Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

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

Sun, Yannan; Hou, Zhangshuan; Meng, Da

2016-07-17

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

Composite load spectra for select space propulsion structural components

NASA Technical Reports Server (NTRS)

Newell, J. F.; Ho, H. W.; Kurth, R. E.

1991-01-01

The work performed to develop composite load spectra (CLS) for the Space Shuttle Main Engine (SSME) using probabilistic methods. The three methods were implemented to be the engine system influence model. RASCAL was chosen to be the principal method as most component load models were implemented with the method. Validation of RASCAL was performed. High accuracy comparable to the Monte Carlo method can be obtained if a large enough bin size is used. Generic probabilistic models were developed and implemented for load calculations using the probabilistic methods discussed above. Each engine mission, either a real fighter or a test, has three mission phases: the engine start transient phase, the steady state phase, and the engine cut off transient phase. Power level and engine operating inlet conditions change during a mission. The load calculation module provides the steady-state and quasi-steady state calculation procedures with duty-cycle-data option. The quasi-steady state procedure is for engine transient phase calculations. In addition, a few generic probabilistic load models were also developed for specific conditions. These include the fixed transient spike model, the poison arrival transient spike model, and the rare event model. These generic probabilistic load models provide sufficient latitude for simulating loads with specific conditions. For SSME components, turbine blades, transfer ducts, LOX post, and the high pressure oxidizer turbopump (HPOTP) discharge duct were selected for application of the CLS program. They include static pressure loads and dynamic pressure loads for all four components, centrifugal force for the turbine blade, temperatures of thermal loads for all four components, and structural vibration loads for the ducts and LOX posts.

Principal component analysis of Raman spectra for TiO2 nanoparticle characterization

NASA Astrophysics Data System (ADS)

Ilie, Alina Georgiana; Scarisoareanu, Monica; Morjan, Ion; Dutu, Elena; Badiceanu, Maria; Mihailescu, Ion

2017-09-01

The Raman spectra of anatase/rutile mixed phases of Sn doped TiO2 nanoparticles and undoped TiO2 nanoparticles, synthesised by laser pyrolysis, with nanocrystallite dimensions varying from 8 to 28 nm, was simultaneously processed with a self-written software that applies Principal Component Analysis (PCA) on the measured spectrum to verify the possibility of objective auto-characterization of nanoparticles from their vibrational modes. The photo-excited process of Raman scattering is very sensible to the material characteristics, especially in the case of nanomaterials, where more properties become relevant for the vibrational behaviour. We used PCA, a statistical procedure that performs eigenvalue decomposition of descriptive data covariance, to automatically analyse the sample's measured Raman spectrum, and to interfere the correlation between nanoparticle dimensions, tin and carbon concentration, and their Principal Component values (PCs). This type of application can allow an approximation of the crystallite size, or tin concentration, only by measuring the Raman spectrum of the sample. The study of loadings of the principal components provides information of the way the vibrational modes are affected by the nanoparticle features and the spectral area relevant for the classification.

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

Statistical analysis of major ion and trace element geochemistry of water, 1986-2006, at seven wells transecting the freshwater/saline-water interface of the Edwards Aquifer, San Antonio, Texas

USGS Publications Warehouse

Mahler, Barbara J.

2008-01-01

The statistical analyses taken together indicate that the geochemistry at the freshwater-zone wells is more variable than that at the transition-zone wells. The geochemical variability at the freshwater-zone wells might result from dilution of ground water by meteoric water. This is indicated by relatively constant major ion molar ratios; a preponderance of positive correlations between SC, major ions, and trace elements; and a principal components analysis in which the major ions are strongly loaded on the first principal component. Much of the variability at three of the four transition-zone wells might result from the use of different laboratory analytical methods or reporting procedures during the period of sampling. This is reflected by a lack of correlation between SC and major ion concentrations at the transition-zone wells and by a principal components analysis in which the variability is fairly evenly distributed across several principal components. The statistical analyses further indicate that, although the transition-zone wells are less well connected to surficial hydrologic conditions than the freshwater-zone wells, there is some connection but the response time is longer. 

Resonant loading of aircraft secondary structure panels for use with thermoelastic stress analysis and digital image correlation

NASA Astrophysics Data System (ADS)

Waugh, Rachael C.; Dulieu-Barton, Janice M.; Quinn, S.

2015-03-01

Thermoelastic stress analysis (TSA) is an established active thermographic approach which uses the thermoelastic effect to correlate the temperature change that occurs as a material is subjected to elastic cyclic loading to the sum of the principal stresses on the surface of the component. Digital image correlation (DIC) tracks features on the surface of a material to establish a displacement field of a component subjected to load, which can then be used to calculate the strain field. The application of both DIC and TSA on a composite plate representative of aircraft secondary structure subject to resonant frequency loading using a portable loading device, i.e. `remote loading' is described. Laboratory based loading for TSA and DIC is typically imparted using a test machine, however in the current work a vibration loading system is used which is able to excite the component of interest at resonant frequency which enables TSA and DIC to be carried out. The accuracy of the measurements made under remote loading of both of the optical techniques applied is discussed. The data are compared to extract complimentary information from the two techniques. This work forms a step towards a combined strain based non-destructive evaluation procedure able to identify and quantify the effect of defects more fully, particularly when examining component performance in service applications.

A principal components analysis of dynamic spatial memory biases.

PubMed

Motes, Michael A; Hubbard, Timothy L; Courtney, Jon R; Rypma, Bart

2008-09-01

Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed targets that moved horizontally from left to right before disappearing or viewed briefly shown stationary targets. After a target disappeared, observers indicated the vanishing position of the target. Principal components analysis revealed that biases along the horizontal axis of motion loaded on separate components from biases along the vertical axis orthogonal to motion. The findings support the hypothesis that implied momentum and implied gravity biases have unique influences on spatial memory. (c) 2008 APA, all rights reserved.

Development of the upper-body dressing scale for a buttoned shirt: a preliminary correlational study.

PubMed

Suzuki, Makoto; Yamada, Sumio; Omori, Mikayo; Hatakeyama, Mayumi; Sugimura, Yuko; Matsushita, Kazuhiko; Tagawa, Yoshikatsu

2008-09-01

A patient with poststroke hemiparesis learns to use the nonparetic arm to compensate for the weakness of the paretic arm to achieve independence in dressing. This is the learning process of new component actions on dressing. The purpose of this study was to develop the Upper-Body Dressing Scale (UBDS) for buttoned shirt dressing, which evaluates the component actions of upper-body dressing, and to provide preliminary data on internal consistency of the UBDS, as well as its reproducibility, validity, and sensitivity to clinical change. Correlational study of concurrent validity and reliability in which 63 consecutive stroke patients were enrolled in the study and were assessed repeatedly by the UBDS and the dressing item of Functional Independent Measure (FIM). Fifty-one patients completed the 3-wk study. The Cronbach's coefficient alpha of UBDS was 0.88. The principal component analysis extracted two components, which explained 62.3% of total variance. All items of the scale had high loading on the first component (0.65-0.83). Actions on the paralytic side were the positive loadings and actions on the healthy side were the negative loadings on the second component. Intraclass correlation coefficient was 0.87. The level of correlation between UBDS score and FIM dressing item scores was -0.72. Logistic regression analysis showed that only the score of UBDS on the first day of evaluation was a significant independent predictor of dressing ability (odds ratio, 0.82; 95% confidence interval, 0.71-0.95). The UBDS scores for paralytic hand passed into the sleeve, sleeve pulled up beyond the elbow joint, and sleeve pulled up beyond the shoulder joint were worse than the score for the other components of the task. These component actions had positive loading on the second component, which was identified by the principal component analysis. The UBDS has good internal consistency, reproducibility, validity, and sensitivity to clinical changes of patients with poststroke hemiparesis. This detailed UBDS assessment enables us to document the most difficult stages in dressing and to assess motor and process skills for independence of dressing.

Q-mode versus R-mode principal component analysis for linear discriminant analysis (LDA)

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2017-05-01

Many literature apply Principal Component Analysis (PCA) as either preliminary visualization or variable con-struction methods or both. Focus of PCA can be on the samples (R-mode PCA) or variables (Q-mode PCA). Traditionally, R-mode PCA has been the usual approach to reduce high-dimensionality data before the application of Linear Discriminant Analysis (LDA), to solve classification problems. Output from PCA composed of two new matrices known as loadings and scores matrices. Each matrix can then be used to produce a plot, i.e. loadings plot aids identification of important variables whereas scores plot presents spatial distribution of samples on new axes that are also known as Principal Components (PCs). Fundamentally, the scores matrix always be the input variables for building classification model. A recent paper uses Q-mode PCA but the focus of analysis was not on the variables but instead on the samples. As a result, the authors have exchanged the use of both loadings and scores plots in which clustering of samples was studied using loadings plot whereas scores plot has been used to identify important manifest variables. Therefore, the aim of this study is to statistically validate the proposed practice. Evaluation is based on performance of external error obtained from LDA models according to number of PCs. On top of that, bootstrapping was also conducted to evaluate the external error of each of the LDA models. Results show that LDA models produced by PCs from R-mode PCA give logical performance and the matched external error are also unbiased whereas the ones produced with Q-mode PCA show the opposites. With that, we concluded that PCs produced from Q-mode is not statistically stable and thus should not be applied to problems of classifying samples, but variables. We hope this paper will provide some insights on the disputable issues.

Different odor tests contribute differently to the evaluation of olfactory loss.

PubMed

Lötsch, Jörn; Reichmann, Heinz; Hummel, Thomas

2008-01-01

In a clinical context, the importance of the sense of smell has increasingly been recognized, for example, in terms of the evaluation of neurodegenerative disorders. In this study, 2 strategies of olfactory testing, a simple one and a more complex one, were compared with respect to their suitability to assess olfactory dysfunction. Odor threshold (T), discrimination (D), and identification (I) were assessed in a control sample of 916 males and 1160 females, aged 6-90 years, and in 81 men and 21 women, aged 38-80 years, suffering from idiopathic Parkinson's disease (IPD). Sums of the 3 subtest results T, D, and I yielded threshold discrimination identification (TDI) scores reflecting olfactory function. Sensitivity of any of the 3 subtests to confirm the diagnosis established by the composite TDI score was assessed separately for each test. Principal component analyses were applied to determine any common source of variance among the 3 specific subtests. Sensitivities of the subtests to provide the diagnosis established by the composite TDI score were 64% (T), 56% (D), and 47% (I), respectively. In IPD patients, each of the subtests provided the correct diagnosis (sensitivity >90%), as olfaction was impaired in 99% of the patient group. Two principal components emerged in both controls and IPD patients, with eigenvalues >0.5. The first component received high loadings from all factors. The second component received high loadings from odor threshold, whereas loadings from odor discrimination and identification were much smaller. In conclusion, combined testing of several components of olfaction, especially including assessment of thresholds, provides the most significant approach to the diagnosis of smell loss.

Sex-based differences in lifting technique under increasing load conditions: A principal component analysis.

PubMed

Sheppard, P S; Stevenson, J M; Graham, R B

2016-05-01

The objective of the present study was to determine if there is a sex-based difference in lifting technique across increasing-load conditions. Eleven male and 14 female participants (n = 25) with no previous history of low back disorder participated in the study. Participants completed freestyle, symmetric lifts of a box with handles from the floor to a table positioned at 50% of their height for five trials under three load conditions (10%, 20%, and 30% of their individual maximum isometric back strength). Joint kinematic data for the ankle, knee, hip, and lumbar and thoracic spine were collected using a two-camera Optotrak motion capture system. Joint angles were calculated using a three-dimensional Euler rotation sequence. Principal component analysis (PCA) and single component reconstruction were applied to assess differences in lifting technique across the entire waveforms. Thirty-two PCs were retained from the five joints and three axes in accordance with the 90% trace criterion. Repeated-measures ANOVA with a mixed design revealed no significant effect of sex for any of the PCs. This is contrary to previous research that used discrete points on the lifting curve to analyze sex-based differences, but agrees with more recent research using more complex analysis techniques. There was a significant effect of load on lifting technique for five PCs of the lower limb (PC1 of ankle flexion, knee flexion, and knee adduction, as well as PC2 and PC3 of hip flexion) (p < 0.005). However, there was no significant effect of load on the thoracic and lumbar spine. It was concluded that when load is standardized to individual back strength characteristics, males and females adopted a similar lifting technique. In addition, as load increased male and female participants changed their lifting technique in a similar manner. Copyright © 2016. Published by Elsevier Ltd.

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.

The viscoelastic behavior of the principal compliance matrix of a unidirectional graphite/epoxy composite

NASA Technical Reports Server (NTRS)

Morris, D. H.; Yeow, Y. T.

1979-01-01

The time-temperature response of the principal compliances of a unidirectional graphite/epoxy composite was determined. It is shown that two components of the compliance matrix are time and temperature independent and that the compliance matrix is symmetric for the viscoelastic composite. The time-temperature superposition principle is used to determine shift factors which are independent of fiber orientation, for fiber angles that vary from 10 D to 90 D with respect to the load direction.

Readers' opinions of romantic poetry are consistent with emotional measures based on the Dictionary of Affect in Language.

PubMed

Whissell, Cynthia

2003-06-01

A principal components analysis of 68 volunteers' subjective ratings of 20 excerpts of Romantic poetry and of Dictionary of Affect scores for the same excerpts produced four components representing Pleasantness, Activation, Romanticism, and Nature. Dictionary measures and subjective ratings of the same constructs loaded on the same factor. Results are interpreted as providing construct validity for the Dictionary of Affect.

Phenomenology of mixed states: a principal component analysis study.

PubMed

Bertschy, G; Gervasoni, N; Favre, S; Liberek, C; Ragama-Pardos, E; Aubry, J-M; Gex-Fabry, M; Dayer, A

2007-12-01

To contribute to the definition of external and internal limits of mixed states and study the place of dysphoric symptoms in the psychopathology of mixed states. One hundred and sixty-five inpatients with major mood episodes were diagnosed as presenting with either pure depression, mixed depression (depression plus at least three manic symptoms), full mixed state (full depression and full mania), mixed mania (mania plus at least three depressive symptoms) or pure mania, using an adapted version of the Mini International Neuropsychiatric Interview (DSM-IV version). They were evaluated using a 33-item inventory of depressive, manic and mixed affective signs and symptoms. Principal component analysis without rotation yielded three components that together explained 43.6% of the variance. The first component (24.3% of the variance) contrasted typical depressive symptoms with typical euphoric, manic symptoms. The second component, labeled 'dysphoria', (13.8%) had strong positive loadings for irritability, distressing sensitivity to light and noise, impulsivity and inner tension. The third component (5.5%) included symptoms of insomnia. Median scores for the first component significantly decreased from the pure depression group to the pure mania group. For the dysphoria component, scores were highest among patients with full mixed states and decreased towards both patients with pure depression and those with pure mania. Principal component analysis revealed that dysphoria represents an important dimension of mixed states.

VEGA Launch Vehicle Vibro-Acoustic Approach for Multi Payload Configuration Qualification

NASA Astrophysics Data System (ADS)

Bartoccini, D.; Di Trapani, C.; Fotino, D.; Bonnet, M.

2014-06-01

Acoustic loads are one of the principal source of structural vibration and internal noise during a launch vehicle flight but do not generally present a critical design condition for the main load-carrying structure. However, acoustic loads may be critical to the proper functioning of vehicle components and their supporting structures, which are otherwise lightly loaded. Concerning the VEGA program, in order to demonstrate VEGA Launch Vehicle (LV) on-ground qualification, prior to flight, to the acoustic load, the following tests have been performed: small-scale acoustic test intended for the determination of the acoustic loading of the LV and its nature and full-scale acoustic chamber test to determine the vibro-acoustic response of the structures as well as of the acoustic cavities.

Between Stressors and Outcomes: Can We Simplify Caregiving Process Variables?

ERIC Educational Resources Information Center

Braithwaite, Valerie

1996-01-01

Examines Lawton, Kleban, Moss, Rovine, and Glickman's (1989) caregiving appraisal through a principal components analysis and varimax rotation of a data set based on in-depth quantitative interviews with 144 caregivers. Five caregiving appraisal dimensions are identified: task load caregiving, dysfunctional caregiving, intimacy and love, social…

WETLAND MORPHOLOGIC AND BIOGEOGRAPHIC INFLUENCES ON ALGAL RESPONSES TO NUTRIENT LOADING IN GREAT LAKES COASTAL WETLANDS

EPA Science Inventory

We are testing the influence of wetland morphology (protected vs. riverine) and biogeography (upper vs. lower Great Lakes) on algal responses to nutrients in Great Lakes Coastal wetlands. Principal components analysis using nutrient-specific GIS data was used to select sites wit...

Design and performance evaluation of a cryogenic condenser for an in-pile experiment

NASA Technical Reports Server (NTRS)

Graham, R. W.; Crum, R. J.; Hsu, Y.

1972-01-01

An apparatus was designed to enable in-pile irradiation of materials in liquid hydrogen at cryogenic temperatures. One of the principal components of this apparatus was a horizontal tube condenser. The performance of the condenser was evaluated by running a liquid-nitrogen prototype of the apparatus at heat loads comparable to or greater than those expected during the irradiation. The test showed that the condenser was capable of handling the design heat load and that the design procedure was sound.

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.

Raman spectra of single cells with autofluorescence suppression by modulated wavelength excitation

NASA Astrophysics Data System (ADS)

Krafft, Christoph; Dochow, Sebastian; Bergner, Norbert; Clement, Joachim H.; Praveen, Bavishna B.; Mazilu, Michael; Marchington, Rob; Dholakia, Kishan; Popp, Jürgen

2012-01-01

Raman spectroscopy is a non-invasive technique offering great potential in the biomedical field for label-free discrimination between normal and tumor cells based on their biochemical composition. First, this contribution describes Raman spectra of lymphocytes after drying, in laser tweezers, and trapped in a microfluidic environment. Second, spectral differences between lymphocytes and acute myeloid leukemia cells (OCI-AML3) are compared for these three experimental conditions. Significant similarities of difference spectra are consistent with the biological relevance of the spectral features. Third, modulated wavelength Raman spectroscopy has been applied to this model system to demonstrate background suppression. Here, the laser excitation wavelength of 785 nm was modulated with a frequency of 40 mHz by 0.6 nm. 40 spectra were accumulated with an exposure time of 5 seconds each. These data were subjected to principal component analysis to calculate modulated Raman signatures. The loading of the principal component shows characteristics of first derivatives with derivative like band shapes. The derivative of this loading corresponds to a pseudo-second derivative spectrum and enables to determine band positions.

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.

Use of Principal Components Analysis to Explain Controls on Nutrient Fluxes to the Chesapeake Bay

NASA Astrophysics Data System (ADS)

Rice, K. C.; Mills, A. L.

2017-12-01

The Chesapeake Bay watershed, on the east coast of the United States, encompasses about 166,000-square kilometers (km2) of diverse land use, which includes a mixture of forested, agricultural, and developed land. The watershed is now managed under a Total Daily Maximum Load (TMDL), which requires implementation of management actions by 2025 that are sufficient to reduce nitrogen, phosphorus, and suspended-sediment fluxes to the Chesapeake Bay and restore the bay's water quality. We analyzed nutrient and sediment data along with land-use and climatic variables in nine sub watersheds to better understand the drivers of flux within the watershed and to provide relevant management implications. The nine sub watersheds range in area from 300 to 30,000 km2, and the analysis period was 1985-2014. The 31 variables specific to each sub watershed were highly statistically significantly correlated, so Principal Components Analysis was used to reduce the dimensionality of the dataset. The analysis revealed that about 80% of the variability in the whole dataset can be explained by discharge, flux, and concentration of nutrients and sediment. The first two principal components (PCs) explained about 68% of the total variance. PC1 loaded strongly on discharge and flux, and PC2 loaded on concentration. The PC scores of both PC1 and PC2 varied by season. Subsequent analysis of PC1 scores versus PC2 scores, broken out by sub watershed, revealed management implications. Some of the largest sub watersheds are largely driven by discharge, and consequently large fluxes. In contrast, some of the smaller sub watersheds are more variable in nutrient concentrations than discharge and flux. Our results suggest that, given no change in discharge, a reduction in nutrient flux to the streams in the smaller watersheds could result in a proportionately larger decrease in fluxes of nutrients down the river to the bay, than in the larger watersheds.

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

Global versus Tract-Specific Components of Cerebral White Matter Integrity: Relation to Adult Age and Perceptual-Motor Speed

PubMed Central

Johnson, Micah A.; Diaz, Michele T.; Madden, David J.

2014-01-01

Although age-related differences in white matter have been well documented, the degree to which regional, tract-specific effects can be distinguished from global, brain-general effects is not yet clear. Similarly, the manner in which global and regional differences in white matter integrity contribute to age-related differences in cognition has not been well established. To address these issues, we analyzed diffusion tensor imaging measures from 52 younger adults (18–28) and 64 older adults (60–85). We conducted principal component analysis on each diffusion measure, using data from eight individual tracts. Two components were observed for fractional anisotropy: The first comprised high loadings from the superior longitudinal fasciculi and corticospinal tracts, and the second comprised high loadings from the optic radiations. In contrast, variation in axial, radial, and mean diffusivities yielded a single-component solution in each case, with high loadings from most or all tracts. For fractional anisotropy, the complementary results of multiple components and variability in component loadings across tracts suggest regional variation. However, for the diffusivity indices, the single component with high loadings from most or all of the tracts suggests primarily global, brain-general variation. Further analyses indicated that age was a significant mediator of the relation between each component and perceptual-motor speed. These data suggest that individual differences in white matter integrity, and their relation to age-related differences in perceptual-motor speed, represent influences that are beyond the level of individual tracts, but the extent to which regional or global effects predominate may differ between anisotropy and diffusivity measures. PMID:24972959

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

Faster tissue interface analysis from Raman microscopy images using compressed factorisation

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Energy Savings in Cellular Networks Based on Space-Time Structure of Traffic Loads

NASA Astrophysics Data System (ADS)

Sun, Jingbo; Wang, Yue; Yuan, Jian; Shan, Xiuming

Since most of energy consumed by the telecommunication infrastructure is due to the Base Transceiver Station (BTS), switching off BTSs when traffic load is low has been recognized as an effective way of saving energy. In this letter, an energy saving scheme is proposed to minimize the number of active BTSs based on the space-time structure of traffic loads as determined by principal component analysis. Compared to existing methods, our approach models traffic loads more accurately, and has a much smaller input size. As it is implemented in an off-line manner, our scheme also avoids excessive communications and computing overheads. Simulation results show that the proposed method has a comparable performance in energy savings.

Distinguishing dissolved organic matter at its origin: size and optical properties of leaf-litter leachates.

PubMed

Cuss, C W; Guéguen, C

2013-09-01

Dissolved organic matter (DOM) was leached from eight distinct samples of leaves taken from six distinct trees (red maple, bur oak at three times of the year, two sugar maple and two white spruce trees from disparate soil types). Multiple samples were taken over 72-96h of leaching. The size and optical properties of leachates were assessed using asymmetrical flow field-flow fractionation (AF4) coupled to diode-array ultraviolet/visible absorbance and excitation-emission matrix fluorescence detectors (EEM). The fluorescence of unfractionated samples was also analyzed. EEMs were analyzed using parallel factor analysis (PARAFAC) and principal component analysis (PCA) of proportional component loadings. Both the unfractionated and AF4-fractionated leachates had distinct size and optical properties. The 95% confidence ranges for molecular weight distributions were determined as: 210-440Da for spruce, 540-920Da for sugar maple, 630-800Da for spring oak leaves, 930-950Da for senescent oak, 1490-1670 for senescent red maple, and 3430-4270Da for oak leaves that were collected from the ground after spring thaw. In most cases the fluorescence properties of leachates were different for individuals from different soil types and across seasons; however, PCA of PARAFAC loadings revealed that the observed distinctiveness was chiefly species-based. Strong correlations were found between the molecular weight distribution of both unfractionated and fractionated leachates and their principal component loadings (R(2)=0.85 and 0.95, respectively). It is concluded that results support a species-based origin for differences in optical properties. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-04-01

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

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream.

PubMed

Byrne, Patrick; Runkel, Robert L; Walton-Day, Katherine

2017-07-01

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.

Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream

USGS Publications Warehouse

Byrne, Patrick; Runkel, Robert L.; Walton-Day, Katie

2017-01-01

Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.

Demographic, socioeconomic and nutritional determinants of daily versus non-daily sugar-sweetened and artificially sweetened beverage consumption.

PubMed

Mullie, P; Aerenhouts, D; Clarys, P

2012-02-01

The aim of this study was to determine the impact of demographic, socioeconomic and nutritional determinants on daily versus non-daily sugar-sweetened and artificially sweetened beverage consumption. Cross-sectional design in 1852 military men. Using mailed questionnaires, sugar-sweetened and artificially sweetened beverage consumption was recorded. Principal component analysis was used for dietary pattern analysis. Sugar-sweetened and artificially sweetened beverages were consumed daily by 36.3% and 33.2% of the participants, respectively. Age, body mass index (BMI), non-smoking and income were negatively related to sugar-sweetened beverage consumption. High BMI and trying to lose weight were related to artificially sweetened beverages consumption. Three major patterns were obtained from principal component analysis: first, the 'meat pattern', was loaded for red meats and processed meats; second, the 'healthy pattern', was loaded for tomatoes, fruit, whole grain, vegetables, fruit, fish, tea and nuts; finally, the 'sweet pattern' was loaded for sweets, desserts, snacks, high-energy drinks, high-fat dairy products and refined grains. The sugar-sweetened beverage consumption was strongly related with both the meat and sweet dietary patterns and inversely related to the healthy dietary pattern. The artificially sweetened beverage consumption was strongly related with the sweet and healthy dietary pattern. Daily consumption of sugar-sweetened beverages was inversely associated with a healthy dietary pattern. Daily consumption of artificially sweetened beverages was clearly associated with weight-loss intention.

The use of multidate multichannel radiance data in urban feature analysis

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

IQ, Skin Color, Crime, HIV/AIDS, and Income in 50 U.S. States

ERIC Educational Resources Information Center

Templer, Donald I.; Rushton, J. Philippe

2011-01-01

In 50 U.S. states, we found a positive manifold across 11 measures including IQ, skin color, birth rate, infant mortality, life expectancy, HIV/AIDS, violent crime, and state income with the first principal component accounting for 33% of the variance (median factor loading = 0.34). The correlation with a composite of total violent crime was…

Failure analysis of pinch-torsion tests as a thermal runaway risk evaluation method of Li-ion cells

NASA Astrophysics Data System (ADS)

Xia, Yuzhi; Li, Tianlei; Ren, Fei; Gao, Yanfei; Wang, Hsin

2014-11-01

Recently a pinch-torsion test is developed for safety testing of Li-ion batteries. It has been demonstrated that this test can generate small internal short-circuit spots in the separator in a controllable and repeatable manner. In the current research, the failure mechanism is examined by numerical simulations and comparisons to experimental observations. Finite element models are developed to evaluate the deformation of the separators under both pure pinch and pinch-torsion loading conditions. It is discovered that the addition of the torsion component significantly increased the maximum first principal strain, which is believed to induce the internal short circuit. In addition, the applied load in the pinch-torsion test is significantly less than in the pure pinch test, thus dramatically improving the applicability of this method to ultra-thick batteries which otherwise require heavy load in excess of machine capability. It is further found that the separator failure is achieved in the early stage of torsion (within a few degree of rotation). Effect of coefficient of friction on the maximum first principal strain is also examined.

Principal component analysis of the Norwegian version of the quality of life in late-stage dementia scale.

PubMed

Mjørud, Marit; Kirkevold, Marit; Røsvik, Janne; Engedal, Knut

2014-01-01

To investigate which factors the Quality of Life in Late-Stage Dementia (QUALID) scale holds when used among people with dementia (pwd) in nursing homes and to find out how the symptom load varies across the different severity levels of dementia. We included 661 pwd [mean age ± SD, 85.3 ± 8.6 years; 71.4% women]. The QUALID and the Clinical Dementia Rating (CDR) scale were applied. A principal component analysis (PCA) with varimax rotation and Kaiser normalization was applied to test the factor structure. Nonparametric analyses were applied to examine differences of symptom load across the three CDR groups. The mean QUALID score was 21.5 (±7.1), and the CDR scores of the three groups were 1 in 22.5%, 2 in 33.6% and 3 in 43.9%. The results of the statistical measures employed were the following: Crohnbach's α of QUALID, 0.74; Bartlett's test of sphericity, p <0.001; the Kaiser-Meyer-Olkin measure, 0.77. The PCA analysis resulted in three components accounting for 53% of the variance. The first component was 'tension' ('facial expression of discomfort', 'appears physically uncomfortable', 'verbalization suggests discomfort', 'being irritable and aggressive', 'appears calm', Crohnbach's α = 0.69), the second was 'well-being' ('smiles', 'enjoys eating', 'enjoys touching/being touched', 'enjoys social interaction', Crohnbach's α = 0.62) and the third was 'sadness' ('appears sad', 'cries', 'facial expression of discomfort', Crohnbach's α 0.65). The mean score on the components 'tension' and 'well-being' increased significantly with increasing severity levels of dementia. Three components of quality of life (qol) were identified. Qol decreased with increasing severity of dementia. © 2013 S. Karger AG, Basel.

Principal component analysis of biometric traits to reveal body confirmation in local hill cattle of Himalayan state of Himachal Pradesh, India.

PubMed

Verma, Deepak; Sankhyan, Varun; Katoch, Sanjeet; Thakur, Yash Pal

2015-12-01

In the present study, biometric traits (body length [BL], heart girth [HG], paunch girth (PG), forelimb length (FLL), hind limb length (HLL), face length, forehead width, forehead length, height at hump, hump length (HL), hook to hook distance, pin to pin distance, tail length (TL), TL up to switch, horn length, horn circumference, and ear length were studied in 218 adult hill cattle of Himachal Pradesh for phenotypic characterization. Morphological and biometrical observations were recorded on 218 hill cattle randomly selected from different districts within the breeding tract. Multivariate statistics and principal component analysis are used to account for the maximum portion of variation present in the original set of variables with a minimum number of composite variables through Statistical software, SAS 9.2. Five components were extracted which accounted for 65.9% of variance. The first component explained general body confirmation and explained 34.7% variation. It was represented by significant loading for BL, HG, PG, FLL, and HLL. Communality estimate ranged from 0.41 (HL) to 0.88 (TL). Second, third, fourth, and fifth component had a high loading for tail characteristics, horn characteristics, facial biometrics, and rear body, respectively. The result of component analysis of biometric traits suggested that indigenous hill cattle of Himachal Pradesh are small and compact size cattle with a medium hump, horizontally placed short ears, and a long tail. The study also revealed that factors extracted from the present investigation could be used in breeding programs with sufficient reduction in the number of biometric traits to be recorded to explain the body confirmation.

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

PubMed Central

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

2012-01-01

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

Comparative multivariate analysis of biometric traits of West African Dwarf and Red Sokoto goats.

PubMed

Yakubu, Abdulmojeed; Salako, Adebowale E; Imumorin, Ikhide G

2011-03-01

The population structure of 302 randomly selected West African Dwarf (WAD) and Red Sokoto (RS) goats was examined using multivariate morphometric analyses. This was to make the case for conservation, rational management and genetic improvement of these two most important Nigerian goat breeds. Fifteen morphometric measurements were made on each individual animal. RS goats were superior (P<0.05) to the WAD for the body size and skeletal proportions investigated. The phenotypic variability between the two breeds was revealed by their mutual responses in the principal components. While four principal components were extracted for WAD goats, three components were obtained for their RS counterparts with variation in the loading traits of each component for each breed. The Mahalanobis distance of 72.28 indicated a high degree of spatial racial separation in morphology between the genotypes. The Ward's option of the cluster analysis consolidated the morphometric distinctness of the two breeds. Application of selective breeding to genetic improvement would benefit from the detected phenotypic differentiation. Other implications for management and conservation of the goats are highlighted.

Damage detection methodology under variable load conditions based on strain field pattern recognition using FBGs, nonlinear principal component analysis, and clustering techniques

NASA Astrophysics Data System (ADS)

Sierra-Pérez, Julián; Torres-Arredondo, M.-A.; Alvarez-Montoya, Joham

2018-01-01

Structural health monitoring consists of using sensors integrated within structures together with algorithms to perform load monitoring, damage detection, damage location, damage size and severity, and prognosis. One possibility is to use strain sensors to infer structural integrity by comparing patterns in the strain field between the pristine and damaged conditions. In previous works, the authors have demonstrated that it is possible to detect small defects based on strain field pattern recognition by using robust machine learning techniques. They have focused on methodologies based on principal component analysis (PCA) and on the development of several unfolding and standardization techniques, which allow dealing with multiple load conditions. However, before a real implementation of this approach in engineering structures, changes in the strain field due to conditions different from damage occurrence need to be isolated. Since load conditions may vary in most engineering structures and promote significant changes in the strain field, it is necessary to implement novel techniques for uncoupling such changes from those produced by damage occurrence. A damage detection methodology based on optimal baseline selection (OBS) by means of clustering techniques is presented. The methodology includes the use of hierarchical nonlinear PCA as a nonlinear modeling technique in conjunction with Q and nonlinear-T 2 damage indices. The methodology is experimentally validated using strain measurements obtained by 32 fiber Bragg grating sensors bonded to an aluminum beam under dynamic bending loads and simultaneously submitted to variations in its pitch angle. The results demonstrated the capability of the methodology for clustering data according to 13 different load conditions (pitch angles), performing the OBS and detecting six different damages induced in a cumulative way. The proposed methodology showed a true positive rate of 100% and a false positive rate of 1.28% for a 99% of confidence.

Changes in element contents of four lichens over 11 years in the Boundary Waters Canoe Area Wilderness, northern Minnesota

USGS Publications Warehouse

Bennett, J.P.; Wetmore, C.M.

1999-01-01

Four species of lichen (Cladina rangiferina, Evernia mesomorpha, Hypogymnia physodes, and Parmelia sulcata) were sampled at six locations in the Boundary Waters Canoe Area Wilderness three times over a span of 11 years and analyzed for concentrations of 16 chemical elements to test the hypotheses that corticolous species would accumulate higher amounts of chemical elements than terricolous species, and that 11 years were sufficient to detect spatial patterns and temporal trends in element contents. Multivariate analyses of over 2770 data points revealed two principal components that accounted for 68% of the total variance in the data. These two components, the first highly loaded with Al, B, Cr, Fe, Ni and S, and the second loaded with Ca, Cd, Mg and Mn, were inversely related to each other over time and space. The first component was interpreted as consisting of an anthropogenic and a dust component, while the second, primarily a nutritional component. Cu, K, Na, P, Pb and Zn were not highly loaded on either component. Component 1 decreased significantly over the 11 years and from west to east, while component 2 increased. The corticolous species were more enriched in heavy metals than the terricolous species. All four elements in component 2 in H. physodes were above enrichment thresholds for this species. Species differences on the two components were greater than the effects of time and space, suggesting that biomonitoring with lichens is strongly species dependent. Some localities in the Boundary Waters Canoe Area Wilderness appear enriched in some anthropogenic elements for no obvious reasons.

Household Food Waste: Multivariate Regression and Principal Components Analyses of Awareness and Attitudes among U.S. Consumers

PubMed Central

2016-01-01

We estimate models of consumer food waste awareness and attitudes using responses from a national survey of U.S. residents. Our models are interpreted through the lens of several theories that describe how pro-social behaviors relate to awareness, attitudes and opinions. Our analysis of patterns among respondents’ food waste attitudes yields a model with three principal components: one that represents perceived practical benefits households may lose if food waste were reduced, one that represents the guilt associated with food waste, and one that represents whether households feel they could be doing more to reduce food waste. We find our respondents express significant agreement that some perceived practical benefits are ascribed to throwing away uneaten food, e.g., nearly 70% of respondents agree that throwing away food after the package date has passed reduces the odds of foodborne illness, while nearly 60% agree that some food waste is necessary to ensure meals taste fresh. We identify that these attitudinal responses significantly load onto a single principal component that may represent a key attitudinal construct useful for policy guidance. Further, multivariate regression analysis reveals a significant positive association between the strength of this component and household income, suggesting that higher income households most strongly agree with statements that link throwing away uneaten food to perceived private benefits. PMID:27441687

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

PubMed

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

2000-07-01

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

Confirmatory Factor Analysis of the Delirium Rating Scale Revised-98 (DRS-R98).

PubMed

Thurber, Steven; Kishi, Yasuhiro; Trzepacz, Paula T; Franco, Jose G; Meagher, David J; Lee, Yanghyun; Kim, Jeong-Lan; Furlanetto, Leticia M; Negreiros, Daniel; Huang, Ming-Chyi; Chen, Chun-Hsin; Kean, Jacob; Leonard, Maeve

2015-01-01

Principal components analysis applied to the Delirium Rating Scale-Revised-98 contributes to understanding the delirium construct. Using a multisite pooled international delirium database, the authors applied confirmatory factor analysis to Delirium Rating Scale-Revised-98 scores from 859 adult patients evaluated by delirium experts (delirium, N=516; nondelirium, N=343). Confirmatory factor analysis found all diagnostic features and core symptoms (cognitive, language, thought process, sleep-wake cycle, motor retardation), except motor agitation, loaded onto factor 1. Motor agitation loaded onto factor 2 with noncore symptoms (delusions, affective lability, and perceptual disturbances). Factor 1 loading supports delirium as a single construct, but when accompanied by psychosis, motor agitation's role may not be solely as a circadian activity indicator.

An analytics of electricity consumption characteristics based on principal component analysis

NASA Astrophysics Data System (ADS)

Feng, Junshu

2018-02-01

Abstract . More detailed analysis of the electricity consumption characteristics can make demand side management (DSM) much more targeted. In this paper, an analytics of electricity consumption characteristics based on principal component analysis (PCA) is given, which the PCA method can be used in to extract the main typical characteristics of electricity consumers. Then, electricity consumption characteristics matrix is designed, which can make a comparison of different typical electricity consumption characteristics between different types of consumers, such as industrial consumers, commercial consumers and residents. In our case study, the electricity consumption has been mainly divided into four characteristics: extreme peak using, peak using, peak-shifting using and others. Moreover, it has been found that industrial consumers shift their peak load often, meanwhile commercial and residential consumers have more peak-time consumption. The conclusions can provide decision support of DSM for the government and power providers.

Interpretation of data on the aggregate composition of typical chernozems under different land use by cluster and principal component analyses

NASA Astrophysics Data System (ADS)

Kholodov, V. A.; Yaroslavtseva, N. V.; Lazarev, V. I.; Frid, A. S.

2016-09-01

Cluster analysis and principal component analysis (PCA) have been used for the interpretation of dry sieving data. Chernozems from the treatments of long-term field experiments with different land-use patterns— annually mowed steppe, continuous potato culture, permanent black fallow, and untilled fallow since 1998 after permanent black fallow—have been used. Analysis of dry sieving data by PCA has shown that the treatments of untilled fallow after black fallow and annually mowed steppe differ most in the series considered; the content of dry aggregates of 10-7 mm makes the largest contribution to the distribution of objects along the first principal component. This fraction has been sieved in water and analyzed by PCA. In contrast to dry sieving data, the wet sieving data showed the closest mathematical distance between the treatment of untilled fallow after black fallow and the undisturbed treatment of annually mowed steppe, while the untilled fallow after black fallow and the permanent black fallow were the most distant treatments. Thus, it may be suggested that the water stability of structure is first restored after the removal of destructive anthropogenic load. However, the restoration of the distribution of structural separates to the parameters characteristic of native soils is a significantly longer process.

[Stress change of periodontal ligament of the anterior teeth at the stage of space closure in lingual appliances: a 3-dimensional finite element analysis].

PubMed

Liu, D W; Li, J; Guo, L; Rong, Q G; Zhou, Y H

2018-02-18

To analyze the stress distribution in the periodontal ligament (PDL) under different loading conditions at the stage of space closure by 3D finite element model of customized lingual appliances. The 3D finite element model was used in ANSYS 11.0 to analyze the stress distribution in the PDL under the following loading conditions: (1) buccal sliding mechanics (0.75 N,1.00 N,1.50 N), (2) palatal sliding mechanics (0.75 N,1.00 N,1.50 N), (3) palatal-buccal combined sliding mechanics (buccal 1.00 N + palatal 0.50 N, buccal 0.75 N + palatal 0.75 N, buccal 0.50 N+ palatal 1.00 N). The maximum principal stress, minimum principal stress and von Mises stress were evaluated. (1) buccal sliding mechanics(0.75 N,1.00 N,1.50 N): maximum principal stress: at the initial of loading, maximum principal stress, which was the compressed stress, distributed in labial PDL of cervix of lateral incisor, and palatal distal PDL of cervix of canine. With increasing loa-ding, the magnitude and range of the stress was increased. Minimum principal stress: at the initial of loading, minimum principal stress which was tonsil stress, distributed in palatal PDL of cervix of lateral incisor and mesial PDL of cervix of canine. With increasing loading, the magnitude and range of minimum principal stress was increased. The area of minimum principal stress appeared in distal and mesial PDL of cervix of central incisor. von Mises stress:it distributed in labial and palatal PDL of cervix of lateral incisor and distal PDL of cervix of canine initially. With increasing loading, the magnitude and range of stress was increased towards the direction of root. Finally, there was stress concentration area at mesial PDL of cervix of canine. (2) palatal sliding mechanics(0.75 N,1.00 N,1.50 N): maximum principal stress: at the initial of loading, maximum principal stress which was the compressed stress, distributed in palatal and distal PDL of cervix of canine, and distal-buccal and palatal PDL of cervix of lateral incisor. With increasing loading, the magnitude and range of the stress was increased. Minimum principal stress: at the initial of loading, minimum principal stress which was tonsil stress, distributed in distal-interproximal PDL of cervix of lateral incisor and mesial-interproximal PDL of cervix of canine. With increasing loading, the magnitude and range of the stress was increased.von Mises stress: von Mises stress distributed in palatal and interproximal PDL of cervix of canine. With increasing loading, the magnitude and range of stress was increased. Finally, von Mises stress distributing area appeared at distal-palatal PDL of cervix of canine. (3) palatal-buccal combined sliding mechanics: maximum principal stress: maximum principal stress still distributed in distal-palatal PDL of cervix of canine. Minimum principal stress: minimum principal stress distributed in palatal PDL of cervix of lateral incisor when buccal force was more than palatal force. As palatal force increased, the stress concentrating area transferred to mesial PDL of cervix of canine.von Mises stress: it was lower and more well-distributed in palatal-buccal combined sliding mechanics than palatal or buccal sliding mechanics. Using buccal sliding mechanics,stress majorly distributed in PDL of lateral incisor and canine, and magnitude and range of stress increased with the increase of loading; Using palatal sliding mechanics, stress majorly distributed in PDL of canine, and magnitude and range of stress increased with the increase of loading; With palatal-buccal combined sliding mechanics, the maximum principal stress distributed in the distal PDL of canine. Minimum principal stress distributed in palatal PDL of cervix of lateral incisor when buccal force was more than palatal force. As palatal force was increasing, the minimum principal stress distributing area shifted to mesial PDL of cervix of canine. When using 1.00 N buccal force and 0.50 N palatal force, the von Mises stress distributed uniformly in PDL and minimal stress appeared.

Stress and Coping: A Comparison of Self-Report Measures of Functioning in Families of Young Children with Cerebral Palsy or No Medical Diagnosis

ERIC Educational Resources Information Center

Britner, Preston A.; Morog, Maria C.; Pianta, Robert C.; Marvin, Robert S.

2003-01-01

We analyzed data from 87 mothers of children ages 15 to 44 months with cerebral palsy (CP) or no diagnosis, who completed the Dyadic Adjustment Scale, Parenting Stress Index, Support Functions Scale, and Inventory of Social Support. Principal components analysis of the 15 subscales from the 5 measures revealed few cross-measure loadings. Mothers…

Overlap and distinction between measures of insight and self-stigma.

PubMed

Hasson-Ohayon, Ilanit

2018-05-24

Multiple studies on insight into one's illness and self-stigma among patients with serious mental illness and their relatives have shown that these constructs are related to one another and that they affect outcome. However, a critical exploration of the items used to assess both constructs raises questions with regard to the possible overlapping and centrality of items. The current study used five different samples to explore the possible overlap and distinction between insight and self-stigma, and to identify central items, via network analyses and principal component factor analysis. Findings from the network analyses showed overlap between insight and self-stigma exist with a relatively clearer observational distinction between the constructs among the two parent samples in comparison to the patient samples. Principal component factor analysis constrained to two factors showed that a relatively high percentage of items were not loaded on either factor, and in a few datasets, several insight items were loaded on the self-stigma scale and vice versa. The author discusses implications for research and calls for rethinking the way insight is assessed. Clinical implications are also discussed in reference to central items of social isolation, future worries and stereotype endorsement among the different study groups. Copyright © 2018 Elsevier B.V. All rights reserved.

Study of seasonal and long-term vertical deformation in Nepal based on GPS and GRACE observations

NASA Astrophysics Data System (ADS)

Zhang, Tengxu; Shen, WenBin; Pan, Yuanjin; Luan, Wei

2018-02-01

Lithospheric deformation signal can be detected by combining data from continuous global positioning system (CGPS) and satellite observations from the Gravity Recovery and Climate Experiment (GRACE). In this paper, we use 2.5- to 19-year-long time series from 35 CGPS stations to estimate vertical deformation rates in Nepal, which is located in the southern side of the Himalaya. GPS results were compared with GRACE observations. Principal component analysis was conducted to decompose the time series into three-dimensional principal components (PCs) and spatial eigenvectors. The top three high-order PCs were calculated to correct common mode errors. Both GPS and GRACE observations showed significant seasonal variations. The observed seasonal GPS vertical variations are in good agreement with those from the GRACE-derived results, particularly for changes in surface pressure, non-tidal oceanic mass loading, and hydrologic loading. The GPS-observed rates of vertical deformation obtained for the region suggest both tectonic impact and mass decrease. The rates of vertical crustal deformation were estimated by removing the GRACE-derived hydrological vertical rates from the GPS measurements. Most of the sites located in the southern part of the Main Himalayan Thrust subsided, whereas the northern part mostly showed an uplift. These results may contribute to the understanding of secular vertical crustal deformation in Nepal.

The DASS-14: Improving the Construct Validity and Reliability of the Depression, Anxiety, and Stress Scale in a Cohort of Health Professionals.

PubMed

Wise, Frances M; Harris, Darren W; Olver, John H

2017-01-01

Considerable research has been undertaken in evaluating the DASS-21 in a variety of clinical populations, but studies of the instrument's psychometric adequacy in healthcare professionals is lacking. This study aimed to establish and improve the construct validity and reliability of the DASS-21 in a cohort of Australian health professionals. 343 rehabilitation health professionals completed the DASS-21, along with a demographic questionnaire. Principal components analysis was performed to identify potential factors in the DASS-21. Factors were interpreted against theoretical constructs underlying the instrument. Items loading on separate factors were then subjected to reliability analysis to determine internal consistency of subscales. Items that demonstrated poor fit, or loaded onto more than one factor, were deleted to maximise the reliability of each subscale. Principal components analysis identified three dimensions (depression, anxiety, stress) in a modified version of the DASS-21 (renamed DASS-14), with appropriate construct validity and good reliability (a=0.73 to 0.88). The three dimensions accounted for over 62% of variance between items. The modified DASS-14 scale is a more parsimonious measure of depression, anxiety, and stress, with acceptable reliability and construct validity, in rehabilitation health professionals and is appropriate for use in studies of similar populations.

Distributed photovoltaic architecture powering a DC bus: Impact of duty cycle and load variations on the efficiency of the generator

NASA Astrophysics Data System (ADS)

Allouache, Hadj; Zegaoui, Abdallah; Boutoubat, Mohamed; Bokhtache, Aicha Aissa; Kessaissia, Fatma Zohra; Charles, Jean-Pierre; Aillerie, Michel

2018-05-01

This paper focuses on a photovoltaic generator feeding a load via a boost converter in a distributed PV architecture. The principal target is the evaluation of the efficiency of a distributed photovoltaic architecture powering a direct current (DC) PV bus. This task is achieved by outlining an original way for tracking the Maximum Power Point (MPP) taking into account load variations and duty cycle on the electrical quantities of the boost converter and on the PV generator output apparent impedance. Thereafter, in a given sized PV system, we analyze the influence of the load variations on the behavior of the boost converter and we deduce the limits imposed by the load on the DC PV bus. The simultaneous influences of 1- the variation of the duty cycle of the boost converter and 2- the load power on the parameters of the various components of the photovoltaic chain and on the boost performances are clearly presented as deduced by simulation.

Tailored multivariate analysis for modulated enhanced diffraction

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

Caliandro, Rocco; Guccione, Pietro; Nico, Giovanni

2015-10-21

Modulated enhanced diffraction (MED) is a technique allowing the dynamic structural characterization of crystalline materials subjected to an external stimulus, which is particularly suited forin situandoperandostructural investigations at synchrotron sources. Contributions from the (active) part of the crystal system that varies synchronously with the stimulus can be extracted by an offline analysis, which can only be applied in the case of periodic stimuli and linear system responses. In this paper a new decomposition approach based on multivariate analysis is proposed. The standard principal component analysis (PCA) is adapted to treat MED data: specific figures of merit based on their scoresmore » and loadings are found, and the directions of the principal components obtained by PCA are modified to maximize such figures of merit. As a result, a general method to decompose MED data, called optimum constrained components rotation (OCCR), is developed, which produces very precise results on simulated data, even in the case of nonperiodic stimuli and/or nonlinear responses. The multivariate analysis approach is able to supply in one shot both the diffraction pattern related to the active atoms (through the OCCR loadings) and the time dependence of the system response (through the OCCR scores). When applied to real data, OCCR was able to supply only the latter information, as the former was hindered by changes in abundances of different crystal phases, which occurred besides structural variations in the specific case considered. To develop a decomposition procedure able to cope with this combined effect represents the next challenge in MED analysis.« less

Failure analysis of pinch-torsion tests as a thermal runaway risk evaluation method of Li-Ion Cells

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

Xia, Yuzhi; Li, Dr. Tianlei; Ren, Prof. Fei

2014-01-01

Recently a pinch-torsion test is developed for safety testing of Li-ion batteries (Ren et al., J. Power Source, 2013). It has been demonstrated that this test can generate small internal short-circuit spots in the separator in a controllable and repeatable manner. In the current research, the failure mechanism is examined by numerical simulations and comparisons to experimental observations. Finite element models are developed to evaluate the deformation of the separators under both pure pinch and pinch-torsion loading conditions. It is discovered that the addition of the torsion component significantly increased the maximum principal strain, which is believed to induce themore » internal short circuit. In addition, the applied load in the pinch-torsion test is significantly less than in the pure pinch test, thus dramatically improving the applicability of this method to ultra-thick batteries which otherwise require heavy load in excess of machine capability. It is further found that the separator failure is achieved in the early stage of torsion (within a few degree of rotation). Effect of coefficient of friction on the maximum principal strain is also examined.« less

Decreased Efficiency of Task-Positive and Task-Negative Networks During Working Memory in Schizophrenia

PubMed Central

Metzak, Paul D.; Riley, Jennifer D.; Wang, Liang; Whitman, Jennifer C.; Ngan, Elton T. C.; Woodward, Todd S.

2012-01-01

Working memory (WM) is one of the most impaired cognitive processes in schizophrenia. Functional magnetic resonance imaging (fMRI) studies in this area have typically found a reduction in information processing efficiency but have focused on the dorsolateral prefrontal cortex. In the current study using the Sternberg Item Recognition Test, we consider networks of regions supporting WM and measure the activation of functionally connected neural networks over different WM load conditions. We used constrained principal component analysis with a finite impulse response basis set to compare the estimated hemodynamic response associated with different WM load condition for 15 healthy control subjects and 15 schizophrenia patients. Three components emerged, reflecting activated (task-positive) and deactivated (task-negative or default-mode) neural networks. Two of the components (with both task-positive and task-negative aspects) were load dependent, were involved in encoding and delay phases (one exclusively encoding and the other both encoding and delay), and both showed evidence for decreased efficiency in patients. The results suggest that WM capacity is reached sooner for schizophrenia patients as the overt levels of WM load increase, to the point that further increases in overt memory load do not increase fMRI activation, and lead to performance impairments. These results are consistent with an account holding that patients show reduced efficiency in task-positive and task-negative networks during WM and also partially support the shifted inverted-U-shaped curve theory of the relationship between WM load and fMRI activation in schizophrenia. PMID:21224491

A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

Complex numbers in chemometrics: examples from multivariate impedance measurements on lipid monolayers.

PubMed

Geladi, Paul; Nelson, Andrew; Lindholm-Sethson, Britta

2007-07-09

Electrical impedance gives multivariate complex number data as results. Two examples of multivariate electrical impedance data measured on lipid monolayers in different solutions give rise to matrices (16x50 and 38x50) of complex numbers. Multivariate data analysis by principal component analysis (PCA) or singular value decomposition (SVD) can be used for complex data and the necessary equations are given. The scores and loadings obtained are vectors of complex numbers. It is shown that the complex number PCA and SVD are better at concentrating information in a few components than the naïve juxtaposition method and that Argand diagrams can replace score and loading plots. Different concentrations of Magainin and Gramicidin A give different responses and also the role of the electrolyte medium can be studied. An interaction of Gramicidin A in the solution with the monolayer over time can be observed.

Building Finite Element Models to Investigate Zebrafish Jaw Biomechanics.

PubMed

Brunt, Lucy H; Roddy, Karen A; Rayfield, Emily J; Hammond, Chrissy L

2016-12-03

Skeletal morphogenesis occurs through tightly regulated cell behaviors during development; many cell types alter their behavior in response to mechanical strain. Skeletal joints are subjected to dynamic mechanical loading. Finite element analysis (FEA) is a computational method, frequently used in engineering that can predict how a material or structure will respond to mechanical input. By dividing a whole system (in this case the zebrafish jaw skeleton) into a mesh of smaller 'finite elements', FEA can be used to calculate the mechanical response of the structure to external loads. The results can be visualized in many ways including as a 'heat map' showing the position of maximum and minimum principal strains (a positive principal strain indicates tension while a negative indicates compression. The maximum and minimum refer the largest and smallest strain). These can be used to identify which regions of the jaw and therefore which cells are likely to be under particularly high tensional or compressional loads during jaw movement and can therefore be used to identify relationships between mechanical strain and cell behavior. This protocol describes the steps to generate Finite Element models from confocal image data on the musculoskeletal system, using the zebrafish lower jaw as a practical example. The protocol leads the reader through a series of steps: 1) staining of the musculoskeletal components, 2) imaging the musculoskeletal components, 3) building a 3 dimensional (3D) surface, 4) generating a mesh of Finite Elements, 5) solving the FEA and finally 6) validating the results by comparison to real displacements seen in movements of the fish jaw.

Mandibular corpus bone strains during mastication in goats (Capra hircus): a comparison of ingestive and rumination chewing.

PubMed

Williams, Susan H; Stover, Kristin K; Davis, Jillian S; Montuelle, Stephane J

2011-10-01

To compare the mechanical loading environment of the jaw in goats during ingestive and rumination chewing. Rosette strain gauges were attached to the external surface of the mandibular corpus in five goats to record bone strains during the mastication of hay and rumination. Strain magnitudes and maximum physiological strain rates during the mastication of hay are significantly higher than during rumination chewing on the working and balancing sides. Principal strain ratios and orientations are similar between the two chewing behaviours. Loading and chewing cycle duration are all longer during rumination chewing, whereas chew duty factor and variances in load and chewing cycle durations are higher during ingestive chewing. For most of the variables, differences in strain magnitudes or durations are similar at all three gauge sites, suggesting that rumination and ingestive chewing do not differentially influence bone at the three gauge sites. Despite lower strain magnitudes, the repetitive nature of rumination chewing makes it an important component of the mechanical loading environment of the selenodont artiodactyl jaw. However, similarities in principal strain orientations and ratios indicate that rumination chewing need not be considered as a unique loading behaviour influencing the biomechanics of the selenodont artiodactyl jaw. Differences in loading and chewing cycle durations during rumination and ingestion demonstrate flexibility in adult chewing frequencies. Finally, although the low within-sequence variability in chewing cycle durations supports the hypothesis that mammalian mastication is energetically efficient, chewing during rumination may not be more efficient than during ingestion. Copyright © 2011 Elsevier Ltd. All rights reserved.

Solder Creep-Fatigue Interactions with Flexible Leaded Part

NASA Technical Reports Server (NTRS)

Ross, R. G., Jr.; Wen, L. C.

1994-01-01

In most electronic packaging applications it is not a single high stress event that breaks a component solder joint; rather it is repeated or prolonged load applications that result in fatigue or creep failure of the solder. The principal strain in solder joints is caused by differential expansion between the part and its mounting environment due to hanges in temperature (thermal cycles) and/or due to temperature gradients between the part and the board.

Using Structural Equation Modeling To Fit Models Incorporating Principal Components.

ERIC Educational Resources Information Center

Dolan, Conor; Bechger, Timo; Molenaar, Peter

1999-01-01

Considers models incorporating principal components from the perspectives of structural-equation modeling. These models include the following: (1) the principal-component analysis of patterned matrices; (2) multiple analysis of variance based on principal components; and (3) multigroup principal-components analysis. Discusses fitting these models…

Kinematic and kinetic synergies of the lower extremities during the pull in olympic weightlifting.

PubMed

Kipp, Kristof; Redden, Josh; Sabick, Michelle; Harris, Chad

2012-07-01

The purpose of this study was to identify multijoint lower extremity kinematic and kinetic synergies in weightlifting and compare these synergies between joints and across different external loads. Subjects completed sets of the clean exercise at loads equal to 65, 75, and 85% of their estimated 1-RM. Functional data analysis was used to extract principal component functions (PCF's) for hip, knee, and ankle joint angles and moments of force during the pull phase of the clean at all loads. The PCF scores were then compared between joints and across loads to determine how much of each PCF was present at each joint and how it differed across loads. The analyses extracted two kinematic and four kinetic PCF's. The statistical comparisons indicated that all kinematic and two of the four kinetic PCF's did not differ across load, but scaled according to joint function. The PCF's captured a set of joint- and load-specific synergies that quantified biomechanical function of the lower extremity during Olympic weightlifting and revealed important technical characteristics that should be considered in sports training and future research.

A Direct Approach to In-Plane Stress Separation using Photoelastic Ptychography

NASA Astrophysics Data System (ADS)

Anthony, Nicholas; Cadenazzi, Guido; Kirkwood, Henry; Huwald, Eric; Nugent, Keith; Abbey, Brian

2016-08-01

The elastic properties of materials, either under external load or in a relaxed state, influence their mechanical behaviour. Conventional optical approaches based on techniques such as photoelasticity or thermoelasticity can be used for full-field analysis of the stress distribution within a specimen. The circular polariscope in combination with holographic photoelasticity allows the sum and difference of principal stress components to be determined by exploiting the temporary birefringent properties of materials under load. Phase stepping and interferometric techniques have been proposed as a method for separating the in-plane stress components in two-dimensional photoelasticity experiments. In this paper we describe and demonstrate an alternative approach based on photoelastic ptychography which is able to obtain quantitative stress information from far fewer measurements than is required for interferometric based approaches. The complex light intensity equations based on Jones calculus for this setup are derived. We then apply this approach to the problem of a disc under diametrical compression. The experimental results are validated against the analytical solution derived by Hertz for the theoretical displacement fields for an elastic disc subject to point loading.

A Direct Approach to In-Plane Stress Separation using Photoelastic Ptychography

PubMed Central

Anthony, Nicholas; Cadenazzi, Guido; Kirkwood, Henry; Huwald, Eric; Nugent, Keith; Abbey, Brian

2016-01-01

The elastic properties of materials, either under external load or in a relaxed state, influence their mechanical behaviour. Conventional optical approaches based on techniques such as photoelasticity or thermoelasticity can be used for full-field analysis of the stress distribution within a specimen. The circular polariscope in combination with holographic photoelasticity allows the sum and difference of principal stress components to be determined by exploiting the temporary birefringent properties of materials under load. Phase stepping and interferometric techniques have been proposed as a method for separating the in-plane stress components in two-dimensional photoelasticity experiments. In this paper we describe and demonstrate an alternative approach based on photoelastic ptychography which is able to obtain quantitative stress information from far fewer measurements than is required for interferometric based approaches. The complex light intensity equations based on Jones calculus for this setup are derived. We then apply this approach to the problem of a disc under diametrical compression. The experimental results are validated against the analytical solution derived by Hertz for the theoretical displacement fields for an elastic disc subject to point loading. PMID:27488605

Optical system for tablet variety discrimination using visible/near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shao, Yongni; He, Yong; Hu, Xingyue

2007-12-01

An optical system based on visible/near-infrared spectroscopy (Vis/NIRS) for variety discrimination of ginkgo (Ginkgo biloba L.) tablets was developed. This system consisted of a light source, beam splitter system, sample chamber, optical detector (diffuse reflection detector), and data collection. The tablet varieties used in the research include Da na kang, Xin bang, Tian bao ning, Yi kang, Hua na xing, Dou le, Lv yuan, Hai wang, and Ji yao. All samples (n=270) were scanned in the Vis/NIR region between 325 and 1075 nm using a spectrograph. The chemometrics method of principal component artificial neural network (PC-ANN) was used to establish discrimination models of them. In PC-ANN models, the scores of the principal components were chosen as the input nodes for the input layer of ANN, and the best discrimination rate of 91.1% was reached. Principal component analysis was also executed to select several optimal wavelengths based on loading values. Wavelengths at 481, 458, 466, 570, 1000, 662, and 400 nm were then used as the input data of stepwise multiple linear regression, the regression equation of ginkgo tablets was obtained, and the discrimination rate was researched 84.4%. The results indicated that this optical system could be applied to discriminating ginkgo (Ginkgo biloba L.) tablets, and it supplied a new method for fast ginkgo tablet variety discrimination.

[Research on spectra recognition method for cabbages and weeds based on PCA and SIMCA].

PubMed

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

2013-10-01

In order to improve the accuracy and efficiency of weed identification, the difference of spectral reflectance was employed to distinguish between crops and weeds. Firstly, the different combinations of Savitzky-Golay (SG) convolutional derivation and multiplicative scattering correction (MSC) method were applied to preprocess the raw spectral data. Then the clustering analysis of various types of plants was completed by using principal component analysis (PCA) method, and the feature wavelengths which were sensitive for classifying various types of plants were extracted according to the corresponding loading plots of the optimal principal components in PCA results. Finally, setting the feature wavelengths as the input variables, the soft independent modeling of class analogy (SIMCA) classification method was used to identify the various types of plants. The experimental results of classifying cabbages and weeds showed that on the basis of the optimal pretreatment by a synthetic application of MSC and SG convolutional derivation with SG's parameters set as 1rd order derivation, 3th degree polynomial and 51 smoothing points, 23 feature wavelengths were extracted in accordance with the top three principal components in PCA results. When SIMCA method was used for classification while the previously selected 23 feature wavelengths were set as the input variables, the classification rates of the modeling set and the prediction set were respectively up to 98.6% and 100%.

Recovering Wood and McCarthy's ERP-prototypes by means of ERP-specific procrustes-rotation.

PubMed

Beauducel, André

2018-02-01

The misallocation of treatment-variance on the wrong component has been discussed in the context of temporal principal component analysis of event-related potentials. There is, until now, no rotation-method that can perfectly recover Wood and McCarthy's prototypes without making use of additional information on treatment-effects. In order to close this gap, two new methods: for component rotation were proposed. After Varimax-prerotation, the first method identifies very small slopes of successive loadings. The corresponding loadings are set to zero in a target-matrix for event-related orthogonal partial Procrustes- (EPP-) rotation. The second method generates Gaussian normal distributions around the peaks of the Varimax-loadings and performs orthogonal Procrustes-rotation towards these Gaussian distributions. Oblique versions of this Gaussian event-related Procrustes- (GEP) rotation and of EPP-rotation are based on Promax-rotation. A simulation study revealed that the new orthogonal rotations recover Wood and McCarthy's prototypes and eliminate misallocation of treatment-variance. In an additional simulation study with a more pronounced overlap of the prototypes GEP Promax-rotation reduced the variance misallocation slightly more than EPP Promax-rotation. Comparison with Existing Method(s): Varimax- and conventional Promax-rotations resulted in substantial misallocations of variance in simulation studies when components had temporal overlap. A substantially reduced misallocation of variance occurred with the EPP-, EPP Promax-, GEP-, and GEP Promax-rotations. Misallocation of variance can be minimized by means of the new rotation methods: Making use of information on the temporal order of the loadings may allow for improvements of the rotation of temporal PCA components. Copyright © 2017 Elsevier B.V. All rights reserved.

Metal-backed versus all-polyethylene unicompartmental knee arthroplasty

PubMed Central

Eaton, M. J.; Nutton, R. W.; Wade, F. A.; Evans, S. L.; Pankaj, P.

2017-01-01

Objectives Up to 40% of unicompartmental knee arthroplasty (UKA) revisions are performed for unexplained pain which may be caused by elevated proximal tibial bone strain. This study investigates the effect of tibial component metal backing and polyethylene thickness on bone strain in a cemented fixed-bearing medial UKA using a finite element model (FEM) validated experimentally by digital image correlation (DIC) and acoustic emission (AE). Materials and Methods A total of ten composite tibias implanted with all-polyethylene (AP) and metal-backed (MB) tibial components were loaded to 2500 N. Cortical strain was measured using DIC and cancellous microdamage using AE. FEMs were created and validated and polyethylene thickness varied from 6 mm to 10 mm. The volume of cancellous bone exposed to < -3000 µε (pathological loading) and < -7000 µε (yield point) minimum principal (compressive) microstrain and > 3000 µε and > 7000 µε maximum principal (tensile) microstrain was computed. Results Experimental AE data and the FEM volume of cancellous bone with compressive strain < -3000 µε correlated strongly: R = 0.947, R2 = 0.847, percentage error 12.5% (p < 0.001). DIC and FEM data correlated: R = 0.838, R2 = 0.702, percentage error 4.5% (p < 0.001). FEM strain patterns included MB lateral edge concentrations; AP concentrations at keel, peg and at the region of load application. Cancellous strains were higher in AP implants at all loads: 2.2- (10 mm) to 3.2-times (6 mm) the volume of cancellous bone compressively strained < -7000 µε. Conclusion AP tibial components display greater volumes of pathologically overstrained cancellous bone than MB implants of the same geometry. Increasing AP thickness does not overcome these pathological forces and comes at the cost of greater bone resection. Cite this article: C. E. H. Scott, M. J. Eaton, R. W. Nutton, F. A. Wade, S. L. Evans, P. Pankaj. Metal-backed versus all-polyethylene unicompartmental knee arthroplasty: Proximal tibial strain in an experimentally validated finite element model. Bone Joint Res 2017;6:22–30. DOI:10.1302/2046-3758.61.BJR-2016-0142.R1 PMID:28077394

Metal-backed versus all-polyethylene unicompartmental knee arthroplasty: Proximal tibial strain in an experimentally validated finite element model.

PubMed

Scott, C E H; Eaton, M J; Nutton, R W; Wade, F A; Evans, S L; Pankaj, P

2017-01-01

Up to 40% of unicompartmental knee arthroplasty (UKA) revisions are performed for unexplained pain which may be caused by elevated proximal tibial bone strain. This study investigates the effect of tibial component metal backing and polyethylene thickness on bone strain in a cemented fixed-bearing medial UKA using a finite element model (FEM) validated experimentally by digital image correlation (DIC) and acoustic emission (AE). A total of ten composite tibias implanted with all-polyethylene (AP) and metal-backed (MB) tibial components were loaded to 2500 N. Cortical strain was measured using DIC and cancellous microdamage using AE. FEMs were created and validated and polyethylene thickness varied from 6 mm to 10 mm. The volume of cancellous bone exposed to < -3000 µε (pathological loading) and < -7000 µε (yield point) minimum principal (compressive) microstrain and > 3000 µε and > 7000 µε maximum principal (tensile) microstrain was computed. Experimental AE data and the FEM volume of cancellous bone with compressive strain < -3000 µε correlated strongly: R = 0.947, R 2 = 0.847, percentage error 12.5% (p < 0.001). DIC and FEM data correlated: R = 0.838, R 2 = 0.702, percentage error 4.5% (p < 0.001). FEM strain patterns included MB lateral edge concentrations; AP concentrations at keel, peg and at the region of load application. Cancellous strains were higher in AP implants at all loads: 2.2- (10 mm) to 3.2-times (6 mm) the volume of cancellous bone compressively strained < -7000 µε. AP tibial components display greater volumes of pathologically overstrained cancellous bone than MB implants of the same geometry. Increasing AP thickness does not overcome these pathological forces and comes at the cost of greater bone resection.Cite this article: C. E. H. Scott, M. J. Eaton, R. W. Nutton, F. A. Wade, S. L. Evans, P. Pankaj. Metal-backed versus all-polyethylene unicompartmental knee arthroplasty: Proximal tibial strain in an experimentally validated finite element model. Bone Joint Res 2017;6:22-30. DOI:10.1302/2046-3758.61.BJR-2016-0142.R1. © 2017 Scott et al.

Energy efficient engine high-pressure turbine component rig performance test report

NASA Technical Reports Server (NTRS)

Leach, K. P.

1983-01-01

A rig test of the cooled high-pressure turbine component for the Energy Efficient Engine was successfully completed. The principal objective of this test was to substantiate the turbine design point performance as well as determine off-design performance with the interaction of the secondary flow system. The measured efficiency of the cooled turbine component was 88.5 percent, which surpassed the rig design goal of 86.5 percent. The secondary flow system in the turbine performed according to the design intent. Characterization studies showed that secondary flow system performance is insensitive to flow and pressure variations. Overall, this test has demonstrated that a highly-loaded, transonic, single-stage turbine can achieve a high level of operating efficiency.

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.

Tailored multivariate analysis for modulated enhanced diffraction

DOE PAGES

Caliandro, Rocco; Guccione, Pietro; Nico, Giovanni; ...

2015-10-21

Modulated enhanced diffraction (MED) is a technique allowing the dynamic structural characterization of crystalline materials subjected to an external stimulus, which is particularly suited forin situandoperandostructural investigations at synchrotron sources. Contributions from the (active) part of the crystal system that varies synchronously with the stimulus can be extracted by an offline analysis, which can only be applied in the case of periodic stimuli and linear system responses. In this paper a new decomposition approach based on multivariate analysis is proposed. The standard principal component analysis (PCA) is adapted to treat MED data: specific figures of merit based on their scoresmore » and loadings are found, and the directions of the principal components obtained by PCA are modified to maximize such figures of merit. As a result, a general method to decompose MED data, called optimum constrained components rotation (OCCR), is developed, which produces very precise results on simulated data, even in the case of nonperiodic stimuli and/or nonlinear responses. Furthermore, the multivariate analysis approach is able to supply in one shot both the diffraction pattern related to the active atoms (through the OCCR loadings) and the time dependence of the system response (through the OCCR scores). Furthermore, when applied to real data, OCCR was able to supply only the latter information, as the former was hindered by changes in abundances of different crystal phases, which occurred besides structural variations in the specific case considered. In order to develop a decomposition procedure able to cope with this combined effect represents the next challenge in MED analysis.« less

Procrustean rotation in concert with principal component analysis of molecular dynamics trajectories: Quantifying global and local differences between conformational samples.

PubMed

Oblinsky, Daniel G; Vanschouwen, Bryan M B; Gordon, Heather L; Rothstein, Stuart M

2009-12-14

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the beta1 domain of protein G.

Procrustean rotation in concert with principal component analysis of molecular dynamics trajectories: Quantifying global and local differences between conformational samples

NASA Astrophysics Data System (ADS)

Oblinsky, Daniel G.; VanSchouwen, Bryan M. B.; Gordon, Heather L.; Rothstein, Stuart M.

2009-12-01

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the β1 domain of protein G.

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

PubMed Central

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

2015-01-01

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

Elemental Characterization and Discrimination of Nontoxic Ammunition Using Scanning Electron Microscopy with Energy Dispersive X-Ray Analysis and Principal Components Analysis.

PubMed

Hogg, Seth R; Hunter, Brian C; Waddell Smith, Ruth

2016-01-01

Concerns over the toxic by-products produced by traditional ammunition have led to an increase in popularity of nontoxic ammunition. In this work, the chemical composition of six brands of nontoxic ammunition was investigated and compared to that of a road flare, which served as an environmental source with similar composition. Five rounds of each brand were fired while a further five were disassembled and the primer alone was fired. Particles collected from all samples, including the road flare, were analyzed by scanning electron microscopy with energy dispersive X-ray analysis. Common elements among the different ammunition brands included aluminum, potassium, silicon, calcium, and strontium. Spectra were then subjected to principal components analysis in which association of the primer to the intact ammunition sample was generally possible, with distinction among brands and from the road flare sample. Further, PCA loadings plots indicated the elements responsible for the association and discrimination observed. © 2015 American Academy of Forensic Sciences.

Raman chemical mapping of magnesium stearate delivered by a punch-face lubrication system on the surface of placebo and active tablets.

PubMed

Šašiċ, Slobodan; Ojakovo, Peter; Warman, Martin; Sanghvi, Tapan

2013-09-01

Raman chemical mapping was used to determine the distribution of magnesium stearate, a lubricant, on the surface of tablets. The lubrication was carried out via a punch-face lubrication system with different spraying rates applied on placebo and active-containing tablets. Principal component analysis was used for decomposing the matrix of Raman mapping spectra. Some of the loadings associated with minuscule variation in the data significantly overlap with the Raman spectrum of magnesium stearate in placebo tablets and allow for imaging the domains of magnesium stearate via corresponding scores. Despite the negligible variation accounted for by respective principal components, the score images seem reliable as demonstrated through thresholding the one-dimensional representation and the spectra of the hot pixels that show a weak but perceivable magnesium stearate band at 1295 cm(-1). The same approach was applied on the active formulation, but no magnesium stearate was identified, presumably due to overwhelming concentration and spectral contribution of the active pharmaceutical ingredient.

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

PubMed

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

2015-10-09

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

Statistical Inference for Porous Materials using Persistent Homology.

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

Moon, Chul; Heath, Jason E.; Mitchell, Scott A.

2017-12-01

We propose a porous materials analysis pipeline using persistent homology. We rst compute persistent homology of binarized 3D images of sampled material subvolumes. For each image we compute sets of homology intervals, which are represented as summary graphics called persistence diagrams. We convert persistence diagrams into image vectors in order to analyze the similarity of the homology of the material images using the mature tools for image analysis. Each image is treated as a vector and we compute its principal components to extract features. We t a statistical model using the loadings of principal components to estimate material porosity, permeability,more » anisotropy, and tortuosity. We also propose an adaptive version of the structural similarity index (SSIM), a similarity metric for images, as a measure to determine the statistical representative elementary volumes (sREV) for persistence homology. Thus we provide a capability for making a statistical inference of the uid ow and transport properties of porous materials based on their geometry and connectivity.« less

Is Allelopathic Activity of Ipomoea murucoides Induced by Xylophage Damage?

PubMed

Flores-Palacios, Alejandro; Corona-López, Angélica María; Rios, María Yolanda; Aguilar-Guadarrama, Berenice; Toledo-Hernández, Víctor Hugo; Rodríguez-López, Verónica; Valencia-Díaz, Susana

2015-01-01

Herbivory activates the synthesis of allelochemicals that can mediate plant-plant interactions. There is an inverse relationship between the activity of xylophages and the abundance of epiphytes on Ipomoea murucoides. Xylophagy may modify the branch chemical constitution, which also affects the liberation of allelochemicals with defense and allelopathic properties. We evaluated the bark chemical content and the effect of extracts from branches subjected to treatments of exclusion, mechanical damage and the presence/absence of epiphytes, on the seed germination of the epiphyte Tillandsia recurvata. Principal component analysis showed that branches without any treatment separate from branches subjected to treatments; damaged and excluded branches had similar chemical content but we found no evidence to relate intentional damage with allelopathy; however 1-hexadecanol, a defense volatile compound correlated positively with principal component (PC) 1. The chemical constitution of branches subject to exclusion plus damage or plus epiphytes was similar among them. PC2 indicated that palmitic acid (allelopathic compound) and squalene, a triterpene that attracts herbivore enemies, correlated positively with the inhibition of seed germination of T. recurvata. Inhibition of seed germination of T. recurvata was mainly correlated with the increment of palmitic acid and this compound reached higher concentrations in excluded branches treatments. Then, it is likely that the allelopathic response of I. murucoides would increase to the damage (shade, load) that may be caused by a high load of epiphytes than to damage caused by the xylophages.

Nonlinear response of unidirectional boron/aluminum

NASA Technical Reports Server (NTRS)

Pindera, M.-J.; Herakovich, C. T.; Becker, W.; Aboudi, J.

1990-01-01

Experimental results obtained for unidirectional boron/aluminum subjected to combined loading using off-axis tension, compression and Iosipescu shear specimens are correlated with a nonlinear micromechanics model. It is illustrated that the nonlinear response in the principal material directions is markedly influenced by the different loading modes and different ratios of the applied stress components. The observed nonlinear response under pure and combined loading is discussed in terms of initial yielding, subsequent hardening, stress-interaction effects and unloading-reloading characteristics. The micromechanics model is based on the concept of a repeating unit cell representative of the composite-at-large and employs the unified theory of Bodner and Partom to model the inelastic response of the matrix. It is shown that the employed micromechanics model is sufficiently general to predict the observed nonlinear response of unidirectional boron/aluminum with good accuracy.

The association between weight, height, and head circumference reconsidered.

PubMed

Scheffler, Christiane; Greil, Holle; Hermanussen, Michael

2017-05-01

Under normal nutritional and health conditions, body height, weight and head circumference are significantly related. We hypothesize that the apparent general association between weight, height, and head circumference of the growing child might be misleading. We reanalyzed data of 7,444 boys and 7,375 girls measured in East-Germany between 1986 and 1990, aged from 0 to 7 y with measurements of body length/height, leg length, sitting height, biacromial shoulder breadth, thoracic breadth, thoracic depth, thoracic circumference, body weight, head volume, percentage of body fat, and hip skinfold vertical, using principal component analysis. Strong associations exist between skeletal growth, fat accumulation, and head volume increments. Yet in spite of this general proportionality, skeletal growth, fat acquisition, and head growth exhibit different patterns. Three components explain between almost 60% and more than 75% of cumulative variance between birth and age 7 y. Parameters of skeletal growth predominantly load on the first component and clearly separate from indicators of fat deposition. After age of 2 y, head volume loads on a separate third component in both sexes indicating independence of head growth. Under appropriate nutritional and health circumstances, nutritional status, body size, and head circumference are not related.

Asian and European American cultural values and communication styles among Asian American and European American college students.

PubMed

Park, Yong S; Kim, Bryan S K

2008-01-01

The present study examined the relationships between adherence to Asian and European cultural values and communication styles among 210 Asian American and 136 European American college students. A principal components analysis revealed that, for both Asian Americans and European Americans, the contentious, dramatic, precise, and open styles loaded onto the first component suggesting low context communication, and interpersonal sensitivity and inferring meaning styles loaded onto the second component suggesting high context communication. Higher adherence to emotional self-control and lower adherence to European American values explained Asian Americans' higher use of the indirect communication, while higher emotional self-control explained why Asian Americans use a less open communication style than their European American counterparts. When differences between sex and race were controlled, adherence to humility was inversely related to contentious and dramatic communication styles but directly related to inferring meaning style, adherence to European American values was positively associated with precise communication and inferring meaning styles, and collectivism was positively related to interpersonal sensitivity style. 2008 APA

Multivariate patterns of biochemical responses of Pinus ponderosa trees at field plots in the San Bernardino Mountains, southern California.

PubMed

Tausz, M; Bytnerowicz, A; Arbaugh, M J; Wonisch, A; Grill, D

2001-03-01

Most environmental stress conditions promote the production of potentially toxic active oxygen species in plant cells. Plants respond with changes in their antioxidant and photoprotective systems. Antioxidants and pigments have been widely used to measure these responses. Because trees are exposed to multiple man-made and natural stresses, their responses are not reflected by changes in single stress markers, but by complex biochemical changes. To evaluate such response patterns, explorative multivariate statistics have been used. In the present study, 12 biochemical variables (chloroplast pigments, state of the xanthophyll cycle, alpha-tocopherol, ascorbate and dehydroascorbate, glutathione and oxidized glutathione) were measured in previous-year needles of field-grown Pinus ponderosa Dougl. ex Laws. The trees were sampled in two consecutive years in the San Bernardino Mountains in southern California, where a pollution gradient is overlaid by gradients in natural stresses (drought, altitude). To explore irradiance effects, needle samples were taken directly in the field (sun exposed) and from detached, dark-adapted branches. A principal component analysis on this data set (n = 80) resulted in four components (Components 1-4) that explained 67% of the variance in the original data. Component 1 was positively loaded by concentrations of alpha-tocopherol, total ascorbate and xanthophyll cycle pools, as well as by the proportion of de-epoxides in the xanthophyll cycle. It was negatively loaded by the proportion of dehydroascorbate in the ascorbate pool. Component 2 was negatively loaded by chlorophyll concentrations, and positively loaded by the ratios of lutein and beta-carotene to chlorophyll and by the de-epoxidation state of the xanthophyll cycle. Component 3 was negatively loaded by GSH concentrations and positively loaded by the proportions of GSSG and tocopherol concentrations. Component 4 was positively loaded by neoxanthin and negatively loaded by beta-carotene. The four components could be assigned to the concerted action of the biochemical protection system: high scores on Component 1 represent highly activated antioxidative defense, changes in pigment composition are represented in Components 2 and 4, and the glutathione system, which is important for antioxidant regeneration, is represented in Component 2. Although Component 1 scores were generally higher (indicating activation of antioxidant defense) in light-adapted needles relative to dark-adapted needles, they were also site dependent with increased scores at sites with less pollution, but higher natural stress impacts. High scores of Components 2 and 3 at the highest elevation site, which was only moderately polluted, indicated an increase in photoprotection by pigments and activation of the glutathione system. Significant differences between light- and dark-adapted needles in Components 2 and 3 were only found at the site with the highest pollution. Use of accumulated variables (components) instead of single biochemical variables enabled recognition of response patterns at particular sites and a better comparison with results of other studies is expected. Typical response patterns could be assigned to particular environmental stress combinations, providing a means of assessing potential biological risks within individual forest stands.

Discrimination of a chestnut-oak forest unit for geologic mapping by means of a principal component enhancement of Landsat multispectral scanner data.

USGS Publications Warehouse

Krohn, M.D.; Milton, N.M.; Segal, D.; Enland, A.

1981-01-01

A principal component image enhancement has been effective in applying Landsat data to geologic mapping in a heavily forested area of E Virginia. The image enhancement procedure consists of a principal component transformation, a histogram normalization, and the inverse principal componnet transformation. The enhancement preserves the independence of the principal components, yet produces a more readily interpretable image than does a single principal component transformation. -from Authors

Relationships between the Definition of the Hyperplane Width to the Fidelity of Principal Component Loading Patterns.

NASA Astrophysics Data System (ADS)

Richman, Michael B.; Gong, Xiaofeng

1999-06-01

When applying eigenanalysis, one decision analysts make is the determination of what magnitude an eigenvector coefficient (e.g., principal component (PC) loading) must achieve to be considered as physically important. Such coefficients can be displayed on maps or in a time series or tables to gain a fuller understanding of a large array of multivariate data. Previously, such a decision on what value of loading designates a useful signal (hereafter called the loading `cutoff') for each eigenvector has been purely subjective. The importance of selecting such a cutoff is apparent since those loading elements in the range of zero to the cutoff are ignored in the interpretation and naming of PCs since only the absolute values of loadings greater than the cutoff are physically analyzed. This research sets out to objectify the problem of best identifying the cutoff by application of matching between known correlation/covariance structures and their corresponding eigenpatterns, as this cutoff point (known as the hyperplane width) is varied.A Monte Carlo framework is used to resample at five sample sizes. Fourteen different hyperplane cutoff widths are tested, bootstrap resampled 50 times to obtain stable results. The key findings are that the location of an optimal hyperplane cutoff width (one which maximized the information content match between the eigenvector and the parent dispersion matrix from which it was derived) is a well-behaved unimodal function. On an individual eigenvector, this enables the unique determination of a hyperplane cutoff value to be used to separate those loadings that best reflect the relationships from those that do not. The effects of sample size on the matching accuracy are dramatic as the values for all solutions (i.e., unrotated, rotated) rose steadily from 25 through 250 observations and then weakly thereafter. The specific matching coefficients are useful to assess the penalties incurred when one analyzes eigenvector coefficients of a lower absolute value than the cutoff (termed coefficient in the hyperplane) or, alternatively, chooses not to analyze coefficients that contain useful physical signal outside of the hyperplane. Therefore, this study enables the analyst to make the best use of the information available in their PCs to shed light on complicated data structures.

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy

PubMed Central

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-01-01

Abstract This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were “present neck pain intensity,” “fear avoidance,” and “anxiety.” The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables “present neck pain intensity,” “fear avoidance,” and “anxiety” had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy. PMID:26091482

Dimensions Underlying Measures of Disability, Personal Factors, and Health Status in Cervical Radiculopathy: A Cross-Sectional Study.

PubMed

Halvorsen, Marie; Kierkegaard, Marie; Harms-Ringdahl, Karin; Peolsson, Anneli; Dedering, Åsa

2015-06-01

This cross-sectional study sought to identify dimensions underlying measures of impairment, disability, personal factors, and health status in patients with cervical radiculopathy. One hundred twenty-four patients with magnetic resonance imaging-verified cervical radiculopathy, attending a neurosurgery clinic in Sweden, participated. Data from clinical tests and questionnaires on disability, personal factors, and health status were used in a principal-component analysis (PCA) with oblique rotation. The PCA supported a 3-component model including 14 variables from clinical tests and questionnaires, accounting for 73% of the cumulative percentage. The first component, pain and disability, explained 56%. The second component, health, fear-avoidance beliefs, kinesiophobia, and self-efficacy, explained 9.2%. The third component including anxiety, depression, and catastrophizing explained 7.6%. The strongest-loading variables of each dimension were "present neck pain intensity," "fear avoidance," and "anxiety." The three underlying dimensions identified and labeled Pain and functioning, Health, beliefs, and kinesiophobia, and Mood state and catastrophizing captured aspects of importance for cervical radiculopathy. Since the variables "present neck pain intensity," "fear avoidance," and "anxiety" had the strongest loading in each of the three dimensions; it may be important to include them in a reduced multidimensional measurement set in cervical radiculopathy.

Principal component regression analysis with SPSS.

PubMed

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

Phenotypic Characterization and Multivariate Analysis to Explain Body Conformation in Lesser Known Buffalo (Bubalus bubalis) from North India

PubMed Central

Vohra, V.; Niranjan, S. K.; Mishra, A. K.; Jamuna, V.; Chopra, A.; Sharma, Neelesh; Jeong, Dong Kee

2015-01-01

Phenotypic characterization and body biometric in 13 traits (height at withers, body length, chest girth, paunch girth, ear length, tail length, length of tail up to switch, face length, face width, horn length, circumference of horn at base, distances between pin bone and hip bone) were recorded in 233 adult Gojri buffaloes from Punjab and Himachal Pradesh states of India. Traits were analysed by using varimax rotated principal component analysis (PCA) with Kaiser Normalization to explain body conformation. PCA revealed four components which explained about 70.9% of the total variation. First component described the general body conformation and explained 31.5% of total variation. It was represented by significant positive high loading of height at wither, body length, heart girth, face length and face width. The communality ranged from 0.83 (hip bone distance) to 0.45 (horn length) and unique factors ranged from 0.16 to 0.55 for all these 13 different biometric traits. Present study suggests that first principal component can be used in the evaluation and comparison of body conformation in buffaloes and thus provides an opportunity to distinguish between early and late maturing to adult, based on a small group of biometric traits to explain body conformation in adult buffaloes. PMID:25656215

Specialists Meeting on Helicopter Design Mission Load Spectra

DTIC Science & Technology

1976-08-01

partement Scientifique AEROSPATIAI*E - B.P n0 13 13 722 -AINN 1I INTRODUCTION Si 1e princips g~ndral de d~tarmination des dur~ea de vie des pibcea d’h...reprdsentatives de l’utilisation h 6valuer un certain nombro do jauges.extensom~triques. Coa jauges , placgos sur chacun des 4ldmonte critiquos au point do Vuo...sensitivity. 1. INTRODUCTION The design of the fatigue critical components of a helicopter, which are mainly the blades, the hub, and the drive system

Functional connectivity among multi-channel EEGs when working memory load reaches the capacity.

PubMed

Zhang, Dan; Zhao, Huipo; Bai, Wenwen; Tian, Xin

2016-01-15

Evidence from behavioral studies has suggested a capacity existed in working memory. As the concept of functional connectivity has been introduced into neuroscience research in the recent years, the aim of this study is to investigate the functional connectivity in the brain when working memory load reaches the capacity. 32-channel electroencephalographs (EEGs) were recorded for 16 healthy subjects, while they performed a visual working memory task with load 1-6. Individual working memory capacity was calculated according to behavioral results. Short-time Fourier transform was used to determine the principal frequency band (theta band) related to working memory. The functional connectivity among EEGs was measured by the directed transform function (DTF) via spectral Granger causal analysis. The capacity was 4 calculated from the behavioral results. The power was focused in the frontal midline region. The strongest connectivity strengths of EEG theta components from load 1 to 6 distributed in the frontal midline region. The curve of DTF values vs load numbers showed that DTF increased from load 1 to 4, peaked at load 4, then decreased after load 4. This study finds that the functional connectivity between EEGs, described quantitatively by DTF, became less strong when working memory load exceeded the capacity. Copyright © 2015 Elsevier B.V. All rights reserved.

Effect of elasticity on stress distribution in CAD/CAM dental crowns: Glass ceramic vs. polymer-matrix composite.

PubMed

Duan, Yuanyuan; Griggs, Jason A

2015-06-01

Further investigations are required to evaluate the mechanical behaviour of newly developed polymer-matrix composite (PMC) blocks for computer-aided design/computer-aided manufacturing (CAD/CAM) applications. The purpose of this study was to investigate the effect of elasticity on the stress distribution in dental crowns made of glass-ceramic and PMC materials using finite element (FE) analysis. Elastic constants of two materials were determined by ultrasonic pulse velocity using an acoustic thickness gauge. Three-dimensional solid models of a full-coverage dental crown on a first mandibular molar were generated based on X-ray micro-CT scanning images. A variety of load case-material property combinations were simulated and conducted using FE analysis. The first principal stress distribution in the crown and luting agent was plotted and analyzed. The glass-ceramic crown had stress concentrations on the occlusal surface surrounding the area of loading and the cemented surface underneath the area of loading, while the PMC crown had only stress concentration on the occlusal surface. The PMC crown had lower maximum stress than the glass-ceramic crown in all load cases, but this difference was not substantial when the loading had a lateral component. Eccentric loading did not substantially increase the maximum stress in the prosthesis. Both materials are resistant to fracture with physiological occlusal load. The PMC crown had lower maximum stress than the glass-ceramic crown, but the effect of a lateral loading component was more pronounced for a PMC crown than for a glass-ceramic crown. Knowledge of the stress distribution in dental crowns with low modulus of elasticity will aid clinicians in planning treatments that include such restorations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Behavioral effects of bidirectional selection for behavior towards human in virgin and lactate Norway rats.

PubMed

Konoshenko, Maria Yu; Plyusnina, Irina Z

2012-06-01

Although numerous studies have demonstrated strong differences in behavioral, hormonal and neurobiological characteristics between male rats selected for elimination (tame) and enhancement (aggressive) of aggressiveness towards humans, few studies have examined changes in female behavior under this selection. The objective of the current work was to evaluate the effects of bidirectional selection for aggressiveness towards humans on behavioral profiles of virgin and lactating rats compared with the behavior in tame, aggressive and unselected (wild-type) females. The behavior of virgin females was studied using the light-dark box, the startle response test and the modified glove test. Tame females were less anxious and more tolerant towards humans than unselected and aggressive rats. Principal component analysis of all behavioral parameters produced three independent factors, explaining 66.37% of the total variability. The measures of behavior towards humans and the measures of anxiety mainly loaded on PC1 (first principal component) which separated the tame females from the unselected and aggressive ones. These data suggest the genetic correlation between the selected behavior towards humans and anxiety-related behavior in virgin rats. No significant effect of line was found for PC2 scores, associated with risk assessment behavior. Measurements of freezing behavior mainly loaded on PC3, and this component separated rats of different genetic groups from each other. The behavior of lactating rats was studied in maternal defense and pup retrieval tests. Females of selected lines did not significantly differ in behavioral measurements of these tests and were characterized by higher maternal motivation than unselected rats. It is suggested that long-term breeding of tame and aggressive rats in captivity has reduced the threshold for maternal behavior. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

Use of principal components analysis and protein microarray to explore the association of HIV-1-specific IgG responses with disease progression.

PubMed

Gerns Storey, Helen L; Richardson, Barbra A; Singa, Benson; Naulikha, Jackie; Prindle, Vivian C; Diaz-Ochoa, Vladimir E; Felgner, Phil L; Camerini, David; Horton, Helen; John-Stewart, Grace; Walson, Judd L

2014-01-01

The role of HIV-1-specific antibody responses in HIV disease progression is complex and would benefit from analysis techniques that examine clusterings of responses. Protein microarray platforms facilitate the simultaneous evaluation of numerous protein-specific antibody responses, though excessive data are cumbersome in analyses. Principal components analysis (PCA) reduces data dimensionality by generating fewer composite variables that maximally account for variance in a dataset. To identify clusters of antibody responses involved in disease control, we investigated the association of HIV-1-specific antibody responses by protein microarray, and assessed their association with disease progression using PCA in a nested cohort design. Associations observed among collections of antibody responses paralleled protein-specific responses. At baseline, greater antibody responses to the transmembrane glycoprotein (TM) and reverse transcriptase (RT) were associated with higher viral loads, while responses to the surface glycoprotein (SU), capsid (CA), matrix (MA), and integrase (IN) proteins were associated with lower viral loads. Over 12 months greater antibody responses were associated with smaller decreases in CD4 count (CA, MA, IN), and reduced likelihood of disease progression (CA, IN). PCA and protein microarray analyses highlighted a collection of HIV-specific antibody responses that together were associated with reduced disease progression, and may not have been identified by examining individual antibody responses. This technique may be useful to explore multifaceted host-disease interactions, such as HIV coinfections.

Asymmetric ground reaction forces and knee kinematics during squat after anterior cruciate ligament (ACL) reconstruction.

PubMed

Sanford, Brooke A; Williams, John L; Zucker-Levin, Audrey; Mihalko, William M

2016-10-01

This bilateral squat study tests whether people with anterior cruciate ligament (ACL) reconstruction have symmetric three-dimensional ground reaction forces (GRFs) and symmetric anterior-posterior (AP) translation rates of the femur with respect to the tibia when compared with healthy control subjects. We hypothesized that there would be no long-term asymmetry in knee kinematics and kinetics in ACL reconstructed subjects following surgery and rehabilitation. Position and GRF data were collected on eight ACL reconstructed and eight control subjects during bilateral squat. The rate of relative AP translation was determined for each subject. Principal component models were developed for each of the three GRF waveforms. Principal component scores were used to assess symmetry within the ACL reconstructed group and within the control group. ACL reconstructed knees analyzed in early flexion during squat descent displayed a four-fold greater rate of change in anterior translation in the reconstructed knee relative to the contralateral side than did a similar comparison of normal knees. Differences were found between the ACL reconstructed subjects' injured and uninjured limbs for all GRFs. Subjects following ACL reconstruction had asymmetric GRFs and relative rates of AP translation at an average of seven years after ACL reconstructive surgery when compared with control subjects. These alterations in loading may lead to altered load distributions across the knee joint and may put some subjects at risk for future complications such as osteoarthritis. Copyright © 2015 Elsevier B.V. All rights reserved.

Is Allelopathic Activity of Ipomoea murucoides Induced by Xylophage Damage?

PubMed Central

Flores-Palacios, Alejandro; Corona-López, Angélica María; Rios, María Yolanda; Aguilar-Guadarrama, Berenice; Toledo-Hernández, Víctor Hugo; Rodríguez-López, Verónica; Valencia-Díaz, Susana

2015-01-01

Herbivory activates the synthesis of allelochemicals that can mediate plant-plant interactions. There is an inverse relationship between the activity of xylophages and the abundance of epiphytes on Ipomoea murucoides. Xylophagy may modify the branch chemical constitution, which also affects the liberation of allelochemicals with defense and allelopathic properties. We evaluated the bark chemical content and the effect of extracts from branches subjected to treatments of exclusion, mechanical damage and the presence/absence of epiphytes, on the seed germination of the epiphyte Tillandsia recurvata. Principal component analysis showed that branches without any treatment separate from branches subjected to treatments; damaged and excluded branches had similar chemical content but we found no evidence to relate intentional damage with allelopathy; however 1-hexadecanol, a defense volatile compound correlated positively with principal component (PC) 1. The chemical constitution of branches subject to exclusion plus damage or plus epiphytes was similar among them. PC2 indicated that palmitic acid (allelopathic compound) and squalene, a triterpene that attracts herbivore enemies, correlated positively with the inhibition of seed germination of T. recurvata. Inhibition of seed germination of T. recurvata was mainly correlated with the increment of palmitic acid and this compound reached higher concentrations in excluded branches treatments. Then, it is likely that the allelopathic response of I. murucoides would increase to the damage (shade, load) that may be caused by a high load of epiphytes than to damage caused by the xylophages. PMID:26625350

Discrimination of various paper types using diffuse reflectance ultraviolet-visible near-infrared (UV-Vis-NIR) spectroscopy: forensic application to questioned documents.

PubMed

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2015-06-01

Diffuse reflectance ultraviolet-visible-near-infrared (UV-Vis-NIR) spectroscopy is applied as a means of differentiating various types of writing, office, and photocopy papers (collected from stationery shops in India) on the basis of reflectance and absorbance spectra that otherwise seem to be almost alike in different illumination conditions. In order to minimize bias, spectra from both sides of paper were obtained. In addition, three spectra from three different locations (from one side) were recorded covering the upper, middle, and bottom portions of the paper sample, and the mean average reflectivity of both the sides was calculated. A significant difference was observed in mean average reflectivity of Side A and Side B of the paper using Student's pair >t-test. Three different approaches were used for discrimination: (1) qualitative features of the whole set of samples, (2) principal component analysis, and (3) a combination of both approaches. On the basis of the first approach, i.e., qualitative features, 96.49% discriminating power (DP) was observed, which shows highly significant results with the UV-Vis-NIR technique. In the second approach the discriminating power is further enhanced by incorporating the principal component analysis (PCA) statistical method, where this method describes each UV-Vis spectrum in a group through numerical loading values connected to the first few principal components. All components described 100% variance of the samples, but only the first three PCs are good enough to explain the variance (PC1 = 51.64%, PC2 = 47.52%, and PC3 = 0.54%) of the samples; i.e., the first three PCs described 99.70% of the data, whereas in the third approach, the four samples, C, G, K, and N, out of a total 19 samples, which were not differentiated using qualitative features (approach no. 1), were therefore subjected to PCA. The first two PCs described 99.37% of the spectral features. The discrimination was achieved by using a loading plot between PC1 and PC2. It is therefore concluded that maximum discrimination of writing, office, and photocopy paper could be achieved on the basis of the second approach. Hence, the present inexpensive analytical method can be appropriate for application to routine questioned document examination work in forensic laboratories because it provides nondestructive, quantitative, reliable, and repeatable results.

On the Fallibility of Principal Components in Research

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.; Li, Tenglong

2017-01-01

The measurement error in principal components extracted from a set of fallible measures is discussed and evaluated. It is shown that as long as one or more measures in a given set of observed variables contains error of measurement, so also does any principal component obtained from the set. The error variance in any principal component is shown…

Retention System and Splinting on Morse Taper Implants in the Posterior Maxilla by 3D Finite Element Analysis.

PubMed

Lemos, Cleidiel Aparecido Araujo; Verri, Fellippo Ramos; Santiago, Joel Ferreira; Almeida, Daniel Augusto de Faria; Batista, Victor Eduardo de Souza; Noritomi, Pedro Yoshito; Pellizzer, Duardo Piza

2018-01-01

The purpose of this study was to evaluate different retention systems (cement- or screw-retained) and crown designs (non-splinted or splinted) of fixed implant-supported restorations, in terms of stress distributions in implants/components and bone tissue, by 3-dimensional (3D) finite element analysis. Four 3D models were simulated with the InVesalius, Rhinoceros 3D, and SolidWorks programs. Models were made of type III bone from the posterior maxillary area. Models included three 4.0-mm-diameter Morse taper (MT) implants with different lengths, which supported metal-ceramic crowns. Models were processed by the Femap and NeiNastran programs, using an axial force of 400 N and oblique force of 200 N. Results were visualized as the von Mises stress and maximum principal stress (σmax). Under axial loading, there was no difference in the distribution of stress in implants/components between retention systems and splinted crowns; however, in oblique loading, cemented prostheses showed better stress distribution than screwed prostheses, whereas splinted crowns tended to reduce stress in the implant of the first molar. In the bone tissue cemented prostheses showed better stress distribution in bone tissue than screwed prostheses under axial and oblique loading. The splinted design only had an effect in the screwed prosthesis, with no influence in the cemented prosthesis. Cemented prostheses on MT implants showed more favorable stress distributions in implants/components and bone tissue. Splinting was favorable for stress distribution only for screwed prostheses under oblique loading.

The development of summary components for the Disablement in the Physically Active scale in collegiate athletes.

PubMed

Houston, Megan N; Hoch, Johanna M; Van Lunen, Bonnie L; Hoch, Matthew C

2015-11-01

The Disablement in the Physically Active scale (DPA) is a generic patient-reported outcome designed to evaluate constructs of disability in physically active populations. The purpose of this study was to analyze the DPA scale structure for summary components. Four hundred and fifty-six collegiate athletes completed a demographic form and the DPA. A principal component analysis (PCA) was conducted with oblique rotation. Factors with eigenvalues >1 that explained >5 % of the variance were retained. The PCA revealed a two-factor structure consistent with paradigms used to develop the original DPA. Items 1-12 loaded on Factors 1 and Items 13-16 loaded on Factor 2. Items 1-12 pertain to impairment, activity limitations, and participation restrictions. Items 13-16 address psychosocial and emotional well-being. Consideration of item content suggested Factor 1 concerned physical function, while Factor 2 concerned mental well-being. Thus, items clustered around Factor 1 and 2 were identified as physical (DPA-PSC) and mental (DPA-MSC) summary components, respectively. Together, the factors accounted for 65.1 % of the variance. The PCA revealed a two-factor structure for the DPA that resulted in DPA-PSC and DPA-MSC. Analyzing the DPA as separate constructs may provide distinct information that could help to prescribe treatment and rehabilitation strategies.

Validation of the National Aeronautics and Space Administration Task Load Index as a tool to evaluate the learning curve for endoscopy training.

PubMed

Mohamed, Rachid; Raman, Maitreyi; Anderson, John; McLaughlin, Kevin; Rostom, Alaa; Coderre, Sylvain

2014-03-01

Although workplace workload assessments exist in different fields, an endoscopy-specific workload assessment tool is lacking. To validate such a workload tool and use it to map the progression of novice trainees in gastroenterology in performing their first endoscopies. The National Aeronautics and Space Administration Task Load Index (NASA-TLX) workload assessment tool was completed by eight novice trainees in gastroenterology and 10 practicing gastroenterologists⁄surgeons. An exploratory factor analysis was performed to construct a streamlined endoscopy-specific task load index, which was subsequently validated. The 'Endoscopy Task Load Index' was used to monitor progression of trainee exertion and self-assessed performance over their first 40 procedures. From the factor analysis of the NASA-TLX, two principal components emerged: a measure of exertion and a measure of self-efficacy. These items became the components of the newly validated Endoscopy Task Load Index. There was a steady decline in self-perceived exertion over the training period, which was more rapid for gastroscopy than colonoscopy. The self-efficacy scores for gastroscopy rapidly increased over the first few procedures, reaching a plateau after this period of time. For colonoscopy, there was a progressive increase in reported self-efficacy over the first three quartiles of procedures, followed by a drop in self-efficacy scores over the final quartile. The present study validated an Endoscopy Task Load Index that can be completed in <1 min. Practical implications of such a tool in endoscopy education include identifying periods of higher perceived exertion among novice endoscopists, facilitating appropriate levels of guidance from trainers.

Long-Term Monitoring of Fresco Paintings in the Cathedral of Valencia (Spain) Through Humidity and Temperature Sensors in Various Locations for Preventive Conservation

PubMed Central

Zarzo, Manuel; Fernández-Navajas, Angel; García-Diego, Fernando-Juan

2011-01-01

We describe the performance of a microclimate monitoring system that was implemented for the preventive conservation of the Renaissance frescoes in the apse vault of the Cathedral of Valencia, that were restored in 2006. This system comprises 29 relative humidity (RH) and temperature sensors: 10 of them inserted into the plaster layer supporting the fresco paintings, 10 sensors in the walls close to the frescoes and nine sensors measuring the indoor microclimate at different points of the vault. Principal component analysis was applied to RH data recorded in 2007. The analysis was repeated with data collected in 2008 and 2010. The resulting loading plots revealed that the similarities and dissimilarities among sensors were approximately maintained along the three years. A physical interpretation was provided for the first and second principal components. Interestingly, sensors recording the highest RH values correspond to zones where humidity problems are causing formation of efflorescence. Recorded data of RH and temperature are discussed according to Italian Standard UNI 10829 (1999). PMID:22164100

Multivariate analysis of mixed contaminants (PAHs and heavy metals) at manufactured gas plant site soils.

PubMed

Thavamani, Palanisami; Megharaj, Mallavarapu; Naidu, Ravi

2012-06-01

Principal component analysis (PCA) was used to provide an overview of the distribution pattern of polycyclic aromatic hydrocarbons (PAHs) and heavy metals in former manufactured gas plant (MGP) site soils. PCA is the powerful multivariate method to identify the patterns in data and expressing their similarities and differences. Ten PAHs (naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]pyrene) and four toxic heavy metals - lead (Pb), cadmium (Cd), chromium (Cr) and zinc (Zn) - were detected in the site soils. PAH contamination was contributed equally by both low and high molecular weight PAHs. PCA was performed using the varimax rotation method in SPSS, 17.0. Two principal components accounting for 91.7% of the total variance was retained using scree test. Principle component 1 (PC1) substantially explained the dominance of PAH contamination in the MGP site soils. All PAHs, except anthracene, were positively correlated in PC1. There was a common thread in high molecular weight PAHs loadings, where the loadings were inversely proportional to the hydrophobicity and molecular weight of individual PAHs. Anthracene, which was less correlated with other individual PAHs, deviated well from the origin which can be ascribed to its lower toxicity and different origin than its isomer phenanthrene. Among the four major heavy metals studied in MGP sites, Pb, Cd and Cr were negatively correlated in PC1 but showed strong positive correlation in principle component 2 (PC2). Although metals may not have originated directly from gaswork processes, the correlation between PAHs and metals suggests that the materials used in these sites may have contributed to high concentrations of Pb, Cd, Cr and Zn. Thus, multivariate analysis helped to identify the sources of PAHs, heavy metals and their association in MGP site, and thereby better characterise the site risk, which would not be possible if one uses chemical analysis alone.

Food patterns and dietary quality associated with organic food consumption during pregnancy; data from a large cohort of pregnant women in Norway.

PubMed

Torjusen, Hanne; Lieblein, Geir; Næs, Tormod; Haugen, Margaretha; Meltzer, Helle Margrete; Brantsæter, Anne Lise

2012-08-06

Little is known about the consumption of organic food during pregnancy. The aim of this study was to describe dietary characteristics associated with frequent consumption of organic food among pregnant women participating in the Norwegian Mother and Child Cohort Study (MoBa). The present study includes 63 808 women who during the years 2002-2007 answered two questionnaires, a general health questionnaire at gestational weeks 15 and a food frequency questionnaire at weeks 17-22. The exploration of food patterns by Principal component analyses (PCA) was followed by ANOVA analyses investigating how these food patterns as well as intake of selected food groups were associated with consumption of organic food. The first principal component (PC1) identified by PCA, accounting for 12% of the variation, was interpreted as a 'health and sustainability component', with high positive loadings for vegetables, fruit and berries, cooking oil, whole grain bread and cereal products and negative loadings for meat, including processed meat, white bread, and cakes and sweets. Frequent consumption of organic food, which was reported among 9.1% of participants (n = 5786), was associated with increased scores on the 'health and sustainability component' (p < 0.001). The increase in score represented approximately 1/10 of the total variation and was independent of sociodemographic and lifestyle characteristics. Participants with frequent consumption of organic food had a diet with higher density of fiber and most nutrients such as folate, beta-carotene and vitamin C, and lower density of sodium compared to participants with no or low organic consumption. The present study showed that pregnant Norwegian women reporting frequent consumption of organically produced food had dietary pattern and quality more in line with public advice for healthy and sustainable diets. A methodological implication is that the overall diet needs to be included in future studies of potential health outcomes related to consumption of organic food during pregnancy.

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.

Capturing multidimensionality in stroke aphasia: mapping principal behavioural components to neural structures

PubMed Central

Butler, Rebecca A.

2014-01-01

Stroke aphasia is a multidimensional disorder in which patient profiles reflect variation along multiple behavioural continua. We present a novel approach to separating the principal aspects of chronic aphasic performance and isolating their neural bases. Principal components analysis was used to extract core factors underlying performance of 31 participants with chronic stroke aphasia on a large, detailed battery of behavioural assessments. The rotated principle components analysis revealed three key factors, which we labelled as phonology, semantic and executive/cognition on the basis of the common elements in the tests that loaded most strongly on each component. The phonology factor explained the most variance, followed by the semantic factor and then the executive-cognition factor. The use of principle components analysis rendered participants’ scores on these three factors orthogonal and therefore ideal for use as simultaneous continuous predictors in a voxel-based correlational methodology analysis of high resolution structural scans. Phonological processing ability was uniquely related to left posterior perisylvian regions including Heschl’s gyrus, posterior middle and superior temporal gyri and superior temporal sulcus, as well as the white matter underlying the posterior superior temporal gyrus. The semantic factor was uniquely related to left anterior middle temporal gyrus and the underlying temporal stem. The executive-cognition factor was not correlated selectively with the structural integrity of any particular region, as might be expected in light of the widely-distributed and multi-functional nature of the regions that support executive functions. The identified phonological and semantic areas align well with those highlighted by other methodologies such as functional neuroimaging and neurostimulation. The use of principle components analysis allowed us to characterize the neural bases of participants’ behavioural performance more robustly and selectively than the use of raw assessment scores or diagnostic classifications because principle components analysis extracts statistically unique, orthogonal behavioural components of interest. As such, in addition to improving our understanding of lesion–symptom mapping in stroke aphasia, the same approach could be used to clarify brain–behaviour relationships in other neurological disorders. PMID:25348632

Enhancing links between visual short term memory, visual attention and cognitive control processes through practice: An electrophysiological insight.

PubMed

Fuggetta, Giorgio; Duke, Philip A

2017-05-01

The operation of attention on visible objects involves a sequence of cognitive processes. The current study firstly aimed to elucidate the effects of practice on neural mechanisms underlying attentional processes as measured with both behavioural and electrophysiological measures. Secondly, it aimed to identify any pattern in the relationship between Event-Related Potential (ERP) components which play a role in the operation of attention in vision. Twenty-seven participants took part in two recording sessions one week apart, performing an experimental paradigm which combined a match-to-sample task with a memory-guided efficient visual-search task within one trial sequence. Overall, practice decreased behavioural response times, increased accuracy, and modulated several ERP components that represent cognitive and neural processing stages. This neuromodulation through practice was also associated with an enhanced link between behavioural measures and ERP components and with an enhanced cortico-cortical interaction of functionally interconnected ERP components. Principal component analysis (PCA) of the ERP amplitude data revealed three components, having different rostro-caudal topographic representations. The first component included both the centro-parietal and parieto-occipital mismatch triggered negativity - involved in integration of visual representations of the target with current task-relevant representations stored in visual working memory - loaded with second negative posterior-bilateral (N2pb) component, involved in categorising specific pop-out target features. The second component comprised the amplitude of bilateral anterior P2 - related to detection of a specific pop-out feature - loaded with bilateral anterior N2, related to detection of conflicting features, and fronto-central mismatch triggered negativity. The third component included the parieto-occipital N1 - related to early neural responses to the stimulus array - which loaded with the second negative posterior-contralateral (N2pc) component, mediating the process of orienting and focusing covert attention on peripheral target features. We discussed these three components as representing different neurocognitive systems modulated with practice within which the input selection process operates. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

A predictive model of human performance.

NASA Technical Reports Server (NTRS)

Walters, R. F.; Carlson, L. D.

1971-01-01

An attempt is made to develop a model describing the overall responses of humans to exercise and environmental stresses for prediction of exhaustion vs an individual's physical characteristics. The principal components of the model are a steady state description of circulation and a dynamic description of thermal regulation. The circulatory portion of the system accepts changes in work load and oxygen pressure, while the thermal portion is influenced by external factors of ambient temperature, humidity and air movement, affecting skin blood flow. The operation of the model is discussed and its structural details are given.

Chemometric techniques on the analysis of Raman spectra of serum blood samples of breast cancer patients

NASA Astrophysics Data System (ADS)

Rocha-Osornio, L. N.; Pichardo-Molina, J. L.; Barbosa-Garcia, O.; Frausto-Reyes, C.; Araujo-Andrade, C.; Huerta-Franco, R.; Gutiérrez-Juárez, G.

2008-02-01

Raman spectroscopy and Multivariate methods were used to study serum blood samples of control and breast cancer patients. Blood samples were obtained from 11 patients and 12 controls from the central region of Mexico. Our results show that principal component analysis is able to discriminate serum sample of breast cancer patients from those of control group, also the loading vectors of PCA plotted as a function of Raman shift shown which bands permitted to make the maximum discrimination between both groups of samples.

Principal component analysis of cardiovascular risk traits in three generations cohort among Indian Punjabi population.

PubMed

Badaruddoza; Kumar, Raman; Kaur, Manpreet

2015-09-01

The current study focused to determine significant cardiovascular risk factors through principal component factor analysis (PCFA) among three generations on 1827 individuals in three generations including 911 males (378 from offspring, 439 from parental and 94 from grand-parental generations) and 916 females (261 from offspring, 515 from parental and 140 from grandparental generations). The study performed PCFA with orthogonal rotation to reduce 12 inter-correlated variables into groups of independent factors. The factors have been identified as 2 for male grandparents, 3 for male offspring, female parents and female grandparents each, 4 for male parents and 5 for female offspring. This data reduction method identified these factors that explained 72%, 84%, 79%, 69%, 70% and 73% for male and female offspring, male and female parents and male and female grandparents respectively, of the variations in original quantitative traits. The factor 1 accounting for the largest portion of variations was strongly loaded with factors related to obesity (body mass index (BMI), waist circumference (WC), waist to hip ratio (WHR), and thickness of skinfolds) among all generations with both sexes, which has been known to be an independent predictor for cardiovascular morbidity and mortality. The second largest components, factor 2 and factor 3 for almost all generations reflected traits of blood pressure phenotypes loaded, however, in male offspring generation it was observed that factor 2 was loaded with blood pressure phenotypes as well as obesity. This study not only confirmed but also extended prior work by developing a cumulative risk scale from factor scores. Till today, such a cumulative and extensive scale has not been used in any Indian studies with individuals of three generations. These findings and study highlight the importance of global approach for assessing the risk and need for studies that elucidate how these different cardiovascular risk factors interact with each other over the time to create clinical disease. The findings also added depth to the negligible amount of literature of factor analysis of cardiovascular risk in any Indian ethnic population.

A simplified soil extraction sequence to monitor the main and trace element speciation in soil after compost and mineral fertilizer additions upon the composition of wheat grains

NASA Astrophysics Data System (ADS)

Sager, Manfred; Erhart, Eva

2016-04-01

High quality biological waste treatment aims at producing compost in order to maintain a clean environment and to sustain soil organic carbon levels. Fertilization with compost as a source of organic carbon, nutrients, and accessory elements, as well as fertilization with mineral N- and PK fertilizer have been tested in a field experiment on a calcaric Fluvisol in the Danube wetlands, at 4 levels each. Yields of wheat were recorded, and grains and soils were sampled from each treatment, and analyzed for main and trace element composition. The corresponding soils were characterized by mobile phases, obtained by leaching with 0,16M acetic acid to cover exchangeables plus carbonates, and subsequently by 0,1M oxalate buffer pH 3 to dissolve the pedogenic oxides. Total amounts were obtained from digests with perchloric- nitric-hydrofluoric acid. For quasi-total amounts, aqua regia was replaced by pressure decomposition with KClO3 in dilute nitric acid. The proposed extraction sequence permits to analyze and interpret soil for main elements, trace elements, nutrients and anions simultaneously. Factor analyses of soil extracts obtained from dilute acetic acid revealed Ba-Be-Cd-Cu-Li-S (traces), Ca-Mg-Mn (main carbonates), Al-Fe-B, Y, and P-K (nutrients) as chemically feasible principal components. Subsequent soil extracts from oxalate contained Al-B-Co-K-Na-Pb-Si-V-S (maybe acid silicate weathering), Cr-Li-Ni-Sr-Ti (maybe basic silicate weathering), Be-Cu-Fe-P, Co-Mg-Mn-Zn (Mn-oxides) and Ba-Sc as principal components. Factor analyses of total element data distinguished the principal components Ce-La-Li-Sc-Y-P (rare earths), Al-Ca-Fe-K-Mg-Na-P (main elements), Cd-Co-Cr-Cu-Ni-Zn (trace elements), As-Pb (contaminants), Ba-Mn-Sr, and Ti, which looks chemically feasible also. Factor analyses of those soil fractions which presumably form the main fractions of exchangeables, carbonates, pedogenic oxides and silicates, showed no cross connections, except for P. Oxalate-soluble Fe together with P and S was independent from oxalate-soluble Al-Mn-Si. In the crops, all element levels were within a non-contaminated and non-deficient range, therefore correlations with concentrations as well as loads in the wheat grains where largely not pronounced. Maximum correlations between plant and soil data were obtained with Li and Be. The load data (concentration times yield, given in g/ha) were much more intercorrelated than the concentrations. Regarding the same element, correlation coefficients between loads and respective concentrations were larger than 0,800 for Al, Ba, Cd, Co, Cr, Li, Mo, Na, Ni, Se, and Sr, which means the transfer remained independent from the load. In case of Ca, Mg, P, S, Zn, however, correlation coefficients between loads and concentrations were < 0,500, thus the transfer was not constant because of obvious metabolic influences. The proposed method of soil characterization was applied at a field trial here for the first time, and offers new possibilities of intercorrelations between plant uptake and geochemical soil fractions.

Discrimination of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics.

PubMed

Maurer, Christian; Federolf, Peter; von Tscharner, Vinzenz; Stirling, Lisa; Nigg, Benno M

2012-05-01

Changes in gait kinematics have often been analyzed using pattern recognition methods such as principal component analysis (PCA). It is usually just the first few principal components that are analyzed, because they describe the main variability within a dataset and thus represent the main movement patterns. However, while subtle changes in gait pattern (for instance, due to different footwear) may not change main movement patterns, they may affect movements represented by higher principal components. This study was designed to test two hypotheses: (1) speed and gender differences can be observed in the first principal components, and (2) small interventions such as changing footwear change the gait characteristics of higher principal components. Kinematic changes due to different running conditions (speed - 3.1m/s and 4.9 m/s, gender, and footwear - control shoe and adidas MicroBounce shoe) were investigated by applying PCA and support vector machine (SVM) to a full-body reflective marker setup. Differences in speed changed the basic movement pattern, as was reflected by a change in the time-dependent coefficient derived from the first principal. Gender was differentiated by using the time-dependent coefficient derived from intermediate principal components. (Intermediate principal components are characterized by limb rotations of the thigh and shank.) Different shoe conditions were identified in higher principal components. This study showed that different interventions can be analyzed using a full-body kinematic approach. Within the well-defined vector space spanned by the data of all subjects, higher principal components should also be considered because these components show the differences that result from small interventions such as footwear changes. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

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.

Numerical assessment of bone remodeling around conventionally and early loaded titanium and titanium-zirconium alloy dental implants.

PubMed

Akça, Kıvanç; Eser, Atılım; Çavuşoğlu, Yeliz; Sağırkaya, Elçin; Çehreli, Murat Cavit

2015-05-01

The aim of this study was to investigate conventionally and early loaded titanium and titanium-zirconium alloy implants by three-dimensional finite element stress analysis. Three-dimensional model of a dental implant was created and a thread area was established as a region of interest in trabecular bone to study a localized part of the global model with a refined mesh. The peri-implant tissues around conventionally loaded (model 1) and early loaded (model 2) implants were implemented and were used to explore principal stresses, displacement values, and equivalent strains in the peri-implant region of titanium and titanium-zirconium implants under static load of 300 N with or without 30° inclination applied on top of the abutment surface. Under axial loading, principal stresses in both models were comparable for both implants and models. Under oblique loading, principal stresses around titanium-zirconium implants were slightly higher in both models. Comparable stress magnitudes were observed in both models. The displacement values and equivalent strain amplitudes around both implants and models were similar. Peri-implant bone around titanium and titanium-zirconium implants experiences similar stress magnitudes coupled with intraosseous implant displacement values under conventional loading and early loading simulations. Titanium-zirconium implants have biomechanical outcome comparable to conventional titanium implants under conventional loading and early loading.

Principal Component Relaxation Mode Analysis of an All-Atom Molecular Dynamics Simulation of Human Lysozyme

NASA Astrophysics Data System (ADS)

Nagai, Toshiki; Mitsutake, Ayori; Takano, Hiroshi

2013-02-01

A new relaxation mode analysis method, which is referred to as the principal component relaxation mode analysis method, has been proposed to handle a large number of degrees of freedom of protein systems. In this method, principal component analysis is carried out first and then relaxation mode analysis is applied to a small number of principal components with large fluctuations. To reduce the contribution of fast relaxation modes in these principal components efficiently, we have also proposed a relaxation mode analysis method using multiple evolution times. The principal component relaxation mode analysis method using two evolution times has been applied to an all-atom molecular dynamics simulation of human lysozyme in aqueous solution. Slow relaxation modes and corresponding relaxation times have been appropriately estimated, demonstrating that the method is applicable to protein systems.

Ideal orthodontic alignment load relationships based on periodontal ligament stress.

PubMed

Viecilli, R F; Burstone, C J

2015-04-01

To test the hypothesis that periodontal ligament (PDL) stress relationships that yield resistance numbers representing load proportions between different teeth depend on alignment load type. Finite element models of all teeth, except the third molars, were produced. Four different types of loads were applied, and the third principal stresses of different teeth in standardized areas of most compression were calculated. Based on these results, resistance numbers, representing the load proportions for each tooth derived from PDL stress, were determined. The third principal stress values for typical alignment loads in the areas of most stress were very different for different load types for each tooth. Differences in resistance numbers between teeth also varied with different loads. Resistance numbers, that is, load proportion numbers between teeth to achieve similar stress at the compressive PDL zone, depend on the type of applied load. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Functional principal component analysis of glomerular filtration rate curves after kidney transplant.

PubMed

Dong, Jianghu J; Wang, Liangliang; Gill, Jagbir; Cao, Jiguo

2017-01-01

This article is motivated by some longitudinal clinical data of kidney transplant recipients, where kidney function progression is recorded as the estimated glomerular filtration rates at multiple time points post kidney transplantation. We propose to use the functional principal component analysis method to explore the major source of variations of glomerular filtration rate curves. We find that the estimated functional principal component scores can be used to cluster glomerular filtration rate curves. Ordering functional principal component scores can detect abnormal glomerular filtration rate curves. Finally, functional principal component analysis can effectively estimate missing glomerular filtration rate values and predict future glomerular filtration rate values.

Nutrients removal and substrate enzyme activities in vertical subsurface flow constructed wetlands for mariculture wastewater treatment: Effects of ammonia nitrogen loading rates and salinity levels.

PubMed

Li, Meng; Liang, Zhenlin; Callier, Myriam D; Roque d'orbcastel, Emmanuelle; Sun, Guoxiang; Ma, Xiaona; Li, Xian; Wang, Shunkui; Liu, Ying; Song, Xiefa

2018-06-01

This study aims to investigate the effects of ammonia nitrogen loading rates and salinity levels on nutrients removal rates and substrate enzyme activities of constructed wetland (CW) microcosms planted with Salicornia bigelovii treating mariculture wastewater. Activities of urease (UA), dehydrogenase (DA), protease (PrA) and phosphatase (PA) were considered. Using principal component analysis (PCA), nutrient removal index (NRI) and enzyme activity index (EAI) were developed to evaluate the effects. The results revealed that increasing ammonia nitrogen loading rates had positive effects on nitrogen removal rates (i.e. NH 4 -N and DIN) and enhanced substrate enzyme activities. Compared with low salinity (i.e. 15 and 22), high salinity levels (i.e. 29 and 36) enhanced nutrients removal rates, DA and UA, but weaken PA and PrA. In conclusion, CW microcosms with Salicornia bigelovii can be used for the removal of nutrients under a range of ammonia nitrogen loadings and high salinity levels. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Relation between Factor Score Estimates, Image Scores, and Principal Component Scores

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

Investigates the relation between factor score estimates, principal component scores, and image scores. The three methods compared are maximum likelihood factor analysis, principal component analysis, and a variant of rescaled image analysis. (RC)

The Butterflies of Principal Components: A Case of Ultrafine-Grained Polyphase Units

NASA Astrophysics Data System (ADS)

Rietmeijer, F. J. M.

1996-03-01

Dusts in the accretion regions of chondritic interplanetary dust particles [IDPs] consisted of three principal components: carbonaceous units [CUs], carbon-bearing chondritic units [GUs] and carbon-free silicate units [PUs]. Among others, differences among chondritic IDP morphologies and variable bulk C/Si ratios reflect variable mixtures of principal components. The spherical shapes of the initially amorphous principal components remain visible in many chondritic porous IDPs but fusion was documented for CUs, GUs and PUs. The PUs occur as coarse- and ultrafine-grained units that include so called GEMS. Spherical principal components preserved in an IDP as recognisable textural units have unique proporties with important implications for their petrological evolution from pre-accretion processing to protoplanet alteration and dynamic pyrometamorphism. Throughout their lifetime the units behaved as closed-systems without chemical exchange with other units. This behaviour is reflected in their mineralogies while the bulk compositions of principal components define the environments wherein they were formed.

Validation of the National Aeronautics and Space Administration Task Load Index as a tool to evaluate-the learning curve for endoscopy training

PubMed Central

Mohamed, Rachid; Raman, Maitreyi; Anderson, John; McLaughlin, Kevin; Rostom, Alaa; Coderre, Sylvain

2014-01-01

BACKGROUND: Although workplace workload assessments exist in different fields, an endoscopy-specific workload assessment tool is lacking. OBJECTIVE: To validate such a workload tool and use it to map the progression of novice trainees in gastroenterology in performing their first endoscopies. METHODS: The National Aeronautics and Space Administration Task Load Index (NASA-TLX) workload assessment tool was completed by eight novice trainees in gastroenterology and 10 practicing gastroenterologists/surgeons. An exploratory factor analysis was performed to construct a streamlined endoscopy-specific task load index, which was subsequently validated. The ‘Endoscopy Task Load Index’ was used to monitor progression of trainee exertion and self-assessed performance over their first 40 procedures. RESULTS: From the factor analysis of the NASA-TLX, two principal components emerged: a measure of exertion and a measure of self-efficacy. These items became the components of the newly validated Endoscopy Task Load Index. There was a steady decline in self-perceived exertion over the training period, which was more rapid for gastroscopy than colonoscopy. The self-efficacy scores for gastroscopy rapidly increased over the first few procedures, reaching a plateau after this period of time. For colonoscopy, there was a progressive increase in reported self-efficacy over the first three quartiles of procedures, followed by a drop in self-efficacy scores over the final quartile. DISCUSSION: The present study validated an Endoscopy Task Load Index that can be completed in <1 min. Practical implications of such a tool in endoscopy education include identifying periods of higher perceived exertion among novice endoscopists, facilitating appropriate levels of guidance from trainers. PMID:24619638

Tracing anthropogenic inputs to production in the Seto Inland Sea, Japan--a stable isotope approach.

PubMed

Miller, Todd W; Omori, Koji; Hamaoka, Hideki; Shibata, Jun-ya; Hidejiro, Onishi

2010-10-01

The Seto Inland Sea (SIS) receives waste runoff from ∼24% of Japan's total population, yet it is also important in regional fisheries, recreation and commerce. During August 2006 we measured carbon and nitrogen stable isotopes of particulate organic matter (POM) and zooplankton across urban population gradients of the SIS. Results showed a consistent trend of increasing δ(15)N in POM and zooplankton from the western to eastern subsystems of the SIS, corresponding to increasing population load. Principal components analysis of environmental variables indicated high positive loadings of δ(15)N and δ(13)C with high chlorophyll-a and surface water temperatures, and negative loadings of low salinities related to inputs from large rivers and high urban development in the eastern SIS. Anthropogenic nitrogen was therefore readily integrated into the SIS food web from primary production to copepods, which are a critical food source for many commercially important fishes. Copyright © 2010 Elsevier Ltd. All rights reserved.

Strength determination of brittle materials as curved monolithic structures.

PubMed

Hooi, P; Addison, O; Fleming, G J P

2014-04-01

The dental literature is replete with "crunch the crown" monotonic load-to-failure studies of all-ceramic materials despite fracture behavior being dominated by the indenter contact surface. Load-to-failure data provide no information on stress patterns, and comparisons among studies are impossible owing to variable testing protocols. We investigated the influence of nonplanar geometries on the maximum principal stress of curved discs tested in biaxial flexure in the absence of analytical solutions. Radii of curvature analogous to elements of complex dental geometries and a finite element analysis method were integrated with experimental testing as a surrogate solution to calculate the maximum principal stress at failure. We employed soda-lime glass discs, a planar control (group P, n = 20), with curvature applied to the remaining discs by slump forming to different radii of curvature (30, 20, 15, and 10 mm; groups R30-R10). The mean deflection (group P) and radii of curvature obtained on slumping (groups R30-R10) were determined by profilometry before and after annealing and surface treatment protocols. Finite element analysis used the biaxial flexure load-to-failure data to determine the maximum principal stress at failure. Mean maximum principal stresses and load to failure were analyzed with one-way analyses of variance and post hoc Tukey tests (α = 0.05). The measured radii of curvature differed significantly among groups, and the radii of curvature were not influenced by annealing. Significant increases in the mean load to failure were observed as the radius of curvature was reduced. The maximum principal stress did not demonstrate sensitivity to radius of curvature. The findings highlight the sensitivity of failure load to specimen shape. The data also support the synergistic use of bespoke computational analysis with conventional mechanical testing and highlight a solution to complications with complex specimen geometries.

The influence of iliotibial band syndrome history on running biomechanics examined via principal components analysis.

PubMed

Foch, Eric; Milner, Clare E

2014-01-03

Iliotibial band syndrome (ITBS) is a common knee overuse injury among female runners. Atypical discrete trunk and lower extremity biomechanics during running may be associated with the etiology of ITBS. Examining discrete data points limits the interpretation of a waveform to a single value. Characterizing entire kinematic and kinetic waveforms may provide additional insight into biomechanical factors associated with ITBS. Therefore, the purpose of this cross-sectional investigation was to determine whether female runners with previous ITBS exhibited differences in kinematics and kinetics compared to controls using a principal components analysis (PCA) approach. Forty participants comprised two groups: previous ITBS and controls. Principal component scores were retained for the first three principal components and were analyzed using independent t-tests. The retained principal components accounted for 93-99% of the total variance within each waveform. Runners with previous ITBS exhibited low principal component one scores for frontal plane hip angle. Principal component one accounted for the overall magnitude in hip adduction which indicated that runners with previous ITBS assumed less hip adduction throughout stance. No differences in the remaining retained principal component scores for the waveforms were detected among groups. A smaller hip adduction angle throughout the stance phase of running may be a compensatory strategy to limit iliotibial band strain. This running strategy may have persisted after ITBS symptoms subsided. © 2013 Published by Elsevier Ltd.

Principal component-based weighted indices and a framework to evaluate indices: Results from the Medical Expenditure Panel Survey 1996 to 2011

PubMed Central

Wu, Chao-Jung

2017-01-01

Producing indices composed of multiple input variables has been embedded in some data processing and analytical methods. We aim to test the feasibility of creating data-driven indices by aggregating input variables according to principal component analysis (PCA) loadings. To validate the significance of both the theory-based and data-driven indices, we propose principles to review innovative indices. We generated weighted indices with the variables obtained in the first years of the two-year panels in the Medical Expenditure Panel Survey initiated between 1996 and 2011. Variables were weighted according to PCA loadings and summed. The statistical significance and residual deviance of each index to predict mortality in the second years was extracted from the results of discrete-time survival analyses. There were 237,832 surviving the first years of panels, represented 4.5 billion civilians in the United States, of which 0.62% (95% CI = 0.58% to 0.66%) died in the second years of the panels. Of all 134,689 weighted indices, there were 40,803 significantly predicting mortality in the second years with or without the adjustment of age, sex and races. The significant indices in the both models could at most lead to 10,200 years of academic tenure for individual researchers publishing four indices per year or 618.2 years of publishing for journals with annual volume of 66 articles. In conclusion, if aggregating information based on PCA loadings, there can be a large number of significant innovative indices composing input variables of various predictive powers. To justify the large quantities of innovative indices, we propose a reporting and review framework for novel indices based on the objectives to create indices, variable weighting, related outcomes and database characteristics. The indices selected by this framework could lead to a new genre of publications focusing on meaningful aggregation of information. PMID:28886057

Preliminary evidence for validity of the Bahasa Indonesian version of Study Process Questionnaire.

PubMed

Liem, Arief Darmanegara; Prasetya, Paulus Hidajat

2007-02-01

This study provides preliminary evidence for the validity of the Bahasa Indonesian version of the Study Process Questionnaire (BI-SPQ) from a sample of 147 psychology students (22 men and 125 women; M age = 21.8 yr., SD = 1.3). The internal consistency alpha of the BI-SPQ subscales were found to range from .46 (Surface Strategy) to .77 (Deep Strategy), with a median of .67. Principal component analysis indicated a two-factor solution, where the Deep and Achieving subscales loaded onto Factor 1 and the Surface subscales loaded on Factor 2. Students' GPAs were associated negatively with Surface Motive (r = -.24) and were associated positively with Deep and Achieving Motives (rs = .20). Further studies with larger samples involving students majoring in other disciplines are needed to provide further evidence of the validity of the BI-SPQ.

Analysis and Modeling of Process of Residual Deformations Accumulation in Soils and Granular Materials

NASA Astrophysics Data System (ADS)

Aleksandrov, A. S.; Dolgih, G. V.; Kalinin, A. L.

2017-11-01

It is established that under the influence of repeated loads the process of plastic deformation in soils and discrete materials is hereditary. To perform the mathematical modeling of plastic deformation, the authors applied the integral equation by solution of which they manage to obtain the power and logarithmic dependencies connecting plastic deformation with the number of repeated loads, the parameters of the material and components of the stress tensor in the principal axes. It is shown that these dependences generalize a number of models proposed earlier in Russia and abroad. Based on the analysis of the experimental data obtained during material testing in the dynamic devices of triaxial compression at different values of the stress deviator, the coefficients in the proposed models of deformation are determined. The authors determined the application domain for logarithmic and degree dependences.

Fibrocartilage tissue engineering: the role of the stress environment on cell morphology and matrix expression.

PubMed

Thomopoulos, Stavros; Das, Rosalina; Birman, Victor; Smith, Lester; Ku, Katherine; Elson, Elliott L; Pryse, Kenneth M; Marquez, Juan Pablo; Genin, Guy M

2011-04-01

Although much is known about the effects of uniaxial mechanical loading on fibrocartilage development, the stress fields to which fibrocartilaginous regions are subjected to during development are mutiaxial. That fibrocartilage develops at tendon-to-bone attachments and in compressive regions of tendons is well established. However, the three-dimensional (3D) nature of the stresses needed for the development of fibrocartilage is not known. Here, we developed and applied an in vitro system to determine whether fibrocartilage can develop under a state of periodic hydrostatic tension in which only a single principal component of stress is compressive. This question is vital to efforts to mechanically guide morphogenesis and matrix expression in engineered tissue replacements. Mesenchymal stromal cells in a 3D culture were exposed to compressive and tensile stresses as a result of an external tensile hydrostatic stress field. The stress field was characterized through mechanical modeling. Tensile cyclic stresses promoted spindle-shaped cells, upregulation of scleraxis and type one collagen, and cell alignment with the direction of tension. Cells experiencing a single compressive stress component exhibited rounded cell morphology and random cell orientation. No difference in mRNA expression of the genes Sox9 and aggrecan was observed when comparing tensile and compressive regions unless the medium was supplemented with the chondrogenic factor transforming growth factor beta3. In that case, Sox9 was upregulated under static loading conditions and aggrecan was upregulated under cyclic loading conditions. In conclusion, the fibrous component of fibrocartilage could be generated using only mechanical cues, but generation of the cartilaginous component of fibrocartilage required biologic factors in addition to mechanical cues. These studies support the hypothesis that the 3D stress environment influences cell activity and gene expression in fibrocartilage development.

Fibrocartilage Tissue Engineering: The Role of the Stress Environment on Cell Morphology and Matrix Expression

PubMed Central

Das, Rosalina; Birman, Victor; Smith, Lester; Ku, Katherine; Elson, Elliott L.; Pryse, Kenneth M.; Marquez, Juan Pablo; Genin, Guy M.

2011-01-01

Although much is known about the effects of uniaxial mechanical loading on fibrocartilage development, the stress fields to which fibrocartilaginous regions are subjected to during development are mutiaxial. That fibrocartilage develops at tendon-to-bone attachments and in compressive regions of tendons is well established. However, the three-dimensional (3D) nature of the stresses needed for the development of fibrocartilage is not known. Here, we developed and applied an in vitro system to determine whether fibrocartilage can develop under a state of periodic hydrostatic tension in which only a single principal component of stress is compressive. This question is vital to efforts to mechanically guide morphogenesis and matrix expression in engineered tissue replacements. Mesenchymal stromal cells in a 3D culture were exposed to compressive and tensile stresses as a result of an external tensile hydrostatic stress field. The stress field was characterized through mechanical modeling. Tensile cyclic stresses promoted spindle-shaped cells, upregulation of scleraxis and type one collagen, and cell alignment with the direction of tension. Cells experiencing a single compressive stress component exhibited rounded cell morphology and random cell orientation. No difference in mRNA expression of the genes Sox9 and aggrecan was observed when comparing tensile and compressive regions unless the medium was supplemented with the chondrogenic factor transforming growth factor beta3. In that case, Sox9 was upregulated under static loading conditions and aggrecan was upregulated under cyclic loading conditions. In conclusion, the fibrous component of fibrocartilage could be generated using only mechanical cues, but generation of the cartilaginous component of fibrocartilage required biologic factors in addition to mechanical cues. These studies support the hypothesis that the 3D stress environment influences cell activity and gene expression in fibrocartilage development. PMID:21091338

Characterization and spacial distribution variability of chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary.

PubMed

Wang, Ying; Zhang, Di; Shen, Zhenyao; Chen, Jing; Feng, Chenghong

2014-01-01

The spatial characteristics and the quantity and quality of the chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary, based on the abundance, degree of humification and sources, were studied using 3D fluorescence excitation emission matrix spectra (F-EEMs) with parallel factor and principal component analysis (PARAFAC-PCA). The results indicated that the CDOM abundance decreased and the aromaticity increased from the upstream to the downstream areas of the estuary. Higher CDOM abundance and degrees of humification were observed in the pore water than that in the surface and bottom waters. Two humic-like components (C1 and C3) and one tryptophan-like component (C2) were identified using the PARAFAC model. The separation of the samples by PCA highlighted the differences in the DOM properties. Components C1 and C3 concurrently displayed positive factor 1 loadings with nearly zero factor 2 loadings, while C2 showed highly positive factor 2 loadings. The C1 and C3 were very similar and exhibited a direct relationship with A355 and DOC. The CDOM in the pore water increased along the river to the coastal area, which was mainly influenced by C1 and C3 and was significantly derived from sediment remineralization and deposition from the inflow of the Yangtze River. The CDOM in the surface and bottom waters was dominated by C2, especially in the inflows of multiple tributaries that were affected by intensive anthropogenic activities. The microbial degradation of exogenous wastes from the tributary inputs and shoreside discharges were dominant sources of the CDOM in the surface and bottom waters. Copyright © 2013 Elsevier Ltd. All rights reserved.

Wastewater-Based Epidemiology of Stimulant Drugs: Functional Data Analysis Compared to Traditional Statistical Methods.

PubMed

Salvatore, Stefania; Bramness, Jørgen Gustav; Reid, Malcolm J; Thomas, Kevin Victor; Harman, Christopher; Røislien, Jo

2015-01-01

Wastewater-based epidemiology (WBE) is a new methodology for estimating the drug load in a population. Simple summary statistics and specification tests have typically been used to analyze WBE data, comparing differences between weekday and weekend loads. Such standard statistical methods may, however, overlook important nuanced information in the data. In this study, we apply functional data analysis (FDA) to WBE data and compare the results to those obtained from more traditional summary measures. We analysed temporal WBE data from 42 European cities, using sewage samples collected daily for one week in March 2013. For each city, the main temporal features of two selected drugs were extracted using functional principal component (FPC) analysis, along with simpler measures such as the area under the curve (AUC). The individual cities' scores on each of the temporal FPCs were then used as outcome variables in multiple linear regression analysis with various city and country characteristics as predictors. The results were compared to those of functional analysis of variance (FANOVA). The three first FPCs explained more than 99% of the temporal variation. The first component (FPC1) represented the level of the drug load, while the second and third temporal components represented the level and the timing of a weekend peak. AUC was highly correlated with FPC1, but other temporal characteristic were not captured by the simple summary measures. FANOVA was less flexible than the FPCA-based regression, and even showed concordance results. Geographical location was the main predictor for the general level of the drug load. FDA of WBE data extracts more detailed information about drug load patterns during the week which are not identified by more traditional statistical methods. Results also suggest that regression based on FPC results is a valuable addition to FANOVA for estimating associations between temporal patterns and covariate information.

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.

Principal component analysis on molecular descriptors as an alternative point of view in the search of new Hsp90 inhibitors.

PubMed

Lauria, Antonino; Ippolito, Mario; Almerico, Anna Maria

2009-10-01

Inhibiting a protein that regulates multiple signal transduction pathways in cancer cells is an attractive goal for cancer therapy. Heat shock protein 90 (Hsp90) is one of the most promising molecular targets for such an approach. In fact, Hsp90 is a ubiquitous molecular chaperone protein that is involved in folding, activating and assembling of many key mediators of signal transduction, cellular growth, differentiation, stress-response and apoptothic pathways. With the aim to analyze which molecular descriptors have the higher importance in the binding interactions of these classes, we first performed molecular docking experiments on the 187 Hsp90 inhibitors included in the BindingDB, a public database of measured binding affinities. Further, for each frozen conformation obtained from the docking, a set of 250 molecular descriptors was calculated, and the resulting Structure/Descriptors matrix was submitted to Principal Component Analysis. From the factor scores it emerged a good clusterization among similar compounds both in terms of structural class and activity spectrum, while examination of the loadings of the first two factors also allowed to study the classes of descriptors which mainly contribute to each one.

Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

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

Eckert-Gallup, Aubrey C.; Sallaberry, Cédric J.; Dallman, Ann R.

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. These environmental contours are characterized by combinations of significant wave height (H s) and either energy period (T e) or peak period (T p) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is a standard design practice for generating environmentalmore » contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. As a result, these modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for determining design loads for marine structures.« less

Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

DOE PAGES

Eckert-Gallup, Aubrey C.; Sallaberry, Cédric J.; Dallman, Ann R.; ...

2016-01-06

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. These environmental contours are characterized by combinations of significant wave height (H s) and either energy period (T e) or peak period (T p) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is a standard design practice for generating environmentalmore » contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. As a result, these modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for determining design loads for marine structures.« less

Selective Detection of Target Volatile Organic Compounds in Contaminated Humid Air Using a Sensor Array with Principal Component Analysis

PubMed Central

Itoh, Toshio; Akamatsu, Takafumi; Tsuruta, Akihiro; Shin, Woosuck

2017-01-01

We investigated selective detection of the target volatile organic compounds (VOCs) nonanal, n-decane, and acetoin for lung cancer-related VOCs, and acetone and methyl i-butyl ketone for diabetes-related VOCs, in humid air with simulated VOC contamination (total concentration: 300 μg/m3). We used six “grain boundary-response type” sensors, including four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2), and two “bulk-response type” sensors, including Zr-doped CeO2 (CeZr10), i.e., eight sensors in total. We then analyzed their sensor signals using principal component analysis (PCA). Although the six “grain boundary-response type” sensors were found to be insufficient for selective detection of the target gases in humid air, the addition of two “bulk-response type” sensors improved the selectivity, even with simulated VOC contamination. To further improve the discrimination, we selected appropriate sensors from the eight sensors based on the PCA results. The selectivity to each target gas was maintained and was not affected by contamination. PMID:28753948

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

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

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging

NASA Astrophysics Data System (ADS)

Zhao, Yan-Ru; Yu, Ke-Qiang; Li, Xiaoli; He, Yong

2016-12-01

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

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.

In vivo quantitative evaluation of vascular parameters for angiogenesis based on sparse principal component analysis and aggregated boosted trees

NASA Astrophysics Data System (ADS)

Zhao, Fengjun; Liu, Junting; Qu, Xiaochao; Xu, Xianhui; Chen, Xueli; Yang, Xiang; Cao, Feng; Liang, Jimin; Tian, Jie

2014-12-01

To solve the multicollinearity issue and unequal contribution of vascular parameters for the quantification of angiogenesis, we developed a quantification evaluation method of vascular parameters for angiogenesis based on in vivo micro-CT imaging of hindlimb ischemic model mice. Taking vascular volume as the ground truth parameter, nine vascular parameters were first assembled into sparse principal components (PCs) to reduce the multicolinearity issue. Aggregated boosted trees (ABTs) were then employed to analyze the importance of vascular parameters for the quantification of angiogenesis via the loadings of sparse PCs. The results demonstrated that vascular volume was mainly characterized by vascular area, vascular junction, connectivity density, segment number and vascular length, which indicated they were the key vascular parameters for the quantification of angiogenesis. The proposed quantitative evaluation method was compared with both the ABTs directly using the nine vascular parameters and Pearson correlation, which were consistent. In contrast to the ABTs directly using the vascular parameters, the proposed method can select all the key vascular parameters simultaneously, because all the key vascular parameters were assembled into the sparse PCs with the highest relative importance.

Molecular Structure, Function, and Dynamics of Clathrin-Mediated Membrane Traffic

PubMed Central

Kirchhausen, Tom; Owen, David; Harrison, Stephen C.

2014-01-01

Clathrin is a molecular scaffold for vesicular uptake of cargo at the plasma membrane, where its assembly into cage-like lattices underlies the clathrin-coated pits of classical endocytosis. This review describes the structures of clathrin, major cargo adaptors, and other proteins that participate in forming a clathrin-coated pit, loading its contents, pinching off the membrane as a lattice-enclosed vesicle, and recycling the components. It integrates as much of the structural information as possible at the time of writing into a sketch of the principal steps in coated-pit and coated-vesicle formation. PMID:24789820

Spectral discrimination of serum from liver cancer and liver cirrhosis using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Yang, Tianyue; Li, Xiaozhou; Yu, Ting; Sun, Ruomin; Li, Siqi

2011-07-01

In this paper, Raman spectra of human serum were measured using Raman spectroscopy, then the spectra was analyzed by multivariate statistical methods of principal component analysis (PCA). Then linear discriminant analysis (LDA) was utilized to differentiate the loading score of different diseases as the diagnosing algorithm. Artificial neural network (ANN) was used for cross-validation. The diagnosis sensitivity and specificity by PCA-LDA are 88% and 79%, while that of the PCA-ANN are 89% and 95%. It can be seen that modern analyzing method is a useful tool for the analysis of serum spectra for diagnosing diseases.

The interrelationship of dopamine D2-like receptor availability in striatal and extrastriatal brain regions in healthy humans: A principal component analysis of [18F]Fallypride binding

PubMed Central

Zald, David H.; Woodward, Neil D.; Cowan, Ronald L.; Riccardi, Patrizia; Ansari, M. Sib; Baldwin, Ronald M.; Cowan, Ronald L.; Smith, Clarence E.; Hakyemez, Helene; Li, Rui; Kessler, Robert M.

2010-01-01

Individual differences in dopamine D2-like receptor availability arise across all brain regions expressing D2-like receptors. However, the inter-relationships in receptor availability across brain regions are poorly understood. To address this issue, we examined the relationship between D2-like binding potential (BPND) across striatal and extrastriatal regions in a sample of healthy participants. PET imaging was performed with the high affinity D2/D3 ligand [18F]fallypride in 45 participants. BPND images were submitted to voxel-wise principal components analysis to determine the pattern of associations across brain regions. Individual differences in D2-like BPND were explained by three distinguishable components. A single component explained almost all of the variance within the striatum, indicating that individual differences in receptor availability vary in a homogenous manner across the caudate, putamen, and ventral striatum. Cortical BPND was only modestly related to striatal BPND, and mostly loaded on a distinct component. After controlling for the general level of cortical D2-like BPND, an inverse relationship emerged between receptor availability in the striatum and the ventral temporal and ventromedial frontal cortices, suggesting possible cross-regulation of D2-like receptors in these regions. The analysis additionally revealed evidence of: 1) a distinct component involving the midbrain and limbic areas; 2) a dissociation between BPND in the medial and lateral temporal regions; and 3) a dissociation between BPND in the medial/midline and lateral thalamus. In summary, individual differences in D2-like receptor availability reflect several distinct patterns. This conclusion has significant implications for neuropsychiatric models that posit global or regionally specific relationships between dopaminergic tone and behavior. PMID:20149883

Nonlinear Principal Components Analysis: Introduction and Application

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Koojj, Anita J.

2007-01-01

The authors provide a didactic treatment of nonlinear (categorical) principal components analysis (PCA). This method is the nonlinear equivalent of standard PCA and reduces the observed variables to a number of uncorrelated principal components. The most important advantages of nonlinear over linear PCA are that it incorporates nominal and ordinal…

Selective principal component regression analysis of fluorescence hyperspectral image to assess aflatoxin contamination in corn

USDA-ARS?s Scientific Manuscript database

Selective principal component regression analysis (SPCR) uses a subset of the original image bands for principal component transformation and regression. For optimal band selection before the transformation, this paper used genetic algorithms (GA). In this case, the GA process used the regression co...

Similarities between principal components of protein dynamics and random diffusion

NASA Astrophysics Data System (ADS)

Hess, Berk

2000-12-01

Principal component analysis, also called essential dynamics, is a powerful tool for finding global, correlated motions in atomic simulations of macromolecules. It has become an established technique for analyzing molecular dynamics simulations of proteins. The first few principal components of simulations of large proteins often resemble cosines. We derive the principal components for high-dimensional random diffusion, which are almost perfect cosines. This resemblance between protein simulations and noise implies that for many proteins the time scales of current simulations are too short to obtain convergence of collective motions.

Directly Reconstructing Principal Components of Heterogeneous Particles from Cryo-EM Images

PubMed Central

Tagare, Hemant D.; Kucukelbir, Alp; Sigworth, Fred J.; Wang, Hongwei; Rao, Murali

2015-01-01

Structural heterogeneity of particles can be investigated by their three-dimensional principal components. This paper addresses the question of whether, and with what algorithm, the three-dimensional principal components can be directly recovered from cryo-EM images. The first part of the paper extends the Fourier slice theorem to covariance functions showing that the three-dimensional covariance, and hence the principal components, of a heterogeneous particle can indeed be recovered from two-dimensional cryo-EM images. The second part of the paper proposes a practical algorithm for reconstructing the principal components directly from cryo-EM images without the intermediate step of calculating covariances. This algorithm is based on maximizing the (posterior) likelihood using the Expectation-Maximization algorithm. The last part of the paper applies this algorithm to simulated data and to two real cryo-EM data sets: a data set of the 70S ribosome with and without Elongation Factor-G (EF-G), and a data set of the inluenza virus RNA dependent RNA Polymerase (RdRP). The first principal component of the 70S ribosome data set reveals the expected conformational changes of the ribosome as the EF-G binds and unbinds. The first principal component of the RdRP data set reveals a conformational change in the two dimers of the RdRP. PMID:26049077

Principal component analysis of Mn(salen) catalysts.

PubMed

Teixeira, Filipe; Mosquera, Ricardo A; Melo, André; Freire, Cristina; Cordeiro, M Natália D S

2014-12-14

The theoretical study of Mn(salen) catalysts has been traditionally performed under the assumption that Mn(acacen') (acacen' = 3,3'-(ethane-1,2-diylbis(azanylylidene))bis(prop-1-en-olate)) is an appropriate surrogate for the larger Mn(salen) complexes. In this work, the geometry and the electronic structure of several Mn(salen) and Mn(acacen') model complexes were studied using Density Functional Theory (DFT) at diverse levels of approximation, with the aim of understanding the effects of truncation, metal oxidation, axial coordination, substitution on the aromatic rings of the salen ligand and chirality of the diimine bridge, as well as the choice of the density functional and basis set. To achieve this goal, geometric and structural data, obtained from these calculations, were subjected to Principal Component Analysis (PCA) and PCA with orthogonal rotation of the components (rPCA). The results show the choice of basis set to be of paramount importance, accounting for up to 30% of the variance in the data, while the differences between salen and acacen' complexes account for about 9% of the variance in the data, and are mostly related to the conformation of the salen/acacen' ligand around the metal centre. Variations in the spin state and oxidation state of the metal centre also account for large fractions of the total variance (up to 10% and 9%, respectively). Other effects, such as the nature of the diimine bridge or the presence of an alkyl substituent in the 3,3 and 5,5 positions of the aldehyde moiety, were found to be less important in terms of explaining the variance within the data set. A matrix of discriminants was compiled using the loadings of the principal and rotated components that best performed in the classification of the entries in the data. The scores obtained from its application to the data set were used as independent variables for devising linear models of different properties, with satisfactory prediction capabilities.

Gaussian vs non-Gaussian turbulence: impact on wind turbine loads

NASA Astrophysics Data System (ADS)

Berg, J.; Mann, J.; Natarajan, A.; Patton, E. G.

2014-12-01

In wind energy applications the turbulent velocity field of the Atmospheric Boundary Layer (ABL) is often characterised by Gaussian probability density functions. When estimating the dynamical loads on wind turbines this has been the rule more than anything else. From numerous studies in the laboratory, in Direct Numerical Simulations, and from in-situ measurements of the ABL we know, however, that turbulence is not purely Gaussian: the smallest and fastest scales often exhibit extreme behaviour characterised by strong non-Gaussian statistics. In this contribution we want to investigate whether these non-Gaussian effects are important when determining wind turbine loads, and hence of utmost importance to the design criteria and lifetime of a wind turbine. We devise a method based on Principal Orthogonal Decomposition where non-Gaussian velocity fields generated by high-resolution pseudo-spectral Large-Eddy Simulation (LES) of the ABL are transformed so that they maintain the exact same second-order statistics including variations of the statistics with height, but are otherwise Gaussian. In that way we can investigate in isolation the question whether it is important for wind turbine loads to include non-Gaussian properties of atmospheric turbulence. As an illustration the Figure show both a non-Gaussian velocity field (left) from our LES, and its transformed Gaussian Counterpart (right). Whereas the horizontal velocity components (top) look close to identical, the vertical components (bottom) are not: the non-Gaussian case is much more fluid-like (like in a sketch by Michelangelo). The question is then: Does the wind turbine see this? Using the load simulation software HAWC2 with both the non-Gaussian and newly constructed Gaussian fields, respectively, we show that the Fatigue loads and most of the Extreme loads are unaltered when using non-Gaussian velocity fields. The turbine thus acts like a low-pass filter which average out the non-Gaussian behaviour on time scales close to and faster than the revolution time of the turbine. For a few of the Extreme load estimations there is, on the other hand, a tendency that non-Gaussian effects increase the overall dynamical load, and hence can be of importance in wind energy load estimations.

Partnering with patients using social media to develop a hypertension management instrument.

PubMed

Kear, Tamara; Harrington, Magdalena; Bhattacharya, Anand

2015-09-01

Hypertension is a lifelong condition; thus, long-term adherence to lifestyle modification, self-monitoring, and medication regimens remains a challenge for patients. The aim of this study was to develop a patient-reported hypertension instrument that measured attitudes, lifestyle behaviors, adherence, and barriers to hypertension management using patient-reported outcome data. The study was conducted using the Open Research Exchange software platform created by PatientsLikeMe. A total of 360 participants completed the psychometric phase of the study; incomplete responses were obtained from 147 patients, and 150 patients opted out. Principal component analysis with orthogonal (varimax) rotation was executed on a data set with all completed responses (N = 249) and applied to 43 items. Based on the review of the factor solution, eigenvalues, and item loadings, 16 items were eliminated and model with 29 items was tested. The process was repeated two more times until final model with 14 items was established. In interpreting the rotated factor pattern, an item was said to load on any given component if the factor loading was ≥0.40 for that component and was <0.40 for the other. In addition to the newly generated instrument, demographic and self-reported clinical characteristics of the study participants such as the type of prescribed hypertension medications, frequency of blood pressure monitoring, and comorbid conditions were examined. The Open Research Exchange platform allowed for ongoing input from patients through each stage of the 14-item instrument development. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

An Introductory Application of Principal Components to Cricket Data

ERIC Educational Resources Information Center

Manage, Ananda B. W.; Scariano, Stephen M.

2013-01-01

Principal Component Analysis is widely used in applied multivariate data analysis, and this article shows how to motivate student interest in this topic using cricket sports data. Here, principal component analysis is successfully used to rank the cricket batsmen and bowlers who played in the 2012 Indian Premier League (IPL) competition. In…

Least Principal Components Analysis (LPCA): An Alternative to Regression Analysis.

ERIC Educational Resources Information Center

Olson, Jeffery E.

Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…

Identifying apple surface defects using principal components analysis and artifical neural networks

USDA-ARS?s Scientific Manuscript database

Artificial neural networks and principal components were used to detect surface defects on apples in near-infrared images. Neural networks were trained and tested on sets of principal components derived from columns of pixels from images of apples acquired at two wavelengths (740 nm and 950 nm). I...

Effects of load and maintenance duration on the time course of information encoding and retrieval in working memory: from perceptual analysis to post-categorization processes.

PubMed

Pinal, Diego; Zurrón, Montserrat; Díaz, Fernando

2014-01-01

information encoding, maintenance, and retrieval; these are supported by brain activity in a network of frontal, parietal and temporal regions. Manipulation of WM load and duration of the maintenance period can modulate this activity. Although such modulations have been widely studied using the event-related potentials (ERP) technique, a precise description of the time course of brain activity during encoding and retrieval is still required. Here, we used this technique and principal component analysis to assess the time course of brain activity during encoding and retrieval in a delayed match to sample task. We also investigated the effects of memory load and duration of the maintenance period on ERP activity. Brain activity was similar during information encoding and retrieval and comprised six temporal factors, which closely matched the latency and scalp distribution of some ERP components: P1, N1, P2, N2, P300, and a slow wave. Changes in memory load modulated task performance and yielded variations in frontal lobe activation. Moreover, the P300 amplitude was smaller in the high than in the low load condition during encoding and retrieval. Conversely, the slow wave amplitude was higher in the high than in the low load condition during encoding, and the same was true for the N2 amplitude during retrieval. Thus, during encoding, memory load appears to modulate the processing resources for context updating and post-categorization processes, and during retrieval it modulates resources for stimulus classification and context updating. Besides, despite the lack of differences in task performance related to duration of the maintenance period, larger N2 amplitude and stronger activation of the left temporal lobe after long than after short maintenance periods were found during information retrieval. Thus, results regarding the duration of maintenance period were complex, and future work is required to test the time-based decay theory predictions.

Cognitive load imposed by knobology may adversely affect learners' perception of utility in using ultrasonography to learn physical examination skills, but not anatomy.

PubMed

Jamniczky, Heather A; McLaughlin, Kevin; Kaminska, Malgorzata E; Raman, Maitreyi; Somayaji, Ranjani; Wright, Bruce; Ma, Irene W Y

2015-01-01

Ultrasonography is increasingly used for teaching anatomy and physical examination skills but its effect on cognitive load is unknown. This study aimed to determine ultrasound's perceived utility for learning, and to investigate the effect of cognitive load on its perceived utility. Consenting first-year medical students (n = 137) completed ultrasound training that includes a didactic component and four ultrasound-guided anatomy and physical examination teaching sessions. Learners then completed a survey on comfort with physical examination techniques (three items; alpha = 0.77), perceived utility of ultrasound in learning (two items; alpha = 0.89), and cognitive load on ultrasound use [measured with a validated nine-point scale (10 items; alpha = 0.88)]. Learners found ultrasound useful for learning for both anatomy and physical examination (mean 4.2 ± 0.9 and 4.4 ± 0.8, respectively; where 1 = very useless and 5 = very useful). Principal components analysis on the cognitive load survey revealed two factors, "image interpretation" and "basic knobology," which accounted for 60.3% of total variance. Weighted factor scores were not associated with perceived utility in learning anatomy (beta = 0.01, P = 0.62 for "image interpretation" and beta = -0.04, P = 0.33 for "basic knobology"). However, factor score on "knobology" was inversely associated with perceived utility for learning physical examination (beta = -0.06; P = 0.03). While a basic introduction to ultrasound may suffice for teaching anatomy, more training may be required for teaching physical examination. Prior to teaching physical examination skills with ultrasonography, we recommend ensuring that learners have sufficient knobology skills. © 2014 American Association of Anatomists.

Finding Planets in K2: A New Method of Cleaning the Data

NASA Astrophysics Data System (ADS)

Currie, Miles; Mullally, Fergal; Thompson, Susan E.

2017-01-01

We present a new method of removing systematic flux variations from K2 light curves by employing a pixel-level principal component analysis (PCA). This method decomposes the light curves into its principal components (eigenvectors), each with an associated eigenvalue, the value of which is correlated to how much influence the basis vector has on the shape of the light curve. This method assumes that the most influential basis vectors will correspond to the unwanted systematic variations in the light curve produced by K2’s constant motion. We correct the raw light curve by automatically fitting and removing the strongest principal components. The strongest principal components generally correspond to the flux variations that result from the motion of the star in the field of view. Our primary method of calculating the strongest principal components to correct for in the raw light curve estimates the noise by measuring the scatter in the light curve after using an algorithm for Savitsy-Golay detrending, which computes the combined photometric precision value (SG-CDPP value) used in classic Kepler. We calculate this value after correcting the raw light curve for each element in a list of cumulative sums of principal components so that we have as many noise estimate values as there are principal components. We then take the derivative of the list of SG-CDPP values and take the number of principal components that correlates to the point at which the derivative effectively goes to zero. This is the optimal number of principal components to exclude from the refitting of the light curve. We find that a pixel-level PCA is sufficient for cleaning unwanted systematic and natural noise from K2’s light curves. We present preliminary results and a basic comparison to other methods of reducing the noise from the flux variations.

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

NASA Astrophysics Data System (ADS)

Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph; Johnson, Jennifer A.

2017-02-01

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]-[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracks in [O/Fe]-[Fe/H] unlike the observed bimodality (separate high-α and low-α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]-[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α-elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.

Multivariate analysis of selected metals in tannery effluents and related soil.

PubMed

Tariq, Saadia R; Shah, Munir H; Shaheen, N; Khalique, A; Manzoor, S; Jaffar, M

2005-06-30

Effluent and relevant soil samples from 38 tanning units housed in Kasur, Pakistan, were obtained for metal analysis by flame atomic absorption spectrophotometric method. The levels of 12 metals, Na, Ca, K, Mg, Fe, Mn, Cr, Co, Cd, Ni, Pb and Zn were determined in the two media. The data were evaluated towards metal distribution and metal-to-metal correlations. The study evidenced enhanced levels of Cr (391, 16.7 mg/L) and Na (25,519, 9369 mg/L) in tannery effluents and relevant soil samples, respectively. The effluent versus soil trace metal content relationship confirmed that the effluent Cr was strongly correlated with soil Cr. For metal source identification the techniques of principal component analysis, and cluster analysis were applied. The principal component analysis yielded two factors for effluents: factor 1 (49.6% variance) showed significant loading for Ca, Fe, Mn, Cr, Cd, Ni, Pb and Zn, referring to a tanning related source for these metals, and factor 2 (12.6% variance) with higher loadings of Na, K, Mg and Co, was associated with the processes during the skin/hide treatment. Similarly, two factors with a cumulative variance of 34.8% were obtained for soil samples: factor 1 manifested the contribution from Mg, Mn, Co, Cd, Ni and Pb, which though soil-based is basically effluent-derived, while factor 2 was found associated with Na, K, Ca, Cr and Zn which referred to a tannery-based source. The dendograms obtained from cluster analysis, also support the observed results. The study exhibits a gross pollution of soils with Cr at levels far exceeding the stipulated safe limit laid down for tannery effluents.

Inflow, Outflow, Yields, and Stellar Population Mixing in Chemical Evolution Models

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

Andrews, Brett H.; Weinberg, David H.; Schönrich, Ralph

Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the stellar initial mass function, the SN Ia delay time distribution, stellar yields, and stellar population mixing. Using flexCE, a flexible one-zone chemical evolution code, we investigate the effects of and trade-offs between parameters. Two critical parameters are SFE and the outflow mass-loading parameter, which shift the knee in [O/Fe]–[Fe/H] and the equilibrium abundances that the simulations asymptotically approach, respectively. One-zone models with simple star formation histories follow narrow tracksmore » in [O/Fe]–[Fe/H] unlike the observed bimodality (separate high- α and low- α sequences) in this plane. A mix of one-zone models with inflow timescale and outflow mass-loading parameter variations, motivated by the inside-out galaxy formation scenario with radial mixing, reproduces the two sequences better than a one-zone model with two infall epochs. We present [X/Fe]–[Fe/H] tracks for 20 elements assuming three different supernova yield models and find some significant discrepancies with solar neighborhood observations, especially for elements with strongly metallicity-dependent yields. We apply principal component abundance analysis to the simulations and existing data to reveal the main correlations among abundances and quantify their contributions to variation in abundance space. For the stellar population mixing scenario, the abundances of α -elements and elements with metallicity-dependent yields dominate the first and second principal components, respectively, and collectively explain 99% of the variance in the model. flexCE is a python package available at https://github.com/bretthandrews/flexCE.« less

Assessment of temporal and spatial water quality in international Gomishan Lagoon, Iran, using multivariate analysis.

PubMed

Basatnia, Nabee; Hossein, Seyed Abbas; Rodrigo-Comino, Jesús; Khaledian, Yones; Brevik, Eric C; Aitkenhead-Peterson, Jacqueline; Natesan, Usha

2018-04-29

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO 2 ), nitrate (NO 3 ), biological oxygen demand (BOD), phosphate (PO 4 ), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R 2 , RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.

Principal component analysis and hydrochemical facies characterization to evaluate groundwater quality in Varahi river basin, Karnataka state, India

NASA Astrophysics Data System (ADS)

Ravikumar, P.; Somashekar, R. K.

2017-05-01

The present study envisages the importance of graphical representations like Piper trilinear diagram and Chadha's plot, respectively to determine variation in hydrochemical facies and understand the evolution of hydrochemical processes in the Varahi river basin. The analytical values obtained from the groundwater samples when plotted on Piper's and Chadha's plots revealed that the alkaline earth metals (Ca2+, Mg2+) are significantly dominant over the alkalis (Na+, K+), and the strong acidic anions (Cl-, SO4 2-) dominant over the weak acidic anions (CO3 2-, HCO3 -). Further, Piper trilinear diagram classified 93.48 % of the samples from the study area under Ca2+-Mg2+-Cl--SO4 2- type and only 6.52 % samples under Ca2+-Mg2+-HCO3 - type. Interestingly, Chadha's plot also demonstrated the dominance of reverse ion exchange water having permanent hardness (viz., Ca-Mg-Cl type) in majority of the samples over recharging water with temporary hardness (i.e., Ca-Mg-HCO3 type). Thus, evaluation of hydrochemical facies from both the plots highlighted the contribution from the reverse ion exchange processes in controlling geochemistry of groundwater in the study area. Further, PCA analysis yielded four principal components (PC1, PC2, PC3 and PC4) with higher eigen values of 1.0 or more, accounting for 65.55, 10.17, 6.88 and 6.52 % of the total variance, respectively. Consequently, majority of the physico-chemical parameters (87.5 %) loaded under PC1 and PC2 were having strong positive loading (>0.75) and these are mainly responsible for regulating the hydrochemistry of groundwater in the study area.

Ecological Risk Assessment of Metals Contamination in the Sediments of Natural Urban Wetlands in Dry Tropical Climate.

PubMed

Rana, Vivek; Maiti, Subodh Kumar; Jagadevan, Sheeja

2016-09-01

The pollution load due to metal contamination in the sediments of urban wetlands (Dhanbad, India) due to illegal release of domestic and industrial wastewater was studied by using various geochemical indices, such as contamination factor (Cf), degree of contamination (Cd), modified degree of contamination (mCd), pollution load index (PLI) and geoaccumulation index (Igeo) for Cu, Co, Cd, Cr and Mn. Cluster analysis (CA) and Principal component analysis (PCA) of metals present in wetland sediments were carried out to assess their origin and relationship with each other. The Cf values for different metals in the wetlands under investigation indicated low to very high level of pollution (Cf ranged between 0.02 and 14.15) with highest Cf (14.15) for Cd. The wetland receiving both domestic and industrial wastewater had the highest values of Cd, mCd and PLI as 17.48, 3.49 and 1.03 respectively.

Directly reconstructing principal components of heterogeneous particles from cryo-EM images.

PubMed

Tagare, Hemant D; Kucukelbir, Alp; Sigworth, Fred J; Wang, Hongwei; Rao, Murali

2015-08-01

Structural heterogeneity of particles can be investigated by their three-dimensional principal components. This paper addresses the question of whether, and with what algorithm, the three-dimensional principal components can be directly recovered from cryo-EM images. The first part of the paper extends the Fourier slice theorem to covariance functions showing that the three-dimensional covariance, and hence the principal components, of a heterogeneous particle can indeed be recovered from two-dimensional cryo-EM images. The second part of the paper proposes a practical algorithm for reconstructing the principal components directly from cryo-EM images without the intermediate step of calculating covariances. This algorithm is based on maximizing the posterior likelihood using the Expectation-Maximization algorithm. The last part of the paper applies this algorithm to simulated data and to two real cryo-EM data sets: a data set of the 70S ribosome with and without Elongation Factor-G (EF-G), and a data set of the influenza virus RNA dependent RNA Polymerase (RdRP). The first principal component of the 70S ribosome data set reveals the expected conformational changes of the ribosome as the EF-G binds and unbinds. The first principal component of the RdRP data set reveals a conformational change in the two dimers of the RdRP. Copyright © 2015 Elsevier Inc. All rights reserved.

40 CFR 60.2998 - What are the principal components of the model rule?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 6 2010-07-01 2010-07-01 false What are the principal components of... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule... management plan. (c) Operator training and qualification. (d) Emission limitations and operating limits. (e...

40 CFR 60.2570 - What are the principal components of the model rule?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 6 2010-07-01 2010-07-01 false What are the principal components of... Construction On or Before November 30, 1999 Use of Model Rule § 60.2570 What are the principal components of... (k) of this section. (a) Increments of progress toward compliance. (b) Waste management plan. (c...

Free energy landscape of a biomolecule in dihedral principal component space: sampling convergence and correspondence between structures and minima.

PubMed

Maisuradze, Gia G; Leitner, David M

2007-05-15

Dihedral principal component analysis (dPCA) has recently been developed and shown to display complex features of the free energy landscape of a biomolecule that may be absent in the free energy landscape plotted in principal component space due to mixing of internal and overall rotational motion that can occur in principal component analysis (PCA) [Mu et al., Proteins: Struct Funct Bioinfo 2005;58:45-52]. Another difficulty in the implementation of PCA is sampling convergence, which we address here for both dPCA and PCA using a tetrapeptide as an example. We find that for both methods the sampling convergence can be reached over a similar time. Minima in the free energy landscape in the space of the two largest dihedral principal components often correspond to unique structures, though we also find some distinct minima to correspond to the same structure. 2007 Wiley-Liss, Inc.

Development and testing of an instrument to measure protective nursing advocacy.

PubMed

Hanks, Robert G

2010-03-01

Patient advocacy is an important aspect of nursing care, yet there are few instruments to measure this essential function. This study was conducted to develop, determine the psychometric properties, and support validity of the Protective Nursing Advocacy Scale (PNAS), which measures nursing advocacy beliefs and actions from a protective perspective. The study used a descriptive correlational design with a systematically selected sample of 419 medical-surgical registered nurses. Analysis of the 43-item instrument was conducted using principal components analysis with promax rotation, which resulted in the items loading onto four components. The four subscales have sufficient internal consistency, as did the overall PNAS. Satisfactory evidence of construct, content, and convergent validity were determined. Implications for nursing practice include using the PNAS in conjunction with an educational program to enhance advocacy skills, which may help to improve patient outcomes.

Clinical Insight Into Latent Variables of Psychiatric Questionnaires for Mood Symptom Self-Assessment

PubMed Central

Saunders, Kate; Bilderbeck, Amy; Palmius, Niclas; Goodwin, Guy; De Vos, Maarten

2017-01-01

Background We recently described a new questionnaire to monitor mood called mood zoom (MZ). MZ comprises 6 items assessing mood symptoms on a 7-point Likert scale; we had previously used standard principal component analysis (PCA) to tentatively understand its properties, but the presence of multiple nonzero loadings obstructed the interpretation of its latent variables. Objective The aim of this study was to rigorously investigate the internal properties and latent variables of MZ using an algorithmic approach which may lead to more interpretable results than PCA. Additionally, we explored three other widely used psychiatric questionnaires to investigate latent variable structure similarities with MZ: (1) Altman self-rating mania scale (ASRM), assessing mania; (2) quick inventory of depressive symptomatology (QIDS) self-report, assessing depression; and (3) generalized anxiety disorder (7-item) (GAD-7), assessing anxiety. Methods We elicited responses from 131 participants: 48 bipolar disorder (BD), 32 borderline personality disorder (BPD), and 51 healthy controls (HC), collected longitudinally (median [interquartile range, IQR]: 363 [276] days). Participants were requested to complete ASRM, QIDS, and GAD-7 weekly (all 3 questionnaires were completed on the Web) and MZ daily (using a custom-based smartphone app). We applied sparse PCA (SPCA) to determine the latent variables for the four questionnaires, where a small subset of the original items contributes toward each latent variable. Results We found that MZ had great consistency across the three cohorts studied. Three main principal components were derived using SPCA, which can be tentatively interpreted as (1) anxiety and sadness, (2) positive affect, and (3) irritability. The MZ principal component comprising anxiety and sadness explains most of the variance in BD and BPD, whereas the positive affect of MZ explains most of the variance in HC. The latent variables in ASRM were identical for the patient groups but different for HC; nevertheless, the latent variables shared common items across both the patient group and HC. On the contrary, QIDS had overall very different principal components across groups; sleep was a key element in HC and BD but was absent in BPD. In GAD-7, nervousness was the principal component explaining most of the variance in BD and HC. Conclusions This study has important implications for understanding self-reported mood. MZ has a consistent, intuitively interpretable latent variable structure and hence may be a good instrument for generic mood assessment. Irritability appears to be the key distinguishing latent variable between BD and BPD and might be useful for differential diagnosis. Anxiety and sadness are closely interlinked, a finding that might inform treatment effects to jointly address these covarying symptoms. Anxiety and nervousness appear to be amongst the cardinal latent variable symptoms in BD and merit close attention in clinical practice. PMID:28546141

Optical Dark-Field and Electron Energy Loss Imaging and Spectroscopy of Symmetry-Forbidden Modes in Loaded Nanogap Antennas.

PubMed

Brintlinger, Todd; Herzing, Andrew A; Long, James P; Vurgaftman, Igor; Stroud, Rhonda; Simpkins, B S

2015-06-23

We have produced large numbers of hybrid metal-semiconductor nanogap antennas using a scalable electrochemical approach and systematically characterized the spectral and spatial character of their plasmonic modes with optical dark-field scattering, electron energy loss spectroscopy with principal component analysis, and full wave simulations. The coordination of these techniques reveal that these nanostructures support degenerate transverse modes which split due to substrate interactions, a longitudinal mode which scales with antenna length, and a symmetry-forbidden gap-localized transverse mode. This gap-localized transverse mode arises from mode splitting of transverse resonances supported on both antenna arms and is confined to the gap load enabling (i) delivery of substantial energy to the gap material and (ii) the possibility of tuning the antenna resonance via active modulation of the gap material's optical properties. The resonant position of this symmetry-forbidden mode is sensitive to gap size, dielectric strength of the gap material, and is highly suppressed in air-gapped structures which may explain its absence from the literature to date. Understanding the complex modal structure supported on hybrid nanosystems is necessary to enable the multifunctional components many seek.

Large Covariance Estimation by Thresholding Principal Orthogonal Complements

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088

Large Covariance Estimation by Thresholding Principal Orthogonal Complements.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2013-09-01

This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.

Application of multivariate analysis to investigate the trace element contamination in top soil of coal mining district in Jorong, South Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Pujiwati, Arie; Nakamura, K.; Watanabe, N.; Komai, T.

2018-02-01

Multivariate analysis is applied to investigate geochemistry of several trace elements in top soils and their relation with the contamination source as the influence of coal mines in Jorong, South Kalimantan. Total concentration of Cd, V, Co, Ni, Cr, Zn, As, Pb, Sb, Cu and Ba was determined in 20 soil samples by the bulk analysis. Pearson correlation is applied to specify the linear correlation among the elements. Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied to observe the classification of trace elements and contamination sources. The results suggest that contamination loading is contributed by Cr, Cu, Ni, Zn, As, and Pb. The elemental loading mostly affects the non-coal mining area, for instances the area near settlement and agricultural land use. Moreover, the contamination source is classified into the areas that are influenced by the coal mining activity, the agricultural types, and the river mixing zone. Multivariate analysis could elucidate the elemental loading and the contamination sources of trace elements in the vicinity of coal mine area.

Detection of Nisin and Fibrinogen Adsorption on Poly(ethylene Oxide) Coated Polyurethane Surfaces by Time-of-Flight Secondary Ion Mass Spectrometry (TOF-SIMS)

PubMed Central

Schilke, Karl F.; McGuire, Joseph

2011-01-01

Stable, pendant polyethylene oxide (PEO) layers were formed on medical-grade Pellethane® and Tygon® polyurethane surfaces, by adsorption and gamma-irradiation of PEO-polybutadiene-PEO triblock surfactants. Coated and uncoated polyurethanes were challenged individually or sequentially with nisin (a small polypeptide with antimicrobial activity) and/or fibrinogen, and then analyzed with time-of-flight secondary ion mass spectrometry (TOF-SIMS). Data reduction by robust principal components analysis (PCA) allowed detection of outliers, and distinguished adsorbed nisin and fibrinogen. Fibrinogen-contacted surfaces, with or without nisin, were very similar on uncoated polymer surfaces, consistent with nearly complete displacement or coverage of previously-adsorbed nisin by fibrinogen. In contrast, nisin-loaded PEO layers remained essentially unchanged upon challenge with fibrinogen, suggesting that the adsorbed nisin is stabilized within the pendant PEO layer, while the peptide-loaded PEO layer retains its ability to repel large proteins. Coatings of PEO loaded with therapeutic polypeptides on medical polymers have the potential to be used to produce anti-fouling and biofunctional surfaces for implantable or blood-contacting devices. PMID:21440897

Fast, Exact Bootstrap Principal Component Analysis for p > 1 million

PubMed Central

Fisher, Aaron; Caffo, Brian; Schwartz, Brian; Zipunnikov, Vadim

2015-01-01

Many have suggested a bootstrap procedure for estimating the sampling variability of principal component analysis (PCA) results. However, when the number of measurements per subject (p) is much larger than the number of subjects (n), calculating and storing the leading principal components from each bootstrap sample can be computationally infeasible. To address this, we outline methods for fast, exact calculation of bootstrap principal components, eigenvalues, and scores. Our methods leverage the fact that all bootstrap samples occupy the same n-dimensional subspace as the original sample. As a result, all bootstrap principal components are limited to the same n-dimensional subspace and can be efficiently represented by their low dimensional coordinates in that subspace. Several uncertainty metrics can be computed solely based on the bootstrap distribution of these low dimensional coordinates, without calculating or storing the p-dimensional bootstrap components. Fast bootstrap PCA is applied to a dataset of sleep electroencephalogram recordings (p = 900, n = 392), and to a dataset of brain magnetic resonance images (MRIs) (p ≈ 3 million, n = 352). For the MRI dataset, our method allows for standard errors for the first 3 principal components based on 1000 bootstrap samples to be calculated on a standard laptop in 47 minutes, as opposed to approximately 4 days with standard methods. PMID:27616801

Principal Workload: Components, Determinants and Coping Strategies in an Era of Standardization and Accountability

ERIC Educational Resources Information Center

Oplatka, Izhar

2017-01-01

Purpose: In order to fill the gap in theoretical and empirical knowledge about the characteristics of principal workload, the purpose of this paper is to explore the components of principal workload as well as its determinants and the coping strategies commonly used by principals to face this personal state. Design/methodology/approach:…

Strategies for reducing large fMRI data sets for independent component analysis.

PubMed

Wang, Ze; Wang, Jiongjiong; Calhoun, Vince; Rao, Hengyi; Detre, John A; Childress, Anna R

2006-06-01

In independent component analysis (ICA), principal component analysis (PCA) is generally used to reduce the raw data to a few principal components (PCs) through eigenvector decomposition (EVD) on the data covariance matrix. Although this works for spatial ICA (sICA) on moderately sized fMRI data, it is intractable for temporal ICA (tICA), since typical fMRI data have a high spatial dimension, resulting in an unmanageable data covariance matrix. To solve this problem, two practical data reduction methods are presented in this paper. The first solution is to calculate the PCs of tICA from the PCs of sICA. This approach works well for moderately sized fMRI data; however, it is highly computationally intensive, even intractable, when the number of scans increases. The second solution proposed is to perform PCA decomposition via a cascade recursive least squared (CRLS) network, which provides a uniform data reduction solution for both sICA and tICA. Without the need to calculate the covariance matrix, CRLS extracts PCs directly from the raw data, and the PC extraction can be terminated after computing an arbitrary number of PCs without the need to estimate the whole set of PCs. Moreover, when the whole data set becomes too large to be loaded into the machine memory, CRLS-PCA can save data retrieval time by reading the data once, while the conventional PCA requires numerous data retrieval steps for both covariance matrix calculation and PC extractions. Real fMRI data were used to evaluate the PC extraction precision, computational expense, and memory usage of the presented methods.

The development and testing of the thermal break divertor monoblock target design delivering 20 MW m-2 heat load capability

NASA Astrophysics Data System (ADS)

Fursdon, M.; Barrett, T.; Domptail, F.; Evans, Ll M.; Luzginova, N.; Greuner, N. H.; You, J.-H.; Li, M.; Richou, M.; Gallay, F.; Visca, E.

2017-12-01

The design and development of a novel plasma facing component (for fusion power plants) is described. The component uses the existing ‘monoblock’ construction which consists of a tungsten ‘block’ joined via a copper interlayer to a through CuCrZr cooling pipe. In the new concept the interlayer stiffness and conductivity properties are tuned so that stress in the principal structural element of the component (the cooling pipe) is reduced. Following initial trials with off-the-shelf materials, the concept was realized by machined features in an otherwise solid copper interlayer. The shape and distribution of the features were tuned by finite element analyses subject to ITER structural design criterion in-vessel components (SDC-IC) design rules. Proof of concept mock-ups were manufactured using a two stage brazing process verified by tomography and micrographic inspection. Full assemblies were inspected using ultrasound and thermographic (SATIR) test methods at ENEA and CEA respectively. High heat flux tests using IPP’s GLADIS facility showed that 200 cycles at 20 MW m-2 and five cycles at 25 MW m-2 could be sustained without apparent component damage. Further testing and component development is planned.

Considering Horn's Parallel Analysis from a Random Matrix Theory Point of View.

PubMed

Saccenti, Edoardo; Timmerman, Marieke E

2017-03-01

Horn's parallel analysis is a widely used method for assessing the number of principal components and common factors. We discuss the theoretical foundations of parallel analysis for principal components based on a covariance matrix by making use of arguments from random matrix theory. In particular, we show that (i) for the first component, parallel analysis is an inferential method equivalent to the Tracy-Widom test, (ii) its use to test high-order eigenvalues is equivalent to the use of the joint distribution of the eigenvalues, and thus should be discouraged, and (iii) a formal test for higher-order components can be obtained based on a Tracy-Widom approximation. We illustrate the performance of the two testing procedures using simulated data generated under both a principal component model and a common factors model. For the principal component model, the Tracy-Widom test performs consistently in all conditions, while parallel analysis shows unpredictable behavior for higher-order components. For the common factor model, including major and minor factors, both procedures are heuristic approaches, with variable performance. We conclude that the Tracy-Widom procedure is preferred over parallel analysis for statistically testing the number of principal components based on a covariance matrix.

Principal Locations of Metal Loading from Flood-Plain Tailings, Lower Silver Creek, Utah, April 2004

USGS Publications Warehouse

Kimball, Briant A.; Runkel, Robert L.; Walton-Day, Katherine

2007-01-01

Because of the historical deposition of mill tailings in flood plains, the process of determining total maximum daily loads for streams in an area like the Park City mining district of Utah is complicated. Understanding the locations of metal loading to Silver Creek and the relative importance of these locations is necessary to make science-based decisions. Application of tracer-injection and synoptic-sampling techniques provided a means to quantify and rank the many possible source areas. A mass-loading study was conducted along a 10,000-meter reach of Silver Creek, Utah, in April 2004. Mass-loading profiles based on spatially detailed discharge and chemical data indicated five principal locations of metal loading. These five locations contributed more than 60 percent of the cadmium and zinc loads to Silver Creek along the study reach and can be considered locations where remediation efforts could have the greatest effect upon improvement of water quality in Silver Creek.

Psychometric Properties of the Canadian Nurse Informatics Competency Assessment Scale.

PubMed

Kleib, Manal; Nagle, Lynn

2018-04-10

Assessment of nursing informatics competencies has gained momentum in the scholarly literature in response to the increased need for resources available to support informatics capacity in nursing. The purpose of this study was to examine the factor structure and internal consistency reliability of the Canadian Nurse Informatics Competency Assessment Scale, a newly developed 21-item measure based on published entry-to-practice informatics competencies for RNs. For this study, 2844 nurses completed the Canadian Nurse Informatics Competency Assessment Scale through a cross-sectional survey. Exploratory principal component analysis with oblique promax rotation revealed a four-component/factor structure for the 21-item Canadian Nurse Informatics Competency Assessment Scale, explaining 61.04% of the variance. Item loading per each component reflected the original Canadian Association of Schools of Nursing grouping of nursing informatics competency indicators, as per three key domains of competency: information and knowledge management (α = .85); professional and regulatory accountability (α = .81); and use of information and communication technology in the delivery of patient care (α = .87) with the exception of one item (Indicator 3), which loaded into the category of foundational information and communication technology skills (α = .81). This study provided preliminary evidence for the construct validity of the entry-to-practice competency domains and the factor structure and reliability of the Canadian Nurse Informatics Competency Assessment Scale among practicing nurses. Further testing among nurses in other settings and among nursing students is recommended.

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

[Support of the nursing process through electronic nursing documentation systems (UEPD) – Initial validation of an instrument].

PubMed

Hediger, Hannele; Müller-Staub, Maria; Petry, Heidi

2016-01-01

Electronic nursing documentation systems, with standardized nursing terminology, are IT-based systems for recording the nursing processes. These systems have the potential to improve the documentation of the nursing process and to support nurses in care delivery. This article describes the development and initial validation of an instrument (known by its German acronym UEPD) to measure the subjectively-perceived benefits of an electronic nursing documentation system in care delivery. The validity of the UEPD was examined by means of an evaluation study carried out in an acute care hospital (n = 94 nurses) in German-speaking Switzerland. Construct validity was analyzed by principal components analysis. Initial references of validity of the UEPD could be verified. The analysis showed a stable four factor model (FS = 0.89) scoring in 25 items. All factors loaded ≥ 0.50 and the scales demonstrated high internal consistency (Cronbach's α = 0.73 – 0.90). Principal component analysis revealed four dimensions of support: establishing nursing diagnosis and goals; recording a case history/an assessment and documenting the nursing process; implementation and evaluation as well as information exchange. Further testing with larger control samples and with different electronic documentation systems are needed. Another potential direction would be to employ the UEPD in a comparison of various electronic documentation systems.

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.

Effect of Dust and Anthropogenic Aerosols on Columnar Aerosol Optical Properties over Darjeeling (2200 m asl), Eastern Himalayas, India

PubMed Central

Chatterjee, Abhijit; Ghosh, Sanjay K.; Adak, Anandamay; Singh, Ajay K.; Devara, Panuganti C. S.; Raha, Sibaji

2012-01-01

Background The loading of atmospheric particulate matter (aerosol) in the eastern Himalaya is mainly regulated by the locally generated anthropogenic aerosols from the biomass burning and by the aerosols transported from the distance sources. These different types of aerosol loading not only affect the aerosol chemistry but also produce consequent signature on the radiative properties of aerosol. Methodology/Principal Findings An extensive study has been made to study the seasonal variations in aerosol components of fine and coarse mode aerosols and black carbon along with the simultaneous measurements of aerosol optical depth on clear sky days over Darjeeling, a high altitude station (2200 masl) at eastern Himalayas during the year 2008. We observed a heavy loading of fine mode dust component (Ca2+) during pre-monsoon (Apr – May) which was higher by 162% than its annual mean whereas during winter (Dec – Feb), the loading of anthropogenic aerosol components mainly from biomass burning (fine mode SO4 2− and black carbon) were higher (76% for black carbon and 96% for fine mode SO4 2−) from their annual means. These high increases in dust aerosols during pre-monsoon and anthropogenic aerosols during winter enhanced the aerosol optical depth by 25 and 40%, respectively. We observed that for every 1% increase in anthropogenic aerosols, AOD increased by 0.55% during winter whereas for every 1% increase in dust aerosols, AOD increased by 0.46% during pre-monsoon. Conclusion/Significance The natural dust transport process (during pre-monsoon) plays as important a role in the radiation effects as the anthropogenic biomass burning (during winter) and their differential effects (rate of increase of the AOD with that of the aerosol concentration) are also very similar. This should be taken into account in proper modeling of the atmospheric environment over eastern Himalayas. PMID:22792264

The Influence Function of Principal Component Analysis by Self-Organizing Rule.

PubMed

Higuchi; Eguchi

1998-07-28

This article is concerned with a neural network approach to principal component analysis (PCA). An algorithm for PCA by the self-organizing rule has been proposed and its robustness observed through the simulation study by Xu and Yuille (1995). In this article, the robustness of the algorithm against outliers is investigated by using the theory of influence function. The influence function of the principal component vector is given in an explicit form. Through this expression, the method is shown to be robust against any directions orthogonal to the principal component vector. In addition, a statistic generated by the self-organizing rule is proposed to assess the influence of data in PCA.

Effects of a cognitive dual task on variability and local dynamic stability in sustained repetitive arm movements using principal component analysis: a pilot study.

PubMed

Longo, Alessia; Federolf, Peter; Haid, Thomas; Meulenbroek, Ruud

2018-06-01

In many daily jobs, repetitive arm movements are performed for extended periods of time under continuous cognitive demands. Even highly monotonous tasks exhibit an inherent motor variability and subtle fluctuations in movement stability. Variability and stability are different aspects of system dynamics, whose magnitude may be further affected by a cognitive load. Thus, the aim of the study was to explore and compare the effects of a cognitive dual task on the variability and local dynamic stability in a repetitive bimanual task. Thirteen healthy volunteers performed the repetitive motor task with and without a concurrent cognitive task of counting aloud backwards in multiples of three. Upper-body 3D kinematics were collected and postural reconfigurations-the variability related to the volunteer's postural change-were determined through a principal component analysis-based procedure. Subsequently, the most salient component was selected for the analysis of (1) cycle-to-cycle spatial and temporal variability, and (2) local dynamic stability as reflected by the largest Lyapunov exponent. Finally, end-point variability was evaluated as a control measure. The dual cognitive task proved to increase the temporal variability and reduce the local dynamic stability, marginally decrease endpoint variability, and substantially lower the incidence of postural reconfigurations. Particularly, the latter effect is considered to be relevant for the prevention of work-related musculoskeletal disorders since reduced variability in sustained repetitive tasks might increase the risk of overuse injuries.

Revisiting AVHRR Tropospheric Aerosol Trends Using Principal Component Analysis

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

The advanced very high resolution radiometer (AVHRR) satellite instruments provide a nearly 25 year continuous record of global aerosol properties over the ocean. It offers valuable insights into the long-term change in global aerosol loading. However, the AVHRR data record is heavily influenced by two volcanic eruptions, El Chichon on March 1982 and Mount Pinatubo on June 1991. The gradual decay of volcanic aerosols may last years after the eruption, which potentially masks the estimation of aerosol trends in the lower troposphere, especially those of anthropogenic origin. In this study, we show that a principal component analysis approach effectively captures the bulk of the spatial and temporal variability of volcanic aerosols into a single mode. The spatial pattern and time series of this mode provide a good match to the global distribution and decay of volcanic aerosols. We further reconstruct the data set by removing the volcanic aerosol component and reestimate the global and regional aerosol trends. Globally, the reconstructed data set reveals an increase of aerosol optical depth from 1985 to 1990 and decreasing trend from 1994 to 2006. Regionally, in the 1980s, positive trends are observed over the North Atlantic and North Arabian Sea, while negative tendencies are present off the West African coast and North Pacific. During the 1994 to 2006 period, the Gulf of Mexico, North Atlantic close to Europe, and North Africa exhibit negative trends, while the coastal regions of East and South Asia, the Sahel region, and South America show positive trends.

Construction of an environmental quality index for public health research

PubMed Central

2014-01-01

Background A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed. Methods The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000–2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural–urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality. Results Concentrations of included variables differed across rural–urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (−4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from −5.86, 2.52). Conclusion The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources. PMID:24886426

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.

Investigation of progressive failure robustness and alternate load paths for damage tolerant structures

NASA Astrophysics Data System (ADS)

Marhadi, Kun Saptohartyadi

Structural optimization for damage tolerance under various unforeseen damage scenarios is computationally challenging. It couples non-linear progressive failure analysis with sampling-based stochastic analysis of random damage. The goal of this research was to understand the relationship between alternate load paths available in a structure and its damage tolerance, and to use this information to develop computationally efficient methods for designing damage tolerant structures. Progressive failure of a redundant truss structure subjected to small random variability was investigated to identify features that correlate with robustness and predictability of the structure's progressive failure. The identified features were used to develop numerical surrogate measures that permit computationally efficient deterministic optimization to achieve robustness and predictability of progressive failure. Analysis of damage tolerance on designs with robust progressive failure indicated that robustness and predictability of progressive failure do not guarantee damage tolerance. Damage tolerance requires a structure to redistribute its load to alternate load paths. In order to investigate the load distribution characteristics that lead to damage tolerance in structures, designs with varying degrees of damage tolerance were generated using brute force stochastic optimization. A method based on principal component analysis was used to describe load distributions (alternate load paths) in the structures. Results indicate that a structure that can develop alternate paths is not necessarily damage tolerant. The alternate load paths must have a required minimum load capability. Robustness analysis of damage tolerant optimum designs indicates that designs are tailored to specified damage. A design Optimized under one damage specification can be sensitive to other damages not considered. Effectiveness of existing load path definitions and characterizations were investigated for continuum structures. A load path definition using a relative compliance change measure (U* field) was demonstrated to be the most useful measure of load path. This measure provides quantitative information on load path trajectories and qualitative information on the effectiveness of the load path. The use of the U* description of load paths in optimizing structures for effective load paths was investigated.

Genetic algorithm applied to the selection of factors in principal component-artificial neural networks: application to QSAR study of calcium channel antagonist activity of 1,4-dihydropyridines (nifedipine analogous).

PubMed

Hemmateenejad, Bahram; Akhond, Morteza; Miri, Ramin; Shamsipur, Mojtaba

2003-01-01

A QSAR algorithm, principal component-genetic algorithm-artificial neural network (PC-GA-ANN), has been applied to a set of newly synthesized calcium channel blockers, which are of special interest because of their role in cardiac diseases. A data set of 124 1,4-dihydropyridines bearing different ester substituents at the C-3 and C-5 positions of the dihydropyridine ring and nitroimidazolyl, phenylimidazolyl, and methylsulfonylimidazolyl groups at the C-4 position with known Ca(2+) channel binding affinities was employed in this study. Ten different sets of descriptors (837 descriptors) were calculated for each molecule. The principal component analysis was used to compress the descriptor groups into principal components. The most significant descriptors of each set were selected and used as input for the ANN. The genetic algorithm (GA) was used for the selection of the best set of extracted principal components. A feed forward artificial neural network with a back-propagation of error algorithm was used to process the nonlinear relationship between the selected principal components and biological activity of the dihydropyridines. A comparison between PC-GA-ANN and routine PC-ANN shows that the first model yields better prediction ability.

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data.

PubMed

Salvatore, Stefania; Bramness, Jørgen G; Røislien, Jo

2016-07-12

Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally. We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data. The first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data. FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

40 CFR 62.14505 - What are the principal components of this subpart?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 8 2010-07-01 2010-07-01 false What are the principal components of this subpart? 62.14505 Section 62.14505 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... components of this subpart? This subpart contains the eleven major components listed in paragraphs (a...

Method of operating a thermoelectric generator

DOEpatents

Reynolds, Michael G; Cowgill, Joshua D

2013-11-05

A method for operating a thermoelectric generator supplying a variable-load component includes commanding the variable-load component to operate at a first output and determining a first load current and a first load voltage to the variable-load component while operating at the commanded first output. The method also includes commanding the variable-load component to operate at a second output and determining a second load current and a second load voltage to the variable-load component while operating at the commanded second output. The method includes calculating a maximum power output of the thermoelectric generator from the determined first load current and voltage and the determined second load current and voltage, and commanding the variable-load component to operate at a third output. The commanded third output is configured to draw the calculated maximum power output from the thermoelectric generator.

Hierarchical Regularity in Multi-Basin Dynamics on Protein Landscapes

NASA Astrophysics Data System (ADS)

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

2004-04-01

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

Principals' Perceptions Regarding Their Supervision and Evaluation

ERIC Educational Resources Information Center

Hvidston, David J.; Range, Bret G.; McKim, Courtney Ann

2015-01-01

This study examined the perceptions of principals concerning principal evaluation and supervisory feedback. Principals were asked two open-ended questions. Respondents included 82 principals in the Rocky Mountain region. The emerging themes were "Superintendent Performance," "Principal Evaluation Components," "Specific…

Critical assessment of day time traffic noise level at curbside open-air microenvironment of Kolkata City, India.

PubMed

Kundu Chowdhury, Anirban; Debsarkar, Anupam; Chakrabarty, Shibnath

2015-01-01

The objective of the research work is to assess day time traffic noise level at curbside open-air microenvironment of Kolkata city, India under heterogeneous environmental conditions. Prevailing traffic noise level in terms of A-weighted equivalent noise level (Leq) at the microenvironment was in excess of 12.6 ± 2.1 dB(A) from the day time standard of 65 dB(A) for commercial area recommended by the Central Pollution Control Board (CPCB) of India. Noise Climate and Traffic Noise Index of the microenvironment were accounted for 13 ± 1.8 dB(A) and 88.8 ± 6.1 dB(A) respectively. A correlation analysis explored that prevailing traffic noise level of the microenvironment had weak negative (-0.21; p < 0.01) and very weak positive (0.19; p < 0.01) correlation with air temperature and relative humidity. A Varimax rotated principal component analysis explored that motorized traffic volume had moderate positive loading with background noise component (L90, L95, L99) and prevailing traffic noise level had very strong positive loading with peak noise component (L1, L5, L10). Background and peak noise component cumulatively explained 80.98 % of variance in the data set. Traffic noise level at curbside open-air microenvironment of Kolkata City was higher than the standard recommended by CPCB of India. It was highly annoying also. Air temperature and relative humidity had little influence and the peak noise component had the most significant influence on the prevailing traffic noise level at curbside open-air microenvironment. Therefore, traffic noise level at the microenvironment of the city can be reduced with careful honking and driving.

Interpersonal differentiation within depression diagnosis: relating interpersonal subgroups to symptom load and the quality of the early therapeutic alliance.

PubMed

Grosse Holtforth, Martin; Altenstein, David; Krieger, Tobias; Flückiger, Christoph; Wright, Aidan G C; Caspar, Franz

2014-01-01

We examined interpersonal problems in psychotherapy outpatients with a principal diagnosis of a depressive disorder in routine care (n=361). These patients were compared to a normative non-clinical sample and to outpatients with other principal diagnoses (n=959). Furthermore, these patients were statistically assigned to interpersonally defined subgroups that were compared regarding symptoms and the quality of the early alliance. The sample of depressive patients reported higher levels of interpersonal problems than the normative sample and the sample of outpatients without a principal diagnosis of depression. Latent Class Analysis identified eight distinct interpersonal subgroups, which differed regarding self-reported symptom load and the quality of the early alliance. However, therapists' alliance ratings did not differentiate between the groups. This interpersonal differentiation within the group of patients with a principal diagnosis of depression may add to a personalized psychotherapy based on interpersonal profiles.

Inequalities in the spiritual health of young Canadians: a national, cross-sectional study.

PubMed

Michaelson, Valerie; Freeman, John; King, Nathan; Ascough, Hannah; Davison, Colleen; Trothen, Tracy; Phillips, Sian; Pickett, William

2016-11-28

Spiritual health, along with physical, emotional, and social aspects, is one of four domains of health. Assessment in this field of research is challenging methodologically. No contemporary population-based studies have profiled the spiritual health of adolescent Canadians with a focus on health inequalities. In a 2014 nationally representative sample of Canadians aged 11-15 years we therefore: (1) psychometrically evaluated a series of items used to assess the perceived importance of spiritual health and its four potential sub-domains (connections with: self, others, nature and the natural environment, and the transcendent) to adolescents; (2) described potential inequalities in spiritual health within adolescent populations, overall and by spiritual health sub-domain, by key socio-demographic factors. Cross-sectional analysis of survey reports from the 2014 (Cycle 7) of the Canadian Health Behaviour in School-aged Children study (weighted n = 25,036). Principal components analysis followed by confirmatory factor analysis were used to explore the psychometric properties of the spiritual health items and the associated composite scale describing perceived importance of spiritual health. Associations among this composite scale, its individual sub-domains, and key socio-demographic factors were then explored. The principal components analysis best supported a four-factor structure where the eight scale items loaded highly according to the original four domains. This was also supported in confirmatory factor analyses. We then combined the eight items into composite spiritual health score as supported by theory, principal components analysis findings, and acceptable tests of reliability. Further confirmatory factor analysis suggested the need for additional refinements to this scale. Based upon exploratory cross-sectional analyses, strong socio-demographic inequalities were observed in the spiritual health measures by age, gender, relative material wealth, immigration status, and province/territory. Study findings highlight potential inequalities in the spiritual health of young Canadians, as well as opportunities for methodological advances in the assessment of adolescent spiritual health in our population.

Biomarkers of furan exposure by metabolic profiling of rat urine with liquid chromatography-tandem mass spectrometry and principal component analysis.

PubMed

Kellert, Marco; Wagner, Silvia; Lutz, Ursula; Lutz, Werner K

2008-03-01

Furan has been found in a number of heated food items and is carcinogenic in the liver of rats and mice. Estimates of human exposure on the basis of concentrations measured in food are not reliable because of the volatility of furan. A biomarker approach is therefore indicated. We searched for metabolites excreted in the urine of male Fischer 344 rats treated by oral gavage with 40 mg of furan per kg of body weight. A control group received the vehicle oil only. Urine collected over two 24-h periods both before and after treatment was analyzed by a column-switching LC-MS/MS method. Data were acquired by a full scan survey scan in combination with information dependent acquisition of fragmentation spectra by the use of a linear ion trap. Areas of 449 peaks were extracted from the chromatograms and used for principal component analysis (PCA). The first principal component fully separated the samples of treated rats from the controls in the first post-treatment sampling period. Thirteen potential biomarkers selected from the corresponding loadings plot were reanalyzed using specific transitions in the MRM mode. Seven peaks that increased significantly upon treatment were further investigated as biomarkers of exposure. MS/MS information indicated conjugation with glutathione on the basis of the characteristic neutral loss of 129 for mercapturates. Adducts with the side chain amino group of lysine were characterized by a neutral loss of 171 for N-acetyl- l-lysine. Analysis of products of in vitro incubations of the reactive furan metabolite cis-2-butene-1,4-dial with the respective amino acid derivatives supported five structures, including a new 3-methylthio-pyrrole metabolite probably formed by beta-lyase reaction on a glutathione conjugate, followed by methylation of the thiol group. Our results demonstrate the potential of comprehensive mass spectrometric analysis of urine combined with multivariate analyses for metabolic profiling in search of biomarkers of exposure.

Principal component analysis of physicochemical and sensory characteristics of beef rounds extended with gum arabic from Acacia senegal var. kerensis.

PubMed

Mwove, Johnson K; Gogo, Lilian A; Chikamai, Ben N; Omwamba, Mary; Mahungu, Symon M

2018-03-01

Principal component analysis (PCA) was carried out to study the relationship between 24 meat quality measurements taken from beef round samples that were injected with curing brines containing gum arabic (1%, 1.5%, 2%, 2.5%, and 3%) and soy protein concentrate (SPC) (3.5%) at two injection levels (30% and 35%). The measurements used to describe beef round quality were expressible moisture, moisture content, cook yield, possible injection, achieved gum arabic level in beef round, and protein content, as well as descriptive sensory attributes for flavor, texture, basic tastes, feeling factors, color, and overall acceptability. Several significant correlations were found between beef round quality parameters. The highest significant negative and positive correlations were recorded between color intensity and gray color and between color intensity and brown color, respectively. The first seven principal components (PCs) were extracted explaining over 95% of the total variance. The first PC was characterized by texture attributes (hardness and denseness), feeling factors (chemical taste and chemical burn), and two physicochemical properties (expressible moisture and achieved gum arabic level). Taste attribute (saltiness), physicochemical attributes (cook yield and possible injection), and overall acceptability were useful in defining the second PC, while the third PC was characterized by metallic taste, gray color, brown color, and physicochemical attributes (moisture and protein content). The correlation loading plot showed that the distribution of the samples on the axes of the first two PCs allowed for differentiation of samples injected to 30% injection level which were placed on the upper side of the biplot from those injected to 35% which were placed on the lower side. Similarly, beef samples extended with gum arabic and those containing SPC were also visible when scores for the first and third PCs were plotted. Thus, PCA was efficient in analyzing the quality characteristics of beef rounds extended with gum arabic.

Chemical and microstructural characterizations of plasma polymer films by time-of-flight secondary ion mass spectrometry and principal component analysis

NASA Astrophysics Data System (ADS)

Cossement, Damien; Renaux, Fabian; Thiry, Damien; Ligot, Sylvie; Francq, Rémy; Snyders, Rony

2015-11-01

It is accepted that the macroscopic properties of functional plasma polymer films (PPF) are defined by their functional density and their crosslinking degree (χ) which are quantities that most of the time behave in opposite trends. If the PPF chemistry is relatively easy to evaluate, it is much more challenging for χ. This paper reviews the recent work developed in our group on the application of principal component analysis (PCA) to time-of-flight secondary ion mass spectrometric (ToF-SIMS) positive spectra data in order to extract the relative cross-linking degree (χ) of PPF. NH2-, COOR- and SH-containing PPF synthesized in our group by plasma enhanced chemical vapor deposition (PECVD) varying the applied radiofrequency power (PRF), have been used as model surfaces. For the three plasma polymer families, the scores of the first computed principal component (PC1) highlighted significant differences in the chemical composition supported by X-Ray photoelectron spectroscopy (XPS) data. The most important fragments contributing to PC1 (loadings > 90%) were used to compute an average C/H ratio index for samples synthesized at low and high PRF. This ratio being an evaluation of χ, these data, accordingly to the literature, indicates an increase of χ with PRF excepted for the SH-PPF. These results have been cross-checked by the evaluation of functional properties of the plasma polymers namely a linear correlation with the stability of NH2-PPF in ethanol and a correlation with the mechanical properties of the COOR-PPF. For the SH-PPF family, the peculiar evolution of χ is supported by the understanding of the growth mechanism of the PPF from plasma diagnostic. The whole set of data clearly demonstrates the potential of the PCA method for extracting information on the microstructure of plasma polymers from ToF-SIMS measurements.

Stress changes ahead of an advancing tunnel

USGS Publications Warehouse

Abel, J.F.; Lee, F.T.

1973-01-01

Instrumentation placed ahead of three model tunnels in the laboratory and ahead of a crosscut driven in a metamorphic rock mass detected stress changes several tunnel diameters ahead of the tunnel face. Stress changes were detected 4 diameters ahead of a model tunnel drilled into nearly elastic acrylic, 2??50 diameters ahead of a model tunnel drilled into concrete, and 2 diameters ahead of a model tunnel drilled into Silver Plume Granite. Stress changes were detected 7??50 diameters ahead of a crosscut driven in jointed, closely foliated gneisses and gneissic granites in an experimental mine at Idaho Springs, Colorado. These results contrast markedly with a theoretical elastic estimate of the onset of detectable stress changes at 1 tunnel diameter ahead of the tunnel face. A small compressive stress concentration was detected 2 diameters ahead of the model tunnel in acrylic, 1.25 diameters ahead of the model tunnel in concrete, and 1 diameter ahead of the model tunnel in granite. A similar stress peak was detected about 6 diameters ahead of the crosscut. No such stress peak is predicted from elastic theory. The 3-dimensional in situ stress determined in the field demonstrate that geologic structure controls stress orientations in the metamorphic rock mass. Two of the computed principal stresses are parallel to the foliation and the other principal stress is normal to it. The principal stress orientations vary approximately as the foliation attitude varies. The average horizontal stress components and the average vertical stress component are three times and twice as large, respectively, as those predicted from the overburden load. An understanding of the measured stress field appears to require the application of either tectonic or residual stress components, or both. Laboratory studies indicate the presence of proportionately large residual stresses. Mining may have triggered the release of strain energy, which is controlled by geologic structure. ?? 1973.

Influence of Different Drying Treatments and Extraction Solvents on the Metabolite Profile and Nitric Oxide Inhibitory Activity of Ajwa Dates.

PubMed

Abdul-Hamid, Nur Ashikin; Abas, Faridah; Ismail, Intan Safinar; Shaari, Khozirah; Lajis, Nordin H

2015-11-01

This study aimed to examine the variation in the metabolite profiles and nitric oxide (NO) inhibitory activity of Ajwa dates that were subjected to 2 drying treatments and different extraction solvents. (1)H NMR coupled with multivariate data analysis was employed. A Griess assay was used to determine the inhibition of the production of NO in RAW 264.7 cells treated with LPS and interferon-γ. The oven dried (OD) samples demonstrated the absence of asparagine and ascorbic acid as compared to the freeze dried (FD) dates. The principal component analysis showed distinct clusters between the OD and FD dates by the second principal component. In respect of extraction solvents, chloroform extracts can be distinguished by the absence of arginine, glycine and asparagine compared to the methanol and 50% methanol extracts. The chloroform extracts can be clearly distinguished from the methanol and 50% methanol extracts by first principal component. Meanwhile, the loading score plot of partial least squares analysis suggested that beta glucose, alpha glucose, choline, ascorbic acid and glycine were among the metabolites that were contributing to higher biological activity displayed by FD and methanol extracts of Ajwa. The results highlight an alternative method of metabolomics approach for determination of the metabolites that contribute to NO inhibitory activity. The association between metabolite profiles and nitric oxide (NO) inhibitory activity of the various extracts of Ajwa dates was evaluated by utilizing partial least squares (PLS) model. The validated PLS model can be employed to predict the NO inhibitory activity of new samples of date fruits based on their NMR spectra which was important for assessing fruit quality. The information gained might be used as guidance for quality control, nutritional values and as a basis for the preparation of any food supplements for human health that employs date palm fruit as the raw material. © 2015 Institute of Food Technologists®

Meta-Analyses of Dehalococcoides mccartyi Strain 195 Transcriptomic Profiles Identify a Respiration Rate-Related Gene Expression Transition Point and Interoperon Recruitment of a Key Oxidoreductase Subunit

PubMed Central

Mansfeldt, Cresten B.; Rowe, Annette R.; Heavner, Gretchen L. W.; Zinder, Stephen H.

2014-01-01

A cDNA-microarray was designed and used to monitor the transcriptomic profile of Dehalococcoides mccartyi strain 195 (in a mixed community) respiring various chlorinated organics, including chloroethenes and 2,3-dichlorophenol. The cultures were continuously fed in order to establish steady-state respiration rates and substrate levels. The organization of array data into a clustered heat map revealed two major experimental partitions. This partitioning in the data set was further explored through principal component analysis. The first two principal components separated the experiments into those with slow (1.6 ± 0.6 μM Cl−/h)- and fast (22.9 ± 9.6 μM Cl−/h)-respiring cultures. Additionally, the transcripts with the highest loadings in these principal components were identified, suggesting that those transcripts were responsible for the partitioning of the experiments. By analyzing the transcriptomes (n = 53) across experiments, relationships among transcripts were identified, and hypotheses about the relationships between electron transport chain members were proposed. One hypothesis, that the hydrogenases Hup and Hym and the formate dehydrogenase-like oxidoreductase (DET0186-DET0187) form a complex (as displayed by their tight clustering in the heat map analysis), was explored using a nondenaturing protein separation technique combined with proteomic sequencing. Although these proteins did not migrate as a single complex, DET0112 (an FdhB-like protein encoded in the Hup operon) was found to comigrate with DET0187 rather than with the catalytic Hup subunit DET0110. On closer inspection of the genome annotations of all Dehalococcoides strains, the DET0185-to-DET0187 operon was found to lack a key subunit, an FdhB-like protein. Therefore, on the basis of the transcriptomic, genomic, and proteomic evidence, the place of the missing subunit in the DET0185-to-DET0187 operon is likely filled by recruiting a subunit expressed from the Hup operon (DET0112). PMID:25063656

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.

[Assessment of the strength of tobacco control on creating smoke-free hospitals using principal components analysis].

PubMed

Liu, Hui-lin; Wan, Xia; Yang, Gong-huan

2013-02-01

To explore the relationship between the strength of tobacco control and the effectiveness of creating smoke-free hospital, and summarize the main factors that affect the program of creating smoke-free hospitals. A total of 210 hospitals from 7 provinces/municipalities directly under the central government were enrolled in this study using stratified random sampling method. Principle component analysis and regression analysis were conducted to analyze the strength of tobacco control and the effectiveness of creating smoke-free hospitals. Two principal components were extracted in the strength of tobacco control index, which respectively reflected the tobacco control policies and efforts, and the willingness and leadership of hospital managers regarding tobacco control. The regression analysis indicated that only the first principal component was significantly correlated with the progression in creating smoke-free hospital (P<0.001), i.e. hospitals with higher scores on the first principal component had better achievements in smoke-free environment creation. Tobacco control policies and efforts are critical in creating smoke-free hospitals. The principal component analysis provides a comprehensive and objective tool for evaluating the creation of smoke-free hospitals.

Transformations of the chemical compositions of high molecular weight DOM along a salinity transect: Using two dimensional correlation spectroscopy and principal component analysis approaches

NASA Astrophysics Data System (ADS)

Abdulla, Hussain A. N.; Minor, Elizabeth C.; Dias, Robert F.; Hatcher, Patrick G.

2013-10-01

In a study of chemical transformations of estuarine high-molecular-weight (HMW, >1000 Da) dissolved organic matter (DOM) collected over a period of two years along a transect through the Elizabeth River/Chesapeake Bay system to the coastal Atlantic Ocean off Virginia, USA, δ13C values, N/C ratios, and principal component analysis (PCA) of the solid-state 13C NMR (nuclear magnetic resonance) spectra of HMW-DOM show an abrupt change in both its sources and chemical structural composition occurring around salinity 20. HMW-DOM in the lower salinity region had lighter isotopic values, higher aromatic and lower carbohydrate contents relative to that in the higher salinity region. These changes around a salinity of 20 are possibly due to introduction of a significant amount of new carbon (autotrophic DOM) to the transect. PC-1 loadings plot shows that spatially differing DOM components are similar to previously reported 13C NMR spectra of heteropolysaccharides (HPS) and carboxyl-rich alicyclic molecules (CRAM). Applying two dimensional correlation spectroscopy techniques to 1H NMR spectra from the same samples reveals increases in the contribution of N-acetyl amino sugars, 6-deoxy sugars, and sulfated polysaccharides to HPS components along the salinity transect, which suggests a transition from plant derived carbohydrates to marine produced carbohydrates within the HMW-DOM pool. In contrast to what has been suggested previously, our combined results from 13C NMR, 1H NMR, and FTIR indicate that CRAM consists of at least two different classes of compounds (aliphatic polycarboxyl compounds and lignin-like compounds).

Critical Factors Explaining the Leadership Performance of High-Performing Principals

ERIC Educational Resources Information Center

Hutton, Disraeli M.

2018-01-01

The study explored critical factors that explain leadership performance of high-performing principals and examined the relationship between these factors based on the ratings of school constituents in the public school system. The principal component analysis with the use of Varimax Rotation revealed that four components explain 51.1% of the…

Molecular dynamics in principal component space.

PubMed

Michielssens, Servaas; van Erp, Titus S; Kutzner, Carsten; Ceulemans, Arnout; de Groot, Bert L

2012-07-26

A molecular dynamics algorithm in principal component space is presented. It is demonstrated that sampling can be improved without changing the ensemble by assigning masses to the principal components proportional to the inverse square root of the eigenvalues. The setup of the simulation requires no prior knowledge of the system; a short initial MD simulation to extract the eigenvectors and eigenvalues suffices. Independent measures indicated a 6-7 times faster sampling compared to a regular molecular dynamics simulation.

Optimized principal component analysis on coronagraphic images of the fomalhaut system

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

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

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

Development of a new connection for precast concrete walls subjected to cyclic loading

NASA Astrophysics Data System (ADS)

Vaghei, Ramin; Hejazi, Farzad; Taheri, Hafez; Jaafar, Mohd Saleh; Aziz, Farah Nora Aznieta Abdul

2017-01-01

The Industrialized Building System (IBS) was recently introduced to minimize the time and cost of project construction. Accordingly, ensuring the integration of the connection of precast components in IBS structures is an important factor that ensures stability of buildings subjected to dynamic loads from earthquakes, vehicles, and machineries. However, structural engineers still lack knowledge on the proper connection and detailed joints of IBS structure construction. Therefore, this study proposes a special precast concrete wall-to-wall connection system for dynamic loads that resists multidirectional imposed loads and reduces vibration effects (PI2014701723). This system is designed to connect two adjacent precast wall panels by using two steel U-shaped channels (i.e., male and female joints). During casting, each joint is adapted for incorporation into a respective wall panel after considering the following conditions: one side of the steel channel opens into the thickness face of the panel; a U-shaped rubber is implemented between the two channels to dissipate the vibration effect; and bolts and nuts are used to create an extension between the two U-shaped male and female steel channels. The developed finite element model of the precast wall is subjected to cyclic loads to evaluate the performance of the proposed connection during an imposed dynamic load. Connection performance is then compared with conventional connections based on the energy dissipation, stress, deformation, and concrete damage in the plastic range. The proposed precast connection is capable of exceeding the energy absorption of precast walls subjected to dynamic load, thereby improving its resistance behavior in all principal directions.

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

PubMed

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

2010-04-01

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

Characterization of freshwater changes in lakes of Nahuel Huapi National Park produced by the 2011 Puyehue-Cordón Caulle eruption.

PubMed

Catán, Soledad Perez; Juarez, Natalia A; Bubach, Débora F

2016-10-01

This work supplies a characterization of the chemical properties, including data of dissolved major and minor components in surface and pore water collected in Argentinean lakes surrounding the impacted area of Puyehue-Cordón Caulle volcanic complex, in the 2011 eruption. The principal component analysis and Pollution Load Index were used for the identification of water changes by volcanic ashes deposited throughout 1 year of eruption. The element content between water column and pore water provided a direct evidence of the potential dissolution of the element. Many chemical transformations, after the pyroclastic material contacted with the freshwater, were observed such as large pH changes from 3.2 to 8.1, electrical conductivity of 28.9 to 457 μs/cm, and redox potential of 171 to 591 mV. The maximum concentrations measured of F, Al, and Hg were 600, 40, and 0.0382 μg/L respectively. These concentrations in water column were lower than the limit of aquatic life protection for chronic toxicity. The Pollution Load Index indicated very low pollution for sites far away from the volcano and moderated pollution in closely sites. The processes were stabilized at the end of the monitoring, 1 year after the eruption.

How multi segmental patterns deviate in spastic diplegia from typical developed.

PubMed

Zago, Matteo; Sforza, Chiarella; Bona, Alessia; Cimolin, Veronica; Costici, Pier Francesco; Condoluci, Claudia; Galli, Manuela

2017-10-01

The relationship between gait features and coordination in children with Cerebral Palsy is not sufficiently analyzed yet. Principal Component Analysis can help in understanding motion patterns decomposing movement into its fundamental components (Principal Movements). This study aims at quantitatively characterizing the functional connections between multi-joint gait patterns in Cerebral Palsy. 65 children with spastic diplegia aged 10.6 (SD 3.7) years participated in standardized gait analysis trials; 31 typically developing adolescents aged 13.6 (4.4) years were also tested. To determine if posture affects gait patterns, patients were split into Crouch and knee Hyperextension group according to knee flexion angle at standing. 3D coordinates of hips, knees, ankles, metatarsal joints, pelvis and shoulders were submitted to Principal Component Analysis. Four Principal Movements accounted for 99% of global variance; components 1-3 explained major sagittal patterns, components 4-5 referred to movements on frontal plane and component 6 to additional movement refinements. Dimensionality was higher in patients than in controls (p<0.01), and the Crouch group significantly differed from controls in the application of components 1 and 4-6 (p<0.05), while the knee Hyperextension group in components 1-2 and 5 (p<0.05). Compensatory strategies of children with Cerebral Palsy (interactions between main and secondary movement patterns), were objectively determined. Principal Movements can reduce the effort in interpreting gait reports, providing an immediate and quantitative picture of the connections between movement components. Copyright © 2017 Elsevier Ltd. All rights reserved.

A reduction in ag/residential signature conflict using principal components analysis of LANDSAT temporal data

NASA Technical Reports Server (NTRS)

Williams, D. L.; Borden, F. Y.

1977-01-01

Methods to accurately delineate the types of land cover in the urban-rural transition zone of metropolitan areas were considered. The application of principal components analysis to multidate LANDSAT imagery was investigated as a means of reducing the overlap between residential and agricultural spectral signatures. The statistical concepts of principal components analysis were discussed, as well as the results of this analysis when applied to multidate LANDSAT imagery of the Washington, D.C. metropolitan area.

Constrained Principal Component Analysis: Various Applications.

ERIC Educational Resources Information Center

Hunter, Michael; Takane, Yoshio

2002-01-01

Provides example applications of constrained principal component analysis (CPCA) that illustrate the method on a variety of contexts common to psychological research. Two new analyses, decompositions into finer components and fitting higher order structures, are presented, followed by an illustration of CPCA on contingency tables and the CPCA of…

Development of a 5-Component Balance for Water Tunnel Applications

NASA Technical Reports Server (NTRS)

Suarez, Carlos J.; Kramer, Brian R.; Smith, Brooke C.

1999-01-01

The principal objective of this research/development effort was to develop a multi-component strain gage balance to measure both static and dynamic forces and moments on models tested in flow visualization water tunnels. A balance was designed that allows measuring normal and side forces, and pitching, yawing and rolling moments (no axial force). The balance mounts internally in the model and is used in a manner typical of wind tunnel balances. The key differences between a water tunnel balance and a wind tunnel balance are the requirement for very high sensitivity since the loads are very low (typical normal force is 90 grams or 0.2 lbs), the need for water proofing the gage elements, and the small size required to fit into typical water tunnel models. The five-component balance was calibrated and demonstrated linearity in the responses of the primary components to applied loads, very low interactions between the sections and no hysteresis. Static experiments were conducted in the Eidetics water tunnel with delta wings and F/A-18 models. The data were compared to forces and moments from wind tunnel tests of the same or similar configurations. The comparison showed very good agreement, providing confidence that loads can be measured accurately in the water tunnel with a relatively simple multi-component internal balance. The success of the static experiments encouraged the use of the balance for dynamic experiments. Among the advantages of conducting dynamic tests in a water tunnel are less demanding motion and data acquisition rates than in a wind tunnel test (because of the low-speed flow) and the capability of performing flow visualization and force/moment (F/M) measurements simultaneously with relative simplicity. This capability of simultaneous flow visualization and for F/M measurements proved extremely useful to explain the results obtained during these dynamic tests. In general, the development of this balance should encourage the use of water tunnels for a wider range of quantitative and qualitative experiments, especially during the preliminary phase of aircraft design.

Public perceptions of key performance indicators of healthcare in Alberta, Canada.

PubMed

Northcott, Herbert C; Harvey, Michael D

2012-06-01

To examine the relationship between public perceptions of key performance indicators assessing various aspects of the health-care system. Cross-sequential survey research. Annual telephone surveys of random samples of adult Albertans selected by random digit dialing and stratified according to age, sex and region (n = 4000 for each survey year). The survey questionnaires included single-item measures of key performance indicators to assess public perceptions of availability, accessibility, quality, outcome and satisfaction with healthcare. Cronbach's α and factor analysis were used to assess the relationship between key performance indicators focusing on the health-care system overall and on a recent interaction with the health-care system. The province of Alberta, Canada during the years 1996-2004. Four thousand adults randomly selected each survey year. Survey questions measuring public perceptions of healthcare availability, accessibility, quality, outcome and satisfaction with healthcare. Factor analysis identified two principal components with key performance indicators focusing on the health system overall loading most strongly on the first component and key performance indicators focusing on the most recent health-care encounter loading most strongly on the second component. Assessments of the quality of care most recently received, accessibility of that care and perceived outcome of care tended to be higher than the more general assessments of overall health system quality and accessibility. Assessments of specific health-care encounters and more general assessments of the overall health-care system, while related, nevertheless comprise separate dimensions for health-care evaluation.

Cognitive Load in Voice Therapy Carry-Over Exercises.

PubMed

Iwarsson, Jenny; Morris, David Jackson; Balling, Laura Winther

2017-01-01

The cognitive load generated by online speech production may vary with the nature of the speech task. This article examines 3 speech tasks used in voice therapy carry-over exercises, in which a patient is required to adopt and automatize new voice behaviors, ultimately in daily spontaneous communication. Twelve subjects produced speech in 3 conditions: rote speech (weekdays), sentences in a set form, and semispontaneous speech. Subjects simultaneously performed a secondary visual discrimination task for which response times were measured. On completion of each speech task, subjects rated their experience on a questionnaire. Response times from the secondary, visual task were found to be shortest for the rote speech, longer for the semispontaneous speech, and longest for the sentences within the set framework. Principal components derived from the subjective ratings were found to be linked to response times on the secondary visual task. Acoustic measures reflecting fundamental frequency distribution and vocal fold compression varied across the speech tasks. The results indicate that consideration should be given to the selection of speech tasks during the process leading to automation of revised speech behavior and that self-reports may be a reliable index of cognitive load.

PCA Based Stress Monitoring of Cylindrical Specimens Using PZTs and Guided Waves

PubMed Central

Mujica, Luis; Ruiz, Magda; Camacho, Johanatan

2017-01-01

Since mechanical stress in structures affects issues such as strength, expected operational life and dimensional stability, a continuous stress monitoring scheme is necessary for a complete integrity assessment. Consequently, this paper proposes a stress monitoring scheme for cylindrical specimens, which are widely used in structures such as pipelines, wind turbines or bridges. The approach consists of tracking guided wave variations due to load changes, by comparing wave statistical patterns via Principal Component Analysis (PCA). Each load scenario is projected to the PCA space by means of a baseline model and represented using the Q-statistical indices. Experimental validation of the proposed methodology is conducted on two specimens: (i) a 12.7 mm (1/2″) diameter, 0.4 m length, AISI 1020 steel rod, and (ii) a 25.4 mm (1″) diameter, 6m length, schedule 40, A-106, hollow cylinder. Specimen 1 was subjected to axial loads, meanwhile specimen 2 to flexion. In both cases, simultaneous longitudinal and flexural guided waves were generated via piezoelectric devices (PZTs) in a pitch-catch configuration. Experimental results show the feasibility of the approach and its potential use as in-situ continuous stress monitoring application. PMID:29194384

Glycemic index and glycemic load in the Opuntia ficus-indica fruit

PubMed

Ibarra-Salas, María de Jesús; Novelo-Huerta, Hilda Irene; De León-Salas, Marcela Alejandra; Sánchez-Murillo, Mayra Elisa; Mata-Obregón, María Del Carmen; Garza-Juárez, Aurora de Jesús

2017-01-01

There is evidence that support the clinical usage of glycemic index (GI) and glycemic load (GL) in the prevention of chronic disease. To determine the GI and GL of the Opuntia ficus-indica fruit. An analytic, transversal study was made involving 25 healthy volunteers accepted by an informed consent with a normal body mass index, glucose, glycoside hemoglobin, cholesterol and serum triglycerides. The homogeneity of the population was evaluated with anthropometrical and biochemical data using principal component analysis (PCA). The equivalent of 50 g of carbohydrates test food (tuna) and 50 g of dextrose as food standard was provided for the measure of the glucose curve. The GI was determined by calculating the area under the curve by the triangulation method. The CG was reported as the product of IG by carbohydrate loading provided. The IG of the tuna was 48.01 ± 17.4, classified as low, while the CG was 24.0 ± 8.7 rated as high. The chemometric analysis by PCA showed that the selection of the normal population for determining the IG, it is important to consider the values of cholesterol and triglycerides. Copyright: © 2017 SecretarÍa de Salud

A measure for objects clustering in principal component analysis biplot: A case study in inter-city buses maintenance cost data

NASA Astrophysics Data System (ADS)

Ginanjar, Irlandia; Pasaribu, Udjianna S.; Indratno, Sapto W.

2017-03-01

This article presents the application of the principal component analysis (PCA) biplot for the needs of data mining. This article aims to simplify and objectify the methods for objects clustering in PCA biplot. The novelty of this paper is to get a measure that can be used to objectify the objects clustering in PCA biplot. Orthonormal eigenvectors, which are the coefficients of a principal component model representing an association between principal components and initial variables. The existence of the association is a valid ground to objects clustering based on principal axes value, thus if m principal axes used in the PCA, then the objects can be classified into 2m clusters. The inter-city buses are clustered based on maintenance costs data by using two principal axes PCA biplot. The buses are clustered into four groups. The first group is the buses with high maintenance costs, especially for lube, and brake canvass. The second group is the buses with high maintenance costs, especially for tire, and filter. The third group is the buses with low maintenance costs, especially for lube, and brake canvass. The fourth group is buses with low maintenance costs, especially for tire, and filter.

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.

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.

Geochemistry of sediments in the Northern and Central Adriatic Sea

NASA Astrophysics Data System (ADS)

De Lazzari, A.; Rampazzo, G.; Pavoni, B.

2004-03-01

Major, minor and trace elements, loss of ignition, specific surface area, quantities of calcite and dolomite, qualitative mineralogical composition, grain-size distribution and organic micropollutants (PAH, PCB, DDT) were determined on surficial marine sediments sampled during the 1990 ASCOP (Adriatic Scientific Cooperative Program) cruise. Mineralogical composition and carbonate content of the samples were found to be comparable with data previously reported in the literature, whereas geochemical composition and distribution of major, minor and trace elements for samples in international waters and in the central basin have never been reported before. The large amount of information contained in the variables of different origin has been processed by means of a comprehensive approach which establishes the relations among the components through the mathematical-statistical calculation of principal components (factors). These account for the major part of data variance loosing only marginal parts of information and are independent from the units of measure. The sample descriptors concerning natural components and contamination load are discussed by means of a statistical model based on an R-mode Factor analysis calculating four significant factors which explain 86.8% of the total variance, and represent important relationships between grain size, mineralogy, geochemistry and organic micropollutants. A description and an interpretation of factor composition is discussed on the basis of pollution inputs, basin geology and hydrodynamics. The areal distribution of the factors showed that it is the fine grain-size fraction, with oxides and hydroxides of colloidal origin, which are the main means of transport and thus the principal link between chemical, physical and granulometric elements in the Adriatic.

Facilitated Visual Interpretation of Scores in Principal Component Analysis by Bioactivity-Labeling of 1H-NMR Spectra-Metabolomics Investigation and Identification of a New α-Glucosidase Inhibitor in Radix Astragali.

PubMed

Liu, Yueqiu; Nyberg, Nils T; Jäger, Anna K; Staerk, Dan

2017-03-06

Radix Astragali is a component of several traditional medicines used for the treatment of type 2 diabetes in China. Radix Astragali is known to contain isoflavones, which inhibit α-glucosidase in the small intestines, and thus lowers the blood glucose levels. In this study, 21 samples obtained from different regions of China were extracted with ethyl acetate, then the IC50-values were determined, and the crude extracts were analyzed by 1H-NMR spectroscopy. A principal component analysis of the 1H-NMR spectra labeled with their IC50-values, that is, bioactivity-labeled 1H-NMR spectra, showed a clear correlation between spectral profiles and the α-glucosidase inhibitory activity. The loading plot and LC-HRMS/NMR of microfractions indicated that previously unknown long chain ferulates could be partly responsible for the observed antidiabetic activity of Radix Astragali. Subsequent preparative scale isolation revealed a compound not previously reported, linoleyl ferulate (1), showing α-glucosidase inhibitory activity (IC50 0.5 mM) at a level comparable to the previously studied isoflavones. A closely related analogue, hexadecyl ferulate (2), did not show significant inhibitory activity, and the double bonds in the alcohol part of 1 seem to be important structural features for the α-glucosidase inhibitory activity. This proof of concept study demonstrates that bioactivity-labeling of the 1H-NMR spectral data of crude extracts allows global and nonselective identification of individual constituents contributing to the crude extract's bioactivity.

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Structural analysis for a 40-story building

NASA Technical Reports Server (NTRS)

Hua, L.

1972-01-01

NASTRAN was chosen as the principal analytical tool for structural analysis of the Illinois Center Plaza Hotel Building in Chicago, Illinois. The building is a 40-story, reinforced concrete structure utilizing a monolithic slab-column system. The displacements, member stresses, and foundation loads due to wind load, live load, and dead load were obtained through a series of NASTRAN runs. These analyses and the input technique are described.

Multivariate classification of the infrared spectra of cell and tissue samples

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

Haaland, D.M.; Jones, H.D.; Thomas, E.V.

1997-03-01

Infrared microspectroscopy of biopsied canine lymph cells and tissue was performed to investigate the possibility of using IR spectra coupled with multivariate classification methods to classify the samples as normal, hyperplastic, or neoplastic (malignant). IR spectra were obtained in transmission mode through BaF{sub 2} windows and in reflection mode from samples prepared on gold-coated microscope slides. Cytology and histopathology samples were prepared by a variety of methods to identify the optimal methods of sample preparation. Cytospinning procedures that yielded a monolayer of cells on the BaF{sub 2} windows produced a limited set of IR transmission spectra. These transmission spectra weremore » converted to absorbance and formed the basis for a classification rule that yielded 100{percent} correct classification in a cross-validated context. Classifications of normal, hyperplastic, and neoplastic cell sample spectra were achieved by using both partial least-squares (PLS) and principal component regression (PCR) classification methods. Linear discriminant analysis applied to principal components obtained from the spectral data yielded a small number of misclassifications. PLS weight loading vectors yield valuable qualitative insight into the molecular changes that are responsible for the success of the infrared classification. These successful classification results show promise for assisting pathologists in the diagnosis of cell types and offer future potential for {ital in vivo} IR detection of some types of cancer. {copyright} {ital 1997} {ital Society for Applied Spectroscopy}« less

Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis

NASA Astrophysics Data System (ADS)

Bispo, Jeyse Aliana Martins; de Sousa Vieira, Elzo Everton; Silveira, Landulfo; Fernandes, Adriana Barrinha

2013-08-01

Patients with diabetes mellitus and hypertension (HT) diseases are predisposed to kidney diseases. The objective of this study was to identify potential biomarkers in the urine of diabetic and hypertensive patients through Raman spectroscopy in order to predict the evolution to complications and kidney failure. Urine samples were collected from control subjects (CTR) and patients with diabetes and HT with no complications (lower risk, LR), high degree of complications (higher risk, HR), and doing blood dialysis (DI). Urine samples were stored frozen (-20°C) before spectral analysis. Raman spectra were obtained using a dispersive spectrometer (830-nm, 300-mW power, and 20-s accumulation). Spectra were then submitted to principal component analysis (PCA) followed by discriminant analysis. The first PCA loading vectors revealed spectral features of urea, creatinine, and glucose. It has been found that the amounts of urea and creatinine decreased as disease evoluted from CTR to LR/HR and DI (PC1, p<0.05), and the amount of glucose increased in the urine of LR/HR compared to CTR (PC3, p<0.05). The discriminating model showed better overall classification rate of 70%. These results could lead to diagnostic information of possible complications and a better disease prognosis.

Correlating the amount of urea, creatinine, and glucose in urine from patients with diabetes mellitus and hypertension with the risk of developing renal lesions by means of Raman spectroscopy and principal component analysis.

PubMed

Bispo, Jeyse Aliana Martins; de Sousa Vieira, Elzo Everton; Silveira, Landulfo; Fernandes, Adriana Barrinha

2013-08-01

Patients with diabetes mellitus and hypertension (HT) diseases are predisposed to kidney diseases. The objective of this study was to identify potential biomarkers in the urine of diabetic and hypertensive patients through Raman spectroscopy in order to predict the evolution to complications and kidney failure. Urine samples were collected from control subjects (CTR) and patients with diabetes and HT with no complications (lower risk, LR), high degree of complications (higher risk, HR), and doing blood dialysis (DI). Urine samples were stored frozen (-20°C) before spectral analysis. Raman spectra were obtained using a dispersive spectrometer (830-nm, 300-mW power, and 20-s accumulation). Spectra were then submitted to principal component analysis (PCA) followed by discriminant analysis. The first PCA loading vectors revealed spectral features of urea, creatinine, and glucose. It has been found that the amounts of urea and creatinine decreased as disease evoluted from CTR to LR/HR and DI (PC1, p<0.05), and the amount of glucose increased in the urine of LR/HR compared to CTR (PC3, p<0.05). The discriminating model showed better overall classification rate of 70%. These results could lead to diagnostic information of possible complications and a better disease prognosis.

Label-free monitoring of inflammatory tissue conditions using a carrageenan-induced acute inflammation rat model.

PubMed

Lee, Seung Ho; Lee, Sang Hwa; Shin, Jae-Ho; Choi, Samjin

2018-06-01

Although the confirmation of inflammatory changes within tissues at the onset of various diseases is critical for the early detection of disease and selection of appropriate treatment, most therapies are based on complex and time-consuming diagnostic procedures. Raman spectroscopy has the ability to provide non-invasive, real-time, chemical bonding analysis through the inelastic scattering of photons. In this study, we evaluate the feasibility of Raman spectroscopy as a new, easy, fast, and accurate diagnostic method to support diagnostic decisions. The molecular changes in carrageenan-induced acute inflammation rat tissues were assessed by Raman spectroscopy. Volumes of 0 (control), 100, 150, and 200 µL of 1% carrageenan were administered to rat hind paws to control the degree of inflammation. The prominent peaks at [1,062, 1,131] cm -1 and [2,847, 2,881] cm -1 were selected as characteristic measurements corresponding to the C-C stretching vibrational modes and the symmetric and asymmetric C-H (CH 2 ) stretching vibrational modes, respectively. Principal component analysis of the inflammatory Raman spectra enabled graphical representation of the degree of inflammation through principal component loading profiles of inflammatory tissues on a two-dimensional plot. Therefore, Raman spectroscopy with multivariate statistical analysis represents a promising method for detecting biomolecular responses based on different types of inflammatory tissues. © 2018 Wiley Periodicals, Inc.

Response of aquatic macro-invertebrate diversity to environmental factors along the Lower Komati River in Swaziland

NASA Astrophysics Data System (ADS)

Dlamini, Vuyisile; Hoko, Zvikomborero; Murwira, Amon; Magagula, Cebisile

This paper assessed macro-invertebrates diversity as an indicator of aquatic ecosystem health in the Lower Komati River. It also investigated whether this diversity is a function of physico-chemical water quality parameters along an area with major agricultural activities. Bio-assessment of aquatic macro-invertebrates present in the Lower Komati River was carried out at seven sites on the river over 3 months. Water samples were also collected at these sites and analysed for pH, dissolved oxygen, electrical conductivity, turbidity, nitrates, ammonia and ortho-phosphates according to standard methods. It was found out that species diversity along agricultural fields was not significantly different ( p > 0.05) between successive sites. However, nitrate and turbidity among the physico-chemical parameters indicated a significant variation of mean values ( p < 0.05) between sites. With the exception of turbidity, no significant relationship ( p > 0.05) was found between diversity and water quality parameters. Principal Component Analysis also demonstrated the influence of turbidity in the sub-catchments as it was the only parameter that showed a significant loading in all Principal Components. Turbidity seems to be the main parameter influencing aquatic macro-invertebrate diversity in the Lower Komati River at the time of study. The study recommends further studies to determine the seasonal variation of the impact of water quality on macro-invertebrates diversity.

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations.

PubMed

Buras, Allan; van der Maaten-Theunissen, Marieke; van der Maaten, Ernst; Ahlgrimm, Svenja; Hermann, Philipp; Simard, Sonia; Heinrich, Ingo; Helle, Gerd; Unterseher, Martin; Schnittler, Martin; Eusemann, Pascal; Wilmking, Martin

2016-01-01

This paper introduces a new approach-the Principal Component Gradient Analysis (PCGA)-to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA.

Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations

PubMed Central

Buras, Allan; van der Maaten-Theunissen, Marieke; van der Maaten, Ernst; Ahlgrimm, Svenja; Hermann, Philipp; Simard, Sonia; Heinrich, Ingo; Helle, Gerd; Unterseher, Martin; Schnittler, Martin; Eusemann, Pascal; Wilmking, Martin

2016-01-01

This paper introduces a new approach–the Principal Component Gradient Analysis (PCGA)–to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA. PMID:27467508

Impact of remote sensing upon the planning, management, and development of water resources

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L.; Fowler, T. R.; Frech, S. L.

1975-01-01

Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.

Linear degrees of freedom in speech production: analysis of cineradio- and labio-film data and articulatory-acoustic modeling.

PubMed

Beautemps, D; Badin, P; Bailly, G

2001-05-01

The following contribution addresses several issues concerning speech degrees of freedom in French oral vowels, stop, and fricative consonants based on an analysis of tongue and lip shapes extracted from cineradio- and labio-films. The midsagittal tongue shapes have been submitted to a linear decomposition where some of the loading factors were selected such as jaw and larynx position while four other components were derived from principal component analysis (PCA). For the lips, in addition to the more traditional protrusion and opening components, a supplementary component was extracted to explain the upward movement of both the upper and lower lips in [v] production. A linear articulatory model was developed; the six tongue degrees of freedom were used as the articulatory control parameters of the midsagittal tongue contours and explained 96% of the tongue data variance. These control parameters were also used to specify the frontal lip width dimension derived from the labio-film front views. Finally, this model was complemented by a conversion model going from the midsagittal to the area function, based on a fitting of the midsagittal distances and the formant frequencies for both vowels and consonants.

Fatigue Life of Bovine Meniscus under Longitudinal and Transverse Tensile Loading

PubMed Central

Creechley, Jaremy J.; Krentz, Madison E.; Lujan, Trevor J.

2017-01-01

The knee meniscus is composed of a fibrous matrix that is subjected to large and repeated loads. Consequently, the meniscus is frequently torn, and a potential mechanism for failure is fatigue. The objective of this study was to measure the fatigue life of bovine meniscus when applying cyclic tensile loads either longitudinal or transverse to the principal fiber direction. Fatigue experiments consisted of cyclic loads to 60, 70, 80 or 90% of the predicted ultimate tensile strength until failure occurred or 20,000 cycles was reached. The fatigue data in each group was fit with a Weibull distribution to generate plots of stress level vs. cycles to failure (S-N curve). Results showed that loading transverse to the principal fiber direction gave a two-fold increase in failure strain, a three-fold increase in creep, and a nearly four-fold increase in cycles to failure (not significant), compared to loading longitudinal to the principal fiber direction. The S-N curves had strong negative correlations between the stress level and the mean cycles to failure for both loading directions, where the slope of the transverse S-N curve was 11% less than the longitudinal S-N curve (longitudinal: S=108–5.9ln(N); transverse: S=112–5.2ln(N)). Collectively, these results suggest that the non-fibrillar matrix is more resistant to fatigue failure than the collagen fibers. Results from this study are relevant to understanding the etiology of atraumatic radial and horizontal meniscal tears, and can be utilized by research groups that are working to develop meniscus implants with fatigue properties that mimic healthy tissue. PMID:28088070

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.

Strain distribution in the lumbar vertebrae under different loading configurations.

PubMed

Cristofolini, Luca; Brandolini, Nicola; Danesi, Valentina; Juszczyk, Mateusz M; Erani, Paolo; Viceconti, Marco

2013-10-01

The stress/strain distribution in the human vertebrae has seldom been measured, and only for a limited number of loading scenarios, at few locations on the bone surface. This in vitro study aimed at measuring how strain varies on the surface of the lumbar vertebral body and how such strain pattern depends on the loading conditions. Eight cadaveric specimens were instrumented with eight triaxial strain gauges each to measure the magnitude and direction of principal strains in the vertebral body. Each vertebra was tested in a three adjacent vertebrae segment fashion. The loading configurations included a compressive force aligned with the vertebral body but also tilted (15°) in each direction in the frontal and sagittal planes, a traction force, and torsion (both directions). Each loading configuration was tested six times on each specimen. The strain magnitude varied significantly between strain measurement locations. The strain distribution varied significantly when different loading conditions were applied (compression vs. torsion vs. traction). The strain distribution when the compressive force was tilted by 15° was also significantly different from the axial compression. Strains were minimal when the compressive force was applied coaxial with the vertebral body, compared with all other loading configurations. Also, strain was significantly more uniform for the axial compression, compared with all other loading configurations. Principal strains were aligned within 19° to the axis of the vertebral body for axial-compression and axial-traction. Conversely, when the applied force was tilted by 15°, the direction of principal strain varied by a much larger angle (15° to 28°). This is the first time, to our knowledge, that the strain distribution in the vertebral body is measured for such a variety of loading configurations and a large number of strain sensors. The present findings suggest that the structure of the vertebral body is optimized to sustain compressive forces, whereas even a small tilt angle makes the vertebral structure work under suboptimal conditions. Copyright © 2013 Elsevier Inc. All rights reserved.

Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices

PubMed Central

Meyer, Karin; Kirkpatrick, Mark

2005-01-01

Principal component analysis is a widely used 'dimension reduction' technique, albeit generally at a phenotypic level. It is shown that we can estimate genetic principal components directly through a simple reparameterisation of the usual linear, mixed model. This is applicable to any analysis fitting multiple, correlated genetic effects, whether effects for individual traits or sets of random regression coefficients to model trajectories. Depending on the magnitude of genetic correlation, a subset of the principal component generally suffices to capture the bulk of genetic variation. Corresponding estimates of genetic covariance matrices are more parsimonious, have reduced rank and are smoothed, with the number of parameters required to model the dispersion structure reduced from k(k + 1)/2 to m(2k - m + 1)/2 for k effects and m principal components. Estimation of these parameters, the largest eigenvalues and pertaining eigenvectors of the genetic covariance matrix, via restricted maximum likelihood using derivatives of the likelihood, is described. It is shown that reduced rank estimation can reduce computational requirements of multivariate analyses substantially. An application to the analysis of eight traits recorded via live ultrasound scanning of beef cattle is given. PMID:15588566

Recognition of units in coarse, unconsolidated braided-stream deposits from geophysical log data with principal components analysis

USGS Publications Warehouse

Morin, R.H.

1997-01-01

Returns from drilling in unconsolidated cobble and sand aquifers commonly do not identify lithologic changes that may be meaningful for Hydrogeologic investigations. Vertical resolution of saturated, Quaternary, coarse braided-slream deposits is significantly improved by interpreting natural gamma (G), epithermal neutron (N), and electromagnetically induced resistivity (IR) logs obtained from wells at the Capital Station site in Boise, Idaho. Interpretation of these geophysical logs is simplified because these sediments are derived largely from high-gamma-producing source rocks (granitics of the Boise River drainage), contain few clays, and have undergone little diagenesis. Analysis of G, N, and IR data from these deposits with principal components analysis provides an objective means to determine if units can be recognized within the braided-stream deposits. In particular, performing principal components analysis on G, N, and IR data from eight wells at Capital Station (1) allows the variable system dimensionality to be reduced from three to two by selecting the two eigenvectors with the greatest variance as axes for principal component scatterplots, (2) generates principal components with interpretable physical meanings, (3) distinguishes sand from cobble-dominated units, and (4) provides a means to distinguish between cobble-dominated units.

Analysis and Evaluation of the Characteristic Taste Components in Portobello Mushroom.

PubMed

Wang, Jinbin; Li, Wen; Li, Zhengpeng; Wu, Wenhui; Tang, Xueming

2018-05-10

To identify the characteristic taste components of the common cultivated mushroom (brown; Portobello), Agaricus bisporus, taste components in the stipe and pileus of Portobello mushroom harvested at different growth stages were extracted and identified, and principal component analysis (PCA) and taste active value (TAV) were used to reveal the characteristic taste components during the each of the growth stages of Portobello mushroom. In the stipe and pileus, 20 and 14 different principal taste components were identified, respectively, and they were considered as the principal taste components of Portobello mushroom fruit bodies, which included most amino acids and 5'-nucleotides. Some taste components that were found at high levels, such as lactic acid and citric acid, were not detected as Portobello mushroom principal taste components through PCA. However, due to their high content, Portobello mushroom could be used as a source of organic acids. The PCA and TAV results revealed that 5'-GMP, glutamic acid, malic acid, alanine, proline, leucine, and aspartic acid were the characteristic taste components of Portobello mushroom fruit bodies. Portobello mushroom was also found to be rich in protein and amino acids, so it might also be useful in the formulation of nutraceuticals and functional food. The results in this article could provide a theoretical basis for understanding and regulating the characteristic flavor components synthesis process of Portobello mushroom. © 2018 Institute of Food Technologists®.

Applications of principal component analysis to breath air absorption spectra profiles classification

NASA Astrophysics Data System (ADS)

Kistenev, Yu. V.; Shapovalov, A. V.; Borisov, A. V.; Vrazhnov, D. A.; Nikolaev, V. V.; Nikiforova, O. Y.

2015-12-01

The results of numerical simulation of application principal component analysis to absorption spectra of breath air of patients with pulmonary diseases are presented. Various methods of experimental data preprocessing are analyzed.

Platform switching: biomechanical evaluation using three-dimensional finite element analysis.

PubMed

Tabata, Lucas Fernando; Rocha, Eduardo Passos; Barão, Valentim Adelino Ricardo; Assunção, Wirley Goncalves

2011-01-01

The objective of this study was to evaluate, using three-dimensional finite element analysis (3D FEA), the stress distribution in peri-implant bone tissue, implants, and prosthetic components of implant-supported single crowns with the use of the platform-switching concept. Three 3D finite element models were created to replicate an external-hexagonal implant system with peri-implant bone tissue in which three different implant-abutment configurations were represented. In the regular platform (RP) group, a regular 4.1-mm-diameter abutment (UCLA) was connected to regular 4.1-mm-diameter implant. The platform-switching (PS) group was simulated by the connection of a wide implant (5.0 mm diameter) to a regular 4.1-mm-diameter UCLA abutment. In the wide-platform (WP) group, a 5.0-mm-diameter UCLA abutment was connected to a 5.0-mm-diameter implant. An occlusal load of 100 N was applied either axially or obliquely on the models using ANSYS software. Both the increase in implant diameter and the use of platform switching played roles in stress reduction. The PS group presented lower stress values than the RP and WP groups for bone and implant. In the peri-implant area, cortical bone exhibited a higher stress concentration than the trabecular bone in all models and both loading situations. Under oblique loading, higher intensity and greater distribution of stress were observed than under axial loading. Platform switching reduced von Mises (17.5% and 9.3% for axial and oblique loads, respectively), minimum (compressive) (19.4% for axial load and 21.9% for oblique load), and maximum (tensile) principal stress values (46.6% for axial load and 26.7% for oblique load) in the peri-implant bone tissue. Platform switching led to improved biomechanical stress distribution in peri-implant bone tissue. Oblique loads resulted in higher stress concentrations than axial loads for all models. Wide-diameter implants had a large influence in reducing stress values in the implant system.

Fatigue experience from tests carried out with forged beam and frame structures in the development of the Saab aircraft Viggen

NASA Technical Reports Server (NTRS)

Larsson, S. E.

1972-01-01

A part of the lower side of the main wing at the joint of the main spar with the fuselage frame was investigated. This wing beam area was simulated by a test specimen consisting of a spar boom of AZ 74 forging (7075 aluminum alloy modified with 0.3 percent Ag) and a portion of a honeycomb sandwich panel attached to the boom flange with steel bolts. The cross section was reduced to half scale. However, the flange thickness, the panel height, and the bolt size were full scale. Further, left and right portions of the fuselage frame intended to carry over the bending moment of the main wing were tested. Each of these frame halves consisted of a forward and a rear forging (7079 aluminum alloy, overaged) connected by an outer and inner skin (Alclad 7075) creating a box beam. These test specimens were full scale and were constructed principally of ordinary aircraft components. The test load spectrum was common to both types of specimens with regard to percentage levels. It consisted of maneuver and gust loads, touchdown loads, and loads due to ground roughness. A load history of 200 hours of flight with 15,000 load cycles was punched on a tape. The loads were randomized in groups according to the flight-by-flight principle. The highest positive load level was 90 percent of limit load and the largest negative load was -27 percent. A total of 20 load levels were used. Both types of specimens were provided with strain gages and had a nominal stress of about 300 MN/sq m in some local areas. As a result of the tests, steps were taken to reduce the risk of fatigue damage in aircraft. Thus stress levels were lowered, radii were increased, and demands on surface finish were sharpened.

[The principal components analysis--method to classify the statistical variables with applications in medicine].

PubMed

Dascălu, Cristina Gena; Antohe, Magda Ecaterina

2009-01-01

Based on the eigenvalues and the eigenvectors analysis, the principal component analysis has the purpose to identify the subspace of the main components from a set of parameters, which are enough to characterize the whole set of parameters. Interpreting the data for analysis as a cloud of points, we find through geometrical transformations the directions where the cloud's dispersion is maximal--the lines that pass through the cloud's center of weight and have a maximal density of points around them (by defining an appropriate criteria function and its minimization. This method can be successfully used in order to simplify the statistical analysis on questionnaires--because it helps us to select from a set of items only the most relevant ones, which cover the variations of the whole set of data. For instance, in the presented sample we started from a questionnaire with 28 items and, applying the principal component analysis we identified 7 principal components--or main items--fact that simplifies significantly the further data statistical analysis.

On Using the Average Intercorrelation Among Predictor Variables and Eigenvector Orientation to Choose a Regression Solution.

ERIC Educational Resources Information Center

Mugrage, Beverly; And Others

Three ridge regression solutions are compared with ordinary least squares regression and with principal components regression using all components. Ridge regression, particularly the Lawless-Wang solution, out-performed ordinary least squares regression and the principal components solution on the criteria of stability of coefficient and closeness…

A Note on McDonald's Generalization of Principal Components Analysis

ERIC Educational Resources Information Center

Shine, Lester C., II

1972-01-01

It is shown that McDonald's generalization of Classical Principal Components Analysis to groups of variables maximally channels the totalvariance of the original variables through the groups of variables acting as groups. An equation is obtained for determining the vectors of correlations of the L2 components with the original variables.…

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

PubMed Central

Peterson, Leif E

2002-01-01

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

Assessment of an improved hydrological loading model from space geodesy: case study in South America

NASA Astrophysics Data System (ADS)

Nicolas, Joëlle; Boy, Jean-Paul; Durand, Frédéric; Mémin, Anthony

2017-04-01

Loading effects are crustal deformations induced by ocean, atmosphere and continental water mass redistributions. In this study we focus on hydrological loading effect monitored by space geodesy and in particular by GNSS and GRACE. Classically, hydrological loading models take into account snow and soil-moisture but don't consider surface waters (rivers, lakes…). As a result, huge discrepancies between GPS observations and those models arise around large rivers such as the Amazon where nearly half of the vertical signal cannot be explained by the combination of atmospheric, oceanic and hydrological loading models. To better resolve the hydrological signal, we improve the continental water storage models computed from soil-moisture and snow GLDAS/Noah or MERRA data sets by including surface water runoff. We investigate how continental water storage model improvements are supported by GNSS and GRACE observations in South America main river basins: Amazon, Orinoco and Parana. In this area the hydrological effects are among the largest in the world mainly due to the river level variations. We present the results of time series analyses with spectral and principal component analysis (PCA) methods. We extract the dominant spatio-temporal annual mode. We also identify and characterize the spatio-temporal changes in the annual hydrology signal, which is the key to a better understanding of the water cycle variations of those major rivers. We demonstrate that it is crucial to take into account the river contribution in fluid signatures before investigating high-frequency variability and episodic events.

The Complexity of Human Walking: A Knee Osteoarthritis Study

PubMed Central

Kotti, Margarita; Duffell, Lynsey D.; Faisal, Aldo A.; McGregor, Alison H.

2014-01-01

This study proposes a framework for deconstructing complex walking patterns to create a simple principal component space before checking whether the projection to this space is suitable for identifying changes from the normality. We focus on knee osteoarthritis, the most common knee joint disease and the second leading cause of disability. Knee osteoarthritis affects over 250 million people worldwide. The motivation for projecting the highly dimensional movements to a lower dimensional and simpler space is our belief that motor behaviour can be understood by identifying a simplicity via projection to a low principal component space, which may reflect upon the underlying mechanism. To study this, we recruited 180 subjects, 47 of which reported that they had knee osteoarthritis. They were asked to walk several times along a walkway equipped with two force plates that capture their ground reaction forces along 3 axes, namely vertical, anterior-posterior, and medio-lateral, at 1000 Hz. Data when the subject does not clearly strike the force plate were excluded, leaving 1–3 gait cycles per subject. To examine the complexity of human walking, we applied dimensionality reduction via Probabilistic Principal Component Analysis. The first principal component explains 34% of the variance in the data, whereas over 80% of the variance is explained by 8 principal components or more. This proves the complexity of the underlying structure of the ground reaction forces. To examine if our musculoskeletal system generates movements that are distinguishable between normal and pathological subjects in a low dimensional principal component space, we applied a Bayes classifier. For the tested cross-validated, subject-independent experimental protocol, the classification accuracy equals 82.62%. Also, a novel complexity measure is proposed, which can be used as an objective index to facilitate clinical decision making. This measure proves that knee osteoarthritis subjects exhibit more variability in the two-dimensional principal component space. PMID:25232949

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;

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

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

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

DETERMINANTS OF SPECIALTY CHOICE OF RESIDENT DOCTORS; CASE STUDY--AMONG RESIDENT DOCTORS IN NIGERIA.

PubMed

Osuoji, Roland I; Adebanji, Atinuke; Abdulsalam, Moruf A; Oludara, Mobolaji A; Abolarinwa, Abimbola A

2015-01-01

This study examined medical specialty selection by Nigerian resident doctors using a marketing research approach to determine the selection criteria and the role of perceptions, expected remuneration, and job placement prospects of various specialties in the selection process. Data were from the Community of residents from April 2014 to July 2014. The cohort included 200 residents, but only 171 had complete information. Data were obtained from a cross section of resident doctors in the Lagos State University Teaching Hospital and at the 2014 Ordinary General Meeting of the National Association of Resident Doctors(NARD) where representatives from over 50 Teaching hospitals in Nigeria attended. Using a client behaviour model as a framework, a tripartite questionnaire was designed and administered to residents to deduce information on their knowledge about and interests in various specialties, their opinions of sixteen specialties, and the criteria they used in specialty selection. A total of 171 (85.5%) questionnaires were returned. ln many instances, consistency between selection criteria and perceptions of a specialty were accompanied by interest in pursuing the specialty. Job security, job availability on completion of programme, duration of training and qualifying examinations were highly correlated with p value < 0.05. Results of the Principal Component Analysis show two components (with Eigen values greater than one) explaining 65.3% of the total variance. The first component had placement and training and practice related variables loaded on it while the second component was loaded with job security and financial remuneration related variables. Using marketing research concepts for medical specialty selection (Weissmanet al 2012) stipulates that choice of speciality is influenced by criteria and perception. This study shows that job security expected financial remuneration, and examination requirements for qualification are major determinants of the choice of speciality for residents.

The relation of object naming and other visual speech production tasks: a large scale voxel-based morphometric study.

PubMed

Lau, Johnny King L; Humphreys, Glyn W; Douis, Hassan; Balani, Alex; Bickerton, Wai-Ling; Rotshtein, Pia

2015-01-01

We report a lesion-symptom mapping analysis of visual speech production deficits in a large group (280) of stroke patients at the sub-acute stage (<120 days post-stroke). Performance on object naming was evaluated alongside three other tests of visual speech production, namely sentence production to a picture, sentence reading and nonword reading. A principal component analysis was performed on all these tests' scores and revealed a 'shared' component that loaded across all the visual speech production tasks and a 'unique' component that isolated object naming from the other three tasks. Regions for the shared component were observed in the left fronto-temporal cortices, fusiform gyrus and bilateral visual cortices. Lesions in these regions linked to both poor object naming and impairment in general visual-speech production. On the other hand, the unique naming component was potentially associated with the bilateral anterior temporal poles, hippocampus and cerebellar areas. This is in line with the models proposing that object naming relies on a left-lateralised language dominant system that interacts with a bilateral anterior temporal network. Neuropsychological deficits in object naming can reflect both the increased demands specific to the task and the more general difficulties in language processing.

Cerebrovascular Injury in Blast Loading

DTIC Science & Technology

2010-01-01

TITLE: Cerebrovascular injury in blast loading PRINCIPAL INVESTIGATOR: Kenneth L. Monson, PhD...SUBTITLE Cerebrovascular injury in blast loading 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-08-1-0295 5c. PROGRAM ELEMENT NUMBER 6...and pH control. 15. SUBJECT TERMS Blast brain injury; cerebrovascular injury and dysfunction; shock tube 16. SECURITY CLASSIFICATION OF: 17

Assessment of second- and third-order ionospheric effects on regional networks: case study in China with longer CMONOC GPS coordinate time series

NASA Astrophysics Data System (ADS)

Deng, Liansheng; Jiang, Weiping; Li, Zhao; Chen, Hua; Wang, Kaihua; Ma, Yifang

2017-02-01

Higher-order ionospheric (HOI) delays are one of the principal technique-specific error sources in precise global positioning system analysis and have been proposed to become a standard part of precise GPS data processing. In this research, we apply HOI delay corrections to the Crustal Movement Observation Network of China's (CMONOC) data processing (from January 2000 to December 2013) and furnish quantitative results for the effects of HOI on CMONOC coordinate time series. The results for both a regional reference frame and global reference frame are analyzed and compared to clarify the HOI effects on the CMONOC network. We find that HOI corrections can effectively reduce the semi-annual signals in the northern and vertical components. For sites with lower semi-annual amplitudes, the average decrease in magnitude can reach 30 and 10 % for the northern and vertical components, respectively. The noise amplitudes with HOI corrections and those without HOI corrections are not significantly different. Generally, the HOI effects on CMONOC networks in a global reference frame are less obvious than the results in the regional reference frame, probably because the HOI-induced errors are smaller in comparison to the higher noise levels seen when using a global reference frame. Furthermore, we investigate the combined contributions of environmental loading and HOI effects on the CMONOC stations. The largest loading effects on the vertical displacement are found in the mid- to high-latitude areas. The weighted root mean square differences between the corrected and original weekly GPS height time series of the loading model indicate that the mass loading adequately reduced the scatter on the CMONOC height time series, whereas the results in the global reference frame showed better agreements between the GPS coordinate time series and the environmental loading. When combining the effects of environmental loading and HOI corrections, the results with the HOI corrections reduced the scatter on the observed GPS height coordinates better than the height when estimated without HOI corrections, and the combined solutions in the regional reference frame indicate more preferred improvements. Therefore, regional reference frames are recommended to investigate the HOI effects on regional networks.

Explaining and modeling the concentration and loading of Escherichia coli in a stream-A case study.

PubMed

Wang, Chaozi; Schneider, Rebecca L; Parlange, Jean-Yves; Dahlke, Helen E; Walter, M Todd

2018-09-01

Escherichia coli (E. coli) level in streams is a public health indicator. Therefore, being able to explain why E. coli levels are sometimes high and sometimes low is important. Using citizen science data from Fall Creek in central NY we found that complementarily using principal component analysis (PCA) and partial least squares (PLS) regression provided insights into the drivers of E. coli and a mechanism for predicting E. coli levels, respectively. We found that stormwater, temperature/season and shallow subsurface flow are the three dominant processes driving the fate and transport of E. coli. PLS regression modeling provided very good predictions under stormwater conditions (R 2  = 0.85 for log (E. coli concentration) and R 2  = 0.90 for log (E. coli loading)); predictions under baseflow conditions were less robust. But, in our case, both E. coli concentration and E. coli loading were significantly higher under stormwater condition, so it is probably more important to predict high-flow E. coli hazards than low-flow conditions. Besides previously reported good indicators of in-stream E. coli level, nitrate-/nitrite-nitrogen and soluble reactive phosphorus were also found to be good indicators of in-stream E. coli levels. These findings suggest management practices to reduce E. coli concentrations and loads in-streams and, eventually, reduce the risk of waterborne disease outbreak. Copyright © 2018. Published by Elsevier B.V.

Assessment of Cr, Ni and Pb Pollution in Rural Agricultural Soils of Tonalite-Trondjhemite Series in Central India.

PubMed

Shukla, Kriti; Kumar, Bijendra; Agrawal, Rahul; Priyanka, Kumari; Venkatesh, Madavi; Anshumali

2017-06-01

Chromium (Cr), nickel (Ni) and lead (Pb) contamination was investigated in wheat cultivated rain-fed and irrigated rural agricultural soils (n = 31) of Tonalite-Trondjhemite Series in Central India. The soil sampling was carried out by using stratified random sampling method. The mean concentrations of Cr, Ni and Pb were 54.8, 38.1 and 68.9 mg/kg, respectively. The average values of enrichment factor (EF), geoaccumulation index (I geo ) and contamination factor (CF) followed the order as: Pb > Ni > Cr. Distribution patterns of soil parent material and weathering processes govern mineral enrichments, irrespective of rainfed or irrigated agricultural practices. Principal component analysis (PCA) showed strong loading of Cr and Ni (PC1) and Pb and clay (PC3). The strong loading on Cr and Ni indicates soils are originating from basic and volcanic rocks in the study area. The strong loading of Pb and clay indicates Pb is strongly adsorbed on clay minerals and Fe-oxides. The cancer risk (CR) index showed negligible carcinogenic risk to the residing population. However, hazard index (HI) values for children exceed the safe limit (HI > 1) for Cr and Pb. Spatial distribution of pollution load index suggest highest pollution in the northeastern part of the district. The study revealed that geogenically enriched soils of the area are suitable for agricultural activities under present conditions.

Biomechanical responses due to discitis infection of a juvenile thoracolumbar spine using finite element modeling.

PubMed

Davidson Jebaseelan, D; Jebaraj, C; Yoganandan, N; Rajasekaran, S; Yerramshetty, J

2014-07-01

Growth modulation changes occur in pediatric spines and lead to kyphotic deformity during discitis infection from mechanical forces. The present study was done to understand the consequences of discitis by simulating inflammatory puss at the T12/L1 disc space using a validated eight-year-old thoracolumbar spine finite element model. Changes in the biomechanical responses of the bone, disc and ligaments were determined under physiological compression and flexion loads in the intact and discitis models. During flexion, the angular-displacement increased by 3.33 times the intact spine and localized at the infected junction (IJ). The IJ became a virtual hinge. During compression loading, higher stresses occurred in the growth plate superior to the IJ. The components of the principal stresses in the growth plates at the T12/L1 junction indicated differential stresses. The strain increased by 143% during flexion loading in the posterior ligaments. The study indicates that the flexible pediatric spine increases the motion of the infected spine during physiological loadings. Understanding intrinsic responses around growth plates is important within the context of growth modulation in children. These results are clinically relevant as it might help surgeons to come up with better decisions while developing treatment protocols or performing surgeries. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Maine Chance.

ERIC Educational Resources Information Center

Trotter, Andrew

1992-01-01

While Principal Norman Higgins was speaking at an out-of-town conference, his high school faculty voted to cancel final exams for seniors and hold a morale-raising picnic. Although some principals dole out site-based power only grudgingly, Higgins takes his coordinator role seriously and delegates loads of responsibility. This article details…

Factors associated with successful transition among children with disabilities in eight European countries

PubMed Central

2017-01-01

Introduction This research paper aims to assess factors reported by parents associated with the successful transition of children with complex additional support requirements that have undergone a transition between school environments from 8 European Union member states. Methods Quantitative data were collected from 306 parents within education systems from 8 EU member states (Bulgaria, Cyprus, Greece, Ireland, the Netherlands, Romania, Spain and the UK). The data were derived from an online questionnaire and consisted of 41 questions. Information was collected on: parental involvement in their child’s transition, child involvement in transition, child autonomy, school ethos, professionals’ involvement in transition and integrated working, such as, joint assessment, cooperation and coordination between agencies. Survey questions that were designed on a Likert-scale were included in the Principal Components Analysis (PCA), additional survey questions, along with the results from the PCA, were used to build a logistic regression model. Results Four principal components were identified accounting for 48.86% of the variability in the data. Principal component 1 (PC1), ‘child inclusive ethos,’ contains 16.17% of the variation. Principal component 2 (PC2), which represents child autonomy and involvement, is responsible for 8.52% of the total variation. Principal component 3 (PC3) contains questions relating to parental involvement and contributed to 12.26% of the overall variation. Principal component 4 (PC4), which involves transition planning and coordination, contributed to 11.91% of the overall variation. Finally, the principal components were included in a logistic regression to evaluate the relationship between inclusion and a successful transition, as well as whether other factors that may have influenced transition. All four principal components were significantly associated with a successful transition, with PC1 being having the most effect (OR: 4.04, CI: 2.43–7.18, p<0.0001). Discussion To support a child with complex additional support requirements through transition from special school to mainstream, governments and professionals need to ensure children with additional support requirements and their parents are at the centre of all decisions that affect them. It is important that professionals recognise the educational, psychological, social and cultural contexts of a child with additional support requirements and their families which will provide a holistic approach and remove barriers for learning. PMID:28636649

Factors associated with successful transition among children with disabilities in eight European countries.

PubMed

Ravenscroft, John; Wazny, Kerri; Davis, John M

2017-01-01

This research paper aims to assess factors reported by parents associated with the successful transition of children with complex additional support requirements that have undergone a transition between school environments from 8 European Union member states. Quantitative data were collected from 306 parents within education systems from 8 EU member states (Bulgaria, Cyprus, Greece, Ireland, the Netherlands, Romania, Spain and the UK). The data were derived from an online questionnaire and consisted of 41 questions. Information was collected on: parental involvement in their child's transition, child involvement in transition, child autonomy, school ethos, professionals' involvement in transition and integrated working, such as, joint assessment, cooperation and coordination between agencies. Survey questions that were designed on a Likert-scale were included in the Principal Components Analysis (PCA), additional survey questions, along with the results from the PCA, were used to build a logistic regression model. Four principal components were identified accounting for 48.86% of the variability in the data. Principal component 1 (PC1), 'child inclusive ethos,' contains 16.17% of the variation. Principal component 2 (PC2), which represents child autonomy and involvement, is responsible for 8.52% of the total variation. Principal component 3 (PC3) contains questions relating to parental involvement and contributed to 12.26% of the overall variation. Principal component 4 (PC4), which involves transition planning and coordination, contributed to 11.91% of the overall variation. Finally, the principal components were included in a logistic regression to evaluate the relationship between inclusion and a successful transition, as well as whether other factors that may have influenced transition. All four principal components were significantly associated with a successful transition, with PC1 being having the most effect (OR: 4.04, CI: 2.43-7.18, p<0.0001). To support a child with complex additional support requirements through transition from special school to mainstream, governments and professionals need to ensure children with additional support requirements and their parents are at the centre of all decisions that affect them. It is important that professionals recognise the educational, psychological, social and cultural contexts of a child with additional support requirements and their families which will provide a holistic approach and remove barriers for learning.

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

PubMed

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

2014-03-01

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

Principal components of wrist circumduction from electromagnetic surgical tracking.

PubMed

Rasquinha, Brian J; Rainbow, Michael J; Zec, Michelle L; Pichora, David R; Ellis, Randy E

2017-02-01

An electromagnetic (EM) surgical tracking system was used for a functionally calibrated kinematic analysis of wrist motion. Circumduction motions were tested for differences in subject gender and for differences in the sense of the circumduction as clockwise or counter-clockwise motion. Twenty subjects were instrumented for EM tracking. Flexion-extension motion was used to identify the functional axis. Subjects performed unconstrained wrist circumduction in a clockwise and counter-clockwise sense. Data were decomposed into orthogonal flexion-extension motions and radial-ulnar deviation motions. PCA was used to concisely represent motions. Nonparametric Wilcoxon tests were used to distinguish the groups. Flexion-extension motions were projected onto a direction axis with a root-mean-square error of [Formula: see text]. Using the first three principal components, there was no statistically significant difference in gender (all [Formula: see text]). For motion sense, radial-ulnar deviation distinguished the sense of circumduction in the first principal component ([Formula: see text]) and in the third principal component ([Formula: see text]); flexion-extension distinguished the sense in the second principal component ([Formula: see text]). The clockwise sense of circumduction could be distinguished by a multifactorial combination of components; there were no gender differences in this small population. These data constitute a baseline for normal wrist circumduction. The multifactorial PCA findings suggest that a higher-dimensional method, such as manifold analysis, may be a more concise way of representing circumduction in human joints.

Metabolite profiling of Clinacanthus nutans leaves extracts obtained from different drying methods by 1H NMR-based metabolomics

NASA Astrophysics Data System (ADS)

Hashim, Noor Haslinda Noor; Latip, Jalifah; Khatib, Alfi

2016-11-01

The metabolites of Clinacanthus nutans leaves extracts and their dependence on drying process were systematically characterized using 1H nuclear magnetic resonance spectroscopy (NMR) multivariate data analysis. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) were able to distinguish the leaves extracts obtained from different drying methods. The identified metabolites were carbohydrates, amino acid, flavonoids and sulfur glucoside compounds. The major metabolites responsible for the separation in PLS-DA loading plots were lupeol, cycloclinacosides, betulin, cerebrosides and choline. The results showed that the combination of 1H NMR spectroscopy and multivariate data analyses could act as an efficient technique to understand the C. nutans composition and its variation.

Metabolic fingerprinting of Angelica sinensis during growth using UPLC-TOFMS and chemometrics data analysis

PubMed Central

2013-01-01

Background The radix of Angelica sinensis is widely used as a medicinal herbal and metabolomics research of this plant during growth is necessary. Results Principal component analysis of the UPLC-QTOFMS data showed that these 27 samples could be separated into 4 different groups. The chemical markers accounting for these separations were identified from the PCA loadings plot. These markers were further verified by accurate mass tandem mass and retention times of available reference standards. The study has shown that accumulation of secondary metabolites of Angelica sinensis is closely related to the growth periods. Conclusions The UPLC-QTOFMS based metabolomics approach has great potential for analysis of the alterations of secondary metabolites of Angelica sinensis during growth. PMID:23453085

Solar Spectral Radiative Forcing Due to Dust Aerosol During the Puerto Rico Dust Experiment

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Bergstrom, R.; Rabbette, M.; Livingston, J.; Russell, P.; Gore, Warren J. (Technical Monitor)

2000-01-01

During the Puerto Rico Dust Experiment (PRIDE) upwelling and downwelling solar spectral irradiance was measured on board the SPAWAR Navajo and downwelling solar spectral flux was measured at a surface site using the NASA Ames Solar Spectral Flux Radiometer. These data will be used to determine the net solar radiative forcing of dust aerosol and to quantify the solar spectral radiative energy budget in the presence of elevated aerosol loading. We will assess the variability in spectral irradiance using formal principal component analysis procedures and relate the radiative variability to aerosol microphysical properties. Finally, we will characterize the sea surface reflectance to improve aerosol optical depth retrievals from the AVHRR satellite and to validate SeaWiFS ocean color products.

Evaluating cumulative effects of anthropogenic inputs in Prince Edward Island estuaries using the mummichog (Fundulus heteroclitus).

PubMed

Finley, Megan A; Courtenay, Simon C; Teather, Kevin L; Hewitt, L Mark; Holdway, D A; Hogan, Natacha S; van den Heuvel, Michael R

2013-07-01

Estuarine eutrophication as a result of agricultural land use, including the use of chemical fertilizers, is increasing worldwide. Prince Edward Island (PEI), Canada has very high agricultural intensity by international standards with approximately 44% of the land area under production, and some watersheds in excess of 75% agricultural land-use. The type of agriculture is also intensive with primarily row crops that have high chemical fertilizer and pesticide usage. In light of these stressors, the hypothesis of this study was that mummichog (Fundulus heteroclitus) population parameters would change with point and nonpoint source pollution, and that multivariate statistics could be used to draw associations with specific stressors. Fish were sampled on a monthly basis from May through August at 7 estuaries spanning a range of land use, nutrient, and contaminant loadings. A suite of environmental variables were simplified into 3 principal components: PC1 representing agricultural land use, N loading, and plant habitat, PC2 being dominated by sediment sand and silt distribution, and PC3 largely reflecting P loading and sediment organic matter. There were significant differences in abundance of both adult and young-of-the-year mummichog, and these changes associated most strongly with PC1, the largely N-driven agricultural influences. In contrast, somatic variables such as liver and gonad size did not show strong association with the environmental quality principal component scores. The sand and silt PC2 appeared to have the opposite association with the biological data, with siltier environments correlating to older, larger, less dense populations of mummichog. Although pesticide residues were detected in estuarine sediment, there was no clear relationship between these and watershed agricultural intensity or biochemical indicators. There was, however, a strong relationship between agricultural environmental variables (PC1) and in vitro steroid production that is suggestive of a potential chemical effect. Eutrophication appeared to be a primary stressor affecting mummichog populations, as nutrient enrichment was associated with changes in habitat variables and these in turn were associated with high mummichog density. Thus, mummichog population demographics appear to have use as an indicator of adverse or worsening conditions in estuaries. We concluded that, based on the subset of environmental factors evaluated, the nonpoint-source inputs of sediments and nutrients exerted the greatest influence on mummichog populations in PEI estuaries. Copyright © 2013 SETAC.

Introduction to uses and interpretation of principal component analyses in forest biology.

Treesearch

J. G. Isebrands; Thomas R. Crow

1975-01-01

The application of principal component analysis for interpretation of multivariate data sets is reviewed with emphasis on (1) reduction of the number of variables, (2) ordination of variables, and (3) applications in conjunction with multiple regression.

Principal component analysis of phenolic acid spectra

USDA-ARS?s Scientific Manuscript database

Phenolic acids are common plant metabolites that exhibit bioactive properties and have applications in functional food and animal feed formulations. The ultraviolet (UV) and infrared (IR) spectra of four closely related phenolic acid structures were evaluated by principal component analysis (PCA) to...

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.

Facilitating in vivo tumor localization by principal component analysis based on dynamic fluorescence molecular imaging

NASA Astrophysics Data System (ADS)

Gao, Yang; Chen, Maomao; Wu, Junyu; Zhou, Yuan; Cai, Chuangjian; Wang, Daliang; Luo, Jianwen

2017-09-01

Fluorescence molecular imaging has been used to target tumors in mice with xenograft tumors. However, tumor imaging is largely distorted by the aggregation of fluorescent probes in the liver. A principal component analysis (PCA)-based strategy was applied on the in vivo dynamic fluorescence imaging results of three mice with xenograft tumors to facilitate tumor imaging, with the help of a tumor-specific fluorescent probe. Tumor-relevant features were extracted from the original images by PCA and represented by the principal component (PC) maps. The second principal component (PC2) map represented the tumor-related features, and the first principal component (PC1) map retained the original pharmacokinetic profiles, especially of the liver. The distribution patterns of the PC2 map of the tumor-bearing mice were in good agreement with the actual tumor location. The tumor-to-liver ratio and contrast-to-noise ratio were significantly higher on the PC2 map than on the original images, thus distinguishing the tumor from its nearby fluorescence noise of liver. The results suggest that the PC2 map could serve as a bioimaging marker to facilitate in vivo tumor localization, and dynamic fluorescence molecular imaging with PCA could be a valuable tool for future studies of in vivo tumor metabolism and progression.

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

NASA Astrophysics Data System (ADS)

Ueki, Kenta; Iwamori, Hikaru

2017-10-01

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

Assessment of New Load Schedules for the Machine Calibration of a Force Balance

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Gisler, R.; Kew, R.

2015-01-01

New load schedules for the machine calibration of a six-component force balance are currently being developed and evaluated at the NASA Ames Balance Calibration Laboratory. One of the proposed load schedules is discussed in the paper. It has a total of 2082 points that are distributed across 16 load series. Several criteria were applied to define the load schedule. It was decided, for example, to specify the calibration load set in force balance format as this approach greatly simplifies the definition of the lower and upper bounds of the load schedule. In addition, all loads are assumed to be applied in a calibration machine by using the one-factor-at-a-time approach. At first, all single-component loads are applied in six load series. Then, three two-component load series are applied. They consist of the load pairs (N1, N2), (S1, S2), and (RM, AF). Afterwards, four three-component load series are applied. They consist of the combinations (N1, N2, AF), (S1, S2, AF), (N1, N2, RM), and (S1, S2, RM). In the next step, one four-component load series is applied. It is the load combination (N1, N2, S1, S2). Finally, two five-component load series are applied. They are the load combination (N1, N2, S1, S2, AF) and (N1, N2, S1, S2, RM). The maximum difference between loads of two subsequent data points of the load schedule is limited to 33 % of capacity. This constraint helps avoid unwanted load "jumps" in the load schedule that can have a negative impact on the performance of a calibration machine. Only loadings of the single- and two-component load series are loaded to 100 % of capacity. This approach was selected because it keeps the total number of calibration points to a reasonable limit while still allowing for the application of some of the more complex load combinations. Data from two of NASA's force balances is used to illustrate important characteristics of the proposed 2082-point calibration load schedule.

Sample displacement chromatography as a method for purification of proteins and peptides from complex mixtures

PubMed Central

Gajdosik, Martina Srajer; Clifton, James; Josic, Djuro

2012-01-01

Sample displacement chromatography (SDC) in reversed-phase and ion-exchange modes was introduced approximately twenty years ago. This method takes advantage of relative binding affinities of components in a sample mixture. During loading, there is a competition among different sample components for the sorption on the surface of the stationary phase. SDC was first used for the preparative purification of proteins. Later, it was demonstrated that this kind of chromatography can also be performed in ion-exchange, affinity and hydrophobic-interaction mode. It has also been shown that SDC can be performed on monoliths and membrane-based supports in both analytical and preparative scale. Recently, SDC in ion-exchange and hydrophobic interaction mode was also employed successfully for the removal of trace proteins from monoclonal antibody preparations and for the enrichment of low abundance proteins from human plasma. In this review, the principals of SDC are introduced, and the potential for separation of proteins and peptides in micro-analytical, analytical and preparative scale is discussed. PMID:22520159

Implant-Supported Fixed Partial Prostheses With Different Prosthetic Materials: A Three-Dimensional Finite Element Stress Analysis.

PubMed

Arinc, Hakan

2018-06-01

To evaluate the effects of prosthetic material on the degree of stress to the cortical bone, trabecular bone, framework, and implants using finite element analysis (FEA). A mandibular implant-supported fixed prosthesis was designed. Different prosthetic materials [cobalt-chromium-supported ceramic, zirconia-supported ceramic, and zirconia-reinforced polymethyl methacrylate (ZRPMMA)-supported resin] were used. FEA was used to evaluate stress under different loading conditions. Maximum principal (σmax), minimum principal (σmin), and von Mises (σvM) stress values were obtained. Similar σmax, σmin, and σvM values were observed in the cortical and trabecular bones and in implants under both loading conditions, with the exception of the ZRPMMA model, which showed the highest σmax, σmin, and σvM values in oblique loading. The ZRPMMA model had the lowest σvM value in the framework under both loading conditions. ZRPMMA had the lowest stress values in the framework, with increased stress values in the implants and bone tissue. Framework and veneering materials may influence stress values under different loading conditions.

Assessment of Supportive, Conflicted, and Controlling Dimensions of Family Functioning: A Principal Components Analysis of Family Environment Scale Subscales in a College Sample.

ERIC Educational Resources Information Center

Kronenberger, William G.; Thompson, Robert J., Jr.; Morrow, Catherine

1997-01-01

A principal components analysis of the Family Environment Scale (FES) (R. Moos and B. Moos, 1994) was performed using 113 undergraduates. Research supported 3 broad components encompassing the 10 FES subscales. These results supported previous research and the generalization of the FES to college samples. (SLD)

Time series analysis of collective motions in proteins

NASA Astrophysics Data System (ADS)

Alakent, Burak; Doruker, Pemra; ćamurdan, Mehmet C.

2004-01-01

The dynamics of α-amylase inhibitor tendamistat around its native state is investigated using time series analysis of the principal components of the Cα atomic displacements obtained from molecular dynamics trajectories. Collective motion along a principal component is modeled as a homogeneous nonstationary process, which is the result of the damped oscillations in local minima superimposed on a random walk. The motion in local minima is described by a stationary autoregressive moving average model, consisting of the frequency, damping factor, moving average parameters and random shock terms. Frequencies for the first 50 principal components are found to be in the 3-25 cm-1 range, which are well correlated with the principal component indices and also with atomistic normal mode analysis results. Damping factors, though their correlation is less pronounced, decrease as principal component indices increase, indicating that low frequency motions are less affected by friction. The existence of a positive moving average parameter indicates that the stochastic force term is likely to disturb the mode in opposite directions for two successive sampling times, showing the modes tendency to stay close to minimum. All these four parameters affect the mean square fluctuations of a principal mode within a single minimum. The inter-minima transitions are described by a random walk model, which is driven by a random shock term considerably smaller than that for the intra-minimum motion. The principal modes are classified into three subspaces based on their dynamics: essential, semiconstrained, and constrained, at least in partial consistency with previous studies. The Gaussian-type distributions of the intermediate modes, called "semiconstrained" modes, are explained by asserting that this random walk behavior is not completely free but between energy barriers.

Burst and Principal Components Analyses of MEA Data Separates Chemicals by Class

EPA Science Inventory

Microelectrode arrays (MEAs) detect drug and chemical induced changes in action potential "spikes" in neuronal networks and can be used to screen chemicals for neurotoxicity. Analytical "fingerprinting," using Principal Components Analysis (PCA) on spike trains recorded from prim...

EVALUATION OF ACID DEPOSITION MODELS USING PRINCIPAL COMPONENT SPACES

EPA Science Inventory

An analytical technique involving principal components analysis is proposed for use in the evaluation of acid deposition models. elationships among model predictions are compared to those among measured data, rather than the more common one-to-one comparison of predictions to mea...

Protein adsorption/desorption and antibody binding stoichiometry on silicon interferometric biosensors examined with TOF-SIMS

NASA Astrophysics Data System (ADS)

Gajos, Katarzyna; Budkowski, Andrzej; Petrou, Panagiota; Pagkali, Varvara; Awsiuk, Kamil; Rysz, Jakub; Bernasik, Andrzej; Misiakos, Konstantinos; Raptis, Ioannis; Kakabakos, Sotirios

2018-06-01

Time-of-flight secondary ion mass spectrometry has been employed to examine, with biomolecular discrimination, sensing arm areas (20 μm × 600 μm) of integrated onto silicon chips Mach-Zehnder interferometers aiming to optimize their biofunctionalization with regard to indirect immunochemical (competitive) detection of ochratoxin A. Sensing areas are examined after: modification with (3-aminopropyl)triethoxysilane, spotting of OTA-ovalbumin conjugate (probe) from solutions with different concentration, blocking with bovine serum albumin, reaction with OTA-specific mouse monoclonal antibody followed by goat anti-mouse IgG secondary antibody. Component mass loadings of all proteins involved in immunodetection are determined from TOF-SIMS micro-analysis combined with ellipsometry of planar surfaces. These data show that partial desorption of surface-bound probe and blocking protein takes place upon primary immunoreaction to a degree that depends on probe concentration in spotting solution. Taking into account this desorption, apparent binding stoichiometry of both antibodies in immune complexes formed onto chip surface is determined more accurately than the respective evaluation based on real-time sensor response. In addition, mass loadings for probe and secondary antibody is observed to saturate for optimum probe concentrations. Also, principal component analysis of TOF-SIMS data could resolve both immunoreactions and biofunctionalization and discriminate surfaces prepared with optimum probe concentrations from those prepared using suboptimum ones.

Water quality of the Luján river, a lowland watercourse near the metropolitan area of Buenos Aires (Argentina).

PubMed

Castañé, Patricia M; Sánchez-Caro, Aníbal; Salibián, Alfredo

2015-10-01

Luján river is a lowland watercourse which runs 130 km before flowing into the Río de la Plata Estuary, and receives a mixture of domestic and industrial wastewaters originating at its margins. In order to know the physicochemical profile of its surface water, 36 physical-chemical variables were analyzed in samples collected seasonally between 2004 and 2006 at three sampling stations. The results obtained through the principal component analysis (PCA) suggest that the variations in water quality are explained by natural components (soluble salts; metals), nonpoint inputs (nutrients), and anthropogenic (organic and bacterial) and industrial (toxic heavy metals) pollutants. The cases did not fit a clear spatial or seasonal pattern when plotted against the first two PCA axes. The three water quality indices calculated gave middle scores; Sampling station 1 gave a baseline for the comparison of the river's water quality along its course while Sampling station 3 (downriver) was the most degraded. A variety of pollution pulses reach and affect the watercourse downstream. Cities' sewage discharges into the river seem to be the major polluting factor, together with natural metals and other solutes loads that are present from the headwaters. The results may be useful for the development of local and regional mitigation and remediation programs regarding toxic and eutrophying loads in the upper basin of the river.

Principal components analysis in clinical studies.

PubMed

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

Complexity of free energy landscapes of peptides revealed by nonlinear principal component analysis.

PubMed

Nguyen, Phuong H

2006-12-01

Employing the recently developed hierarchical nonlinear principal component analysis (NLPCA) method of Saegusa et al. (Neurocomputing 2004;61:57-70 and IEICE Trans Inf Syst 2005;E88-D:2242-2248), the complexities of the free energy landscapes of several peptides, including triglycine, hexaalanine, and the C-terminal beta-hairpin of protein G, were studied. First, the performance of this NLPCA method was compared with the standard linear principal component analysis (PCA). In particular, we compared two methods according to (1) the ability of the dimensionality reduction and (2) the efficient representation of peptide conformations in low-dimensional spaces spanned by the first few principal components. The study revealed that NLPCA reduces the dimensionality of the considered systems much better, than did PCA. For example, in order to get the similar error, which is due to representation of the original data of beta-hairpin in low dimensional space, one needs 4 and 21 principal components of NLPCA and PCA, respectively. Second, by representing the free energy landscapes of the considered systems as a function of the first two principal components obtained from PCA, we obtained the relatively well-structured free energy landscapes. In contrast, the free energy landscapes of NLPCA are much more complicated, exhibiting many states which are hidden in the PCA maps, especially in the unfolded regions. Furthermore, the study also showed that many states in the PCA maps are mixed up by several peptide conformations, while those of the NLPCA maps are more pure. This finding suggests that the NLPCA should be used to capture the essential features of the systems. (c) 2006 Wiley-Liss, Inc.

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

PubMed

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

2016-04-19

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

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.

Short communication: Discrimination between retail bovine milks with different fat contents using chemometrics and fatty acid profiling.

PubMed

Vargas-Bello-Pérez, Einar; Toro-Mujica, Paula; Enriquez-Hidalgo, Daniel; Fellenberg, María Angélica; Gómez-Cortés, Pilar

2017-06-01

We used a multivariate chemometric approach to differentiate or associate retail bovine milks with different fat contents and non-dairy beverages, using fatty acid profiles and statistical analysis. We collected samples of bovine milk (whole, semi-skim, and skim; n = 62) and non-dairy beverages (n = 27), and we analyzed them using gas-liquid chromatography. Principal component analysis of the fatty acid data yielded 3 significant principal components, which accounted for 72% of the total variance in the data set. Principal component 1 was related to saturated fatty acids (C4:0, C6:0, C8:0, C12:0, C14:0, C17:0, and C18:0) and monounsaturated fatty acids (C14:1 cis-9, C16:1 cis-9, C17:1 cis-9, and C18:1 trans-11); whole milk samples were clearly differentiated from the rest using this principal component. Principal component 2 differentiated semi-skim milk samples by n-3 fatty acid content (C20:3n-3, C20:5n-3, and C22:6n-3). Principal component 3 was related to C18:2 trans-9,trans-12 and C20:4n-6, and its lower scores were observed in skim milk and non-dairy beverages. A cluster analysis yielded 3 groups: group 1 consisted of only whole milk samples, group 2 was represented mainly by semi-skim milks, and group 3 included skim milk and non-dairy beverages. Overall, the present study showed that a multivariate chemometric approach is a useful tool for differentiating or associating retail bovine milks and non-dairy beverages using their fatty acid profile. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

[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.

Evidence for age-associated disinhibition of the wake drive provided by scoring principal components of the resting EEG spectrum in sleep-provoking conditions.

PubMed

Putilov, Arcady A; Donskaya, Olga G

2016-01-01

Age-associated changes in different bandwidths of the human electroencephalographic (EEG) spectrum are well documented, but their functional significance is poorly understood. This spectrum seems to represent summation of simultaneous influences of several sleep-wake regulatory processes. Scoring of its orthogonal (uncorrelated) principal components can help in separation of the brain signatures of these processes. In particular, the opposite age-associated changes were documented for scores on the two largest (1st and 2nd) principal components of the sleep EEG spectrum. A decrease of the first score and an increase of the second score can reflect, respectively, the weakening of the sleep drive and disinhibition of the opposing wake drive with age. In order to support the suggestion of age-associated disinhibition of the wake drive from the antagonistic influence of the sleep drive, we analyzed principal component scores of the resting EEG spectra obtained in sleep deprivation experiments with 81 healthy young adults aged between 19 and 26 and 40 healthy older adults aged between 45 and 66 years. At the second day of the sleep deprivation experiments, frontal scores on the 1st principal component of the EEG spectrum demonstrated an age-associated reduction of response to eyes closed relaxation. Scores on the 2nd principal component were either initially increased during wakefulness or less responsive to such sleep-provoking conditions (frontal and occipital scores, respectively). These results are in line with the suggestion of disinhibition of the wake drive with age. They provide an explanation of why older adults are less vulnerable to sleep deprivation than young adults.

Thermally determining flow and/or heat load distribution in parallel paths

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

Chainer, Timothy J.; Iyengar, Madhusudan K.; Parida, Pritish R.

A method including obtaining calibration data for at least one sub-component in a heat transfer assembly, wherein the calibration data comprises at least one indication of coolant flow rate through the sub-component for a given surface temperature delta of the sub-component and a given heat load into said sub-component, determining a measured heat load into the sub-component, determining a measured surface temperature delta of the sub-component, and determining a coolant flow distribution in a first flow path comprising the sub-component from the calibration data according to the measured heat load and the measured surface temperature delta of the sub-component.

Thermally determining flow and/or heat load distribution in parallel paths

DOEpatents

Chainer, Timothy J.; Iyengar, Madhusudan K.; Parida, Pritish R.

2016-12-13

A method including obtaining calibration data for at least one sub-component in a heat transfer assembly, wherein the calibration data comprises at least one indication of coolant flow rate through the sub-component for a given surface temperature delta of the sub-component and a given heat load into said sub-component, determining a measured heat load into the sub-component, determining a measured surface temperature delta of the sub-component, and determining a coolant flow distribution in a first flow path comprising the sub-component from the calibration data according to the measured heat load and the measured surface temperature delta of the sub-component.

Application of principal component analysis to ecodiversity assessment of postglacial landscape (on the example of Debnica Kaszubska commune, Middle Pomerania)

NASA Astrophysics Data System (ADS)

Wojciechowski, Adam

2017-04-01

In order to assess ecodiversity understood as a comprehensive natural landscape factor (Jedicke 2001), it is necessary to apply research methods which recognize the environment in a holistic way. Principal component analysis may be considered as one of such methods as it allows to distinguish the main factors determining landscape diversity on the one hand, and enables to discover regularities shaping the relationships between various elements of the environment under study on the other hand. The procedure adopted to assess ecodiversity with the use of principal component analysis involves: a) determining and selecting appropriate factors of the assessed environment qualities (hypsometric, geological, hydrographic, plant, and others); b) calculating the absolute value of individual qualities for the basic areas under analysis (e.g. river length, forest area, altitude differences, etc.); c) principal components analysis and obtaining factor maps (maps of selected components); d) generating a resultant, detailed map and isolating several classes of ecodiversity. An assessment of ecodiversity with the use of principal component analysis was conducted in the test area of 299,67 km2 in Debnica Kaszubska commune. The whole commune is situated in the Weichselian glaciation area of high hypsometric and morphological diversity as well as high geo- and biodiversity. The analysis was based on topographical maps of the commune area in scale 1:25000 and maps of forest habitats. Consequently, nine factors reflecting basic environment elements were calculated: maximum height (m), minimum height (m), average height (m), the length of watercourses (km), the area of water reservoirs (m2), total forest area (ha), coniferous forests habitats area (ha), deciduous forest habitats area (ha), alder habitats area (ha). The values for individual factors were analysed for 358 grid cells of 1 km2. Based on the principal components analysis, four major factors affecting commune ecodiversity were distinguished: hypsometric component (PC1), deciduous forest habitats component (PC2), river valleys and alder habitats component (PC3), and lakes component (PC4). The distinguished factors characterise natural qualities of postglacial area and reflect well the role of the four most important groups of environment components in shaping ecodiversity of the area under study. The map of ecodiversity of Debnica Kaszubska commune was created on the basis of the first four principal component scores and then five classes of diversity were isolated: very low, low, average, high and very high. As a result of the assessment, five commune regions of very high ecodiversity were separated. These regions are also very attractive for tourists and valuable in terms of their rich nature which include protected areas such as Slupia Valley Landscape Park. The suggested method of ecodiversity assessment with the use of principal component analysis may constitute an alternative methodological proposition to other research methods used so far. Literature Jedicke E., 2001. Biodiversität, Geodiversität, Ökodiversität. Kriterien zur Analyse der Landschaftsstruktur - ein konzeptioneller Diskussionsbeitrag. Naturschutz und Landschaftsplanung, 33(2/3), 59-68.

A HIERARCHIAL STOCHASTIC MODEL OF LARGE SCALE ATMOSPHERIC CIRCULATION PATTERNS AND MULTIPLE STATION DAILY PRECIPITATION

EPA Science Inventory

A stochastic model of weather states and concurrent daily precipitation at multiple precipitation stations is described. our algorithms are invested for classification of daily weather states; k means, fuzzy clustering, principal components, and principal components coupled with ...

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.

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.

Multilevel sparse functional principal component analysis.

PubMed

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

[Content of mineral elements of Gastrodia elata by principal components analysis].

PubMed

Li, Jin-ling; Zhao, Zhi; Liu, Hong-chang; Luo, Chun-li; Huang, Ming-jin; Luo, Fu-lai; Wang, Hua-lei

2015-03-01

To study the content of mineral elements and the principal components in Gastrodia elata. Mineral elements were determined by ICP and the data was analyzed by SPSS. K element has the highest content-and the average content was 15.31 g x kg(-1). The average content of N element was 8.99 g x kg(-1), followed by K element. The coefficient of variation of K and N was small, but the Mn was the biggest with 51.39%. The highly significant positive correlation was found among N, P and K . Three principal components were selected by principal components analysis to evaluate the quality of G. elata. P, B, N, K, Cu, Mn, Fe and Mg were the characteristic elements of G. elata. The content of K and N elements was higher and relatively stable. The variation of Mn content was biggest. The quality of G. elata in Guizhou and Yunnan was better from the perspective of mineral elements.

Uncertainty quantification for personalized analyses of human proximal femurs.

PubMed

Wille, Hagen; Ruess, Martin; Rank, Ernst; Yosibash, Zohar

2016-02-29

Computational models for the personalized analysis of human femurs contain uncertainties in bone material properties and loads, which affect the simulation results. To quantify the influence we developed a probabilistic framework based on polynomial chaos (PC) that propagates stochastic input variables through any computational model. We considered a stochastic E-ρ relationship and a stochastic hip contact force, representing realistic variability of experimental data. Their influence on the prediction of principal strains (ϵ1 and ϵ3) was quantified for one human proximal femur, including sensitivity and reliability analysis. Large variabilities in the principal strain predictions were found in the cortical shell of the femoral neck, with coefficients of variation of ≈40%. Between 60 and 80% of the variance in ϵ1 and ϵ3 are attributable to the uncertainty in the E-ρ relationship, while ≈10% are caused by the load magnitude and 5-30% by the load direction. Principal strain directions were unaffected by material and loading uncertainties. The antero-superior and medial inferior sides of the neck exhibited the largest probabilities for tensile and compression failure, however all were very small (pf<0.001). In summary, uncertainty quantification with PC has been demonstrated to efficiently and accurately describe the influence of very different stochastic inputs, which increases the credibility and explanatory power of personalized analyses of human proximal femurs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visualizing Hyolaryngeal Mechanics in Swallowing Using Dynamic MRI

PubMed Central

Pearson, William G.; Zumwalt, Ann C.

2013-01-01

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

Structured Sparse Principal Components Analysis With the TV-Elastic Net Penalty.

PubMed

de Pierrefeu, Amicie; Lofstedt, Tommy; Hadj-Selem, Fouad; Dubois, Mathieu; Jardri, Renaud; Fovet, Thomas; Ciuciu, Philippe; Frouin, Vincent; Duchesnay, Edouard

2018-02-01

Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover the dominant patterns of variability within a population. Despite its ability to represent a data set in a low-dimensional space, PCA's interpretability remains limited. Indeed, the components produced by PCA are often noisy or exhibit no visually meaningful patterns. Furthermore, the fact that the components are usually non-sparse may also impede interpretation, unless arbitrary thresholding is applied. However, in neuroimaging, it is essential to uncover clinically interpretable phenotypic markers that would account for the main variability in the brain images of a population. Recently, some alternatives to the standard PCA approach, such as sparse PCA (SPCA), have been proposed, their aim being to limit the density of the components. Nonetheless, sparsity alone does not entirely solve the interpretability problem in neuroimaging, since it may yield scattered and unstable components. We hypothesized that the incorporation of prior information regarding the structure of the data may lead to improved relevance and interpretability of brain patterns. We therefore present a simple extension of the popular PCA framework that adds structured sparsity penalties on the loading vectors in order to identify the few stable regions in the brain images that capture most of the variability. Such structured sparsity can be obtained by combining, e.g., and total variation (TV) penalties, where the TV regularization encodes information on the underlying structure of the data. This paper presents the structured SPCA (denoted SPCA-TV) optimization framework and its resolution. We demonstrate SPCA-TV's effectiveness and versatility on three different data sets. It can be applied to any kind of structured data, such as, e.g., -dimensional array images or meshes of cortical surfaces. The gains of SPCA-TV over unstructured approaches (such as SPCA and ElasticNet PCA) or structured approach (such as GraphNet PCA) are significant, since SPCA-TV reveals the variability within a data set in the form of intelligible brain patterns that are easier to interpret and more stable across different samples.

Obesity, metabolic syndrome, impaired fasting glucose, and microvascular dysfunction: a principal component analysis approach.

PubMed

Panazzolo, Diogo G; Sicuro, Fernando L; Clapauch, Ruth; Maranhão, Priscila A; Bouskela, Eliete; Kraemer-Aguiar, Luiz G

2012-11-13

We aimed to evaluate the multivariate association between functional microvascular variables and clinical-laboratorial-anthropometrical measurements. Data from 189 female subjects (34.0 ± 15.5 years, 30.5 ± 7.1 kg/m2), who were non-smokers, non-regular drug users, without a history of diabetes and/or hypertension, were analyzed by principal component analysis (PCA). PCA is a classical multivariate exploratory tool because it highlights common variation between variables allowing inferences about possible biological meaning of associations between them, without pre-establishing cause-effect relationships. In total, 15 variables were used for PCA: body mass index (BMI), waist circumference, systolic and diastolic blood pressure (BP), fasting plasma glucose, levels of total cholesterol, high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), triglycerides (TG), insulin, C-reactive protein (CRP), and functional microvascular variables measured by nailfold videocapillaroscopy. Nailfold videocapillaroscopy was used for direct visualization of nutritive capillaries, assessing functional capillary density, red blood cell velocity (RBCV) at rest and peak after 1 min of arterial occlusion (RBCV(max)), and the time taken to reach RBCV(max) (TRBCV(max)). A total of 35% of subjects had metabolic syndrome, 77% were overweight/obese, and 9.5% had impaired fasting glucose. PCA was able to recognize that functional microvascular variables and clinical-laboratorial-anthropometrical measurements had a similar variation. The first five principal components explained most of the intrinsic variation of the data. For example, principal component 1 was associated with BMI, waist circumference, systolic BP, diastolic BP, insulin, TG, CRP, and TRBCV(max) varying in the same way. Principal component 1 also showed a strong association among HDL-c, RBCV, and RBCV(max), but in the opposite way. Principal component 3 was associated only with microvascular variables in the same way (functional capillary density, RBCV and RBCV(max)). Fasting plasma glucose appeared to be related to principal component 4 and did not show any association with microvascular reactivity. In non-diabetic female subjects, a multivariate scenario of associations between classic clinical variables strictly related to obesity and metabolic syndrome suggests a significant relationship between these diseases and microvascular reactivity.

An Empirical Cumulus Parameterization Scheme for a Global Spectral Model

NASA Technical Reports Server (NTRS)

Rajendran, K.; Krishnamurti, T. N.; Misra, V.; Tao, W.-K.

2004-01-01

Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This also suggests that in the absence of explicit models for convection, the proposed statistical scheme improves the modeling of the vertical distribution of heating and moistening in areas of deep convection.

Stress Analysis of B-52B and B-52H Air-Launching Systems Failure-Critical Structural Components

NASA Technical Reports Server (NTRS)

Ko, William L.

2005-01-01

The operational life analysis of any airborne failure-critical structural component requires the stress-load equation, which relates the applied load to the maximum tangential tensile stress at the critical stress point. The failure-critical structural components identified are the B-52B Pegasus pylon adapter shackles, B-52B Pegasus pylon hooks, B-52H airplane pylon hooks, B-52H airplane front fittings, B-52H airplane rear pylon fitting, and the B-52H airplane pylon lower sway brace. Finite-element stress analysis was performed on the said structural components, and the critical stress point was located and the stress-load equation was established for each failure-critical structural component. The ultimate load, yield load, and proof load needed for operational life analysis were established for each failure-critical structural component.

The factorial reliability of the Middlesex Hospital Questionnaire in normal subjects.

PubMed

Bagley, C

1980-03-01

The internal reliability of the Middlesex Hospital Questionnaire and its component subscales has been checked by means of principal components analyses of data on 256 normal subjects. The subscales (with the possible exception of Hysteria) were found to contribute to the general underlying factor of psychoneurosis. In general, the principal components analysis points to the reliability of the subscales, despite some item overlap.

The Derivation of Job Compensation Index Values from the Position Analysis Questionnaire (PAQ). Report No. 6.

ERIC Educational Resources Information Center

McCormick, Ernest J.; And Others

The study deals with the job component method of establishing compensation rates. The basic job analysis questionnaire used in the study was the Position Analysis Questionnaire (PAQ) (Form B). On the basis of a principal components analysis of PAQ data for a large sample (2,688) of jobs, a number of principal components (job dimensions) were…

Perceptions of the Principal Evaluation Process and Performance Criteria: A Qualitative Study of the Challenge of Principal Evaluation

ERIC Educational Resources Information Center

Faginski-Stark, Erica; Casavant, Christopher; Collins, William; McCandless, Jason; Tencza, Marilyn

2012-01-01

Recent federal and state mandates have tasked school systems to move beyond principal evaluation as a bureaucratic function and to re-imagine it as a critical component to improve principal performance and compel school renewal. This qualitative study investigated the district leaders' and principals' perceptions of the performance evaluation…

MOD-1 Wind Turbine Generator Analysis and Design Report, Volume 2

NASA Technical Reports Server (NTRS)

1979-01-01

The MOD-1 detail design is appended. The supporting analyses presented include a parametric system trade study, a verification of the computer codes used for rotor loads analysis, a metal blade study, and a definition of the design loads at each principal wind turbine generator interface for critical loading conditions. Shipping and assembly requirements, composite blade development, and electrical stability are also discussed.

2L-PCA: a two-level principal component analyzer for quantitative drug design and its applications.

PubMed

Du, Qi-Shi; Wang, Shu-Qing; Xie, Neng-Zhong; Wang, Qing-Yan; Huang, Ri-Bo; Chou, Kuo-Chen

2017-09-19

A two-level principal component predictor (2L-PCA) was proposed based on the principal component analysis (PCA) approach. It can be used to quantitatively analyze various compounds and peptides about their functions or potentials to become useful drugs. One level is for dealing with the physicochemical properties of drug molecules, while the other level is for dealing with their structural fragments. The predictor has the self-learning and feedback features to automatically improve its accuracy. It is anticipated that 2L-PCA will become a very useful tool for timely providing various useful clues during the process of drug development.

1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas.

PubMed

Son, Hong-Seok; Kim, Ki Myong; van den Berg, Frans; Hwang, Geum-Sook; Park, Won-Mok; Lee, Cherl-Ho; Hong, Young-Shick

2008-09-10

(1)H NMR spectroscopy was used to investigate the metabolic differences in wines produced from different grape varieties and different regions. A significant separation among wines from Campbell Early, Cabernet Sauvignon, and Shiraz grapes was observed using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The metabolites contributing to the separation were assigned to be 2,3-butanediol, lactate, acetate, proline, succinate, malate, glycerol, tartarate, glucose, and phenolic compounds by PCA and PLS-DA loading plots. Wines produced from Cabernet Sauvignon grapes harvested in the continental areas of Australia, France, and California were also separated. PLS-DA loading plots revealed that the level of proline in Californian Cabernet Sauvignon wines was higher than that in Australian and French Cabernet Sauvignon, Australian Shiraz, and Korean Campbell Early wines, showing that the chemical composition of the grape berries varies with the variety and growing area. This study highlights the applicability of NMR-based metabolomics with multivariate statistical data sets in determining wine quality and product origin.

Development of a multicomponent force and moment balance for water tunnel applications, volume 1

NASA Technical Reports Server (NTRS)

Suarez, Carlos J.; Malcolm, Gerald N.; Kramer, Brian R.; Smith, Brooke C.; Ayers, Bert F.

1994-01-01

The principal objective of this research effort was to develop a multicomponent strain gauge balance to measure forces and moments on models tested in flow visualization water tunnels. An internal balance was designed that allows measuring normal and side forces, and pitching, yawing and rolling moments (no axial force). The five-components to applied loads, low interactions between the sections and no hysteresis. Static experiments (which are discussed in this Volume) were conducted in the Eidetics water tunnel with delta wings and a model of the F/A-18. Experiments with the F/A-18 model included a thorough baseline study and investigations of the effect of control surface deflections and of several Forebody Vortex Control (FVC) techniques. Results were compared to wind tunnel data and, in general, the agreement is very satisfactory. The results of the static tests provide confidence that loads can be measured accurately in the water tunnel with a relatively simple multicomponent internal balance. Dynamic experiments were also performed using the balance, and the results are discussed in detail in Volume 2 of this report.

Dissolved Concentrations, Sources, and Risk Evaluation of Selected Metals in Surface Water from Mangla Lake, Pakistan

PubMed Central

Saleem, Muhammad; Iqbal, Javed; Shah, Munir H.

2014-01-01

The present study is carried out for the assessment of water quality parameters and selected metals levels in surface water from Mangla Lake, Pakistan. The metal levels (Ca, Cd, Co, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Pb, Sr, and Zn) were determined by flame atomic absorption spectrophotometry. Average levels of Cd, Co, Cr, Ni, and Pb were higher than the allowable concentrations set by national and international agencies. Principal component analysis indicated significant anthropogenic contributions of Cd, Co, Cr, Ni, and Pb in the water reservoir. Noncarcinogenic risk assessment was then evaluated using Hazard Quotient (HQing/derm) and Hazard Index (HIing/derm) following USEPA methodology. For adults and children, Cd, Co, Cr, and Pb (HQing > 1) emerged as the most important pollutants leading to noncarcinogenic concerns via ingestion route, whereas there was no risk via dermal contact of surface water. This study helps in establishing pollutant loading reduction goal and the total maximum daily loads, and consequently contributes to preserve public health and develop water conservation strategy. PMID:24744690

Estimation of skeletal muscle mass from body creatine content

NASA Technical Reports Server (NTRS)

Pace, N.; Rahlmann, D. F.

1982-01-01

Procedures have been developed for studying the effect of changes in gravitational loading on skeletal muscle mass through measurements of the body creatine content. These procedures were developed for studies of gravitational scale effects in a four-species model, comprising the hamster, rat, guinea pig, and rabbit, which provides a sufficient range of body size for assessment of allometric parameters. Since intracellular muscle creatine concentration varies among species, and with age within a given species, the concentration values for metabolically mature individuals of these four species were established. The creatine content of the carcass, skin, viscera, smooth muscle, and skeletal muscle was determined for each species. In addition, the skeletal muscle mass of the major body components was determined, as well as the total and fat-free masses of the body and carcass, and the percent skeletal muscle in each. It is concluded that these procedures are particularly useful for studying the effect of gravitational loading on the skeletal muscle content of the animal carcass, which is the principal weight-bearing organ of the body.

Sewer infiltration/inflow: long-term monitoring based on diurnal variation of pollutant mass flux.

PubMed

Bares, V; Stránský, D; Sýkora, P

2009-01-01

The paper deals with a method for quantification of infiltrating groundwater based on the variation of diurnal pollutant load and continuous water quality and quantity monitoring. Although the method gives us the potential to separate particular components of wastewater hygrograph, several aspects of the method should be discussed. Therefore, the paper investigates the cost-effectiveness, the relevance of pollutant load from surface waters (groundwater) and the influence of measurement time step. These aspects were studied in an experimental catchment of Prague sewer system, Czech Republic, within a three-month period. The results indicate high contribution of parasitic waters on night minimal discharge. Taking into account the uncertainty of the results and time-consuming maintenance of the sensor, the principal advantages of the method are evaluated. The study introduces a promising potential of the discussed measuring concept for quantification of groundwater infiltrating into the sewer system. It is shown that the conventional approach is sufficient and cost-effective even in those catchments, where significant contribution of foul sewage in night minima would have been assumed.

Raman spectroscopy of single extracellular vesicles reveals subpopulations with varying membrane content (Conference Presentation)

NASA Astrophysics Data System (ADS)

Smith, Zachary J.; Lee, Changwon; Rojalin, Tatu; Carney, Randy P.; Hazari, Sidhartha; Knudson, Alisha; Lam, Kit S.; Saari, Heikki; Lazaro Ibañez, Elisa; Viitala, Tapani; Laaksonen, Timo; Yliperttula, Marjo; Wachsmann-Hogiu, Sebastian

2016-03-01

Exosomes are small (~100nm) membrane bound vesicles excreted by cells as part of their normal biological processes. These extracellular vesicles are currently an area of intense research, since they were recently found to carry functional mRNA that allows transfer of proteins and other cellular instructions between cells. Exosomes have been implicated in a wide range of diseases, including cancer. Cancer cells are known to have increased exosome production, and may use those exosomes to prepare remote environments for metastasis. Therefore, there is a strong need to develop characterization methods to help understand the structure and function of these vesicles. However, current techniques, such as proteomics and genomics technologies, rely on aggregating a large amount of exosome material and reporting on chemical content that is averaged over many millions of exosomes. Here we report on the use of laser-tweezers Raman spectroscopy (LTRS) to probe individual vesicles, discovering distinct heterogeneity among exosomes both within a cell line, as well as between different cell lines. Through principal components analysis followed by hierarchical clustering, we have identified four "subpopulations" of exosomes shared across seven cell lines. The key chemical differences between these subpopulations, as determined by spectral analysis of the principal component loadings, are primarily related to membrane composition. Specifically, the differences can be ascribed to cholesterol content, cholesterol to phospholipid ratio, and surface protein expression. Thus, we have shown LTRS to be a powerful method to probe the chemical content of single extracellular vesicles.

Application of Electronic Nose for Measuring Total Volatile Basic Nitrogen and Total Viable Counts in Packaged Pork During Refrigerated Storage.

PubMed

Li, Miaoyun; Wang, Haibiao; Sun, Lingxia; Zhao, Gaiming; Huang, Xianqing

2016-04-01

The objective of this study was to predict the total viable counts (TVC) and total volatile basic nitrogen (TVB-N) in pork using an electronic nose (E-nose), and to assess the freshness of chilled pork during storage using different packaging methods, including pallet packaging (PP), vacuum packaging (VP), and modified atmosphere packaging (MAP, 40% O2 /40% CO2 /20% N2 ). Principal component analysis (PCA) was used to analyze the E-nose signals, and the results showed that the relationships between the freshness of chilled pork and E-nose signals could be distinguished in the loadings plots, and the freshness of chilled pork could be distributed along 2 first principal components. Multiple linear regression (MLR) was used to correlate TVC and TVB-N to E-nose signals. High F and R2 values were obtained in the MLR output of TVB-N (F = 32.1, 21.6, and 24.2 for PP [R2 = 0.93], VP [R2 = 0.94], and MAP [R2 = 0.95], respectively) and TVC (F = 34.2, 46.4, and 7.8 for PP [R2 = 0.98], VP [R2 = 0.89], and MAP [R2 = 0.85], respectively). The results of this study suggest that it is possible to use the E-nose technology to predict TVB-N and TVC for assessing the freshness of chilled pork during storage. © 2016 Institute of Food Technologists®

Principal component analysis for the comparison of metabolic profiles from human rectal cancer biopsies and colorectal xenografts using high-resolution magic angle spinning 1H magnetic resonance spectroscopy

PubMed Central

Seierstad, Therese; Røe, Kathrine; Sitter, Beathe; Halgunset, Jostein; Flatmark, Kjersti; Ree, Anne H; Olsen, Dag Rune; Gribbestad, Ingrid S; Bathen, Tone F

2008-01-01

Background This study was conducted in order to elucidate metabolic differences between human rectal cancer biopsies and colorectal HT29, HCT116 and SW620 xenografts by using high-resolution magnetic angle spinning (MAS) magnetic resonance spectroscopy (MRS) and for determination of the most appropriate human rectal xenograft model for preclinical MR spectroscopy studies. A further aim was to investigate metabolic changes following irradiation of HT29 xenografts. Methods HR MAS MRS of tissue samples from xenografts and rectal biopsies were obtained with a Bruker Avance DRX600 spectrometer and analyzed using principal component analysis (PCA) and partial least square (PLS) regression analysis. Results and conclusion HR MAS MRS enabled assignment of 27 metabolites. Score plots from PCA of spin-echo and single-pulse spectra revealed separate clusters of the different xenografts and rectal biopsies, reflecting underlying differences in metabolite composition. The loading profile indicated that clustering was mainly based on differences in relative amounts of lipids, lactate and choline-containing compounds, with HT29 exhibiting the metabolic profile most similar to human rectal cancers tissue. Due to high necrotic fractions in the HT29 xenografts, radiation-induced changes were not detected when comparing spectra from untreated and irradiated HT29 xenografts. However, PLS calibration relating spectral data to the necrotic fraction revealed a significant correlation, indicating that necrotic fraction can be assessed from the MR spectra. PMID:18439252

Biomechanical implications of intraspecific shape variation in chimpanzee crania: moving towards an integration of geometric morphometrics and finite element analysis

PubMed Central

Smith, Amanda L.; Benazzi, Stefano; Ledogar, Justin A.; Tamvada, Kelli; Smith, Leslie C. Pryor; Weber, Gerhard W.; Spencer, Mark A.; Dechow, Paul C.; Grosse, Ian R.; Ross, Callum F.; Richmond, Brian G.; Wright, Barth W.; Wang, Qian; Byron, Craig; Slice, Dennis E.; Strait, David S.

2014-01-01

In a broad range of evolutionary studies, an understanding of intraspecific variation is needed in order to contextualize and interpret the meaning of variation between species. However, mechanical analyses of primate crania using experimental or modeling methods typically encounter logistical constraints that force them to rely on data gathered from only one or a few individuals. This results in a lack of knowledge concerning the mechanical significance of intraspecific shape variation that limits our ability to infer the significance of interspecific differences. This study uses geometric morphometric methods (GM) and finite element analysis (FEA) to examine the biomechanical implications of shape variation in chimpanzee crania, thereby providing a comparative context in which to interpret shape-related mechanical variation between hominin species. Six finite element models (FEMs) of chimpanzee crania were constructed from CT scans following shape-space Principal Component Analysis (PCA) of a matrix of 709 Procrustes coordinates (digitized onto 21 specimens) to identify the individuals at the extremes of the first three principal components. The FEMs were assigned the material properties of bone and were loaded and constrained to simulate maximal bites on the P3 and M2. Resulting strains indicate that intraspecific cranial variation in morphology is associated with quantitatively high levels of variation in strain magnitudes, but qualitatively little variation in the distribution of strain concentrations. Thus, interspecific comparisons should include considerations of the spatial patterning of strains rather than focus only their magnitude. PMID:25529239

Statistical shape modeling of human cochlea: alignment and principal component analysis

NASA Astrophysics Data System (ADS)

Poznyakovskiy, Anton A.; Zahnert, Thomas; Fischer, Björn; Lasurashvili, Nikoloz; Kalaidzidis, Yannis; Mürbe, Dirk

2013-02-01

The modeling of the cochlear labyrinth in living subjects is hampered by insufficient resolution of available clinical imaging methods. These methods usually provide resolutions higher than 125 μm. This is too crude to record the position of basilar membrane and, as a result, keep apart even the scala tympani from other scalae. This problem could be avoided by the means of atlas-based segmentation. The specimens can endure higher radiation loads and, conversely, provide better-resolved images. The resulting surface can be used as the seed for atlas-based segmentation. To serve this purpose, we have developed a statistical shape model (SSM) of human scala tympani based on segmentations obtained from 10 μCT image stacks. After segmentation, we aligned the resulting surfaces using Procrustes alignment. This algorithm was slightly modified to accommodate single models with nodes which do not necessarily correspond to salient features and vary in number between models. We have established correspondence by mutual proximity between nodes. Rather than using the standard Euclidean norm, we have applied an alternative logarithmic norm to improve outlier treatment. The minimization was done using BFGS method. We have also split the surface nodes along an octree to reduce computation cost. Subsequently, we have performed the principal component analysis of the training set with Jacobi eigenvalue algorithm. We expect the resulting method to help acquiring not only better understanding in interindividual variations of cochlear anatomy, but also a step towards individual models for pre-operative diagnostics prior to cochlear implant insertions.

Validation and factor structure of the Thai version of the EURO-D scale for depression among older psychiatric patients.

PubMed

Jirapramukpitak, Tawanchai; Darawuttimaprakorn, Niphon; Punpuing, Sureeporn; Abas, Melanie

2009-11-01

To assess the concurrent and the construct validity of the Euro-D in older Thai persons. Eight local psychiatrists used the major depressive episode section of the Mini International Neuropsychiatric Interview to interview 150 consecutive psychiatric clinic attendees. A trained interviewer administered the Euro-D. We used receiver operating characteristic (ROC) analysis to assess the overall discriminability of the Euro-D scale and principal components factor analysis to assess its construct validity. The area under the ROC curve for the Euro-D with respect to major depressive episode was 0.78 [95% confidence interval (CI) 0.70-0.90] indicating moderately good discriminability. At a cut-point of 5/6 the sensitivity for major depressive episodes is 84.3%, specificity 58.6%, and kappa 0.37 (95% CI 0.22-0.52) indicating fair concordance. However, at the 3/4 cut-point recommended from European studies there is high sensitivity (94%) but poor specificity (34%). The principal components analysis suggested four factors. The first two factors conformed to affective suffering (depression, suicidality and tearfulness) and motivation (interest, concentration and enjoyment). Sleep and appetite constituted a separate factor, whereas pessimism loaded on its own factor. Among Thai psychiatric clinic attendees Euro-D is moderately valid for major depression. A much higher cut-point may be required than that which is usually advocated. The Thai version also shares two common factors as reported from most of previous studies.

Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

PubMed

Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

2017-05-01

Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

Evolutionary dynamics of ecological niche in three Rhinogobio fishes from the upper Yangtze River inferred from morphological traits

PubMed Central

Wang, Meirong; Liu, Fei; Lin, Pengcheng; Yang, Shaorong; Liu, Huanzhang

2015-01-01

In the past decades, it has been debated whether ecological niche should be conserved among closely related species (phylogenetic niche conservatism, PNC) or largely divergent (traditional ecological niche theory and ecological speciation) and whether niche specialist and generalist might remain in equilibrium or niche generalist could not appear. In this study, we employed morphological traits to describe ecological niche and test whether different niche dimensions exhibit disparate evolutionary patterns. We conducted our analysis on three Rhinogobio fish species (R. typus,R. cylindricus, and R. ventralis) from the upper Yangtze River, China. Among the 32 measured morphological traits except body length, PCA extracted the first four principal components with their loading scores >1.000. To find the PNC among species, Mantel tests were conducted with the Euclidean distances calculated from the four principal components (representing different niche dimensions) against the pairwise distances calculated from mitochondrial cytochrome b sequence variations. The results showed that the second and the third niche dimension, both related to swimming ability and behavior, exhibited phylogenetic conservatism. Further comparison on niche breadth among these three species revealed that the fourth dimension of R. typus showed the greatest width, indicating that this dimension exhibited niche generalism. In conclusion, our results suggested that different niche dimensions could show different evolutionary dynamic patterns: they may exhibit PNC or not, and some dimensions may evolve generalism. PMID:25691981

A psychometric appraisal of the Jefferson Scale of Empathy using law students.

PubMed

Williams, Brett; Sifris, Adiva; Lynch, Marty

2016-01-01

A growing body of literature indicates that empathic behaviors are positively linked, in several ways, with the professional performance and mental well-being of lawyers and law students. It is therefore important to assess empathy levels among law students using psychometrically sound tools that are suitable for this cohort. The 20-item Jefferson Scale of Empathy - Health Profession Students Version was adapted for a law context (eg, the word "health care" became "legal"), and the new Jefferson Scale of Empathy - Law Students (JSE-L-S) version was completed by 275 students at Monash University, Melbourne, Australia. Data were subjected to principal component analysis. Four factors emerged from the principal component analysis ("understanding the client's perspective", "responding to clients' experiences and emotions", "responding to clients' cues and behaviors", and "standing in clients' shoes"), which accounted for 46.7% of the total variance. The reliability of the factors varied, but the overall 18-item JSE-L-S yielded a Cronbach's alpha coefficient of 0.80. Several patterns among the item loadings were similar to those reported in studies using other versions of the Jefferson Scale of Empathy. The JSE-L-S appears to be a reliable measure of empathy among undergraduate law students, which could help provide insights into law student welfare and future performance as legal practitioners. Additional evaluation of the JSE-L-S is required to disambiguate some of the minor findings explored. Adjustments may improve the psychometric properties.

Differential distribution of amino acids in plants.

PubMed

Kumar, Vinod; Sharma, Anket; Kaur, Ravdeep; Thukral, Ashwani Kumar; Bhardwaj, Renu; Ahmad, Parvaiz

2017-05-01

Plants are a rich source of amino acids and their individual abundance in plants is of great significance especially in terms of food. Therefore, it is of utmost necessity to create a database of the relative amino acid contents in plants as reported in literature. Since in most of the cases complete analysis of profiles of amino acids in plants was not reported, the units used and the methods applied and the plant parts used were different, amino acid contents were converted into relative units with respect to lysine for statistical analysis. The most abundant amino acids in plants are glutamic acid and aspartic acid. Pearson's correlation analysis among different amino acids showed that there were no negative correlations between the amino acids. Cluster analysis (CA) applied to relative amino acid contents of different families. Alismataceae, Cyperaceae, Capparaceae and Cactaceae families had close proximity with each other on the basis of their relative amino acid contents. First three components of principal component analysis (PCA) explained 79.5% of the total variance. Factor analysis (FA) explained four main underlying factors for amino acid analysis. Factor-1 accounted for 29.4% of the total variance and had maximum loadings on glycine, isoleucine, leucine, threonine and valine. Factor-2 explained 25.8% of the total variance and had maximum loadings on alanine, aspartic acid, serine and tyrosine. 14.2% of the total variance was explained by factor-3 and had maximum loadings on arginine and histidine. Factor-4 accounted 8.3% of the total variance and had maximum loading on the proline amino acid. The relative content of different amino acids presented in this paper is alanine (1.4), arginine (1.8), asparagine (0.7), aspartic acid (2.4), cysteine (0.5), glutamic acid (2.8), glutamine (0.6), glycine (1.0), histidine (0.5), isoleucine (0.9), leucine (1.7), lysine (1.0), methionine (0.4), phenylalanine (0.9), proline (1.1), serine (1.0), threonine (1.0), tryptophan (0.3), tyrosine (0.7) and valine (1.2).

Advanced zinc-doped adhesives for high performance at the resin-carious dentin interface.

PubMed

Toledano, Manuel; Osorio, Raquel; Osorio, Estrella; García-Godoy, Franklin; Toledano-Osorio, Manuel; Aguilera, Fátima S

2016-09-01

The purpose of this study was to evaluate the remineralization ability of an etch-and-rinse Zn-doped resin applied on caries-affected dentin (CAD). CAD surfaces were subjected to: (i) 37% phosphoric acid (PA) or (ii) 0.5M ethylenediaminetetraacetic acid (EDTA). 10wt% ZnO nanoparticles or 2wt% ZnCl2 were added into the adhesive Single Bond (SB), to create the following groups: PA+SB, PA+SB-ZnO, PA+SB-ZnCl2, EDTA+SB, EDTA+SB-ZnO, EDTA+SB-ZnCl2. Bonded interfaces were submitted to mechanical loading or stored during 24h. Remineralization of the bonded interfaces was studied by AFM nano-indentation (hardness and Young׳s modulus), Raman spectroscopy [mapping with principal component analysis (PCA), and hierarchical cluster analysis (HCA)] and Masson׳s trichrome staining technique. Dentin samples treated with PA+SB-ZnO attained the highest values of nano-mechanical properties. Load cycling increased both mineralization and crystallographic maturity at the interface; this effect was specially noticed when using ZnCl2-doped resin in EDTA-treated carious dentin. Crosslinking attained higher frequencies indicating better conformation and organization of collagen in specimens treated with PA+SB-ZnO, after load cycling. Trichrome staining technique depicted a deeper demineralized dentin fringe that became reduced after loading, and it was not observable in EDTA+SB groups. Multivariate analysis confirmed de homogenizing effect of load cycling in the percentage of variances, traces of centroids and distribution of clusters, especially in specimens treated with EDTA+SB-ZnCl2. Copyright © 2016 Elsevier Ltd. All rights reserved.

Carotenoid-based bill colour is an integrative signal of multiple parasite infection in blackbird

NASA Astrophysics Data System (ADS)

Biard, Clotilde; Saulnier, Nicolas; Gaillard, Maria; Moreau, Jérôme

2010-11-01

In the study of parasite-mediated sexual selection, there has been controversial evidence for the prediction that brighter males should have fewer parasites. Most of these studies have focused on one parasite species. Our aim was to investigate the expression of carotenoid-based coloured signals in relation to patterns of multiple parasite infections, to determine whether colour reflects parasite load of all parasite species, or whether different relationships might be found when looking at each parasite species independently. We investigated the relationship between bill colour, body mass and plasma carotenoids and parasite load (feather chewing lice, blood parasite Plasmodium sp., intestinal parasites cestodes and coccidia) in the blackbird ( Turdus merula). Bill colour on its own appeared to be a poor predictor of parasite load when investigating its relationships with individual parasite species. Variation in parasite intensities at the community level was summarised using principal component analysis to derive synthetic indexes of relative parasite species abundance and absolute parasite load. The relative abundance of parasite species was strongly related to bill colour, plasma carotenoid levels and body mass: birds with relatively more cestodes and chewing lice and relatively less Plasmodium and coccidia had a more colourful bill, circulated more carotenoids and were heavier. These results suggest that bill colour more accurately reflects the relative intensities of parasite infection, rather than one-by-one relationships with parasites or absolute parasite burden. Investigating patterns of multiple parasite infection would thus improve our understanding of the information conveyed by coloured signals on parasite load.

Optical components damage parameters database system

NASA Astrophysics Data System (ADS)

Tao, Yizheng; Li, Xinglan; Jin, Yuquan; Xie, Dongmei; Tang, Dingyong

2012-10-01

Optical component is the key to large-scale laser device developed by one of its load capacity is directly related to the device output capacity indicators, load capacity depends on many factors. Through the optical components will damage parameters database load capacity factors of various digital, information technology, for the load capacity of optical components to provide a scientific basis for data support; use of business processes and model-driven approach, the establishment of component damage parameter information model and database systems, system application results that meet the injury test optical components business processes and data management requirements of damage parameters, component parameters of flexible, configurable system is simple, easy to use, improve the efficiency of the optical component damage test.

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

The Same Story or a Unique Novel? Within-Participant Principle Component Analysis of Training Load Measures in Professional Rugby Union Skills Training.

PubMed

Weaving, Dan; Dalton, Nicholas E; Black, Christopher; Darrall-Jones, Joshua; Phibbs, Padraic J; Gray, Michael; Jones, Ben; Roe, Gregory A B

2018-03-27

The study aimed to identify which combination of external and internal training load (TL) metrics capture similar or unique information for individual professional players during skills training in rugby union using principal component analysis (PCA). TL data were collected from twenty-one male professional rugby union players across a competitive season. This included PlayerLoad™, total distance (TD), and individualised high-speed distance (HSD; >61% maximal velocity; all external TL) obtained from a micro-technology device worn by each player (Optimeye X4, Catapult Innovations, Melbourne, Australia) and the session-rating of perceived exertion (sRPE; internal TL). PCA was conducted on each individual to extract the underlying combinations of the four TL measures that best describe the total information (variance) provided by the measures. TL measures with PC "loadings" (PC L ) above 0.7 were deemed to possess well-defined relationships with the extracted PC. The findings show that from the four TL measures, the majority of an individual's TL information (1 st PC: 55 to 70%) during skills training can be explained by either sRPE (PC L : 0.72 to 0.95), TD (PC L : 0.86 to 0.98) or PlayerLoad™ (PC L : 0.71 to 0.98). HSD was the only variable to relate to the 2nd PC (PC L : 0.72 to 1.00), which captured additional TL information (+19 to 28%). Findings suggest practitioners could quantify the TL of rugby union skills training with one of PlayerLoad™, TD, or sRPE plus HSD whilst limiting omitted information of the TL imposed during professional rugby union skills training.

Phases of female sexual response cycle among Malaysian women with infertility: a factor analysis study.

PubMed

Seen Heng, Yeoh; Sidi, Hatta; Nik Jaafar, Nik Ruzyanei; Razali, Rosdinom; Ram, Hari

2013-04-01

This cross-sectional study aimed to determine the construct of the phases of the female sexual response cycle (SRC) among women attending an infertility clinic in a Malaysian tertiary center. The sexual response phases were measured with a validated Malay version of the Female Sexual Function Index (FSFI). The correlation structure of the items of the SRC phases (i.e. desire, arousal, orgasm, satisfaction and pain) was determined using principal component analysis (PCA), with varimax rotation method. The number of factors obtained was decided using Kaiser's criteria. A total of 150 married women with a mean age of 32 years participated in this study. Factor loadings using PCA with varimax rotation divided the sexual domains into three components. The first construct comprised sexual arousal, lubrication and pain (suggesting a mechanical component). The second construct were orgasm and sexual satisfaction (suggesting a physical achievement). Sexual desire, suggesting a psychological component, stood on its own as the third. The findings suggest that three constructs could be identified and in favor of the Basson model (a non-linear concept of SRC) for Malaysian women's sexual functioning. Understanding this would help clinicians to strategize the treatment approach of sexual dysfunction in women with infertility. Copyright © 2013 Wiley Publishing Asia Pty Ltd.

Experimental Researches on the Durability Indicators and the Physiological Comfort of Fabrics using the Principal Component Analysis (PCA) Method

NASA Astrophysics Data System (ADS)

Hristian, L.; Ostafe, M. M.; Manea, L. R.; Apostol, L. L.

2017-06-01

The work pursued the distribution of combed wool fabrics destined to manufacturing of external articles of clothing in terms of the values of durability and physiological comfort indices, using the mathematical model of Principal Component Analysis (PCA). Principal Components Analysis (PCA) applied in this study is a descriptive method of the multivariate analysis/multi-dimensional data, and aims to reduce, under control, the number of variables (columns) of the matrix data as much as possible to two or three. Therefore, based on the information about each group/assortment of fabrics, it is desired that, instead of nine inter-correlated variables, to have only two or three new variables called components. The PCA target is to extract the smallest number of components which recover the most of the total information contained in the initial data.

Information extraction from multivariate images

NASA Technical Reports Server (NTRS)

Park, S. K.; Kegley, K. A.; Schiess, J. R.

1986-01-01

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

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

PubMed

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

2016-10-01

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

Distinguishing grief from depression during acute recovery from spinal cord injury.

PubMed

Klyce, Daniel W; Bombardier, Charles H; Davis, Trevor J; Hartoonian, Narineh; Hoffman, Jeanne M; Fann, Jesse R; Kalpakjian, Claire Z

2015-08-01

To examine whether grief is a psychometrically sound construct that is distinct from depression in individuals who have recently sustained a spinal cord injury (SCI). Cross-sectional survey. Inpatient rehabilitation units at 3 geographically diverse, university-affiliated medical centers. Patients with SCI (N=206) were recruited (163 men [79.1%]). Most patients were non-Hispanic whites (n=175 [85.0%]). Most patients sustained a cervical SCI (n=134 [64.4%]). Various injury etiologies were represented, with the majority being accounted for by falls (n=72 [31.5%]) and vehicle-related accidents (n=69 [33.5%]). The mean time since injury was 53.5±40.5 days. Not applicable. An adapted version of the 12-item structured clinical interview for Prolonged Grief Disorder was used to assess symptoms of grief, and the Patient Health Questionnaire-9 was used to measure depression. Demographic and injury-related data were also collected. A principal component analysis (with direct oblimin rotation) of the grief measure suggested a 2-component solution. The content of items loading on the separate components suggested 2 subscales: loss (6 items; Cronbach α=.810) and trauma (6 items; Cronbach α=.823). Follow-up principal component analyses including both grief and depression measures suggested clear differentiation of grief-related loss from depression. The prevalence of clinically significant levels of grief was low (6%), and levels of depression were consistent with previous findings related to inpatient rehabilitation (23.5%). The items used to assess grief symptoms in patients participating in inpatient rehabilitation for recently sustained SCI appear to capture a psychometrically reliable construct that is distinct from that of depression. Research is needed on the predictive validity of early grief symptoms after SCI and the relation of grief to other psychological constructs over time. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

ERIC Educational Resources Information Center

Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

Analysis of the principal component algorithm in phase-shifting interferometry.

PubMed

Vargas, J; Quiroga, J Antonio; Belenguer, T

2011-06-15

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

Psychometric Measurement Models and Artificial Neural Networks

ERIC Educational Resources Information Center

Sese, Albert; Palmer, Alfonso L.; Montano, Juan J.

2004-01-01

The study of measurement models in psychometrics by means of dimensionality reduction techniques such as Principal Components Analysis (PCA) is a very common practice. In recent times, an upsurge of interest in the study of artificial neural networks apt to computing a principal component extraction has been observed. Despite this interest, the…

Burst and Principal Components Analyses of MEA Data for 16 Chemicals Describe at Least Three Effects Classes.

EPA Science Inventory

Microelectrode arrays (MEAs) detect drug and chemical induced changes in neuronal network function and have been used for neurotoxicity screening. As a proof-•of-concept, the current study assessed the utility of analytical "fingerprinting" using Principal Components Analysis (P...

Incremental principal component pursuit for video background modeling

DOEpatents

Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt

2017-03-14

An incremental Principal Component Pursuit (PCP) algorithm for video background modeling that is able to process one frame at a time while adapting to changes in background, with a computational complexity that allows for real-time processing, having a low memory footprint and is robust to translational and rotational jitter.

MFTF-. cap alpha. + T progress report

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

Nelson, W.D.

1985-04-01

Early in FY 1983, several upgrades of the Mirror Fusion Test Facility (MFTF-B) at Lawrence Livermore National Laboratory (LLNL) were proposed to the fusion community. The one most favorably received was designated MFTF-..cap alpha..+T. The engineering design of this device, guided by LLNL, has been a principal activity of the Fusion Engineering Design Center during FY 1983. This interim progress report represents a snapshot of the device design, which was begun in FY 1983 and will continue for several years. The report is organized as a complete design description. Because it is an interim report, some parts are incomplete; theymore » will be supplied as the design study proceeds. As described in this report, MFTF-..cap alpha..+T uses existing facilities, many MFTF-B components, and a number of innovations to improve on the physics parameters of MFTF-B. It burns deuterium-tritium and has a central-cell Q of 2, a wall loading GAMMA/sub n/ of 2 MW/m/sup 2/ (with a central-cell insert module), and an availability of 10%. The machine is fully shielded, allows hands-on maintenance of components outside the vacuum vessel 24 h after shutdown, and has provisions for repair of all operating components.« less

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.

Principal locations of major-ion, trace-element, nitrate, and Escherichia coli loading to Emigration Creek, Salt Lake County, Utah, October 2005

USGS Publications Warehouse

Kimball, Briant A.; Runkel, Robert L.; Walton-Day, Katherine

2008-01-01

Housing development and recreational activity in Emigration Canyon have increased substantially since 1980, perhaps causing an observed decrease in water quality of this northern Utah stream located near Salt Lake City. To identify reaches of the stream that contribute to water-quality degradation, a tracer-injection and synoptic-sampling study was done to quantify mass loading of major ions, trace elements, nitrate, and Escherichia coli (E. coli) to the stream. The resulting mass-loading profiles for major ions and trace elements indicate both geologic and anthropogenic inputs to the stream, principally from tributary and spring inflows to the stream at Brigham Fork, Burr Fork, Wagner Spring, Emigration Tunnel Spring, Blacksmith Hollow, and Killyon Canyon. The pattern of nitrate loading does not correspond to the major-ion and trace-element loading patterns. Nitrate levels in the stream did not exceed water-quality standards at the time of synoptic sampling. The majority of nitrate mass loading can be considered related to anthropogenic input, based on the field settings and trends in stable isotope ratios of nitrogen. The pattern of E. coli loading does not correspond to the major-ion, trace-element, or nitrate loading patterns. The majority of E. coli loading was related to anthropogenic sources based on field setting, but a considerable part of the loading also comes from possible animal sources in Killyon Canyon, in Perkins Flat, and in Rotary Park. In this late summer sampling, E. coli concentrations only exceeded water-quality standards in limited sections of the study reach. The mass-loading approach used in this study provides a means to design future studies and to evaluate the loading on a catchment scale.

Joint Procrustes Analysis for Simultaneous Nonsingular Transformation of Component Score and Loading Matrices

ERIC Educational Resources Information Center

Adachi, Kohei

2009-01-01

In component analysis solutions, post-multiplying a component score matrix by a nonsingular matrix can be compensated by applying its inverse to the corresponding loading matrix. To eliminate this indeterminacy on nonsingular transformation, we propose Joint Procrustes Analysis (JPA) in which component score and loading matrices are simultaneously…

A principal components model of soundscape perception.

PubMed

Axelsson, Östen; Nilsson, Mats E; Berglund, Birgitta

2010-11-01

There is a need for a model that identifies underlying dimensions of soundscape perception, and which may guide measurement and improvement of soundscape quality. With the purpose to develop such a model, a listening experiment was conducted. One hundred listeners measured 50 excerpts of binaural recordings of urban outdoor soundscapes on 116 attribute scales. The average attribute scale values were subjected to principal components analysis, resulting in three components: Pleasantness, eventfulness, and familiarity, explaining 50, 18 and 6% of the total variance, respectively. The principal-component scores were correlated with physical soundscape properties, including categories of dominant sounds and acoustic variables. Soundscape excerpts dominated by technological sounds were found to be unpleasant, whereas soundscape excerpts dominated by natural sounds were pleasant, and soundscape excerpts dominated by human sounds were eventful. These relationships remained after controlling for the overall soundscape loudness (Zwicker's N(10)), which shows that 'informational' properties are substantial contributors to the perception of soundscape. The proposed principal components model provides a framework for future soundscape research and practice. In particular, it suggests which basic dimensions are necessary to measure, how to measure them by a defined set of attribute scales, and how to promote high-quality soundscapes.

Changes in frontal plane dynamics and the loading response phase of the gait cycle are characteristic of severe knee osteoarthritis application of a multidimensional analysis technique.

PubMed

Astephen, J L; Deluzio, K J

2005-02-01

Osteoarthritis of the knee is related to many correlated mechanical factors that can be measured with gait analysis. Gait analysis results in large data sets. The analysis of these data is difficult due to the correlated, multidimensional nature of the measures. A multidimensional model that uses two multivariate statistical techniques, principal component analysis and discriminant analysis, was used to discriminate between the gait patterns of the normal subject group and the osteoarthritis subject group. Nine time varying gait measures and eight discrete measures were included in the analysis. All interrelationships between and within the measures were retained in the analysis. The multidimensional analysis technique successfully separated the gait patterns of normal and knee osteoarthritis subjects with a misclassification error rate of <6%. The most discriminatory feature described a static and dynamic alignment factor. The second most discriminatory feature described a gait pattern change during the loading response phase of the gait cycle. The interrelationships between gait measures and between the time instants of the gait cycle can provide insight into the mechanical mechanisms of pathologies such as knee osteoarthritis. These results suggest that changes in frontal plane loading and alignment and the loading response phase of the gait cycle are characteristic of severe knee osteoarthritis gait patterns. Subsequent investigations earlier in the disease process may suggest the importance of these factors to the progression of knee osteoarthritis.

Occurrence and distribution of bacteria indicators, chemical tracers and pathogenic vibrios in Singapore coastal waters.

PubMed

Goh, Shin Giek; Bayen, Stéphane; Burger, David; Kelly, Barry C; Han, Ping; Babovic, Vladan; Gin, Karina Yew-Hoong

2017-01-15

Water quality in Singapore's coastal area was evaluated with microbial indicators, pathogenic vibrios, chemical tracers and physico-chemical parameters. Sampling sites were grouped into two clusters (coastal sites at (i) northern and (ii) southern part of Singapore). The coastal sites located at northern part of Singapore along the Johor Straits exhibited greater pollution. Principal component analysis revealed that sampling sites at Johor Straits have greater loading on carbamazepine, while turbidity poses greater influence on sampling sites at Singapore Straits. Detection of pathogenic vibrios was also more prominent at Johor Straits than the Singapore Straits. This study examined the spatial variations in Singapore's coastal water quality and provided the baseline information for health risk assessment and future pollution management. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Spanish-Language Risk Perception Survey for Developing Diabetes: Translation Process and Assessment of Psychometric Properties.

PubMed

Joiner, Kevin L; Sternberg, Rosa Maria; Kennedy, Christine; Chen, Jyu-Lin; Fukuoka, Yoshimi; Janson, Susan L

2016-12-01

Create a Spanish-language version of the Risk Perception Survey for Developing Diabetes (RPS-DD) and assess psychometric properties. The Spanish-language version was created through translation, harmonization, and presentation to the tool's original author. It was field tested in a foreignborn Latino sample and properties evaluated in principal components analysis. Personal Control, Optimistic Bias, and Worry multi-item Likert subscale responses did not cluster together. A clean solution was obtained after removing two Personal Control subscale items. Neither the Personal Disease Risk scale nor the Environmental Health Risk scale responses loaded onto single factors. Reliabilities ranged from .54 to .88. Test of knowledge performance varied by item. This study contributes to evidence of validation of a Spanish-language RPS-DD in foreign-born Latinos.

Nitrogen Loading in Jamaica Bay, Long Island, New York: Predevelopment to 2005

USGS Publications Warehouse

Benotti, Mark J.; Abbene, Irene; Terracciano, Stephen A.

2007-01-01

Nitrogen loading to Jamaica Bay, a highly urbanized estuary on the southern shore of western Long Island, New York, has increased from an estimated rate of 35.6 kilograms per day (kg/d) under predevelopment conditions (pre-1900), chiefly as nitrate plus nitrite from ground-water inflow, to an estimated 15,800 kilograms per day as total nitrogen in 2005. The principal point sources are wastewater-treatment plants, combined sewer overflow/stormwater discharge during heavy precipitation, and subway dewatering, which account for 92 percent of the current (2005) nitrogen load. The principal nonpoint sources are landfill leachate, ground-water flow, and atmospheric deposition, which account for 8 percent of the current nitrogen load. The largest single source of nitrogen to Jamaica Bay is wastewater-treatment plants, which account for 89 percent of the nitrogen load. The current and historic contributions of nitrogen from seawater are unknown, although at present, the ocean likely serves as a sink for nitrogen from Jamaica Bay. Currently, concentrations of nitrogen in surface water are high throughout Jamaica Bay, but some areas with relatively little mixing have concentrations that are five times higher than areas that are well mixed.

Application of principal component analysis in protein unfolding: an all-atom molecular dynamics simulation study.

PubMed

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-28

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide-ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

Application of principal component analysis in protein unfolding: An all-atom molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-01

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide—ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

SAS program for quantitative stratigraphic correlation by principal components

USGS Publications Warehouse

Hohn, M.E.

1985-01-01

A SAS program is presented which constructs a composite section of stratigraphic events through principal components analysis. The variables in the analysis are stratigraphic sections and the observational units are range limits of taxa. The program standardizes data in each section, extracts eigenvectors, estimates missing range limits, and computes the composite section from scores of events on the first principal component. Provided is an option of several types of diagnostic plots; these help one to determine conservative range limits or unrealistic estimates of missing values. Inspection of the graphs and eigenvalues allow one to evaluate goodness of fit between the composite and measured data. The program is extended easily to the creation of a rank-order composite. ?? 1985.

Implementation of an integrating sphere for the enhancement of noninvasive glucose detection using quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Werth, Alexandra; Liakat, Sabbir; Dong, Anqi; Woods, Callie M.; Gmachl, Claire F.

2018-05-01

An integrating sphere is used to enhance the collection of backscattered light in a noninvasive glucose sensor based on quantum cascade laser spectroscopy. The sphere enhances signal stability by roughly an order of magnitude, allowing us to use a thermoelectrically (TE) cooled detector while maintaining comparable glucose prediction accuracy levels. Using a smaller TE-cooled detector reduces form factor, creating a mobile sensor. Principal component analysis has predicted principal components of spectra taken from human subjects that closely match the absorption peaks of glucose. These principal components are used as regressors in a linear regression algorithm to make glucose concentration predictions, over 75% of which are clinically accurate.

Full-field stress determination in photoelasticity with phase shifting technique

NASA Astrophysics Data System (ADS)

Guo, Enhai; Liu, Yonggang; Han, Yongsheng; Arola, Dwayne; Zhang, Dongsheng

2018-04-01

Photoelasticity is an effective method for evaluating the stress and its spatial variations within a stressed body. In the present study, a method to determine the stress distribution by means of phase shifting and a modified shear-difference is proposed. First, the orientation of the first principal stress and the retardation between the principal stresses are determined in the full-field through phase shifting. Then, through bicubic interpolation and derivation of a modified shear-difference method, the internal stress is calculated from the point with a free boundary along its normal direction. A method to reduce integration error in the shear difference scheme is proposed and compared to the existing methods; the integration error is reduced when using theoretical photoelastic parameters to calculate the stress component with the same points. Results show that when the value of Δx/Δy approaches one, the error is minimum, and although the interpolation error is inevitable, it has limited influence on the accuracy of the result. Finally, examples are presented for determining the stresses in a circular plate and ring subjected to diametric loading. Results show that the proposed approach provides a complete solution for determining the full-field stresses in photoelastic models.

Principals' Perceptions of Collegial Support as a Component of Administrative Inservice.

ERIC Educational Resources Information Center

Daresh, John C.

To address the problem of increasing professional isolation of building administrators, the Principals' Inservice Project helps establish principals' collegial support groups across the nation. The groups are typically composed of 6 to 10 principals who meet at least once each month over a 2-year period. One collegial support group of seven…

Training the Trainers: Learning to Be a Principal Supervisor

ERIC Educational Resources Information Center

Saltzman, Amy

2017-01-01

While most principal supervisors are former principals themselves, few come to the role with specific training in how to do the job effectively. For this reason, both the Washington, D.C., and Tulsa, Oklahoma, principal supervisor programs include a strong professional development component. In this article, the author takes a look inside these…

Optimal acetabular component orientation estimated using edge-loading and impingement risk in patients with metal-on-metal hip resurfacing arthroplasty.

PubMed

Mellon, Stephen J; Grammatopoulos, George; Andersen, Michael S; Pandit, Hemant G; Gill, Harinderjit S; Murray, David W

2015-01-21

Edge-loading in patients with metal-on-metal resurfaced hips can cause high serum metal ion levels, the development of soft-tissue reactions local to the joint called pseudotumours and ultimately, failure of the implant. Primary edge-loading is where contact between the femoral and acetabular components occurs at the edge/rim of the acetabular component whereas impingement of the femoral neck on the acetabular component's edge causes secondary or contrecoup edge-loading. Although the relationship between the orientation of the acetabular component and primary edge-loading has been identified, the contribution of acetabular component orientation to impingement and secondary edge-loading is less clear. Our aim was to estimate the optimal acetabular component orientation for 16 metal-on-metal hip resurfacing arthroplasty (MoMHRA) subjects with known serum metal ion levels. Data from motion analysis, subject-specific musculoskeletal modelling and Computed Tomography (CT) measurements were used to calculate the dynamic contact patch to rim (CPR) distance and impingement risk for 3416 different acetabular component orientations during gait, sit-to-stand, stair descent and static standing. For each subject, safe zones free from impingement and edge-loading (CPR <10%) were defined and, consequently, an optimal acetabular component orientation was determined (mean inclination 39.7° (SD 6.6°) mean anteversion 14.9° (SD 9.0°)). The results of this study suggest that the optimal acetabular component orientation can be determined from a patient's motion and anatomy. However, 'safe' zones of acetabular component orientation associated with reduced risk of dislocation and pseudotumour are also associated with a reduced risk of edge-loading and impingement. Copyright © 2014 Elsevier Ltd. All rights reserved.

Use of Geochemistry Data Collected by the Mars Exploration Rover Spirit in Gusev Crater to Teach Geomorphic Zonation through Principal Components Analysis

ERIC Educational Resources Information Center

Rodrigue, Christine M.

2011-01-01

This paper presents a laboratory exercise used to teach principal components analysis (PCA) as a means of surface zonation. The lab was built around abundance data for 16 oxides and elements collected by the Mars Exploration Rover Spirit in Gusev Crater between Sol 14 and Sol 470. Students used PCA to reduce 15 of these into 3 components, which,…

An approach to quantify sources, seasonal change, and biogeochemical processes affecting metal loading in streams: Facilitating decisions for remediation of mine drainage

USGS Publications Warehouse

Kimball, B.A.; Runkel, R.L.; Walton-Day, K.

2010-01-01

Historical mining has left complex problems in catchments throughout the world. Land managers are faced with making cost-effective plans to remediate mine influences. Remediation plans are facilitated by spatial mass-loading profiles that indicate the locations of metal mass-loading, seasonal changes, and the extent of biogeochemical processes. Field-scale experiments during both low- and high-flow conditions and time-series data over diel cycles illustrate how this can be accomplished. A low-flow experiment provided spatially detailed loading profiles to indicate where loading occurred. For example, SO42 - was principally derived from sources upstream from the study reach, but three principal locations also were important for SO42 - loading within the reach. During high-flow conditions, Lagrangian sampling provided data to interpret seasonal changes and indicated locations where snowmelt runoff flushed metals to the stream. Comparison of metal concentrations between the low- and high-flow experiments indicated substantial increases in metal loading at high flow, but little change in metal concentrations, showing that toxicity at the most downstream sampling site was not substantially greater during snowmelt runoff. During high-flow conditions, a detailed temporal sampling at fixed sites indicated that Zn concentration more than doubled during the diel cycle. Monitoring programs must account for diel variation to provide meaningful results. Mass-loading studies during different flow conditions and detailed time-series over diel cycles provide useful scientific support for stream management decisions.

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.

A Principal Components Analysis and Validation of the Coping with the College Environment Scale (CWCES)

ERIC Educational Resources Information Center

Ackermann, Margot Elise; Morrow, Jennifer Ann

2008-01-01

The present study describes the development and initial validation of the Coping with the College Environment Scale (CWCES). Participants included 433 college students who took an online survey. Principal Components Analysis (PCA) revealed six coping strategies: planning and self-management, seeking support from institutional resources, escaping…

Wavelet based de-noising of breath air absorption spectra profiles for improved classification by principal component analysis

NASA Astrophysics Data System (ADS)

Kistenev, Yu. V.; Shapovalov, A. V.; Borisov, A. V.; Vrazhnov, D. A.; Nikolaev, V. V.; Nikiforova, O. Yu.

2015-11-01

The comparison results of different mother wavelets used for de-noising of model and experimental data which were presented by profiles of absorption spectra of exhaled air are presented. The impact of wavelets de-noising on classification quality made by principal component analysis are also discussed.

Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

NASA Astrophysics Data System (ADS)

Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

2013-06-01

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

Stability of Nonlinear Principal Components Analysis: An Empirical Study Using the Balanced Bootstrap

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Kooij, Anita J.

2007-01-01

Principal components analysis (PCA) is used to explore the structure of data sets containing linearly related numeric variables. Alternatively, nonlinear PCA can handle possibly nonlinearly related numeric as well as nonnumeric variables. For linear PCA, the stability of its solution can be established under the assumption of multivariate…

40 CFR 60.2998 - What are the principal components of the model rule?

Code of Federal Regulations, 2012 CFR

2012-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

40 CFR 60.2998 - What are the principal components of the model rule?

Code of Federal Regulations, 2014 CFR

2014-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

40 CFR 60.2998 - What are the principal components of the model rule?

Code of Federal Regulations, 2011 CFR

2011-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

40 CFR 60.1580 - What are the principal components of the model rule?

Code of Federal Regulations, 2010 CFR

2010-07-01

... the model rule? 60.1580 Section 60.1580 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines..., 1999 Use of Model Rule § 60.1580 What are the principal components of the model rule? The model rule...

40 CFR 60.2998 - What are the principal components of the model rule?

Code of Federal Regulations, 2013 CFR

2013-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

Students' Perceptions of Teaching and Learning Practices: A Principal Component Approach

ERIC Educational Resources Information Center

Mukorera, Sophia; Nyatanga, Phocenah

2017-01-01

Students' attendance and engagement with teaching and learning practices is perceived as a critical element for academic performance. Even with stipulated attendance policies, students still choose not to engage. The study employed a principal component analysis to analyze first- and second-year students' perceptions of the importance of the 12…

Principal Perspectives about Policy Components and Practices for Reducing Cyberbullying in Urban Schools

ERIC Educational Resources Information Center

Hunley-Jenkins, Keisha Janine

2012-01-01

This qualitative study explores large, urban, mid-western principal perspectives about cyberbullying and the policy components and practices that they have found effective and ineffective at reducing its occurrence and/or negative effect on their schools' learning environments. More specifically, the researcher was interested in learning more…

Principal Component Analysis: Resources for an Essential Application of Linear Algebra

ERIC Educational Resources Information Center

Pankavich, Stephen; Swanson, Rebecca

2015-01-01

Principal Component Analysis (PCA) is a highly useful topic within an introductory Linear Algebra course, especially since it can be used to incorporate a number of applied projects. This method represents an essential application and extension of the Spectral Theorem and is commonly used within a variety of fields, including statistics,…

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…

Applications of Nonlinear Principal Components Analysis to Behavioral Data.

ERIC Educational Resources Information Center

Hicks, Marilyn Maginley

1981-01-01

An empirical investigation of the statistical procedure entitled nonlinear principal components analysis was conducted on a known equation and on measurement data in order to demonstrate the procedure and examine its potential usefulness. This method was suggested by R. Gnanadesikan and based on an early paper of Karl Pearson. (Author/AL)

Relationships between Association of Research Libraries (ARL) Statistics and Bibliometric Indicators: A Principal Components Analysis

ERIC Educational Resources Information Center

Hendrix, Dean

2010-01-01

This study analyzed 2005-2006 Web of Science bibliometric data from institutions belonging to the Association of Research Libraries (ARL) and corresponding ARL statistics to find any associations between indicators from the two data sets. Principal components analysis on 36 variables from 103 universities revealed obvious associations between…

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.

Principal Component 2-D Long Short-Term Memory for Font Recognition on Single Chinese Characters.

PubMed

Tao, Dapeng; Lin, Xu; Jin, Lianwen; Li, Xuelong

2016-03-01

Chinese character font recognition (CCFR) has received increasing attention as the intelligent applications based on optical character recognition becomes popular. However, traditional CCFR systems do not handle noisy data effectively. By analyzing in detail the basic strokes of Chinese characters, we propose that font recognition on a single Chinese character is a sequence classification problem, which can be effectively solved by recurrent neural networks. For robust CCFR, we integrate a principal component convolution layer with the 2-D long short-term memory (2DLSTM) and develop principal component 2DLSTM (PC-2DLSTM) algorithm. PC-2DLSTM considers two aspects: 1) the principal component layer convolution operation helps remove the noise and get a rational and complete font information and 2) simultaneously, 2DLSTM deals with the long-range contextual processing along scan directions that can contribute to capture the contrast between character trajectory and background. Experiments using the frequently used CCFR dataset suggest the effectiveness of PC-2DLSTM compared with other state-of-the-art font recognition methods.

Dynamic of consumer groups and response of commodity markets by principal component analysis

NASA Astrophysics Data System (ADS)

Nobi, Ashadun; Alam, Shafiqul; Lee, Jae Woo

2017-09-01

This study investigates financial states and group dynamics by applying principal component analysis to the cross-correlation coefficients of the daily returns of commodity futures. The eigenvalues of the cross-correlation matrix in the 6-month timeframe displays similar values during 2010-2011, but decline following 2012. A sharp drop in eigenvalue implies the significant change of the market state. Three commodity sectors, energy, metals and agriculture, are projected into two dimensional spaces consisting of two principal components (PC). We observe that they form three distinct clusters in relation to various sectors. However, commodities with distinct features have intermingled with one another and scattered during severe crises, such as the European sovereign debt crises. We observe the notable change of the position of two dimensional spaces of groups during financial crises. By considering the first principal component (PC1) within the 6-month moving timeframe, we observe that commodities of the same group change states in a similar pattern, and the change of states of one group can be used as a warning for other group.

[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.

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

Hyperspectral optical imaging of human iris in vivo: characteristics of reflectance spectra

NASA Astrophysics Data System (ADS)

Medina, José M.; Pereira, Luís M.; Correia, Hélder T.; Nascimento, Sérgio M. C.

2011-07-01

We report a hyperspectral imaging system to measure the reflectance spectra of real human irises with high spatial resolution. A set of ocular prosthesis was used as the control condition. Reflectance data were decorrelated by the principal-component analysis. The main conclusion is that spectral complexity of the human iris is considerable: between 9 and 11 principal components are necessary to account for 99% of the cumulative variance in human irises. Correcting image misalignments associated with spontaneous ocular movements did not influence this result. The data also suggests a correlation between the first principal component and different levels of melanin present in the irises. It was also found that although the spectral characteristics of the first five principal components were not affected by the radial and angular position of the selected iridal areas, they affect the higher-order ones, suggesting a possible influence of the iris texture. The results show that hyperspectral imaging in the iris, together with adequate spectroscopic analyses provide more information than conventional colorimetric methods, making hyperspectral imaging suitable for the characterization of melanin and the noninvasive diagnosis of ocular diseases and iris color.

Seeing wholes: The concept of systems thinking and its implementation in school leadership

NASA Astrophysics Data System (ADS)

Shaked, Haim; Schechter, Chen

2013-12-01

Systems thinking (ST) is an approach advocating thinking about any given issue as a whole, emphasising the interrelationships between its components rather than the components themselves. This article aims to link ST and school leadership, claiming that ST may enable school principals to develop highly performing schools that can cope successfully with current challenges, which are more complex than ever before in today's era of accountability and high expectations. The article presents the concept of ST - its definition, components, history and applications. Thereafter, its connection to education and its contribution to school management are described. The article concludes by discussing practical processes including screening for ST-skilled principal candidates and developing ST skills among prospective and currently performing school principals, pinpointing three opportunities for skills acquisition: during preparatory programmes; during their first years on the job, supported by veteran school principals as mentors; and throughout their entire career. Such opportunities may not only provide school principals with ST skills but also improve their functioning throughout the aforementioned stages of professional development.

A modified procedure for mixture-model clustering of regional geochemical data

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David B.; Horton, John D.

2014-01-01

A modified procedure is proposed for mixture-model clustering of regional-scale geochemical data. The key modification is the robust principal component transformation of the isometric log-ratio transforms of the element concentrations. This principal component transformation and the associated dimension reduction are applied before the data are clustered. The principal advantage of this modification is that it significantly improves the stability of the clustering. The principal disadvantage is that it requires subjective selection of the number of clusters and the number of principal components. To evaluate the efficacy of this modified procedure, it is applied to soil geochemical data that comprise 959 samples from the state of Colorado (USA) for which the concentrations of 44 elements are measured. The distributions of element concentrations that are derived from the mixture model and from the field samples are similar, indicating that the mixture model is a suitable representation of the transformed geochemical data. Each cluster and the associated distributions of the element concentrations are related to specific geologic and anthropogenic features. In this way, mixture model clustering facilitates interpretation of the regional geochemical data.

Temporal evolution of financial-market correlations.

PubMed

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

2011-08-01

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

Temporal evolution of financial-market correlations

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

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.%}

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.

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Thermal load leveling during silicon crystal growth from a melt using anisotropic materials

DOEpatents

Carlson, Frederick M.; Helenbrook, Brian T.

2016-10-11

An apparatus for growing a silicon crystal substrate comprising a heat source, an anisotropic thermal load leveling component, a crucible, and a cold plate component is disclosed. The anisotropic thermal load leveling component possesses a high thermal conductivity and may be positioned atop the heat source to be operative to even-out temperature and heat flux variations emanating from the heat source. The crucible may be operative to contain molten silicon in which the top surface of the molten silicon may be defined as a growth interface. The crucible may be substantially surrounded by the anisotropic thermal load leveling component. The cold plate component may be positioned above the crucible to be operative with the anisotropic thermal load leveling component and heat source to maintain a uniform heat flux at the growth surface of the molten silicon.

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

Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

PubMed

Gao, Hao; Zhang, Yawei; Ren, Lei; Yin, Fang-Fang

2018-01-01

This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images. In the proposed PCR method, the matrix factorization is utilized as an explicit low-rank regularization of 4D images that are represented as a product of spatial principal components and temporal motion coefficients. The key hypothesis of PCR is that temporal coefficients from 4D images can be reasonably approximated by temporal coefficients learned from 2D fluoroscopic training projections. For this purpose, we can acquire fluoroscopic training projections for a few breathing periods at fixed gantry angles that are free from geometric distortion due to gantry rotation, that is, fluoroscopy-based motion learning. Such training projections can provide an effective characterization of the breathing motion. The temporal coefficients can be extracted from these training projections and used as priors for PCR, even though principal components from training projections are certainly not the same for these 4D images to be reconstructed. For this purpose, training data are synchronized with reconstruction data using identical real-time breathing position intervals for projection binning. In terms of image reconstruction, with a priori temporal coefficients, the data fidelity for PCR changes from nonlinear to linear, and consequently, the PCR method is robust and can be solved efficiently. PCR is formulated as a convex optimization problem with the sum of linear data fidelity with respect to spatial principal components and spatiotemporal total variation regularization imposed on 4D image phases. The solution algorithm of PCR is developed based on alternating direction method of multipliers. The implementation is fully parallelized on GPU with NVIDIA CUDA toolbox and each reconstruction takes about a few minutes. The proposed PCR method is validated and compared with a state-of-art method, that is, PICCS, using both simulation and experimental data with the on-board cone-beam CT setting. The results demonstrated the feasibility of PCR for cine CBCT and significantly improved reconstruction quality of PCR from PICCS for cine CBCT. With a priori estimated temporal motion coefficients using fluoroscopic training projections, the PCR method can accurately reconstruct spatial principal components, and then generate cine CT images as a product of temporal motion coefficients and spatial principal components. © 2017 American Association of Physicists in Medicine.

Prestressing Shock Resistant Mechanical Components and Mechanisms Made from Hard, Superelastic Materials

NASA Technical Reports Server (NTRS)

DellaCorte, Christopher (Inventor)

2014-01-01

A method and an apparatus confer full superelastic properties to the active surface of a mechanical component constructed of a superelastic material prior to service. A compressive load is applied to the active surface of the mechanical component followed by removing the compressive load from the active surface whereby substantially all load strain is recoverable after applying and removing of subsequent compressive loads.

Sensitivity and diagnosticity of NASA-TLX and simplified SWAT to assess the mental workload associated with operating an agricultural sprayer.

PubMed

Dey, Asit; Mann, Danny D

2010-07-01

The objectives of the present study were: a) to investigate three continuous variants of the NASA-Task Load Index (TLX) (standard NASA (CNASA), average NASA (C1NASA) and principal component NASA (PCNASA)) and five different variants of the simplified subjective workload assessment technique (SSWAT) (continuous standard SSWAT (CSSWAT), continuous average SSWAT (C1SSWAT), continuous principal component SSWAT (PCSSWAT), discrete event-based SSWAT (D1SSWAT) and discrete standard SSWAT (DSSWAT)) in terms of their sensitivity and diagnosticity to assess the mental workload associated with agricultural spraying; b) to compare and select the best variants of NASA-TLX and SSWAT for future mental workload research in the agricultural domain. A total of 16 male university students (mean 30.4 +/- 12.5 years) participated in this study. All the participants were trained to drive an agricultural spraying simulator. Sensitivity was assessed by the ability of the scales to report the maximum change in workload ratings due to the change in illumination and difficulty levels. In addition, the factor loading method was used to quantify sensitivity. The diagnosticity was assessed by the ability of the scale to diagnose the change in task levels from single to dual. Among all the variants of NASA-TLX and SSWAT, PCNASA and discrete variants of SSWAT showed the highest sensitivity and diagnosticity. Moreover, among all the variants of NASA and SSWAT, the discrete variants of SSWAT showed the highest sensitivity and diagnosticity but also high between-subject variability. The continuous variants of both scales had relatively low sensitivity and diagnosticity and also low between-subject variability. Hence, when selecting a scale for future mental workload research in the agricultural domain, a researcher should decide what to compromise: 1) between-subject variability or 2) sensitivity and diagnosticity. STATEMENT OF RELEVANCE: The use of subjective workload scales is very popular in mental workload research. The present study investigated the different variants of two popular workload rating scales (i.e. NASA-TLX and SSWAT) in terms of their sensitivity and diagnositicity and selected the best variants of each scale for future mental workload research.

Food patterns and dietary quality associated with organic food consumption during pregnancy; data from a large cohort of pregnant women in Norway

PubMed Central

2012-01-01

Background Little is known about the consumption of organic food during pregnancy. The aim of this study was to describe dietary characteristics associated with frequent consumption of organic food among pregnant women participating in the Norwegian Mother and Child Cohort Study (MoBa). Methods The present study includes 63 808 women who during the years 2002–2007 answered two questionnaires, a general health questionnaire at gestational weeks 15 and a food frequency questionnaire at weeks 17-22. The exploration of food patterns by Principal component analyses (PCA) was followed by ANOVA analyses investigating how these food patterns as well as intake of selected food groups were associated with consumption of organic food. Results The first principal component (PC1) identified by PCA, accounting for 12% of the variation, was interpreted as a ‘health and sustainability component’, with high positive loadings for vegetables, fruit and berries, cooking oil, whole grain bread and cereal products and negative loadings for meat, including processed meat, white bread, and cakes and sweets. Frequent consumption of organic food, which was reported among 9.1% of participants (n = 5786), was associated with increased scores on the ‘health and sustainability component’ (p < 0.001). The increase in score represented approximately 1/10 of the total variation and was independent of sociodemographic and lifestyle characteristics. Participants with frequent consumption of organic food had a diet with higher density of fiber and most nutrients such as folate, beta-carotene and vitamin C, and lower density of sodium compared to participants with no or low organic consumption. Conclusion The present study showed that pregnant Norwegian women reporting frequent consumption of organically produced food had dietary pattern and quality more in line with public advice for healthy and sustainable diets. A methodological implication is that the overall diet needs to be included in future studies of potential health outcomes related to consumption of organic food during pregnancy. PMID:22862737

Chemometrics-based Approach in Analysis of Arnicae flos

PubMed Central

Zheleva-Dimitrova, Dimitrina Zh.; Balabanova, Vessela; Gevrenova, Reneta; Doichinova, Irini; Vitkova, Antonina

2015-01-01

Introduction: Arnica montana flowers have a long history as herbal medicines for external use on injuries and rheumatic complaints. Objective: To investigate Arnicae flos of cultivated accessions from Bulgaria, Poland, Germany, Finland, and Pharmacy store for phenolic derivatives and sesquiterpene lactones (STLs). Materials and Methods: Samples of Arnica from nine origins were prepared by ultrasound-assisted extraction with 80% methanol for phenolic compounds analysis. Subsequent reverse-phase high-performance liquid chromatography (HPLC) separation of the analytes was performed using gradient elution and ultraviolet detection at 280 and 310 nm (phenolic acids), and 360 nm (flavonoids). Total STLs were determined in chloroform extracts by solid-phase extraction-HPLC at 225 nm. The HPLC generated chromatographic data were analyzed using principal component analysis (PCA) and hierarchical clustering (HC). Results: The highest total amount of phenolic acids was found in the sample from Botanical Garden at Joensuu University, Finland (2.36 mg/g dw). Astragalin, isoquercitrin, and isorhamnetin 3-glucoside were the main flavonol glycosides being present up to 3.37 mg/g (astragalin). Three well-defined clusters were distinguished by PCA and HC. Cluster C1 comprised of the German and Finnish accessions characterized by the highest content of flavonols. Cluster C2 included the Bulgarian and Polish samples presenting a low content of flavonoids. Cluster C3 consisted only of one sample from a pharmacy store. Conclusion: A validated HPLC method for simultaneous determination of phenolic acids, flavonoid glycosides, and aglycones in A. montana flowers was developed. The PCA loading plot showed that quercetin, kaempferol, and isorhamnetin can be used to distinguish different Arnica accessions. SUMMARY A principal component analysis (PCA) on 13 phenolic compounds and total amount of sesquiterpene lactones in Arnicae flos collection tended to cluster the studied 9 accessions into three main groups. The profiles obtained demonstrated that the samples from Germany and Finland are characterized by greater amounts of phenolic derivatives than the Bulgarian and Polish ones. The PCA loading plot showed that quercetin, kaemferol and isorhamnetin can be used to distinguish different arnica accessions. PMID:27013791

Cultivating an Environment that Contributes to Teaching and Learning in Schools: High School Principals' Actions

ERIC Educational Resources Information Center

Lin, Mind-Dih

2012-01-01

Improving principal leadership is a vital component to the success of educational reform initiatives that seek to improve whole-school performance, as principal leadership often exercises positive but indirect effects on student learning. Because of the importance of principals within the field of school improvement, this article focuses on…

Measuring Principals' Effectiveness: Results from New Jersey's First Year of Statewide Principal Evaluation. REL 2016-156

ERIC Educational Resources Information Center

Herrmann, Mariesa; Ross, Christine

2016-01-01

States and districts across the country are implementing new principal evaluation systems that include measures of the quality of principals' school leadership practices and measures of student achievement growth. Because these evaluation systems will be used for high-stakes decisions, it is important that the component measures of the evaluation…

The Views of Novice and Late Career Principals Concerning Instructional and Organizational Leadership within Their Evaluation

ERIC Educational Resources Information Center

Hvidston, David J.; Range, Bret G.; McKim, Courtney Ann; Mette, Ian M.

2015-01-01

This study examined the perspectives of novice and late career principals concerning instructional and organizational leadership within their performance evaluations. An online survey was sent to 251 principals with a return rate of 49%. Instructional leadership components of the evaluation that were most important to all principals were:…

17 CFR 270.22d-1 - Exemption from section 22(d) to permit sales of redeemable securities at prices which reflect...

Code of Federal Regulations, 2010 CFR

2010-04-01

... registered investment company that is the issuer of redeemable securities, a principal underwriter of such... load to particular classes of investors or transactions, Provided, That: (a) The company, the principal underwriter and dealers in the company's shares apply any scheduled variation uniformly to all offerees in the...

Blending Together, Step by Step: Principal Uses Professional Learning to Combine Two School Cultures into One

ERIC Educational Resources Information Center

Martin, Linda E.; Shafer, Tracy; Kragler, Sherry

2009-01-01

There is no denying that combining two schools, or even opening a new school, is loaded with challenges and frustrations as well as high expectations. Principal Tracy Shafer saw a rural school consolidation as an opportunity to use professional development to create a community focused on student learning, meeting the need for high-quality…

Mapping ash properties using principal components analysis

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Cerda, Artemi; Ubeda, Xavier; Novara, Agata; Francos, Marcos; Rodrigo-Comino, Jesus; Bogunovic, Igor; Khaledian, Yones

2017-04-01

In post-fire environments ash has important benefits for soils, such as protection and source of nutrients, crucial for vegetation recuperation (Jordan et al., 2016; Pereira et al., 2015a; 2016a,b). The thickness and distribution of ash are fundamental aspects for soil protection (Cerdà and Doerr, 2008; Pereira et al., 2015b) and the severity at which was produced is important for the type and amount of elements that is released in soil solution (Bodi et al., 2014). Ash is very mobile material, and it is important were it will be deposited. Until the first rainfalls are is very mobile. After it, bind in the soil surface and is harder to erode. Mapping ash properties in the immediate period after fire is complex, since it is constantly moving (Pereira et al., 2015b). However, is an important task, since according the amount and type of ash produced we can identify the degree of soil protection and the nutrients that will be dissolved. The objective of this work is to apply to map ash properties (CaCO3, pH, and select extractable elements) using a principal component analysis (PCA) in the immediate period after the fire. Four days after the fire we established a grid in a 9x27 m area and took ash samples every 3 meters for a total of 40 sampling points (Pereira et al., 2017). The PCA identified 5 different factors. Factor 1 identified high loadings in electrical conductivity, calcium, and magnesium and negative with aluminum and iron, while Factor 3 had high positive loadings in total phosphorous and silica. Factor 3 showed high positive loadings in sodium and potassium, factor 4 high negative loadings in CaCO3 and pH, and factor 5 high loadings in sodium and potassium. The experimental variograms of the extracted factors showed that the Gaussian model was the most precise to model factor 1, the linear to model factor 2 and the wave hole effect to model factor 3, 4 and 5. The maps produced confirm the patternd observed in the experimental variograms. Factor 1 and 2 maps showed high values in one area of the plot, while factors 3,4 and 5 had a cycled pattern. Using a PCA we resume the information of all dataset and we identify that ash properties have a different distribution in the studied area, that may be attributed to the different fire severities. References Bodi, M., Martin, D.A., Santin, C., Balfour, V., Doerr, S.H., Pereira, P., Cerda, A., Mataix-Solera, J. (2014) Wildland fire ash: production, composition and eco-hydro-geomorphic effects. Earth-Science Reviews, 130, 103-127. Cerdà A, Doerr SH. (2008) The effect of ash and needle cover on surface runoff and erosion in the immediate post-fire period. Catena 74, 256-263. Jordan, A., Zavala, L., Granjed, A.J., Gordillo-Rivero, A.J., Garcia-Moreno, J., Pereira, P., Barcenas-Moreno, G., Celis, R., Jimenez-Compan, E., Alanis, N. Wettability of ash conditions splash erosion and runoff rates in the postfire. Science of the Total Environment, 572, 1261-1268. Pereira, P. Cerdà, A., Úbeda, X., Mataix-Solera, J. Arcenegui, V., Zavala, L. (2015b) Modelling the impacts of wildfire on ash thickness in a short-term period. Land Degradation and Development, 26, 180-192. Pereira, P., Brevik, E., Cerda, A., Ubeda, X., Novara, A., Francos, M., Comino, R., Bogunovic, I., Khaledian, Y. Mapping ash extractable elements using principal component analysis In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (eds) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006 Pereira, P., Cerdà, A., Jordan, A., Zavala, L., Mataix-Solera, J., Arcenegui, V., Misiune, I., Keesstra, S., Novara, A. (2016) Vegetation recovery after a grassland fire in Lithuania. The effects of fire severity, slope position and aspect. Land Degradation and Development, 27, 1523-1534. Pereira, P., Rein, G., Martin, D. Editorial: Past and Present Post-Fire Environments. Science of the Total Environment, 573, 442-436. Pereira, P., Jordan, A., Cerdà, A., Martin, D. Editorial: The role of ash in fire-affected ecosystems. Catena, 135, 337-379.

Load control system. [for space shuttle external tank ground tests

NASA Technical Reports Server (NTRS)

Grosse, J. C.

1977-01-01

The load control system developed for the shuttle external structural tests is described. The system consists of a load programming/display module, and a load control module along with the following hydraulic system components: servo valves, dump valves, hydraulic system components, and servo valve manifold blocks. One load programming/display subsystem can support multiple load control subsystem modules.

Mechanical signals in plant development: a new method for single cell studies

NASA Technical Reports Server (NTRS)

Lynch, T. M.; Lintilhac, P. M.

1997-01-01

Cell division, which is critical to plant development and morphology, requires the orchestration of hundreds of intracellular processes. In the end, however, cells must make critical decisions, based on a discrete set of mechanical signals such as stress, strain, and shear, to divide in such a way that they will survive the mechanical loads generated by turgor pressure and cell enlargement within the growing tissues. Here we report on a method whereby tobacco protoplasts swirled into a 1.5% agarose entrapment medium will survive and divide. The application of a controlled mechanical load to agarose blocks containing protoplasts orients the primary division plane of the embedded cells. Photoelastic analysis of the agarose entrapment medium can identify the lines of principal stress within the agarose, confirming the hypothesis that cells divide either parallel or perpendicular to the principal stress tensors. The coincidence between the orientation of the new division wall and the orientation of the principal stress tensors suggests that the perception of mechanical stress is a characteristic of individual plant cells. The ability of a cell to determine a shear-free orientation for a new partition wall may be related to the applied load through the deformation of the matrix material. In an isotropic matrix a uniaxial load will produce a rotationally symmetric strain field, which will define a shear-free plane. Where high stress intensities combine with the loading geometry to produce multiaxial loads there will be no axis of rotational symmetry and hence no shear free plane. This suggests that two mechanisms may be orienting the division plane, one a mechanism that works in rotationally symmetrical fields, yielding divisions perpendicular to the compressive tensor, parallel to the long axis of the cell, and one in asymmetric fields, yielding divisions parallel to the short axis of the cell and the compressive tensor.

Study on common seasonal signals in GPS time series and environmental loadings using Multichannel Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Gruszczynska, Marta; Rosat, Severine; Klos, Anna; Bogusz, Janusz

2017-04-01

Seasonal oscillations in the GPS position time series can arise from real geophysical effects and numerical artefacts. According to Dong et al. (2002) environmental loading effects can account for approximately 40% of the total variance of the annual signals in GPS time series, however using generally acknowledged methods (e.g. Least Squares Estimation, Wavelet Decomposition, Singular Spectrum Analysis) to model seasonal signals we are not able to separate real from spurious signals (effects of mismodelling aliased into annual period as well as draconitic). Therefore, we propose to use Multichannel Singular Spectrum Analysis (MSSA) to determine seasonal oscillations (with annual and semi-annual periods) from GPS position time series and environmental loading displacement models. The MSSA approach is an extension of the classical Karhunen-Loève method and it is a special case of SSA for multivariate time series. The main advantage of MSSA is the possibility to extract common seasonal signals for stations from selected area and to investigate the causality between a set of time series as well. In this research, we explored the ability of MSSA application to separate real geophysical effects from spurious effects in GPS time series. For this purpose, we used GPS position changes and environmental loading models. We analysed the topocentric time series from 250 selected stations located worldwide, delivered from Network Solution obtained by the International GNSS Service (IGS) as a contribution to the latest realization of the International Terrestrial Reference System (namely ITRF2014, Rebishung et al., 2016). We also researched atmospheric, hydrological and non-tidal oceanic loading models provided by the EOST/IPGS Loading Service in the Centre-of-Figure (CF) reference frame. The analysed displacements were estimated from ERA-Interim (surface pressure), MERRA-land (soil moisture and snow) as well as ECCO2 ocean bottom pressure. We used Multichannel Singular Spectrum Analysis to determine common seasonal signals in two case studies with adopted a 3-years lag-window as the optimal window size. We also inferred the statistical significance of oscillations through the Monte Carlo MSSA method (Allen and Robertson, 1996). In the first case study, we investigated the common spatio-temporal seasonal signals for all stations. For this purpose, we divided selected stations with respect to the continents. For instance, for stations located in Europe, seasonal oscillations accounts for approximately 45% of the GPS-derived data variance. Much higher variance of seasonal signals is explained by hydrological loadings of about 92%, while the non-tidal oceanic loading accounted for 31% of total variance. In the second case study, we analysed the capability of the MSSA method to establish a causality between several time series. Each of estimated Principal Component represents pattern of the common signal for all analysed data. For ZIMM station (Zimmerwald, Switzerland), the 1st, 2nd and 9th, 10th Principal Components, which accounts for 35% of the variance, corresponds to the annual and semi-annual signals. In this part, we applied the non-parametric MSSA approach to extract the common seasonal signals for GPS time series and environmental loadings for each of the 250 stations with clear statement, that some part of seasonal signal reflects the real geophysical effects. REFERENCES: 1. Allen, M. and Robertson, A.: 1996, Distinguishing modulated oscillations from coloured noise in multivariate datasets. Climate Dynamics, 12, No. 11, 775-784. DOI: 10.1007/s003820050142. 2. Dong, D., Fang, P., Bock, Y., Cheng, M.K. and Miyazaki, S.: 2002, Anatomy of apparent seasonal variations from GPS-derived site position time series. Journal of Geophysical Research, 107, No. B4, 2075. DOI: 10.1029/2001JB000573. 3. Rebischung, P., Altamimi, Z., Ray, J. and Garayt, B.: 2016, The IGS contribution to ITRF2014. Journal of Geodesy, 90, No. 7, 611-630. DOI:10.1007/s00190-016-0897-6.

Checking Dimensionality in Item Response Models with Principal Component Analysis on Standardized Residuals

ERIC Educational Resources Information Center

Chou, Yeh-Tai; Wang, Wen-Chung

2010-01-01

Dimensionality is an important assumption in item response theory (IRT). Principal component analysis on standardized residuals has been used to check dimensionality, especially under the family of Rasch models. It has been suggested that an eigenvalue greater than 1.5 for the first eigenvalue signifies a violation of unidimensionality when there…

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

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.

Matrix partitioning and EOF/principal component analysis of Antarctic Sea ice brightness temperatures

NASA Technical Reports Server (NTRS)

Murray, C. W., Jr.; Mueller, J. L.; Zwally, H. J.

1984-01-01

A field of measured anomalies of some physical variable relative to their time averages, is partitioned in either the space domain or the time domain. Eigenvectors and corresponding principal components of the smaller dimensioned covariance matrices associated with the partitioned data sets are calculated independently, then joined to approximate the eigenstructure of the larger covariance matrix associated with the unpartitioned data set. The accuracy of the approximation (fraction of the total variance in the field) and the magnitudes of the largest eigenvalues from the partitioned covariance matrices together determine the number of local EOF's and principal components to be joined by any particular level. The space-time distribution of Nimbus-5 ESMR sea ice measurement is analyzed.

Fast principal component analysis for stacking seismic data

NASA Astrophysics Data System (ADS)

Wu, Juan; Bai, Min

2018-04-01

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

Multivariate analyses of salt stress and metabolite sensing in auto- and heterotroph Chenopodium cell suspensions.

PubMed

Wongchai, C; Chaidee, A; Pfeiffer, W

2012-01-01

Global warming increases plant salt stress via evaporation after irrigation, but how plant cells sense salt stress remains unknown. Here, we searched for correlation-based targets of salt stress sensing in Chenopodium rubrum cell suspension cultures. We proposed a linkage between the sensing of salt stress and the sensing of distinct metabolites. Consequently, we analysed various extracellular pH signals in autotroph and heterotroph cell suspensions. Our search included signals after 52 treatments: salt and osmotic stress, ion channel inhibitors (amiloride, quinidine), salt-sensing modulators (proline), amino acids, carboxylic acids and regulators (salicylic acid, 2,4-dichlorphenoxyacetic acid). Multivariate analyses revealed hirarchical clusters of signals and five principal components of extracellular proton flux. The principal component correlated with salt stress was an antagonism of γ-aminobutyric and salicylic acid, confirming involvement of acid-sensing ion channels (ASICs) in salt stress sensing. Proline, short non-substituted mono-carboxylic acids (C2-C6), lactic acid and amiloride characterised the four uncorrelated principal components of proton flux. The proline-associated principal component included an antagonism of 2,4-dichlorphenoxyacetic acid and a set of amino acids (hydrophobic, polar, acidic, basic). The five principal components captured 100% of variance of extracellular proton flux. Thus, a bias-free, functional high-throughput screening was established to extract new clusters of response elements and potential signalling pathways, and to serve as a core for quantitative meta-analysis in plant biology. The eigenvectors reorient research, associating proline with development instead of salt stress, and the proof of existence of multiple components of proton flux can help to resolve controversy about the acid growth theory. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

CFD-based design load analysis of 5MW offshore wind turbine

NASA Astrophysics Data System (ADS)

Tran, T. T.; Ryu, G. J.; Kim, Y. H.; Kim, D. H.

2012-11-01

The structure and aerodynamic loads acting on NREL 5MW reference wind turbine blade are calculated and analyzed based on advanced Computational Fluid Dynamics (CFD) and unsteady Blade Element Momentum (BEM). A detailed examination of the six force components has been carried out (three force components and three moment components). Structure load (gravity and inertia load) and aerodynamic load have been obtained by additional structural calculations (CFD or BEM, respectively,). In CFD method, the Reynolds Average Navier-Stokes approach was applied to solve the continuity equation of mass conservation and momentum balance so that the complex flow around wind turbines was modeled. Written in C programming language, a User Defined Function (UDF) code which defines transient velocity profile according to the Extreme Operating Gust condition was compiled into commercial FLUENT package. Furthermore, the unsteady BEM with 3D stall model has also adopted to investigate load components on wind turbine rotor. The present study introduces a comparison between advanced CFD and unsteady BEM for determining load on wind turbine rotor. Results indicate that there are good agreements between both present methods. It is importantly shown that six load components on wind turbine rotor is significant effect under Extreme Operating Gust (EOG) condition. Using advanced CFD and additional structural calculations, this study has succeeded to construct accuracy numerical methodology to estimate total load of wind turbine that compose of aerodynamic load and structure load.

[The application of the multidimensional statistical methods in the evaluation of the influence of atmospheric pollution on the population's health].

PubMed

Surzhikov, V D; Surzhikov, D V

2014-01-01

The search and measurement of causal relationships between exposure to air pollution and health state of the population is based on the system analysis and risk assessment to improve the quality of research. With this purpose there is applied the modern statistical analysis with the use of criteria of independence, principal component analysis and discriminate function analysis. As a result of analysis out of all atmospheric pollutants there were separated four main components: for diseases of the circulatory system main principal component is implied with concentrations of suspended solids, nitrogen dioxide, carbon monoxide, hydrogen fluoride, for the respiratory diseases the main c principal component is closely associated with suspended solids, sulfur dioxide and nitrogen dioxide, charcoal black. The discriminant function was shown to be used as a measure of the level of air pollution.

Priority of VHS Development Based in Potential Area using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs.

PubMed

Azevedo, C F; Nascimento, M; Silva, F F; Resende, M D V; Lopes, P S; Guimarães, S E F; Glória, L S

2015-10-09

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required. Among these methods, independent component regression, principal component regression, partial least squares, and partial principal components stand out. Thus, the aim of this study was to propose an application of the methods of dimensionality reduction to GWS of carcass traits in an F2 (Piau x commercial line) pig population. The results show similarities between the principal and the independent component methods and provided the most accurate genomic breeding estimates for most carcass traits in pigs.

Assessing women's lacrosse head impacts using finite element modelling.

PubMed

Clark, J Michio; Hoshizaki, T Blaine; Gilchrist, Michael D

2018-04-01

Recently studies have assessed the ability of helmets to reduce peak linear and rotational acceleration for women's lacrosse head impacts. However, such measures have had low correlation with injury. Maximum principal strain interprets loading curves which provide better injury prediction than peak linear and rotational acceleration, especially in compliant situations which create low magnitude accelerations but long impact durations. The purpose of this study was to assess head and helmet impacts in women's lacrosse using finite element modelling. Linear and rotational acceleration loading curves from women's lacrosse impacts to a helmeted and an unhelmeted Hybrid III headform were input into the University College Dublin Brain Trauma Model. The finite element model was used to calculate maximum principal strain in the cerebrum. The results demonstrated for unhelmeted impacts, falls and ball impacts produce higher maximum principal strain values than stick and shoulder collisions. The strain values for falls and ball impacts were found to be within the range of concussion and traumatic brain injury. The results also showed that men's lacrosse helmets reduced maximum principal strain for follow-through slashing, falls and ball impacts. These findings are novel and demonstrate that for high risk events, maximum principal strain can be reduced by implementing the use of helmets if the rules of the sport do not effectively manage such situations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Rapid and quantitative detection of the microbial spoilage in chicken meat by diffuse reflectance spectroscopy (600-1100 nm).

PubMed

Lin, M; Al-Holy, M; Mousavi-Hesary, M; Al-Qadiri, H; Cavinato, A G; Rasco, B A

2004-01-01

To evaluate the feasibility of visible and short-wavelength near-infrared (SW-NIR) diffuse reflectance spectroscopy (600-1100 nm) to quantify the microbial loads in chicken meat and to develop a rapid methodology for monitoring the onset of spoilage. Twenty-four prepackaged fresh chicken breast muscle samples were prepared and stored at 21 degrees C for 24 h. Visible and SW-NIR was used to detect and quantify the microbial loads in chicken breast muscle at time intervals of 0, 2, 4, 6, 8, 10, 12 and 24 h. Spectra were collected in the diffuse reflectance mode (600-1100 nm). Total aerobic plate count (APC) of each sample was determined by the spread plate method at 32 degrees C for 48 h. Principal component analysis (PCA) and partial least squares (PLS) based prediction models were developed. PCA analysis showed clear segregation of samples held 8 h or longer compared with 0-h control. An optimum PLS model required eight latent variables for chicken muscle (R = 0.91, SEP = 0.48 log CFU g(-1)). Visible and SW-NIR combined with PCA is capable of perceiving the change of the microbial loads in chicken muscle once the APC increases slightly above 1 log cycle. Accurate quantification of the bacterial loads in chicken muscle can be calculated from the PLS-based prediction method. Visible and SW-NIR spectroscopy is a technique with a considerable potential for monitoring food safety and food spoilage. Visible and SW-NIR can acquire a metabolic snapshot and quantify the microbial loads of food samples rapidly, accurately, and noninvasively. This method would allow for more expeditious applications of quality control in food industries.

Cervicovaginal cytokines, sialidase activity and bacterial load in reproductive-aged women with intermediate vaginal flora.

PubMed

Santos-Greatti, Mariana Morena de Vieira; da Silva, Márcia Guimarães; Ferreira, Carolina Sanitá Tafner; Marconi, Camila

2016-11-01

Studies have shown that not only bacterial vaginosis, but also intermediate vaginal flora has deleterious effects for women's reproductive health. However, literature still lacks information about microbiological and immunological aspects of intermediate flora. To characterize intermediate flora regarding levels of Interleukin (IL)-1beta, IL-6, IL-8, tumor necrosis factor-alpha, interleukin 1 receptor antagonist (IL-1ra), IL-10, sialidase; loads of Gardnerella vaginalis, total bacteria and to verify whether it is closer related to normal flora or bacterial vaginosis. This cross-sectional study enrolled 526 non-pregnant reproductive-aged women distributed in 3 groups according to pattern of vaginal flora using Nugent's system in normal, intermediate and bacterial vaginosis. Cervicovaginal levels of cytokines, sialidases, loads of G. vaginalis and total bacteria were assessed by ELISA, conversion of MUAN and quantitative real-time PCR, respectively. A principal component analysis(PCA) using all measured parameters was performed to compare the three different types of flora. Results showed that intermediate flora is associated with increased cervicovaginal IL-1beta in relation to normal flora(P<0.0001). When compared to bacterial vaginosis, intermediate flora has higher IL-8 and IL-10 levels(P<0.01). Sialidases were in significantly lower levels in normal and intermediate flora than bacterial vaginosis(P<0.0001). Loads of G. vaginalis and total bacterial differed among all groups(P<0.0001), being highest in bacterial vaginosis. PCA showed that normal and intermediate flora were closely scattered, while bacterial vaginosis were grouped separately. Although intermediate flora shows some differences in cytokines, sialidases and bacterial loads in relation to normal flora and bacterial vaginosis, when taken together, general microbiological and immunological pattern pattern of intermediate flora resembles the normal flora. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Adaptation and validation of the Evidence-Based Practice Belief and Implementation scales for French-speaking Swiss nurses and allied healthcare providers.

PubMed

Verloo, Henk; Desmedt, Mario; Morin, Diane

2017-09-01

To evaluate two psychometric properties of the French versions of the Evidence-Based Practice Beliefs and Evidence-Based Practice Implementation scales, namely their internal consistency and construct validity. The Evidence-Based Practice Beliefs and Evidence-Based Practice Implementation scales developed by Melnyk et al. are recognised as valid, reliable instruments in English. However, no psychometric validation for their French versions existed. Secondary analysis of a cross sectional survey. Source data came from a cross-sectional descriptive study sample of 382 nurses and other allied healthcare providers. Cronbach's alpha was used to evaluate internal consistency, and principal axis factor analysis and varimax rotation were computed to determine construct validity. The French Evidence-Based Practice Beliefs and Evidence-Based Practice Implementation scales showed excellent reliability, with Cronbach's alphas close to the scores established by Melnyk et al.'s original versions. Principal axis factor analysis showed medium-to-high factor loading scores without obtaining collinearity. Principal axis factor analysis with varimax rotation of the 16-item Evidence-Based Practice Beliefs scale resulted in a four-factor loading structure. Principal axis factor analysis with varimax rotation of the 17-item Evidence-Based Practice Implementation scale revealed a two-factor loading structure. Further research should attempt to understand why the French Evidence-Based Practice Implementation scale showed a two-factor loading structure but Melnyk et al.'s original has only one. The French versions of the Evidence-Based Practice Beliefs and Evidence-Based Practice Implementation scales can both be considered valid and reliable instruments for measuring Evidence-Based Practice beliefs and implementation. The results suggest that the French Evidence-Based Practice Beliefs and Evidence-Based Practice Implementation scales are valid and reliable and can therefore be used to evaluate the effectiveness of organisational strategies aimed at increasing professionals' confidence in Evidence-Based Practice, supporting its use and implementation. © 2017 John Wiley & Sons Ltd.

Changes in drop-jump landing biomechanics during prolonged intermittent exercise.

PubMed

Schmitz, Randy J; Cone, John C; Tritsch, Amanda J; Pye, Michele L; Montgomery, Melissa M; Henson, Robert A; Shultz, Sandra J

2014-03-01

As injury rates rise in the later stages of sporting activities, a better understanding of lower extremity biomechanics in the later phases of gamelike situations may improve training and injury prevention programs. Lower extremity biomechanics of a drop-jump task (extracted from a principal components analysis) would reveal factors associated with risk of anterior cruciate ligament injury during a 90-minute individualized intermittent exercise protocol (IEP) and for 1 hour following the IEP. Controlled laboratory study. Level 4. Fifty-nine athletes (29 women, 30 men) completed 3 sessions. The first session assessed fitness for an IEP designed to simulate the demands of a soccer match. An experimental session assessed drop-jump biomechanics, after a dynamic warm-up, every 15 minutes during the 90-minute IEP, and for 1 hour following the IEP. A control session with no exercise assessed drop-jump performance at the same intervals. Two biomechanical factors early in the first half (hip flexion at initial contact and hip loading; ankle loading and knee shear force) decreased at the end of the IEP and into the 60-minute recovery period, while a third factor (knee loading) decreased only during the recovery period (P ≤ 0.05). The individualized sport-specific IEP may have more subtle effects on landing biomechanics when compared with short-term, exhaustive fatigue protocols. Potentially injurious landing biomechanics may not occur until the later stages of soccer activity.

The BepiColombo Laser Altimeter (BeLA) power converter module (PCM): Concept and characterisation.

PubMed

Rodrigo, J; Gasquet, E; Castro, J-M; Herranz, M; Lara, L-M; Muñoz, M; Simon, A; Behnke, T; Thomas, N

2017-03-01

This paper presents the principal considerations when designing DC-DC converters for space instruments, in particular for the power converter module as part of the first European space laser altimeter: "BepiColombo Laser Altimeter" on board the European Space Agency-Japan Aerospace Exploration Agency (JAXA) mission BepiColombo. The main factors which determine the design of the DC-DC modules in space applications are printed circuit board occupation, mass, DC-DC converter efficiency, and environmental-survivability constraints. Topics included in the appropriated DC-DC converter design flow are hereby described. The topology and technology for the primary and secondary stages, input filters, transformer design, and peripheral components are discussed. Component selection and design trade-offs are described. Grounding, load and line regulation, and secondary protection circuitry (under-voltage, over-voltage, and over-current) are then introduced. Lastly, test results and characterization of the final flight design are also presented. Testing of the inrush current, the regulated output start-up, and the switching function of the power supply indicate that these performances are fully compliant with the requirements.

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.

Performance-Based Preparation of Principals: A Framework for Improvement. A Special Report of the NASSP Consortium for the Performance-Based Preparation of Principals.

ERIC Educational Resources Information Center

National Association of Secondary School Principals, Reston, VA.

Preparation programs for principals should have excellent academic and performance based components. In examining the nature of performance based principal preparation this report finds that school administration programs must bridge the gap between conceptual learning in the classroom and the requirements of professional practice. A number of…

Numerical Investigation of the Dynamic Properties of Intermittent Jointed Rock Models Subjected to Cyclic Uniaxial Compression

NASA Astrophysics Data System (ADS)

Liu, Yi; Dai, Feng; Zhao, Tao; Xu, Nu-wen

2017-01-01

Intermittent jointed rocks, which exist in a myriad of engineering projects, are extraordinarily susceptible to cyclic loadings. Understanding the dynamic fatigue properties of jointed rocks is necessary for evaluating the stability of rock engineering structures. This study numerically investigated the influences of cyclic loading conditions (i.e., frequency, maximum stress and amplitude) and joint geometric configurations (i.e., dip angle, persistency and interspace) on the dynamic fatigue mechanisms of jointed rock models. A reduction model of stiffness and strength was first proposed, and then, sixteen cyclic uniaxial loading tests with distinct loading parameters and joint geometries were simulated. Our results indicate that the reduction model can effectively reproduce the hysteresis loops and the accumulative plastic deformation of jointed rocks in the cyclic process. Both the loading parameters and the joint geometries significantly affect the dynamic properties, including the irreversible strain, damage evolution, dynamic residual strength and fatigue life. Three failure modes of jointed rocks, which are principally controlled by joint geometries, occur in the simulations: splitting failure through the entire rock sample, sliding failure along joint planes and mixed failure, which are principally controlled by joint geometries. Furthermore, the progressive failure processes of the jointed rock samples are numerically observed, and the different loading stages can be distinguished by the relationship between the number of broken bonds and the axial stress.

Principal component greenness transformation in multitemporal agricultural Landsat data

NASA Technical Reports Server (NTRS)

Abotteen, R. A.

1978-01-01

A data compression technique for multitemporal Landsat imagery which extracts phenological growth pattern information for agricultural crops is described. The principal component greenness transformation was applied to multitemporal agricultural Landsat data for information retrieval. The transformation was favorable for applications in agricultural Landsat data analysis because of its physical interpretability and its relation to the phenological growth of crops. It was also found that the first and second greenness eigenvector components define a temporal small-grain trajectory and nonsmall-grain trajectory, respectively.

Does Maximal External Tibial Component Rotation Influence Tibiofemoral Load Distribution in the Primary Knee Arthroplasty Setting: A Comparison of Neutral vs Maximal Anatomical External Rotatory States.

PubMed

Manning, William A; Ghosh, Kanishka M; Blain, Alasdair P; Longstaff, Lee M; Rushton, Steven P; Deehan, David J

2017-06-01

Tibial component rotation at time of knee arthroplasty can influence conformity, load transmission across the polyethylene surface, and perhaps ultimately determined survivorship. Optimal tibial component rotation on the cut surface is reliant on standard per operative manual stressing. This subjective assessment aims to balance constraint and stability of the articulation through a full arc of movement. Using a cadaveric model, computer navigation and under defined, previously validated loaded conditions mimicking the in vivo setting, the influence of maximal tibial component external rotation compared with the neutral state was examined for changes in laxity and tibiofemoral continuous load using 3D displacement measurement and an orthosensor continuous load sensor implanted within the polyethylene spacer in a simulated single radius total knee arthroplasty. No significant difference was found throughout arc of motion (0-115 degrees of flexion) for maximal varus and/or valgus or rotatory laxity between the 2 states. The neutral state achieved equivalence for mediolateral load distribution at each point of flexion. We have found that external rotation of the tibial component increased medial compartment load in comparison with the neutral position. Compared with the neutral state, external rotation consistently effected a marginal, but not significant reduction in lateral load under similar loading conditions. The effects were most pronounced in midflexion. On the basis of these findings, we would advocate for the midtibial tubercle point to determine tibial component rotation and caution against component external rotation. Copyright © 2017 Elsevier Inc. All rights reserved.

Mapping common aphasia assessments to underlying cognitive processes and their neural substrates

PubMed Central

Lacey, Elizabeth H.; Skipper-Kallal, LM; Xing, S; Fama, ME; Turkeltaub, PE

2017-01-01

Background Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. Objective To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Methods 25 behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high resolution MRI was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. Results The principal components analysis yielded four dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. Conclusions An extensive clinical aphasia assessment identifies four independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual’s specific pattern of deficits and preserved abilities. PMID:28135902

Exercise barriers self-efficacy: development and validation of a subcale for individuals with cancer-related lymphedema.

PubMed

Buchan, Jena; Janda, Monika; Box, Robyn; Rogers, Laura; Hayes, Sandi

2015-03-18

No tool exists to measure self-efficacy for overcoming lymphedema-related exercise barriers in individuals with cancer-related lymphedema. However, an existing scale measures confidence to overcome general exercise barriers in cancer survivors. Therefore, the purpose of this study was to develop, validate and assess the reliability of a subscale, to be used in conjunction with the general barriers scale, for determining exercise barriers self-efficacy in individuals facing lymphedema-related exercise barriers. A lymphedema-specific exercise barriers self-efficacy subscale was developed and validated using a cohort of 106 cancer survivors with cancer-related lymphedema, from Brisbane, Australia. An initial ten-item lymphedema-specific barrier subscale was developed and tested, with participant feedback and principal components analysis results used to guide development of the final version. Validity and test-retest reliability analyses were conducted on the final subscale. The final lymphedema-specific subscale contained five items. Principal components analysis revealed these items loaded highly (>0.75) on a separate factor when tested with a well-established nine-item general barriers scale. The final five-item subscale demonstrated good construct and criterion validity, high internal consistency (Cronbach's alpha = 0.93) and test-retest reliability (ICC = 0.67, p < 0.01). A valid and reliable lymphedema-specific subscale has been developed to assess exercise barriers self-efficacy in individuals with cancer-related lymphedema. This scale can be used in conjunction with an existing general exercise barriers scale to enhance exercise adherence in this understudied patient group.

Geographic variation in floral allometry suggests repeated transitions between selfing and outcrossing in a mixed mating plant.

PubMed

Summers, Holly E; Hartwick, Sally M; Raguso, Robert A

2015-05-01

Isometric and allometric scaling of a conserved floral plan could provide a parsimonious mechanism for rapid and reversible transitions between breeding systems. This scaling may occur during transitions between predominant autogamy and xenogamy, contributing to the maintenance of a stable mixed mating system. We compared nine disjunct populations of the polytypic, mixed mating species Oenothera flava (Onagraceae) to two parapatric relatives, the obligately xenogamous species O. acutissima and the mixed mating species O. triloba. We compared floral morphology of all taxa using principal component analysis (PCA) and developmental trajectories of floral organs using ANCOVA homogeneity of slopes. The PCA revealed both isometric and allometric scaling of a conserved floral plan. Three principal components (PCs) explained 92.5% of the variation in the three species. PC1 predominantly loaded on measures of floral size and accounts for 36% of the variation. PC2 accounted for 35% of the variation, predominantly in traits that influence pollinator handling. PC3 accounted for 22% of the variation, primarily in anther-stigma distance (herkogamy). During O. flava subsp. taraxacoides development, style elongation was accelerated relative to anthers, resulting in positive herkogamy. During O. flava subsp. flava development, style elongation was decelerated, resulting in zero or negative herkogamy. Of the two populations with intermediate morphology, style elongation was accelerated in one population and decelerated in the other. Isometric and allometric scaling of floral organs in North American Oenothera section Lavauxia drive variation in breeding system. Multiple developmental paths to intermediate phenotypes support the likelihood of multiple mating system transitions. © 2015 Botanical Society of America, Inc.

Statistical shape analysis of clavicular cortical bone with applications to the development of mean and boundary shape models.

PubMed

Lu, Yuan-Chiao; Untaroiu, Costin D

2013-09-01

During car collisions, the shoulder belt exposes the occupant's clavicle to large loading conditions which often leads to a bone fracture. To better understand the geometric variability of clavicular cortical bone which may influence its injury tolerance, twenty human clavicles were evaluated using statistical shape analysis. The interior and exterior clavicular cortical bone surfaces were reconstructed from CT-scan images. Registration between one selected template and the remaining 19 clavicle models was conducted to remove translation and rotation differences. The correspondences of landmarks between the models were then established using coordinates and surface normals. Three registration methods were compared: the LM-ICP method; the global method; and the SHREC method. The LM-ICP registration method showed better performance than the global and SHREC registration methods, in terms of compactness, generalization, and specificity. The first four principal components obtained by using the LM-ICP registration method account for 61% and 67% of the overall anatomical variation for the exterior and interior cortical bone shapes, respectively. The length was found to be the most significant variation mode of the human clavicle. The mean and two boundary shape models were created using the four most significant principal components to investigate the size and shape variation of clavicular cortical bone. In the future, boundary shape models could be used to develop probabilistic finite element models which may help to better understand the variability in biomechanical responses and injuries to the clavicle. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Validating a Cantonese short version of the Zarit Burden Interview (CZBI-Short) for dementia caregivers.

PubMed

Tang, Jennifer Yee-Man; Ho, Andy Hau-Yan; Luo, Hao; Wong, Gloria Hoi-Yan; Lau, Bobo Hi-Po; Lum, Terry Yat-Sang; Cheung, Karen Siu-Lan

2016-09-01

The present study aimed to develop and validate a Cantonese short version of the Zarit Burden Interview (CZBI-Short) for Hong Kong Chinese dementia caregivers. The 12-item Zarit Burden Interview (ZBI) was translated into spoken Cantonese and back-translated by two bilingual research assistants and face validated by a panel of experts. Five hundred Chinese dementia caregivers showing signs of stress reported their burden using the translated ZBI and rated their depressive symptoms, overall health, and care recipients' physical functioning and behavioral problems. The factor structure of the translated scale was identified using principal component analysis and confirmatory factor analysis; internal consistency and item-total correlations were assessed; and concurrent validity was tested by correlating the ZBI with depressive symptoms, self-rated health, and care recipients' physical functioning and behavioral problems. The principal component analysis resulted in 11 items loading on a three-factor model comprised role strain, self-criticism, and negative emotion, which accounted for 59% of the variance. The confirmatory factor analysis supported the three-factor model (CZBI-Short) that explained 61% of the total variance. Cronbach's alpha (0.84) and item-total correlations (rho = 0.39-0.71) indicated CZBI-Short had good reliability. CZBI-Short showed correlations with depressive symptoms (r = 0.50), self-rated health (r = -0.26) and care recipients' physical functioning (r = 0.18-0.26) and disruptive behaviors (r = 0.36). The 12-item CZBI-Short is a concise, reliable, and valid instrument to assess burden in Chinese dementia caregivers in clinical and social care settings.

Locomotor Recovery in Spinal Cord Injury: Insights Beyond Walking Speed and Distance.

PubMed

Awai, Lea; Curt, Armin

2016-08-01

Recovery of locomotor function after incomplete spinal cord injury (iSCI) is clinically assessed through walking speed and distance, while improvements in these measures might not be in line with a normalization of gait quality and are, on their own, insensitive at revealing potential mechanisms underlying recovery. The objective of this study was to relate changes of gait parameters to the recovery of walking speed while distinguishing between parameters that rather reflect speed improvements from factors contributing to overall recovery. Kinematic data of 16 iSCI subjects were repeatedly recorded during in-patient rehabilitation. The responsiveness of gait parameters to walking speed was assessed by linear regression. Principal component analysis (PCA) was applied on the multivariate data across time to identify factors that contribute to recovery after iSCI. Parameters of gait cycle and movement dynamics were both responsive and closely related to the recovery of walking speed, which increased by 96%. Multivariate analysis revealed specific gait parameters (intralimb shape normality and consistency) that, although less related to speed increments, loaded highly on principal component one (PC1) (58.6%) explaining the highest proportion of variance (i.e., recovery of outcome over time). Interestingly, measures of hip, knee, and ankle range of motion showed varying degrees of responsiveness (from very high to very low) while not contributing to gait recovery as revealed by PCA. The conjunct application of two analysis methods distinguishes gait parameters that simply reflect increased walking speed from parameters that actually contribute to gait recovery in iSCI. This distinction may be of value for the evaluation of interventions for locomotor recovery.

A psychometric appraisal of the Jefferson Scale of Empathy using law students

PubMed Central

Williams, Brett; Sifris, Adiva; Lynch, Marty

2016-01-01

Background A growing body of literature indicates that empathic behaviors are positively linked, in several ways, with the professional performance and mental well-being of lawyers and law students. It is therefore important to assess empathy levels among law students using psychometrically sound tools that are suitable for this cohort. Participants and methods The 20-item Jefferson Scale of Empathy – Health Profession Students Version was adapted for a law context (eg, the word “health care” became “legal”), and the new Jefferson Scale of Empathy – Law Students (JSE-L-S) version was completed by 275 students at Monash University, Melbourne, Australia. Data were subjected to principal component analysis. Results Four factors emerged from the principal component analysis (“understanding the client’s perspective”, “responding to clients’ experiences and emotions”, “responding to clients’ cues and behaviors”, and “standing in clients’ shoes”), which accounted for 46.7% of the total variance. The reliability of the factors varied, but the overall 18-item JSE-L-S yielded a Cronbach’s alpha coefficient of 0.80. Several patterns among the item loadings were similar to those reported in studies using other versions of the Jefferson Scale of Empathy. Conclusion The JSE-L-S appears to be a reliable measure of empathy among undergraduate law students, which could help provide insights into law student welfare and future performance as legal practitioners. Additional evaluation of the JSE-L-S is required to disambiguate some of the minor findings explored. Adjustments may improve the psychometric properties. PMID:27524924

Predicting Visual Disability in Glaucoma With Combinations of Vision Measures.

PubMed

Lin, Stephanie; Mihailovic, Aleksandra; West, Sheila K; Johnson, Chris A; Friedman, David S; Kong, Xiangrong; Ramulu, Pradeep Y

2018-04-01

We characterized vision in glaucoma using seven visual measures, with the goals of determining the dimensionality of vision, and how many and which visual measures best model activity limitation. We analyzed cross-sectional data from 150 older adults with glaucoma, collecting seven visual measures: integrated visual field (VF) sensitivity, visual acuity, contrast sensitivity (CS), area under the log CS function, color vision, stereoacuity, and visual acuity with noise. Principal component analysis was used to examine the dimensionality of vision. Multivariable regression models using one, two, or three vision tests (and nonvisual predictors) were compared to determine which was best associated with Rasch-analyzed Glaucoma Quality of Life-15 (GQL-15) person measure scores. The participants had a mean age of 70.2 and IVF sensitivity of 26.6 dB, suggesting mild-to-moderate glaucoma. All seven vision measures loaded similarly onto the first principal component (eigenvectors, 0.220-0.442), which explained 56.9% of the variance in vision scores. In models for GQL scores, the maximum adjusted- R 2 values obtained were 0.263, 0.296, and 0.301 when using one, two, and three vision tests in the models, respectively, though several models in each category had similar adjusted- R 2 values. All three of the best-performing models contained CS. Vision in glaucoma is a multidimensional construct that can be described by several variably-correlated vision measures. Measuring more than two vision tests does not substantially improve models for activity limitation. A sufficient description of disability in glaucoma can be obtained using one to two vision tests, especially VF and CS.

Prediction of genomic breeding values for dairy traits in Italian Brown and Simmental bulls using a principal component approach.

PubMed

Pintus, M A; Gaspa, G; Nicolazzi, E L; Vicario, D; Rossoni, A; Ajmone-Marsan, P; Nardone, A; Dimauro, C; Macciotta, N P P

2012-06-01

The large number of markers available compared with phenotypes represents one of the main issues in genomic selection. In this work, principal component analysis was used to reduce the number of predictors for calculating genomic breeding values (GEBV). Bulls of 2 cattle breeds farmed in Italy (634 Brown and 469 Simmental) were genotyped with the 54K Illumina beadchip (Illumina Inc., San Diego, CA). After data editing, 37,254 and 40,179 single nucleotide polymorphisms (SNP) were retained for Brown and Simmental, respectively. Principal component analysis carried out on the SNP genotype matrix extracted 2,257 and 3,596 new variables in the 2 breeds, respectively. Bulls were sorted by birth year to create reference and prediction populations. The effect of principal components on deregressed proofs in reference animals was estimated with a BLUP model. Results were compared with those obtained by using SNP genotypes as predictors with either the BLUP or Bayes_A method. Traits considered were milk, fat, and protein yields, fat and protein percentages, and somatic cell score. The GEBV were obtained for prediction population by blending direct genomic prediction and pedigree indexes. No substantial differences were observed in squared correlations between GEBV and EBV in prediction animals between the 3 methods in the 2 breeds. The principal component analysis method allowed for a reduction of about 90% in the number of independent variables when predicting direct genomic values, with a substantial decrease in calculation time and without loss of accuracy. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Identifying sources of emerging organic contaminants in a mixed use watershed using principal components analysis.

PubMed

Karpuzcu, M Ekrem; Fairbairn, David; Arnold, William A; Barber, Brian L; Kaufenberg, Elizabeth; Koskinen, William C; Novak, Paige J; Rice, Pamela J; Swackhamer, Deborah L

2014-01-01

Principal components analysis (PCA) was used to identify sources of emerging organic contaminants in the Zumbro River watershed in Southeastern Minnesota. Two main principal components (PCs) were identified, which together explained more than 50% of the variance in the data. Principal Component 1 (PC1) was attributed to urban wastewater-derived sources, including municipal wastewater and residential septic tank effluents, while Principal Component 2 (PC2) was attributed to agricultural sources. The variances of the concentrations of cotinine, DEET and the prescription drugs carbamazepine, erythromycin and sulfamethoxazole were best explained by PC1, while the variances of the concentrations of the agricultural pesticides atrazine, metolachlor and acetochlor were best explained by PC2. Mixed use compounds carbaryl, iprodione and daidzein did not specifically group with either PC1 or PC2. Furthermore, despite the fact that caffeine and acetaminophen have been historically associated with human use, they could not be attributed to a single dominant land use category (e.g., urban/residential or agricultural). Contributions from septic systems did not clarify the source for these two compounds, suggesting that additional sources, such as runoff from biosolid-amended soils, may exist. Based on these results, PCA may be a useful way to broadly categorize the sources of new and previously uncharacterized emerging contaminants or may help to clarify transport pathways in a given area. Acetaminophen and caffeine were not ideal markers for urban/residential contamination sources in the study area and may need to be reconsidered as such in other areas as well.

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Experimental Investigation of Principal Residual Stress and Fatigue Performance for Turned Nickel-Based Superalloy Inconel 718.

PubMed

Hua, Yang; Liu, Zhanqiang

2018-05-24

Residual stresses of turned Inconel 718 surface along its axial and circumferential directions affect the fatigue performance of machined components. However, it has not been clear that the axial and circumferential directions are the principle residual stress direction. The direction of the maximum principal residual stress is crucial for the machined component service life. The present work aims to focuses on determining the direction and magnitude of principal residual stress and investigating its influence on fatigue performance of turned Inconel 718. The turning experimental results show that the principal residual stress magnitude is much higher than surface residual stress. In addition, both the principal residual stress and surface residual stress increase significantly as the feed rate increases. The fatigue test results show that the direction of the maximum principal residual stress increased by 7.4%, while the fatigue life decreased by 39.4%. The maximum principal residual stress magnitude diminished by 17.9%, whereas the fatigue life increased by 83.6%. The maximum principal residual stress has a preponderant influence on fatigue performance as compared to the surface residual stress. The maximum principal residual stress can be considered as a prime indicator for evaluation of the residual stress influence on fatigue performance of turned Inconel 718.

Principal component analysis for designed experiments.

PubMed

Konishi, Tomokazu

2015-01-01

Principal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit. The effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes. Together, these introduced options result in improved generality and objectivity of the analytical results. The methodology has thus become more like a set of multiple regression analyses that find independent models that specify each of the axes.

Spatio-temporal variability of hydro-chemical characteristics of coastal waters of Gulf of Mannar Marine Biosphere Reserve (GoMMBR), South India

NASA Astrophysics Data System (ADS)

Kathiravan, K.; Natesan, Usha; Vishnunath, R.

2017-03-01

The intention of this study was to appraise the spatial and temporal variations in the physico-chemical parameters of coastal waters of Rameswaram Island, Gulf of Mannar Marine Biosphere Reserve, south India, using multivariate statistical techniques, such as cluster analysis, factor analysis and principal component analysis. Spatio-temporal variations among the physico-chemical parameters are observed in the coastal waters of Gulf of Mannar, especially during northeast and post monsoon seasons. It is inferred that the high loadings of pH, temperature, suspended particulate matter, salinity, dissolved oxygen, biochemical oxygen demand, chlorophyll a, nutrient species of nitrogen and phosphorus strongly determine the discrimination of coastal water quality. Results highlight the important role of monsoonal variations to determine the coastal water quality around Rameswaram Island.

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

NASA Technical Reports Server (NTRS)

1991-01-01

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Method of determining the optimal dilution ratio for fluorescence fingerprint of food constituents.

PubMed

Trivittayasil, Vipavee; Tsuta, Mizuki; Kokawa, Mito; Yoshimura, Masatoshi; Sugiyama, Junichi; Fujita, Kaori; Shibata, Mario

2015-01-01

Quantitative determination by fluorescence spectroscopy is possible because of the linear relationship between the intensity of emitted fluorescence and the fluorophore concentration. However, concentration quenching may cause the relationship to become nonlinear, and thus, the optimal dilution ratio has to be determined. In the case of fluorescence fingerprint (FF) measurement, fluorescence is measured under multiple wavelength conditions and a method of determining the optimal dilution ratio for multivariate data such as FFs has not been reported. In this study, the FFs of mixed solutions of tryptophan and epicatechin of different concentrations and composition ratios were measured. Principal component analysis was applied, and the resulting loading plots were found to contain useful information about each constituent. The optimal concentration ranges could be determined by identifying the linear region of the PC score plotted against total concentration.

Multivariate and geo-spatial approach for seawater quality of Chidiyatappu Bay, south Andaman Islands, India.

PubMed

Jha, Dilip Kumar; Vinithkumar, Nambali Valsalan; Sahu, Biraja Kumar; Dheenan, Palaiya Sukumaran; Das, Apurba Kumar; Begum, Mehmuna; Devi, Marimuthu Prashanthi; Kirubagaran, Ramalingam

2015-07-15

Chidiyatappu Bay is one of the least disturbed marine environments of Andaman & Nicobar Islands, the union territory of India. Oceanic flushing from southeast and northwest direction is prevalent in this bay. Further, anthropogenic activity is minimal in the adjoining environment. Considering the pristine nature of this bay, seawater samples collected from 12 sampling stations covering three seasons were analyzed. Principal Component Analysis (PCA) revealed 69.9% of total variance and exhibited strong factor loading for nitrite, chlorophyll a and phaeophytin. In addition, analysis of variance (ANOVA-one way), regression analysis, box-whisker plots and Geographical Information System based hot spot analysis further simplified and supported multivariate results. The results obtained are important to establish reference conditions for comparative study with other similar ecosystems in the region. Copyright © 2015 Elsevier Ltd. All rights reserved.

History of 232-F, tritium extraction processing

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

Blackburn, G.W.

1994-08-01

In 1950 the Atomic Energy Commission authorized the Savannah River Project principally for the production of tritium and plutonium-239 for use in thermonuclear weapons. 232-F was built as an interim facility in 1953--1954, at a cost of $3.9M. Tritium extraction operations began in October, 1955, after the reactor and separations startups. In July, 1957 a larger tritium facility began operation in 232-H. In 1958 the capacity of 232-H was doubled. Also, in 1957 a new task was assigned to Savannah River, the loading of tritium into reservoirs that would be actual components of thermonuclear weapons. This report describes the historymore » of 232-F, the process for tritium extraction, and the lessons learned over the years that were eventually incorporated into the new Replacement Tritium Facility.« less

Coping with Multicollinearity: An Example on Application of Principal Components Regression in Dendroecology

Treesearch

B. Desta Fekedulegn; J.J. Colbert; R.R., Jr. Hicks; Michael E. Schuckers

2002-01-01

The theory and application of principal components regression, a method for coping with multicollinearity among independent variables in analyzing ecological data, is exhibited in detail. A concrete example of the complex procedures that must be carried out in developing a diagnostic growth-climate model is provided. We use tree radial increment data taken from breast...

Application of Principal Component Analysis (PCA) to Reduce Multicollinearity Exchange Rate Currency of Some Countries in Asia Period 2004-2014

ERIC Educational Resources Information Center

Rahayu, Sri; Sugiarto, Teguh; Madu, Ludiro; Holiawati; Subagyo, Ahmad

2017-01-01

This study aims to apply the model principal component analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hong Kong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield…

Radiative Transfer Modeling and Retrievals for Advanced Hyperspectral Sensors

NASA Technical Reports Server (NTRS)

Liu, Xu; Zhou, Daniel K.; Larar, Allen M.; Smith, William L., Sr.; Mango, Stephen A.

2009-01-01

A novel radiative transfer model and a physical inversion algorithm based on principal component analysis will be presented. Instead of dealing with channel radiances, the new approach fits principal component scores of these quantities. Compared to channel-based radiative transfer models, the new approach compresses radiances into a much smaller dimension making both forward modeling and inversion algorithm more efficient.

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

PubMed

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

2016-02-01

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

Edge Principal Components and Squash Clustering: Using the Special Structure of Phylogenetic Placement Data for Sample Comparison

PubMed Central

Matsen IV, Frederick A.; Evans, Steven N.

2013-01-01

Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used techniques for analyzing the differences between nucleic acid sequence samples taken from a given environment. They have led to many insights regarding the structure of microbial communities. We have developed two new complementary methods that leverage how this microbial community data sits on a phylogenetic tree. Edge principal components analysis enables the detection of important differences between samples that contain closely related taxa. Each principal component axis is a collection of signed weights on the edges of the phylogenetic tree, and these weights are easily visualized by a suitable thickening and coloring of the edges. Squash clustering outputs a (rooted) clustering tree in which each internal node corresponds to an appropriate “average” of the original samples at the leaves below the node. Moreover, the length of an edge is a suitably defined distance between the averaged samples associated with the two incident nodes, rather than the less interpretable average of distances produced by UPGMA, the most widely used hierarchical clustering method in this context. We present these methods and illustrate their use with data from the human microbiome. PMID:23505415

Time Management Ideas for Assistant Principals.

ERIC Educational Resources Information Center

Cronk, Jerry

1987-01-01

Prioritizing the use of time, effective communication, delegating authority, having detailed job descriptions, and good secretarial assistance are important components of time management for assistant principals. (MD)

The principal components model: a model for advancing spirituality and spiritual care within nursing and health care practice.

PubMed

McSherry, Wilfred

2006-07-01

The aim of this study was to generate a deeper understanding of the factors and forces that may inhibit or advance the concepts of spirituality and spiritual care within both nursing and health care. This manuscript presents a model that emerged from a qualitative study using grounded theory. Implementation and use of this model may assist all health care practitioners and organizations to advance the concepts of spirituality and spiritual care within their own sphere of practice. The model has been termed the principal components model because participants identified six components as being crucial to the advancement of spiritual health care. Grounded theory was used meaning that there was concurrent data collection and analysis. Theoretical sampling was used to develop the emerging theory. These processes, along with data analysis, open, axial and theoretical coding led to the identification of a core category and the construction of the principal components model. Fifty-three participants (24 men and 29 women) were recruited and all consented to be interviewed. The sample included nurses (n=24), chaplains (n=7), a social worker (n=1), an occupational therapist (n=1), physiotherapists (n=2), patients (n=14) and the public (n=4). The investigation was conducted in three phases to substantiate the emerging theory and the development of the model. The principal components model contained six components: individuality, inclusivity, integrated, inter/intra-disciplinary, innate and institution. A great deal has been written on the concepts of spirituality and spiritual care. However, rhetoric alone will not remove some of the intrinsic and extrinsic barriers that are inhibiting the advancement of the spiritual dimension in terms of theory and practice. An awareness of and adherence to the principal components model may assist nurses and health care professionals to engage with and overcome some of the structural, organizational, political and social variables that are impacting upon spiritual care.

Numerical verification of two-component dental implant in the context of fatigue life for various load cases.

PubMed

Szajek, Krzysztof; Wierszycki, Marcin

2016-01-01

Dental implant designing is a complex process which considers many limitations both biological and mechanical in nature. In earlier studies, a complete procedure for improvement of two-component dental implant was proposed. However, the optimization tasks carried out required assumption on representative load case, which raised doubts on optimality for the other load cases. This paper deals with verification of the optimal design in context of fatigue life and its main goal is to answer the question if the assumed load scenario (solely horizontal occlusal load) leads to the design which is also "safe" for oblique occlussal loads regardless the angle from an implant axis. The verification is carried out with series of finite element analyses for wide spectrum of physiologically justified loads. The design of experiment methodology with full factorial technique is utilized. All computations are done in Abaqus suite. The maximal Mises stress and normalized effective stress amplitude for various load cases are discussed and compared with the assumed "safe" limit (equivalent of fatigue life for 5e6 cycles). The obtained results proof that coronial-appical load component should be taken into consideration in the two component dental implant when fatigue life is optimized. However, its influence in the analyzed case is small and does not change the fact that the fatigue life improvement is observed for all components within whole range of analyzed loads.

Principal component analysis of the nonlinear coupling of harmonic modes in heavy-ion collisions

NASA Astrophysics Data System (ADS)

BoŻek, Piotr

2018-03-01

The principal component analysis of flow correlations in heavy-ion collisions is studied. The correlation matrix of harmonic flow is generalized to correlations involving several different flow vectors. The method can be applied to study the nonlinear coupling between different harmonic modes in a double differential way in transverse momentum or pseudorapidity. The procedure is illustrated with results from the hydrodynamic model applied to Pb + Pb collisions at √{sN N}=2760 GeV. Three examples of generalized correlations matrices in transverse momentum are constructed corresponding to the coupling of v22 and v4, of v2v3 and v5, or of v23,v33 , and v6. The principal component decomposition is applied to the correlation matrices and the dominant modes are calculated.

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

Firstly, this paper establishes the principal component regression model to analyze the data quantitatively, based on principal component analysis to get the three principal component factors of flight delays. Then the least square method is used to analyze the factors and obtained the regression equation expression by substitution, and then found that the main reason for flight delays is airlines, followed by weather and traffic. Aiming at the above problems, this paper improves the controllable aspects of traffic flow control. For reasons of traffic flow control, an adaptive genetic queuing model is established for the runway terminal area. This paper, establish optimization method that fifteen planes landed simultaneously on the three runway based on Beijing capital international airport, comparing the results with the existing FCFS algorithm, the superiority of the model is proved.

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.

Polyhedral gamut representation of natural objects based on spectral reflectance database and its application

NASA Astrophysics Data System (ADS)

Haneishi, Hideaki; Sakuda, Yasunori; Honda, Toshio

2002-06-01

Spectral reflectance of most reflective objects such as natural objects and color hardcopy is relatively smooth and can be approximated by several numbers of principal components with high accuracy. Though the subspace spanned by those principal components represents a space in which reflective objects can exist, it dos not provide the bound in which the samples distribute. In this paper we propose to represent the gamut of reflective objects in more distinct form, i.e., as a polyhedron in the subspace spanned by several principal components. Concept of the polyhedral gamut representation and its application to calculation of metamer ensemble are described. Color-mismatch volume caused by different illuminant and/or observer for a metamer ensemble is also calculated and compared with theoretical one.

Evaluation of Low-Voltage Distribution Network Index Based on Improved Principal Component Analysis

NASA Astrophysics Data System (ADS)

Fan, Hanlu; Gao, Suzhou; Fan, Wenjie; Zhong, Yinfeng; Zhu, Lei

2018-01-01

In order to evaluate the development level of the low-voltage distribution network objectively and scientifically, chromatography analysis method is utilized to construct evaluation index model of low-voltage distribution network. Based on the analysis of principal component and the characteristic of logarithmic distribution of the index data, a logarithmic centralization method is adopted to improve the principal component analysis algorithm. The algorithm can decorrelate and reduce the dimensions of the evaluation model and the comprehensive score has a better dispersion degree. The clustering method is adopted to analyse the comprehensive score because the comprehensive score of the courts is concentrated. Then the stratification evaluation of the courts is realized. An example is given to verify the objectivity and scientificity of the evaluation method.

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.

The impact of point source pollution on shallow groundwater used for human consumption in a threshold country.

PubMed

Cruz, Mercedes Cecilia; Cacciabue, Dolores Gutiérrez; Gil, José F; Gamboni, Oscar; Vicente, María Soledad; Wuertz, Stefan; Gonzo, Elio; Rajal, Verónica B

2012-09-01

Many developing and threshold countries rely on shallow groundwater wells for their water supply whilst pit latrines are used for sanitation. We employed a unified strategy involving satellite images and environmental monitoring of 16 physico-chemical and microbiological water quality parameters to identify significant land uses that can lead to unacceptable deterioration of source water, in a region with a subtropical climate and seasonally restricted torrential rainfall in Northern Argentina. Agricultural and non-agricultural sources of nitrate were illustrated in satellite images and used to assess the organic load discharged. The estimated human organic load per year was 28.5 BOD(5) tons and the N load was 7.5 tons, while for poultry farms it was 9940-BOD(5) tons and 1037-N tons, respectively. Concentrations of nitrates and organics were significantly different between seasons in well water (p values of 0.026 and 0.039, respectively). The onset of the wet season had an extraordinarily negative impact on well water due in part to the high permeability of soils made up of fine gravels and coarse sand. Discriminant analysis showed that land uses had a pronounced seasonal influence on nitrates and introduced additional microbial contamination, causing nitrification and denitrification in shallow groundwater. P-well was highly impacted by a poultry farm while S-well was affected by anthropogenic pollution and background load, as revealed by Principal Component Analysis. The application of microbial source tracking techniques is recommended to corroborate local sources of human versus animal origin.

A ToF-SIMS and XPS study of protein adsorption and cell attachment across PEG-like plasma polymer films with lateral compositional gradients

NASA Astrophysics Data System (ADS)

Menzies, Donna J.; Jasieniak, Marek; Griesser, Hans J.; Forsythe, John S.; Johnson, Graham; McFarland, Gail A.; Muir, Benjamin W.

2012-12-01

In this work we report a detailed X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) study of poly(ethylene glycol) PEG-like chemical gradients deposited via plasma enhanced chemical vapour deposition (PECVD) at two different load powers using diethylene glycol dimethyl ether (DG) as a monomer. Principal component analysis (PCA) was applied to the ToF-SIMS data both before and after protein adsorption on the plasma polymer thin films. Results of the PCA loadings indicated a higher content of hydrocarbon fragments across the higher load power gradient, which adsorbed higher amounts of proteins. Gradients deposited at a lower load power retained a higher degree of monomer like functionality as did the central region directly underneath the knife edge electrode. Analysis of the adsorption of serum proteins (human serum albumin and fetal bovine serum) was monitored across the gradient films and increased with decreasing ether (PEG-like) film chemistries. The effect of protein incubation time on the levels adsorbed fetal bovine serum on the plasma polymer films was critical, with significantly more protein adsorbing after 24 hour incubation times on both gradient films. The attachment of HeLa cells on the gradients appeared to be dictated not only by the surface chemistry, but also by the adsorption of serum proteins. XPS analysis revealed that at surface ether concentrations of less than 70% in the gradient films, significant increases in protein and cell attachment were observed.

Dietary patterns among Norwegian 2-year-olds in 1999 and in 2007 and associations with child and parent characteristics.

PubMed

Kristiansen, Anne Lene; Lande, Britt; Sexton, Joseph Andrew; Andersen, Lene Frost

2013-07-14

Infant and childhood nutrition influences short- and long-term health. The objective of the present paper has been to explore dietary patterns and their associations with child and parent characteristics at two time points. Parents of Norwegian 2-year-olds were, in 1999 (n 3000) and in 2007 (n 2984), invited to participate in a national dietary survey. At both time points, diet was assessed by a semi-quantitative FFQ that also provided information on several child and parent characteristics. A total of 1373 participants in the 1999 sample and 1472 participants in the 2007 sample were included in the analyses. Dietary patterns were identified by principal components analysis and related to child and parent characteristics using the general linear model. Four dietary patterns were identified at each time point. The 'unhealthy' and 'healthy' patterns in 1999 and 2007 showed similarities with regard to loadings of food groups. Both the 'bread and spread-based' pattern in 1999 and the 'traditional' pattern in 2007 had high positive loadings for bread and spreads; however, the 'traditional' pattern did also include positive associations with a warm meal. The last patterns identified in 1999 and in 2007 were not comparable with regard to loadings of food groups. All dietary patterns were significantly associated with one or several child and parent characteristics. In conclusion, the 'unhealthy' patterns in 1999 and in 2007 showed similarities with regard to loadings of food groups and were, at both time points, associated with sex, breastfeeding at 12 months of age, parity, maternal age and maternal work situation.

Streamflow and water-quality conditions including geologic sources and processes affecting selenium loading in the Toll Gate Creek watershed, Aurora, Arapahoe County, Colorado, 2007

USGS Publications Warehouse

Paschke, Suzanne S.; Runkel, Robert L.; Walton-Day, Katherine; Kimball, Briant A.; Schaffrath, Keelin R.

2013-01-01

Toll Gate Creek is a perennial stream draining a suburban area in Aurora, Colorado, where selenium concentrations have consistently exceeded the State of Colorado aquatic-life standard for selenium of 4.6 micrograms per liter since the early 2000s. In cooperation with the City of Aurora, Colorado, Utilities Department, a synoptic water-quality study was performed along an 18-kilometer reach of Toll Gate Creek extending from downstream from Quincy Reservoir to the confluence with Sand Creek to develop a detailed understanding of streamflow and concentrations and loads of selenium in Toll Gate Creek. Streamflow and surface-water quality were characterized for summer low-flow conditions (July–August 2007) using four spatially overlapping synoptic-sampling subreaches. Mass-balance methods were applied to the synoptic-sampling and tracer-injection results to estimate streamflow and develop spatial profiles of concentration and load for selenium and other chemical constituents in Toll Gate Creek surface water. Concurrent groundwater sampling determined concentrations of selenium and other chemical constituents in groundwater in areas surrounding the Toll Gate Creek study reaches. Multivariate principal-component analysis was used to group samples and to suggest common sources for dissolved selenium and major ions. Hydrogen and oxygen stable-isotope ratios, groundwater-age interpretations, and chemical analysis of water-soluble paste extractions from core samples are presented, and interpretation of the hydrologic and geochemical data support conclusions regarding geologic sources of selenium and the processes affecting selenium loading in the Toll Gate Creek watershed.

Parametric study on the thermal performance of beam screen samples of the High-Luminosity LHC upgrade

NASA Astrophysics Data System (ADS)

Borges de Sousa, P.; Morrone, M.; Hovenga, N.; Garion, C.; van Weelderen, R.; Koettig, T.; Bremer, J.

2017-12-01

The High-Luminosity upgrade of the Large Hadron Collider (HL-LHC) will increase the accelerator’s luminosity by a factor 10 beyond its original design value, giving rise to more collisions and generating an intense flow of debris. A new beam screen has been designed for the inner triplets that incorporates tungsten alloy blocks to shield the superconducting magnets and the 1.9 K superfluid helium bath from incoming radiation. These screens will operate between 60 K and 80 K and are designed to sustain a nominal head load of 15 Wm-1, over 10 times the nominal heat load for the original LHC design. Their overall new and more complex design requires them and their constituent parts to be characterised from a thermal performance standpoint. In this paper we describe the experimental parametric study carried out on two principal thermal components: a representative sample of the beam screen with a tungsten-based alloy block and thermal link and the supporting structure composed of an assembly of ceramic spheres and titanium springs. Results from both studies are shown and discussed regarding their impact on the baseline considerations for the thermal design of the beam screens.

CELCAP: A Computer Model for Cogeneration System Analysis

NASA Technical Reports Server (NTRS)

1985-01-01

A description of the CELCAP cogeneration analysis program is presented. A detailed description of the methodology used by the Naval Civil Engineering Laboratory in developing the CELCAP code and the procedures for analyzing cogeneration systems for a given user are given. The four engines modeled in CELCAP are: gas turbine with exhaust heat boiler, diesel engine with waste heat boiler, single automatic-extraction steam turbine, and back-pressure steam turbine. Both the design point and part-load performances are taken into account in the engine models. The load model describes how the hourly electric and steam demand of the user is represented by 24 hourly profiles. The economic model describes how the annual and life-cycle operating costs that include the costs of fuel, purchased electricity, and operation and maintenance of engines and boilers are calculated. The CELCAP code structure and principal functions of the code are described to how the various components of the code are related to each other. Three examples of the application of the CELCAP code are given to illustrate the versatility of the code. The examples shown represent cases of system selection, system modification, and system optimization.

Multi-objective/loading optimization for rotating composite flexbeams

NASA Technical Reports Server (NTRS)

Hamilton, Brian K.; Peters, James R.

1989-01-01

With the evolution of advanced composites, the feasibility of designing bearingless rotor systems for high speed, demanding maneuver envelopes, and high aircraft gross weights has become a reality. These systems eliminate the need for hinges and heavily loaded bearings by incorporating a composite flexbeam structure which accommodates flapping, lead-lag, and feathering motions by bending and twisting while reacting full blade centrifugal force. The flight characteristics of a bearingless rotor system are largely dependent on hub design, and the principal element in this type of system is the composite flexbeam. As in any hub design, trade off studies must be performed in order to optimize performance, dynamics (stability), handling qualities, and stresses. However, since the flexbeam structure is the primary component which will determine the balance of these characteristics, its design and fabrication are not straightforward. It was concluded that: pitchcase and snubber damper representations are required in the flexbeam model for proper sizing resulting from dynamic requirements; optimization is necessary for flexbeam design, since it reduces the design iteration time and results in an improved design; and inclusion of multiple flight conditions and their corresponding fatigue allowables is necessary for the optimization procedure.

Research of trace metals as markers of entry pathways in combined sewers.

PubMed

Gounou, C; Varrault, G; Amedzro, K; Gasperi, J; Moilleron, R; Garnaud, S; Chebbo, G

2011-01-01

Combined sewers receive high toxic trace metal loads emitted by various sources, such as traffic, industry, urban heating and building materials. During heavy rain events, Combined Sewer Overflows (CSO) can occur and, if so, are discharged directly into the aquatic system and therefore could have an acute impact on receiving waters. In this study, the concentrations of 18 metals have been measured in 89 samples drawn from the three pollutant Entry Pathways in Combined Sewers (EPCS): i) roof runoff, ii) street runoff, and iii) industrial and domestic effluents and also drawn from sewer deposits (SD). The aim of this research is to identify metallic markers for each EPCS; the data matrix was submitted to principal component analysis in order to determine metallic markers for the three EPCS and SD. This study highlights the fact that metallic content variability across samples from different EPCS and SD exceeds the spatio-temporal variability of samples from the same EPCS. In the catchment studied here, the most valuable EPCS and SD markers are lead, sodium, boron, antimony and zinc; these markers could be used in future studies to identify the contributions of each EPCS to CSO metallic loads.

Understanding the synergistic effect and the main factors influencing the enzymatic hydrolyzability of corn stover at low enzyme loading by hydrothermal and/or ultrafine grinding pretreatment.

PubMed

Zhang, Haiyan; Li, Junbao; Huang, Guangqun; Yang, Zengling; Han, Lujia

2018-05-26

A thorough assessment of the microstructural changes and synergistic effects of hydrothermal and/or ultrafine grinding pretreatment on the subsequent enzymatic hydrolysis of corn stover was performed in this study. The mechanism of pretreatment was elucidated by characterizing the particle size, specific surface area (SSA), pore volume (PV), average pore size, cellulose crystallinity (CrI) and surface morphology of the pretreated samples. In addition, the underlying relationships between the structural parameters and final glucose yields were elucidated, and the relative significance of the factors influencing enzymatic hydrolyzability were assessed by principal component analysis (PCA). Hydrothermal pretreatment at a lower temperature (170 °C) combined with ultrafine grinding achieved a high glucose yield (80.36%) at a low enzyme loading (5 filter paper unit (FPU)/g substrate) which is favorable. The relative significance of structural parameters in enzymatic hydrolyzability was SSA > PV > average pore size > CrI/cellulose > particle size. PV and SSA exhibited logarithmic correlations with the final enzymatic hydrolysis yield. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Near infrared reflectance spectroscopy (NIRS): a novel approach to reconstructing historical changes of primary productivity in Antarctic lake].

PubMed

Chen, Qian-Qian; Liu, Xiao-Dong; Liu, Wen-Qi; Jiang, Shan

2011-10-01

Compared with traditional chemical analysis methods, reflectance spectroscopy has the advantages of speed, minimal or no sample preparation, non-destruction, and low cost. In order to explore the potential application of spectroscopy technology in the paleolimnological study on Antarctic lakes, we took a lake sediment core in Mochou Lake at Zhongshan Station of Antarctic, and analyzed the near infrared reflectance spectroscopy (NIRS) data in the sedimentary samples. The results showed that the factor loadings of principal component analysis (PCA) displayed very similar depth-profile change pattern with the S2 index, a reliable proxy for the change in historical lake primary productivity. The correlation analysis showed that the values of PCA factor loading and S2 were correlated significantly, suggesting that it is feasible to infer paleoproductivity changes recorded in Antarctic lakes using NIRS technology. Compared to the traditional method of the trough area between 650 and 700 nm, the authors found that the PCA statistical approach was more accurate for reconstructing the change in historical lake primary productivity. The results reported here demonstrate that reflectance spectroscopy can provide a rapid method for the reconstruction of lake palaeoenviro nmental change in the remote Antarctic regions.

Relative importance of wastewater treatment plants and non-point sources of perfluorinated compounds to Washington State rivers.

PubMed

Furl, Chad V; Meredith, Callie A; Strynar, Mark J; Nakayama, Shoji F

2011-07-01

Perfluorinated compounds (PFCs) were measured in 10 Washington State rivers and 4 wastewater treatment plants (WWTPs) under periods of low and high flows to investigate the relative importance of point and non-point sources to rivers. PFCs were detected in all samples with summed values ranging from 1.11 to 74.9 ng/L in surface waters and 62.3-418 ng/L in WWTP effluent. Concentrations in 6 of the 10 rivers exhibited a positive relationship with flow, indicating runoff as a contributing source, with PFC loads greatest at all 10 waterbodies during high flows. Perfluoroheptanoic acid:perfluorooctanoic acid homologue ratios suggest atmospheric contributions to the waterbodies are important throughout the year. Principal component analysis (PCA) indicated distinct homologue profiles for high flow, low flow, and effluent samples. The PCA demonstrates that during the spring when flows and loads are at their greatest; WWTP discharges are not the primary sources of PFCs to the river systems. Taken together, the evidence provided signifies non-point inputs are a major pathway for PFCs to surface waters in Washington State. Copyright © 2011 Elsevier B.V. All rights reserved.

Common mode error in Antarctic GPS coordinate time series on its effect on bedrock-uplift estimates

NASA Astrophysics Data System (ADS)

Liu, Bin; King, Matt; Dai, Wujiao

2018-05-01

Spatially-correlated common mode error always exists in regional, or-larger, GPS networks. We applied independent component analysis (ICA) to GPS vertical coordinate time series in Antarctica from 2010 to 2014 and made a comparison with the principal component analysis (PCA). Using PCA/ICA, the time series can be decomposed into a set of temporal components and their spatial responses. We assume the components with common spatial responses are common mode error (CME). An average reduction of ˜40% about the RMS values was achieved in both PCA and ICA filtering. However, the common mode components obtained from the two approaches have different spatial and temporal features. ICA time series present interesting correlations with modeled atmospheric and non-tidal ocean loading displacements. A white noise (WN) plus power law noise (PL) model was adopted in the GPS velocity estimation using maximum likelihood estimation (MLE) analysis, with ˜55% reduction of the velocity uncertainties after filtering using ICA. Meanwhile, spatiotemporal filtering reduces the amplitude of PL and periodic terms in the GPS time series. Finally, we compare the GPS uplift velocities, after correction for elastic effects, with recent models of glacial isostatic adjustment (GIA). The agreements of the GPS observed velocities and four GIA models are generally improved after the spatiotemporal filtering, with a mean reduction of ˜0.9 mm/yr of the WRMS values, possibly allowing for more confident separation of various GIA model predictions.