styrene as a second major compound. The level of styrene does not affect the male flowers odor concentration. The level of β-phenylethyl cinnamate and trans-methyl cinnamate in the fermented male flowers decreased as the fermentation time increased. This was due to the Penicillium enzymatic action on the fermented male flowers.

The Two-Component Virial Theorem and the Physical Properties of Stellar Systems.

PubMed

Dantas; Ribeiro; Capelato; de Carvalho RR

2000-01-01

Motivated by present indirect evidence that galaxies are surrounded by dark matter halos, we investigate whether their physical properties can be described by a formulation of the virial theorem that explicitly takes into account the gravitational potential term representing the interaction of the dark halo with the baryonic or luminous component. Our analysis shows that the application of such a "two-component virial theorem" not only accounts for the scaling relations displayed by, in particular, elliptical galaxies, but also for the observed properties of all virialized stellar systems, ranging from globular clusters to galaxy clusters.

Observations of X-ray flares in G-K dwarfs by XMM-Newton

NASA Astrophysics Data System (ADS)

Pandey, Jeewan Chandra

Eclipsing binary BD +5 706 is best investigated member of rare class of cool Algols, which differ from clasical Algol systems in that the mass gaining component is also a late-type star. The analysis of X-ray lightcurve of this system registered by ROSAT suggested the primary component to be the dominant source of activity in the system (Torres et al, AJ 125, 3237, 2003). We reconstruct the spatial structure of coronal emission within the system according to the method proposed by Siarkowski, and show that coronal emission is most likely attributed to both components.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Extension of similarity test procedures to cooled engine components with insulating ceramic coatings

NASA Technical Reports Server (NTRS)

Gladden, H. J.

1980-01-01

Material thermal conductivity was analyzed for its effect on the thermal performance of air cooled gas turbine components, both with and without a ceramic thermal-barrier material, tested at reduced temperatures and pressures. The analysis shows that neglecting the material thermal conductivity can contribute significant errors when metal-wall-temperature test data taken on a turbine vane are extrapolated to engine conditions. This error in metal temperature for an uncoated vane is of opposite sign from that for a ceramic-coated vane. A correction technique is developed for both ceramic-coated and uncoated components.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data

NASA Astrophysics Data System (ADS)

Xu, Jing; Liu, Xiaofei; Wang, Yutian

2016-08-01

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components.

Music video shot segmentation using independent component analysis and keyframe extraction based on image complexity

NASA Astrophysics Data System (ADS)

Li, Wei; Chen, Ting; Zhang, Wenjun; Shi, Yunyu; Li, Jun

2012-04-01

In recent years, Music video data is increasing at an astonishing speed. Shot segmentation and keyframe extraction constitute a fundamental unit in organizing, indexing, retrieving video content. In this paper a unified framework is proposed to detect the shot boundaries and extract the keyframe of a shot. Music video is first segmented to shots by illumination-invariant chromaticity histogram in independent component (IC) analysis feature space .Then we presents a new metric, image complexity, to extract keyframe in a shot which is computed by ICs. Experimental results show the framework is effective and has a good performance.

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.

Human genome-microbiome interaction: metagenomics frontiers for the aetiopathology of autoimmune diseases.

PubMed

Gundogdu, Aycan; Nalbantoglu, Ufuk

2017-04-01

A short while ago, the human genome and microbiome were analysed simultaneously for the first time as a multi-omic approach. The analyses of heterogeneous population cohorts showed that microbiome components were associated with human genome variations. In-depth analysis of these results reveals that the majority of those relationships are between immune pathways and autoimmune disease-associated microbiome components. Thus, it can be hypothesized that autoimmunity may be associated with homeostatic disequilibrium of the human-microbiome interactome. Further analysis of human genome-human microbiome relationships in disease contexts with tailored systems biology approaches may yield insights into disease pathogenesis and prognosis.

Human genome-microbiome interaction: metagenomics frontiers for the aetiopathology of autoimmune diseases

PubMed Central

Nalbantoglu, Ufuk

2017-01-01

A short while ago, the human genome and microbiome were analysed simultaneously for the first time as a multi-omic approach. The analyses of heterogeneous population cohorts showed that microbiome components were associated with human genome variations. In-depth analysis of these results reveals that the majority of those relationships are between immune pathways and autoimmune disease-associated microbiome components. Thus, it can be hypothesized that autoimmunity may be associated with homeostatic disequilibrium of the human-microbiome interactome. Further analysis of human genome–human microbiome relationships in disease contexts with tailored systems biology approaches may yield insights into disease pathogenesis and prognosis. PMID:28785422

Pre-compound emission in low-energy heavy-ion interactions

NASA Astrophysics Data System (ADS)

Sharma, Manoj Kumar; Shuaib, Mohd.; Sharma, Vijay R.; Yadav, Abhishek; Singh, Pushpendra P.; Singh, Devendra P.; Unnati; Singh, B. P.; Prasad, R.

2017-11-01

Recent experimental studies have shown the presence of pre-compound emission component in heavy ion reactions at low projectile energy ranging from 4 to 7 MeV/nucleons. In earlier measurements strength of the pre-compound component has been estimated from the difference in forward-backward distributions of emitted particles. Present measurement is a part of an ongoing program on the study of reaction dynamics of heavy ion interactions at low energies aimed at investigating the effect of momentum transfer in compound, precompound, complete and incomplete fusion processes in heavy ion reactions. In the present work on the basis of momentum transfer the measurement of the recoil range distributions of heavy residues has been used to decipher the components of compound and pre-compound emission processes in the fusion of 16O projectile with 159Tb and 169Tm targets. The analysis of recoil range distribution measurements show two distinct linear momentum transfer components corresponding to pre-compound and compound nucleus processes are involved. In order to obtain the mean input angular momentum associated with compound and pre-compound emission processes, an online measurement of the spin distributions of the residues has been performed. The analysis of spin distribution indicate that the mean input angular momentum associated with pre-compound products is found to be relatively lower than that associated with compound nucleus process. The pre-compound components obtained from the present analysis are consistent with those obtained from the analysis of excitation functions.

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.

Changes in the dissolved organic matter leaching from soil under severe temperature and N-deposition.

PubMed

Nguyen, Hang Vo-Minh; Choi, Jung Hyun

2015-06-01

In this study, we conducted growth chamber experiments using three types of soil (wetland, rice paddy, and forest) under the conditions of a severe increase in the temperature and N-deposition in order to investigate how extreme weather influences the characteristics of the dissolved organic matter (DOM) leaching from different soil types. This leachate controls the quantity and quality of DOM in surface water systems. After 5 months of incubation, the dissolved organic carbon (DOC) concentrations decreased in the range of 21.1 to 88.9 %, while the specific UV absorption (SUVA) values increased substantially in the range of 19.9 to 319.9 % for all of the samples. Higher increases in the SUVA values were observed at higher temperatures, whereas the opposite trend was observed for samples with N-addition. The parallel factor analysis (PARAFAC) results showed that four fluorescence components: terrestrial humic-like (component 1 (C1)), microbial humic-like (component 2 (C2)), protein-like (component 3 (C3)), and anthropogenic humic-like (component 4 (C4)) constituted the fluorescence matrices of soil samples. During the experiment, labile DOM from the soils was consumed and transformed into resistant aromatic carbon structures and less biodegradable components via microbial processes. The principle component analysis (PCA) results indicated that severe temperatures and N-deposition could enhance the contribution of the aromatic carbon compounds and humic-like components in the soil samples.

Time series analysis of ozone data in Isfahan

NASA Astrophysics Data System (ADS)

Omidvari, M.; Hassanzadeh, S.; Hosseinibalam, F.

2008-07-01

Time series analysis used to investigate the stratospheric ozone formation and decomposition processes. Different time series methods are applied to detect the reason for extreme high ozone concentrations for each season. Data was convert into seasonal component and frequency domain, the latter has been evaluated by using the Fast Fourier Transform (FFT), spectral analysis. The power density spectrum estimated from the ozone data showed peaks at cycle duration of 22, 20, 36, 186, 365 and 40 days. According to seasonal component analysis most fluctuation was in 1999 and 2000, but the least fluctuation was in 2003. The best correlation between ozone and sun radiation was found in 2000. Other variables which are not available cause to this fluctuation in the 1999 and 2001. The trend of ozone is increasing in 1999 and is decreasing in other years.

Compatibility Assessment Tool

NASA Technical Reports Server (NTRS)

Egbert, James Allen

2016-01-01

In support of ground system development for the Space Launch System (SLS), engineers are tasked with building immense engineering models of extreme complexity. The various systems require rigorous analysis of pneumatics, hydraulic, cryogenic, and hypergolic systems. There are certain standards that each of these systems must meet, in the form of pressure vessel system (PVS) certification reports. These reports can be hundreds of pages long, and require many hours to compile. Traditionally, each component is analyzed individually, often utilizing hand calculations in the design process. The objective of this opportunity is to perform these analyses in an integrated fashion with the parametric CADCAE environment. This allows for systems to be analyzed on an assembly level in a semi-automated fashion, which greatly improves accuracy and efficiency. To accomplish this, component specific parameters were stored in the Windchill database to individual Creo Parametric models based on spec control drawings. These parameters were then accessed by using the Prime Analysis within Creo Parametric. MathCAD Prime spreadsheets were created that automatically extracted these parameters, performed calculations, and generated reports. The reports described component compatibility based on local conditions such as pressure, temperature, density, and flow rates. The reports also determined component pairing compatibility, such as properly sizing relief valves with regulators. The reports stored the input conditions that were used to determine compatibility to increase traceability of component selection. The desired workflow for using this tool would begin with a Creo Schematics diagram of a PVS system. This schematic would store local conditions and locations of components. The schematic would then populate an assembly within Creo Parametric, using Windchill database parts. These parts would have their attributes already assigned, and the MathCAD spreadsheets could begin running through database parts to determine which components would be suited for specific locations within the assembly. This eliminates a significant amount of time from the design process, and makes initial analysis assessments more accurate. Each component that would be checked for a location within the assembly would generate a report, showing whether the component was compatible. These reports could be used to generate the PVS report without the need to perform the same analysis multiple times. This process also has the potential to be expanded upon to further automate PVS reports. The integration of software codes or macros could be used to automatically check through hundreds of parts for each location on the schematic. If the software could recognize which type of component would be necessary for each location, it is possible that simply starting the macro could completely choose all the components needed for the schematic, and in turn the system. This would save many hours of work initially selecting components, which could end up saving money. Overall, this process helps to automate initial component selections for PVS systems to fit local design specifications. These selections will automatically generate reports showing how the design criteria are met by the specific component that was chosen. These reports will contribute to easier compilation of the PVS certification reports, which currently take a great amount of time and effort to produce.

Understanding Groups in Outdoor Adventure Education through Social Network Analysis

ERIC Educational Resources Information Center

Jostad, Jeremy; Sibthorp, Jim; Paisley, Karen

2013-01-01

Relationships are a critical component to the experience of an outdoor adventure education (OAE) program, therefore, more fruitful ways of investigating groups is needed. Social network analysis (SNA) is an effective tool to study the relationship structure of small groups. This paper provides an explanation of SNA and shows how it was used by the…

Is It Necessary to Dry Primary Standards before Analysis?

ERIC Educational Resources Information Center

Spraggins, Jeffrey M., II; Williams, Theodore R.

2005-01-01

The thermal gravimetric analysis (TGA) data suggests that the quantity of volatile components in primary standards is less than 1% of the initial weight and differential scanning calorimetry (DSC) data shows that water present in the same chemicals is below the limit of detection of the instrumentation. This suggests that the 1-2 hour drying…

What Klein's "Semantic Gradient" Does and Does Not Really Show: Decomposing Stroop Interference into Task and Informational Conflict Components.

PubMed

Levin, Yulia; Tzelgov, Joseph

2016-01-01

The present study suggests that the idea that Stroop interference originates from multiple components may gain theoretically from integrating two independent frameworks. The first framework is represented by the well-known notion of "semantic gradient" of interference and the second one is the distinction between two types of conflict - the task and the informational conflict - giving rise to the interference (MacLeod and MacDonald, 2000; Goldfarb and Henik, 2007). The proposed integration led to the conclusion that two (i.e., orthographic and lexical components) of the four theoretically distinct components represent task conflict, and the other two (i.e., indirect and direct informational conflict components) represent informational conflict. The four components were independently estimated in a series of experiments. The results confirmed the contribution of task conflict (estimated by a robust orthographic component) and of informational conflict (estimated by a strong direct informational conflict component) to Stroop interference. However, the performed critical review of the relevant literature (see General Discussion), as well as the results of the experiments reported, showed that the other two components expressing each type of conflict (i.e., the lexical component of task conflict and the indirect informational conflict) were small and unstable. The present analysis refines our knowledge of the origins of Stroop interference by providing evidence that each type of conflict has its major and minor contributions. The implications for cognitive control of an automatic reading process are also discussed.

What Klein’s “Semantic Gradient” Does and Does Not Really Show: Decomposing Stroop Interference into Task and Informational Conflict Components

PubMed Central

Levin, Yulia; Tzelgov, Joseph

2016-01-01

The present study suggests that the idea that Stroop interference originates from multiple components may gain theoretically from integrating two independent frameworks. The first framework is represented by the well-known notion of “semantic gradient” of interference and the second one is the distinction between two types of conflict – the task and the informational conflict – giving rise to the interference (MacLeod and MacDonald, 2000; Goldfarb and Henik, 2007). The proposed integration led to the conclusion that two (i.e., orthographic and lexical components) of the four theoretically distinct components represent task conflict, and the other two (i.e., indirect and direct informational conflict components) represent informational conflict. The four components were independently estimated in a series of experiments. The results confirmed the contribution of task conflict (estimated by a robust orthographic component) and of informational conflict (estimated by a strong direct informational conflict component) to Stroop interference. However, the performed critical review of the relevant literature (see General Discussion), as well as the results of the experiments reported, showed that the other two components expressing each type of conflict (i.e., the lexical component of task conflict and the indirect informational conflict) were small and unstable. The present analysis refines our knowledge of the origins of Stroop interference by providing evidence that each type of conflict has its major and minor contributions. The implications for cognitive control of an automatic reading process are also discussed. PMID:26955363

DMT-TAFM: a data mining tool for technical analysis of futures market

NASA Astrophysics Data System (ADS)

Stepanov, Vladimir; Sathaye, Archana

2002-03-01

Technical analysis of financial markets describes many patterns of market behavior. For practical use, all these descriptions need to be adjusted for each particular trading session. In this paper, we develop a data mining tool for technical analysis of the futures markets (DMT-TAFM), which dynamically generates rules based on the notion of the price pattern similarity. The tool consists of three main components. The first component provides visualization of data series on a chart with different ranges, scales, and chart sizes and types. The second component constructs pattern descriptions using sets of polynomials. The third component specifies the training set for mining, defines the similarity notion, and searches for a set of similar patterns. DMT-TAFM is useful to prepare the data, and then reveal and systemize statistical information about similar patterns found in any type of historical price series. We performed experiments with our tool on three decades of trading data fro hundred types of futures. Our results for this data set shows that, we can prove or disprove many well-known patterns based on real data, as well as reveal new ones, and use the set of relatively consistent patterns found during data mining for developing better futures trading strategies.

Hilbert-Huang transform analysis of dynamic and earthquake motion recordings

USGS Publications Warehouse

Zhang, R.R.; Ma, S.; Safak, E.; Hartzell, S.

2003-01-01

This study examines the rationale of Hilbert-Huang transform (HHT) for analyzing dynamic and earthquake motion recordings in studies of seismology and engineering. In particular, this paper first provides the fundamentals of the HHT method, which consist of the empirical mode decomposition (EMD) and the Hilbert spectral analysis. It then uses the HHT to analyze recordings of hypothetical and real wave motion, the results of which are compared with the results obtained by the Fourier data processing technique. The analysis of the two recordings indicates that the HHT method is able to extract some motion characteristics useful in studies of seismology and engineering, which might not be exposed effectively and efficiently by Fourier data processing technique. Specifically, the study indicates that the decomposed components in EMD of HHT, namely, the intrinsic mode function (IMF) components, contain observable, physical information inherent to the original data. It also shows that the grouped IMF components, namely, the EMD-based low- and high-frequency components, can faithfully capture low-frequency pulse-like as well as high-frequency wave signals. Finally, the study illustrates that the HHT-based Hilbert spectra are able to reveal the temporal-frequency energy distribution for motion recordings precisely and clearly.

Component-Level Electronic-Assembly Repair (CLEAR) Spacecraft Circuit Diagnostics by Analog and Complex Signature Analysis

NASA Technical Reports Server (NTRS)

Oeftering, Richard C.; Wade, Raymond P.; Izadnegahdar, Alain

2011-01-01

The Component-Level Electronic-Assembly Repair (CLEAR) project at the NASA Glenn Research Center is aimed at developing technologies that will enable space-flight crews to perform in situ component-level repair of electronics on Moon and Mars outposts, where there is no existing infrastructure for logistics spares. These technologies must provide effective repair capabilities yet meet the payload and operational constraints of space facilities. Effective repair depends on a diagnostic capability that is versatile but easy to use by crew members that have limited training in electronics. CLEAR studied two techniques that involve extensive precharacterization of "known good" circuits to produce graphical signatures that provide an easy-to-use comparison method to quickly identify faulty components. Analog Signature Analysis (ASA) allows relatively rapid diagnostics of complex electronics by technicians with limited experience. Because of frequency limits and the growing dependence on broadband technologies, ASA must be augmented with other capabilities. To meet this challenge while preserving ease of use, CLEAR proposed an alternative called Complex Signature Analysis (CSA). Tests of ASA and CSA were used to compare capabilities and to determine if the techniques provided an overlapping or complementary capability. The results showed that the methods are complementary.

KSC 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT) Report

NASA Technical Reports Server (NTRS)

Barbre, Robert E.

2015-01-01

This report documents analysis results of the Kennedy Space Center updated 50-MHz Doppler Radar Wind Profiler (DRWP) Operational Acceptance Test (OAT). This test was designed to demonstrate that the new DRWP operates in a similar manner to the previous DRWP for use as a situational awareness asset for mission operations at the Eastern Range to identify rapid changes in the wind environment that weather balloons cannot depict. Data examination and two analyses showed that the updated DRWP meets the specifications in the OAT test plan and performs at least as well as the previous DRWP. Data examination verified that the DRWP provides complete profiles every five minutes from 1.8-19.5 km in vertical increments of 150 m. Analysis of 5,426 wind component reports from 49 concurrent DRWP and balloon profiles presented root mean square (RMS) wind component differences around 2.0 m/s. The DRWP's effective vertical resolution (EVR) was found to be 300 m for both the westerly and southerly wind component, which the best EVR possible given the DRWP's vertical sampling interval. A third analysis quantified the sensitivity to rejecting data that do not have adequate signal by assessing the number of first-guess propagations at each altitude. This report documents the data, quality control procedures, methodology, and results of each analysis. It also shows that analysis of the updated DRWP produced results that were at least as good as the previous DRWP with proper rationale. The report recommends acceptance of the updated DRWP for situational awareness usage as per the OAT's intent.

Evaluating Possible Heating Mechanisms Using the Transition Region Line Profiles of Late-Type Stars

NASA Technical Reports Server (NTRS)

Wood, Brian E.; Linsky, Jeffrey L.; Ayres, Thomas R.

1997-01-01

Our analysis of high-resolution Goddard High-Resolution Spectrograph (GHRS) spectra of late-type stars shows that the Si IV and C IV lines formed near 10(exp 5) K can be decomposed into the sum of two Gaussians, a broad component and a narrow component. We find that the flux contribution of the broad components is correlated with both the C IV and X-ray surface fluxes. For main-sequence stars, the widths of the narrow components suggest subsonic nonthermal velocities, and there appears to be a tight correlation between these nonthermal velocities and stellar surface gravity [xi(sub nc) varies as g(sup (-.68 +/-.07))]. For evolved stars with lower surface gravities, the nonthermal velocities suggested by the narrow components are at or just above the sound speed. Nonthermal velocities computed from the widths of the broad components are always highly supersonic. We propose that the broad components are diagnostics for microflare heating. Turbulent dissipation and Alfven waves are both viable candidates for the narrow component heating mechanism. A solar analog for the broad components might be the 'explosive events' detected by the High-Resolution Telescope and Spectrograph (HRTS) experiment. The broad component we observe for the Si IV lambda 1394 line of alpha Cen A, a star that is nearly identical to the Sun, has a FWHM of 109 +/- 10 km/s and is blueshifted by 9 +/- 3 km/s relative to the narrow component. Both of these properties are consistent with the properties of the solar explosive events. However, the alpha Cen A broad component accounts for 25% +/- 4% of the total Si IV line flux, while solar explosive events are currently thought to account for no more than 5% of the Sun's total transition region emission. This discrepancy must be resolved before the connection between broad components and explosive events can be positively established. In addition to our analysis of the Si IV and C IV lines of many stars, we also provide a more thorough analysis of all of the available GHRS data for alpha Cen A (G2 V) and alpha Cen B (K1 V). We find that the transition region lines of both stars have redshifts almost identical to those observed on the Sun: showing an increase with line formation temperature up to about log T = 5.2 and then a rapid decrease. Using the O IV] lines as density diagnostics, we compute electron densities of log n(sub e) = 9.65 +/- 0.20 and log n(sub e) = 9.50 +/- 0.30 for alpha Cen A and alpha Cen B, respectively.

Wave number determination of Pc 1-2 mantle waves considering He++ ions: A Cluster study

NASA Astrophysics Data System (ADS)

Grison, B.; Escoubet, C. P.; Santolík, O.; Cornilleau-Wehrlin, N.; Khotyaintsev, Y.

2014-09-01

The present case study concerns narrowband electromagnetic emission detected in the distant cusp region simultaneously with upgoing plasma flows. The wave properties match the usual properties of the Pc 1-2 mantle waves: small angle between the wave vector and the magnetic field line, left-hand polarization, and propagation toward the ionosphere. We report here the first direct wave vector measurement of these waves (about 1.2 × 10- 2 rad/km) through multi spacecraft analysis using the three magnetic components and, at the same time, through single spacecraft analysis based on the refractive index analysis using the three magnetic components and two electric components. The refractive index analysis offers a simple way to estimate wave numbers in this frequency range. Numerical calculations are performed under the observed plasma conditions. The obtained results show that the ion distribution functions are unstable to ion cyclotron instability at the observed wave vector value, due to the large ion temperature anisotropy. We thus show that these electromagnetic ion cyclotron (EMIC) waves are amplified in the distant cusp region. The Poynting flux of the waves is counterstreaming with respect to the plasma flow. This sense of propagation is consistent with the time necessary to amplify the emissions to the observed level. We point out the role of the wave damping at the He++ gyrofrequency to explain that such waves cannot be observed from the ground at the cusp foot print location.

A new methodology based on functional principal component analysis to study postural stability post-stroke.

PubMed

Sánchez-Sánchez, M Luz; Belda-Lois, Juan-Manuel; Mena-Del Horno, Silvia; Viosca-Herrero, Enrique; Igual-Camacho, Celedonia; Gisbert-Morant, Beatriz

2018-05-05

A major goal in stroke rehabilitation is the establishment of more effective physical therapy techniques to recover postural stability. Functional Principal Component Analysis provides greater insight into recovery trends. However, when missing values exist, obtaining functional data presents some difficulties. The purpose of this study was to reveal an alternative technique for obtaining the Functional Principal Components without requiring the conversion to functional data beforehand and to investigate this methodology to determine the effect of specific physical therapy techniques in balance recovery trends in elderly subjects with hemiplegia post-stroke. A randomized controlled pilot trial was developed. Thirty inpatients post-stroke were included. Control and target groups were treated with the same conventional physical therapy protocol based on functional criteria, but specific techniques were added to the target group depending on the subjects' functional level. Postural stability during standing was quantified by posturography. The assessments were performed once a month from the moment the participants were able to stand up to six months post-stroke. The target group showed a significant improvement in postural control recovery trend six months after stroke that was not present in the control group. Some of the assessed parameters revealed significant differences between treatment groups (P < 0.05). The proposed methodology allows Functional Principal Component Analysis to be performed when data is scarce. Moreover, it allowed the dynamics of recovery of two different treatment groups to be determined, showing that the techniques added in the target group increased postural stability compared to the base protocol. Copyright © 2018 Elsevier Ltd. All rights reserved.

Critical Literacy: Does Advertising Show Gender and Cultural Stereotyping?

ERIC Educational Resources Information Center

Russo, Elizabeth

1996-01-01

The critical literacy component of an adult program developed skills in analyzing media advertising; using math for data analysis, graphing, and computation; interpreting data; and becoming aware of advertising's part in reenforcing gender roles. (SK)

[Content determination of twelve major components in Tibetan medicine Zuozhu Daxi by UPLC].

PubMed

Qu, Yan; Li, Jin-hua; Zhang, Chen; Li, Chun-xue; Dong, Hong-jiao; Wang, Chang-sheng; Zeng, Rui; Chen, Xiao-hu

2015-05-01

A quantitative analytical method of ultra-high performance liquid chromatography (UPLC) was developed for simultaneously determining twelve components in Tibetan medicine Zuozhu Daxi. SIMPCA 12.0 software was used a principal component analysis PCA) and partial small squares analysis (PLSD-DA) on the twelve components in 10 batches from four pharmaceutical factories. Acquity UPLC BEH C15 column (2.1 mm x 100 mm, 1.7 µm) was adopted at the column temperature of 35 °C and eluted with acetonitrile (A) -0.05% phosphate acid solution (B) as the mobile phase with a flow rate of 0. 3 mL · min(-1). The injection volume was 1 µL. The detection wavelengths were set at 210 nm for alantolactone, isoalantolactone and oleanolic; 260 nm for trychnine and brucine; 288 nm for protopine; 306 nm for protopine, resveratrol and piperine; 370 nm for quercetin and isorhamnetin. The results showed a good separation among index components, with a good linearity relationship (R2 = 0.999 6) within the selected concentration range. The average sample recovery rates ranged between 99.44%-101.8%, with RSD between 0.37%-1.7%, indicating the method is rapid and accurate with a good repeatability and stability. The PCA and PLSD-DA analysis on the sample determination results revealed a great difference among samples from different pharmaceutical factories. The twelve components included in this study contributed significantly to the quantitative determination of intrinsic quality of Zuozhu Daxi. The UPLC established for to the quantitative determination of the twelve components can provide scientific basis for the comprehensive quality evaluation of Zuozhu Daxi.

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 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 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

Chemical composition measurements of the low activity waste (LAW) EPA-Series glasses

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

Fox, K.; Edwards, T. B.

2016-03-01

In this report, the Savannah River National Laboratory provides chemical analysis results for a series of simulated low activity waste glasses provided by Pacific Northwest National Laboratory as part of an ongoing development task. The measured chemical composition data are reported and compared with the targeted values for each component for each glass. A detailed review showed no indications of errors in the preparation or measurement of the study glasses. All of the measured sums of oxides for the study glasses fell within the interval of 100.2 to 100.8 wt %, indicating recovery of all components. Comparisons of the targetedmore » and measured chemical compositions showed that the measured values for the glasses met the targeted concentrations within 10% for those components present at more than 5 wt %.« less

GRB-081029: A Step Towards Understanding Multiple Afterglow Components

NASA Technical Reports Server (NTRS)

Holland Stephen T.

2010-01-01

We present an analysis of the unusual optical light curve of the gamma-ray burst-081029 at a redshift of z = 3.8474. We combine X-ray and optical observations from (Swift) with optical and infrared data from REM to obtain a detailed data set extending from approx 10(exp 2)s to approx 10(exp 5)s after the BAT trigger, and from approx.10 keV to 16,000 AA. The X-ray afterglow showed a shallow initial decay followed by u rapid decay after about 18,000 s. The optical afterglow, however, shows an uncharecteristic rise at about 5000 s that has no corresponding feature in the X-ray light curve. The data are not consistent with a single-component jet. It is possible that there are multiple physical components contributing to the afterglow of GRB-081029.

Modulation by EEG features of BOLD responses to interictal epileptiform discharges

PubMed Central

LeVan, Pierre; Tyvaert, Louise; Gotman, Jean

2013-01-01

Introduction EEG-fMRI of interictal epileptiform discharges (IEDs) usually assumes a fixed hemodynamic response function (HRF). This study investigates HRF variability with respect to IED amplitude fluctuations using independent component analysis (ICA), with the goal of improving the specificity of EEG-fMRI analyses. Methods We selected EEG-fMRI data from 10 focal epilepsy patients with a good quality EEG. IED amplitudes were calculated in an average reference montage. The fMRI data were decomposed by ICA and a deconvolution method identified IED-related components by detecting time courses with a significant HRF time-locked to the IEDs (F-test, p<0.05). Individual HRF amplitudes were then calculated for each IED. Components with a significant HRF/IED amplitude correlation (Spearman test, p< 0.05) were compared to the presumed epileptogenic focus and to results of a general linear model (GLM) analysis. Results In 7 patients, at least one IED-related component was concordant with the focus, but many IED-related components were at distant locations. When considering only components with a significant HRF/IED amplitude correlation, distant components could be discarded, significantly increasing the relative proportion of activated voxels in the focus (p=0.02). In the 3 patients without concordant IED-related components, no HRF/IED amplitude correlations were detected inside the brain. Integrating IED-related amplitudes in the GLM significantly improved fMRI signal modeling in the epileptogenic focus in 4 patients (p< 0.05). Conclusion Activations in the epileptogenic focus appear to show significant correlations between HRF and IED amplitudes, unlike distant responses. These correlations could be integrated in the analysis to increase the specificity of EEG-fMRI studies in epilepsy. PMID:20026222

Tin-Platinum catalysts interactions on titania and silica

NASA Astrophysics Data System (ADS)

Nava, N.; Del Angel, P.; Salmones, J.; Baggio-Saitovitch, E.; Santiago, P.

2007-09-01

Pt-Sn was supported on titania and silica, and the resulting interactions between the components in prepared samples and the resulting interactions between the components before and after treatment with hydrogen were characterized by Mössbauer spectroscopy, X-ray diffraction, Rietveld refinement, high-resolution transmission electron microscopy (HRTEM) and catalytic tests data. Results show the presence of Pt and SnO 2 after calcinations, and Pt 3Sn, PtSn and PtSn 3 after reduction. Rietveld analysis shows that some Ti 4+ are replaced by Sn 4+ atoms in the titania structure. Finally, HRTEM and the practically absence of activity observed confirms that metallic platinum is encapsulated.

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.

Cone-Beam Computed Tomography Analysis of Mucosal Thickening in Unilateral Cleft Lip and Palate Maxillary Sinuses.

PubMed

Kula, Katherine; Hale, Lindsay N; Ghoneima, Ahmed; Tholpady, Sunil; Starbuck, John M

2016-11-01

  To compare maxillary mucosal thickening and sinus volumes of unilateral cleft lip and palate subjects (UCLP) with noncleft (nonCLP) controls.   Randomized, retrospective study of cone-beam computed tomographs (CBCT).   University.   Fifteen UCLP subjects and 15 sex- and age-matched non-CLP controls, aged 8 to 14 years.   Following institutional review board approval and reliability tests, Dolphin three-dimensional imaging software was used to segment and slice maxillary sinuses on randomly selected CBCTs. The surface area (SA) of bony sinus and airspace on all sinus slices was determined using Dolphin and multiplied by slice thickness (0.4 mm) to calculate volume. Mucosal thickening was the difference between bony sinus and airspace volumes. The number of slices with bony sinus and airspace outlines was totaled. Right and left sinus values for each group were pooled (t tests, P > .05; n = 30 each group). All measures were compared (principal components analysis, multivariate analysis of variance, analysis of variance) by group and age (P ≤ .016 was considered significant).   Principal components analysis axis 1 and 2 explained 89.6% of sample variance. Principal components analysis showed complete separation based on the sample on axis 1 only. Age groups showed some separation on axis 2. Unilateral cleft lip and palate subjects had significantly smaller bony sinus and airspace volumes, fewer bony and airspace slices, and greater mucosal thickening and percentage mucosal thickening when compared with controls. Older subjects had significantly greater bony sinus and airspace volumes than younger subjects.   Children with UCLP have significantly more maxillary sinus mucosal thickening and smaller sinuses than controls.

Encapsulated Papillary Carcinoma in A Man with Gynecomastia: Ultrasonography, Mammography and Magnetic Resonance Imaging Features with Pathologic Correlation.

PubMed

Yılmaz, Ravza; Cömert, Rana Günöz; Aliyev, Samil; Toktaş, Yücel; Önder, Semen; Emirikçi, Selman; Özmen, Vahit

2018-04-01

Male breast cancer is an uncommon disease that constitutes 1% of all breast cancers and encapsulated papillary carcinoma (EPC) is a rare subtype of malignant male diseases. Gynecomastia is the most common disease of the male breast. We report a 63-year-old male patient with EPC accompanied by gynecomastia that was diagnosed and treated at our breast center. Mammography showed an oval-shaped dense mass with circumscribed margins on the ground of nodular gynecomastia. On ultrasonographic exam, we saw a well-circumscribed complex mass with a solid component which was vascular on Doppler ultrasonography. Magnetic resonance imaging revealed a complex cystic mass containing solid components. Dynamic images showed enhancement of the cystic mass wall and mural components. Tumor stage was evaluated as T2N0. The lesion's histologic examination and immunohistochemical analysis by showing no myoepithelial layer revealed an encapsulated papillary carcinoma. To our knowledge, this is the first case report which describes MR imaging findings of male breast encapsulated papillary cancer.

Extraction of the aortic and pulmonary components of the second heart sound using a nonlinear transient chirp signal model.

PubMed

Xu, J; Durand, L G; Pibarot, P

2001-03-01

The objective of this paper is to adapt and validate a nonlinear transient chirp signal modeling approach for the analysis and synthesis of overlapping aortic (A2) and pulmonary (P2) components of the second heart sound (S2). The approach is based on the time-frequency representation of multicomponent signals for estimating and reconstructing the instantaneous phase and amplitude functions of each component. To evaluate the accuracy of the approach, a simulated S2 with A2 and P2 components having different overlapping intervals (5-30 ms) was synthesized. The simulation results show that the technique is very effective for extracting the two components, even in the presence of noise (-15 dB). The normalized root-mean-squared error between the original A2 and P2 components and their reconstructed versions varied between 1% and 6%, proportionally to the duration of the overlapping interval, and it increased by less than 2% in the presence of noise. The validated technique was then applied to S2 components recorded in pigs under normal or high pulmonary artery pressures. The results show that this approach can successfully isolate and extract overlapping A2 and P2 components from successive S2 recordings obtained from different heartbeats of the same animal as well from different animals.

Characterization of an ntrX mutant of Neisseria gonorrhoeae reveals a response regulator that controls expression of respiratory enzymes in oxidase-positive proteobacteria.

PubMed

Atack, John M; Srikhanta, Yogitha N; Djoko, Karrera Y; Welch, Jessica P; Hasri, Norain H M; Steichen, Christopher T; Vanden Hoven, Rachel N; Grimmond, Sean M; Othman, Dk Seti Maimonah Pg; Kappler, Ulrike; Apicella, Michael A; Jennings, Michael P; Edwards, Jennifer L; McEwan, Alastair G

2013-06-01

NtrYX is a sensor-histidine kinase/response regulator two-component system that has had limited characterization in a small number of Alphaproteobacteria. Phylogenetic analysis of the response regulator NtrX showed that this two-component system is extensively distributed across the bacterial domain, and it is present in a variety of Betaproteobacteria, including the human pathogen Neisseria gonorrhoeae. Microarray analysis revealed that the expression of several components of the respiratory chain was reduced in an N. gonorrhoeae ntrX mutant compared to that in the isogenic wild-type (WT) strain 1291. These included the cytochrome c oxidase subunit (ccoP), nitrite reductase (aniA), and nitric oxide reductase (norB). Enzyme activity assays showed decreased cytochrome oxidase and nitrite reductase activities in the ntrX mutant, consistent with microarray data. N. gonorrhoeae ntrX mutants had reduced capacity to survive inside primary cervical cells compared to the wild type, and although they retained the ability to form a biofilm, they exhibited reduced survival within the biofilm compared to wild-type cells, as indicated by LIVE/DEAD staining. Analyses of an ntrX mutant in a representative alphaproteobacterium, Rhodobacter capsulatus, showed that cytochrome oxidase activity was also reduced compared to that in the wild-type strain SB1003. Taken together, these data provide evidence that the NtrYX two-component system may be a key regulator in the expression of respiratory enzymes and, in particular, cytochrome c oxidase, across a wide range of proteobacteria, including a variety of bacterial pathogens.

Kottamia 74-inch telescope discovery of the new eclipsing binary KAO-EGYPT J225702.44+523222.1.: First CCD photometry and light curve analysis

NASA Astrophysics Data System (ADS)

Shokry, A.; Darwish, M. S.; Saad, S. M.; Eldepsy, M.; Zead, I.

2017-08-01

We present the first multicolor CCD photometry for the newly discovered binary system KAO-EGYPT J225702.44+523222.1. New times of light minimum and new ephemeris were obtained. The VR I light curves were analyzed using WD code, the difference in maximum light at phase 0.25 is modeled with a cool spot on the secondary component. The solution show that the system is A-subtype, overcontact binary with fill-out factor = 42% and low mass ratio, q = 0.275. The two components of spectral types K0 and K1 and the primary component is the massive one. The position of both components on the M-L and M-R relations revealed that the primary component is a main sequence star while the secondary is an evolved component.

Lithology and mineralogy recognition from geochemical logging tool data using multivariate statistical analysis.

PubMed

Konaté, Ahmed Amara; Ma, Huolin; Pan, Heping; Qin, Zhen; Ahmed, Hafizullah Abba; Dembele, N'dji Dit Jacques

2017-10-01

The availability of a deep well that penetrates deep into the Ultra High Pressure (UHP) metamorphic rocks is unusual and consequently offers a unique chance to study the metamorphic rocks. One such borehole is located in the southern part of Donghai County in the Sulu UHP metamorphic belt of Eastern China, from the Chinese Continental Scientific Drilling Main hole. This study reports the results obtained from the analysis of oxide log data. A geochemical logging tool provides in situ, gamma ray spectroscopy measurements of major and trace elements in the borehole. Dry weight percent oxide concentration logs obtained for this study were SiO 2 , K 2 O, TiO 2 , H 2 O, CO 2 , Na 2 O, Fe 2 O 3 , FeO, CaO, MnO, MgO, P 2 O 5 and Al 2 O 3 . Cross plot and Principal Component Analysis methods were applied for lithology characterization and mineralogy description respectively. Cross plot analysis allows lithological variations to be characterized. Principal Component Analysis shows that the oxide logs can be summarized by two components related to the feldspar and hydrous minerals. This study has shown that geochemical logging tool data is accurate and adequate to be tremendously useful in UHP metamorphic rocks analysis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Global loss of a nuclear lamina component, lamin A/C, and LINC complex components SUN1, SUN2, and nesprin-2 in breast cancer.

PubMed

Matsumoto, Ayaka; Hieda, Miki; Yokoyama, Yuhki; Nishioka, Yu; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Matsuura, Nariaki

2015-10-01

Cancer cells exhibit a variety of features indicative of atypical nuclei. However, the molecular mechanisms underlying these phenomena remain to be elucidated. The linker of nucleoskeleton and cytoskeleton (LINC) complex, a nuclear envelope protein complex consisting mainly of the SUN and nesprin proteins, connects nuclear lamina and cytoskeletal filaments and helps to regulate the size and shape of the nucleus. Using immunohistology, we found that a nuclear lamina component, lamin A/C and all of the investigated LINC complex components, SUN1, SUN2, and nesprin-2, were downregulated in human breast cancer tissues. In the majority of cases, we observed lower expression levels of these analytes in samples' cancerous regions as compared to their cancer-associated noncancerous regions (in cancerous regions, percentage of tissue samples exhibiting low protein expression: lamin A/C, 85% [n = 73]; SUN1, 88% [n = 43]; SUN2, 74% [n = 43]; and nesprin-2, 79% [n = 53]). Statistical analysis showed that the frequencies of recurrence and HER2 expression were negatively correlated with lamin A/C expression (P < 0.05), and intrinsic subtype and ki-67 level were associated with nesprin-2 expression (P < 0.05). In addition, combinatorial analysis using the above four parameters showed that all patients exhibited reduced expression of at least one of four components despite the tumor's pathological classification. Furthermore, several cultured breast cancer cell lines expressed less SUN1, SUN2, nesprin-2 mRNA, and lamin A/C compared to noncancerous mammary gland cells. Together, these results suggest that the strongly reduced expression of LINC complex and nuclear lamina components may play fundamental pathological functions in breast cancer progression. © 2015 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

NMR signal analysis to attribute the components to the solid/liquid phases present in mixes and ice creams.

PubMed

Mariette, François; Lucas, Tiphaine

2005-03-09

The NMR relaxation signals from complex products such as ice cream are hard to interpret because of the multiexponential behavior of the relaxation signal and the difficulty of attributing the NMR relaxation components to specific molecule fractions. An attribution of the NMR relaxation parameters is proposed, however, based on an approach that combines quantitative analysis of the spin-spin and spin-lattice relaxation times and the signal intensities with characterization of the ice cream components. We have been able to show that NMR can be used to describe the crystallized and liquid phases separately. The first component of the spin-spin and spin-lattice relaxation describes the behavior of the protons of the crystallized fat in the mix. The amount of fat crystals can then be estimated. In the case of ice cream, only the spin-lattice relaxation signal from the crystallized fraction is relevant. However, it enables the ice protons and the protons of the crystallized fat to be distinguished. The spin-lattice relaxation time can be used to describe the mobility of the protons in the different crystallized phases and also to quantify the amount of ice crystals and fat crystals in the ice cream. The NMR relaxation of the liquid phase of the mix has a biexponential behavior. A first component is attributable to the liquid fraction of the fat and to the sugars, while a second component is attributable to the aqueous phase. Overall, the study shows that despite the complexity of the NMR signal from ice cream, a number of relevant parameters can be extracted to study the influence of the formulation and of the process stages on the ice fraction, the crystallized fat fraction, and the liquid aqueous fraction.

Nonlinear Extraction of Independent Components of Natural Images Using Radial Gaussianization

PubMed Central

Lyu, Siwei; Simoncelli, Eero P.

2011-01-01

We consider the problem of efficiently encoding a signal by transforming it to a new representation whose components are statistically independent. A widely studied linear solution, known as independent component analysis (ICA), exists for the case when the signal is generated as a linear transformation of independent nongaussian sources. Here, we examine a complementary case, in which the source is nongaussian and elliptically symmetric. In this case, no invertible linear transform suffices to decompose the signal into independent components, but we show that a simple nonlinear transformation, which we call radial gaussianization (RG), is able to remove all dependencies. We then examine this methodology in the context of natural image statistics. We first show that distributions of spatially proximal bandpass filter responses are better described as elliptical than as linearly transformed independent sources. Consistent with this, we demonstrate that the reduction in dependency achieved by applying RG to either nearby pairs or blocks of bandpass filter responses is significantly greater than that achieved by ICA. Finally, we show that the RG transformation may be closely approximated by divisive normalization, which has been used to model the nonlinear response properties of visual neurons. PMID:19191599

Assessments of higher-order ionospheric effects on GPS coordinate time series: A case study of CMONOC with longer time series

NASA Astrophysics Data System (ADS)

Jiang, Weiping; Deng, Liansheng; Zhou, Xiaohui; Ma, Yifang

2014-05-01

Higher-order ionospheric (HIO) corrections are proposed to become a standard part for precise GPS data analysis. For this study, we deeply investigate the impacts of the HIO corrections on the coordinate time series by implementing re-processing of the GPS data from Crustal Movement Observation Network of China (CMONOC). Nearly 13 year data are used in our three processing runs: (a) run NO, without HOI corrections, (b) run IG, both second- and third-order corrections are modeled using the International Geomagnetic Reference Field 11 (IGRF11) to model the magnetic field, (c) run ID, the same with IG but dipole magnetic model are applied. Both spectral analysis and noise analysis are adopted to investigate these effects. Results show that for CMONOC stations, HIO corrections are found to have brought an overall improvement. After the corrections are applied, the noise amplitudes decrease, with the white noise amplitudes showing a more remarkable variation. Low-latitude sites are more affected. For different coordinate components, the impacts vary. The results of an analysis of stacked periodograms show that there is a good match between the seasonal amplitudes and the HOI corrections, and the observed variations in the coordinate time series are related to HOI effects. HOI delays partially explain the seasonal amplitudes in the coordinate time series, especially for the U component. The annual amplitudes for all components are decreased for over one-half of the selected CMONOC sites. Additionally, the semi-annual amplitudes for the sites are much more strongly affected by the corrections. However, when diplole model is used, the results are not as optimistic as IGRF model. Analysis of dipole model indicate that HIO delay lead to the increase of noise amplitudes, and that HIO delays with dipole model can generate false periodic signals. When dipole model are used in modeling HIO terms, larger residual and noise are brought in rather than the effective improvements.

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

Navier-Stokes Entropy Controlled Combustion Instability Analysis for Liquid Propellants

NASA Technical Reports Server (NTRS)

Chung, T. J.; Yoon, W. S.

1990-01-01

Navier-Stokes solutions are used to calculate oscillatory components of pressure, velocity, and density, which in turn provide necessary data to compute energy growth factors to determine combustion instability. It is shown that wave instabilities are associated with changes in entropy and the space and time averages of oscillatory components of pressure, velocity and density, together with the mean flow field in the energy equation. Compressible laminar and turbulent flows and reacting flows with hydrogen/oxygen combustion are considered. The SSME combustion/thrust chamber is used for illustration of the theory. The analysis shows that the increase of mean pressure and disturbances consistently results in the increase of instability. It is shown that adequate combustion instability analysis requires at least third order nonlinearity in energy growth or decay.

Discrimination of rectal cancer through human serum using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Li, Xiaozhou; Yang, Tianyue; Li, Siqi; Zhang, Su; Jin, Lili

2015-05-01

In this paper, surface-enhanced Raman spectroscopy (SERS) was used to detect the changes in blood serum components that accompany rectal cancer. The differences in serum SERS data between rectal cancer patients and healthy controls were examined. Postoperative rectal cancer patients also participated in the comparison to monitor the effects of cancer treatments. The results show that there are significant variations at certain wavenumbers which indicates alteration of corresponding biological substances. Principal component analysis (PCA) and parameters of intensity ratios were used on the original SERS spectra for the extraction of featured variables. These featured variables then underwent linear discriminant analysis (LDA) and classification and regression tree (CART) for the discrimination analysis. Accuracies of 93.5 and 92.4 % were obtained for PCA-LDA and parameter-CART, respectively.

High frequency oscillations evoked by peripheral magnetic stimulation.

PubMed

Biller, S; Simon, L; Fiedler, P; Strohmeier, D; Haueisen, J

2011-01-01

The analysis of somatosensory evoked potentials (SEP) and / or fields (SEF) is a well-established and important tool for investigating the functioning of the peripheral and central human nervous system. A standard technique to evoke SEPs / SEFs is the stimulation of the median nerve by using a bipolar electrical stimulus. We aim at an alternative stimulation technique enabling stimulation of deep nerve structures while reducing patient stress and error susceptibility. In the current study, we apply a commercial transcranial magnetic stimulation system for peripheral magnetic stimulation of the median nerve. We compare the results of simultaneously recorded EEG signals to prove applicability of our technique to evoke SEPs including low frequency components (LFC) as well as high frequency oscillations (HFO). Therefore, we compare amplitude, latency and time-frequency characteristics of the SEP of 14 healthy volunteers after electric and magnetic stimulation. Both low frequency components and high frequency oscillations were detected. The HFOs were superimposed onto the primary cortical response N20. Statistical analysis revealed significantly lower amplitudes and increased latencies for LFC and HFO components after magnetic stimulation. The differences indicate the inability of magnetic stimulation to elicit supramaximal responses. A psycho-perceptual evaluation showed that magnetic stimulation was less unpleasant for 12 out of the 14 volunteers. In conclusion, we showed that LFC and HFO components related to median nerve stimulation can be evoked by peripheral magnetic stimulation.

Classification of high-resolution multispectral satellite remote sensing images using extended morphological attribute profiles and independent component analysis

NASA Astrophysics Data System (ADS)

Wu, Yu; Zheng, Lijuan; Xie, Donghai; Zhong, Ruofei

2017-07-01

In this study, the extended morphological attribute profiles (EAPs) and independent component analysis (ICA) were combined for feature extraction of high-resolution multispectral satellite remote sensing images and the regularized least squares (RLS) approach with the radial basis function (RBF) kernel was further applied for the classification. Based on the major two independent components, the geometrical features were extracted using the EAPs method. In this study, three morphological attributes were calculated and extracted for each independent component, including area, standard deviation, and moment of inertia. The extracted geometrical features classified results using RLS approach and the commonly used LIB-SVM library of support vector machines method. The Worldview-3 and Chinese GF-2 multispectral images were tested, and the results showed that the features extracted by EAPs and ICA can effectively improve the accuracy of the high-resolution multispectral image classification, 2% larger than EAPs and principal component analysis (PCA) method, and 6% larger than APs and original high-resolution multispectral data. Moreover, it is also suggested that both the GURLS and LIB-SVM libraries are well suited for the multispectral remote sensing image classification. The GURLS library is easy to be used with automatic parameter selection but its computation time may be larger than the LIB-SVM library. This study would be helpful for the classification application of high-resolution multispectral satellite remote sensing images.

Advanced exergoenvironmental analysis of a near-zero emission power plant with chemical looping combustion.

PubMed

Petrakopoulou, Fontina; Tsatsaronis, George; Morosuk, Tatiana

2012-03-06

Carbon capture and storage (CCS) from power plants can be used to mitigate CO(2) emissions from the combustion of fossil fuels. However, CCS technologies are energy intensive, decreasing the operating efficiency of a plant and increasing its costs. Recently developed advanced exergy-based analyses can uncover the potential for improvement of complex energy conversion systems, as well as qualify and quantify plant component interactions. In this paper, an advanced exergoenvironmental analysis is used for the first time as means to evaluate an oxy-fuel power plant with CO(2) capture. The environmental impacts of each component are split into avoidable/unavoidable and endogenous/exogenous parts. In an effort to minimize the environmental impact of the plant operation, we focus on the avoidable part of the impact (which is also split into endogenous and exogenous parts) and we seek ways to decrease it. The results of the advanced exergoenvironmental analysis show that the majority of the environmental impact related to the exergy destruction of individual components is unavoidable and endogenous. Thus, the improvement potential is rather limited, and the interactions of the components are of lower importance. The environmental impact of construction of the components is found to be significantly lower than that associated with their operation; therefore, our suggestions for improvement focus on measures concerning the reduction of exergy destruction and pollutant formation.

Analysis of Carbon Fiber Reinforced PEEK Hinge Mechanism Articulation Components in a Rotating Hinge Knee Design: A Comparison of In Vitro and Retrieval Findings.

PubMed

Schierjott, Ronja A; Giurea, Alexander; Neuhaus, Hans-Joachim; Schwiesau, Jens; Pfaff, Andreas M; Utzschneider, Sandra; Tozzi, Gianluca; Grupp, Thomas M

2016-01-01

Carbon fiber reinforced poly-ether-ether-ketone (CFR-PEEK) represents a promising alternative material for bushings in total knee replacements, after early clinical failures of polyethylene in this application. The objective of the present study was to evaluate the damage modes and the extent of damage observed on CFR-PEEK hinge mechanism articulation components after in vivo service in a rotating hinge knee (RHK) system and to compare the results with corresponding components subjected to in vitro wear tests. Key question was if there were any similarities or differences between in vivo and in vitro damage characteristics. Twelve retrieved RHK systems after an average of 34.9 months in vivo underwent wear damage analysis with focus on the four integrated CFR-PEEK components and distinction between different damage modes and classification with a scoring system. The analysis included visual examination, scanning electron microscopy, and energy dispersive X-ray spectroscopy, as well as surface roughness and profile measurements. The main wear damage modes were comparable between retrieved and in vitro specimens ( n = 3), whereby the size of affected area on the retrieved components showed a higher variation. Overall, the retrieved specimens seemed to be slightly heavier damaged which was probably attributable to the more complex loading and kinematic conditions in vivo.

GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution

PubMed Central

2011-01-01

Background Ontologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data. Results We present GOMMA, a generic infrastructure for managing and analyzing life science ontologies and their evolution. GOMMA utilizes a generic repository to uniformly and efficiently manage ontology versions and different kinds of mappings. Furthermore, it provides components for ontology matching, and determining evolutionary ontology changes. These components are used by analysis tools, such as the Ontology Evolution Explorer (OnEX) and the detection of unstable ontology regions. We introduce the component-based infrastructure and show analysis results for selected components and life science applications. GOMMA is available at http://dbs.uni-leipzig.de/GOMMA. Conclusions GOMMA provides a comprehensive and scalable infrastructure to manage large life science ontologies and analyze their evolution. Key functions include a generic storage of ontology versions and mappings, support for ontology matching and determining ontology changes. The supported features for analyzing ontology changes are helpful to assess their impact on ontology-dependent applications such as for term enrichment. GOMMA complements OnEX by providing functionalities to manage various versions of mappings between two ontologies and allows combining different match approaches. PMID:21914205

Inventory of File gfs.t06z.pgrb2.0p25.anl

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 005 10 mb VGRD analysis V-Component of Wind [m/s] 006 10 mb -Component of Wind [m/s] 011 20 mb VGRD analysis V-Component of Wind [m/s] 012 20 mb ABSV analysis Absolute UGRD analysis U-Component of Wind [m/s] 018 30 mb VGRD analysis V-Component of Wind [m/s] 019 30 mb

Inventory of File gfs.t06z.pgrb2.0p50.anl

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 005 10 mb VGRD analysis V-Component of Wind [m/s] 006 10 mb -Component of Wind [m/s] 011 20 mb VGRD analysis V-Component of Wind [m/s] 012 20 mb ABSV analysis Absolute UGRD analysis U-Component of Wind [m/s] 018 30 mb VGRD analysis V-Component of Wind [m/s] 019 30 mb

Fabrication of Titanium-Niobium-Zirconium-Tantalium Alloy (TNZT) Bioimplant Components with Controllable Porosity by Spark Plasma Sintering

PubMed Central

Rechtin, Jack; Torresani, Elisa; Ivanov, Eugene; Olevsky, Eugene

2018-01-01

Spark Plasma Sintering (SPS) is used to fabricate Titanium-Niobium-Zirconium-Tantalum alloy (TNZT) powder—based bioimplant components with controllable porosity. The developed densification maps show the effects of final SPS temperature, pressure, holding time, and initial particle size on final sample relative density. Correlations between the final sample density and mechanical properties of the fabricated TNZT components are also investigated and microstructural analysis of the processed material is conducted. A densification model is proposed and used to calculate the TNZT alloy creep activation energy. The obtained experimental data can be utilized for the optimized fabrication of TNZT components with specific microstructural and mechanical properties suitable for biomedical applications. PMID:29364165

LUTE telescope structural design

NASA Technical Reports Server (NTRS)

Ruthven, Gregory

1993-01-01

The major objective of the Lunar Ultraviolet Transit Experiment (LUTE) Telescope Structural Design Study was to investigate the feasibility of designing an ultralightweight 1-m aperture system within optical performance requirements and mass budget constraints. This study uses the results from our previous studies on LUTE as a basis for further developing the LUTE structural architecture. After summarizing our results in Section 2, Section 3 begins with the overall logic we used to determine which telescope 'structural form' should be adopted for further analysis and weight estimates. Specific telescope component analysis showing calculated fundamental frequencies and how they compare with our derived requirements are included. 'First-order' component stress analyses to ensure telescope optical and structural component (i.e. mirrors & main bulkhead) weights are realistic are presented. Layouts of both the primary and tertiary mirrors showing dimensions that are consistent with both our weight and frequency calculations also form part of Section 3. Section 4 presents our calculated values for the predicted thermally induced primary-to-secondary mirror despace motion due to the large temperature range over which LUTE must operate. Two different telescope design approaches (one which utilizes fused quartz metering rods and one which assumes the entire telescope is fabricated from beryllium) are considered in this analysis. We bound the secondary mirror focus mechanism range (in despace) based on these two telescope configurations. In Section 5 we show our overall design of the UVTA (Ultraviolet Telescope Assembly) via an 'exploded view' of the sub-system. The 'exploded view' is annotated to help aid in the understanding of each sub-assembly. We also include a two view layout of the UVTA from which telescope and telescope component dimensions can be measured. We conclude our study with a set of recommendations not only with respect to the LUTE structural architecture but also on other topics related to the overall feasibility of the LUTE telescope sub-system.

Comparison of gray matter volume and thickness for analysis of cortical changes in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Liu, Jiachao; Li, Ziyi; Chen, Kewei; Yao, Li; Wang, Zhiqun; Li, Kunchen; Guo, Xiaojuan

2011-03-01

Gray matter volume and cortical thickness are two indices of concern in brain structure magnetic resonance imaging research. Gray matter volume reflects mixed-measurement information of cerebral cortex, while cortical thickness reflects only the information of distance between inner surface and outer surface of cerebral cortex. Using Scaled Subprofile Modeling based on Principal Component Analysis (SSM_PCA) and Pearson's Correlation Analysis, this study further provided quantitative comparisons and depicted both global relevance and local relevance to comprehensively investigate morphometrical abnormalities in cerebral cortex in Alzheimer's disease (AD). Thirteen patients with AD and thirteen age- and gender-matched healthy controls were included in this study. Results showed that factor scores from the first 8 principal components accounted for ~53.38% of the total variance for gray matter volume, and ~50.18% for cortical thickness. Factor scores from the fifth principal component showed significant correlation. In addition, gray matter voxel-based volume was closely related to cortical thickness alterations in most cortical cortex, especially, in some typical abnormal brain regions such as insula and the parahippocampal gyrus in AD. These findings suggest that these two measurements are effective indices for understanding the neuropathology in AD. Studies using both gray matter volume and cortical thickness can separate the causes of the discrepancy, provide complementary information and carry out a comprehensive description of the morphological changes of brain structure.

Photovoltaic solar panels of crystalline silicon: Characterization and separation.

PubMed

Dias, Pablo Ribeiro; Benevit, Mariana Gonçalves; Veit, Hugo Marcelo

2016-03-01

Photovoltaic panels have a limited lifespan and estimates show large amounts of solar modules will be discarded as electronic waste in a near future. In order to retrieve important raw materials, reduce production costs and environmental impacts, recycling such devices is important. Initially, this article investigates which silicon photovoltaic module's components are recyclable through their characterization using X-ray fluorescence, X-ray diffraction, energy dispersion spectroscopy and atomic absorption spectroscopy. Next, different separation methods are tested to favour further recycling processes. The glass was identified as soda-lime glass, the metallic filaments were identified as tin-lead coated copper, the panel cells were made of silicon and had silver filaments attached to it and the modules' frames were identified as aluminium, all of which are recyclable. Moreover, three different components segregation methods have been studied. Mechanical milling followed by sieving was able to separate silver from copper while chemical separation using sulphuric acid was able to detach the semiconductor material. A thermo gravimetric analysis was performed to evaluate the use of a pyrolysis step prior to the component's removal. The analysis showed all polymeric fractions present degrade at 500 °C. © The Author(s) 2016.

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

PubMed

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

2017-11-01

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

Investigation of Structure and Property of Indian Cocos nucifera L. Fibre

NASA Astrophysics Data System (ADS)

Basu, Gautam; Mishra, Leena; Samanta, Ashis Kumar

2017-12-01

Structure and physico-mechanical properties of Cocos nucifera L. fibre from a specific agro-climatic region of India, was thoroughly studied. Fine structure of the fibre was examined by Fourier Transform Infra-Red (FTIR) spectroscopy, Thermo-Gravimetric Analysis (TGA), X-Ray Diffraction (XRD), component analysis, Scanning Electron Microscope (SEM) and optical microscope. SEM shows prominent longitudinal cracks and micro-pores on the surface. XRD shows a low degree of crystallinity (45%), bigger crystallite size, and even the presence of appreciable amount of non-cellulose matter. FTIR reveals presence of large quantities of hydroxyl, phenolic and aldehyde groups. Component and thermal analyses indicates presence of cellulose and lignin as major components. Physical parameters reveal that, fibres are highly variable in length (range 44-305 mm), and diameter (range 100-795 µm). Mechanical properties of the fibre viz. breaking tenacity, breaking extensibility, specific work of rupture, and coefficient of friction were measured. Microbial decomposition test under soil reveals excellent durability of coconut fibre which makes it appropriate for the application in geotextiles. Mass specific electrical resistance of 4 Ω-kg/m2 indicates its enhanced insulation as compared to the jute.

A cost analysis: processing maple syrup products

Treesearch

Neil K. Huyler; Lawrence D. Garrett

1979-01-01

A cost analysis of processing maple sap to syrup for three fuel types, oil-, wood-, and LP gas-fired evaporators, indicates that: (1) fuel, capital, and labor are the major cost components of processing sap to syrup; (2) wood-fired evaporators show a slight cost advantage over oil- and LP gas-fired evaporators; however, as the cost of wood approaches $50 per cord, wood...

Polysaccharide components from the scape of Musa paradisiaca: main structural features of water-soluble polysaccharide component.

PubMed

Anjaneyalu, Y V; Jagadish, R L; Raju, T S

1997-06-01

Polysaccharide components present in the pseudo-stem (scape) of M. paradisiaca were purified from acetone powder of the scape by delignification followed by extraction with aqueous solvents into water soluble polysaccharide (WSP), EDTA-soluble polysaccharide (EDTA-SP), alkali-soluble polysaccharide (ASP) and alkali-insoluble polysaccharide (AISP) fractions. Sugar compositional analysis showed that WSP and EDTA-SP contained only D-Glc whereas ASP contained D-Glc, L-Ara and D-Xyl in approximately 1:1:10 ratio, respectively, and AISP contained D-Glc, L-Ara and D-Xyl in approximately 10:1:2 ratio, respectively. WSP was further purified by complexation with iso-amylalcohol and characterized by specific rotation, IR spectroscopy, Iodine affinity, ferricyanide number, blue value, hydrolysis with alpha-amylase and glucoamylase, and methylation linkage analysis, and shown to be a amylopectin type alpha-D-glucan.

An oilspill trajectory analysis model with a variable wind deflection angle

USGS Publications Warehouse

Samuels, W.B.; Huang, N.E.; Amstutz, D.E.

1982-01-01

The oilspill trajectory movement algorithm consists of a vector sum of the surface drift component due to wind and the surface current component. In the U.S. Geological Survey oilspill trajectory analysis model, the surface drift component is assumed to be 3.5% of the wind speed and is rotated 20 degrees clockwise to account for Coriolis effects in the Northern Hemisphere. Field and laboratory data suggest, however, that the deflection angle of the surface drift current can be highly variable. An empirical formula, based on field observations and theoretical arguments relating wind speed to deflection angle, was used to calculate a new deflection angle at each time step in the model. Comparisons of oilspill contact probabilities to coastal areas calculated for constant and variable deflection angles showed that the model is insensitive to this changing angle at low wind speeds. At high wind speeds, some statistically significant differences in contact probabilities did appear. ?? 1982.

Guided Wave Propagation Study on Laminated Composites by Frequency-Wavenumber Technique

NASA Technical Reports Server (NTRS)

Tian, Zhenhua; Yu, Lingyu; Leckey, Cara A. C.

2014-01-01

Toward the goal of delamination detection and quantification in laminated composites, this paper examines guided wave propagation and wave interaction with delamination damage in laminated carbon fiber reinforced polymer (CFRP) composites using frequency-wavenumber (f-kappa) analysis. Three-dimensional elastodynamic finite integration technique (EFIT) is used to acquire simulated time-space wavefields for a CFRP composite. The time-space wavefields show trapped waves in the delamination region. To unveil the wave propagation physics, the time-space wavefields are further analyzed by using two-dimensional (2D) Fourier transforms (FT). In the analysis results, new f-k components are observed when the incident guided waves interact with the delamination damage. These new f-kappa components in the simulations are experimentally verified through data obtained from scanning laser Doppler vibrometer (SLDV) tests. By filtering the new f-kappa components, delamination damage is detected and quantified.

Simultaneous determination of rifampicin, isoniazid and pyrazinamide in tablet preparations by multivariate spectrophotometric calibration.

PubMed

Goicoechea, H C; Olivieri, A C

1999-08-01

The use of multivariate spectrophotometric calibration is presented for the simultaneous determination of the active components of tablets used in the treatment of pulmonary tuberculosis. The resolution of ternary mixtures of rifampicin, isoniazid and pyrazinamide has been accomplished by using partial least squares (PLS-1) regression analysis. Although the components show an important degree of spectral overlap, they have been simultaneously determined with high accuracy and precision, rapidly and with no need of nonaqueous solvents for dissolving the samples. No interference has been observed from the tablet excipients. A comparison is presented with the related multivariate method of classical least squares (CLS) analysis, which is shown to yield less reliable results due to the severe spectral overlap among the studied compounds. This is highlighted in the case of isoniazid, due to the small absorbances measured for this component.

Economic sustainability assessment in semi-steppe rangelands.

PubMed

Mofidi Chelan, Morteza; Alijanpour, Ahmad; Barani, Hossein; Motamedi, Javad; Azadi, Hossein; Van Passel, Steven

2018-05-08

This study was conducted to determine indices and components of economic sustainability assessment in the pastoral units of Sahand summer rangelands. The method was based on descriptive-analytical survey (experts and researchers) with questionnaires. Analysis of variance showed that the mean values of economic components are significantly different from each other and the efficiency component has the highest mean value (0.57). The analysis of rangeland pastoral units with the technique for order-preference by similarity to ideal solution (TOPSIS) indicated that from an economic sustainability standpoint, Garehgol (Ci = 0.519) and Badir Khan (Ci = 0.129), pastoral units ranked first and last, respectively. This study provides a clear understanding of existing resources and opportunities for policy makers that is crucial to approach economic sustainable development. Accordingly, this study can help better define sustainable development goals and monitor the progress of achieving them. Copyright © 2018 Elsevier B.V. All rights reserved.

Sequential analysis of hydrochemical data for watershed characterization.

PubMed

Thyne, Geoffrey; Güler, Cüneyt; Poeter, Eileen

2004-01-01

A methodology for characterizing the hydrogeology of watersheds using hydrochemical data that combine statistical, geochemical, and spatial techniques is presented. Surface water and ground water base flow and spring runoff samples (180 total) from a single watershed are first classified using hierarchical cluster analysis. The statistical clusters are analyzed for spatial coherence confirming that the clusters have a geological basis corresponding to topographic flowpaths and showing that the fractured rock aquifer behaves as an equivalent porous medium on the watershed scale. Then principal component analysis (PCA) is used to determine the sources of variation between parameters. PCA analysis shows that the variations within the dataset are related to variations in calcium, magnesium, SO4, and HCO3, which are derived from natural weathering reactions, and pH, NO3, and chlorine, which indicate anthropogenic impact. PHREEQC modeling is used to quantitatively describe the natural hydrochemical evolution for the watershed and aid in discrimination of samples that have an anthropogenic component. Finally, the seasonal changes in the water chemistry of individual sites were analyzed to better characterize the spatial variability of vertical hydraulic conductivity. The integrated result provides a method to characterize the hydrogeology of the watershed that fully utilizes traditional data.

[Balanced scorecard for performance measurement of a nursing organization in a Korean hospital].

PubMed

Hong, Yoonmi; Hwang, Kyung Ja; Kim, Mi Ja; Park, Chang Gi

2008-02-01

The purpose of this study was to develop a balanced scorecard (BSC) for performance measurement of a Korean hospital nursing organization and to evaluate the validity and reliability of performance measurement indicators. Two hundred fifty-nine nurses in a Korean hospital participated in a survey questionnaire that included 29-item performance evaluation indicators developed by investigators of this study based on the Kaplan and Norton's BSC (1992). Cronbach's alpha was used to test the reliability of the BSC. Exploratory and confirmatory factor analysis with a structure equation model (SEM) was applied to assess the construct validity of the BSC. Cronbach's alpha of 29 items was .948. Factor analysis of the BSC showed 5 principal components (eigen value >1.0) which explained 62.7% of the total variance, and it included a new one, community service. The SEM analysis results showed that 5 components were significant for the hospital BSC tool. High degree of reliability and validity of this BSC suggests that it may be used for performance measurements of a Korean hospital nursing organization. Future studies may consider including a balanced number of nurse managers and staff nurses in the study. Further data analysis on the relationships among factors is recommended.

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

[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.

6-C polarization analysis using point measurements of translational and rotational ground-motion: theory and applications

NASA Astrophysics Data System (ADS)

Sollberger, David; Greenhalgh, Stewart A.; Schmelzbach, Cedric; Van Renterghem, Cédéric; Robertsson, Johan O. A.

2018-04-01

We provide a six-component (6-C) polarization model for P-, SV-, SH-, Rayleigh-, and Love-waves both inside an elastic medium as well as at the free surface. It is shown that single-station 6-C data comprised of three components of rotational motion and three components of translational motion provide the opportunity to unambiguously identify the wave type, propagation direction, and local P- and S-wave velocities at the receiver location by use of polarization analysis. To extract such information by conventional processing of three-component (3-C) translational data would require large and dense receiver arrays. The additional rotational components allow the extension of the rank of the coherency matrix used for polarization analysis. This enables us to accurately determine the wave type and wave parameters (propagation direction and velocity) of seismic phases, even if more than one wave is present in the analysis time window. This is not possible with standard, pure-translational 3-C recordings. In order to identify modes of vibration and to extract the accompanying wave parameters, we adapt the multiple signal classification algorithm (MUSIC). Due to the strong nonlinearity of the MUSIC estimator function, it can be used to detect the presence of specific wave types within the analysis time window at very high resolution. We show how the extracted wavefield properties can be used, in a fully automated way, to separate the wavefield into its different wave modes using only a single 6-C recording station. As an example, we apply the method to remove surface wave energy while preserving the underlying reflection signal and to suppress energy originating from undesired directions, such as side-scattered waves.

Searching for the main anti-bacterial components in artificial Calculus bovis using UPLC and microcalorimetry coupled with multi-linear regression analysis.

PubMed

Zang, Qing-Ce; Wang, Jia-Bo; Kong, Wei-Jun; Jin, Cheng; Ma, Zhi-Jie; Chen, Jing; Gong, Qian-Feng; Xiao, Xiao-He

2011-12-01

The fingerprints of artificial Calculus bovis extracts from different solvents were established by ultra-performance liquid chromatography (UPLC) and the anti-bacterial activities of artificial C. bovis extracts on Staphylococcus aureus (S. aureus) growth were studied by microcalorimetry. The UPLC fingerprints were evaluated using hierarchical clustering analysis. Some quantitative parameters obtained from the thermogenic curves of S. aureus growth affected by artificial C. bovis extracts were analyzed using principal component analysis. The spectrum-effect relationships between UPLC fingerprints and anti-bacterial activities were investigated using multi-linear regression analysis. The results showed that peak 1 (taurocholate sodium), peak 3 (unknown compound), peak 4 (cholic acid), and peak 6 (chenodeoxycholic acid) are more significant than the other peaks with the standard parameter estimate 0.453, -0.166, 0.749, 0.025, respectively. So, compounds cholic acid, taurocholate sodium, and chenodeoxycholic acid might be the major anti-bacterial components in artificial C. bovis. Altogether, this work provides a general model of the combination of UPLC chromatography and anti-bacterial effect to study the spectrum-effect relationships of artificial C. bovis extracts, which can be used to discover the main anti-bacterial components in artificial C. bovis or other Chinese herbal medicines with anti-bacterial effects. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Smoothing of the bivariate LOD score for non-normal quantitative traits.

PubMed

Buil, Alfonso; Dyer, Thomas D; Almasy, Laura; Blangero, John

2005-12-30

Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

PAH Baselines for Amazonic Surficial Sediments: A Case of Study in Guajará Bay and Guamá River (Northern Brazil).

PubMed

Rodrigues, Camila Carneiro Dos Santos; Santos, Ewerton; Ramos, Brunalisa Silva; Damasceno, Flaviana Cardoso; Correa, José Augusto Martins

2018-06-01

The 16 priority PAH were determined in sediment samples from the insular zone of Guajará Bay and Guamá River (Southern Amazon River mouth). Low hydrocarbon levels were observed and naphthalene was the most representative PAH. The low molecular weight PAH represented 51% of the total PAH. Statistical analysis showed that the sampling sites are not significantly different. Source analysis by PAH ratios and principal component analysis revealed that PAH are primary from a few rate of fossil fuel combustion, mainly related to the local small community activity. All samples presented no biological stress or damage potencial according to the sediment quality guidelines. This study discuss baselines for PAH in surface sediments from Amazonic aquatic systems based on source determination by PAH ratios and principal component analysis, sediment quality guidelines and through comparison with previous studies data.

[In vitro transdermal delivery of the active fraction of xiangfusiwu decoction based on principal component analysis].

PubMed

Li, Zhen-Hao; Liu, Pei; Qian, Da-Wei; Li, Wei; Shang, Er-Xin; Duan, Jin-Ao

2013-06-01

The objective of the present study was to establish a method based on principal component analysis (PCA) for the study of transdermal delivery of multiple components in Chinese medicine, and to choose the best penetration enhancers for the active fraction of Xiangfusiwu decoction (BW) with this method. Improved Franz diffusion cells with isolated rat abdomen skins were carried out to experiment on the transdermal delivery of six active components, including ferulic acid, paeoniflorin, albiflorin, protopine, tetrahydropalmatine and tetrahydrocolumbamine. The concentrations of these components were determined by LC-MS/MS, then the total factor scores of the concentrations at different times were calculated using PCA and were employed instead of the concentrations to compute the cumulative amounts and steady fluxes, the latter of which were considered as the indexes for optimizing penetration enhancers. The results showed that compared to the control group, the steady fluxes of the other groups increased significantly and furthermore, 4% azone with 1% propylene glycol manifested the best effect. The six components could penetrate through skin well under the action of penetration enhancers. The method established in this study has been proved to be suitable for the study of transdermal delivery of multiple components, and it provided a scientific basis for preparation research of Xiangfusiwu decoction and moreover, it could be a reference for Chinese medicine research.

Daily rainfall forecasting for one year in a single run using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

Effective modelling and prediction of smaller time step rainfall is reported to be very difficult owing to its highly erratic nature. Accurate forecast of daily rainfall for longer duration (multi time step) may be exceptionally helpful in the efficient planning and management of water resources systems. Identification of inherent patterns in a rainfall time series is also important for an effective water resources planning and management system. In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component. In order to forecast the time series for longer time step (365 days-one window length), the signal and noise components of the time series are forecasted separately and then added together. The results of the study show that the method of SSA could extract the various components of the time series effectively and could also forecast the daily rainfall time series for longer duration such as one year in a single run with reasonable accuracy.

A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run.

PubMed

Armeanu, Daniel; Andrei, Jean Vasile; Lache, Leonard; Panait, Mirela

2017-01-01

The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets.

A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run

PubMed Central

Armeanu, Daniel; Lache, Leonard; Panait, Mirela

2017-01-01

The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets. PMID:28742100

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

H.Zhang, P. Titus, P. Rogoff, A.Zolfaghari, D. Mangra, M. Smith

The National Spherical Torus Experiment (NSTX) is a low aspect ratio, spherical torus (ST) configuration device which is located at Princeton Plasma Physics Laboratory (PPPL) This device is presently being updated to enhance its physics by doubling the TF field to 1 Tesla and increasing the plasma current to 2 Mega-amperes. The upgrades include a replacement of the centerstack and addition of a second neutral beam. The upgrade analyses have two missions. The first is to support design of new components, principally the centerstack, the second is to qualify existing NSTX components for higher loads, which will increase by amore » factor of four. Cost efficiency was a design goal for new equipment qualification, and reanalysis of the existing components. Showing that older components can sustain the increased loads has been a challenging effort in which designs had to be developed that would limit loading on weaker components, and would minimize the extent of modifications needed. Two areas representing this effort have been chosen to describe in more details: analysis of the current distribution in the new TF inner legs, and, second, analysis of the out-of-plane support of the existing TF outer legs.« less

The effect of loving-kindness meditation on positive emotions: a meta-analytic review.

PubMed

Zeng, Xianglong; Chiu, Cleo P K; Wang, Rong; Oei, Tian P S; Leung, Freedom Y K

2015-01-01

While it has been suggested that loving-kindness meditation (LKM) is an effective practice for promoting positive emotions, the empirical evidence in the literature remains unclear. Here, we provide a systematic review of 24 empirical studies (N = 1759) on LKM with self-reported positive emotions. The effect of LKM on positive emotions was estimated with meta-analysis, and the influence of variations across LKM interventions was further explored with subgroup analysis and meta-regression. The meta-analysis showed that (1) medium effect sizes for LKM interventions on daily positive emotions in both wait-list controlled RCTs and non-RCT studies; and (2) small to large effect sizes for the on-going practice of LKM on immediate positive emotions across different comparisons. Further analysis showed that (1) interventions focused on loving-kindness had medium effect size, but interventions focused on compassion showed small effect sizes; (2) the length of interventions and the time spent on meditation did not influence the effect sizes, but the studies without didactic components in interventions had small effect sizes. A few individual studies reported that the nature of positive emotions and individual differences also influenced the results. In sum, LKM practice and interventions are effective in enhancing positive emotions, but more studies are needed to identify the active components of the interventions, to compare different psychological operations, and to explore the applicability in clinical populations.

The effect of loving-kindness meditation on positive emotions: a meta-analytic review

PubMed Central

Zeng, Xianglong; Chiu, Cleo P. K.; Wang, Rong; Oei, Tian P. S.; Leung, Freedom Y. K.

2015-01-01

While it has been suggested that loving-kindness meditation (LKM) is an effective practice for promoting positive emotions, the empirical evidence in the literature remains unclear. Here, we provide a systematic review of 24 empirical studies (N = 1759) on LKM with self-reported positive emotions. The effect of LKM on positive emotions was estimated with meta-analysis, and the influence of variations across LKM interventions was further explored with subgroup analysis and meta-regression. The meta-analysis showed that (1) medium effect sizes for LKM interventions on daily positive emotions in both wait-list controlled RCTs and non-RCT studies; and (2) small to large effect sizes for the on-going practice of LKM on immediate positive emotions across different comparisons. Further analysis showed that (1) interventions focused on loving-kindness had medium effect size, but interventions focused on compassion showed small effect sizes; (2) the length of interventions and the time spent on meditation did not influence the effect sizes, but the studies without didactic components in interventions had small effect sizes. A few individual studies reported that the nature of positive emotions and individual differences also influenced the results. In sum, LKM practice and interventions are effective in enhancing positive emotions, but more studies are needed to identify the active components of the interventions, to compare different psychological operations, and to explore the applicability in clinical populations. PMID:26579061

Direct Analysis in Real Time by Mass Spectrometric Technique for Determining the Variation in Metabolite Profiles of Cinnamomum tamala Nees and Eberm Genotypes

PubMed Central

Singh, Vineeta; Gupta, Atul Kumar; Singh, S. P.; Kumar, Anil

2012-01-01

Cinnamomum tamala Nees & Eberm. is an important traditional medicinal plant, mentioned in various ancient literatures such as Ayurveda. Several of its medicinal properties have recently been proved. To characterize diversity in terms of metabolite profiles of Cinnamomum tamala Nees and Eberm genotypes, a newly emerging mass spectral ionization technique direct time in real time (DART) is very helpful. The DART ion source has been used to analyze an extremely wide range of phytochemicals present in leaves of Cinnamomum tamala. Ten genotypes were assessed for the presence of different phytochemicals. Phytochemical analysis showed the presence of mainly terpenes and phenols. These constituents vary in the different genotypes of Cinnamomum tamala. Principal component analysis has also been employed to analyze the DART data of these Cinnamomum genotypes. The result shows that the genotype of Cinnamomum tamala could be differentiated using DART MS data. The active components present in Cinnamomum tamala may be contributing significantly to high amount of antioxidant property of leaves and, in turn, conditional effects for diabetic patients. PMID:22701361

[Study on Commercial Specification of Lonicerae Japonicae Flos].

PubMed

Zhou, Jie; Zou, Lin; Liu, Wei; Bian, Li-hua; Wang, Xiao; Zhang, Yong-qing; Dan, Staerk

2015-04-01

To provide the basis data for the institute of commercial specification standard of Lonicerae Japonicae Flos. 39 samples of Lonicerae Japonicae Flos commercial of different grades in market were collected, and vernier caliper and electronic balance were used to measure the numbers of flower bud and blooming rate per 0. 5 g, contamination content, browning degree, milden and rot, length, upside diameter, middle diameter and bottom diameter of Lonicerae Japonicae Flos. The content of neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, rutin, galuteolin,3,5-icaffeoylquinic acid and 4,5-dicaffeoylquinic acid were detected by HPLC. Correlation analysis, principal component analysis and cluster analysis were used by SPSS to analyze all index data,and the correlation of appearance characteristics and intrinsic active constituents was discussed. The numbers of flower bud and blooming rate per 0. 5 g, contamination content and browning degree were principal component indexes. The length of flower bud showed a significant correlation with galuteolin content, and the browning degree and upside diameter showed a significant correlation with chlorogenic acid content. Lonicerae Japonicae Flos commercial should be divided into four specification grades by sieved indexes.

Genotype evaluation of cowpea seeds (Vigna unguiculata) using 1H qNMR combined with exploratory tools and solid-state NMR.

PubMed

Alves Filho, Elenilson G; Silva, Lorena M A; Teofilo, Elizita M; Larsen, Flemming H; de Brito, Edy S

2017-01-01

The ultimate aim of this study was to apply a non-targeted chemometric analysis (principal component analysis and hierarchical clustering analysis using the heat map approach) of NMR data to investigate the variability of organic compounds in nine genotype cowpea seeds, without any complex pre-treatment. In general, both exploratory tools show that Tvu 233, CE-584, and Setentão genotypes presented higher amount mainly of raffinose and Tvu 382 presented the highest content of choline and least content of raffinose. The evaluation of the aromatic region showed the Setentão genotype with highest content of niacin/vitamin B3 whereas Tvu 382 with lowest amount. To investigate rigid and mobile components in the seeds cotyledon, 13 C CP and SP/MAS solid-state NMR experiments were performed. The cotyledon of the cowpea comprised a rigid part consisting of starch as well as a soft portion made of starch, fatty acids, and protein. The variable contact time experiment suggests the presence of lipid-amylose complexes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Characterization of volatile profile from ten different varieties of Chinese jujubes by HS-SPME/GC-MS coupled with E-nose.

PubMed

Chen, Qinqin; Song, Jianxin; Bi, Jinfeng; Meng, Xianjun; Wu, Xinye

2018-03-01

Volatile profile of ten different varieties of fresh jujubes was characterized by HS-SPME/GC-MS (headspace solid phase micro-extraction combined with gas chromatography-mass spectrometry) and E-nose (electronic nose). GC-MS results showed that a total of 51 aroma compounds were identified in jujubes, hexanoic acid, hexanal, (E)-2-hexenal, (Z)-2-heptenal, benzaldehyde and (E)-2-nonenal were the main aroma components with contributions that over 70%. Differentiation of jujube varieties was conducted by cluster analysis of GC-MS data and principal component analysis & linear discriminant analysis of E-nose data. Both results showed that jujubes could be mainly divided into two groups: group A (JZ, PDDZ, JSXZ and LWZZ) and group B (BZ, YZ, MZ, XZ and DZ). There were significant differences in contents of alcohols, acids and aromatic compounds between group A and B. GC-MS coupled with E-nose could be a fast and accurate method to identify the general flavor difference in different varieties of jujubes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Model-free fMRI group analysis using FENICA.

PubMed

Schöpf, V; Windischberger, C; Robinson, S; Kasess, C H; Fischmeister, F PhS; Lanzenberger, R; Albrecht, J; Kleemann, A M; Kopietz, R; Wiesmann, M; Moser, E

2011-03-01

Exploratory analysis of functional MRI data allows activation to be detected even if the time course differs from that which is expected. Independent Component Analysis (ICA) has emerged as a powerful approach, but current extensions to the analysis of group studies suffer from a number of drawbacks: they can be computationally demanding, results are dominated by technical and motion artefacts, and some methods require that time courses be the same for all subjects or that templates be defined to identify common components. We have developed a group ICA (gICA) method which is based on single-subject ICA decompositions and the assumption that the spatial distribution of signal changes in components which reflect activation is similar between subjects. This approach, which we have called Fully Exploratory Network Independent Component Analysis (FENICA), identifies group activation in two stages. ICA is performed on the single-subject level, then consistent components are identified via spatial correlation. Group activation maps are generated in a second-level GLM analysis. FENICA is applied to data from three studies employing a wide range of stimulus and presentation designs. These are an event-related motor task, a block-design cognition task and an event-related chemosensory experiment. In all cases, the group maps identified by FENICA as being the most consistent over subjects correspond to task activation. There is good agreement between FENICA results and regions identified in prior GLM-based studies. In the chemosensory task, additional regions are identified by FENICA and temporal concatenation ICA that we show is related to the stimulus, but exhibit a delayed response. FENICA is a fully exploratory method that allows activation to be identified without assumptions about temporal evolution, and isolates activation from other sources of signal fluctuation in fMRI. It has the advantage over other gICA methods that it is computationally undemanding, spotlights components relating to activation rather than artefacts, allows the use of familiar statistical thresholding through deployment of a higher level GLM analysis and can be applied to studies where the paradigm is different for all subjects. Copyright © 2010 Elsevier Inc. All rights reserved.

AEROFROSH: a shock condition calculator for multi-component fuel aerosol-laden flows

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

Campbell, Matthew Frederick; Haylett, D. R.; Davidson, D. F.

Here, this paper introduces an algorithm that determines the thermodynamic conditions behind incident and reflectedshocksinaerosol-ladenflows.Importantly,the algorithm accounts for the effects of droplet evaporation on post-shock properties. Additionally, this article describes an algorithm for resolving the effects of multiple-component- fuel droplets. This article presents the solution methodology and compares the results to those of another similar shock calculator. It also provides examples to show the impact of droplets on post-shock properties and the impact that multi-component fuel droplets have on shock experimental parameters. Finally, this paper presents a detailed uncertainty analysis of this algorithm’s calculations given typical exper- imental uncertainties

Decomposition of ECG by linear filtering.

PubMed

Murthy, I S; Niranjan, U C

1992-01-01

A simple method is developed for the delineation of a given electrocardiogram (ECG) signal into its component waves. The properties of discrete cosine transform (DCT) are exploited for the purpose. The transformed signal is convolved with appropriate filters and the component waves are obtained by computing the inverse transform (IDCT) of the filtered signals. The filters are derived from the time signal itself. Analysis of continuous strips of ECG signals with various arrhythmias showed that the performance of the method is satisfactory both qualitatively and quantitatively. The small amplitude P wave usually had a high percentage rms difference (PRD) compared to the other large component waves.

AEROFROSH: a shock condition calculator for multi-component fuel aerosol-laden flows

DOE PAGES

Campbell, Matthew Frederick; Haylett, D. R.; Davidson, D. F.; ...

2015-08-18

Here, this paper introduces an algorithm that determines the thermodynamic conditions behind incident and reflectedshocksinaerosol-ladenflows.Importantly,the algorithm accounts for the effects of droplet evaporation on post-shock properties. Additionally, this article describes an algorithm for resolving the effects of multiple-component- fuel droplets. This article presents the solution methodology and compares the results to those of another similar shock calculator. It also provides examples to show the impact of droplets on post-shock properties and the impact that multi-component fuel droplets have on shock experimental parameters. Finally, this paper presents a detailed uncertainty analysis of this algorithm’s calculations given typical exper- imental uncertainties

Automatic removal of eye-movement and blink artifacts from EEG signals.

PubMed

Gao, Jun Feng; Yang, Yong; Lin, Pan; Wang, Pei; Zheng, Chong Xun

2010-03-01

Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

A symmetrical subtraction combined with interpolated values for eliminating scattering from fluorescence EEM data.

PubMed

Xu, Jing; Liu, Xiaofei; Wang, Yutian

2016-08-05

Parallel factor analysis is a widely used method to extract qualitative and quantitative information of the analyte of interest from fluorescence emission-excitation matrix containing unknown components. Big amplitude of scattering will influence the results of parallel factor analysis. Many methods of eliminating scattering have been proposed. Each of these methods has its advantages and disadvantages. The combination of symmetrical subtraction and interpolated values has been discussed. The combination refers to both the combination of results and the combination of methods. Nine methods were used for comparison. The results show the combination of results can make a better concentration prediction for all the components. Copyright © 2016 Elsevier B.V. All rights reserved.

Component mode synthesis and large deflection vibrations of complex structures. [beams and trusses

NASA Technical Reports Server (NTRS)

Mei, C.

1984-01-01

The accuracy of the NASTRAN modal synthesis analysis was assessed by comparing it with full structure NASTRAN and nine other modal synthesis results using a nine-bay truss. A NASTRAN component mode transient response analysis was also performed on the free-free truss structure. A finite element method was developed for nonlinear vibration of beam structures subjected to harmonic excitation. Longitudinal deformation and inertia are both included in the formula. Tables show the finite element free vibration results with and without considering the effects of longitudinal deformation and inertia as well as the frequency ratios for a simply supported and a clamped beam subjected to a uniform harmonic force.

Study of ionospheric anomalies due to impact of typhoon using Principal Component Analysis and image processing

NASA Astrophysics Data System (ADS)

LIN, JYH-WOEI

2012-08-01

Principal Component Analysis (PCA) and image processing are used to determine Total Electron Content (TEC) anomalies in the F-layer of the ionosphere relating to Typhoon Nakri for 29 May, 2008 (UTC). PCA and image processing are applied to the global ionospheric map (GIM) with transforms conducted for the time period 12:00-14:00 UT on 29 May, 2008 when the wind was most intense. Results show that at a height of approximately 150-200 km the TEC anomaly is highly localized; however, it becomes more intense and widespread with height. Potential causes of these results are discussed with emphasis given to acoustic gravity waves caused by wind force.

Iris recognition based on robust principal component analysis

NASA Astrophysics Data System (ADS)

Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong

2014-11-01

Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

Spectral Comparison and Stability of Red Regions on Jupiter

NASA Technical Reports Server (NTRS)

Simon, A. A.; Carlson, R. W.; Sanchez-Lavega, A.

2013-01-01

A study of absolute color on Jupiter from Hubble Space Telescope imaging data shows that the Great Red Spot (GRS) is not the reddest region of the planet. Rather, a transient red cyclone visible in 1995 and the North Equatorial Belt both show redder spectra than the GRS (i.e., more absorption at blue and green wavelengths). This cyclone is unique among vortices in that it is intensely colored yet low altitude, unlike the GRS. Temporal analysis shows that the darkest regions of the NEB are relative constant in color from 1995 to 2008, while the slope of the GRS core may vary slightly. Principal component analysis shows several spectral components are needed, in agreement with past work, and further highlights the differences between regions. These color differences may be indicative of the same chromophore(s) under different conditions, such as mixing with white clouds, longer UV irradiation at higher altitude, and thermal processing, or may indicate abundance variations in colored compounds. A single compound does not fit the spectrum of any region well and mixes of multiple compounds including NH4SH, photolyzed NH3, hydrocarbons, and possibly P4, are likely needed to fully match each spectrum.

Evaluation of CDOM sources and their links with water quality in the lakes of Northeast China using fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Zhao, Ying; Song, Kaishan; Wen, Zhidan; Fang, Chong; Shang, Yingxin; Lv, Lili

2017-07-01

The spatial distributions of the fluorescence intensities Fmax for chromophoric dissolved organic matter (CDOM) components, the fluorescence indices (FI370 and FI310) and their correlations with water quality of 19 lakes in the Songhua River Basin (SHRB) across semiarid regions of Northeast China were examined with the data collected in September 2012 and 2015. The 19 lakes were divided into two groups according to EC (threshold value = 800 μS cm-1): fresh water (N = 13) and brackish water lakes (N = 6). The fluorescent characteristics of CDOM in the 19 lakes were investigated using excitation-emission matrix fluorescence spectroscopy (EEM) coupled with parallel factor (PARAFAC) and multivariate analysis. Two humic-like components (C1 and C3), one tryptophan-like component (C2), and one tyrosine-like component (C4) were identified by PARAFAC. The component C4 was not included in subsequent analyses due to the strong scatter in some colloidal water samples from brackish water lakes. The correlations between Fmax for the three EEM-PARAFAC extracted CDOM components C1-C3, the fluorescence indices (FI370 and FI310) and the water quality parameters (i.e., TN, TP, Chl-a, pH, EC, turbidity (Turb) and dissolved organic carbon (DOC)) were determined by redundancy analysis (RDA). The results of RDA analysis showed that spatial variation in land cover, pollution sources, and salinity/EC gradients in water quality affected Fmax for the fluorescent components C1-C3 and the fluorescence indices (FI370 and FI310). Further examination indicated that the CDOM fluorescent components and the fluorescence indices (FI370 and FI310) did not significantly differ (t-test, p > 0.05) in fresh water (N = 13) and brackish water lakes (N = 6). There was a difference in the distribution of the average Fmax for the CDOM fluorescent components between C1 to C3 from agricultural sources and urban wastewater sources in hypereutrophic brackish water lakes. The Fmax for humic-like components C1 and C3 spatially varied with land cover among the 19 lakes. Our results indicated that the spatial distributions of Fmax for CDOM fluorescent components and their correlations with water quality can be evaluated by EEM-PARAFAC and multivariate analysis among the 19 lakes across semiarid regions of Northeast China, which has potential implication for lakes with similar genesis.

A new questionnaire for measuring quality of life - the Stark QoL.

PubMed

Hardt, Jochen

2015-10-26

The Stark questionnaire measures health-related quality of life (QoL) using pictures almost exclusively. It is supplemented by a minimum of words. It comprises a mental and a physical health component. A German sample of n = 500 subjects, age and gender stratified, filled out the Stark Qol questionnaire along with various other questionnaires via internet. The physical component shows good reliability (Cronbach's alpha = McDonalds Omega = greatest lower bound = .93), the mental component can be improved (Cronbach's alpha = .63, McDonalds Omega = .72, greatest lower bound = .77). Confirmatory factor analysis shows a good fit (Bentlers CFI = .97). Construct validity was proven. The Stark QoL is a promising new development in measuring QoL, it is a short and easy to apply questionnaire. Additionally, it is particularly promising for international research.

Chemistry, antioxidant, antibacterial and antifungal activities of volatile oils and their components.

PubMed

De Martino, Laura; De Feo, Vincenzo; Fratianni, Florinda; Nazzaro, Filomena

2009-12-01

The present paper reports the chemical composition, antioxidant and antibacterial activities of several essential oils and their components. Analysis showed that three oils (Carum carvi L., Verbena officinalis L. and Majorana hortensis L.) contained predominantly oxygenated monoterpenes, while others studied (Pimpinella anisum L., Foeniculum vulgare Mill.) mainly contained anethole. C. carvi, V. officinalis and M. hortensis oils exhibited the most potent antioxidant activity, due their contents of carvacrol, anethole and estragol. Antibacterial action was assessed against a range of pathogenic and useful bacteria and fungi of agro-food interest. V. officinalis and C. carvi oils proved the most effective, in particular against Bacillus cereus and Pseudomonas aeruginosa. Carvacrol proved most active against Escherichia coli, and completely inhibited the growth of Penicillium citrinum. The oils proved inactive towards some Lactobacilli strains, whereas single components showed an appreciable activity. These results may be important for use of the essential oils as natural preservatives for food products.

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

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.

A probability index for surface zonda wind occurrence at Mendoza city through vertical sounding principal components analysis

NASA Astrophysics Data System (ADS)

Otero, Federico; Norte, Federico; Araneo, Diego

2018-01-01

The aim of this work is to obtain an index for predicting the probability of occurrence of zonda event at surface level from sounding data at Mendoza city, Argentine. To accomplish this goal, surface zonda wind events were previously found with an objective classification method (OCM) only considering the surface station values. Once obtained the dates and the onset time of each event, the prior closest sounding for each event was taken to realize a principal component analysis (PCA) that is used to identify the leading patterns of the vertical structure of the atmosphere previously to a zonda wind event. These components were used to construct the index model. For the PCA an entry matrix of temperature ( T) and dew point temperature (Td) anomalies for the standard levels between 850 and 300 hPa was build. The analysis yielded six significant components with a 94 % of the variance explained and the leading patterns of favorable weather conditions for the development of the phenomenon were obtained. A zonda/non-zonda indicator c can be estimated by a logistic multiple regressions depending on the PCA component loadings, determining a zonda probability index \\widehat{c} calculable from T and Td profiles and it depends on the climatological features of the region. The index showed 74.7 % efficiency. The same analysis was performed by adding surface values of T and Td from Mendoza Aero station increasing the index efficiency to 87.8 %. The results revealed four significantly correlated PCs with a major improvement in differentiating zonda cases and a reducing of the uncertainty interval.

A Principal Component Analysis/Fuzzy Comprehensive Evaluation for Rockburst Potential in Kimberlite

NASA Astrophysics Data System (ADS)

Pu, Yuanyuan; Apel, Derek; Xu, Huawei

2018-02-01

Kimberlite is an igneous rock which sometimes bears diamonds. Most of the diamonds mined in the world today are found in kimberlite ores. Burst potential in kimberlite has not been investigated, because kimberlite is mostly mined using open-pit mining, which poses very little threat of rock bursting. However, as the mining depth keeps increasing, the mines convert to underground mining methods, which can pose a threat of rock bursting in kimberlite. This paper focuses on the burst potential of kimberlite at a diamond mine in northern Canada. A combined model with the methods of principal component analysis (PCA) and fuzzy comprehensive evaluation (FCE) is developed to process data from 12 different locations in kimberlite pipes. Based on calculated 12 fuzzy evaluation vectors, 8 locations show a moderate burst potential, 2 locations show no burst potential, and 2 locations show strong and violent burst potential, respectively. Using statistical principles, a Mahalanobis distance is adopted to build a comprehensive fuzzy evaluation vector for the whole mine and the final evaluation for burst potential is moderate, which is verified by a practical rockbursting situation at mine site.

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-01

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: the case of domain motions.

PubMed

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-14

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

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.

Development of high performance scientific components for interoperability of computing packages

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

Gulabani, Teena Pratap

2008-01-01

Three major high performance quantum chemistry computational packages, NWChem, GAMESS and MPQC have been developed by different research efforts following different design patterns. The goal is to achieve interoperability among these packages by overcoming the challenges caused by the different communication patterns and software design of each of these packages. A chemistry algorithm is hard to develop as well as being a time consuming process; integration of large quantum chemistry packages will allow resource sharing and thus avoid reinvention of the wheel. Creating connections between these incompatible packages is the major motivation of the proposed work. This interoperability is achievedmore » by bringing the benefits of Component Based Software Engineering through a plug-and-play component framework called Common Component Architecture (CCA). In this thesis, I present a strategy and process used for interfacing two widely used and important computational chemistry methodologies: Quantum Mechanics and Molecular Mechanics. To show the feasibility of the proposed approach the Tuning and Analysis Utility (TAU) has been coupled with NWChem code and its CCA components. Results show that the overhead is negligible when compared to the ease and potential of organizing and coping with large-scale software applications.« less

Paratesticular dedifferentiated liposarcoma with leiomyosarcomatous differentiation: a case report with a review of literature.

PubMed

Hatanaka, Kazuhito; Yoshioka, Takako; Tasaki, Takashi; Tanimoto, Akihide

2013-08-23

Paratesticular liposarcoma is a rare neoplasm, described in single case studies or components of larger studies, as histologically well-differentiated liposarcoma (WDL) and dedifferentiated liposarcoma (DL). However, leiomyosarcomatous differentiation is an extremely rare occurrence in WDL and DL. We report a case of leiomyosarcomatous differentiation in a 77-year-old man. The patient presented with a painless right scrotal mass. Magnetic resonance imaging showed a large mass along the right spermatic cord. The resected mass, measuring 17.5 × 12 × 5 cm, was composed of a high-grade pleomorphic undifferentiated sarcomatous component with necrosis. Atypical smooth muscle differentiation was also detected. Additional tumor sampling revealed the presence of a WDL component. Immunohistochemical analysis of the pleomorphic sarcomatous component showed positive staining for MDM2 and CDK4, and negative staining for alpha smooth muscle actin (αSMA) and desmin. The smooth muscle component was positive for αSMA and desmin, and negative for MDM2 and CDK4. Extension from primary retroperitoneal sarcoma was not proved. We diagnosed of DL with leiomyosarcomatous differentiation. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1484291498104021.

Paratesticular dedifferentiated liposarcoma with leiomyosarcomatous differentiation: a case report with a review of literature

PubMed Central

2013-01-01

Abstract Paratesticular liposarcoma is a rare neoplasm, described in single case studies or components of larger studies, as histologically well-differentiated liposarcoma (WDL) and dedifferentiated liposarcoma (DL). However, leiomyosarcomatous differentiation is an extremely rare occurrence in WDL and DL. We report a case of leiomyosarcomatous differentiation in a 77-year-old man. The patient presented with a painless right scrotal mass. Magnetic resonance imaging showed a large mass along the right spermatic cord. The resected mass, measuring 17.5 × 12 × 5 cm, was composed of a high-grade pleomorphic undifferentiated sarcomatous component with necrosis. Atypical smooth muscle differentiation was also detected. Additional tumor sampling revealed the presence of a WDL component. Immunohistochemical analysis of the pleomorphic sarcomatous component showed positive staining for MDM2 and CDK4, and negative staining for alpha smooth muscle actin (αSMA) and desmin. The smooth muscle component was positive for αSMA and desmin, and negative for MDM2 and CDK4. Extension from primary retroperitoneal sarcoma was not proved. We diagnosed of DL with leiomyosarcomatous differentiation. Virtual slides The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1484291498104021. PMID:23971887

Principal Component Analysis of Cerebellar Shape on MRI Separates SCA Types 2 and 6 into Two Archetypal Modes of Degeneration

PubMed Central

Jung, Brian C.; Choi, Soo I.; Du, Annie X.; Cuzzocreo, Jennifer L.; Geng, Zhuo Z.; Ying, Howard S.; Perlman, Susan L.; Toga, Arthur W.; Prince, Jerry L.

2014-01-01

Although “cerebellar ataxia” is often used in reference to a disease process, presumably there are different underlying pathogenetic mechanisms for different subtypes. Indeed, spinocerebellar ataxia (SCA) types 2 and 6 demonstrate complementary phenotypes, thus predicting a different anatomic pattern of degeneration. Here, we show that an unsupervised classification method, based on principal component analysis (PCA) of cerebellar shape characteristics, can be used to separate SCA2 and SCA6 into two classes, which may represent disease-specific archetypes. Patients with SCA2 (n=11) and SCA6 (n=7) were compared against controls (n=15) using PCA to classify cerebellar anatomic shape characteristics. Within the first three principal components, SCA2 and SCA6 differed from controls and from each other. In a secondary analysis, we studied five additional subjects and found that these patients were consistent with the previously defined archetypal clusters of clinical and anatomical characteristics. Secondary analysis of five subjects with related diagnoses showed that disease groups that were clinically and pathophysiologically similar also shared similar anatomic characteristics. Specifically, Archetype #1 consisted of SCA3 (n=1) and SCA2, suggesting that cerebellar syndromes accompanied by atrophy of the pons may be associated with a characteristic pattern of cerebellar neurodegeneration. In comparison, Archetype #2 was comprised of disease groups with pure cerebellar atrophy (episodic ataxia type 2 (n=1), idiopathic late-onset cerebellar ataxias (n=3), and SCA6). This suggests that cerebellar shape analysis could aid in discriminating between different pathologies. Our findings further suggest that magnetic resonance imaging is a promising imaging biomarker that could aid in the diagnosis and therapeutic management in patients with cerebellar syndromes. PMID:22258915

Simulation and analysis of conjunctive use with MODFLOW's farm process

USGS Publications Warehouse

Hanson, R.T.; Schmid, W.; Faunt, C.C.; Lockwood, B.

2010-01-01

The extension of MODFLOW onto the landscape with the Farm Process (MF-FMP) facilitates fully coupled simulation of the use and movement of water from precipitation, streamflow and runoff, groundwater flow, and consumption by natural and agricultural vegetation throughout the hydrologic system at all times. This allows for more complete analysis of conjunctive use water-resource systems than previously possible with MODFLOW by combining relevant aspects of the landscape with the groundwater and surface water components. This analysis is accomplished using distributed cell-by-cell supply-constrained and demand-driven components across the landscape within " water-balance subregions" comprised of one or more model cells that can represent a single farm, a group of farms, or other hydrologic or geopolitical entities. Simulation of micro-agriculture in the Pajaro Valley and macro-agriculture in the Central Valley are used to demonstrate the utility of MF-FMP. For Pajaro Valley, the simulation of an aquifer storage and recovery system and related coastal water distribution system to supplant coastal pumpage was analyzed subject to climate variations and additional supplemental sources such as local runoff. For the Central Valley, analysis of conjunctive use from different hydrologic settings of northern and southern subregions shows how and when precipitation, surface water, and groundwater are important to conjunctive use. The examples show that through MF-FMP's ability to simulate natural and anthropogenic components of the hydrologic cycle, the distribution and dynamics of supply and demand can be analyzed, understood, and managed. This analysis of conjunctive use would be difficult without embedding them in the simulation and are difficult to estimate a priori. Journal compilation ?? 2010 National Ground Water Association. No claim to original US government works.

X-ray and optical observations of 2 new cataclysmic variables

NASA Technical Reports Server (NTRS)

Singh, K. P.; Szkody, P.; Barrett, P.; Schlegel, E.; White, N. E.; Silber, A.; Fierce, E.; Hoard, D.; Hakala, P. J.; Piirola, V.;

Three dimensional tracking with misalignment between display and control axes

NASA Technical Reports Server (NTRS)

Ellis, Stephen R.; Tyler, Mitchell; Kim, Won S.; Stark, Lawrence

1992-01-01

Human operators confronted with misaligned display and control frames of reference performed three dimensional, pursuit tracking in virtual environment and virtual space simulations. Analysis of the components of the tracking errors in the perspective displays presenting virtual space showed that components of the error due to visual motor misalignment may be linearly separated from those associated with the mismatch between display and control coordinate systems. Tracking performance improved with several hours practice despite previous reports that such improvement did not take place.

The research of statistical properties of colorimetric features of screens with a three-component color formation principle

NASA Astrophysics Data System (ADS)

Zharinov, I. O.; Zharinov, O. O.

2017-12-01

The problem of the research is concerned with quantitative analysis of influence of technological variation of the screen color profile parameters on chromaticity coordinates of the displayed image. Some mathematical expressions which approximate the two-dimensional distribution of chromaticity coordinates of an image, which is displayed on the screen with a three-component color formation principle were proposed. Proposed mathematical expressions show the way to development of correction techniques to improve reproducibility of the colorimetric features of displays.

UTE bi-component analysis of T2* relaxation in articular cartilage

PubMed Central

Shao, H.; Chang, E.Y.; Pauli, C.; Zanganeh, S.; Bae, W.; Chung, C.B.; Tang, G.; Du, J.

2015-01-01

SUMMARY Objectives To determine T2* relaxation in articular cartilage using ultrashort echo time (UTE) imaging and bi-component analysis, with an emphasis on the deep radial and calcified cartilage. Methods Ten patellar samples were imaged using two-dimensional (2D) UTE and Car-Purcell-Meiboom-Gill (CPMG) sequences. UTE images were fitted with a bi-component model to calculate T2* and relative fractions. CPMG images were fitted with a single-component model to calculate T2. The high signal line above the subchondral bone was regarded as the deep radial and calcified cartilage. Depth and orientation dependence of T2*, fraction and T2 were analyzed with histopathology and polarized light microscopy (PLM), confirming normal regions of articular cartilage. An interleaved multi-echo UTE acquisition scheme was proposed for in vivo applications (n = 5). Results The short T2* values remained relatively constant across the cartilage depth while the long T2* values and long T2* fractions tended to increase from subchondral bone to the superficial cartilage. Long T2*s and T2s showed significant magic angle effect for all layers of cartilage from the medial to lateral facets, while the short T2* values and T2* fractions are insensitive to the magic angle effect. The deep radial and calcified cartilage showed a mean short T2* of 0.80 ± 0.05 ms and short T2* fraction of 39.93 ± 3.05% in vitro, and a mean short T2* of 0.93 ± 0.58 ms and short T2* fraction of 35.03 ± 4.09% in vivo. Conclusion UTE bi-component analysis can characterize the short and long T2* values and fractions across the cartilage depth, including the deep radial and calcified cartilage. The short T2* values and T2* fractions are magic angle insensitive. PMID:26382110

Effects on noise properties of GPS time series caused by higher-order ionospheric corrections

NASA Astrophysics Data System (ADS)

Jiang, Weiping; Deng, Liansheng; Li, Zhao; Zhou, Xiaohui; Liu, Hongfei

2014-04-01

Higher-order ionospheric (HOI) effects are one of the principal technique-specific error sources in precise global positioning system (GPS) analysis. These effects also influence the non-linear characteristics of GPS coordinate time series. In this paper, we investigate these effects on coordinate time series in terms of seasonal variations and noise amplitudes. Both power spectral techniques and maximum likelihood estimators (MLE) are used to evaluate these effects quantitatively and qualitatively. Our results show an overall improvement for the analysis of global sites if HOI effects are considered. We note that the noise spectral index that is used for the determination of the optimal noise models in our analysis ranged between -1 and 0 both with and without HOI corrections, implying that the coloured noise cannot be removed by these corrections. However, the corrections were found to have improved noise properties for global sites. After the corrections were applied, the noise amplitudes at most sites decreased, among which the white noise amplitudes decreased remarkably. The white noise amplitudes of up to 81.8% of the selected sites decreased in the up component, and the flicker noise of 67.5% of the sites decreased in the north component. Stacked periodogram results show that, no matter whether the HOI effects are considered or not, a common fundamental period of 1.04 cycles per year (cpy), together with the expected annual and semi-annual signals, can explain all peaks of the north and up components well. For the east component, however, reasonable results can be obtained only based on HOI corrections. HOI corrections are useful for better detecting the periodic signals in GPS coordinate time series. Moreover, the corrections contributed partly to the seasonal variations of the selected sites, especially for the up component. Statistically, HOI corrections reduced more than 50% and more than 65% of the annual and semi-annual amplitudes respectively at the selected sites.

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.

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.

Supplemental protein from dairy products increases body weight and vitamin D improves physical performance in older adults: a systematic review and meta-analysis.

PubMed

Dewansingh, Priya; Melse-Boonstra, Alida; Krijnen, Wim P; van der Schans, Cees P; Jager-Wittenaar, Harriët; van den Heuvel, Ellen G H M

2018-01-01

The purpose of these systematic review and meta-analysis was to assess the effectiveness of dairy components on nutritional status and physical fitness in older adults, as evidence for efficacy of the supplementation of these components is inconclusive. Scopus and MEDLINE were searched. Main inclusion criteria for articles were as follows: double-blind, randomized, placebo-controlled trials including participants aged ≥55 years who received dairy components or a placebo. Outcome measures were nutrient status (body weight and body mass index) and physical fitness (body composition, muscle strength, and physical performance). Thirty-six trials with 4947participants were included. Most trials investigated protein and vitamin D supplementation and showed no effect on the outcomes. Meta-analysis on the effect of protein on body weight showed a significant increase in mean difference of 1.13 kg (95% confidence interval, 0.59-1.67). This effect increased by selecting trials with study a duration of 6 months in which less nourished and physically fit participants were included. Trials where the participants were (pre-)frail, inactive older adults or when supplementing ≥20 g of protein per day tended to increase lean body mass. Only small significant effects of vitamin D supplementation on Timed Up and Go (mean difference -0.75 seconds; 95% confidence interval -1.44 to -0.07) were determined. This effect increased when vitamin D doses ranged between 400 and 1000 IU. Additional large randomized controlled trials of ≥6 months are needed regarding the effect of dairy components containing an adequate amount of vitamin D (400-1000 IU) and/or protein (≥20 g) on nutritional status and physical fitness in malnourished or frail older adults. Copyright © 2017 Elsevier Inc. All rights reserved.

The structural basis for the functional comparability of factor VIII and the long-acting variant recombinant factor VIII Fc fusion protein

DOE PAGES

Leksa, N. C.; Chiu, P. -L.; Bou-Assaf, G. M.; ...

2017-05-03

Fusion of the human IgG 1 Fc domain to the C-terminal C2 domain of B-domain-deleted (BDD) factor VIII (FVIII) results in the recombinant FVIII Fc (rFVIIIFc) fusion protein, which has a 1.5-fold longer half-life in humans. To assess the structural properties of rFVIIIFc by comparing its constituent FVIII and Fc elements with their respective isolated components, and evaluating their structural independence within rFVIIIFc. rFVIIIFc and its isolated FVIII and Fc components were compared by the use of hydrogen–deuterium exchange mass spectrometry (HDX-MS). The structure of rFVIIIFc was also evaluated by the use of X-ray crystallography, small-angle X-ray scattering (SAXS), andmore » electron microscopy (EM). The degree of steric interference by the appended Fc domain was assessed by EM and surface plasmon resonance (SPR). HDX-MS analysis of rFVIIIFc revealed that fusion caused no structural perturbations in FVIII or Fc. The rFVIIIFc crystal structure showed that the FVIII component is indistinguishable from published BDD FVIII structures. The Fc domain was not observed, indicating high mobility. SAXS analysis was consistent with an ensemble of rigid-body models in which the Fc domain exists in a largely extended orientation relative to FVIII. Binding of Fab fragments of anti-C2 domain antibodies to BDD FVIII was visualized by EM, and the affinities of the corresponding intact antibodies for BDD FVIII and rFVIIIFc were comparable by SPR analysis. Thus, the FVIII and Fc components of rFVIIIFc are structurally indistinguishable from their isolated constituents, and show a high degree of structural independence, consistent with the functional comparability of rFVIIIFc and unmodified FVIII.« less

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

PubMed Central

2015-01-01

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377

Relativistic Iron K Emission and Absorption in the Seyfert 1.9 Galaxy MCG-05-23-16

NASA Technical Reports Server (NTRS)

Braito, V.; Reeves, J. N.; Dewangan, G. C.; George, I.; Griffiths, R.; Markowitz, A.; Nandra, K.; Porquet, D.; Ptak, A.; Turner, T. J.;

Analysis of Soluble Proteins in Natural Cordyceps sinensis from Different Producing Areas by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis and Two-dimensional Electrophoresis

PubMed Central

Li, Chun-Hong; Zuo, Hua-Li; Zhang, Qian; Wang, Feng-Qin; Hu, Yuan-Jia; Qian, Zheng-Ming; Li, Wen-Jia; Xia, Zhi-Ning; Yang, Feng-Qing

2017-01-01

Background: As one of the bioactive components in Cordyceps sinensis (CS), proteins were rarely used as index components to study the correlation between the protein components and producing areas of natural CS. Objective: Protein components of 26 natural CS samples produced in Qinghai, Tibet, and Sichuan provinces were analyzed and compared to investigate the relationship among 26 different producing areas. Materials and Methods: Proteins from 26 different producing areas were extracted by Tris-HCl buffer with Triton X-100, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2-DE). Results: The SDS-PAGE results indicated that the number of protein bands and optical density curves of proteins in 26 CS samples was a bit different. However, the 2-DE results showed that the numbers and abundance of protein spots in protein profiles of 26 samples were obviously different and showed certain association with producing areas. Conclusions: Based on the expression values of matched protein spots, 26 batches of CS samples can be divided into two main categories (Tibet and Qinghai) by hierarchical cluster analysis. SUMMARY The number of protein bands and optical density curves of proteins in 26 Cordyceps sinensis samples were a bit different on the sodium dodecyl sulfate-polyacrylamide gel electrophoresis protein profilesNumbers and abundance of protein spots in protein profiles of 26 samples were obvious different on two-dimensional electrophoresis mapsTwenty-six different producing areas of natural Cordyceps sinensis samples were divided into two main categories (Tibet and Qinghai) by Hierarchical cluster analysis based on the values of matched protein spots. Abbreviations Used: SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, Cordyceps sinensis: CS, TCMs: Traditional Chinese medicines PMID:28250651

Analysis of Soluble Proteins in Natural Cordyceps sinensis from Different Producing Areas by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis and Two-dimensional Electrophoresis.

PubMed

Li, Chun-Hong; Zuo, Hua-Li; Zhang, Qian; Wang, Feng-Qin; Hu, Yuan-Jia; Qian, Zheng-Ming; Li, Wen-Jia; Xia, Zhi-Ning; Yang, Feng-Qing

2017-01-01

As one of the bioactive components in Cordyceps sinensis (CS), proteins were rarely used as index components to study the correlation between the protein components and producing areas of natural CS. Protein components of 26 natural CS samples produced in Qinghai, Tibet, and Sichuan provinces were analyzed and compared to investigate the relationship among 26 different producing areas. Proteins from 26 different producing areas were extracted by Tris-HCl buffer with Triton X-100, and separated using sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and two-dimensional electrophoresis (2-DE). The SDS-PAGE results indicated that the number of protein bands and optical density curves of proteins in 26 CS samples was a bit different. However, the 2-DE results showed that the numbers and abundance of protein spots in protein profiles of 26 samples were obviously different and showed certain association with producing areas. Based on the expression values of matched protein spots, 26 batches of CS samples can be divided into two main categories (Tibet and Qinghai) by hierarchical cluster analysis. The number of protein bands and optical density curves of proteins in 26 Cordyceps sinensis samples were a bit different on the sodium dodecyl sulfate-polyacrylamide gel electrophoresis protein profilesNumbers and abundance of protein spots in protein profiles of 26 samples were obvious different on two-dimensional electrophoresis mapsTwenty-six different producing areas of natural Cordyceps sinensis samples were divided into two main categories (Tibet and Qinghai) by Hierarchical cluster analysis based on the values of matched protein spots. Abbreviations Used : SDS-PAGE: Sodium dodecyl sulfate polyacrylamide gel electrophoresis, 2-DE: Two-dimensional electrophoresis, Cordyceps sinensis : CS, TCMs: Traditional Chinese medicines.

FTIR gas chromatographic analysis of perfumes

NASA Astrophysics Data System (ADS)

Diederich, H.; Stout, Phillip J.; Hill, Stephen L.; Krishnan, K.

1992-03-01

Perfumes, natural or synthetic, are complex mixtures consisting of numerous components. Gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) techniques have been extensively utilized for the analysis of perfumes and essential oils. A limited number of perfume samples have also been analyzed by FT-IR gas chromatographic (GC-FTIR) techniques. Most of the latter studies have been performed using the conventional light pipe (LP) based GC-FTIR systems. In recent years, cold-trapping (in a matrix or neat) GC-FTIR systems have become available. The cold-trapping systems are capable of sub-nanogram sensitivities. In this paper, comparison data between the LP and the neat cold-trapping GC- FTIR systems is presented. The neat cold-trapping interface is known as Tracer. The results of GC-FTIR analysis of some commercial perfumes is also presented. For comparison of LP and Tracer GC-FTIR systems, a reference (synthetic) mixture containing 16 major and numerous minor constituents was used. The components of the mixture are the compounds commonly encountered in commercial perfumes. The GC-FTIR spectra of the reference mixture was obtained under identical chromatographic conditions from an LP and a Tracer system. A comparison of the two sets of data thus generated do indeed show the enhanced sensitivity level of the Tracer system. The comparison also shows that some of the major components detected by the Tracer system were absent from the LP data. Closer examination reveals that these compounds undergo thermal decomposition on contact with the hot gold surface that is part of the LP system. GC-FTIR data were obtained for three commercial perfume samples. The major components of these samples could easily be identified by spectra search against a digitized spectral library created using the Tracer data from the reference mixture.

Progress in mass spectrometry for the analysis of set-off phenomena in plastic food packaging materials.

PubMed

Aznar, Margarita; Alfaro, Pilar; Nerín, Cristina; Jones, Emrys; Riches, Eleanor

2016-07-01

In most cases, food packaging materials contain inks whose components can migrate to food by diffusion through the material as well as by set-off phenomena. In this work, different mass spectrometry approaches had been used in order to identify and confirm the presence of ink components in ethanol (95%) and Tenax(®) as food simulants. Three different sets of materials, manufactured with different printing technologies and with different structures, were analyzed. Sample analysis by ultra performance liquid chromatography mass spectrometry (UPLC-MS), using a quadrupole-time of flight (Q-TOF) as a mass analyser proved to be an excellent tool for identification purposes while ion mobility mass spectrometry (IM-MS) shown to be very useful for the confirmation of the candidates proposed. The results showed the presence of different non-volatile ink components in migration such as colorants (Solvent Red 49), plasticizers (dimethyl sebacate, tributyl o-acetyl citrate) or surfactants (SchercodineM, triethylene glycol caprilate). An oxidation product of an ink additive (triphenyl phosphine oxide) was also detected. In addition, a surface analysis technique, desorption electrospray mass spectrometry (DESI-MS), was used for analyzing the distribution of some ink components (tributyl o-acetyl citrate Schercodine L, phthalates) in the material. The detection of some of these compounds in the back-printed side confirmed the transference of this compound from the non-food to the food contact side. The results also showed that concentration of ink migrants decreased when an aluminum or polypropylene layer covered the ink. When aluminum was used, concentration of most of ink migrants decreased, and for 5 out of the 9 even disappeared. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

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

2006-01-01

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

The structural basis for the functional comparability of factor VIII and the long-acting variant recombinant factor VIII Fc fusion protein

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

Leksa, N. C.; Chiu, P. -L.; Bou-Assaf, G. M.

Fusion of the human IgG 1 Fc domain to the C-terminal C2 domain of B-domain-deleted (BDD) factor VIII (FVIII) results in the recombinant FVIII Fc (rFVIIIFc) fusion protein, which has a 1.5-fold longer half-life in humans. To assess the structural properties of rFVIIIFc by comparing its constituent FVIII and Fc elements with their respective isolated components, and evaluating their structural independence within rFVIIIFc. rFVIIIFc and its isolated FVIII and Fc components were compared by the use of hydrogen–deuterium exchange mass spectrometry (HDX-MS). The structure of rFVIIIFc was also evaluated by the use of X-ray crystallography, small-angle X-ray scattering (SAXS), andmore » electron microscopy (EM). The degree of steric interference by the appended Fc domain was assessed by EM and surface plasmon resonance (SPR). HDX-MS analysis of rFVIIIFc revealed that fusion caused no structural perturbations in FVIII or Fc. The rFVIIIFc crystal structure showed that the FVIII component is indistinguishable from published BDD FVIII structures. The Fc domain was not observed, indicating high mobility. SAXS analysis was consistent with an ensemble of rigid-body models in which the Fc domain exists in a largely extended orientation relative to FVIII. Binding of Fab fragments of anti-C2 domain antibodies to BDD FVIII was visualized by EM, and the affinities of the corresponding intact antibodies for BDD FVIII and rFVIIIFc were comparable by SPR analysis. Thus, the FVIII and Fc components of rFVIIIFc are structurally indistinguishable from their isolated constituents, and show a high degree of structural independence, consistent with the functional comparability of rFVIIIFc and unmodified FVIII.« less

Investigation of cell wall composition related to stem lodging resistance in wheat (Triticum aestivum L.) by FTIR spectroscopy.

PubMed

Wang, Jian; Zhu, Jinmao; Huang, RuZhu; Yang, YuSheng

2012-07-01

We explored the rapid qualitative analysis of wheat cultivars with good lodging resistances by Fourier transform infrared resonance (FTIR) spectroscopy and multivariate statistical analysis. FTIR imaging showing that wheat stem cell walls were mainly composed of cellulose, pectin, protein, and lignin. Principal components analysis (PCA) was used to eliminate multicollinearity among multiple peak absorptions. PCA revealed the developmental internodes of wheat stems could be distributed from low to high along the load of the second principal component, which was consistent with the corresponding bands of cellulose in the FTIR spectra of the cell walls. Furthermore, four distinct stem populations could also be identified by spectral features related to their corresponding mechanical properties via PCA and cluster analysis. Histochemical staining of four types of wheat stems with various abilities to resist lodging revealed that cellulose contributed more than lignin to the ability to resist lodging. These results strongly suggested that the main cell wall component responsible for these differences was cellulose. Therefore, the combination of multivariate analysis and FTIR could rapidly screen wheat cultivars with good lodging resistance. Furthermore, the application of these methods to a much wider range of cultivars of unknown mechanical properties promises to be of interest.

Principal component analysis for protein folding dynamics.

PubMed

Maisuradze, Gia G; Liwo, Adam; Scheraga, Harold A

2009-01-09

Protein folding is considered here by studying the dynamics of the folding of the triple beta-strand WW domain from the Formin-binding protein 28. Starting from the unfolded state and ending either in the native or nonnative conformational states, trajectories are generated with the coarse-grained united residue (UNRES) force field. The effectiveness of principal components analysis (PCA), an already established mathematical technique for finding global, correlated motions in atomic simulations of proteins, is evaluated here for coarse-grained trajectories. The problems related to PCA and their solutions are discussed. The folding and nonfolding of proteins are examined with free-energy landscapes. Detailed analyses of many folding and nonfolding trajectories at different temperatures show that PCA is very efficient for characterizing the general folding and nonfolding features of proteins. It is shown that the first principal component captures and describes in detail the dynamics of a system. Anomalous diffusion in the folding/nonfolding dynamics is examined by the mean-square displacement (MSD) and the fractional diffusion and fractional kinetic equations. The collisionless (or ballistic) behavior of a polypeptide undergoing Brownian motion along the first few principal components is accounted for.

[Simultaneous determination of five main index components and specific chromatograms analysis in Xiaochaihu granules].

PubMed

Zhuang, Yan-Shuang; Cai, Hao; Liu, Xiao; Cai, Bao-Chang

2012-01-01

Reversed phase high performance liquid chromatography with diode array detector was employed for simultaneous determination of five main index components and specific chromatograms analysis in Xiaochaihu granules with a linear gradient elution of acetonitrile-water (containing 0.1% phosphoric acid) as mobile phase. The results showed that five main index components (baicalin, baicalein, wogonoside, wogonin, enoxolone) were separated well under the analytical condition. The linear ranges of five components were 0.518 - 16.576, 0.069 - 2.197, 0.167 - 5.333, 0.009 - 0.297 and 0.006 - 0.270 mg x g(-1), respectively. The correlation coefficients were 0.999 9, and the average recoveries ranged from 95% to 105%. Twelve common peaks were selected as the specific chromatograms of Xiaochaihu granules with baicalin as the reference peak. There were good similarities between the reference and the ten batches of samples. The similarity coefficients were no less than 0.9. The analytical method established is highly sensitive with strong specificity and it can be used efficiently in the quality control of Xiaochaihu granules.

Concurrent white matter bundles and grey matter networks using independent component analysis.

PubMed

O'Muircheartaigh, Jonathan; Jbabdi, Saad

2018-04-15

Developments in non-invasive diffusion MRI tractography techniques have permitted the investigation of both the anatomy of white matter pathways connecting grey matter regions and their structural integrity. In parallel, there has been an expansion in automated techniques aimed at parcellating grey matter into distinct regions based on functional imaging. Here we apply independent component analysis to whole-brain tractography data to automatically extract brain networks based on their associated white matter pathways. This method decomposes the tractography data into components that consist of paired grey matter 'nodes' and white matter 'edges', and automatically separates major white matter bundles, including known cortico-cortical and cortico-subcortical tracts. We show how this framework can be used to investigate individual variations in brain networks (in terms of both nodes and edges) as well as their associations with individual differences in behaviour and anatomy. Finally, we investigate correspondences between tractography-based brain components and several canonical resting-state networks derived from functional MRI. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

[Comparative analysis of the efficacy of a playful-narrative program to teach mathematics at pre-school level].

PubMed

Gil Llario, M D; Vicent Catalá, Consuelo

2009-02-01

Comparative analysis of the efficacy of a playful-narrative program to teach mathematics at pre-school level. In this paper, the effectiveness of a programme comprising several components that are meant to consolidate mathematical concepts and abilities at the pre-school level is analyzed. The instructional methodology of this programme is compared to other methodologies. One-hundred 5-6 year-old children made up the sample that was distributed in the following conditions: (1) traditional methodology; (2) methodology with perceptual and manipulative components, and (3) methodology with language and playful components. Mathematical competence was assessed with the Mathematical Criterial Pre-school Test and the subtest of quantitative-numeric concepts of BADyG. Participants were evaluated before and after the academic course during which they followed one of these methodologies. The results show that the programme with language and playful components is more effective than the traditional methodology (p<.000) and also more effective than the perceptual and manipulative methodology (p<.000). Implications of the results for instructional practices are analyzed.

Inventory of File sref_em.t03z.pgrb212.ctl.grib2

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Inventory of File sref_nmm.t03z.pgrb132.ctl.grib2

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UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

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Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb132.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

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Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb243.ctl.grib2

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UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb221.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb212.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb216.ctl.grib2

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UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb216.ctl.grib2

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UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

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

PubMed Central

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

2016-01-01

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

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

PubMed

Yin, Yihang; Liu, Fengzheng; Zhou, Xiang; Li, Quanzhong

2015-08-07

Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

Classification and identification of Rhodobryum roseum Limpr. and its adulterants based on fourier-transform infrared spectroscopy (FTIR) and chemometrics.

PubMed

Cao, Zhen; Wang, Zhenjie; Shang, Zhonglin; Zhao, Jiancheng

2017-01-01

Fourier-transform infrared spectroscopy (FTIR) with the attenuated total reflectance technique was used to identify Rhodobryum roseum from its four adulterants. The FTIR spectra of six samples in the range from 4000 cm-1 to 600 cm-1 were obtained. The second-derivative transformation test was used to identify the small and nearby absorption peaks. A cluster analysis was performed to classify the spectra in a dendrogram based on the spectral similarity. Principal component analysis (PCA) was used to classify the species of six moss samples. A cluster analysis with PCA was used to identify different genera. However, some species of the same genus exhibited highly similar chemical components and FTIR spectra. Fourier self-deconvolution and discrete wavelet transform (DWT) were used to enhance the differences among the species with similar chemical components and FTIR spectra. Three scales were selected as the feature-extracting space in the DWT domain. The results show that FTIR spectroscopy with chemometrics is suitable for identifying Rhodobryum roseum and its adulterants.

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

Liu, Lu; Albright, Austin P; Rahimpour, Alireza

Wide-area-measurement systems (WAMSs) are used in smart grid systems to enable the efficient monitoring of grid dynamics. However, the overwhelming amount of data and the severe contamination from noise often impede the effective and efficient data analysis and storage of WAMS generated measurements. To solve this problem, we propose a novel framework that takes advantage of Multivariate Empirical Mode Decomposition (MEMD), a fully data-driven approach to analyzing non-stationary signals, dubbed MEMD based Signal Analysis (MSA). The frequency measurements are considered as a linear superposition of different oscillatory components and noise. The low-frequency components, corresponding to the long-term trend and inter-areamore » oscillations, are grouped and compressed by MSA using the mean shift clustering algorithm. Whereas, higher-frequency components, mostly noise and potentially part of high-frequency inter-area oscillations, are analyzed using Hilbert spectral analysis and they are delineated by statistical behavior. By conducting experiments on both synthetic and real-world data, we show that the proposed framework can capture the characteristics, such as trends and inter-area oscillation, while reducing the data storage requirements« less

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.

Analysis of Alternatives for Dismantling of the Equipment in Building 117/1 at Ignalina NPP - 13278

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

Poskas, Povilas; Simonis, Audrius; Poskas, Gintautas

2013-07-01

Ignalina NPP was operating two RBMK-1500 reactors which are under decommissioning now. In this paper dismantling alternatives of the equipment in Building 117/1 are analyzed. After situation analysis and collection of the primary information related to components' physical and radiological characteristics, location and other data, two different alternatives for dismantling of the equipment are formulated - the first (A1), when major components (vessels and pipes of Emergency Core Cooling System - ECCS) are segmented/halved in situ using flame cutting (oxy-acetylene) and the second one (A2), when these components are segmented/halved at the workshop using CAMC (Contact Arc Metal Cutting) technique.more » To select the preferable alternative MCDA method - AHP (Analytic Hierarchy Process) is applied. Hierarchical list of decision criteria, necessary for assessment of alternatives performance, are formulated. Quantitative decision criteria values for these alternatives are calculated using software DECRAD, which was developed by Lithuanian Energy Institute Nuclear engineering laboratory. While qualitative decision criteria are evaluated using expert judgment. Analysis results show that alternative A1 is better than alternative A2. (authors)« less

Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake.

PubMed

Mimura, Natsuki; Isogai, Atsuko; Iwashita, Kazuhiro; Bamba, Takeshi; Fukusaki, Eiichiro

2014-10-01

Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

NASA Astrophysics Data System (ADS)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

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.

Analysis Of Direct Numerical Simulation Results Of Adverse Pressure Gradient Boundary Layer Through Anisotropy Invariant Mapping And Comparison With The Rans Simulations

NASA Astrophysics Data System (ADS)

Gungor, Ayse Gul; Nural, Ozan Ekin; Ertunc, Ozgur

2017-11-01

Purpose of this study is to analyze the direct numerical simulation data of a turbulent boundary layer subjected to strong adverse pressure gradient through anisotropy invariant mapping. RANS simulation using the ``Elliptic Blending Model'' of Manceau and Hanjolic (2002) is also conducted for the same flow case with commercial software Star-CCM+ and comparison of the results with DNS data is done. RANS simulation captures the general trends in the velocity field but, significant deviations are found when skin friction coefficients are compared. Anisotropy invariant map of Lumley and Newman (1977) and barycentric map of Banerjee et al. (2007) are used for the analysis. Invariant mapping of the DNS data has yielded that at locations away from the wall, flow is close to one component turbulence state. In the vicinity of the wall, turbulence is at two component limit which is one border of the barycentric map and as the flow evolves along the streamwise direction, it approaches to two component turbulence state. Additionally, at the locations away from the wall, turbulence approaches to two component limit. Furthermore, analysis of the invariants of the RANS simulations shows dissimilar results. In RANS simulations invariants do not approach to any of the limit states unlike the DNS.

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

NASA Astrophysics Data System (ADS)

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

2005-05-01

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

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

PubMed

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

2016-03-15

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

QTL mapping of sake brewing characteristics of yeast.

PubMed

Katou, Taku; Namise, Masahiro; Kitagaki, Hiroshi; Akao, Takeshi; Shimoi, Hitoshi

2009-04-01

A haploid sake yeast strain derived from the commercial diploid sake yeast strain Kyokai no. 7 showed better characteristics for sake brewing compared to the haploid laboratory yeast strain X2180-1B, including higher production of ethanol and aromatic components. A hybrid of these two strains showed intermediate characteristics in most cases. After sporulation of the hybrid strain, we obtained 100 haploid segregants of the hybrid. Small-scale sake brewing tests of these segregants showed a smooth continuous distribution of the sake brewing characteristics, suggesting that these traits are determined by multiple quantitative trait loci (QTLs). To examine these sake brewing characteristics at the genomic level, we performed QTL analysis of sake brewing characteristics using 142 DNA markers that showed heterogeneity between the two parental strains. As a result, we identified 25 significant QTLs involved in the specification of sake brewing characteristics such as ethanol fermentation and the production of aromatic components.

Orbit Clustering Based on Transfer Cost

NASA Technical Reports Server (NTRS)

Gustafson, Eric D.; Arrieta-Camacho, Juan J.; Petropoulos, Anastassios E.

2013-01-01

We propose using cluster analysis to perform quick screening for combinatorial global optimization problems. The key missing component currently preventing cluster analysis from use in this context is the lack of a useable metric function that defines the cost to transfer between two orbits. We study several proposed metrics and clustering algorithms, including k-means and the expectation maximization algorithm. We also show that proven heuristic methods such as the Q-law can be modified to work with cluster analysis.

Using participant hedonic ratings of food images to construct data driven food groupings.

PubMed

Johnson, Susan L; Boles, Richard E; Burger, Kyle S

2014-08-01

Little is known regarding how individuals' hedonic ratings of a variety of foods interrelate and how hedonic ratings correspond to habitual dietary intake. Participant ratings of food appeal of 104 food images were collected while participants were in a fed state (n = 129). Self-reported frequency of intake of the food items, perceived hunger, body mass index (BMI), and dietary restraint were also assessed. Principal components analysis (PCA) was employed to analyze hedonic ratings of the foods, to identify component structures and to reduce the number of variables. The resulting component structures comprised 63 images loading on seven components including Energy-Dense Main Courses, Light Main Courses and Seafood as well as components more analogous to traditional food groups (e.g., Fruits, Grains, Desserts, Meats). However, vegetables were not represented in a unique, independent component. All components were positively correlated with reported intake of the food items (r's = .26-.52, p <.05), except for the Light Main Course component (r = .10). BMI showed a small positive relation with aggregated food appeal ratings (r = .19; p <.05), which was largely driven by the relations between BMI and appeal ratings for Energy-Dense Main Courses (r = .24; p <.01) and Desserts (r = .27; p <.01). Dietary restraint showed a small significant negative relation to Energy-Dense Main Courses (r = -.21; p <.05), and Meats (r = -.18; p <.05). The present investigation provides novel evidence regarding how individuals' hedonic ratings of foods aggregate into food components and how these component ratings relate to dietary intake. The notable absence of a vegetable component suggests that individuals' liking for vegetables is highly variable and, from an empirical standpoint, not related to how they respond hedonically to other food categories. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

Ultra-high-performance liquid chromatography/tandem high-resolution mass spectrometry analysis of sixteen red beverages containing carminic acid: identification of degradation products by using principal component analysis/discriminant analysis.

PubMed

Gosetti, Fabio; Chiuminatto, Ugo; Mazzucco, Eleonora; Mastroianni, Rita; Marengo, Emilio

2015-01-15

The study investigates the sunlight photodegradation process of carminic acid, a natural red colourant used in beverages. For this purpose, both carminic acid aqueous standard solutions and sixteen different commercial beverages, ten containing carminic acid and six containing E120 dye, were subjected to photoirradiation. The results show different patterns of degradation, not only between the standard solutions and the beverages, but also from beverage to beverage. Due to the different beverage recipes, unpredictable reactions take place between the dye and the other ingredients. To identify the dye degradation products in a very complex scenario, a methodology was used, based on the combined use of principal component analysis with discriminant analysis and ultra-high-performance liquid chromatography coupled with tandem high resolution mass spectrometry. The methodology is unaffected by beverage composition and allows the degradation products of carminic acid dye to be identified for each beverage. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Researches on Damage Detection Method for Truss Structures

NASA Astrophysics Data System (ADS)

Wang, Meng Hong; Cao, Xiao Nan

2018-06-01

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

Optical Properties of Fluorescent Mixtures: Comparing Quantum Dots to Organic Dyes

ERIC Educational Resources Information Center

Hutchins, Benjamin M.; Morgan, Thomas T.; Ucak-Astarlioglu, Mine G.; Wlilliams, Mary Elizabeth

2007-01-01

The study describes and compares the size-dependent optical properties of organic dyes with those of semiconductor nanocrystals or quantum dots (QDs). The analysis shows that mixtures of QDs contain emission colors that are sum of the individual QD components.

Fast volumetric imaging of bound and pore water in cortical bone using three-dimensional ultrashort-TE (UTE) and inversion recovery UTE sequences.

PubMed

Chen, Jun; Carl, Michael; Ma, Yajun; Shao, Hongda; Lu, Xing; Chen, Bimin; Chang, Eric Y; Wu, Zhihong; Du, Jiang

2016-10-01

We report the three-dimensional ultrashort-TE (3D UTE) and adiabatic inversion recovery UTE (IR-UTE) sequences employing a radial trajectory with conical view ordering for bi-component T2 * analysis of bound water (T2 *(BW) ) and pore water (T2 *(PW) ) in cortical bone. An interleaved dual-echo 3D UTE acquisition scheme was developed for fast bi-component analysis of bound and pore water in cortical bone. A 3D IR-UTE acquisition scheme employing multiple spokes per IR was developed for bound water imaging. Two-dimensional UTE (2D UTE) and IR-UTE sequences were employed for comparison. The sequences were applied to bovine bone samples (n = 6) and volunteers (n = 6) using a 3-T scanner. Bi-component fitting of 3D UTE images of bovine samples showed a mean T2 *(BW) of 0.26 ± 0.04 ms and T2 *(PW) of 4.16 ± 0.35 ms, with fractions of 21.5 ± 3.6% and 78.5 ± 3.6%, respectively. The 3D IR-UTE signal showed a single-component decay with a mean T2 *(BW) of 0.29 ± 0.05 ms, suggesting selective imaging of bound water. Similar results were achieved with the 2D UTE and IR-UTE sequences. Bi-component fitting of 3D UTE images of the tibial midshafts of healthy volunteers showed a mean T2 *(BW) of 0.32 ± 0.08 ms and T2 *(PW) of 5.78 ± 1.24 ms, with fractions of 34.2 ± 7.4% and 65.8 ± 7.4%, respectively. Single-component fitting of 3D IR-UTE images showed a mean T2 *(BW) of 0.35 ± 0.09 ms. The 3D UTE and 3D IR-UTE techniques allow fast volumetric mapping of bound and pore water in cortical bone. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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.

Development and psychometric evaluation of the Professional Practice Environment (PPE) scale.

PubMed

Erickson, Jeanette Ives; Duffy, Mary E; Gibbons, M Patricia; Fitzmaurice, Joan; Ditomassi, Marianne; Jones, Dorothy

2004-01-01

To describe the Professional Practice Environment (PPE) scale, its conceptual development and psychometric evaluation, and its uses in measuring eight characteristics of the professional practice environment in an acute care setting. The 38-item PPE Scale was validated on a sample of 849 professional practice staff at the Massachusetts General Hospital in Boston. Psychometric analysis included: item analysis, principal components analysis (PCA) with varimax rotation and Kaiser normalization, and internal consistency reliability using Cronbach's alpha coefficient. Eight components were shown, confirming the original conceptually derived model's structure and accounting for 61% of explained variance. Cronbach's alpha coefficients for the eight PPE subscales ranged from .78 to .88. Findings showed the 38-item PPE Scale was reliable and valid for use in health outcomes research to examine the professional practice environment of staff working in acute care settings.

Correlation between resting state fMRI total neuronal activity and PET metabolism in healthy controls and patients with disorders of consciousness.

PubMed

Soddu, Andrea; Gómez, Francisco; Heine, Lizette; Di Perri, Carol; Bahri, Mohamed Ali; Voss, Henning U; Bruno, Marie-Aurélie; Vanhaudenhuyse, Audrey; Phillips, Christophe; Demertzi, Athena; Chatelle, Camille; Schrouff, Jessica; Thibaut, Aurore; Charland-Verville, Vanessa; Noirhomme, Quentin; Salmon, Eric; Tshibanda, Jean-Flory Luaba; Schiff, Nicholas D; Laureys, Steven

2016-01-01

The mildly invasive 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established imaging technique to measure 'resting state' cerebral metabolism. This technique made it possible to assess changes in metabolic activity in clinical applications, such as the study of severe brain injury and disorders of consciousness. We assessed the possibility of creating functional MRI activity maps, which could estimate the relative levels of activity in FDG-PET cerebral metabolic maps. If no metabolic absolute measures can be extracted, our approach may still be of clinical use in centers without access to FDG-PET. It also overcomes the problem of recognizing individual networks of independent component selection in functional magnetic resonance imaging (fMRI) resting state analysis. We extracted resting state fMRI functional connectivity maps using independent component analysis and combined only components of neuronal origin. To assess neuronality of components a classification based on support vector machine (SVM) was used. We compared the generated maps with the FDG-PET maps in 16 healthy controls, 11 vegetative state/unresponsive wakefulness syndrome patients and four locked-in patients. The results show a significant similarity with ρ = 0.75 ± 0.05 for healthy controls and ρ = 0.58 ± 0.09 for vegetative state/unresponsive wakefulness syndrome patients between the FDG-PET and the fMRI based maps. FDG-PET, fMRI neuronal maps, and the conjunction analysis show decreases in frontoparietal and medial regions in vegetative patients with respect to controls. Subsequent analysis in locked-in syndrome patients produced also consistent maps with healthy controls. The constructed resting state fMRI functional connectivity map points toward the possibility for fMRI resting state to estimate relative levels of activity in a metabolic map.

Realism of Indian Summer Monsoon Simulation in a Quarter Degree Global Climate Model

NASA Astrophysics Data System (ADS)

Salunke, P.; Mishra, S. K.; Sahany, S.; Gupta, K.

2017-12-01

This study assesses the fidelity of Indian Summer Monsoon (ISM) simulations using a global model at an ultra-high horizontal resolution (UHR) of 0.25°. The model used was the atmospheric component of the Community Earth System Model version 1.2.0 (CESM 1.2.0) developed at the National Center for Atmospheric Research (NCAR). Precipitation and temperature over the Indian region were analyzed for a wide range of space and time scales to evaluate the fidelity of the model under UHR, with special emphasis on the ISM simulations during the period of June-through-September (JJAS). Comparing the UHR simulations with observed data from the India Meteorological Department (IMD) over the Indian land, it was found that 0.25° resolution significantly improved spatial rainfall patterns over many regions, including the Western Ghats and the South-Eastern peninsula as compared to the standard model resolution. Convective and large-scale rainfall components were analyzed using the European Centre for Medium Range Weather Forecast (ECMWF) Re-Analysis (ERA)-Interim (ERA-I) data and it was found that at 0.25° resolution, there was an overall increase in the large-scale component and an associated decrease in the convective component of rainfall as compared to the standard model resolution. Analysis of the diurnal cycle of rainfall suggests a significant improvement in the phase characteristics simulated by the UHR model as compared to the standard model resolution. Analysis of the annual cycle of rainfall, however, failed to show any significant improvement in the UHR model as compared to the standard version. Surface temperature analysis showed small improvements in the UHR model simulations as compared to the standard version. Thus, one may conclude that there are some significant improvements in the ISM simulations using a 0.25° global model, although there is still plenty of scope for further improvement in certain aspects of the annual cycle of rainfall.

Psychometric evaluation of the canine brief pain inventory in a Swedish sample of dogs with pain related to osteoarthritis.

PubMed

Essner, Ann; Zetterberg, Lena; Hellström, Karin; Gustås, Pia; Högberg, Hans; Sjöström, Rita

2017-07-01

To evaluate intervention, implement evidence-based practice and enhance the welfare of dogs with naturally occurring osteoarthritis (OA), access to valid, reliable and clinically relevant outcome measures is crucial for researchers, veterinarians and rehabilitation practitioners. The objectives of the present study were to translate and evaluate psychometric properties, in terms of internal consistency and construct validity, of the owner-reported measure canine brief pain inventory (CBPI) in a Swedish sample of dogs with pain related to OA. Twenty-one owners of clinically sound dogs and 58 owners of dogs with pain related to OA were included in this observational and cross-sectional study. After being translated according to the guidelines for patient-reported outcome measures, the CBPI was completed by the canine owners. Construct validity was assessed by confirmatory factor analysis, by repeating the principal component analysis and by assessing for differences between clinically sound dogs and dogs with pain related to OA. Internal consistency was estimated by Cronbach's α. Confirmatory factor analysis was not able to confirm the factor-structure models tested in our sample. Principal component analysis showed a two-component structure, pain severity and pain interference of function. Two components accounted for 76.8% of the total variance, suggesting an acceptable fit of a two-component structure. The ratings from the clinically sound dogs differed from OA dogs and showed significantly lower CBPI total sum. Cronbach's α was 0.94 for the total CBPI, 0.91 for the pain severity and 0.91 for the pain interference of function. The results indicate that the translated version of the CBPI is valid for use in the Swedish language. The findings suggest satisfying psychometric properties in terms of high internal consistencies and ability to discriminate clinically sound dogs from OA dogs. However, based on the confirmatory factor analysis, the original factor structure in the CBPI is not ideally suited to measure pain related to OA in our sample and the hypothesis of the presented two-factor structure was rejected. Further research needs to be conducted to determine whether the original psychometric results from CBPI can be replicated across different target groups and particularly with larger sample size.

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

Analytical Formulation for Sizing and Estimating the Dimensions and Weight of Wind Turbine Hub and Drivetrain Components

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

Guo, Y.; Parsons, T.; King, R.

This report summarizes the theory, verification, and validation of a new sizing tool for wind turbine drivetrain components, the Drivetrain Systems Engineering (DriveSE) tool. DriveSE calculates the dimensions and mass properties of the hub, main shaft, main bearing(s), gearbox, bedplate, transformer if up-tower, and yaw system. The level of fi¬ delity for each component varies depending on whether semiempirical parametric or physics-based models are used. The physics-based models have internal iteration schemes based on system constraints and design criteria. Every model is validated against available industry data or finite-element analysis. The verification and validation results show that the models reasonablymore » capture primary drivers for the sizing and design of major drivetrain components.« less

Using McStas for modelling complex optics, using simple building bricks

NASA Astrophysics Data System (ADS)

Willendrup, Peter K.; Udby, Linda; Knudsen, Erik; Farhi, Emmanuel; Lefmann, Kim

2011-04-01

The McStas neutron ray-tracing simulation package is a versatile tool for producing accurate neutron simulations, extensively used for design and optimization of instruments, virtual experiments, data analysis and user training.In McStas, component organization and simulation flow is intrinsically linear: the neutron interacts with the beamline components in a sequential order, one by one. Historically, a beamline component with several parts had to be implemented with a complete, internal description of all these parts, e.g. a guide component including all four mirror plates and required logic to allow scattering between the mirrors.For quite a while, users have requested the ability to allow “components inside components” or meta-components, allowing to combine functionality of several simple components to achieve more complex behaviour, i.e. four single mirror plates together defining a guide.We will here show that it is now possible to define meta-components in McStas, and present a set of detailed, validated examples including a guide with an embedded, wedged, polarizing mirror system of the Helmholtz-Zentrum Berlin type.

Existence of a new emitting singlet state of proflavine: femtosecond dynamics of the excited state processes and quantum chemical studies in different solvents.

PubMed

Kumar, Karuppannan Senthil; Selvaraju, Chellappan; Malar, Ezekiel Joy Padma; Natarajan, Paramasivam

2012-01-12

Proflavine (3,6-diaminoacridine) shows fluorescence emission with lifetime, 4.6 ± 0.2 ns, in all the solvents irrespective of the solvent polarity. To understand this unusual photophysical property, investigations were carried out using steady state and time-resolved fluorescence spectroscopy in the pico- and femtosecond time domain. Molecular geometries in the ground and low-lying excited states of proflavine were examined by complete structural optimization using ab initio quantum chemical computations at HF/6-311++G** and CIS/6-311++G** levels. Time dependent density functional theory (TDDFT) calculations were performed to study the excitation energies in the low-lying excited states. The steady state absorption and emission spectral details of proflavine are found to be influenced by solvents. The femtosecond fluorescence decay of the proflavine in all the solvents follows triexponential function with two ultrafast decay components (τ(1) and τ(2)) in addition to the nanosecond component. The ultrafast decay component, τ(1), is attributed to the solvation dynamics of the particular solvent used. The second ultrafast decay component, τ(2), is found to vary from 50 to 215 ps depending upon the solvent. The amplitudes of the ultrafast decay components vary with the wavelength and show time dependent spectral shift in the emission maximum. The observation is interpreted that the time dependent spectral shift is not only due to solvation dynamics but also due to the existence of more than one emitting state of proflavine in the solvent used. Time resolved area normalized emission spectral (TRANES) analysis shows an isoemissive point, indicating the presence of two emitting states in homogeneous solution. Detailed femtosecond fluorescence decay analysis allows us to isolate the two independent emitting components of the close lying singlet states. The CIS and TDDFT calculations also support the existence of the close lying emitting states. The near constant lifetime observed for proflavine in different solvents is suggested to be due to the similar dipole moments of the ground and the evolved emitting singlet state of the dye from the Franck-Condon excited state.

Chemical and biotechnological processing of collagen-containing raw materials into functional components of feed suitable for production of high-quality meat from farm animals

NASA Astrophysics Data System (ADS)

Baburina, M. I.; Ivankin, A. N.; Stanovova, I. A.

2017-09-01

The process of chemical biotechnological processing of collagen-containing raw materials into functional components of feeds for effective pig rearing was studied. Protein components of feeds were obtained as a result of hydrolysis in the presence of lactic acid of the animal collagen from secondary raw materials, which comprised subcutaneous collagen (cuticle), skin and veined mass with tendons from cattle. For comparison, a method is described for preparing protein components of feeds by cultivating Lactobacillus plantarum. Analysis of the kinetic data of the conversion of a high-molecular collagen protein to an aminolyte polypeptide mixture showed the advantage of microbiological synthesis in obtaining a protein for feeds. Feed formulations have been developed to include the components obtained, and which result in high quality pork suitable for the production of quality meat products.

A gravitational lens candidate discovered with the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Maoz, Dan; Bahcall, John N.; Schneider, Donald P.; Doxsey, Rodger; Bahcall, Neta A.; Filippenko, Alexei V.; Goss, W. M.; Lahav, Ofer; Yanny, Brian

1992-01-01

Evidence is reported for gravitational lensing of the high-redshift (z = 3.8) quasar 1208 + 101, observed as part of the Snapshot survey with the HST Planetary Camera. An HST V image taken on gyroscopes resolves the quasar into three point-source components, with the two fainter images having separations of 0.1 and 0.5 arcsec from the central bright component. A radio observation of the quasar with the VLA at 2 cm shows that, like most quasars of this redhsift, 1208 + 101 is radio quiet. Based on positional information alone, the probability that the observed optical components are chance superpositions of Galactic stars is small, but not negligible. Analysis of a combined ground-based spectrum of all three components, using the relative brightnesses of the HST image, supports the lensing hypothesis. If all the components are lensed images of the quasar, the observed configuration cannot be reproduced by simple lens models.

Identification of Histological Patterns in Clinically Affected and Unaffected Palm Regions in Dupuytren's Disease

PubMed Central

Alfonso-Rodríguez, Camilo-Andrés; Garzón, Ingrid; Garrido-Gómez, Juan; Oliveira, Ana-Celeste-Ximenes; Martín-Piedra, Miguel-Ángel; Scionti, Giuseppe; Carriel, Víctor; Hernández-Cortés, Pedro; Campos, Antonio; Alaminos, Miguel

2014-01-01

Dupuytren's disease is a fibro-proliferative disease characterized by a disorder of the extracellular matrix (ECM) and high myofibroblast proliferation. However, studies failed to determine if the whole palm fascia is affected by the disease. The objective of this study was to analyze several components of the extracellular matrix of three types of tissues—Dupuytren's diseased contracture cords (DDC), palmar fascia clinically unaffected by Dupuytren's disease contracture (NPF), and normal forehand fascia (NFF). Histological analysis, quantification of cells recultured from each type of tissue, mRNA microarrays and immunohistochemistry for smooth muscle actin (SMA), fibrillar ECM components and non-fibrillar ECM components were carried out. The results showed that DDC samples had abundant fibrosis with reticular fibers and few elastic fibers, high cell proliferation and myofibroblasts, laminin and glycoproteins, whereas NFF did not show any of these findings. Interestingly, NPF tissues had more cells showing myofibroblasts differentiation and more collagen and reticular fibers, laminin and glycoproteins than NFF, although at lower level than DDC, with similar elastic fibers than DDC. Immunohistochemical expression of decorin was high in DDC, whereas versican was highly expressed NFF, with no differences for aggrecan. Cluster analysis revealed that the global expression profile of NPF was very similar to DDC, and reculturing methods showed that cells corresponding to DDC tissues proliferated more actively than NPF, and NPF more actively than NFF. All these results suggest that NPF tissues may be affected, and that a modification of the therapeutic approach used for the treatment of Dupuytren's disease should be considered. PMID:25379672