A Test-Retest Analysis of the Vanderbilt Assessment for Leadership in Education in the USA

ERIC Educational Resources Information Center

Minor, Elizabeth Covay; Porter, Andrew C.; Murphy, Joseph; Goldring, Ellen; Elliott, Stephen N.

2017-01-01

The Vanderbilt Assessment for Leadership in Education (VAL-ED) is a 360-degree learning-centered behaviors principal evaluation tool that includes ratings from the principal, supervisors, and teachers. The current study assesses the test-retest reliability of the VAL-ED for a sample of seven school districts as part of multiple validity and…

Use of principal component analysis in the evaluation of adherence to statin treatment: a method to determine a potential target population for public health intervention.

PubMed

Latry, Philippe; Martin-Latry, Karin; Labat, Anne; Molimard, Mathieu; Peter, Claude

2011-08-01

The prevalence of statin use is high but adherence low. For public health intervention to be rational, subpopulations of nonadherent subjects must be defined. To categorise statin users with respect to patterns of reimbursement, this study was performed using the main French health reimbursement database for the Aquitaine region of south-western France. The cohort included subjects who submitted a reimbursement for at least one delivery of a statin (index) during the inclusion period (1st of September 2004-31st of December 2004). Indicators of adherence from reimbursement data were considered for principal component analysis. The 119,570 subjects included and analysed had a sex ratio of 1.1, mean (SD) age of 65.9 (11.9), and 13% were considered incident statin users. Principal component analysis found three dimensions that explained 67% of the variance. Using a K-means classification combined with a hierarchical ascendant classification, six groups were characterised. One group was considered nonadherent (10% of study population) and one group least adherent (1%). This novel application of principal component analysis identified groups that may be potential targets for intervention. The least adherent group appears to be one of the most appropriate because of both its relatively small size for case review with prescribing physicians and its very poor adherence. © 2010 The Authors Fundamental and Clinical Pharmacology © 2010 Société Française de Pharmacologie et de Thérapeutique.

Three Dimensional Cross-Sectional Properties From Bone Densitometry

NASA Technical Reports Server (NTRS)

Cleek, Tammy M.; Whalen, Robert T.; Dalton, Bonnie P. (Technical Monitor)

2001-01-01

Bone densitometry has previously been used to obtain cross-sectional properties of bone in a single scan plane. Using three non-coplanar scans, we have extended the method to obtain the principal area Moments of inertia and orientations of the principal axes at each cross-section along the length of the scan. Various 5 aluminum phantoms were used to examine scanner characteristics to develop the highest accuracy possible for in vitro non-invasive analysis of mass distribution. Factors considered included X-ray photon energy, initial scan orientation, the included angle of the 3 scans, and Imin/Imax ratios. Principal moments of inertia were accurate to within 3.1% and principal angles were within 1 deg. of the expected value for phantoms scanned with included angles of 60 deg. and 90 deg. at the higher X-ray photon energy. Low standard deviations in error also 10 indicate high precision of calculated measurements with these included angles. Accuracy and precision decreased slightly when the included angle was reduced to 30 deg. The method was then successfully applied to a pair of excised cadaveric tibiae. The accuracy and insensitivity of the algorithms to cross-sectional shape and changing isotropy (Imin/Imax) values when various included angles are used make this technique viable for future in vivo studies.

NASA's Agency-Wide Strategy for Environmental Regulatory Risk Analysis and Communication

NASA Technical Reports Server (NTRS)

Scroggins, Sharon; Duda, Kristen

2008-01-01

This viewgraph presentation gives an overview of NASA's risk analysis communication programs associated with changing environmental policies. The topics include: 1) NASA Program Transition; 2) Principal Center for Regulatory Risk Analysis and Communication (RRAC PC); and 3) Regulatory Tracking and Communication Process.

Multivariate analysis of molecular and morphological diversity in fig (Ficus carica L.)

USDA-ARS?s Scientific Manuscript database

Genetic polymorphism across 15 microsatellite loci among 194 fig accessions including Common, Smyrna, San Pedro, and Caprifig were analyzed using a cluster analysis (CA) and the principal components analysis (PCA). The collection was moderately variable with observed number of alleles per locus rang...

Principals' instructional management skills and middle school science teacher job satisfaction

NASA Astrophysics Data System (ADS)

Gibbs-Harper, Nzinga A.

The purpose of this research study was to determine if a relationship exists between teachers' perceptions of principals' instructional leadership behaviors and middle school teacher job satisfaction. Additionally, this study sought to assess whether principal's instructional leadership skills were predictors of middle school teachers' satisfaction with work itself. This study drew from 13 middle schools in an urban Mississippi school district. Participants included teachers who taught science. Each teacher was given the Principal Instructional Management Rating Scale (PIMRS; Hallinger, 2011) and the Teacher Job Satisfaction Questionnaire (TJSQ; Lester, 1987) to answer the research questions. The study was guided by two research questions: (a) Is there a relationship between the independent variables Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program and the dependent variable Work Itself?; (b) Are Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program predictors of Work Itself? The Pearson's correlation and multiple regression analysis were utilized to examine the relationship between the three dimensions of principals' instructional leadership and teacher satisfaction with work itself. The data revealed that there was a strong, positive correlation between all three dimensions of principals' instructional leadership and teacher satisfaction with work itself. However, the multiple regression analysis determined that teachers' perceptions of principals' instructional management skills is a slight predictor of Defining the School's Mission only.

Rank estimation and the multivariate analysis of in vivo fast-scan cyclic voltammetric data

PubMed Central

Keithley, Richard B.; Carelli, Regina M.; Wightman, R. Mark

2010-01-01

Principal component regression has been used in the past to separate current contributions from different neuromodulators measured with in vivo fast-scan cyclic voltammetry. Traditionally, a percent cumulative variance approach has been used to determine the rank of the training set voltammetric matrix during model development, however this approach suffers from several disadvantages including the use of arbitrary percentages and the requirement of extreme precision of training sets. Here we propose that Malinowski’s F-test, a method based on a statistical analysis of the variance contained within the training set, can be used to improve factor selection for the analysis of in vivo fast-scan cyclic voltammetric data. These two methods of rank estimation were compared at all steps in the calibration protocol including the number of principal components retained, overall noise levels, model validation as determined using a residual analysis procedure, and predicted concentration information. By analyzing 119 training sets from two different laboratories amassed over several years, we were able to gain insight into the heterogeneity of in vivo fast-scan cyclic voltammetric data and study how differences in factor selection propagate throughout the entire principal component regression analysis procedure. Visualizing cyclic voltammetric representations of the data contained in the retained and discarded principal components showed that using Malinowski’s F-test for rank estimation of in vivo training sets allowed for noise to be more accurately removed. Malinowski’s F-test also improved the robustness of our criterion for judging multivariate model validity, even though signal-to-noise ratios of the data varied. In addition, pH change was the majority noise carrier of in vivo training sets while dopamine prediction was more sensitive to noise. PMID:20527815

Cluster and principal component analysis based on SSR markers of Amomum tsao-ko in Jinping County of Yunnan Province

NASA Astrophysics Data System (ADS)

Ma, Mengli; Lei, En; Meng, Hengling; Wang, Tiantao; Xie, Linyan; Shen, Dong; Xianwang, Zhou; Lu, Bingyue

2017-08-01

Amomum tsao-ko is a commercial plant that used for various purposes in medicinal and food industries. For the present investigation, 44 germplasm samples were collected from Jinping County of Yunnan Province. Clusters analysis and 2-dimensional principal component analysis (PCA) was used to represent the genetic relations among Amomum tsao-ko by using simple sequence repeat (SSR) markers. Clustering analysis clearly distinguished the samples groups. Two major clusters were formed; first (Cluster I) consisted of 34 individuals, the second (Cluster II) consisted of 10 individuals, Cluster I as the main group contained multiple sub-clusters. PCA also showed 2 groups: PCA Group 1 included 29 individuals, PCA Group 2 included 12 individuals, consistent with the results of cluster analysis. The purpose of the present investigation was to provide information on genetic relationship of Amomum tsao-ko germplasm resources in main producing areas, also provide a theoretical basis for the protection and utilization of Amomum tsao-ko resources.

School food policies and practices: a state-wide survey of secondary school principals.

PubMed

French, Simone A; Story, Mary; Fulkerson, Jayne A

2002-12-01

To describe food-related policies and practices in secondary schools in Minnesota. Mailed anonymous survey including questions about the secondary school food environment and food-related practices and policies. Members of a statewide professional organization for secondary school principals (n = 610; response rate: 463/610 = 75%). Of the 463 surveys returned, 336 met the eligibility criteria (current position was either principal or assistant principal and school included at least one of the grades of 9 through 12). Descriptive statistics examined the prevalence of specific policies and practices. Chi2 analysis examined associations between policies and practices and school variables. Among principals, 65% believed it was important to have a nutrition policy for the high school; however, only 32% reported a policy at their school. Principals reported positive attitudes about providing a healthful school food environment, but 98% of the schools had soft drink vending machines and 77% had contracts with soft drink companies. Food sold at school fundraisers was most often candy, fruit, and cookies. Dietetics professionals who work in secondary school settings should collaborate with other key school staff members and parents to develop and implement a comprehensive school nutrition policy. Such a policy could foster a school food environment that is supportive of healthful food choices among youth.

Cross-sectional structural parameters from densitometry

NASA Technical Reports Server (NTRS)

Cleek, Tammy M.; Whalen, Robert T.

2002-01-01

Bone densitometry has previously been used to obtain cross-sectional properties of bone from a single X-ray projection across the bone width. Using three unique projections, we have extended the method to obtain the principal area moments of inertia and orientations of the principal axes at each scan cross-section along the length of the scan. Various aluminum phantoms were used to examine scanner characteristics to develop the highest accuracy possible for in vitro non-invasive analysis of cross-sectional properties. Factors considered included X-ray photon energy, initial scan orientation, the angle spanned by the three scans (included angle), and I(min)/I(max) ratios. Principal moments of inertia were accurate to within +/-3.1% and principal angles were within +/-1 degrees of the expected value for phantoms scanned with included angles of 60 degrees and 90 degrees at the higher X-ray photon energy (140 kVp). Low standard deviations in the error (0.68-1.84%) also indicate high precision of calculated measurements with these included angles. Accuracy and precision decreased slightly when the included angle was reduced to 30 degrees. The method was then successfully applied to a pair of excised cadaveric tibiae. The accuracy and insensitivity of the algorithms to cross-sectional shape and changing isotropy (I(min)/I(max)) values when various included angles are used make this technique viable for future in vivo studies.

Three dimensional empirical mode decomposition analysis apparatus, method and article manufacture

NASA Technical Reports Server (NTRS)

Gloersen, Per (Inventor)

2004-01-01

An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

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.

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

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.

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

PubMed

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

2002-10-09

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

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

PubMed

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can reliably be used in the low SNR data set (set B) compared to the high SNR data set (set A). Despite the fact that no definitive threshold could be found, this method may help to determine the cutoff for the number of principal components used in discriminant analysis. Future analysis of a selection of spectral databases using this technique will allow optimum thresholds to be selected for different applications and spectral data quality levels.

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.

Factorial and Item-Level Invariance of a Principal Perspectives Survey: German and U.S. Principals.

PubMed

Wang, Chuang; Hancock, Dawson R; Muller, Ulrich

This study examined the factorial and item-level invariance of a survey of principals' job satisfaction and perspectives about reasons and barriers to becoming a principal with a sample of US principals and another sample of German principals. Confirmatory factor analysis (CFA) and differential item functioning (DIF) analysis were employed at the test and item level, respectively. A single group CFA was conducted first, and the model was found to fit the data collected. The factorial invariance between the German and the US principals was tested through three steps: (a) configural invariance; (b) measurement invariance; and (c) structural invariance. The results suggest that the survey is a viable measure of principals' job satisfaction and perspectives about reasons and barriers to becoming a principal because principals from two different cultures shared a similar pattern on all three constructs. The DIF analysis further revealed that 22 out of the 28 items functioned similarly between German and US principals.

A Genealogical Interpretation of Principal Components Analysis

PubMed Central

McVean, Gil

2009-01-01

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

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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)

A Principal Components Analysis of the Rathus Assertiveness Schedule.

ERIC Educational Resources Information Center

Law, H. G.; And Others

1979-01-01

Investigated the adequacy of the Rathus Assertiveness Schedule (RAS) as a global measure of assertiveness. Analysis indicated that the RAS does not provide a unidimensional index of assertiveness, but rather measures a number of factors including situation-specific assertive behavior, aggressiveness, and a more general assertiveness. (Author)

Professional Standards and Performance Evaluation for Principals in China: A Policy Analysis of the Development of Principal Standards

ERIC Educational Resources Information Center

Liu, Shujie; Xu, Xianxuan; Grant, Leslie; Strong, James; Fang, Zheng

2017-01-01

This article presents the results of an interpretive policy analysis of China's Ministry of Education Standards (2013) for the professional practice of principals. In addition to revealing the evolution of the evaluation of principals in China and the processes by which this policy is formulated, a comparative analysis was conducted to compare it…

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

PubMed Central

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

2012-01-01

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

Principal Leadership for Technology-enhanced Learning in Science

NASA Astrophysics Data System (ADS)

Gerard, Libby F.; Bowyer, Jane B.; Linn, Marcia C.

2008-02-01

Reforms such as technology-enhanced instruction require principal leadership. Yet, many principals report that they need help to guide implementation of science and technology reforms. We identify strategies for helping principals provide this leadership. A two-phase design is employed. In the first phase we elicit principals' varied ideas about the Technology-enhanced Learning in Science (TELS) curriculum materials being implemented by teachers in their schools, and in the second phase we engage principals in a leadership workshop designed based on the ideas they generated. Analysis uses an emergent coding scheme to categorize principals' ideas, and a knowledge integration framework to capture the development of these ideas. The analysis suggests that principals frame their thinking about the implementation of TELS in terms of: principal leadership, curriculum, educational policy, teacher learning, student outcomes and financial resources. They seek to improve their own knowledge to support this reform. The principals organize their ideas around individual school goals and current political issues. Principals prefer professional development activities that engage them in reviewing curricula and student work with other principals. Based on the analysis, this study offers guidelines for creating learning opportunities that enhance principals' leadership abilities in technology and science reform.

An Analysis of Factor Extraction Strategies: A Comparison of the Relative Strengths of Principal Axis, Ordinary Least Squares, and Maximum Likelihood in Research Contexts That Include Both Categorical and Continuous Variables

ERIC Educational Resources Information Center

Coughlin, Kevin B.

2013-01-01

This study is intended to provide researchers with empirically derived guidelines for conducting factor analytic studies in research contexts that include dichotomous and continuous levels of measurement. This study is based on the hypotheses that ordinary least squares (OLS) factor analysis will yield more accurate parameter estimates than…

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.

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.

[Methods of a posteriori identification of food patterns in Brazilian children: a systematic review].

PubMed

Carvalho, Carolina Abreu de; Fonsêca, Poliana Cristina de Almeida; Nobre, Luciana Neri; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2016-01-01

The objective of this study is to provide guidance for identifying dietary patterns using the a posteriori approach, and analyze the methodological aspects of the studies conducted in Brazil that identified the dietary patterns of children. Articles were selected from the Latin American and Caribbean Literature on Health Sciences, Scientific Electronic Library Online and Pubmed databases. The key words were: Dietary pattern; Food pattern; Principal Components Analysis; Factor analysis; Cluster analysis; Reduced rank regression. We included studies that identified dietary patterns of children using the a posteriori approach. Seven studies published between 2007 and 2014 were selected, six of which were cross-sectional and one cohort, Five studies used the food frequency questionnaire for dietary assessment; one used a 24-hour dietary recall and the other a food list. The method of exploratory approach used in most publications was principal components factor analysis, followed by cluster analysis. The sample size of the studies ranged from 232 to 4231, the values of the Kaiser-Meyer-Olkin test from 0.524 to 0.873, and Cronbach's alpha from 0.51 to 0.69. Few Brazilian studies identified dietary patterns of children using the a posteriori approach and principal components factor analysis was the technique most used.

Product competitiveness analysis for e-commerce platform of special agricultural products

NASA Astrophysics Data System (ADS)

Wan, Fucheng; Ma, Ning; Yang, Dongwei; Xiong, Zhangyuan

2017-09-01

On the basis of analyzing the influence factors of the product competitiveness of the e-commerce platform of the special agricultural products and the characteristics of the analytical methods for the competitiveness of the special agricultural products, the price, the sales volume, the postage included service, the store reputation, the popularity, etc. were selected in this paper as the dimensionality for analyzing the competitiveness of the agricultural products, and the principal component factor analysis was taken as the competitiveness analysis method. Specifically, the web crawler was adopted to capture the information of various special agricultural products in the e-commerce platform ---- chi.taobao.com. Then, the original data captured thereby were preprocessed and MYSQL database was adopted to establish the information library for the special agricultural products. Then, the principal component factor analysis method was adopted to establish the analysis model for the competitiveness of the special agricultural products, and SPSS was adopted in the principal component factor analysis process to obtain the competitiveness evaluation factor system (support degree factor, price factor, service factor and evaluation factor) of the special agricultural products. Then, the linear regression method was adopted to establish the competitiveness index equation of the special agricultural products for estimating the competitiveness of the special agricultural products.

Career Paths in Educational Leadership: Examining Principals' Narratives

ERIC Educational Resources Information Center

Parylo, Oksana; Zepeda, Sally J.; Bengtson, Ed

2012-01-01

This qualitative study analyzes the career path narratives of active principals. Structural narrative analysis was supplemented with sociolinguistic theory and thematic narrative analysis to discern the similarities and differences, as well as the patterns in the language used by participating principals. Thematic analysis found four major themes…

Testing a Model of Special Educators' Intent to Stay in Teaching.

ERIC Educational Resources Information Center

Cross, Lawrence H.; Billingsley, Bonnie S.

1994-01-01

This study used path analysis to examine the effects of work-related factors--including principal support, stress, role problems, job satisfaction, and commitment--on 542 Virginia special educators' expressions of intent to stay in teaching. The study concluded that these work-related variables should be included in strategies for retaining…

Principals' transformational leadership and teachers' collective efficacy.

PubMed

Dussault, Marc; Payette, Daniel; Leroux, Mathieu

2008-04-01

The study was designed to test the relationship of principals' transformational, transactional, and laissez-faire leadership with teachers' collective efficacy. Bandura's theory of efficacy applied to the group and Bass's transformational leadership theory were used as the theoretical framework. Participants included 487 French Canadian teachers from 40 public high schools. As expected, there were positive and significant correlations between principals' transformational and transactional leadership and teachers' collective efficacy. Also, there was a negative and significant correlation between laissez-faire leadership and teachers' collective efficacy. Moreover, regression analysis showed transformational leadership significantly enhanced the predictive capabilities of transactional leadership on teachers' collective efficacy. These results confirm the importance of leadership to predict collective efficacy and, by doing so, strengthen Bass's theory of leadership.

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

PubMed

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

2018-03-20

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

Learning representative features for facial images based on a modified principal component analysis

NASA Astrophysics Data System (ADS)

Averkin, Anton; Potapov, Alexey

2013-05-01

The paper is devoted to facial image analysis and particularly deals with the problem of automatic evaluation of the attractiveness of human faces. We propose a new approach for automatic construction of feature space based on a modified principal component analysis. Input data sets for the algorithm are the learning data sets of facial images, which are rated by one person. The proposed approach allows one to extract features of the individual subjective face beauty perception and to predict attractiveness values for new facial images, which were not included into a learning data set. The Pearson correlation coefficient between values predicted by our method for new facial images and personal attractiveness estimation values equals to 0.89. This means that the new approach proposed is promising and can be used for predicting subjective face attractiveness values in real systems of the facial images analysis.

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

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

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

Classification of adulterated honeys by multivariate analysis.

PubMed

Amiry, Saber; Esmaiili, Mohsen; Alizadeh, Mohammad

2017-06-01

In this research, honey samples were adulterated with date syrup (DS) and invert sugar syrup (IS) at three concentrations (7%, 15% and 30%). 102 adulterated samples were prepared in six batches with 17 replications for each batch. For each sample, 32 parameters including color indices, rheological, physical, and chemical parameters were determined. To classify the samples, based on type and concentrations of adulterant, a multivariate analysis was applied using principal component analysis (PCA) followed by a linear discriminant analysis (LDA). Then, 21 principal components (PCs) were selected in five sets. Approximately two-thirds were identified correctly using color indices (62.75%) or rheological properties (67.65%). A power discrimination was obtained using physical properties (97.06%), and the best separations were achieved using two sets of chemical properties (set 1: lactone, diastase activity, sucrose - 100%) (set 2: free acidity, HMF, ash - 95%). Copyright © 2016 Elsevier Ltd. 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,…

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.

Identification among morphologically similar Argyreia (Convolvulaceae) based on leaf anatomy and phenetic analyses.

PubMed

Traiperm, Paweena; Chow, Janene; Nopun, Possathorn; Staples, G; Swangpol, Sasivimon C

2017-12-01

The genus Argyreia Lour. is one of the species-rich Asian genera in the family Convolvulaceae. Several species complexes were recognized in which taxon delimitation was imprecise, especially when examining herbarium materials without fully developed open flowers. The main goal of this study is to investigate and describe leaf anatomy for some morphologically similar Argyreia using epidermal peeling, leaf and petiole transverse sections, and scanning electron microscopy. Phenetic analyses including cluster analysis and principal component analysis were used to investigate the similarity of these morpho-types. Anatomical differences observed between the morpho-types include epidermal cell walls and the trichome types on the leaf epidermis. Additional differences in the leaf and petiole transverse sections include the epidermal cell shape of the adaxial leaf blade, the leaf margins, and the petiole transverse sectional outline. The phenogram from cluster analysis using the UPGMA method represented four groups with an R value of 0.87. Moreover, the important quantitative and qualitative leaf anatomical traits of the four groups were confirmed by the principal component analysis of the first two components. The results from phenetic analyses confirmed the anatomical differentiation between the morpho-types. Leaf anatomical features regarded as particularly informative for morpho-type differentiation can be used to supplement macro morphological identification.

Long duration exposure facility post-flight thermal analysis: Orbital/thermal environment data package

NASA Technical Reports Server (NTRS)

Berrios, William M.

1990-01-01

A post flight mission thermal environment for the Long Duration Exposure Facility was created as part of the thermal analysis data reduction effort. The data included herein is the thermal parameter data used in the calculation of boundary temperatures. This boundary temperature data is to be released in the near future for use by the LDEF principal investigators in the final analysis of their particular experiment temperatures. Also included is the flight temperature data as recorded by the LDEF Thermal Measurements System (THERM) for the first 90 days of flight.

Classifying Facial Actions

PubMed Central

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

2010-01-01

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

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

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

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

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

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

DOE PAGES

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

2017-12-28

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

Female Traditional Principals and Co-Principals: Experiences of Role Conflict and Job Satisfaction

ERIC Educational Resources Information Center

Eckman, Ellen Wexler; Kelber, Sheryl Talcott

2010-01-01

This paper presents a secondary analysis of survey data focusing on role conflict and job satisfaction of 102 female principals. Data were collected from 51 female traditional principals and 51 female co-principals. By examining the traditional and co-principal leadership models as experienced by female principals, this paper addresses the impact…

A Curriculum Development Route Map for a Technology Enhanced Learning Era

ERIC Educational Resources Information Center

Castañeda, Linda; Prendes, Paz

2013-01-01

In this paper we are trying to present a model of analysis that includes a comprehensive perspective of the state of the art in the specialized literature about curriculum development. From this theoretical approach, we get a complete curriculum overview. Including insights into: what are the curriculum principal elements, what we already know…

Infrared Space Observatory (ISO) Data Analysis

NASA Technical Reports Server (NTRS)

Joseph, Robert D.; Sanders, David B.; Stockton, Alan; Hu, Esther

1999-01-01

Joseph is an ISO Co-Investigator. His Guaranteed Time Observations include both a major programme for which he is the Principal Investigator, and a number of other prgrammes in collaboration with other ISPHOT Co-Investigators, David Sanders, Alan Stockton, and Esther Hu.

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…

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.

An application of principal component analysis to the clavicle and clavicle fixation devices.

PubMed

Daruwalla, Zubin J; Courtis, Patrick; Fitzpatrick, Clare; Fitzpatrick, David; Mullett, Hannan

2010-03-26

Principal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed. Using PCA, we present a novel method that examines the major modes of size and three-dimensional shape variation in male and female clavicles and suggests a method of grouping the clavicle into size and shape categories. Twenty-one high-resolution computerized tomography scans of the clavicle were reconstructed and analyzed using a specifically developed statistical software package. After performing statistical shape analysis, PCA was applied to study the factors that account for anatomical variation. The first principal component representing size accounted for 70.5 percent of anatomical variation. The addition of a further three principal components accounted for almost 87 percent. Using statistical shape analysis, clavicles in males have a greater lateral depth and are longer, wider and thicker than in females. However, the sternal angle in females is larger than in males. PCA confirmed these differences between genders but also noted that men exhibit greater variance and classified clavicles into five morphological groups. This unique approach is the first that standardizes a clavicular orientation. It provides information that is useful to both, the biomedical engineer and clinician. Other applications include implant design with regard to modifying current or designing future clavicle fixation devices. Our findings support the need for further development of clavicle fixation devices and the questioning of whether gender-specific devices are necessary.

Statistical classification of hydrogeologic regions in the fractured rock area of Maryland and parts of the District of Columbia, Virginia, West Virginia, Pennsylvania, and Delaware

USGS Publications Warehouse

Fleming, Brandon J.; LaMotte, Andrew E.; Sekellick, Andrew J.

2013-01-01

Hydrogeologic regions in the fractured rock area of Maryland were classified using geographic information system tools with principal components and cluster analyses. A study area consisting of the 8-digit Hydrologic Unit Code (HUC) watersheds with rivers that flow through the fractured rock area of Maryland and bounded by the Fall Line was further subdivided into 21,431 catchments from the National Hydrography Dataset Plus. The catchments were then used as a common hydrologic unit to compile relevant climatic, topographic, and geologic variables. A principal components analysis was performed on 10 input variables, and 4 principal components that accounted for 83 percent of the variability in the original data were identified. A subsequent cluster analysis grouped the catchments based on four principal component scores into six hydrogeologic regions. Two crystalline rock hydrogeologic regions, including large parts of the Washington, D.C. and Baltimore metropolitan regions that represent over 50 percent of the fractured rock area of Maryland, are distinguished by differences in recharge, Precipitation minus Potential Evapotranspiration, sand content in soils, and groundwater contributions to streams. This classification system will provide a georeferenced digital hydrogeologic framework for future investigations of groundwater availability in the fractured rock area of Maryland.

Principal Recruitment: Assessing Job Pursuit Intentions among Educators Enrolled in Principal Certification Programs

ERIC Educational Resources Information Center

Winter, Paul A.; Rinehart, James S.; Keedy, John L.; Bjork, Lars G.

2007-01-01

A statewide cadre of principal certification students (N = 516) completed a principal job survey and role-played as applicants for a principal position by completing a principal job evaluation instrument. Significant predictors of principal job rating included the following: self-reported capability to do the job, expected satisfaction with work…

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.

Demography of Principals' Work and School Improvement: Content Validity of Kentucky's Standards and Indicators for School Improvement (SISI)

ERIC Educational Resources Information Center

Lindle, Jane Clark; Stalion, Nancy; Young, Lu

2005-01-01

Kentucky's accountability system includes a school-processes audit known as Standards and Indicators for School Improvement (SISI), which is in a nascent stage of validation. Content validity methods include comparison to instruments measuring similar constructs as well as other techniques such as job analysis. This study used a two-phase process…

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

PubMed

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

2004-08-01

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

An Analysis of the Position of Assistant Principal of the Year in Indiana: An Analysis of What Is Really Important

ERIC Educational Resources Information Center

Mercer, Stephen D.

2016-01-01

This work is an analysis of the alignment between schools associated with an Indiana Assistant Principal of the Year, as selected by the Indiana Association of School Principals, and increases in academic performance of those schools on state mandated "high stakes" academic tests. The focus was on school improvement using annual school…

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…

The Professional Development Needs Analysis Questionnaire for Deputy Principals

ERIC Educational Resources Information Center

Khumalo, Jan Balotlhanyi; Van Der Westhuizen, Philip; Van Vuuren, Herman; van der Vyver, Cornelius P.

2017-01-01

This article reports on the design of the Professional Development Needs Analysis Questionnaire for Deputy Principals (PDNAQ) to measure the problems they experienced and the skills they needed. In the literature, no validated questionnaire to measure the problems experienced and skills needed by deputy principals in South African schools was…

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...

KSC-2011-7879

NASA Image and Video Library

2011-11-22

CAPE CANAVERAL, Fla. – NASA’s Kennedy Space Center in Florida is host to a Mars Science Laboratory (MSL) science briefing as part of preflight activities for the MSL mission. From left, NASA Public Affairs Officer Guy Webster moderates the conference featuring Michael Meyer, lead scientist for NASA Mars Exploration Program; John Grotzinger, project scientist for Mars Science Laboratory California Institute of Technology, Pasadena, Calif.; Michael Malin, principal investigator for the Mast Camera and Mars Descent Imager investigations on Curiosity, Malin Space Science Systems; Roger Wiens, principal investigator for Chemistry and Camera investigation on Curiosity, Los Alamos National Laboratory; David Blake, NASA principal investigator for Chemistry and Mineralogy investigation on Curiosity, NASA Ames Research Center; and Paul Mahaffy, NASA principal investigator for Sample Analysis at Mars investigation on Curiosity, NASA Goddard Space Flight Center. MSL’s components include a car-sized rover, Curiosity, which has 10 science instruments designed to search for signs of life, including methane, and help determine if the gas is from a biological or geological source. Launch of MSL aboard a United Launch Alliance Atlas V rocket is scheduled for Nov. 26 from Space Launch Complex 41 on Cape Canaveral Air Force Station in Florida. For more information, visit http://www.nasa.gov/msl. Photo credit: NASA/Kim Shiflett

KSC-2011-7878

NASA Image and Video Library

2011-11-22

CAPE CANAVERAL, Fla. – NASA’s Kennedy Space Center in Florida is host to a Mars Science Laboratory (MSL) science briefing as part of preflight activities for the MSL mission. From left, NASA Public Affairs Officer Guy Webster moderates the conference featuring Michael Meyer, lead scientist for NASA Mars Exploration Program; John Grotzinger, project scientist for Mars Science Laboratory California Institute of Technology, Pasadena, Calif.; Michael Malin, principal investigator for the Mast Camera and Mars Descent Imager investigations on Curiosity, Malin Space Science Systems; Roger Wiens, principal investigator for Chemistry and Camera investigation on Curiosity, Los Alamos National Laboratory; David Blake, NASA principal investigator for Chemistry and Mineralogy investigation on Curiosity, NASA Ames Research Center; and Paul Mahaffy, NASA principal investigator for Sample Analysis at Mars investigation on Curiosity, NASA Goddard Space Flight Center. MSL’s components include a car-sized rover, Curiosity, which has 10 science instruments designed to search for signs of life, including methane, and help determine if the gas is from a biological or geological source. Launch of MSL aboard a United Launch Alliance Atlas V rocket is scheduled for Nov. 26 from Space Launch Complex 41 on Cape Canaveral Air Force Station in Florida. For more information, visit http://www.nasa.gov/msl. Photo credit: NASA/Kim Shiflett

An introduction to kernel-based learning algorithms.

PubMed

Müller, K R; Mika, S; Rätsch, G; Tsuda, K; Schölkopf, B

2001-01-01

This paper provides an introduction to support vector machines, kernel Fisher discriminant analysis, and kernel principal component analysis, as examples for successful kernel-based learning methods. We first give a short background about Vapnik-Chervonenkis theory and kernel feature spaces and then proceed to kernel based learning in supervised and unsupervised scenarios including practical and algorithmic considerations. We illustrate the usefulness of kernel algorithms by discussing applications such as optical character recognition and DNA analysis.

The Impact of Principal Movement and School Achievement on Principal Salaries

ERIC Educational Resources Information Center

Tran, Henry; Buckman, David G.

2017-01-01

This study examines whether principals' movements and school achievement are associated with their salaries. Predictors of principal salaries were examined using three years of panel data. Results from a fixed-effects regression analysis suggest that principals who moved to school leadership positions in other districts leveraged higher salaries…

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

DOE PAGES

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

2012-01-01

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

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

Parallel processing for nonlinear dynamics simulations of structures including rotating bladed-disk assemblies

NASA Technical Reports Server (NTRS)

Hsieh, Shang-Hsien

1993-01-01

The principal objective of this research is to develop, test, and implement coarse-grained, parallel-processing strategies for nonlinear dynamic simulations of practical structural problems. There are contributions to four main areas: finite element modeling and analysis of rotational dynamics, numerical algorithms for parallel nonlinear solutions, automatic partitioning techniques to effect load-balancing among processors, and an integrated parallel analysis system.

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.

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.

A Simulation Investigation of Principal Component Regression.

ERIC Educational Resources Information Center

Allen, David E.

Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

When You Do Whole Language Instruction, how Will You Keep Track of Reading and Writing Skills? (When the Principal Asks).

ERIC Educational Resources Information Center

Harp, Bill

1988-01-01

Discusses several ways to evaluate reading and writing skills in a whole language classroom, including evaluation checklists, holistic evaluation of writing, and miscue analysis. Provides a literacy development checklist for reading and writing. (MM)

The Impact of Leadership Behaviors of Blue Ribbon Catholic School Principals on School Culture

ERIC Educational Resources Information Center

Cardarelli, Rosaline

2014-01-01

The purpose of this study was to conduct an analysis of six successful Blue Ribbon Catholic schools to determine the relationship between principal's leadership behaviors, teacher's perceptions of principals and resulting school culture within six successful Blue Ribbon schools. A mixed methods approach for analysis was used through both…

New predictor of aortic enlargement in uncomplicated type B aortic dissection based on elliptic Fourier analysis.

PubMed

Sato, Hiroshi; Ito, Toshiro; Kuroda, Yosuke; Uchiyama, Hiroki; Watanabe, Toshitaka; Yasuda, Naomi; Nakazawa, Junji; Harada, Ryo; Kawaharada, Nobuyoshi

2017-12-01

This study aimed to re-examine the conventional predictive factors for dissected aortic enlargement, such as the aortic and false lumen diameter and to consider whether the morphological elements of the dissected aorta could be predictors by quantifying the 'shape' of the true lumen based on elliptic Fourier analysis. A total of 80 patients with uncomplicated type B aortic dissection were included. The patients were divided into 'Enlargement group' and 'No Change group.' Between the 2 groups, the mean systolic blood pressure during follow-up, aortic and false lumen maximum diameters, and analysed morphological data were compared using each statistical method. The maximum aortic and false lumen diameters were significantly larger in the Enlargement group than in the No Change group (39.3 vs 35.9 mm; P = 0.0058) (23.5 vs 18.2 mm; P = 0.000095). The principal component 1, which is the data calculated by elliptic Fourier analysis, was significantly lower in the Enlargement group than in the No Change group (0.020 vs - 0.072; P = 0.000049). The mean systolic blood pressure ≥130 mmHg, aortic diameter, false lumen diameter and principal component 1 were included in the Cox proportional hazard model as covariates to determine the significant predictive variable. Principal component 1 demonstrated the only significance with aortic enlargement on multivariate analysis (odds ratio = 0.32; P = 0.048). The analysed and calculated morphological data of the shape of the true lumen can be more effective predictive factors of aortic enlargement of type B dissection than the conventional factors. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Optics education in an optometric setting

NASA Astrophysics Data System (ADS)

Putnam, Nicole M.

2017-08-01

The first year optics curriculum at the Arizona College of Optometry aims to provide students with an understanding of geometrical, physical, and visual optics principals that will be the foundation of their clinical understanding of the optics of the eye and its correction in advanced courses such as ophthalmic optics and contact lenses. Although the optics of the eye are a fantastic model to use in optics education, the clinical applications may not become apparent until later in the course of study. Successful strategies are needed to engage students and facilitate the understanding of optical principals and the growth of process skills including problem solving, analysis, and critical thinking that will help in their future as health care providers. These include the implementation of ophthalmic applications as early as possible, encouragement of group work including open office hours, and the use of video problem set solutions to supplement traditional static solutions.

A qualitative study of junior high school principals' and school food service directors' experiences with the Texas school nutrition policy.

PubMed

Roberts, Stephen M; Pobocik, Rebecca S; Deek, Rima; Besgrove, Ashley; Prostine, Becky A

2009-01-01

The objective of this study was to learn about the experiences of principals and school food service directors with the Texas Public School Nutrition Policy. Semistructured qualitative interviews were conducted to gain first hand reactions to the new nutrition policy. Data were gathered from Texas middle schools. Principals and food service directors from 24 schools randomly selected from 10 Texas Education regions were interviewed. Participants were interviewed about their reactions to the implementation of the Texas School Nutrition Policy. Two researchers, using thematic analysis, independently analyzed each interview. Differences in coding were reconciled and themes were generated. The themes that surfaced included resistance to the policy, policy development process, communication, government role, parental role, food rewards, fund raising, and leadership. Resistance to the policy was not extreme. In the future a wider array of school personnel who are affected by school food regulations should be included in the development of new policies. It is critical to communicate with all concerned parties about the policy.

A New 4D Trajectory-Based Approach Unveils Abnormal LV Revolution Dynamics in Hypertrophic Cardiomyopathy

PubMed Central

Madeo, Andrea; Piras, Paolo; Re, Federica; Gabriele, Stefano; Nardinocchi, Paola; Teresi, Luciano; Torromeo, Concetta; Chialastri, Claudia; Schiariti, Michele; Giura, Geltrude; Evangelista, Antonietta; Dominici, Tania; Varano, Valerio; Zachara, Elisabetta; Puddu, Paolo Emilio

2015-01-01

The assessment of left ventricular shape changes during cardiac revolution may be a new step in clinical cardiology to ease early diagnosis and treatment. To quantify these changes, only point registration was adopted and neither Generalized Procrustes Analysis nor Principal Component Analysis were applied as we did previously to study a group of healthy subjects. Here, we extend to patients affected by hypertrophic cardiomyopathy the original approach and preliminarily include genotype positive/phenotype negative individuals to explore the potential that incumbent pathology might also be detected. Using 3D Speckle Tracking Echocardiography, we recorded left ventricular shape of 48 healthy subjects, 24 patients affected by hypertrophic cardiomyopathy and 3 genotype positive/phenotype negative individuals. We then applied Generalized Procrustes Analysis and Principal Component Analysis and inter-individual differences were cleaned by Parallel Transport performed on the tangent space, along the horizontal geodesic, between the per-subject consensuses and the grand mean. Endocardial and epicardial layers were evaluated separately, different from many ecocardiographic applications. Under a common Principal Component Analysis, we then evaluated left ventricle morphological changes (at both layers) explained by first Principal Component scores. Trajectories’ shape and orientation were investigated and contrasted. Logistic regression and Receiver Operating Characteristic curves were used to compare these morphometric indicators with traditional 3D Speckle Tracking Echocardiography global parameters. Geometric morphometrics indicators performed better than 3D Speckle Tracking Echocardiography global parameters in recognizing pathology both in systole and diastole. Genotype positive/phenotype negative individuals clustered with patients affected by hypertrophic cardiomyopathy during diastole, suggesting that incumbent pathology may indeed be foreseen by these methods. Left ventricle deformation in patients affected by hypertrophic cardiomyopathy compared to healthy subjects may be assessed by modern shape analysis better than by traditional 3D Speckle Tracking Echocardiography global parameters. Hypertrophic cardiomyopathy pathophysiology was unveiled in a new manner whereby also diastolic phase abnormalities are evident which is more difficult to investigate by traditional ecocardiographic techniques. PMID:25875818

75 FR 73987 - Target Date Disclosure

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-30

... (Commission) held a joint public hearing to explore issues related to TDFs, including how they are managed at... principal strategies (including a general description of the types of assets held by the investment), and... goals, principal strategies and principal risks, historical performance, and fees and expenses, the...

Learning about Leadership from a Visit to the Art Museum

ERIC Educational Resources Information Center

Kaimal, Girija; Drescher, Jon; Fairbank, Holly; Gonzaga, Adele M. L.; Junkin, Janelle S.; White, George P.

2016-01-01

This qualitative study presents an analysis of how guided visits to an art museum can provide leadership lessons for developing school leaders. The principal interns participated in teaching artists-facilitated guided arts engagement sessions at a large metropolitan museum. The sessions included art-making, observations of portraiture in the…

Rural Economic Development: What Makes Rural Communities Grow?

ERIC Educational Resources Information Center

Aldrich, Lorna; Kusmin, Lorin

This report identifies local factors that foster rural economic growth. A review of the literature revealed potential indicators of county economic growth, and those indicators were then tested against data for nonmetro counties during the 1980s using multiple regression analysis. The principal variables examined included demographic and labor…

Learning Molecular Behaviour May Improve Student Explanatory Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Harris, Sara E.; Gold, Anne U.

2018-01-01

We assessed undergraduates' representations of the greenhouse effect, based on student-generated concept sketches, before and after a 30-min constructivist lesson. Principal component analysis of features in student sketches revealed seven distinct and coherent explanatory models including a new "Molecular Details" model. After the…

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.

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.

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

PubMed

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

2015-09-01

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

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®.

An Assessment of the Perceived Instructional Leadership Behaviors of Assistant Principals

ERIC Educational Resources Information Center

Atkinson, Ronald E., Jr.

2013-01-01

This study examined the extent to which the role of the assistant principal is perceived to include instructional leadership behaviors. Specifically, this study compared the perceptions of instructional leadership practices of elementary, middle, and high school assistant principals from the perspectives of assistant principals, principals, and…

Principal's Time Use and School Effectiveness

ERIC Educational Resources Information Center

Horng, Eileen Lai; Klasik, Daniel; Loeb, Susanna

2010-01-01

School principals have complex jobs. To better understand the work lives of principals, this study uses observational time use data for all high school principals in one district. This article examines the relationship between the time principals spent on different types of activities and school outcomes, including student achievement, teacher and…

A Program Evaluation of a Leadership Academy for School Principals

ERIC Educational Resources Information Center

Wagner, Kristi E.

2014-01-01

This program evaluation focused on mid-range outcomes of a leadership academy for school principals. The mixed-methods evaluation included interviews, principals' instructional observation database, and teacher surveys. The Principal Academy program was designed to build principals' knowledge of high-yield instructional strategies (Hattie, 2009),…

Effectiveness Leadership of Principal

ERIC Educational Resources Information Center

Kempa, Rudolf; Ulorlo, Marthen; Wenno, Izaak Hendrik

2017-01-01

Effective principal leadership is a leadership that can foster cooperative efforts and maintain an ideal working climate in schools. The purpose of this research is to know the effectiveness leadership of the principal of the 2nd State Junior High School of Ambon, with qualitative approach. Data sources include school principals, vice principals,…

Methods of Implementation of Evidence-Based Stroke Care in Europe: European Implementation Score Collaboration.

PubMed

Di Carlo, Antonio; Pezzella, Francesca Romana; Fraser, Alec; Bovis, Francesca; Baeza, Juan; McKevitt, Chris; Boaz, Annette; Heuschmann, Peter; Wolfe, Charles D A; Inzitari, Domenico

2015-08-01

Differences in stroke care and outcomes reported in Europe may reflect different degrees of implementation of evidence-based interventions. We evaluated strategies for implementing research evidence into stroke care in 10 European countries. A questionnaire was developed and administered through face-to-face interviews with key informants. Implementation strategies were investigated considering 3 levels (macro, meso, and micro, eg, policy, organization, patients/professionals) identified by the framing analysis, and different settings (primary, hospital, and specialist) of stroke care. Similarities and differences among countries were evaluated using the categorical principal components analysis. Implementation methods reported by ≥7 countries included nonmandatory policies, public financial incentives, continuing professional education, distribution of educational material, educational meetings and campaigns, guidelines, opinion leaders', and stroke patients associations' activities. Audits were present in 6 countries at national level; national and regional regulations in 4 countries. Private financial incentives, reminders, and educational outreach visits were reported only in 2 countries. At national level, the first principal component of categorical principal components analysis separated England, France, Scotland, and Sweden, all with positive object scores, from the other countries. Belgium and Lithuania obtained the lowest scores. At regional level, England, France, Germany, Italy, and Sweden had positive scores in the first principal component, whereas Belgium, Lithuania, Poland, and Scotland showed negative scores. Spain was in an intermediate position. We developed a novel method to assess different domains of implementation in stroke care. Clear variations were observed among European countries. The new tool may be used elsewhere for future contributions. © 2015 American Heart Association, Inc.

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

PubMed

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

2018-05-05

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

Guiding Principals: An Analysis of Public School Leaders in Greater Milwaukee. The Second Report in the Metro Milwaukee Educator Series

ERIC Educational Resources Information Center

Yeado, Joe

2015-01-01

In this report, we address this question with a comprehensive look at public school leaders in Greater Milwaukee. Our analysis covers the four-county Milwaukee metropolitan area and uses the most up-to-date data available to answer a number of questions, including: (1) How many school leaders are there in Greater Milwaukee and how does that number…

Spectral Quantitation Of Hydroponic Nutrients

NASA Technical Reports Server (NTRS)

Schlager, Kenneth J.; Kahle, Scott J.; Wilson, Monica A.; Boehlen, Michelle

1996-01-01

Instrument continuously monitors hydroponic solution by use of absorption and emission spectrometry to determine concentrations of principal nutrients, including nitrate, iron, potassium, calcium, magnesium, phosphorus, sodium, and others. Does not depend on extraction and processing of samples, use of such surrograte parameters as pH or electrical conductivity for control, or addition of analytical reagents to solution. Solution not chemically altered by analysis and can be returned to hydroponic process stream after analysis.

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.

Heavy metal contamination of agricultural soils affected by mining activities around the Ganxi River in Chenzhou, Southern China.

PubMed

Ma, Li; Sun, Jing; Yang, Zhaoguang; Wang, Lin

2015-12-01

Heavy metal contamination attracted a wide spread attention due to their strong toxicity and persistence. The Ganxi River, located in Chenzhou City, Southern China, has been severely polluted by lead/zinc ore mining activities. This work investigated the heavy metal pollution in agricultural soils around the Ganxi River. The total concentrations of heavy metals were determined by inductively coupled plasma-mass spectrometry. The potential risk associated with the heavy metals in soil was assessed by Nemerow comprehensive index and potential ecological risk index. In both methods, the study area was rated as very high risk. Multivariate statistical methods including Pearson's correlation analysis, hierarchical cluster analysis, and principal component analysis were employed to evaluate the relationships between heavy metals, as well as the correlation between heavy metals and pH, to identify the metal sources. Three distinct clusters have been observed by hierarchical cluster analysis. In principal component analysis, a total of two components were extracted to explain over 90% of the total variance, both of which were associated with anthropogenic sources.

Multivariate Analysis of Remains of Molluscan Foods Consumed by Latest Pleistocene and Holocene Humans in Nerja Cave, Málaga, Spain

NASA Astrophysics Data System (ADS)

Serrano, Francisco; Guerra-Merchán, Antonio; Lozano-Francisco, Carmen; Vera-Peláez, José Luis

1997-09-01

Nerja Cave is a karstic cavity used by humans from Late Paleolithic to post-Chalcolithic times. Remains of molluscan foods in the uppermost Pleistocene and Holocene sediments were studied with cluster analysis and principal components analysis, in both Qand Rmodes. The results from cluster analysis distinguished interval groups mainly in accordance with chronology and distinguished assemblages of species mainly according to habitat. Significant changes in the shellfish diet through time were revealed. In the Late Magdalenian, most molluscs consumed consisted of pulmonate gastropods and species from sandy sea bottoms. The Epipaleolithic diet was more varied and included species from rocky shorelines. From the Neolithic onward most molluscs consumed were from rocky shorelines. From the principal components analysis in Qmode, the first factor reflected mainly changes in the predominant capture environment, probably because of major paleogeographic changes. The second factor may reflect selective capture along rocky coastlines during certain times. The third factor correlated well with the sea-surface temperature curve in the western Mediterranean (Alboran Sea) during the late Quaternary.

Principals' Experiences of Being Evaluated: A Phenomenological Study

ERIC Educational Resources Information Center

Parylo, Oksana; Zepeda, Sally J.; Bengtson, Ed

2012-01-01

This phenomenological study sought to understand principals' lived experiences of being evaluated with reliance on the principles of developmental supervision and adult learning theory. Analysis of interview data from 16 principals revealed 3 major constructs in principal evaluation: evaluation is a complex, constantly changing system; principal…

Procedures for experimental measurement and theoretical analysis of large plastic deformations

NASA Technical Reports Server (NTRS)

Morris, R. E.

1974-01-01

Theoretical equations are derived and analytical procedures are presented for the interpretation of experimental measurements of large plastic strains in the surface of a plate. Orthogonal gage lengths established on the metal surface are measured before and after deformation. The change in orthogonality after deformation is also measured. Equations yield the principal strains, deviatoric stresses in the absence of surface friction forces, true stresses if the stress normal to the surface is known, and the orientation angle between the deformed gage line and the principal stress-strain axes. Errors in the measurement of nominal strains greater than 3 percent are within engineering accuracy. Applications suggested for this strain measurement system include the large-strain-stress analysis of impact test models, burst tests of spherical or cylindrical pressure vessels, and to augment small-strain instrumentation tests where large strains are anticipated.

Spatial and temporal variability of hyperspectral signatures of terrain

NASA Astrophysics Data System (ADS)

Jones, K. F.; Perovich, D. K.; Koenig, G. G.

2008-04-01

Electromagnetic signatures of terrain exhibit significant spatial heterogeneity on a range of scales as well as considerable temporal variability. A statistical characterization of the spatial heterogeneity and spatial scaling algorithms of terrain electromagnetic signatures are required to extrapolate measurements to larger scales. Basic terrain elements including bare soil, grass, deciduous, and coniferous trees were studied in a quasi-laboratory setting using instrumented test sites in Hanover, NH and Yuma, AZ. Observations were made using a visible and near infrared spectroradiometer (350 - 2500 nm) and hyperspectral camera (400 - 1100 nm). Results are reported illustrating: i) several difference scenes; ii) a terrain scene time series sampled over an annual cycle; and iii) the detection of artifacts in scenes. A principal component analysis indicated that the first three principal components typically explained between 90 and 99% of the variance of the 30 to 40-channel hyperspectral images. Higher order principal components of hyperspectral images are useful for detecting artifacts in scenes.

When Ethics and Policy Collide

ERIC Educational Resources Information Center

Hightower, Bynum Blake; Klinker, JoAnn Franklin

2012-01-01

This case study explores an ethical dilemma faced by a new junior high school principal. It is appropriate for use in all preparation course work, including the internship. Studies show that novice principal decision making differs from that of experienced principals in moral dilemmas, including following policy versus best interests of the…

Strain Transient Detection Techniques: A Comparison of Source Parameter Inversions of Signals Isolated through Principal Component Analysis (PCA), Non-Linear PCA, and Rotated PCA

NASA Astrophysics Data System (ADS)

Lipovsky, B.; Funning, G. J.

2009-12-01

We compare several techniques for the analysis of geodetic time series with the ultimate aim to characterize the physical processes which are represented therein. We compare three methods for the analysis of these data: Principal Component Analysis (PCA), Non-Linear PCA (NLPCA), and Rotated PCA (RPCA). We evaluate each method by its ability to isolate signals which may be any combination of low amplitude (near noise level), temporally transient, unaccompanied by seismic emissions, and small scale with respect to the spatial domain. PCA is a powerful tool for extracting structure from large datasets which is traditionally realized through either the solution of an eigenvalue problem or through iterative methods. PCA is an transformation of the coordinate system of our data such that the new "principal" data axes retain maximal variance and minimal reconstruction error (Pearson, 1901; Hotelling, 1933). RPCA is achieved by an orthogonal transformation of the principal axes determined in PCA. In the analysis of meteorological data sets, RPCA has been seen to overcome domain shape dependencies, correct for sampling errors, and to determine principal axes which more closely represent physical processes (e.g., Richman, 1986). NLPCA generalizes PCA such that principal axes are replaced by principal curves (e.g., Hsieh 2004). We achieve NLPCA through an auto-associative feed-forward neural network (Scholz, 2005). We show the geophysical relevance of these techniques by application of each to a synthetic data set. Results are compared by inverting principal axes to determine deformation source parameters. Temporal variability in source parameters, estimated by each method, are also compared.

[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.

Principal Stability and the Rural Divide

ERIC Educational Resources Information Center

Pendola, Andrew; Fuller, Edward J.

2018-01-01

This article examines the unique features of the rural school context and how these features are associated with the stability of principals in these schools. Given the small but growing literature on the characteristics of rural principals, this study presents an exploratory analysis of principal stability across schools located in different…

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures

PubMed Central

Theobald, Douglas L.; Wuttke, Deborah S.

2008-01-01

Summary THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. PMID:16777907

Measuring Principal Performance: How Rigorous Are Commonly Used Principal Performance Assessment Instruments? A Quality School Leadership Issue Brief

ERIC Educational Resources Information Center

Condon, Christopher; Clifford, Matthew

2010-01-01

This brief reviews the publicly available principal assessments and points superintendents and policy makers toward strong instruments to measure principal performance. Specifically, the measures included in this review are expressly intended to evaluate principal performance and have varying degrees of publicly available evidence of psychometric…

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.

How Many Separable Sources? Model Selection In Independent Components Analysis

PubMed Central

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

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.

Path Analysis of Work Family Conflict, Job Salary and Promotion Satisfaction, Work Engagement to Subjective Well-Being of the Primary and Middle School Principals

ERIC Educational Resources Information Center

Hu, Chun-mei; Cui, Shu-jing; Wang, Lei

2016-01-01

Objective: To investigate the path analysis of work family conflict, job salary and promotion satisfaction, work engagement to subjective well-being of the primary and middle school principals, and provide advice for enhancing their well-being. Methods: Using convenient sampling, totally 300 primary and middle school principals completed the WFC,…

A Structural Analysis of the Determinants of Job Satisfactions in On-Going Organizations.

ERIC Educational Resources Information Center

Vaughn, William J.; Dunn, J. D.

Organizational effectiveness is composed of two concepts: (1) job satisfactions and (2) employee performance. In this paper the concept of job satisfactions is delimited to include five principal areas, viz., work, pay, promotion, people, and supervision. Employee performance is the reciprocal concept. This paper is directed toward the job…

Engineering study of the rotary-vee engine concept

NASA Technical Reports Server (NTRS)

Willis, Edward A.; Bartrand, Timothy A.; Beard, John E.

1989-01-01

The applicable thermodynamic cycle and performance considerations when the rotary-vee mechanism is used as an internal combustion (I.C.) heat engine are reviewed. Included is a simplified kinematic analysis and studies of the effects of design parameters on the critical pressures, torques and parasitic losses. A discussion of the principal findings is presented.

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Principal Component Analysis Study of Visual and Verbal Metaphoric Comprehension in Children with Autism and Learning Disabilities

ERIC Educational Resources Information Center

Mashal, Nira; Kasirer, Anat

2012-01-01

This research extends previous studies regarding the metaphoric competence of autistic and learning disabled children on different measures of visual and verbal non-literal language comprehension, as well as cognitive abilities that include semantic knowledge, executive functions, similarities, and reading fluency. Thirty seven children with…

Exploring Effects of C2 Warfare on C2 Ability in a Simulated Environment

DTIC Science & Technology

2011-06-01

Principal Axis Factoring, Oblimin rotation with Kaiser Normalization) included all prerequisites, but not the total value of C2 ability ( KMO = .84...Mission intent had the lowest value in this factor, a separate factor analysis was conducted on this factor ( KMO = .75; Bartlett’s test of

School Administrators' Perceptions of the Achievement Gap between African American Students and White Students

ERIC Educational Resources Information Center

Royle, Jonathan; Brown, Casey Graham

2014-01-01

This study included an analysis of principal perceptions of the achievement gap between African American and White students. School administrators from campuses with a substantial number of African American students within the subgroup were interviewed to explore their perceptions of the achievement gap. The study revealed factors within the…

Qualitative Research and the Radical Right: Cats and Dogs and Other Natural Enemies.

ERIC Educational Resources Information Center

Lincoln, Yvonna S.; Cannella, Gaile S.

This investigation was conducted to explore contemporary critiques that challenge the growing body of scholarly research that would reveal and support diverse understandings of the world. Principal methods for this deconstruction of contemporary critiques include document analysis of writing that examines content and author location and context…

National Survey: What Do Principals Believe? Technology Counts, 2018. Education Week. Volume 37, Issue 27

ERIC Educational Resources Information Center

Bushweller, Kevin C., Ed.

2018-01-01

The 2018 edition of "Technology Counts" is a nationally representative survey of 500 principals, assistant principals, and other school leaders to better understand what principals are thinking and doing about some of the technology issues in their schools today. Contents include: (1) Pressure Points for Principals (Kevin Bushweller);…

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

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.

Thermal Inspection of a Composite Fuselage Section Using a Fixed Eigenvector Principal Component Analysis Method

NASA Technical Reports Server (NTRS)

Zalameda, Joseph N.; Bolduc, Sean; Harman, Rebecca

2017-01-01

A composite fuselage aircraft forward section was inspected with flash thermography. The fuselage section is 24 feet long and approximately 8 feet in diameter. The structure is primarily configured with a composite sandwich structure of carbon fiber face sheets with a Nomex(Trademark) honeycomb core. The outer surface area was inspected. The thermal data consisted of 477 data sets totaling in size of over 227 Gigabytes. Principal component analysis (PCA) was used to process the data sets for substructure and defect detection. A fixed eigenvector approach using a global covariance matrix was used and compared to a varying eigenvector approach. The fixed eigenvector approach was demonstrated to be a practical analysis method for the detection and interpretation of various defects such as paint thickness variation, possible water intrusion damage, and delamination damage. In addition, inspection considerations are discussed including coordinate system layout, manipulation of the fuselage section, and the manual scanning technique used for full coverage.

Sustainability at the local scale: defining highly aggregated indices for assessing environmental performance. The province of Reggio Emilia (Italy) as a case study.

PubMed

Clerici, Nicola; Bodini, Antonio; Ferrarini, Alessandro

2004-10-01

In order to achieve improved sustainability, local authorities need to use tools that adequately describe and synthesize environmental information. This article illustrates a methodological approach that organizes a wide suite of environmental indicators into few aggregated indices, making use of correlation, principal component analysis, and fuzzy sets. Furthermore, a weighting system, which includes stakeholders' priorities and ambitions, is applied. As a case study, the described methodology is applied to the Reggio Emilia Province in Italy, by considering environmental information from 45 municipalities. Principal component analysis is used to condense an initial set of 19 indicators into 6 fundamental dimensions that highlight patterns of environmental conditions at the provincial scale. These dimensions are further aggregated in two indices of environmental performance through fuzzy sets. The simple form of these indices makes them particularly suitable for public communication, as they condensate a wide set of heterogeneous indicators. The main outcomes of the analysis and the potential applications of the method are discussed.

Weak acid extractable metals in Bramble Bay, Queensland, Australia: temporal behaviour, enrichment and source apportionment.

PubMed

Brady, James P; Ayoko, Godwin A; Martens, Wayde N; Goonetilleke, Ashantha

2015-02-15

Sediment samples were taken from six sampling sites in Bramble Bay, Queensland, Australia between February and November in 2012. They were analysed for a range of heavy metals including Al, Fe, Mn, Ti, Ce, Th, U, V, Cr, Co, Ni, Cu, Zn, As, Cd, Sb, Te, Hg, Tl and Pb. Fraction analysis, Enrichment Factors and Principal Component Analysis-Absolute Principal Component Scores (PCA-APCS) were carried out in order to assess metal pollution, potential bioavailability and source apportionment. Cr and Ni exceeded the Australian Interim Sediment Quality Guidelines at some sampling sites, while Hg was found to be the most enriched metal. Fraction analysis identified increased weak acid soluble Hg and Cd during the sampling period. Source apportionment via PCA-APCS found four sources of metals pollution, namely, marine sediments, shipping, antifouling coatings and a mixed source. These sources need to be considered in any metal pollution control measure within Bramble Bay. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Principal Component Analysis of the Diffuse Interstellar Bands

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

Ensor, T.; Cami, J.; Bhatt, N. H.

2017-02-20

We present a principal component (PC) analysis of 23 line-of-sight parameters (including the strengths of 16 diffuse interstellar bands, DIBs) for a well-chosen sample of single-cloud sightlines representing a broad range of environmental conditions. Our analysis indicates that the majority (∼93%) of the variations in the measurements can be captured by only four parameters The main driver (i.e., the first PC) is the amount of DIB-producing material in the line of sight, a quantity that is extremely well traced by the equivalent width of the λ 5797 DIB. The second PC is the amount of UV radiation, which correlates wellmore » with the λ 5797/ λ 5780 DIB strength ratio. The remaining two PCs are more difficult to interpret, but are likely related to the properties of dust in the line of sight (e.g., the gas-to-dust ratio). With our PCA results, the DIBs can then be used to estimate these line-of-sight parameters.« less

Problem-Solving Processes of Expert and Typical School Principals: A Quantitative Look

ERIC Educational Resources Information Center

Brenninkmeyer, Lawrence D.; Spillane, James P.

2008-01-01

Principals are increasingly expected to be the instructional as well as administrative leaders of their schools. However, little is known about how principals reason through the instructional issues that they face. An analysis of principal reasoning in instructional contexts is critical. The study presented in this article draws on interviews with…

Personality Typologies as a Predictor of Being a Successful Elementary School Principal

ERIC Educational Resources Information Center

Mendiburu, John G.

2010-01-01

Purpose: The purpose of this study was to examine personality typologies as a predictor of being a successful elementary school principal. Methodology: A post-hoc analysis design was used to describe the personality typologies as a predictor of being a successful elementary school principal. Eighteen principals were selected to participate in…

Urban School Principals and Their Role as Multicultural Leaders

ERIC Educational Resources Information Center

Gardiner, Mary E.; Enomoto, Ernestine K.

2006-01-01

This study focuses on the role of urban school principals as multicultural leaders. Using cross-case analysis, the authors describe what 6 practicing principals do in regard to multicultural leadership. The findings suggest that although multicultural preparation was lacking for these principals, some did engage in work that promoted diversity in…

Out over Their Skis: A Study of Principal Preparation Program Policy in Florida

ERIC Educational Resources Information Center

Storey, Valerie A.; Johnson, Jerry

2017-01-01

Perceived shortage of principals, increased accountability demands, the changing role of principals, and the growing influence of the state over school administration have created a set of challenges for principal certification and licensure that have propelled a renewed need for analysis of certification and licensure processes. Recent calls to…

Which Field Experiences Best Prepare Future School Leaders? An Analysis of Kentucky's Principal Preparation Program

ERIC Educational Resources Information Center

Dodson, Richard L.

2014-01-01

This paper examines the effectiveness of field experiences in preparing school principals for the exigencies of the job. Current school principals throughout Kentucky were surveyed regarding their perceptions of the utility and comparative effectiveness of field experiences in the principal preparation program (PPP) each attended. Surveys were…

Burnout among Iranian school principals.

PubMed

Rashidzadeh, Mohammad Ali

2002-02-01

This study investigated burnout among Iranian school principals. Also, the relationships of sex, years of administration, age, and marital status were considered. The sample were 200 principals (100 men, 100 women) who completed the Friedman School Principal Burnout Scale. Analysis showed principals who completed the scale felt exhausted, aloof, and deprecated. The women scored lower. There were significant correlationships between marital status and years of administration with the scores on burnout.

[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.

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.

Rural Principal: A Case Study of an Effective Disciplinarian.

ERIC Educational Resources Information Center

Standard, Marilynn

1986-01-01

Describes discipline program initiated by the principal of a "tough" midwestern rural junior-senior high school. Includes ethnographic methodology; community characteristics; principal's background, self-concept, and leadership qualities; aspects of the program; and faculty, parent, and student perceptions of the principal and his…

Improving Conditions for Principal Effectiveness: Policy Implications of Research on Effective Principals.

ERIC Educational Resources Information Center

Manasse, A. Lorri

This paper reviews principal effectiveness research and suggests measures that might promote effective principalship. The first section discusses principals' behavior patterns and conditions bearing on their effectiveness. Topics examined include role ambiguity, goal setting behavior, leadership and initiative, management behaviors, instructional…

The Perceived Stress Levels of Primary and Secondary Principals.

ERIC Educational Resources Information Center

Savery, Lawson K.; Detiuk, Michael

1986-01-01

Research conducted in Western Australian government schools indicates perceived stress among principals, particularly role overload and role conflict. Primary principals experienced greater stress than secondary principals. Suggestions on how the education department can reduce employee stress include altering leadership styles and offering stress…

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.

[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.

Information Operations: A Research Aid Includes Coverage of: Information Warfare, Information Assurance, and Infrastructure Protection.

DTIC Science & Technology

1997-09-01

Policy Implications Stephen D. Biddle, IDA Papaer P-3123 Institute for Defense Analysis (IDA), Strategy Forces and Research Division 1801 N...IDA INSTITUTE FOR DEFENSE ANALYSES Information Operations: A Research Aid Includes Coverage of: Information Warfare, Information Assurance...Gray, Principal Investigator [pBC Q^^E^ nsSSPECTBD 8’ 19980303 031 This work was conducted under IDA’S central research program. The publication of

A Known Group Analysis Validity Study of the Vanderbilt Assessment of Leadership in Education in US Elementary and Secondary Schools

ERIC Educational Resources Information Center

Covay Minor, Elizabeth; Porter, Andrew C.; Murphy, Joseph; Goldring, Ellen B.; Cravens, Xiu; Elloitt, Stephen N.

2014-01-01

The Vanderbilt Assessment of Leadership in Education (VAL-ED) provides educators with a tool for principal evaluation based on principal, teacher, and supervisor reports of principals' learning-centered leadership. In this study, we conduct a known group analysis as part of a larger argument for the validity of the VAL-ED in US elementary and…

Pollution Assessment and Sources Identification of Heavy Metals in Surface Sediments from the Nantaizi Lake, Middle China

NASA Astrophysics Data System (ADS)

Ma, Jinlong; Li, Fei; Jia, Xiaolin; Zhang, Jingdong

2018-01-01

The total contents of heavy metal elements including Cr, Cd, Cu, Zn, Pb and As were investigated in sediments from the Nantaizi Lake in Hanyang district of Wuhan. The heavy metal pollution level of Nantaizi Lake was calculated by potential ecological risk index and the main sources of pollutants were researched by correlation analysis and principal component analysis. The results show that heavy metal concentration of Nantaizi Lake sediments is within the Chinese Environmental Quality Standard for Soils (GB 15618-1995) level-II standard limitation. According to the result of potential ecological risk index, ecological hazard rank of heavy metal element of Nantaizi Lake sediments is: Cd>Cu>As>Pb>Zn>Cr, and whole water environment of lake is slightly polluted. Through correlation analysis and principal component analysis, it is found that industrial sewage and domestic wastewater in human activities are the main contributors to heavy metal sources of Nantaizi Lake, and chemical processes, such as endogenous microbial activities of lake etc., also affect heavy metal sources in sediments simultaneously.

Genetic Evaluation of Dual-Purpose Buffaloes (Bubalus bubalis) in Colombia Using Principal Component Analysis

PubMed Central

Agudelo-Gómez, Divier; Pineda-Sierra, Sebastian; Cerón-Muñoz, Mario Fernando

2015-01-01

Genealogy and productive information of 48621 dual-purpose buffaloes born in Colombia between years 1996 and 2014 was used. The following traits were assessed using one-trait models: milk yield at 270 days (MY270), age at first calving (AFC), weaning weight (WW), and weights at the following ages: first year (W12), 18 months (W18), and 2 years (W24). Direct additive genetic and residual random effects were included in all the traits. Maternal permanent environmental and maternal additive genetic effects were included for WW and W12. The fixed effects were: contemporary group (for all traits), sex (for WW, W12, W18, and W24), parity (for WW, W12, and MY270). Age was included as covariate for WW, W12, W18 and W24. Principal component analysis (PCA) was conducted using the genetic values of 133 breeding males whose breeding-value reliability was higher than 50% for all the traits in order to define the number of principal components (PC) which would explain most of the variation. The highest heritabilities were for W18 and MY270, and the lowest for AFC; with 0.53, 0.23, and 0.17, respectively. The first three PCs represented 66% of the total variance. Correlation of the first PC with meat production traits was higher than 0.73, and it was -0.38 with AFC. Correlations of the second PC with maternal genetic component traits for WW and W12 were above 0.75. The third PC had 0.84 correlation with MY270. PCA is an alternative approach for analyzing traits in dual-purpose buffaloes and reduces the dimension of the traits. PMID:26230093

Source Evaluation and Trace Metal Contamination in Benthic Sediments from Equatorial Ecosystems Using Multivariate Statistical Techniques

PubMed Central

Benson, Nsikak U.; Asuquo, Francis E.; Williams, Akan B.; Essien, Joseph P.; Ekong, Cyril I.; Akpabio, Otobong; Olajire, Abaas A.

2016-01-01

Trace metals (Cd, Cr, Cu, Ni and Pb) concentrations in benthic sediments were analyzed through multi-step fractionation scheme to assess the levels and sources of contamination in estuarine, riverine and freshwater ecosystems in Niger Delta (Nigeria). The degree of contamination was assessed using the individual contamination factors (ICF) and global contamination factor (GCF). Multivariate statistical approaches including principal component analysis (PCA), cluster analysis and correlation test were employed to evaluate the interrelationships and associated sources of contamination. The spatial distribution of metal concentrations followed the pattern Pb>Cu>Cr>Cd>Ni. Ecological risk index by ICF showed significant potential mobility and bioavailability for Cu, Cu and Ni. The ICF contamination trend in the benthic sediments at all studied sites was Cu>Cr>Ni>Cd>Pb. The principal component and agglomerative clustering analyses indicate that trace metals contamination in the ecosystems was influenced by multiple pollution sources. PMID:27257934

The Baptist Health Nurse Retention Questionnaire: A Methodological Study, Part 1.

PubMed

Lengerich, Alexander; Bugajski, Andrew; Marchese, Matthew; Hall, Brittany; Yackzan, Susan; Davies, Claire; Brockopp, Dorothy

2017-05-01

The purposes of this study were to develop and test the Baptist Health Nurse Retention Questionnaire (BHNRQ) and examine the importance of nurse retention factors. Multiple factors, including increasing patient acuity levels, have led to concerns regarding nurse retention. An understanding of current factors related to retention is limited. To establish the psychometric properties of the BHNRQ, data were collected from 279 bedside nurses at a 391-bed, Magnet® redesignated community hospital. A principal component analysis was conducted to determine the subscale structure of the BHNRQ. Additional analyses were conducted related to content validity and test-retest reliability. The results of the principal components analysis revealed 3 subscales: nursing practice, management, and staffing. Analyses demonstrate that the BHNRQ is a reliable and valid instrument for measuring nurse retention factors. The BHNRQ was found to be a clinically useful instrument for measuring important factors related to nurse retention.

A statistically derived index for classifying East Coast fever reactions in cattle challenged with Theileria parva under experimental conditions.

PubMed

Rowlands, G J; Musoke, A J; Morzaria, S P; Nagda, S M; Ballingall, K T; McKeever, D J

2000-04-01

A statistically derived disease reaction index based on parasitological, clinical and haematological measurements observed in 309 5 to 8-month-old Boran cattle following laboratory challenge with Theileria parva is described. Principal component analysis was applied to 13 measures including first appearance of schizonts, first appearance of piroplasms and first occurrence of pyrexia, together with the duration and severity of these symptoms, and white blood cell count. The first principal component, which was based on approximately equal contributions of the 13 variables, provided the definition for the disease reaction index, defined on a scale of 0-10. As well as providing a more objective measure of the severity of the reaction, the continuous nature of the index score enables more powerful statistical analysis of the data compared with that which has been previously possible through clinically derived categories of non-, mild, moderate and severe reactions.

An improved principal component analysis based region matching method for fringe direction estimation

NASA Astrophysics Data System (ADS)

He, A.; Quan, C.

2018-04-01

The principal component analysis (PCA) and region matching combined method is effective for fringe direction estimation. However, its mask construction algorithm for region matching fails in some circumstances, and the algorithm for conversion of orientation to direction in mask areas is computationally-heavy and non-optimized. We propose an improved PCA based region matching method for the fringe direction estimation, which includes an improved and robust mask construction scheme, and a fast and optimized orientation-direction conversion algorithm for the mask areas. Along with the estimated fringe direction map, filtered fringe pattern by automatic selective reconstruction modification and enhanced fast empirical mode decomposition (ASRm-EFEMD) is used for Hilbert spiral transform (HST) to demodulate the phase. Subsequently, windowed Fourier ridge (WFR) method is used for the refinement of the phase. The robustness and effectiveness of proposed method are demonstrated by both simulated and experimental fringe patterns.

Principal States of Dynamic Functional Connectivity Reveal the Link Between Resting-State and Task-State Brain: An fMRI Study.

PubMed

Cheng, Lin; Zhu, Yang; Sun, Junfeng; Deng, Lifu; He, Naying; Yang, Yang; Ling, Huawei; Ayaz, Hasan; Fu, Yi; Tong, Shanbao

2018-01-25

Task-related reorganization of functional connectivity (FC) has been widely investigated. Under classic static FC analysis, brain networks under task and rest have been demonstrated a general similarity. However, brain activity and cognitive process are believed to be dynamic and adaptive. Since static FC inherently ignores the distinct temporal patterns between rest and task, dynamic FC may be more a suitable technique to characterize the brain's dynamic and adaptive activities. In this study, we adopted [Formula: see text]-means clustering to investigate task-related spatiotemporal reorganization of dynamic brain networks and hypothesized that dynamic FC would be able to reveal the link between resting-state and task-state brain organization, including broadly similar spatial patterns but distinct temporal patterns. In order to test this hypothesis, this study examined the dynamic FC in default-mode network (DMN) and motor-related network (MN) using Blood-Oxygenation-Level-Dependent (BOLD)-fMRI data from 26 healthy subjects during rest (REST) and a hand closing-and-opening (HCO) task. Two principal FC states in REST and one principal FC state in HCO were identified. The first principal FC state in REST was found similar to that in HCO, which appeared to represent intrinsic network architecture and validated the broadly similar spatial patterns between REST and HCO. However, the second FC principal state in REST with much shorter "dwell time" implied the transient functional relationship between DMN and MN during REST. In addition, a more frequent shifting between two principal FC states indicated that brain network dynamically maintained a "default mode" in the motor system during REST, whereas the presence of a single principal FC state and reduced FC variability implied a more temporally stable connectivity during HCO, validating the distinct temporal patterns between REST and HCO. Our results further demonstrated that dynamic FC analysis could offer unique insights in understanding how the brain reorganizes itself during rest and task states, and the ways in which the brain adaptively responds to the cognitive requirements of tasks.

Preparing Politically Savvy Principals in Ontario, Canada

ERIC Educational Resources Information Center

Winton, Sue; Pollock, Katina

2013-01-01

Purpose: The aim of the paper is to argue that principal preparation programs should help candidates: recognize the political role of the school principal; develop political skills (including the ability to strategically appropriate policy); and understand that the political approach of the principal influences teaching, learning, relationships,…

76 FR 11821 - Submission for OMB Review; Comment Request Survey of Principal Investigators on Earthquake...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-03

...: Survey of Principal Investigators on Earthquake Engineering Research Awards Made by the National Science... survey of Principal Investigators on NSF earthquake engineering research awards, including but not... NATIONAL SCIENCE FOUNDATION Submission for OMB Review; Comment Request Survey of Principal...

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.

The Micropolitics of School Principals' Decision Making in Nigeria: Principals' Perspective

ERIC Educational Resources Information Center

Olayiwola, Shina; Alabi, Kingsley

2015-01-01

This study depicted a micropolitical analysis of school principals' decision making as regards the influence of formal and informal groups on school administrative processes from the point of view of principals. It was based on descriptive survey study of all 24 public secondary schools within Ile-Ife community, Osun State, Nigeria, out of which a…

What Makes Them the Best? An Analysis of the Relationship between State Education Quality and Principal Preparation Practices

ERIC Educational Resources Information Center

Dodson, Richard L.

2015-01-01

This article examines the relationship between principals' training experiences and perceived school quality in seven U.S. states. Current school principals were surveyed regarding their perceptions of the comparative effectiveness of field experiences in the principal preparation program (PPP) each attended. States were selected to represent…

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.

Influential Observations in Principal Factor Analysis.

ERIC Educational Resources Information Center

Tanaka, Yutaka; Odaka, Yoshimasa

1989-01-01

A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)

Principal Component and Linkage Analysis of Cardiovascular Risk Traits in the Norfolk Isolate

PubMed Central

Cox, Hannah C.; Bellis, Claire; Lea, Rod A.; Quinlan, Sharon; Hughes, Roger; Dyer, Thomas; Charlesworth, Jac; Blangero, John; Griffiths, Lyn R.

2009-01-01

Objective(s) An individual's risk of developing cardiovascular disease (CVD) is influenced by genetic factors. This study focussed on mapping genetic loci for CVD-risk traits in a unique population isolate derived from Norfolk Island. Methods This investigation focussed on 377 individuals descended from the population founders. Principal component analysis was used to extract orthogonal components from 11 cardiovascular risk traits. Multipoint variance component methods were used to assess genome-wide linkage using SOLAR to the derived factors. A total of 285 of the 377 related individuals were informative for linkage analysis. Results A total of 4 principal components accounting for 83% of the total variance were derived. Principal component 1 was loaded with body size indicators; principal component 2 with body size, cholesterol and triglyceride levels; principal component 3 with the blood pressures; and principal component 4 with LDL-cholesterol and total cholesterol levels. Suggestive evidence of linkage for principal component 2 (h2 = 0.35) was observed on chromosome 5q35 (LOD = 1.85; p = 0.0008). While peak regions on chromosome 10p11.2 (LOD = 1.27; p = 0.005) and 12q13 (LOD = 1.63; p = 0.003) were observed to segregate with principal components 1 (h2 = 0.33) and 4 (h2 = 0.42), respectively. Conclusion(s): This study investigated a number of CVD risk traits in a unique isolated population. Findings support the clustering of CVD risk traits and provide interesting evidence of a region on chromosome 5q35 segregating with weight, waist circumference, HDL-c and total triglyceride levels. PMID:19339786

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

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.

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae).

PubMed

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks's λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant ( p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species.

A Continuum Approach for Developing School Leaders in an Urban District

ERIC Educational Resources Information Center

Normore, Anthony

2007-01-01

This study examined a four-staged leadership development continuum for school leaders in a large urban school district in the southeastern United States. The program under examination included: LEAD Program; Interim Assistant Principal Program; Intern Principal Program, and; First Year Principal Support/Interim Principal Program. Qualitative…

The Development of Assistant Principals: A Literature Review

ERIC Educational Resources Information Center

Oleszewski, Ashley; Shoho, Alan; Barnett, Bruce

2012-01-01

Purpose: The purpose of this review is to add to the discussion of assistant principals (APs), a position that has been under-represented in the professional literature. Design/methodology/approach: An extensive search was undertaken on assistant principals, vice principals, and deputy head teachers from various sources, including journals,…

Instructional Leadership: Four Ethnographic Studies on Junior High School Principals.

ERIC Educational Resources Information Center

Newberg, Norman A.; Glatthorn, Allan A.

This study explores the principal's role as instructional leader in four urban schools showing improvement in test scores. Data gathering procedures included ethnographic observations and interviews of principals; principals' logs of time use; interviews with teachers, school administrators, and students; and faculty surveys. The findings were…

Space station systems analysis study. Part 2, Volume 3: Appendixes, Book 1. Program requirements documentation

NASA Technical Reports Server (NTRS)

1977-01-01

The objective elements representative of the kinds of space activities that will be supported by the space construction base (SCB) are discussed in (1) a brief mission overview including the primary purpose and general objectives; (2) descriptions of the processes involved (where applicable), the mission hardware, the principal activities to be undertaken, the test requirements, and the principal tests; and (3) the SCB requirements including such items as special devices (e.g., fabrication modules, assembly or construction fixtures, cranes, and airlocks), power, data management and communications, waste management, environmental control, safety, and logistics. Each program option is then described in terms of the objective elements it supports, its orbit, the general makeup of the SCB, the transportation approach, and the program schedule goals. The specific requirements that are imposed on the SCB in order to support program option L are given.

Turbine Engine Hot Section Technology, 1984

NASA Technical Reports Server (NTRS)

1984-01-01

Presentations were made concerning the hot section environment and behavior of combustion liners, turbine blades, and waves. The presentations were divided into six sessions: instrumentation, combustion, turbine heat transfer, structural analysis, fatigue and fracture, and surface properties. The principal objective of each session was to disseminate research results to date, along with future plans. Topics discussed included modeling of thermal and fluid flow phenomena, structural analysis, fatigue and fracture, surface protective coatings, constitutive behavior, stress-strain response, and life prediction methods.

Engineering study on the rotary-vee engine concept

NASA Technical Reports Server (NTRS)

Willis, Edward A.; Bartland, Timothy A.; Beard, John E.

1989-01-01

This paper provides a review of the applicable thermodynamic cycle and performance considerations when the rotary-vee mechanism is used as an internal combustion (IC) heat engine. Included is a simplified kinematic analysis and studies of the effects of design parameters on the critical pressures, torques and parasitic losses. A discussion of the principal findings is presented.

Responses to Including Parents in Teacher Evaluation Policy: A Critical Policy Analysis

ERIC Educational Resources Information Center

Fernández, Erica; LeChasseur, Kimberly; Donaldson, Morgaen L.

2018-01-01

The intersection of development in family and school settings has been well established and education policies have begun to promote ways to bridge the two contexts (i.e. teacher evaluations). For this manuscript, authors focus on how teachers and principals used a state educator evaluation policy to position parents as authorities on education.…

The Influence of Typologies of School Leaders on Teacher Retention: A Multilevel Latent Class Analysis

ERIC Educational Resources Information Center

Urick, Angela

2016-01-01

Purpose: While school leadership literature has searched for practices with the largest effect on outcomes, we know little about how these behaviors vary by context. Further, recent shifts to include teachers in leadership have prompted a need for purposeful distinction between teacher and principal perceptions and roles. Person-centered…

Leaders of School Technology Innovation: A Confirmatory Factor Analysis of the Change Facilitator Style Questionnaire (CFSQ)

ERIC Educational Resources Information Center

Liu, Feng; Ritzhaupt, Albert; Cavanaugh, Cathy

2013-01-01

Purpose: This paper aims to describe a construct validation study of the Change Facilitator Style Questionnaire (CFSQ), an instrument designed to measure the leadership style of school principals as change facilitators. Design/methodology/approach: Participants included 614 K-12 teachers across the state of Florida involved in the Enhancing…

Refurbishment of Railroad Crossties : A Technical and Economic Analysis

DOT National Transportation Integrated Search

1977-12-01

An analysis of the principal modes of failure for wooden railroad crossties was conducted and an evaluation of the technical and economic feasibility of refurbishing these ties was conducted. Among the principal modes of structural deterioration, onl...

Contact- and distance-based principal component analysis of protein dynamics.

PubMed

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-28

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Contact- and distance-based principal component analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Ernst, Matthias; Sittel, Florian; Stock, Gerhard

2015-12-01

To interpret molecular dynamics simulations of complex systems, systematic dimensionality reduction methods such as principal component analysis (PCA) represent a well-established and popular approach. Apart from Cartesian coordinates, internal coordinates, e.g., backbone dihedral angles or various kinds of distances, may be used as input data in a PCA. Adopting two well-known model problems, folding of villin headpiece and the functional dynamics of BPTI, a systematic study of PCA using distance-based measures is presented which employs distances between Cα-atoms as well as distances between inter-residue contacts including side chains. While this approach seems prohibitive for larger systems due to the quadratic scaling of the number of distances with the size of the molecule, it is shown that it is sufficient (and sometimes even better) to include only relatively few selected distances in the analysis. The quality of the PCA is assessed by considering the resolution of the resulting free energy landscape (to identify metastable conformational states and barriers) and the decay behavior of the corresponding autocorrelation functions (to test the time scale separation of the PCA). By comparing results obtained with distance-based, dihedral angle, and Cartesian coordinates, the study shows that the choice of input variables may drastically influence the outcome of a PCA.

Attributes of School Leaders Towards Achieving Sustainable Leadership: A Factor Analysis

ERIC Educational Resources Information Center

Goolamally, Norlia; Ahmad, Jamil

2014-01-01

A principal plays a very important role in deciding the direction and success of a school. Whether a school is dynamic is dependent upon the skills and abilities of the principal. In order to be excellent, the principal must be in possession of an excellent character. Therefore, the selection and promotion of school principals should be conducted…

Reel Principals: A Descriptive Content Analysis of the Images of School Principals Depicted in Movies from 1997-2009

ERIC Educational Resources Information Center

Wolfrom, Katy J.

2010-01-01

According to Glanz's early research, school principals have been depicted as autocrats, bureaucrats, buffoons, and/or villains in movies from 1950 to 1996. The purpose of this study was to determine if these stereotypical characterizations of school principals have continued in films from 1997-2009, or if more favorable images have emerged that…

Textbook Leadership? An Analysis of Leading Books Used in Principal Preparation. PEPG 05-03

ERIC Educational Resources Information Center

Hess, Frederick M.; Kelly, Andrew P.

2005-01-01

In an era of accountability, where school leaders are expected to demonstrate bottom-line results and use data to drive decisions, the skill and knowledge of principals matter more than ever. Amidst the efforts to prepare principals for this new world, little scholarly attention has been paid to the content of what principals are actually reading…

Principals Play Many Parts: A Review of the Research on School Principals as Special Education Leaders 2001-2011

ERIC Educational Resources Information Center

Cobb, Cam

2015-01-01

This meta-analysis examines current North American research on the work of school principals in the special education milieu. More specifically, it considers how elementary and secondary principals envision and act in ways that foster inclusion within a school community. Three core special education-oriented domains arose in the 19 studies…

An Analysis of How the Gender and Race of School Principals Influences Their Perceptions of Multicultural Education

ERIC Educational Resources Information Center

McCray, Carlos R.; Beachum, Floyd D.

2010-01-01

The purpose of this study was to investigate secondary school principals' perceptions of multicultural education in a rural southeastern state. The researchers wanted to ascertain whether or not the race or gender of school principals have a role in how those principals view multicultural education in theory (its theoretical value). For the…

What Do We Expect of School Principals? Congruence between Principal Evaluation and Performance Standards

ERIC Educational Resources Information Center

Catano, Nancy; Stronge, James H.

2007-01-01

This study used both quantitative and qualitative methods of content analysis to examine principal evaluation instruments and state and professional standards for principals in school districts located in a mid-Atlantic state in the USA. The purposes of this study were to (a) determine the degrees of emphasis that are placed upon leadership and…

Principal Stratification — Uses and Limitations

PubMed Central

VanderWeele, Tyler J

2011-01-01

Pearl (2011) asked for the causal inference community to clarify the role of the principal stratification framework in the analysis of causal effects. Here, I argue that the notion of principal stratification has shed light on problems of non-compliance, censoring-by-death, and the analysis of post-infection outcomes; that it may be of use in considering problems of surrogacy but further development is needed; that it is of some use in assessing “direct effects”; but that it is not the appropriate tool for assessing “mediation.” There is nothing within the principal stratification framework that corresponds to a measure of an “indirect” or “mediated” effect. PMID:21841939

Exploring visuospatial abilities and their contribution to constructional abilities and nonverbal intelligence.

PubMed

Trojano, Luigi; Siciliano, Mattia; Cristinzio, Chiara; Grossi, Dario

2018-01-01

The present study aimed at exploring relationships among the visuospatial tasks included in the Battery for Visuospatial Abilities (BVA), and at assessing the relative contribution of different facets of visuospatial processing on tests tapping constructional abilities and nonverbal abstract reasoning. One hundred forty-four healthy subjects with a normal score on Mini Mental State Examination completed the BVA plus Raven's Coloured Progressive Matrices and Constructional Apraxia test. We used Principal Axis Factoring and Parallel Analysis to investigate relationships among the BVA visuospatial tasks, and performed regression analyses to assess the visuospatial contribution to constructional abilities and nonverbal abstract reasoning. Principal Axis Factoring and Parallel Analysis revealed two eigenvalues exceeding 1, accounting for about 60% of the variance. A 2-factor model provided the best fit. Factor 1 included sub-tests exploring "complex" visuospatial skills, whereas Factor 2 included two subtests tapping "simple" visuospatial skills. Regression analyses revealed that both Factor 1 and Factor 2 significantly affected performance on Raven's Coloured Progressive Matrices, whereas only the Factor 1 affected performance on Constructional Apraxia test. Our results supported functional segregation proposed by De Renzi, suggesting clinical caution to utilize a single test to assess visuospatial domain, and qualified the visuospatial contribution in drawing and non-verbal intelligence test.

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.

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.

[Determination of the Plant Origin of Licorice Oil Extract, a Natural Food Additive, by Principal Component Analysis Based on Chemical Components].

PubMed

Tada, Atsuko; Ishizuki, Kyoko; Sugimoto, Naoki; Yoshimatsu, Kayo; Kawahara, Nobuo; Suematsu, Takako; Arifuku, Kazunori; Fukai, Toshio; Tamura, Yukiyoshi; Ohtsuki, Takashi; Tahara, Maiko; Yamazaki, Takeshi; Akiyama, Hiroshi

2015-01-01

"Licorice oil extract" (LOE) (antioxidant agent) is described in the notice of Japanese food additive regulations as a material obtained from the roots and/or rhizomes of Glycyrrhiza uralensis, G. inflata or G. glabra. In this study, we aimed to identify the original Glycyrrhiza species of eight food additive products using LC/MS. Glabridin, a characteristic compound in G. glabra, was specifically detected in seven products, and licochalcone A, a characteristic compound in G. inflata, was detected in one product. In addition, Principal Component Analysis (PCA) (a kind of multivariate analysis) using the data of LC/MS or (1)H-NMR analysis was performed. The data of thirty-one samples, including LOE products used as food additives, ethanol extracts of various Glycyrrhiza species and commercially available Glycyrrhiza species-derived products were assessed. Based on the PCA results, the majority of LOE products was confirmed to be derived from G. glabra. This study suggests that PCA using (1)H-NMR analysis data is a simple and useful method to identify the plant species of origin of natural food additive products.

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

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

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.« less

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.

Thermal power systems small power systems applications project. Decision analysis for evaluating and ranking small solar thermal power system technologies. Volume 1: A brief introduction to multiattribute decision analysis. [explanation of multiattribute decision analysis methods used in evaluating alternatives for small powered systems

NASA Technical Reports Server (NTRS)

Feinberg, A.; Miles, R. F., Jr.

1978-01-01

The principal concepts of the Keeney and Raiffa approach to multiattribute decision analysis are described. Topics discussed include the concepts of decision alternatives, outcomes, objectives, attributes and their states, attribute utility functions, and the necessary independence properties for the attribute states to be aggregated into a numerical representation of the preferences of the decision maker for the outcomes and decision alternatives.

Multivariate analysis of fatty acid and biochemical constitutes of seaweeds to characterize their potential as bioresource for biofuel and fine chemicals.

PubMed

Verma, Priyanka; Kumar, Manoj; Mishra, Girish; Sahoo, Dinabandhu

2017-02-01

In the present study bio prospecting of thirty seaweeds from Indian coasts was analyzed for their biochemical components including pigments, fatty acid and ash content. Multivariate analysis of biochemical components and fatty acids was done using Principal Component Analysis (PCA) and Agglomerative hierarchical clustering (AHC) to manifest chemotaxonomic relationship among various seaweeds. The overall analysis suggests that these seaweeds have multi-functional properties and can be utilized as promising bioresource for proteins, lipids, pigments and carbohydrates for the food/feed and biofuel industry. Copyright © 2016. Published by Elsevier Ltd.

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...

Legal Problems of the Principal.

ERIC Educational Resources Information Center

Stern, Ralph D.; And Others

The three talks included here treat aspects of the law--tort liability, student records, and the age of majority--as they relate to the principal. Specifically, the talk on torts deals with the consequences of principal negligence in the event of injuries to students. Assurance is given that a reasonable and prudent principal will have a minimum…

Leadership Behaviors and Its Relation with Principals' Management Experience

ERIC Educational Resources Information Center

Mehdinezhad, Vali; Sardarzahi, Zaid

2016-01-01

This paper aims at studying the leadership behaviors reported by principals and observed by teachers and its relationship with management experience of principals. A quantitative method was used in this study. The target population included all principals and teachers of guidance schools and high schools in the Dashtiari District, Iran. A sample…

Differences and Similarities between School Principals in Costa Rica and the United States

ERIC Educational Resources Information Center

Ballestero, Victor; Wright, Sam

2008-01-01

The need for effective school leadership is a global concern. This paper provides a comparison of the school principal in Costa Rica to the United States. Differences and similarities are described for principals in both nations. Major differences for principals in Costa Rica include administrative salaries, selection procedures, induction, no…

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…

Two Charter School Principals' Engagement in Instructional Leadership

ERIC Educational Resources Information Center

Bickmore, Dana L.; Sulentic Dowell, Margaret-Mary

2014-01-01

This comparative case (Merriam, 2009) study explored two charter school principals' engagement in instructional leadership. Analysis of three data sources--interviews, observations, and documents--revealed that principals were almost exclusively focused on state accountability and possessed limited knowledge of pedagogical practices. In…

Principals: Learn P.R. Survival Skills.

ERIC Educational Resources Information Center

Reep, Beverly B.

1988-01-01

School building level public relations depends on the principal or vice principal. Strategies designed to enhance school public relations programs include linking school and community, working with the press, and keeping morale high inside the school. (MLF)

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.

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

PubMed

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

2013-10-01

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

Analysis of School Leaders Licensure Assessment Content Category I-V Scores and Principal Internship Self-Assessment Scores for ISLLC Standards I-V

ERIC Educational Resources Information Center

Kelly, Michael D.

2016-01-01

This study compares School Leaders Licensure Assessment (SLLA) sub-scores with principal interns' self-assessment sub-scores (ISA) for a principal internship evaluation instrument in one educational leadership graduate program. The results of the study will be used to help establish the effectiveness of the current principal internship program,…

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…

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.

Quantitative study of flavonoids in leaves of citrus plants.

PubMed

Kawaii, S; Tomono, Y; Katase, E; Ogawa, K; Yano, M; Koizumi, M; Ito, C; Furukawa, H

2000-09-01

Leaf flavonoids were quantitatively determined in 68 representative or economically important Citrus species, cultivars, and near-Citrus relatives. Contents of 23 flavonoids including 6 polymethoxylated flavones were analyzed by means of reversed phase HPLC analysis. Principal component analysis revealed that the 7 associations according to Tanaka's classification were observed, but some do overlap each other. Group VII species could be divided into two different subgroups, namely, the first-10-species class and the last-19-species class according to Tanaka's classification numbers.

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

Kravtsov, A.I.

To determine the effect of geologic factors on the composition of abyssal derivates (complementing existing information on the geochemistry of volcanic gases) isotopic analysis of carbon was used to obtain physicochemical criteria of the origin of gases, independent of geologic-petrographic data. The investigations include component analysis of all the gases, particularly hydrocarbon compounds, repeatedly found in the fumarole emanations of pyroclastic streams. Volcanic carbon dioxide which is the principal component of gases of active volcanoes and hot springs in the Kuril-Kamchatka volcanic arc and of other volcanoes was investigated.

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.

The impact of the principal in the implementation of promoting science among English language learners (P-SELL)

NASA Astrophysics Data System (ADS)

Kittrell, Resma

School organizations are in a constant state of change. One of the major changes that all schools encounter is adopting new curriculum. It is important to look at the role of the principal during the implementation of a new curriculum so that we can identify specific strategies that might be useful in other areas of school change. This study focuses on the role of the principal during the adoption of a new science curriculum, Promoting Science Among English Language Learners (P-SELL), within six elementary schools. This multiple case study included teacher focus group interviews, principal interviews, and teacher and principal written surveys to identify specific roles and strategies that principals illustrated during implementation of P-SELL. The overarching themes uncovered included (a) distributive leadership, (b) clear communication, and (c) supportive conditions. These findings can be used to understand the process of change within an organization.

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.

Genetic diversity among air yam (Dioscorea bulbifera) varieties based on single sequence repeat markers.

PubMed

Silva, D M; Siqueira, M V B M; Carrasco, N F; Mantello, C C; Nascimento, W F; Veasey, E A

2016-05-23

Dioscorea is the largest genus in the Dioscoreaceae family, and includes a number of economically important species including the air yam, D. bulbifera L. This study aimed to develop new single sequence repeat primers and characterize the genetic diversity of local varieties that originated in several municipalities of Brazil. We developed an enriched genomic library for D. bulbifera resulting in seven primers, six of which were polymorphic, and added four polymorphic loci developed for other Dioscorea species. This resulted in 10 polymorphic primers to evaluate 42 air yam accessions. Thirty-three alleles (bands) were found, with an average of 3.3 alleles per locus. The discrimination power ranged from 0.113 to 0.834, with an average of 0.595. Both principal coordinate and cluster analyses (using the Jaccard Index) failed to clearly separate the accessions according to their origins. However, the 13 accessions from Conceição dos Ouros, Minas Gerais State were clustered above zero on the principal coordinate 2 axis, and were also clustered into one subgroup in the cluster analysis. Accessions from Ubatuba, São Paulo State were clustered below zero on the same principal coordinate 2 axis, except for one accession, although they were scattered in several subgroups in the cluster analysis. Therefore, we found little spatial structure in the accessions, although those from Conceição dos Ouros and Ubatuba exhibited some spatial structure, and that there is a considerable level of genetic diversity in D. bulbifera maintained by traditional farmers in Brazil.

Assistant Principals' Lived Experiences with Managerial Skills Needed for Promotion: A Phenomenological Study

ERIC Educational Resources Information Center

Flowers, Melnice

2014-01-01

The purpose of this qualitative, phenomenological study was to explore the lived experiences of assistant principals in what they deem to be the needed managerial skills for promotion to campus principal. The sample for the study included 20 assistant principals in an urban school district located in Texas. The process of phenomenological enquiry…

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…

Problematic Preferences? A Mixed Method Examination of Principals' Preferences for Teacher Characteristics in Chicago

ERIC Educational Resources Information Center

Engel, Mimi

2013-01-01

Purpose: Relatively little is known about how principals make decisions about teacher hiring. This article uses mixed methods to examine what characteristics principals look for in teachers. Research Methods: Data were gathered using a mixed method approach, including in-depth interviews with a representative sample of 31 principals as well as an…

2 CFR 1532.995 - Principal (EPA supplement to government-wide definition at 2 CFR 180.995).

Code of Federal Regulations, 2010 CFR

2010-01-01

... transactions include: (a) Principal investigators; (b) Technical or management consultants; (c) Individuals... 2 Grants and Agreements 1 2010-01-01 2010-01-01 false Principal (EPA supplement to government-wide... § 1532.995 Principal (EPA supplement to government-wide definition at 2 CFR 180.995). In addition to...

School Principals as Marketing Managers: The Expanding Role of Marketing for School Development

ERIC Educational Resources Information Center

Anast-May, Linda; Mitchell, Mark; Buckner, Barbara Chesler; Elsberry, Cindy

2012-01-01

This study examined the relative importance that school principals attach to aspects of their role as marketing managers for their schools and their relative satisfaction with their efforts to date. The study included 60 principals from two school districts. Findings suggest that principals are aware of the importance of marketing in today's…

Challenges to Library Materials from Principals in United States Secondary Schools--A "Victory" of Sorts.

ERIC Educational Resources Information Center

Hopkins, Dianne McAfee

1995-01-01

Examines challenges to school library materials initiated by principals in public middle, junior, and senior high school libraries based on a 1990 survey. A review of literature emphasizing the leadership of principals, their role in school library program development, and the principal and school library censorship is included. (Author/LRW)

Perceptions of Kentucky High School Principals and Superintendents on the Role of the Superintendent Influencing Principal Instructional Leadership

ERIC Educational Resources Information Center

Hamilton, Charles L., Jr.

2011-01-01

This exploratory study surveyed the promotion of instructional leadership of high school principals by superintendents, as perceived by self and the principals they supervise. The two-phased study included an initial questionnaire administered to both study groups and comparisons of responses analyzed. All superintendents (N = 173), except the…

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.

Hot spot of structural ambivalence in prion protein revealed by secondary structure principal component analysis.

PubMed

Yamamoto, Norifumi

2014-08-21

The conformational conversion of proteins into an aggregation-prone form is a common feature of various neurodegenerative disorders including Alzheimer's, Huntington's, Parkinson's, and prion diseases. In the early stage of prion diseases, secondary structure conversion in prion protein (PrP) causing β-sheet expansion facilitates the formation of a pathogenic isoform with a high content of β-sheets and strong aggregation tendency to form amyloid fibrils. Herein, we propose a straightforward method to extract essential information regarding the secondary structure conversion of proteins from molecular simulations, named secondary structure principal component analysis (SSPCA). The definite existence of a PrP isoform with an increased β-sheet structure was confirmed in a free-energy landscape constructed by mapping protein structural data into a reduced space according to the principal components determined by the SSPCA. We suggest a "spot" of structural ambivalence in PrP-the C-terminal part of helix 2-that lacks a strong intrinsic secondary structure, thus promoting a partial α-helix-to-β-sheet conversion. This result is important to understand how the pathogenic conformational conversion of PrP is initiated in prion diseases. The SSPCA has great potential to solve various challenges in studying highly flexible molecular systems, such as intrinsically disordered proteins, structurally ambivalent peptides, and chameleon sequences.

Assessing the Structure of the Ways of Coping Questionnaire in Fibromyalgia Patients Using Common Factor Analytic Approaches.

PubMed

Van Liew, Charles; Santoro, Maya S; Edwards, Larissa; Kang, Jeremy; Cronan, Terry A

2016-01-01

The Ways of Coping Questionnaire (WCQ) is a widely used measure of coping processes. Despite its use in a variety of populations, there has been concern about the stability and structure of the WCQ across different populations. This study examines the factor structure of the WCQ in a large sample of individuals diagnosed with fibromyalgia. The participants were 501 adults (478 women) who were part of a larger intervention study. Participants completed the WCQ at their 6-month assessment. Foundational factoring approaches were performed on the data (i.e., maximum likelihood factoring [MLF], iterative principal factoring [IPF], principal axis factoring (PAF), and principal components factoring [PCF]) with oblique oblimin rotation. Various criteria were evaluated to determine the number of factors to be extracted, including Kaiser's rule, Scree plot visual analysis, 5 and 10% unique variance explained, 70 and 80% communal variance explained, and Horn's parallel analysis (PA). It was concluded that the 4-factor PAF solution was the preferable solution, based on PA extraction and the fact that this solution minimizes nonvocality and multivocality. The present study highlights the need for more research focused on defining the limits of the WCQ and the degree to which population-specific and context-specific subscale adjustments are needed.

Assessing the Structure of the Ways of Coping Questionnaire in Fibromyalgia Patients Using Common Factor Analytic Approaches

PubMed Central

Edwards, Larissa; Kang, Jeremy

2016-01-01

The Ways of Coping Questionnaire (WCQ) is a widely used measure of coping processes. Despite its use in a variety of populations, there has been concern about the stability and structure of the WCQ across different populations. This study examines the factor structure of the WCQ in a large sample of individuals diagnosed with fibromyalgia. The participants were 501 adults (478 women) who were part of a larger intervention study. Participants completed the WCQ at their 6-month assessment. Foundational factoring approaches were performed on the data (i.e., maximum likelihood factoring [MLF], iterative principal factoring [IPF], principal axis factoring (PAF), and principal components factoring [PCF]) with oblique oblimin rotation. Various criteria were evaluated to determine the number of factors to be extracted, including Kaiser's rule, Scree plot visual analysis, 5 and 10% unique variance explained, 70 and 80% communal variance explained, and Horn's parallel analysis (PA). It was concluded that the 4-factor PAF solution was the preferable solution, based on PA extraction and the fact that this solution minimizes nonvocality and multivocality. The present study highlights the need for more research focused on defining the limits of the WCQ and the degree to which population-specific and context-specific subscale adjustments are needed. PMID:28070160

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.

Comparison of patella bone strain between females with and without patellofemoral pain: a finite element analysis study.

PubMed

Ho, Kai-Yu; Keyak, Joyce H; Powers, Christopher M

2014-01-03

Elevated bone principal strain (an indicator of potential bone injury) resulting from reduced cartilage thickness has been suggested to contribute to patellofemoral symptoms. However, research linking patella bone strain, articular cartilage thickness, and patellofemoral pain (PFP) remains limited. The primary purpose was to determine whether females with PFP exhibit elevated patella bone strain when compared to pain-free controls. A secondary objective was to determine the influence of patella cartilage thickness on patella bone strain. Ten females with PFP and 10 gender, age, and activity-matched pain-free controls participated. Patella bone strain fields were quantified utilizing subject-specific finite element (FE) models of the patellofemoral joint (PFJ). Input parameters for the FE model included (1) PFJ geometry, (2) elastic moduli of the patella bone, (3) weight-bearing PFJ kinematics, and (4) quadriceps muscle forces. Using quasi-static simulations, peak and average minimum principal strains as well as peak and average maximum principal strains were quantified. Cartilage thickness was quantified by computing the perpendicular distance between opposing voxels defining the cartilage edges on axial plane magnetic resonance images. Compared to the pain-free controls, individuals with PFP exhibited increased peak and average minimum and maximum principal strain magnitudes in the patella. Additionally, patella cartilage thickness was negatively associated with peak minimum principal patella strain and peak maximum principal patella strain. The elevated bone strain magnitudes resulting from reduced cartilage thickness may contribute to patellofemoral symptoms and bone injury in persons with PFP. © 2013 Published by Elsevier Ltd.

Development and Factor Analysis of an Instrument to Measure Preservice Teachers' Perceptions of Learning Objects

ERIC Educational Resources Information Center

Sahin, Sami

2010-01-01

The purpose of this study was to develop a questionnaire to measure student teachers' perception of digital learning objects. The participants included 308 voluntary senior students attending courses in a college of education of a public university in Turkey. The items were extracted to their related factors by the principal axis factoring method.…

Pathways to the Principalship: An Event History Analysis of the Careers of Teachers with Principal Certification

ERIC Educational Resources Information Center

Davis, Bradley W.; Gooden, Mark A.; Bowers, Alex J.

2017-01-01

Utilizing rich data on nearly 11,000 educators over 17 academic years in a highly diverse context, we examine the career paths of teachers to determine whether and when they transition into the principalship. We utilize a variety of event history analyses, including discrete-time hazard modeling, to determine how an individual's race, gender, and…

Physician Manpower in Georgia: Report of the Task Force for Physician Manpower to the Georgia Comprehensive Health Planning Council.

ERIC Educational Resources Information Center

Georgia State Dept. of Public Health, Atlanta. Office of Comprehensive Health Planning.

This report is a result of a study of the state's physician manpower by representatives of the fields of medical education and professional practice in Georgia. Contents include introduction and principal findings, recommendations, and analysis of present supply of physicians and other data. Recommendations suggest improvement of the utilization…

Spacelab Level 4 Programmatic Implementation Assessment Study. Volume 4: Executive summary

NASA Technical Reports Server (NTRS)

1978-01-01

The study objectives of the Spacelab level 4 analysis were defined, along with the most significant results. The approach used in the synthesis and selection of alternate level 4 integration is described; the options included distributed site, lead center, and launch site. Principal characteristics, as well as the functional flow diagrams for each option, are presented and explained.

Ill health and early retirement among school principals in Bavaria.

PubMed

Weber, A; Weltle, D; Lederer, P

2005-05-01

School principals play an important role in maintaining the performance and health of teachers but often feel over-burdened themselves and suffer illnesses, which not only impairs their health-promoting function but also leads to limitations in their fitness for the occupation. The aim of our study was, therefore, using objective parameters and larger numbers of cases, to obtain a differentiated insight into the morbidity and the health-related early retirement of school principals. In a prospective total assessment (the whole of Bavaria, a state in southern Germany) in the period from 1997 to 1999 all medical examinations of school principals performed to decide the question of early retirement were evaluated. The analysis included, e.g., socio-demographic/occupational factors, diagnoses, assessment of performance and rehabilitation. The data were sampled in a standardised, anonymous questionnaire, which provided the database. Evaluation was carried out by means of descriptive statistics. The median age of the 408 school principals included in the evaluation (heads and vice-heads, 30% of whom were women) was 58 years (minimum 41 years, maximum 64 years). The most frequent workplaces were primary schools (63%). A total of 84% (n=342) of the headmasters was assessed to be unfit for work. The main reasons for early retirement were psychiatric/psychosomatic disorders (F-ICD 10) which made up 45% of the cases. The relative frequency was higher in women than in men. Depressive disorders and exhaustion syndromes (burnout) dominated among the psychiatric diagnoses (proportion 57%). The most frequent somatic illnesses were cardiovascular diseases (I-ICD10) in 19% of cases, then muscular/skeletal diseases (M-ICD10) in 10% and malignant tumours (C-ICD 10) in 9% of cases. Cardiovascular diseases, in particular arterial hypertension and ischaemic heart disease, were found in headmasters significantly more frequently than in teachers without a headship function (P

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

24 CFR 1003.204 - Special activities by Community-Based Development Organizations (CBDOs).

Code of Federal Regulations, 2010 CFR

2010-04-01

... activities that increase economic opportunity, principally for persons of low- and moderate-income, or that stimulate or retain businesses or permanent jobs, including projects that include one or more such... jobs; (3) Energy conservation project includes activities that address energy conservation, principally...

A Principal's Guide to ILS Facilities Installation.

ERIC Educational Resources Information Center

Ross, Tweed W.

1992-01-01

Outlines five facilities considerations that school principals need to address prior to the installation of an integrated learning system (ILS): (1) placement, i.e., labs or classrooms; (2) wiring; (3) environment, including furniture and noise; (4) security, including fire, theft, vandalism, and misuse; and (5) usability, including afterschool…

Recharge in semiarid mountain environments

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

Gross, G.W.

A systematic investigation of tritium activity in precipitation, surface water, springs, and ground water of the Roswell artesian basin in New Mexico, has been supplemented by hydrogeologic reconnaissance of spring systems; by various statistical correlations and spectral analysis of stream flow and water level records of observation wells; by spring discharge measurements; by stable isotope determinations (oxygen 18 and deuterium); and by numerical modeling of part of the basin. Two recharge contributions to the Principal or Carbonate Aquifer have been distinguished principally on the basis of their tritium label and aquifer response characteristics. Almost all basin waters (including deep groundmore » water) fall close to the meteoric line of hydrogen/oxygen isotope composition, and this rules out a juvenile origin or appreciable bedrock interaction.« less

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.

Extracting spectral contrast in Landsat Thematic Mapper image data using selective principal component analysis

USGS Publications Warehouse

Chavez, P.S.; Kwarteng, A.Y.

1989-01-01

A challenge encountered with Landsat Thematic Mapper (TM) data, which includes data from size reflective spectral bands, is displaying as much information as possible in a three-image set for color compositing or digital analysis. Principal component analysis (PCA) applied to the six TM bands simultaneously is often used to address this problem. However, two problems that can be encountered using the PCA method are that information of interest might be mathematically mapped to one of the unused components and that a color composite can be difficult to interpret. "Selective' PCA can be used to minimize both of these problems. The spectral contrast among several spectral regions was mapped for a northern Arizona site using Landsat TM data. Field investigations determined that most of the spectral contrast seen in this area was due to one of the following: the amount of iron and hematite in the soils and rocks, vegetation differences, standing and running water, or the presence of gypsum, which has a higher moisture retention capability than do the surrounding soils and rocks. -from Authors

Fault-slip inversions: Their importance in terms of strain, heterogeneity, and kinematics of brittle deformation

NASA Astrophysics Data System (ADS)

Riller, U.; Clark, M. D.; Daxberger, H.; Doman, D.; Lenauer, I.; Plath, S.; Santimano, T.

2017-08-01

Heterogeneous deformation is intrinsic in natural deformation, but often underestimated in the analysis and interpretation of mesoscopic brittle shear faults. Based on the analysis of 11,222 faults from two distinct tectonic settings, the Central Andes in Argentina and the Sudbury area in Canada, interpolation of principal strain directions and scaled analogue modelling, we revisit controversial issues of fault-slip inversions, collectively adhering to heterogeneous deformation. These issues include the significance of inversion solutions in terms of (1) strain or paleo-stress; (2) displacement, notably plate convergence; (3) local versus far-field deformation; (4) strain perturbations and (5) spacing between stations of fault-slip data acquisition. Furthermore, we highlight the value of inversions for identifying the kinematics of master fault zones in the absence of displaced geological markers. A key result of our assessment is that fault-slip inversions relate to local strain, not paleo-stress, and thus can aid in inferring, the kinematics of master faults. Moreover, strain perturbations caused by mechanical anomalies of the deforming upper crust significantly influence local principal strain directions. Thus, differently oriented principal strain axes inferred from fault-slip inversions in a given region may not point to regional deformation caused by successive and distinct deformation regimes. This outcome calls into question the common practice of separating heterogeneous fault-slip data sets into apparently homogeneous subsets. Finally, the fact that displacement vectors and principal strains are rarely co-linear defies the use of brittle fault data as proxy for estimating directions of plate-scale motions.

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…

Challenging the Image of the American Principalship.

ERIC Educational Resources Information Center

Langer, Sondra; Boris-Schacter, Sheryl

2003-01-01

Reports results of three year study of more than 200 principals about the tensions between role expectations and reality. Analysis of surveys and interviews finds most principals having to deal with three pairs of tensions: Between instructional leadership and management tasks, between personal and professional demands, and between the principal's…

Analyzing Principal Professional Development Practices through the Lens of Adult Learning Theory

ERIC Educational Resources Information Center

Zepeda, Sally J.; Parylo, Oksana; Bengtson, Ed

2014-01-01

This qualitative study sought to identify current principal professional development practices in four school systems in Georgia and to examine them by applying the principles of adult learning theory. The cross-case analysis of principal professional development initiatives in four school districts revealed nine common practices: connecting…

Perceptions of Leadership Behaviors by Female Principals in North Carolina

ERIC Educational Resources Information Center

McFadden, Cheryl; Maahs-Fladung, Cathy; Beck-Frazier, Susan; Bruckner, Kermit

2009-01-01

This study was designed to investigate whether significant differences exist among the perceptions of leadership behaviors of female principals in North Carolina using Bolman and Deal's (1984) four frames (structural, human resource, political, and symbolic) for analysis. Participants consisted of 1,245 female principals from elementary,middle,…

Challenges Facing Principals in the First Year at Their Schools

ERIC Educational Resources Information Center

Bayar, Adem

2016-01-01

The aim of this study is to identify key challenges of practice that principals face. In line with this purpose, the researcher has employed a qualitative research methodology, interviewing principals working in Amasya district, over and above doing document analysis to collect detailed information concerning leadership and administration…

Predicting Teacher Job Satisfaction Based on Principals' Instructional Supervision Behaviours: A Study of Turkish Teachers

ERIC Educational Resources Information Center

Ilgan, Abdurrahman; Parylo, Oksana; Sungu, Hilmi

2015-01-01

This quantitative research examined instructional supervision behaviours of school principals as a predictor of teacher job satisfaction through the analysis of Turkish teachers' perceptions of principals' instructional supervision behaviours. There was a statistically significant difference found between the teachers' job satisfaction level and…

Principal Leadership and School Capacity Effects on Teacher Learning in Hong Kong

ERIC Educational Resources Information Center

Li, Lijuan; Hallinger, Philip; Ko, James

2016-01-01

Purpose: Over the past decade, studies of school leadership effects have increasingly aimed at identifying and validating the paths through which principal leadership impacts key teaching and learning processes in schools. A recent meta-analysis by Robinson and colleagues identified principal practices that shape teacher professional development…

Effects of mutation, truncation, and temperature on the folding kinetics of a WW domain.

PubMed

Maisuradze, Gia G; Zhou, Rui; Liwo, Adam; Xiao, Yi; Scheraga, Harold A

2012-07-20

The purpose of this work is to show how mutation, truncation, and change of temperature can influence the folding kinetics of a protein. This is accomplished by principal component analysis of molecular-dynamics-generated folding trajectories of the triple β-strand WW domain from formin binding protein 28 (FBP28) (Protein Data Bank ID: 1E0L) and its full-size, and singly- and doubly-truncated mutants at temperatures below and very close to the melting point. The reasons for biphasic folding kinetics [i.e., coexistence of slow (three-state) and fast (two-state) phases], including the involvement of a solvent-exposed hydrophobic cluster and another delocalized hydrophobic core in the folding kinetics, are discussed. New folding pathways are identified in free-energy landscapes determined in terms of principal components for full-size mutants. Three-state folding is found to be a main mechanism for folding the FBP28 WW domain and most of the full-size and truncated mutants. The results from the theoretical analysis are compared to those from experiment. Agreements and discrepancies between the theoretical and experimental results are discussed. Because of its importance in understanding protein kinetics and function, the diffusive mechanism by which the FBP28 WW domain and its full-size and truncated mutants explore their conformational space is examined in terms of the mean-square displacement and principal component analysis eigenvalue spectrum analyses. Subdiffusive behavior is observed for all studied systems. Copyright © 2012. Published by Elsevier Ltd.

Metabolic profiling of Zingiber zerumbet following Pythium myriotylum infection: investigations on the defensive role of the principal secondary metabolite, zerumbone.

PubMed

Keerthi, D; Geethu, C; Nair, R Aswati; Pillai, Padmesh

2014-03-01

Induced biosynthesis of bioactive secondary metabolites constitutes one of the mechanisms of plant basal innate immunity to fungal infection. Metabolic changes were studied in rhizomes of Zingiber zerumbet, a wild congener of ginger, after infection with soft rot-causative necrotrophic phytopathogen, Pythium myriotylum, by gas chromatography-mass spectrometry (GC-MS) analysis. Infection triggered a considerable alteration in the relative content of zerumbone and α-caryophyllene (humulene) with enhancement in zerumbone content (81.59%) and that of α-caryophyllene (11.91%) compared to 9.97 and 1.11%, respectively, in uninfected rhizomes. While zerumbone is the principal secondary metabolite in Z. zerumbet, α-caryophyllene is its immediate precursor. Principal component analysis (PCA) identified the correlations between metabolite changes in Z. zerumbet rhizomes and P. myriotylum infection. Radial diffusion assay with zerumbone indicated a concentration-dependent P. myriotylum growth inhibition with 93.75% inhibition observed at 700 μg and 50% maximal effective concentration (EC50) value of 206 μg. Scanning electron microscopy (SEM) analysis revealed that the mechanistic basis of zerumbone's antagonistic action on P. myriotylum growth involved the induction of aberrant morphology including severe hyphal deformities and membrane disruption. Results are discussed highlighting the critical role played by sesquiterpenoid zerumbone in affording resistance in Z. zerumbet and could expedite the development of appropriate strategies for biocontrol of Pythium spp., thus reducing the usage of broad-spectrum fungicides.

Morphological analysis of Trichomycterus areolatus Valenciennes, 1846 from southern Chilean rivers using a truss-based system (Siluriformes, Trichomycteridae)

PubMed Central

Colihueque, Nelson; Corrales, Olga; Yáñez, Miguel

2017-01-01

Abstract Trichomycterus areolatus Valenciennes, 1846 is a small endemic catfish inhabiting the Andean river basins of Chile. In this study, the morphological variability of three T. areolatus populations, collected in two river basins from southern Chile, was assessed with multivariate analyses, including principal component analysis (PCA) and discriminant function analysis (DFA). It is hypothesized that populations must segregate morphologically from each other based on the river basin that they were sampled from, since each basin presents relatively particular hydrological characteristics. Significant morphological differences among the three populations were found with PCA (ANOSIM test, r = 0.552, p < 0.0001) and DFA (Wilks’s λ = 0.036, p < 0.01). PCA accounted for a total variation of 56.16% by the first two principal components. The first Principal Component (PC1) and PC2 explained 34.72 and 21.44% of the total variation, respectively. The scatter-plot of the first two discriminant functions (DF1 on DF2) also validated the existence of three different populations. In group classification using DFA, 93.3% of the specimens were correctly-classified into their original populations. Of the total of 22 transformed truss measurements, 17 exhibited highly significant (p < 0.01) differences among populations. The data support the existence of T. areolatus morphological variation across different rivers in southern Chile, likely reflecting the geographic isolation underlying population structure of the species. PMID:29134012

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

PubMed

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

2018-01-01

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

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.

Using Administrative Data for Research: A Companion Guide to "A Descriptive Analysis of the Principal Workforce in Florida Schools." REL 2015-049

ERIC Educational Resources Information Center

Folsom, Jessica Sidler; Osborne-Lampkin, La'Tara; Herrington, Carolyn D.

2014-01-01

This document is a companion guide to "A Descriptive Analysis of the Principal Workforce in Florida Schools" (Folsom, Osborne-Lampkin, & Herrington, in press). It describes the methods used to extract information from the Florida Department of Education database in order to conduct a descriptive analysis of the demographic…

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.%}

17 CFR 270.30a-3 - Controls and procedures.

Code of Federal Regulations, 2010 CFR

2010-04-01

... management must evaluate, with the participation of the company's principal executive and principal financial... accumulated and communicated to the investment company's management, including its principal executive and...) Every registered management investment company, other than a small business investment company...

The role of engineering in the flight equipment purchasing process

NASA Technical Reports Server (NTRS)

1977-01-01

The role of the airline engineering department in the flight equipment acquisition process is examined. The data for the study was collected from six airlines. The principal findings of the study include: (1) engineering activities permeate, but do not dominate the airline flight equipment decision process. (2) The principal criterion for the flight equipment acquisition decision is return on investment. (3) The principal sources of information for the airline engineering departments in the monitoring process are the manufacturers of equipment. Subsidiary information sources include NASA publications and conferences, among others and (4) The engineering department is the principal communication channel for technical information.

Evaluating the Role of Principals in Teacher Teams: A Longitudinal Analysis of Principal Involvement and Impact in a District-Wide Initiative to Increase Teacher Collaboration

ERIC Educational Resources Information Center

Outhouse, Craig Michael

2012-01-01

Principal leadership is one of the most heavily researched topics in the field of education and is a key to increasing school effectiveness and stimulating school change. One of the most important principal roles that have emerged in the literature is the facilitation of a collaborative culture. Teacher collaboration has been linked to a variety…

Good Principals, Good Schools.

ERIC Educational Resources Information Center

Adams, Jeanne P.

1999-01-01

A three-county survey of administrative credential students in California found that 26% of respondents serving in administrative positions are considering leaving their jobs; 62% of qualified candidates are staying in the classroom. Solutions to principal overload include hiring more assistant principals and grooming inhouse talent. (MLH)

Patterns of behavior in online homework for introductory physics

NASA Astrophysics Data System (ADS)

Fredericks, Colin

Student activity in online homework was obtained from courses in physics in 2003 and 2005. This data was analyzed through a variety of methods, including principal component analysis, Pearson's r correlation, and comparison to performance measures such as detailed exam scores. Through this analysis it was determined which measured homework behaviors were associated with high exam scores and course grades. It was also determined that homework problems requiring analysis can have an impact on certain types of exam problems where traditional homework does not. Suggestions are given for future research and possible use of these methods in other contexts.

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.

Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition.

PubMed

Gilbert, Peter B; Gabriel, Erin E; Huang, Ying; Chan, Ivan S F

2015-09-01

A common problem of interest within a randomized clinical trial is the evaluation of an inexpensive response endpoint as a valid surrogate endpoint for a clinical endpoint, where a chief purpose of a valid surrogate is to provide a way to make correct inferences on clinical treatment effects in future studies without needing to collect the clinical endpoint data. Within the principal stratification framework for addressing this problem based on data from a single randomized clinical efficacy trial, a variety of definitions and criteria for a good surrogate endpoint have been proposed, all based on or closely related to the "principal effects" or "causal effect predictiveness (CEP)" surface. We discuss CEP-based criteria for a useful surrogate endpoint, including (1) the meaning and relative importance of proposed criteria including average causal necessity (ACN), average causal sufficiency (ACS), and large clinical effect modification; (2) the relationship between these criteria and the Prentice definition of a valid surrogate endpoint; and (3) the relationship between these criteria and the consistency criterion (i.e., assurance against the "surrogate paradox"). This includes the result that ACN plus a strong version of ACS generally do not imply the Prentice definition nor the consistency criterion, but they do have these implications in special cases. Moreover, the converse does not hold except in a special case with a binary candidate surrogate. The results highlight that assumptions about the treatment effect on the clinical endpoint before the candidate surrogate is measured are influential for the ability to draw conclusions about the Prentice definition or consistency. In addition, we emphasize that in some scenarios that occur commonly in practice, the principal strata sub-populations for inference are identifiable from the observable data, in which cases the principal stratification framework has relatively high utility for the purpose of effect modification analysis, and is closely connected to the treatment marker selection problem. The results are illustrated with application to a vaccine efficacy trial, where ACN and ACS for an antibody marker are found to be consistent with the data and hence support the Prentice definition and consistency.

Surrogate Endpoint Evaluation: Principal Stratification Criteria and the Prentice Definition

PubMed Central

Gilbert, Peter B.; Gabriel, Erin E.; Huang, Ying; Chan, Ivan S.F.

2015-01-01

A common problem of interest within a randomized clinical trial is the evaluation of an inexpensive response endpoint as a valid surrogate endpoint for a clinical endpoint, where a chief purpose of a valid surrogate is to provide a way to make correct inferences on clinical treatment effects in future studies without needing to collect the clinical endpoint data. Within the principal stratification framework for addressing this problem based on data from a single randomized clinical efficacy trial, a variety of definitions and criteria for a good surrogate endpoint have been proposed, all based on or closely related to the “principal effects” or “causal effect predictiveness (CEP)” surface. We discuss CEP-based criteria for a useful surrogate endpoint, including (1) the meaning and relative importance of proposed criteria including average causal necessity (ACN), average causal sufficiency (ACS), and large clinical effect modification; (2) the relationship between these criteria and the Prentice definition of a valid surrogate endpoint; and (3) the relationship between these criteria and the consistency criterion (i.e., assurance against the “surrogate paradox”). This includes the result that ACN plus a strong version of ACS generally do not imply the Prentice definition nor the consistency criterion, but they do have these implications in special cases. Moreover, the converse does not hold except in a special case with a binary candidate surrogate. The results highlight that assumptions about the treatment effect on the clinical endpoint before the candidate surrogate is measured are influential for the ability to draw conclusions about the Prentice definition or consistency. In addition, we emphasize that in some scenarios that occur commonly in practice, the principal strata sub-populations for inference are identifiable from the observable data, in which cases the principal stratification framework has relatively high utility for the purpose of effect modification analysis, and is closely connected to the treatment marker selection problem. The results are illustrated with application to a vaccine efficacy trial, where ACN and ACS for an antibody marker are found to be consistent with the data and hence support the Prentice definition and consistency. PMID:26722639

Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

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

Eckert-Gallup, Aubrey Celia; Sallaberry, Cedric Jean-Marie; Dallman, Ann Renee

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulation s as a part of the stand ard current practice for designing marine structure s to survive extreme sea states. Such environmental contours are characterized by combinations of significant wave height ( ) and energy period ( ) 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 (IFORM) i s standard design practice for generating environmental contours.more » In this paper, the traditional appli cation of the IFORM to generating environmental contours representing extreme sea states is described in detail and its merits and drawbacks are assessed. The application of additional methods for analyzing sea state data including the use of principal component analysis (PCA) to create an uncorrelated representation of the data under consideration is proposed. A reexamination of the components of the IFORM application to the problem at hand including the use of new distribution fitting techniques are shown to contribute to the development of more accurate a nd reasonable representations of extreme sea states for use in survivability analysis for marine struc tures. Keywords: In verse FORM, Principal Component Analysis , Environmental Contours, Extreme Sea State Characteri zation, Wave Energy Converters« less

SESNPCA: Principal Component Analysis Applied to Stripped-Envelope Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Williamson, Marc; Bianco, Federica; Modjaz, Maryam

2018-01-01

In the new era of time-domain astronomy, it will become increasingly important to have rigorous, data driven models for classifying transients, including supernovae (SNe). We present the first application of principal component analysis (PCA) to stripped-envelope core-collapse supernovae (SESNe). Previous studies of SNe types Ib, IIb, Ic, and broad-line Ic (Ic-BL) focus only on specific spectral features, while our PCA algorithm uses all of the information contained in each spectrum. We use one of the largest compiled datasets of SESNe, containing over 150 SNe, each with spectra taken at multiple phases. Our work focuses on 49 SNe with spectra taken 15 ± 5 days after maximum V-band light where better distinctions can be made between SNe type Ib and Ic spectra. We find that spectra of SNe type IIb and Ic-BL are separable from the other types in PCA space, indicating that PCA is a promising option for developing a purely data driven model for SESNe classification.

Multilevel Analysis of the Relationship between Principals' Perceived Practices of Instructional Leadership and Teachers' Self-Efficacy Perceptions

ERIC Educational Resources Information Center

Bellibas, Mehmet Sukru; Liu, Yan

2017-01-01

Purpose: The purpose of this paper is to investigate the extent to which principals' instructional leadership predicts teacher self-efficacy, in order to identify whether a relationship exists between principals' perceived instructional leadership practices and teachers perceived self-efficacy in classroom management, instruction, and student…

The Other Side of the Principalship: An Informal Organization Perspective.

ERIC Educational Resources Information Center

Licata, Joseph W.; Hack, Walter G.

Analysis of an informal subculture among school principals reveals the existence of norms and beliefs that may help them function in their jobs. Researchers interviewed all 28 principals in a medium-sized suburban Ohio school district to investigate their informal communications with each other. The norms identified forbid principals to be…

School Principals Speaking Back to Widening Participation Policies in Higher Education

ERIC Educational Resources Information Center

Blackmore, Jill; Hutchison, Kirsten; Keary, Anne

2017-01-01

This paper examines school principal responses to the policy discourse of widening participation in higher education. As a critical analysis of how policy is produced, read and responded to by principals [Bacchi, C., 2009. "Analysing policy: what's the problem represented to be?" New York: Pearson], the paper questions the assumptions…

Instructional Leadership Challenges and Practices of Novice Principals in Rural Schools

ERIC Educational Resources Information Center

Wiezorek, Douglas; Manard, Carolyn

2018-01-01

We report on a phenomenological study of the leadership experiences of six novice, rural public school principals in a midwestern U.S. state. We situated our analysis within existing research on leadership for learning, particularly how novice principals interpreted instructional leadership challenges in the context of rural school leadership. Our…

Micro-Political Analysis of the Principal Selection in a Taiwanese Elementary School

ERIC Educational Resources Information Center

Chen, Hsin-Jen

2013-01-01

This paper aims to investigate the micropolitical actions and strategies employed by the principal in the researched elementary school located in Northern Taiwan. Firstly, the author argues that the mechanism of the principal selection in Taiwan is the product of educational reform affected by policy borrowing. Secondly, drawing on ethnographic…

Principal Leadership in New Teacher Induction: Becoming Agents of Change

ERIC Educational Resources Information Center

Cherian, Finney; Daniel, Yvette

2008-01-01

This small-scale pilot study investigated the role of school principals in the induction of new teachers in Ontario, Canada. Building upon the theoretical framework of Bolman and Deal (2002), as well as interviews, document analysis, and review of extant literature, the following findings were established: (a) Principals expressed that the…

Conceptualizations of School Leadership among High School Principals in Jamaica

ERIC Educational Resources Information Center

Newman, Mairette

2013-01-01

Drawing on evidence from research that adopted a qualitative case study design and used grounded theory methods of data analysis, this study examined how selected high school principals in Jamaica conceptualize school leadership. Data were sourced from semi-structured interviews, field observations as well as from school, principal and official…

Describing an "Effective" Principal: Perceptions of the Central Office Leaders

ERIC Educational Resources Information Center

Parylo, Oksana; Zepeda, Sally J.

2014-01-01

The purpose of this qualitative study was to examine how district leaders of two school systems in the USA describe an effective principal. Membership categorisation analysis revealed that district leaders believed an effective principal had four major categories of characteristics: (1) documented characteristics (having a track record and being a…

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…

Investing in Leadership: The District's Role in Managing Principal Turnover

ERIC Educational Resources Information Center

Mascall, Blair; Leithwood, Kenneth

2010-01-01

This article presents the results of research into the impact of principal turnover on schools, and the ability of schools to mitigate the negative effects of frequent turnover by distributing leadership in the schools. The findings from this qualitative and quantitative analysis show that rapid principal turnover does indeed have a negative…

The Reflexive Adaptations of School Principals in a "Local" South African Space

ERIC Educational Resources Information Center

Fataar, Aslam

2009-01-01

This paper is an analysis of the work of three principals in an impoverished black township in post-apartheid South Africa. Based on qualitative approaches, it discusses the principals' entry into the township, and their navigation of their schools' surrounding social dynamics. It combines the lenses of "space" and…

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...

A Descriptive Analysis of the Principal Workforce in Wisconsin. Issues & Answers. REL 2012-No. 135

ERIC Educational Resources Information Center

Clifford, Matthew; Condon, Chris; Greenberg, Ariela; Williams, Ryan; Gerdeman, R. Dean; Fetters, Jenni; Baker, Bruce

2012-01-01

This study responds to a request from the Wisconsin Department of Public Instruction for information on Wisconsin's school principal workforce population. Descriptive analyses addressed two research questions: (1) How do the demographic characteristics of Wisconsin school principals compare how did these characteristics change over 1999-2009?; and…

Principals' Leadership Behaviors as Perceived by Teachers in At-Risk Middle Schools

ERIC Educational Resources Information Center

Johnson, R. Anthony

2011-01-01

A need for greater understanding of teachers' (N = 530) perceptions of the leadership behaviors of principals in Title I middle schools (n = 13) is prevalent exists. The researcher used the "Audit of Principal Effectiveness" survey to collect data. The researcher also used Hierarchical Linear Modeling as the quantitative analysis.…

Representing Embodiment and the Policy Implementing Principal Using Photovoice

ERIC Educational Resources Information Center

Werts, Amanda B.; Brewer, Curtis A.; Mathews, Sarah A.

2012-01-01

Purpose: The purpose of this paper is to contribute to the literature on the many dimensions of the principal's positionality by using a unique research approach to link the experiences of the policy implementing principal to embodiment. Design/methodology/approach: The researchers employed a form of critical policy analysis that utilized…

Measurement Invariance of the "Servant Leadership Questionnaire" across K-12 Principal Gender

ERIC Educational Resources Information Center

Xu, Lihua; Stewart, Trae; Haber-Curran, Paige

2015-01-01

Measurement invariance of the five-factor "Servant Leadership Questionnaire" between female and male K-12 principals was tested using multi-group confirmatory factor analysis. A sample of 956 principals (56.9% were females and 43.1% were males) was analysed in this study. The hierarchical multi-step measurement invariance test supported…

School Principals' Job Satisfaction: The Effects of Work Intensification

ERIC Educational Resources Information Center

Wang, Fei; Pollock, Katina; Hauseman, Cameron

2018-01-01

This study examines principals' job satisfaction in relation to their work intensification. Frederick Herzberg's two-factor theory was used to shed light on how motivating and maintenance factors affect principals' job satisfaction. Logistic multiple regressions were used in the analysis of survey data that were collected from 2,701 elementary and…

Principals' Reactions to Feedback Received by School Inspection: A Longitudinal Study

ERIC Educational Resources Information Center

Behnke, Kristin; Steins, Gisela

2017-01-01

This article presents the results of a follow-up study on the attitudes of German principals towards receiving feedback from school inspections. In a first study, we explored the attitudes of 50 principals towards feedback from school inspections [Quality Analysis (QA) in North Rhine-Westphalia] before school inspections took place at these…

School Administrators' Perceptions of a Principal Preparation Program after Participating in Portfolio Defenses

ERIC Educational Resources Information Center

Armenta, Tony; DeVaney, Thomas

2008-01-01

A major recommendation, or mandate in some cases, handed down to principal preparation programs from accrediting agencies, state certication departments, or other bodies, is to prominently include school districts in the program. This might include Advisory Councils that include public school administrators, involving districts in the selection of…

Clinical feasibility and validation of 3D principal strain analysis from cine MRI: comparison to 2D strain by MRI and 3D speckle tracking echocardiography.

PubMed

Satriano, Alessandro; Heydari, Bobak; Narous, Mariam; Exner, Derek V; Mikami, Yoko; Attwood, Monica M; Tyberg, John V; Lydell, Carmen P; Howarth, Andrew G; Fine, Nowell M; White, James A

2017-12-01

Two-dimensional (2D) strain analysis is constrained by geometry-dependent reference directions of deformation (i.e. radial, circumferential, and longitudinal) following the assumption of cylindrical chamber architecture. Three-dimensional (3D) principal strain analysis may overcome such limitations by referencing intrinsic (i.e. principal) directions of deformation. This study aimed to demonstrate clinical feasibility of 3D principal strain analysis from routine 2D cine MRI with validation to strain from 2D tagged cine analysis and 3D speckle tracking echocardiography. Thirty-one patients undergoing cardiac MRI were studied. 3D strain was measured from routine, multi-planar 2D cine SSFP images using custom software designed to apply 4D deformation fields to 3D cardiac models to derive principal strain. Comparisons of strain estimates versus those by 2D tagged cine, 2D non-tagged cine (feature tracking), and 3D speckle tracking echocardiography (STE) were performed. Mean age was 51 ± 14 (36% female). Mean LV ejection fraction was 66 ± 10% (range 37-80%). 3D principal strain analysis was feasible in all subjects and showed high inter- and intra-observer reproducibility (ICC range 0.83-0.97 and 0.83-0.98, respectively-p < 0.001 for all directions). Strong correlations of minimum and maximum principal strain were respectively observed versus the following: 3D STE estimates of longitudinal (r = 0.81 and r = -0.64), circumferential (r = 0.76 and r = -0.58) and radial (r = -0.80 and r = 0.63) strain (p < 0.001 for all); 2D tagged cine estimates of longitudinal (r = 0.81 and r = -0.81), circumferential (r = 0.87 and r = -0.85), and radial (r = -0.76 and r = 0.81) strain (p < 0.0001 for all); and 2D cine (feature tracking) estimates of longitudinal (r = 0.85 and -0.83), circumferential (r = 0.88 and r = -0.87), and radial strain (r = -0.79 and r = 0.84, p < 0.0001 for all). 3D principal strain analysis is feasible using routine, multi-planar 2D cine MRI and shows high reproducibility with strong correlations to 2D conventional strain analysis and 3D STE-based analysis. Given its independence from geometry-related directions of deformation this technique may offer unique benefit for the detection and prognostication of myocardial disease, and warrants expanded investigation.

Principal Component-Based Radiative Transfer Model (PCRTM) for Hyperspectral Sensors. Part I; Theoretical Concept

NASA Technical Reports Server (NTRS)

Liu, Xu; Smith, William L.; Zhou, Daniel K.; Larar, Allen

2005-01-01

Modern infrared satellite sensors such as Atmospheric Infrared Sounder (AIRS), Cosmic Ray Isotope Spectrometer (CrIS), Thermal Emission Spectrometer (TES), Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and Infrared Atmospheric Sounding Interferometer (IASI) are capable of providing high spatial and spectral resolution infrared spectra. To fully exploit the vast amount of spectral information from these instruments, super fast radiative transfer models are needed. This paper presents a novel radiative transfer model based on principal component analysis. Instead of predicting channel radiance or transmittance spectra directly, the Principal Component-based Radiative Transfer Model (PCRTM) predicts the Principal Component (PC) scores of these quantities. This prediction ability leads to significant savings in computational time. The parameterization of the PCRTM model is derived from properties of PC scores and instrument line shape functions. The PCRTM is very accurate and flexible. Due to its high speed and compressed spectral information format, it has great potential for super fast one-dimensional physical retrievals and for Numerical Weather Prediction (NWP) large volume radiance data assimilation applications. The model has been successfully developed for the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I) and AIRS instruments. The PCRTM model performs monochromatic radiative transfer calculations and is able to include multiple scattering calculations to account for clouds and aerosols.

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.

Carcinogenic N-Nitrosamines. Formation, Properties, and Analysis

NASA Astrophysics Data System (ADS)

Kostyukovskii, Ya L.; Melamed, D. B.

1988-04-01

Literature data on the formation of carcinogenic N-nitrosamines in the environment, their physicochemical properties, their action on the human organism, the methods for their microanalysis, and also their content in the atmosphere, water sources, soil, and industrial agricultural and food products are described systematically and surveyed. The principal features of this comparatively new class of powerful chemical carcinogens are indicated. The bibliography includes 284 references.

Sexual function in cervical cancer patients: Psychometric properties and performance of a Chinese version of the Female Sexual Function Index.

PubMed

Liu, Huayun; Yu, Juping; Chen, Yongyi; He, Pingping; Zhou, Lianqing; Tang, Xinhui; Liu, Xiangyu; Li, Xuying; Wu, Yanping; Wang, Yuhua

2016-02-01

This study aimed to examine the psychometric properties and performance of a Chinese version of the Female Sexual Function Index (FSFI) among a sample of Chinese women with cervical cancer. A cross-sectional survey design was used. The respondents included 215 women with cervical cancer in an oncology hospital in China. A translated Chinese version of the FSFI was used to investigate their sexual functioning. Psychometric testing included internal consistency reliability (Cronbach's alpha coefficient and item-total correlations), test-retest reliability, construct validity (principal component analysis via oblique rotation and confirmatory factor analysis), and variability (floor and ceiling effects). The mean score of the total scale was 20.65 ± 4.77. The Cronbach values were .94 for the total scale, .72-.90 for the domains. Test-retest correlation coefficients over 2-4 weeks were .84 (p < .05) for the total scale, .68-.83 for the subscales. Item-total correlation coefficients ranged between .47 and .83 (p < .05). A five-factor model was identified via principal component analysis and established by confirmatory factor analysis, including desire/arousal, lubrication, orgasm, satisfaction, and pain. There was no evidence of floor or ceiling effects. With good psychometric properties similar to its original English version, this Chinese version of the FSFI is demonstrated to be a reliable and valid instrument that can be used to assess sexual functioning of women with cervical cancer in China. Future research is still needed to confirm its psychometric properties and performance among a large sample. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-08-01

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

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.

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.

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures.

PubMed

Theobald, Douglas L; Wuttke, Deborah S

2006-09-01

THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. ANSI C source code and selected binaries for various computing platforms are available under the GNU open source license from http://monkshood.colorado.edu/theseus/ or http://www.theseus3d.org.

Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques.

PubMed

Tahir, Haroon Elrasheid; Xiaobo, Zou; Xiaowei, Huang; Jiyong, Shi; Mariod, Abdalbasit Adam

2016-09-01

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

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…

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…

Analysis of Manager Selection and Appointment to Educational Organizations Process in Turkey

ERIC Educational Resources Information Center

Yard?b?, Nursel; Küçük, Fazil

2015-01-01

This study's aim is that to determine the requirements for school principals' selection and assignment conditions and to present these requirements' effects. Qualitative research design was used in this research, and also this study is content analysis research. School principals' selection and assignment conditions in Regulations between the…

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)

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.…

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…

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

PubMed

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

2011-01-01

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

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.

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.

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state

PubMed Central

Zhao, Fang; Tsien, Joe Z.

2017-01-01

Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC), an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine’s psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA), and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine. PMID:29073221

Distinct retrosplenial cortex cell populations and their spike dynamics during ketamine-induced unconscious state.

PubMed

Fox, Grace E; Li, Meng; Zhao, Fang; Tsien, Joe Z

2017-01-01

Ketamine is known to induce psychotic-like symptoms, including delirium and visual hallucinations. It also causes neuronal damage and cell death in the retrosplenial cortex (RSC), an area that is thought to be a part of high visual cortical pathways and at least partially responsible for ketamine's psychotomimetic activities. However, the basic physiological properties of RSC cells as well as their response to ketamine in vivo remained largely unexplored. Here, we combine a computational method, the Inter-Spike Interval Classification Analysis (ISICA), and in vivo recordings to uncover and profile excitatory cell subtypes within layers 2&3 and 5&6 of the RSC in mice within both conscious, sleep, and ketamine-induced unconscious states. We demonstrate two distinct excitatory principal cell sub-populations, namely, high-bursting excitatory principal cells and low-bursting excitatory principal cells, within layers 2&3, and show that this classification is robust over the conscious states, namely quiet awake, and natural unconscious sleep periods. Similarly, we provide evidence of high-bursting and low-bursting excitatory principal cell sub-populations within layers 5&6 that remained distinct during quiet awake and sleep states. We further examined how these subtypes are dynamically altered by ketamine. During ketamine-induced unconscious state, these distinct excitatory principal cell subtypes in both layer 2&3 and layer 5&6 exhibited distinct dynamics. We also uncovered different dynamics of local field potential under various brain states in layer 2&3 and layer 5&6. Interestingly, ketamine administration induced high gamma oscillations in layer 2&3 of the RSC, but not layer 5&6. Our results show that excitatory principal cells within RSC layers 2&3 and 5&6 contain multiple physiologically distinct sub-populations, and they are differentially affected by ketamine.

The Effective High School Principal: Lessons from an Experienced Practitioner.

ERIC Educational Resources Information Center

DiCicco, James M.

The success of high schools depends on the principals. High school principals should concentrate on their schools, use their assistants efficiently, and inspire school pride. According to previous research, the major elements of effective schools include high expectations for practitioners and students, parent involvement, administrative…

The Principal: Leadership for the Effective and Productive School.

ERIC Educational Resources Information Center

Bookbinder, Robert M.

This book synthesizes research findings on principal effectiveness, viewing the principal as a key factor in ensuring school effectiveness and productivity. Methodology includes an extensive literature review, participation and observation grounded in theory, and pragmatic responses to conditions and issues. Chapter 1 presents an overview of…

What Matters to Principals When they Evaluate Teachers? Evidence from Cyprus

ERIC Educational Resources Information Center

Orphanos, Stelios

2014-01-01

Teacher evaluation conducted by school principals is a common worldwide practice. However, there are many reservations about principals' ability to evaluate teachers reliably. Reservations appearing in the literature include inflated ratings, minimal discrimination of teacher quality, and evaluations influenced by factors irrelevant to teacher…

Superintendents' Perceptions of the Principal Shortage

ERIC Educational Resources Information Center

Pijanowski, John C.; Hewitt, Paul M.; Brady, Kevin P.

2009-01-01

The research literature on the principal shortage is inconsistent regarding the actual scope of the shortage and a clear articulation of factors contributing to the successful recruitment and retention of today's school leaders. Often, critical data related to the principal shortage are ignored, including the number of younger principals…

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

The Extent to Which Principals' Leadership and Decision-Making Processes Exerts Influence on the Operations of Inclusion Classrooms Including Students with Autism Spectrum Disorder at the Elementary School Level

ERIC Educational Resources Information Center

Bermani, Michelle Ines

2017-01-01

In this quantitative and qualitative mixed study, the researcher focused on a range of factors that drive principals' decision making and examined the variables that affect principals' decision-making. The study assessed the extent to which principals' leadership and decision-making processes exert influence on the operations of inclusion…

SandiaMRCR

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

2012-01-05

SandiaMCR was developed to identify pure components and their concentrations from spectral data. This software efficiently implements the multivariate calibration regression alternating least squares (MCR-ALS), principal component analysis (PCA), and singular value decomposition (SVD). Version 3.37 also includes the PARAFAC-ALS Tucker-1 (for trilinear analysis) algorithms. The alternating least squares methods can be used to determine the composition without or with incomplete prior information on the constituents and their concentrations. It allows the specification of numerous preprocessing, initialization and data selection and compression options for the efficient processing of large data sets. The software includes numerous options including the definition ofmore » equality and non-negativety constraints to realistically restrict the solution set, various normalization or weighting options based on the statistics of the data, several initialization choices and data compression. The software has been designed to provide a practicing spectroscopist the tools required to routinely analysis data in a reasonable time and without requiring expert intervention.« less

Minia, Egypt: Principal Component Analysis

PubMed

Abdelrehim, Marwa G; Mahfouz, Eman M; Ewis, Ashraf A; Seedhom, Amany E; Afifi, Hassan M; Shebl, Fatma M

2018-02-26

Background: Pancreatic cancer (PC) is a serious and rapidly progressing malignancy. Identifying risk factors including dietary elements is important to develop preventive strategies. This study focused on possible links between diet and PC. Methods: We conducted a case-control study including all PC patients diagnosed at Minia Cancer Center and controls from general population from June 2014 to December 2015. Dietary data were collected directly through personal interviews. Principal component analysis (PCA) was performed to identify dietary groups. The data were analyzed using crude odds ratios (ORs) and multivariable logistic regression with adjusted ORs and 95% confidence intervals (CIs). Results: A total of 75 cases and 149 controls were included in the study. PCA identified six dietary groups, labeled as cereals and grains, vegetables, proteins, dairy products, fruits, and sugars. Bivariate analysis showed that consumption of vegetables, fruits, sugars, and total energy intake were associated with change in PC risk. In multivariable-adjusted models comparing highest versus lowest levels of intake, we observed significant lower odds of PC in association with vegetable intake (OR 0.24; 95% CI, 0.07-0.85, P=0.012) and a higher likelihood with the total energy intake (OR 9.88; 95% CI, 2.56-38.09, P<0.0001). There was also a suggested link between high fruit consumption and reduced odds of PC. Conclusions: The study supports the association between dietary factors and the odds of PC development in Egypt. It was found that higher energy intake is associated with an increase in likelihood of PC, while increased vegetable consumption is associated with a lower odds ratio. Creative Commons Attribution License

A New Tool for Nutrition App Quality Evaluation (AQEL): Development, Validation, and Reliability Testing

PubMed Central

Huang, Wenhao; Chapman-Novakofski, Karen M

2017-01-01

Background The extensive availability and increasing use of mobile apps for nutrition-based health interventions makes evaluation of the quality of these apps crucial for integration of apps into nutritional counseling. Objective The goal of this research was the development, validation, and reliability testing of the app quality evaluation (AQEL) tool, an instrument for evaluating apps’ educational quality and technical functionality. Methods Items for evaluating app quality were adapted from website evaluations, with additional items added to evaluate the specific characteristics of apps, resulting in 79 initial items. Expert panels of nutrition and technology professionals and app users reviewed items for face and content validation. After recommended revisions, nutrition experts completed a second AQEL review to ensure clarity. On the basis of 150 sets of responses using the revised AQEL, principal component analysis was completed, reducing AQEL into 5 factors that underwent reliability testing, including internal consistency, split-half reliability, test-retest reliability, and interrater reliability (IRR). Two additional modifiable constructs for evaluating apps based on the age and needs of the target audience as selected by the evaluator were also tested for construct reliability. IRR testing using intraclass correlations (ICC) with all 7 constructs was conducted, with 15 dietitians evaluating one app. Results Development and validation resulted in the 51-item AQEL. These were reduced to 25 items in 5 factors after principal component analysis, plus 9 modifiable items in two constructs that were not included in principal component analysis. Internal consistency and split-half reliability of the following constructs derived from principal components analysis was good (Cronbach alpha >.80, Spearman-Brown coefficient >.80): behavior change potential, support of knowledge acquisition, app function, and skill development. App purpose split half-reliability was .65. Test-retest reliability showed no significant change over time (P>.05) for all but skill development (P=.001). Construct reliability was good for items assessing age appropriateness of apps for children, teens, and a general audience. In addition, construct reliability was acceptable for assessing app appropriateness for various target audiences (Cronbach alpha >.70). For the 5 main factors, ICC (1,k) was >.80, with a P value of <.05. When 15 nutrition professionals evaluated one app, ICC (2,15) was .98, with a P value of <.001 for all 7 constructs when the modifiable items were specified for adults seeking weight loss support. Conclusions Our preliminary effort shows that AQEL is a valid, reliable instrument for evaluating nutrition apps’ qualities for clinical interventions by nutrition clinicians, educators, and researchers. Further efforts in validating AQEL in various contexts are needed. PMID:29079554

An Exploratory Analysis of the Longitudinal Impact of Principal Change on Elementary School Achievement

ERIC Educational Resources Information Center

Hochbein, Craig; Cunningham, Brittany C.

2013-01-01

Recent reform initiatives, such as the Title I School Improvement Grants and Race to the Top, recommended a principal change to jump-start school turnaround. Yet, few educational researchers have examined principal change as way to improve schools in a state of systematic reform; furthermore, no large-scale quantitative study has determined the…

A Feel for the Game--A Bourdieuian Analysis of Principal Leadership: A Study of Queensland Secondary School Principals

ERIC Educational Resources Information Center

Addison, Bruce

2009-01-01

Educational leadership discourse has for sometime been the major intellectual pillar of what was once known as the field of educational administration. An examination of the postgraduate coursework programmes available to aspiring principal leaders at every Australian university supports such a contention. While this discourse does shed light on…

What Are the Different Types of Principals across the United States? A Latent Class Analysis of Principal Perception of Leadership

ERIC Educational Resources Information Center

Urick, Angela; Bowers, Alex J.

2014-01-01

Purpose: Effective styles of principal leadership can help address multiple issues in struggling schools, such as low student achievement and high rates of teacher attrition. Although the literature has nominated certain "idealized" leadership styles as being more or less effective, such as transformational, instructional, and shared…

Principals' Conceptions of Instructional Leadership and Their Informal Social Networks: An Exploration of the Mechanisms of the Mesolevel

ERIC Educational Resources Information Center

Rigby, Jessica G.

2016-01-01

First-year principals encounter multiple messages about what it means to be instructional leaders; this may matter for how they enact instructional leadership. This cross-case qualitative study uses a qualitative approach of social network analysis to uncover the mechanisms through which first-year principals encountered particular beliefs about…

Holding the Reins of the Professional Learning Community: Eight Themes from Research on Principals' Perceptions of Professional Learning Communities

ERIC Educational Resources Information Center

Cranston, Jerome

2009-01-01

Using a naturalistic inquiry approach and thematic analysis, this paper outlines the findings of a research study that examined 12 Manitoba principals' conceptions of professional learning communities. The study found that these principals consider the development of professional learning communities to be a normative imperative within the…

The School Makes a Difference: Analysis of Teacher Perceptions of Their Principal and School Climate.

ERIC Educational Resources Information Center

Watson, Pat; And Others

Survey responses from over half of Oklahoma City's 2,500 teachers indicated their views of the effectiveness and leadership of the city's 94 school principals. The survey's 82 items were selected from ideas suggested in the principal effectiveness literature and from the leadership component of Oklahoma City's prinipal evaluation forms. The…

An Analysis of the Relationship of Perceived Principal Instructional Leadership Behaviors and Student Academic Achievement

ERIC Educational Resources Information Center

Schindler, Kerry Andrew

2012-01-01

The primary purpose of the present study was to determine if a relationship existed between perceived instructional leadership behaviors of high school principals and student academic achievement. A total of 124 principals and 410 teachers representing 75 high school campuses completed the School Leadership Behaviors Survey (SLBS), an instrument…

An Analysis of Principals' Ethical Decision Making Using Rest's Four Component Model of Moral Behavior.

ERIC Educational Resources Information Center

Klinker, JoAnn Franklin; Hackmann, Donald G.

High school principals confront ethical dilemmas daily. This report describes a study that examined how MetLife/NASSP secondary principals of the year made ethical decisions conforming to three dispositions from Standard 5 of the ISLLC standards and whether they could identify processes used to reach those decisions through Rest's Four Component…

A Descriptive Analysis of the Principal Workforce in Wisconsin. Summary. Issues & Answers. REL 2012-No. 135

ERIC Educational Resources Information Center

Clifford, Matthew; Condon, Chris; Greenberg, Ariela; Williams, Ryan; Gerdeman, R. Dean; Fetters, Jenni; Baker, Bruce

2012-01-01

This summary describes a study that responds to a request from the Wisconsin Department of Public Instruction for information on Wisconsin's school principal workforce population. In the study, descriptive analyses addressed two research questions: (1) How do the demographic characteristics of Wisconsin school principals compare how did these…

Analysis of the Reliability and Validity of a Mentor's Assessment for Principal Internships

ERIC Educational Resources Information Center

Koonce, Glenn L.; Kelly, Michael D.

2014-01-01

In this study, researchers analyzed the reliability and validity of the mentor's assessment for principal internships at a university in the Southeast region of the United States. The results of the study yielded how trustworthy and dependable the instrument is and the effectiveness of the instrument in the current principal preparation program.…

From Vision to Reality: Views of Primary School Principals on Inclusive Education in New South Wales, Australia

ERIC Educational Resources Information Center

Graham, Linda J.; Spandagou, Ilektra

2011-01-01

This paper discusses the findings of a research study that used semi-structured interviews to explore the views of primary school principals on inclusive education in New South Wales, Australia. Content analysis of the transcript data indicates that principals' attitudes towards inclusive education and their success in engineering inclusive…

Following the Leaders: An Analysis of Graduate Effectiveness from Five Principal Preparation Programs

ERIC Educational Resources Information Center

George W. Bush Institute, Education Reform Initiative, 2016

2016-01-01

When an effective principal is at the helm of a school, students benefit. Principals play a critical role in establishing a school's climate and culture and in selecting and developing teachers, among other roles. Indeed, school leadership is second only to direct classroom teaching among school-level influences on achievement. Although there may…

A Descriptive Analysis of the Principal Workforce in Florida Schools. REL 2015-068

ERIC Educational Resources Information Center

Folsom, Jessica Sidler; Osborne-Lampkin, La'Tara; Herrington, Carolyn

2015-01-01

This report describes the results of a REL Southeast study using the Florida Department of Education staffing database to describe the demographic make-up, Florida Educator Certificate coverages, career paths from 2001/02 to 2011/12, and evaluation ratings of Florida's educational leaders (i.e., assistant principals and principals) in the 2011/12…

A Content Analysis of Themes That Emerge from School Principals' Web2.0 Conversations

ERIC Educational Resources Information Center

Manning, Rory

2011-01-01

The purpose of this qualitative study was to analyze the self initiated conversations held by school principals on web2.o platforms, such as blogs, through the lens of current leadership standards. The online writings of thirteen school principals were analyzed using grounded theory techniques (Strauss and Corbin, 1998) to elucidate emerging…

The Effects of Professional Development Activities on Principals' Perceived Instructional Leadership Practices: Multi-Country Data Analysis Using TALIS 2013

ERIC Educational Resources Information Center

Gumus, Emine; Bellibas, Mehmet Sukru

2016-01-01

The purpose of this study was to investigate the extent to which professional development predicts principals' instructional leadership in order to identify whether a relationship exists between the duration of principals' participation in distinct professional development activities and their perceived practice of instructional leadership while…

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.

Resume and analysis of NACA lateral control research

NASA Technical Reports Server (NTRS)

Weick, Fred E; Jones, Robert T

1937-01-01

An analysis of the principal results of recent NACA lateral control research is made by utilizing the experience and progress gained during the course of the investigation. Two things are considered of primary importance in judging the effectiveness of different control devices: the (calculated) banking and yawing motion of a typical small airplane caused by a deflection of the control, and the stick force required to produce this deflection. The report includes a table in which a number of different lateral control devices are compared on these bases.

[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.

Exploring the Factor Structure of Neurocognitive Measures in Older Individuals

PubMed Central

Santos, Nadine Correia; Costa, Patrício Soares; Amorim, Liliana; Moreira, Pedro Silva; Cunha, Pedro; Cotter, Jorge; Sousa, Nuno

2015-01-01

Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the “best fit” model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate. PMID:25880732

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.

13 CFR 115.36 - Indemnity settlements and reinstatement of Principal.

Code of Federal Regulations, 2010 CFR

2010-01-01

... for SBA's consideration must include current financial information, including financial statements... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Indemnity settlements and reinstatement of Principal. 115.36 Section 115.36 Business Credit and Assistance SMALL BUSINESS ADMINISTRATION...

Perceptions of the School Self-Evaluation Process: The Case of Abu Dhabi

ERIC Educational Resources Information Center

Blaik Hourani, Rida; Litz, David

2016-01-01

The Abu Dhabi Education Council (ADEC) has initiated educational change and school improvements. As part of the school reform agenda, ADEC has introduced school self-evaluation-Irtiqaa (SSE-Irtiqaa). This research probes the effectiveness of school administrators (SAs), including principals, vice principals, academic principals, and heads of…

Principal Appraisals Get a Remake

ERIC Educational Resources Information Center

Zubrzycki, Jaclyn

2013-01-01

A growing number of school districts--including large ones like those in Chicago, Dallas, Los Angeles, and Hawaii--have become recent converts to new principal-evaluation systems that tie school leaders' appraisals to student test scores. As of this school year, student achievement accounts for 40 percent to 50 percent of principals' evaluations…

Principals: Instructional Leaders to Support All Students

ERIC Educational Resources Information Center

Kroener, Julienne Patricia

2017-01-01

As principals work towards meeting the educational needs of all students, including students with disabilities, in an inclusive environment it is essential to understand the challenges that may occur throughout this process. This study examined the barriers that exist for principals as instructional leaders when ensuring equitable education for…

Identifying and Addressing Themes of Job Dissatisfaction for Secondary Principals

ERIC Educational Resources Information Center

De Jong, David; Grundmeyer, Trent; Yankey, Julie

2017-01-01

Secondary principals serve in important roles that are complex, high-stress, and include demanding job responsibilities. Key stakeholders such as superintendents, school board members, and legislators must understand the challenges facing secondary principals in order to address the current themes of job dissatisfaction. Using new survey data…

Approximating lens power.

PubMed

Kaye, Stephen B

2009-04-01

To provide a scalar measure of refractive error, based on geometric lens power through principal, orthogonal and oblique meridians, that is not limited to the paraxial and sag height approximations. A function is derived to model sections through the principal meridian of a lens, followed by rotation of the section through orthogonal and oblique meridians. Average focal length is determined using the definition for the average of a function. Average univariate power in the principal meridian (including spherical aberration), can be computed from the average of a function over the angle of incidence as determined by the parameters of the given lens, or adequately computed from an integrated series function. Average power through orthogonal and oblique meridians, can be similarly determined using the derived formulae. The widely used computation for measuring refractive error, the spherical equivalent, introduces non-constant approximations, leading to a systematic bias. The equations proposed provide a good univariate representation of average lens power and are not subject to a systematic bias. They are particularly useful for the analysis of aggregate data, correlating with biological treatment variables and for developing analyses, which require a scalar equivalent representation of refractive power.

Study of atmospheric dynamics and pollution in the coastal area of English Channel using clustering technique

NASA Astrophysics Data System (ADS)

Sokolov, Anton; Dmitriev, Egor; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmenten, Marc

2016-04-01

The problem of atmospheric contamination by principal air pollutants was considered in the industrialized coastal region of English Channel in Dunkirk influenced by north European metropolitan areas. MESO-NH nested models were used for the simulation of the local atmospheric dynamics and the online calculation of Lagrangian backward trajectories with 15-minute temporal resolution and the horizontal resolution down to 500 m. The one-month mesoscale numerical simulation was coupled with local pollution measurements of volatile organic components, particulate matter, ozone, sulphur dioxide and nitrogen oxides. Principal atmospheric pathways were determined by clustering technique applied to backward trajectories simulated. Six clusters were obtained which describe local atmospheric dynamics, four winds blowing through the English Channel, one coming from the south, and the biggest cluster with small wind speeds. This last cluster includes mostly sea breeze events. The analysis of meteorological data and pollution measurements allows relating the principal atmospheric pathways with local air contamination events. It was shown that contamination events are mostly connected with a channelling of pollution from local sources and low-turbulent states of the local atmosphere.

Corrected confidence bands for functional data using principal components.

PubMed

Goldsmith, J; Greven, S; Crainiceanu, C

2013-03-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. Copyright © 2013, The International Biometric Society.

Corrected Confidence Bands for Functional Data Using Principal Components

PubMed Central

Goldsmith, J.; Greven, S.; Crainiceanu, C.

2014-01-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. PMID:23003003

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.

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.

Blindness and Visual Impairment Profile and Rapid Assessment of Avoidable Blindness in South East Asia: Analysis of New Data. 2017 APAO Holmes Lecture.

PubMed

Das, Taraprasad

2018-03-13

The International Agency for Prevention of Blindness (IAPB) South East Asia region (SEAR) that consists of 11 countries contains 26% of the world's population (1,761,000,000). In this region 12 million are blind and 78.5 million are visually impaired. This amounts to 30% of global blindness and 32% of global visual impairment. Rapid assessment of avoidable blindness (RAAB) survey analysis. RAAB, either a repeat or a first time survey, was completed in 8 countries in this decade (2010 onwards). These include Bangladesh, Bhutan, India, Indonesia, Maldives, Sri Lanka, Thailand, and Timor Leste. Cataract is the principal cause of blindness and severe visual impairment in all countries. Refractive error is the principal cause of moderate visual impairment in 4 countries: Bangladesh, India, Maldives, and Sri Lanka; cataract continues to be the principal cause of moderate visual impairment in 4 other countries: Bhutan, Indonesia, Thailand, and Timor Leste. Outcome of cataract surgery is suboptimal in the Maldives and Timor Leste. Rigorous focus is necessary to improve cataract surgery outcomes and correction of refractive error without neglecting the quality of care. At the same time allowances must be made for care of the emerging causes of visual impairment and blindness such as glaucoma and posterior segment disorders, particularly diabetic retinopathy. Copyright 2018 Asia-Pacific Academy of Ophthalmology.

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

PubMed

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

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

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

PubMed Central

Ahmadi, Mehdi; Shahlaei, Mohsen

2015-01-01

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

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.

Regionalization of precipitation characteristics in Iran's Lake Urmia basin

NASA Astrophysics Data System (ADS)

Fazel, Nasim; Berndtsson, Ronny; Uvo, Cintia Bertacchi; Madani, Kaveh; Kløve, Bjørn

2018-04-01

Lake Urmia in northwest Iran, once one of the largest hypersaline lakes in the world, has shrunk by almost 90% in area and 80% in volume during the last four decades. To improve the understanding of regional differences in water availability throughout the region and to refine the existing information on precipitation variability, this study investigated the spatial pattern of precipitation for the Lake Urmia basin. Daily rainfall time series from 122 precipitation stations with different record lengths were used to extract 15 statistical descriptors comprising 25th percentile, 75th percentile, and coefficient of variation for annual and seasonal total precipitation. Principal component analysis in association with cluster analysis identified three main homogeneous precipitation groups in the lake basin. The first sub-region (group 1) includes stations located in the center and southeast; the second sub-region (group 2) covers mostly northern and northeastern part of the basin, and the third sub-region (group 3) covers the western and southern edges of the basin. Results of principal component (PC) and clustering analyses showed that seasonal precipitation variation is the most important feature controlling the spatial pattern of precipitation in the lake basin. The 25th and 75th percentiles of winter and autumn are the most important variables controlling the spatial pattern of the first rotated principal component explaining about 32% of the total variance. Summer and spring precipitation variations are the most important variables in the second and third rotated principal components, respectively. Seasonal variation in precipitation amount and seasonality are explained by topography and influenced by the lake and westerly winds that are related to the strength of the North Atlantic Oscillation. Despite using incomplete time series with different lengths, the identified sub-regions are physically meaningful.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis.

PubMed

Fernández-Arjona, María Del Mar; Grondona, Jesús M; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor.

Microglia Morphological Categorization in a Rat Model of Neuroinflammation by Hierarchical Cluster and Principal Components Analysis

PubMed Central

Fernández-Arjona, María del Mar; Grondona, Jesús M.; Granados-Durán, Pablo; Fernández-Llebrez, Pedro; López-Ávalos, María D.

2017-01-01

It is known that microglia morphology and function are closely related, but only few studies have objectively described different morphological subtypes. To address this issue, morphological parameters of microglial cells were analyzed in a rat model of aseptic neuroinflammation. After the injection of a single dose of the enzyme neuraminidase (NA) within the lateral ventricle (LV) an acute inflammatory process occurs. Sections from NA-injected animals and sham controls were immunolabeled with the microglial marker IBA1, which highlights ramifications and features of the cell shape. Using images obtained by section scanning, individual microglial cells were sampled from various regions (septofimbrial nucleus, hippocampus and hypothalamus) at different times post-injection (2, 4 and 12 h). Each cell yielded a set of 15 morphological parameters by means of image analysis software. Five initial parameters (including fractal measures) were statistically different in cells from NA-injected rats (most of them IL-1β positive, i.e., M1-state) compared to those from control animals (none of them IL-1β positive, i.e., surveillant state). However, additional multimodal parameters were revealed more suitable for hierarchical cluster analysis (HCA). This method pointed out the classification of microglia population in four clusters. Furthermore, a linear discriminant analysis (LDA) suggested three specific parameters to objectively classify any microglia by a decision tree. In addition, a principal components analysis (PCA) revealed two extra valuable variables that allowed to further classifying microglia in a total of eight sub-clusters or types. The spatio-temporal distribution of these different morphotypes in our rat inflammation model allowed to relate specific morphotypes with microglial activation status and brain location. An objective method for microglia classification based on morphological parameters is proposed. Main points Microglia undergo a quantifiable morphological change upon neuraminidase induced inflammation.Hierarchical cluster and principal components analysis allow morphological classification of microglia.Brain location of microglia is a relevant factor. PMID:28848398

Research of seafloor topographic analyses for a staged mineral exploration

NASA Astrophysics Data System (ADS)

Ikeda, M.; Kadoshima, K.; Koizumi, Y.; Yamakawa, T.; Asakawa, E.; Sumi, T.; Kose, M.

2016-12-01

J-MARES (Research and Development Partnership for Next Generation Technology of Marine Resources Survey, JAPAN) has been designing a low-cost and high-efficiency exploration system for seafloor hydrothermal massive sulfide (SMS) deposits in "Cross-ministerial Strategic Innovation Promotion Program (SIP)" granted by the Cabinet Office, Government of Japan since 2014. We proposed the multi-stage approach, which is designed from the regional scaled to the detail scaled survey stages through semi-detail scaled, focusing a prospective area by seafloor topographic analyses. We applied this method to the area of more than 100km x 100km around Okinawa Trough, including some well-known mineralized deposits. In the regional scale survey, we assume survey areas are more than 100 km x 100km. Then the spatial resolution of topography data should be bigger than 100m. The 500 m resolution data which is interpolated into 250 m resolution was used for extracting depression and performing principal component analysis (PCA) by the wavelength obtained from frequency analysis. As the result, we have successfully extracted the areas having the topographic features quite similar to well-known mineralized deposits. In the semi-local survey stage, we use the topography data obtained by bathymetric survey using multi-narrow beam echo-sounder. The 30m-resolution data was used for extracting depression, relative-large mounds, hills, lineaments as fault, and also for performing frequency analysis. As the result, wavelength as principal component constituting in the target area was extracted by PCA of wavelength obtained from frequency analysis. Therefore, color image was composited by using the second principal component (PC2) to the forth principal component (PC4) in which the continuity of specific wavelength was observed, and consistent with extracted lineaments. In addition, well-known mineralized deposits were discriminated in the same clusters by using clustering from PC2 to PC4.We applied the results described above to a new area, and successfully extract the quite similar area in vicinity to one of the well-known mineralized deposits. So we are going to verify the extracted areas by using geophysical methods, such as vertical cable seismic and time-domain EM survey, developed in this SIP project.

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…

"Vergara v. State of California": A Political Analysis and Implications for Principal Practice

ERIC Educational Resources Information Center

Tabron, Lolita A.; Irby, Beverly J.

2015-01-01

This political analysis uses the Vergara case as an example of how principals can be dynamic leaders who are well prepared for and engaged in their political terrain. This will be important to decrease judicial dependency and legislative interference to better ensure that reform begins with those closest to the problem.

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…

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.

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.

Genetic Classification of Populations Using Supervised Learning

PubMed Central

Bridges, Michael; Heron, Elizabeth A.; O'Dushlaine, Colm; Segurado, Ricardo; Morris, Derek; Corvin, Aiden; Gill, Michael; Pinto, Carlos

2011-01-01

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case–control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available. In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies. PMID:21589856

Expansion of the wilderness values scale with three sub-scales: Personal maintenance, expression and learning, and societal maintenance

Treesearch

Rudy M. Schuster; Ken Cordell; Gary T. Green

2007-01-01

The purpose of this research was to expand the wilderness value scale administered in the 1994 and 2000 versions of the National Survey on Recreation and the Environment using questions included in the 2003 NSRE. A data set of 1,900 cases was randomly split in half. Validity of the additional questions was tested using principal component analysis, a confirmatory...

PuffinPlot: A versatile, user-friendly program for paleomagnetic analysis

NASA Astrophysics Data System (ADS)

Lurcock, P. C.; Wilson, G. S.

2012-06-01

PuffinPlot is a user-friendly desktop application for analysis of paleomagnetic data, offering a unique combination of features. It runs on several operating systems, including Windows, Mac OS X, and Linux; supports both discrete and long core data; and facilitates analysis of very weakly magnetic samples. As well as interactive graphical operation, PuffinPlot offers batch analysis for large volumes of data, and a Python scripting interface for programmatic control of its features. Available data displays include demagnetization/intensity, Zijderveld, equal-area (for sample, site, and suite level demagnetization data, and for magnetic susceptibility anisotropy data), a demagnetization data table, and a natural remanent magnetization intensity histogram. Analysis types include principal component analysis, Fisherian statistics, and great-circle path intersections. The results of calculations can be exported as CSV (comma-separated value) files; graphs can be printed, and can also be saved as publication-quality vector files in SVG or PDF format. PuffinPlot is free, and the program, user manual, and fully documented source code may be downloaded from http://code.google.com/p/puffinplot/.

Principal's Organizational Activities: An Analysis of the Differences between Actual and Ideal Time Expenditures as a Function of Career Stage

ERIC Educational Resources Information Center

Kellogg, Sharon

2005-01-01

This study investigated the gap between elementary school principals' rankings on current and ideal allocations of time for staff, student, managerial, curriculum, strategic, fiscal, and community activities as a function of career stage. Most principals surveyed preferred to spend more time on curricular and strategic activities than they were…

Influence Actions of School Principals in Hong Kong, Mainland China and the United States: A Cross-Cultural Perspective

ERIC Educational Resources Information Center

Pisapia, John; Pang, Nicholas Sun-Keung

2013-01-01

The aim of the study was to determine if Chinese school principals use influence actions differently from US principals. The concepts framing this study are leader influence actions, societal and local culture. The analysis was conducted with data from two independent studies conducted in each country using the strategic leadership questionnaire…

Concerns, Use of Time, and the Intersections of Leadership: Case Study of Two Charter School Principals

ERIC Educational Resources Information Center

Bickmore, Dana L.; Dowell, Margaret-Mary Sulentic

2011-01-01

As part of a multiple case study of charter school leadership, the researchers in this study examined 2 principals' priorities and practices through their expressed concerns and use of time. Through an embedded case design and analysis, 6 themes surfaced from the principal interviews that occurred over the course of a school year--accountability,…

Behaviour of Turkish Elementary School Principals in the Change Process: An Analysis of the Perceptions of Both Teachers and School Principals

ERIC Educational Resources Information Center

Gokce, Feyyat

2009-01-01

Technological and economic changes affect societies, and consequently bring about change in education. Elementary school principals in Turkey spend considerable time and effort managing change in their schools. This study contributes to the better management of Turkish elementary schools by determining the behavior of elementary school principals…

Examining School Improvement through the Lens of Principal and Teacher Flow of Influence in High-Achieving, High-Poverty Schools

ERIC Educational Resources Information Center

Murley, Lisa Downing; Keedy, John L.; Welsh, John F.

2008-01-01

Based on the social exchange theory of Homans, Gouldner, and Malinowski, this sociocultural analysis of three elementary schools focused on principal-teacher and teacher-teacher exchanges of instructional influence. Two questions were asked: (a) In what ways, if any, do principals and teachers in high-achieving, high-poverty schools exchange…

Kentucky Principal Perceptions of the State's New Teacher Evaluation System: A Survey Analysis

ERIC Educational Resources Information Center

Dodson, Richard L.

2015-01-01

This research examines how public school principals in Kentucky perceive their new teacher evaluation system and the proficiency exam they must take and pass in order to evaluate their staff. An online survey was developed and 308 out of an estimated 1,100 working school principals across Kentucky responded, yielding a response rate of 28%.…

Analysis of Principals' Managerial Competencies for Effective Management of School Resources in Secondary Schools in Anambra State, Nigeria

ERIC Educational Resources Information Center

Victor, Akinfolarin Akinwale

2017-01-01

This study analyses principals' managerial competencies for effective management of school resources in secondary schools in Anambra State. The study was conducted in Anambra State. The study population comprised 257 principals in public secondary schools in the State. The study adopted a descriptive survey design. A 24 items researcher developed…

Assessing the Measurement Properties of the Principal Instructional Management Rating Scale: A Meta-Analysis of Reliability Studies

ERIC Educational Resources Information Center

Hallinger, Phillip; Wang, Wen-Chung; Chen, Chia-Wen

2013-01-01

Background: In a recent article, Hallinger (2011b) reviewed 135 empirical studies that had employed the Principal Instructional Management Rating Scale (PIMRS) over the prior three decades. The author concluded that the PIMRS appeared to have attained a consistent record of yielding reliable and valid data on principal instructional leadership.…

Principal Cluster Axes: A Projection Pursuit Index for the Preservation of Cluster Structures in the Presence of Data Reduction

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.; Henson, Robert

2012-01-01

A measure of "clusterability" serves as the basis of a new methodology designed to preserve cluster structure in a reduced dimensional space. Similar to principal component analysis, which finds the direction of maximal variance in multivariate space, principal cluster axes find the direction of maximum clusterability in multivariate space.…

Improving Hispanic students' performance on science standardized tests: Successful practices from four elementary campuses

NASA Astrophysics Data System (ADS)

Gonzalez, Yvonne Lynne

This qualitative, descriptive multiple case study took place in a Southwest Texas city bordering Mexico. The study examined specific resources and practices used in four different exemplary-rated elementary school campuses, with standardized test data reflecting 93% or more of their 5th-grade Hispanic student population passing the state mandated standardized science test. The sample for this study included one principal, one assistant principal, and three 5th-grade teachers from each campus. In total, the sample participants consisted of four principals, four assistant principals, and 12 5th-grade teachers. Data collection involved conducting in-depth, semi-structured interviews guided by five literature-based, researcher-generated questions. Fifth grade teachers and administrators reflected and reported upon their pedagogy for best practices in helping Hispanic students achieve success. Analysis of the data revealed eight themes: (a) successful schools have committed teachers, an environment conducive to learning, and incorporate best practices that work for all students; (b) curriculum alignment is very important; (c) teachers have access to a variety of resources; (d) teacher collaboration and planning is very important; (e) science camps, science reviews, and hands-on centers are effective in preparing students for the standardized test; (f) the most effective instructional practices include high emphasis on vocabulary, hands-on and differentiated instruction, and the 5E Model; (g) teachers see value in self-contained, dual-language classes; and (h) professional development and performance feedback are important to educators. The results of this study provide educational leaders with specific science instructional resources, practices, and interventions proven effective for the 5 th-grade Hispanic student population in passing the science state standardized test.

Cloning Their Own: Aspirant Principals and the School-Based Selection Game

ERIC Educational Resources Information Center

Gronn, Peter; Lacey, Kathy

2006-01-01

In this article, we report data from two projects concerned with the aspirant principals' perspectives about school principal recruitment in three Australian states. In particular, we consider what our informants perceive as factors that inhibit the realisation of their aspirations. These factors include aspects of the operation of school-based…

School Principals' Perceptions of and Expectations for Physical Education

ERIC Educational Resources Information Center

George, Meredith L.; Curtner-Smith, Matthew D.

2017-01-01

The purposes of this study were to (a) examine 19 school principals' perceptions of and expectations for physical education (PE) and (b) describe the factors influencing school principals' perceptions of and expectations for PE. We collected data using an electronic survey that included questions on (a) the goals of PE, (b) pedagogies and…

Are Teacher and Principal Candidates Prepared to Address Student Cyberbullying?

ERIC Educational Resources Information Center

Styron, Ronald A., Jr.; Bonner, Jessica L.; Styron, Jennifer L.; Bridgeforth, James; Martin, Cecelia

2016-01-01

The purpose of this study was to examine the preparation of teacher and principal candidates to address problems created in K-12 settings as a result of cyberbullying. Participants included teacher and principal preparation students. Findings indicated that respondents were familiar with the most common forms of cyberbullying and its impact on…

Planning for Principal Succession: A Conceptual Framework for Research and Practice

ERIC Educational Resources Information Center

Russell, Jennifer Lin; Sabina, Lou L.

2014-01-01

Many school districts struggle to recruit sufficient high-quality principals for their schools. A variety of conditions contribute to this challenge, including the retirement of the baby boom cohort and diminishing interest in administrative careers due to the expanded responsibilities of school principals. In response, districts enact a range of…

"Mujeres" in the Principal's Office: Latina School Leaders

ERIC Educational Resources Information Center

Méndez-Morse, Sylvia; Murakami, Elizabeth T.; Byrne-Jiménez, Mónica; Hernandez, Frank

2015-01-01

This article is based on a national survey of Latina/o principals and assistant principals conducted by the National Latina/o Leadership Project and focuses on the women participants. Included is a description of Latinas' leadership experiences, their career paths, and the influence of racial/ethnic identity on their leadership practice. The…

Characteristics and Career Paths of North Carolina School Leaders. REL 2017-230

ERIC Educational Resources Information Center

Osborne-Lampkin, La'Tara; Folsom, Jessica Sidler

2017-01-01

Researchers have linked positive student outcomes, including student achievement, to high-quality school leadership. Due in part to this research, the North Carolina Department of Public Instruction and the North Carolina Principals and Assistant Principals' Association are interested in increasing the number of high-quality principals in North…

State Efforts to Strengthen School Leadership: Insights from CCSSO Action Groups

ERIC Educational Resources Information Center

Riley, Derek L.; Meredith, Julie

2017-01-01

Many states across the nation are working to improve school leadership, some on a substantial scale. Several factors encourage state-level work focused on principals, including: research evidence of principal effects on student learning, flexibility in the Every Student Succeeds Act (ESSA), new national professional standards for principals,…

Increasing Assistant Principals' Capacity for Success Based on the New Principal Evaluation Instrument

ERIC Educational Resources Information Center

Hager, Rhonda Keever

2012-01-01

The importance of leadership is critical with current accountability for student performance. The increased accountability for school leaders has caused a change in leadership roles to incorporate collaboration and shared leadership. Assistant principals are included in the concept of distributive leadership. A review of the literature shows…

Looking to the 21st Century--Principals with Vision Needed To Make Schools Exciting Places of Learning.

ERIC Educational Resources Information Center

Glines, Don E.

1987-01-01

If schools and their programs are to prepare youth for tommorrow's world, principals today must be "dreamers of the dreams," advises this educator. He provides a rationale for his imperatives, followed by specific steps that principals should take. Includes three pages of references. (Author/MD)

Fundamental Features of Fostering Teacher Collective Efficacy: Principals' Attitudes, Behaviors, and Practices

ERIC Educational Resources Information Center

Nordick, Shelley

2017-01-01

The purpose of this study was to explore the attitudes, practices, and behaviors of principals who foster teacher collective efficacy. The research questions were developed based upon Bandura's social cognitive theory to include (a) what are the "attitudes" held by principals that influence TCE; (b) what are the "behaviors"…

Use of Accountability Indicators to Evaluate Elementary School Principal Performance

ERIC Educational Resources Information Center

Byun-Kitayama, Chiae

2012-01-01

Recently, the federal government has pressured states to add student growth data as a part of the evaluation system. State legislatures in New York and Colorado have passed legislation to revamp teacher and principal evaluation to include student growth data. Numerous researchers acknowledged the critical impact of school principals on student…

The Effects of Principals' Loneliness in the Workplace on Their Self-Performance

ERIC Educational Resources Information Center

Yengin Sarpkaya, Pinar

2014-01-01

The main purpose of this research is to analyse the effect of the loneliness status of principals' working at the schools in Aydin, Turkey to their individual performance. The partcipants included 286 principals, working in Aydin city center, district or villages. "Loneliness at Work Scale" (LAWS) and "Employee Performance…

Results from an Empirical Study of School Principals' Decisions about Disclosure of HIV Status

ERIC Educational Resources Information Center

Chenneville, Tiffany

2007-01-01

Elementary school principals' decisions about disclosure of school age children's confidential medical information was empirically studied. Participants included a stratified sample of 339 elementary school principals from the seven largest school districts in Florida. Each participant received one of six vignettes describing a student with HIV,…

Consistency of Principals' Leadership Styles and Teachers' Perceptions in the Commonwealth of the Northern Marianas.

ERIC Educational Resources Information Center

Quitugua, Jacqueline A.

The consistency of principals' self-perceptions of their leadership styles with those of their teachers is determined in this study. Other focuses include differences between elementary and secondary teachers' perceptions of their principals' leadership styles and gender differences in such perceptions. The Leader Effectiveness and Adaptability…

Catholic School Principal Job Satisfaction: Keys to Retention and Recruitment

ERIC Educational Resources Information Center

Fraser, Jennifer; Brock, Barbara L.

2006-01-01

This article presents a study on principal retention in New South Wales, Australia. Factors in job retention included economic security, role enjoyment, and the opportunity to contribute. Disincentives to the principalship included lack of support from the employing authority, inadequate pay, isolation, growing responsibilities, difficult parents,…

17 CFR 3.44 - Temporary licensing of applicants for guaranteed introducing broker registration.

Code of Federal Regulations, 2014 CFR

2014-04-01

... fingerprints of the applicant, if a sole proprietor, and of each principal (including each branch office manager) thereof on fingerprint cards provided by the National Futures Association for that purpose. (b... any principal (including any branch office manager) thereof or for the resubmission of a fingerprint...

17 CFR 3.44 - Temporary licensing of applicants for guaranteed introducing broker registration.

Code of Federal Regulations, 2013 CFR

2013-04-01

... fingerprints of the applicant, if a sole proprietor, and of each principal (including each branch office manager) thereof on fingerprint cards provided by the National Futures Association for that purpose. (b... any principal (including any branch office manager) thereof or for the resubmission of a fingerprint...

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.

Results of the first provisional technical secretariat interlaboratory comparison test

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

Stuff, J.R.; Hoffland, L.

1995-06-01

The principal task of this laboratory in the first Provisional Technical Secretariat (PTS) Interlaboratory Comparison Test was to verify and test the extraction and preparation procedures outlined in the Recommended Operating Procedures for Sampling and Analysis in the Verification of Chemical Disarmament in addition to our laboratory extraction methods and our laboratory analysis methods. Sample preparation began on 16 May 1994 and analysis was completed on 12 June 1994. The analytical methods used included NMR ({sup 1}H and {sup 31}P) GC/AED, GC/MS (EI and methane CI), GC/IRD, HPLC/IC, HPLC/TSP/MS, MS/MS(Electrospray), and CZE.

Screening of oil sources by using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry and multivariate statistical analysis.

PubMed

Zhang, Wanfeng; Zhu, Shukui; He, Sheng; Wang, Yanxin

2015-02-06

Using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOFMS), volatile and semi-volatile organic compounds in crude oil samples from different reservoirs or regions were analyzed for the development of a molecular fingerprint database. Based on the GC×GC/TOFMS fingerprints of crude oils, principal component analysis (PCA) and cluster analysis were used to distinguish the oil sources and find biomarkers. As a supervised technique, the geological characteristics of crude oils, including thermal maturity, sedimentary environment etc., are assigned to the principal components. The results show that tri-aromatic steroid (TAS) series are the suitable marker compounds in crude oils for the oil screening, and the relative abundances of individual TAS compounds have excellent correlation with oil sources. In order to correct the effects of some other external factors except oil sources, the variables were defined as the content ratio of some target compounds and 13 parameters were proposed for the screening of oil sources. With the developed model, the crude oils were easily discriminated, and the result is in good agreement with the practical geological setting. Copyright © 2014 Elsevier B.V. All rights reserved.

A programmable laboratory testbed in support of evaluation of functional brain activation and connectivity.

PubMed

Barbour, Randall L; Graber, Harry L; Xu, Yong; Pei, Yaling; Schmitz, Christoph H; Pfeil, Douglas S; Tyagi, Anandita; Andronica, Randy; Lee, Daniel C; Barbour, San-Lian S; Nichols, J David; Pflieger, Mark E

2012-03-01

An important determinant of the value of quantitative neuroimaging studies is the reliability of the derived information, which is a function of the data collection conditions. Near infrared spectroscopy (NIRS) and electroencelphalography are independent sensing domains that are well suited to explore principal elements of the brain's response to neuroactivation, and whose integration supports development of compact, even wearable, systems suitable for use in open environments. In an effort to maximize the translatability and utility of such resources, we have established an experimental laboratory testbed that supports measures and analysis of simulated macroscopic bioelectric and hemodynamic responses of the brain. Principal elements of the testbed include 1) a programmable anthropomorphic head phantom containing a multisignal source array embedded within a matrix that approximates the background optical and bioelectric properties of the brain, 2) integrated translatable headgear that support multimodal studies, and 3) an integrated data analysis environment that supports anatomically based mapping of experiment-derived measures that are directly and not directly observable. Here, we present a description of system components and fabrication, an overview of the analysis environment, and findings from a representative study that document the ability to experimentally validate effective connectivity models based on NIRS tomography.

Gut microbiota drives the attenuation of dextran sulphate sodium-induced colitis by Huangqin decoction

PubMed Central

Ye, Juan; Cai, Xueting; Tsering, Pamo; Cheng, Xiaolan; Hu, Chunping; Zhang, Shuangquan; Cao, Peng

2017-01-01

The gut microbiota, including probiotics and pathogenic microorganisms, is involved in ulcerative colitis (UC) by regulating pathogenic microorganisms and the production of intestinal mucosal antibodies. Huangqin decoction (HQD), a traditional Chinese formula chronicled in the Shanghan lun, has been recognized as an effective drug for UC, owing to its anti-inflammatory and anti-oxidative properties. In the present study, we investigated whether HQD ameliorates dextran sulphate sodium (DSS)-induced colitis through alteration of the gut microbiota. We found that HQD significantly inhibited colitis, alleviating the loss of body weight, disease activity index, colon shortening, tissue injury, and inflammatory cytokine changes induced by DSS treatment. Principal component analysis and principal co-ordinate analysis showed an obvious difference among the groups, with increased diversity in the DSS and DSS+HQD groups. Linear discriminant analysis effect size was used to determine differences between the groups. The relative abundance of Lactococcus was higher in the DSS+HQD group than in the DSS group, whereas Desulfovibrio and Helicobacter were decreased. Furthermore, the protective effect of HQD was attenuated only in antibiotic-treated mice. In conclusion, our results suggest that HQD could ameliorate DSS-induced inflammation through alteration of the gut microbiota. PMID:28415628

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

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.

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

PubMed

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

2011-02-01

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

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.

Spatial, temporal, and health associations of eating alone: A cross-cultural analysis of young adults in urban Australia and Japan.

PubMed

Takeda, Wakako; Melby, Melissa K

2017-11-01

Eating alone is driven by social and cultural factors, not solely by individual preferences. In academic research, eating alone is often simply treated as an alternative to social, commensal eating, and little is known about the practice of eating alone itself. This study employs a cross-cultural analysis to explore social and cultural associations of eating alone. The analysis is based on 1) cultural domain data, derived from principal component analysis of freelist responses, a set of words or phrases related to the topic of eating alone; and 2) in-depth interviews with 72 young adults aged 20-40 in urban Australia and Japan. Many Australian and Japanese young adult participants associated eating alone with both pleasure and stress of being isolated from others. However, the comparison of principal components between Australian and Japanese groups and gender subgroups showed cross-cultural variations and complexity in the context of eating alone including: locations and timings of eating alone, and associations with healthy/unhealthy eating. Analyses of interviews are included to deepen understandings of cultural domains. These key associations are influenced by a range of social and cultural environments such as fast food cultures, work and life environments, and the scope of public health nutrition programs. The association between eating alone and healthy eating among young adults indicates that individualistic understandings of food intake in current public health nutrition programs are more favorable to eating alone and foster a gap between ideas of healthy eating and commensal eating as a cultural ideal. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping

PubMed Central

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-01-01

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply. PMID:27128915

A Comparative Analysis of Machine Learning with WorldView-2 Pan-Sharpened Imagery for Tea Crop Mapping.

PubMed

Chuang, Yung-Chung Matt; Shiu, Yi-Shiang

2016-04-26

Tea is an important but vulnerable economic crop in East Asia, highly impacted by climate change. This study attempts to interpret tea land use/land cover (LULC) using very high resolution WorldView-2 imagery of central Taiwan with both pixel and object-based approaches. A total of 80 variables derived from each WorldView-2 band with pan-sharpening, standardization, principal components and gray level co-occurrence matrix (GLCM) texture indices transformation, were set as the input variables. For pixel-based image analysis (PBIA), 34 variables were selected, including seven principal components, 21 GLCM texture indices and six original WorldView-2 bands. Results showed that support vector machine (SVM) had the highest tea crop classification accuracy (OA = 84.70% and KIA = 0.690), followed by random forest (RF), maximum likelihood algorithm (ML), and logistic regression analysis (LR). However, the ML classifier achieved the highest classification accuracy (OA = 96.04% and KIA = 0.887) in object-based image analysis (OBIA) using only six variables. The contribution of this study is to create a new framework for accurately identifying tea crops in a subtropical region with real-time high-resolution WorldView-2 imagery without field survey, which could further aid agriculture land management and a sustainable agricultural product supply.

Intelligent data analysis to interpret major risk factors for diabetic patients with and without ischemic stroke in a small population

PubMed Central

Gürgen, Fikret; Gürgen, Nurgül

2003-01-01

This study proposes an intelligent data analysis approach to investigate and interpret the distinctive factors of diabetes mellitus patients with and without ischemic (non-embolic type) stroke in a small population. The database consists of a total of 16 features collected from 44 diabetic patients. Features include age, gender, duration of diabetes, cholesterol, high density lipoprotein, triglyceride levels, neuropathy, nephropathy, retinopathy, peripheral vascular disease, myocardial infarction rate, glucose level, medication and blood pressure. Metric and non-metric features are distinguished. First, the mean and covariance of the data are estimated and the correlated components are observed. Second, major components are extracted by principal component analysis. Finally, as common examples of local and global classification approach, a k-nearest neighbor and a high-degree polynomial classifier such as multilayer perceptron are employed for classification with all the components and major components case. Macrovascular changes emerged as the principal distinctive factors of ischemic-stroke in diabetes mellitus. Microvascular changes were generally ineffective discriminators. Recommendations were made according to the rules of evidence-based medicine. Briefly, this case study, based on a small population, supports theories of stroke in diabetes mellitus patients and also concludes that the use of intelligent data analysis improves personalized preventive intervention. PMID:12685939

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

PubMed

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

2016-11-22

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

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

PubMed Central

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

2016-01-01

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

A Model to Explain Plant Growth Promotion Traits: A Multivariate Analysis of 2,211 Bacterial Isolates

PubMed Central

da Costa, Pedro Beschoren; Granada, Camille E.; Ambrosini, Adriana; Moreira, Fernanda; de Souza, Rocheli; dos Passos, João Frederico M.; Arruda, Letícia; Passaglia, Luciane M. P.

2014-01-01

Plant growth-promoting bacteria can greatly assist sustainable farming by improving plant health and biomass while reducing fertilizer use. The plant-microorganism-environment interaction is an open and complex system, and despite the active research in the area, patterns in root ecology are elusive. Here, we simultaneously analyzed the plant growth-promoting bacteria datasets from seven independent studies that shared a methodology for bioprospection and phenotype screening. The soil richness of the isolate's origin was classified by a Principal Component Analysis. A Categorical Principal Component Analysis was used to classify the soil richness according to isolate's indolic compound production, siderophores production and phosphate solubilization abilities, and bacterial genera composition. Multiple patterns and relationships were found and verified with nonparametric hypothesis testing. Including niche colonization in the analysis, we proposed a model to explain the expression of bacterial plant growth-promoting traits according to the soil nutritional status. Our model shows that plants favor interaction with growth hormone producers under rich nutrient conditions but favor nutrient solubilizers under poor conditions. We also performed several comparisons among the different genera, highlighting interesting ecological interactions and limitations. Our model could be used to direct plant growth-promoting bacteria bioprospection and metagenomic sampling. PMID:25542031

Screen-related sedentary behaviours of school-aged children: Principals’ and teachers’ perspectives

PubMed Central

He, Meizi; Piché, Leonard; Beynon, Charlene; Kurtz, Joanne; Harris, Stewart

2010-01-01

Objective To solicit school principals’ and teachers’ perspectives on children’s screen-related sedentary behaviour and to identify possible solutions to reduce sedentary behaviours among school-aged children. Method In-person interviews using a semi-structured interview guide were conducted with school principals and grades five and six classroom teachers in 14 randomly selected elementary schools in London and Middlesex County, Ontario. Fourteen principals and 39 classroom teachers participated in the study. Inductive content analysis was performed independently by two researchers. Results Both principals and teachers were very concerned about children’s excessive screen activities, but they did not perceive that they could play a key role in reducing these behaviours. Key barriers were identified to reducing screen-related sedentary behaviour and to children’s active living both at and away from school. They included competing demands from other subjects, limited gym resources/space within the school, a lack of control over the home environment, and a perception that parents were poor role models. Notwithstanding the above barriers, principals and teachers still recommended increasing children’s daily physical activity both within and outside of school hours. Furthermore, they stressed the need for parents to play a key role in reducing their children’s screen-related sedentary behaviours and increasing their level of physical activity. Conclusion School principals and teachers were very concerned about excessive screen-behaviour among school-aged children when away from school and suggested that interventions should emphasize increasing daily physical education, promoting recreational sports at or away from school, and engaging parents in regulating screen time at home. PMID:21468163

Multi-segmental movements as a function of experience in karate.

PubMed

Zago, Matteo; Codari, Marina; Iaia, F Marcello; Sforza, Chiarella

2017-08-01

Karate is a martial art that partly depends on subjective scoring of complex movements. Principal component analysis (PCA)-based methods can identify the fundamental synergies (principal movements) of motor system, providing a quantitative global analysis of technique. In this study, we aimed at describing the fundamental multi-joint synergies of a karate performance, under the hypothesis that the latter are skilldependent; estimate karateka's experience level, expressed as years of practice. A motion capture system recorded traditional karate techniques of 10 professional and amateur karateka. At any time point, the 3D-coordinates of body markers produced posture vectors that were normalised, concatenated from all karateka and submitted to a first PCA. Five principal movements described both gross movement synergies and individual differences. A second PCA followed by linear regression estimated the years of practice using principal movements (eigenpostures and weighting curves) and centre of mass kinematics (error: 3.71 years; R2 = 0.91, P ≪ 0.001). Principal movements and eigenpostures varied among different karateka and as functions of experience. This approach provides a framework to develop visual tools for the analysis of motor synergies in karate, allowing to detect the multi-joint motor patterns that should be restored after an injury, or to be specifically trained to increase performance.

Examining Parents' Ratings of Middle-School Students' Academic Self-Regulation Using Principal Axis Factoring Analysis

ERIC Educational Resources Information Center

Chen, Peggy P.; Cleary, Timothy J.; Lui, Angela M.

2015-01-01

This study examined the reliability and validity of a parent rating scale, the "Self-Regulation Strategy Inventory: Parent Rating Scale" ("SRSI-PRS"), using a sample of 451 parents of sixth- and seventh-grade middle-school students. Principal axis factoring (PAF) analysis revealed a 3-factor structure for the 23-item SRSI-PRS:…

How Teacher Evaluation Methods Matter for Accountability: A Comparative Analysis of Teacher Effectiveness Ratings by Principals and Teacher Value-Added Measures

ERIC Educational Resources Information Center

Harris, Douglas N.; Ingle, William K.; Rutledge, Stacey A.

2014-01-01

Policymakers are revolutionizing teacher evaluation by attaching greater stakes to student test scores and observation-based teacher effectiveness measures, but relatively little is known about why they often differ so much. Quantitative analysis of thirty schools suggests that teacher value-added measures and informal principal evaluations are…

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)

Predictive Validity of National Basketball Association Draft Combine on Future Performance.

PubMed

Teramoto, Masaru; Cross, Chad L; Rieger, Randall H; Maak, Travis G; Willick, Stuart E

2018-02-01

Teramoto, M, Cross, CL, Rieger, RH, Maak, TG, and Willick, SE. Predictive validity of national basketball association draft combine on future performance. J Strength Cond Res 32(2): 396-408, 2018-The National Basketball Association (NBA) Draft Combine is an annual event where prospective players are evaluated in terms of their athletic abilities and basketball skills. Data collected at the Combine should help NBA teams select right the players for the upcoming NBA draft; however, its value for predicting future performance of players has not been examined. This study investigated predictive validity of the NBA Draft Combine on future performance of basketball players. We performed a principal component analysis (PCA) on the 2010-2015 Combine data to reduce correlated variables (N = 234), a correlation analysis on the Combine data and future on-court performance to examine relationships (maximum pairwise N = 217), and a robust principal component regression (PCR) analysis to predict first-year and 3-year on-court performance from the Combine measures (N = 148 and 127, respectively). Three components were identified within the Combine data through PCA (= Combine subscales): length-size, power-quickness, and upper-body strength. As per the correlation analysis, the individual Combine items for anthropometrics, including height without shoes, standing reach, weight, wingspan, and hand length, as well as the Combine subscale of length-size, had positive, medium-to-large-sized correlations (r = 0.313-0.545) with defensive performance quantified by Defensive Box Plus/Minus. The robust PCR analysis showed that the Combine subscale of length-size was a predictor most significantly associated with future on-court performance (p ≤ 0.05), including Win Shares, Box Plus/Minus, and Value Over Replacement Player, followed by upper-body strength. In conclusion, the NBA Draft Combine has value for predicting future performance of players.

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.

New software for statistical analysis of Cambridge Structural Database data

PubMed Central

Sykes, Richard A.; McCabe, Patrick; Allen, Frank H.; Battle, Gary M.; Bruno, Ian J.; Wood, Peter A.

2011-01-01

A collection of new software tools is presented for the analysis of geometrical, chemical and crystallographic data from the Cambridge Structural Database (CSD). This software supersedes the program Vista. The new functionality is integrated into the program Mercury in order to provide statistical, charting and plotting options alongside three-dimensional structural visualization and analysis. The integration also permits immediate access to other information about specific CSD entries through the Mercury framework, a common requirement in CSD data analyses. In addition, the new software includes a range of more advanced features focused towards structural analysis such as principal components analysis, cone-angle correction in hydrogen-bond analyses and the ability to deal with topological symmetry that may be exhibited in molecular search fragments. PMID:22477784

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 components analysis of the photoresponse nonuniformity of a matrix detector.

PubMed

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

2007-01-01

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

A Perceptional Analysis of the South Carolina Principal Induction Program as Perceived by Program Participants

ERIC Educational Resources Information Center

Hudson, Jerome A.

2009-01-01

School districts are grappling with the problem of an alarming number of certified principals who are choosing not to enter the principalship. In many cases those who do enter are exiting only after a few years of service. Principals cite the long hours, low pay, and the stress of accountability as major reasons they are leaving the profession.…

Using Principal-Agent Theory as a Framework for Analysis in Evaluating the Multiple Stakeholders Involved in the Accreditation and Quality Assurance of International Medical Branch Campuses

ERIC Educational Resources Information Center

Borgos, Jill E.

2013-01-01

This article applies the theoretical framework of principal-agent theory in order to better understand the complex organisational relationships emerging between entities invested in the establishment and monitoring of cross-border international branch campus medical schools. Using the key constructs of principal-agent theory, information asymmetry…

A Qualitative Study of Three Urban Catholic High Schools: Investigating Parent and Principal Expectations and Realizations of Parental Involvement and the Parent-School Relationship

ERIC Educational Resources Information Center

Holyk-Casey, Karen

2012-01-01

This qualitative study investigated parents' and principals' expectations of their roles in the parent-school relationship and how they defined, encouraged, and realized parental involvement within an urban Catholic high school setting. Through pattern analysis and axial coding of the data collected from parents and principal interviews,…

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.

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

PubMed

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

2018-05-30

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

Applications of genetic algorithms on the structure-activity relationship analysis of some cinnamamides.

PubMed

Hou, T J; Wang, J M; Liao, N; Xu, X J

1999-01-01

Quantitative structure-activity relationships (QSARs) for 35 cinnamamides were studied. By using a genetic algorithm (GA), a group of multiple regression models with high fitness scores was generated. From the statistical analyses of the descriptors used in the evolution procedure, the principal features affecting the anticonvulsant activity were found. The significant descriptors include the partition coefficient, the molar refraction, the Hammet sigma constant of the substituents on the benzene ring, and the formation energy of the molecules. It could be found that the steric complementarity and the hydrophobic interaction between the inhibitors and the receptor were very important to the biological activity, while the contribution of the electronic effect was not so obvious. Moreover, by construction of the spline models for these four principal descriptors, the effective range for each descriptor was identified.

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators

PubMed Central

2017-01-01

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC—acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology. PMID:29049281

Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators.

PubMed

Barone, Lindsay; Williams, Jason; Micklos, David

2017-10-01

In a 2016 survey of 704 National Science Foundation (NSF) Biological Sciences Directorate principal investigators (BIO PIs), nearly 90% indicated they are currently or will soon be analyzing large data sets. BIO PIs considered a range of computational needs important to their work, including high performance computing (HPC), bioinformatics support, multistep workflows, updated analysis software, and the ability to store, share, and publish data. Previous studies in the United States and Canada emphasized infrastructure needs. However, BIO PIs said the most pressing unmet needs are training in data integration, data management, and scaling analyses for HPC-acknowledging that data science skills will be required to build a deeper understanding of life. This portends a growing data knowledge gap in biology and challenges institutions and funding agencies to redouble their support for computational training in biology.

Roughness encoding in human and biomimetic artificial touch: spatiotemporal frequency modulation and structural anisotropy of fingerprints.

PubMed

Oddo, Calogero Maria; Beccai, Lucia; Wessberg, Johan; Wasling, Helena Backlund; Mattioli, Fabio; Carrozza, Maria Chiara

2011-01-01

The influence of fingerprints and their curvature in tactile sensing performance is investigated by comparative analysis of different design parameters in a biomimetic artificial fingertip, having straight or curved fingerprints. The strength in the encoding of the principal spatial period of ridged tactile stimuli (gratings) is evaluated by indenting and sliding the surfaces at controlled normal contact force and tangential sliding velocity, as a function of fingertip rotation along the indentation axis. Curved fingerprints guaranteed higher directional isotropy than straight fingerprints in the encoding of the principal frequency resulting from the ratio between the sliding velocity and the spatial periodicity of the grating. In parallel, human microneurography experiments were performed and a selection of results is included in this work in order to support the significance of the biorobotic study with the artificial tactile system.

Development and Validation of the Caring Loneliness Scale.

PubMed

Karhe, Liisa; Kaunonen, Marja; Koivisto, Anna-Maija

2016-12-01

The Caring Loneliness Scale (CARLOS) includes 5 categories derived from earlier qualitative research. This article assesses the reliability and construct validity of a scale designed to measure patient experiences of loneliness in a professional caring relationship. Statistical analysis with 4 different sample sizes included Cronbach's alpha and exploratory factor analysis with principal axis factoring extraction. The sample size of 250 gave the most useful and comprehensible structure, but all 4 samples yielded underlying content of loneliness experiences. The initial 5 categories were reduced to 4 factors with 24 items and Cronbach's alpha ranging from .77 to .90. The findings support the reliability and validity of CARLOS for the assessment of Finnish breast cancer and heart surgery patients' experiences but as all instruments, further validation is needed.

Development of the Clinical Teaching Effectiveness Questionnaire in the United States.

PubMed

Wormley, Michelle E; Romney, Wendy; Greer, Anna E

2017-01-01

The purpose of this study was to develop a valid measure for assessing clinical teaching effectiveness within the field of physical therapy. The Clinical Teaching Effectiveness Questionnaire (CTEQ) was developed via a 4-stage process, including (1) initial content development, (2) content analysis with 8 clinical instructors with over 5 years of clinical teaching experience, (3) pilot testing with 205 clinical instructors from 2 universities in the Northeast of the United States, and (4) psychometric evaluation, including principal component analysis. The scale development process resulted in a 30-item questionnaire with 4 sections that relate to clinical teaching: learning experiences, learning environment, communication, and evaluation. The CTEQ provides a preliminary valid measure for assessing clinical teaching effectiveness in physical therapy practice.

Architectural measures of the cancellous bone of the mandibular condyle identified by principal components analysis.

PubMed

Giesen, E B W; Ding, M; Dalstra, M; van Eijden, T M G J

2003-09-01

As several morphological parameters of cancellous bone express more or less the same architectural measure, we applied principal components analysis to group these measures and correlated these to the mechanical properties. Cylindrical specimens (n = 24) were obtained in different orientations from embalmed mandibular condyles; the angle of the first principal direction and the axis of the specimen, expressing the orientation of the trabeculae, ranged from 10 degrees to 87 degrees. Morphological parameters were determined by a method based on Archimedes' principle and by micro-CT scanning, and the mechanical properties were obtained by mechanical testing. The principal components analysis was used to obtain a set of independent components to describe the morphology. This set was entered into linear regression analyses for explaining the variance in mechanical properties. The principal components analysis revealed four components: amount of bone, number of trabeculae, trabecular orientation, and miscellaneous. They accounted for about 90% of the variance in the morphological variables. The component loadings indicated that a higher amount of bone was primarily associated with more plate-like trabeculae, and not with more or thicker trabeculae. The trabecular orientation was most determinative (about 50%) in explaining stiffness, strength, and failure energy. The amount of bone was second most determinative and increased the explained variance to about 72%. These results suggest that trabecular orientation and amount of bone are important in explaining the anisotropic mechanical properties of the cancellous bone of the mandibular condyle.

Training Needs of Governmental Schools' Principals Hosting Kindergartens Classes: The Case for Jordan

ERIC Educational Resources Information Center

Ashraah, Mamdouh M.; Al-Olaimat, Ali M.; Takash, Hanan M.

2015-01-01

This study aimed at identifying the training needs of governmental schools' principals with kindergarten classes. The sample of the study consisted of a random sample of (62) female principal. The instrument of the study was developed by the researchers and included 60 items distributed on four domains (planning, organizing, guidance, and…

Emerging Technology Trends and Ethical Practices for the School Principal

ERIC Educational Resources Information Center

Garland, Virginia E.

2010-01-01

What is the school principal's role in ensuring ethical technology use while promoting the use of wireless and advanced technologies in instruction? The rapid advances in technology in only the past 5 years, including the increase in laptops and smart phones, have transformed both educational practices and the role of the school principal as…

The Views and Opinions of School Principals and Teachers on Positive Education

ERIC Educational Resources Information Center

Bas, Asli Uz; Firat, Necla Sahin

2017-01-01

The purpose of this study is to assess the views and opinions of school principals and teachers on positive education. The sample of the study includes 8 school principals and 12 teachers who attend different public schools in Izmir, Turkey. Data is collected through semi-structured interview technique. Findings show that majority of the…

Emotional Intelligence: The Contribution to Leadership Skills in Female Catholic Elementary School Principals

ERIC Educational Resources Information Center

Dziewior, Jane M.

2009-01-01

Past research was not clear what the relationship was between emotional intelligence (EI) and leadership style for school principals. This researcher examined EI and its contribution to leadership skills of 22 female Catholic elementary school principals. The method included a self-reported questionnaire of leadership style and EI to explore if…

The Relationship between Emotional Intelligence of Principals and the Overall Organizational Climate of Public Elementary Schools

ERIC Educational Resources Information Center

Juma, Dalal Sabri

2013-01-01

In this study the researcher examined the influence between a principal's self-perceived emotional intelligence and the overall organizational climate of one public elementary school as perceived by the principal's followers. These followers included teaching and non-teaching staff. It was not known how self-perceived emotional intelligence of a…

78 FR 16547 - Self-Regulatory Organizations; New York Stock Exchange LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-15

... orders together with the Retail Orders as part of the riskless principal transaction. The text of the... include non-retail orders together with the Retail Orders as part of the riskless principal transaction.\\3... FR 7824 (Feb. 4, 2013). Riskless principal transactions permitted by this amendment would be...

Identifying Principal and Teacher Descriptions of the Continuation High School Teacher's "Special Fitness to Perform"

ERIC Educational Resources Information Center

Vargas, Nestor Albert

2013-01-01

The objective of this study was to generate principal and teacher descriptions of what constitutes a teacher's "special fitness to perform" in a public urban continuation high school with a concentration of at-risk students. The sample included 6 continuation principals and 15 continuation teachers from a large urban school district in…

Principal Leadership in the Accountability Era: Influence of Expanding Job Responsibilities on Functional Work Performance, Stress Management, and Overall Job Satisfaction

ERIC Educational Resources Information Center

Andreyko, Tammy A.

2010-01-01

This study examined the relationship of stress, burnout, and coping strategies among middle school principals in Western Pennsylvania. This study assessed coping skill preferences among middle school principals, especially regarding their age, gender, marital status, experience, and school enrollment. A review of the literature included studies…

Resiliency and the Individual Demographics of School Leaders: Making a Difference in the Quality of Educational Leadership

ERIC Educational Resources Information Center

Isaacs, Albert J.

2012-01-01

The purpose of this quantitative study was to investigate the relationships among the dimensions of resilience and the individual demographics of high school principals toward strengthening the leadership abilities of school principals. The study employs the survey method in its research design. Those surveyed included 68 high school principals,…

Teacher & Principal School Report: Equity in Education

ERIC Educational Resources Information Center

Scholastic Inc., 2016

2016-01-01

A national survey of 4,721 public school educators was conducted by YouGov between July 22, 2016 and August 26, 2016, via an email-to-online survey method. Lists of teachers and principals were sourced from Market Data Retrieval's (MDR) database of public school Pre-K-12 teachers and principals. A total of 3,694 teachers (including 76 school…

Teacher and Principal Perceptions of How Principal Transformational and Instructional Leadership Behaviors Relate to Student Achievement

ERIC Educational Resources Information Center

Steele, Gayle

2012-01-01

Because of public concern over the effectiveness of our schools, a new evaluation system was put in place to hold principals and teachers directly accountable for student academic achievement. Part of this evaluation included student performance on state assessments. The purpose of this qualitative study sought to examine how the transformation…

School Law for the Principal: A Handbook for Practitioners.

ERIC Educational Resources Information Center

Shoop, Robert J.; Dunklee, Dennis R.

The relationship between the principal and the law has never been easy to define. This book provides basic information on the current status of law, risk, and site-based management as they relate to the legal rights and responsibilities of principals. Twenty-one chapters are included in five sections. The first section discusses the school and the…

School Community Involvement: New Realities for Schools and Their Principals.

ERIC Educational Resources Information Center

McCleary, Lloyd E., Ed.

Reconceptualizing the secondary school principal's role in relation to school-community involvements, this paper is the result of a three-part study. That study included a survey sample of school principals, a series of site conferences, and a seminar sharing data and plans from which the manuscript was prepared. The first chapter discusses the…

The Principal's Role in Implementation of Effective Teaching Strategies/Curriculum on the Reading Achievement of African American Middle School Students

ERIC Educational Resources Information Center

Booker, Kimberley Haynes

2009-01-01

The challenges for secondary schools and principals in the United States include changing demographics, schools and curricula that are inappropriately designed for today's adolescents, principals trained to be managers rather than instructional leaders, and a dramatic shortage of qualified candidates willing to take on the principalship. The…

The Learning Principal[R]. Volume 4, Number 7

ERIC Educational Resources Information Center

von Frank, Valerie, Ed.

2009-01-01

"The Learning Principal" is an eight-page newsletter published eight times a year. It focuses on the important and unique work of school principals. This issue includes: (1) A Learning Community Is Built on Trust (Valerie von Frank); (2) School Leadership: Q & A: Turnaround Doesn't Have to Take Years, Just Solid Leadership (Valerie von Frank); (3)…

E-Mentoring for New Principals: A Case Study of a Mentoring Program

ERIC Educational Resources Information Center

Russo, Erin D.

2013-01-01

This descriptive case study includes both new principals and their mentor principals engaged in e-mentoring activities. This study examines the components of a school district's mentoring program in order to make sense of e-mentoring technology. The literature review highlights mentoring practices in education, and also draws upon e-mentoring…

Who Is Responsible for Addressing Cyberbullying? Perspectives from Teachers and Senior Managers

ERIC Educational Resources Information Center

Green, Vanessa A.; Johnston, Michael; Mattioni, Loreto; Prior, Tessa; Harcourt, Susan; Lynch, Tegan

2017-01-01

This study investigates responsibility for addressing cyberbullying and the extent to which specific training is needed. A total of 888 school staff completed an anonymous online survey and included two groups: (a) teachers, including heads of departments, and (b) principals, deputy principals, and deans (i.e., school managers). The majority…

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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.

Development of a scale for attitude toward condom use for migrant workers in India.

PubMed

Talukdar, Arunansu; Bal, Runa; Sanyal, Debasis; Roy, Krishnendu; Talukdar, Payel Sengupta

2008-02-01

The propaganda for the use of condoms remains one of the mainstay for prevention of human immunodeficiency virus (HIV) transmission. In spite of the proven efficacy of condom, some moral, social and psychological obstacles are still prevalent, hindering the use of condoms. The study tried to construct a short condom-attitude scale for use among the migrant workers, a major bridge population in India. The study was conducted among the male migrant workers who were 18-49 years old, sexually active and had heard about condoms and were engaged in nonformal jobs. We recruited 234 and 280 candidates for Phase 1 and Phase 2 respectively. Ten items from the original 40-item Brown's ATC (attitude towards condom) scale were selected in Phase 1. After analysis of Phase 1 results, using principal component analysis six items were found appropriate for measuring attitude towards condom use. These six items were then administered in another group in Phase 2. Utilizing Pearson's correlations, scale items were examined in terms of their mean response scores and the correlation matrix between items. Cornbach's alpha and construct validity were also assessed for the entire sample. Study subjects were categorized as condom users and nonusers. The scale structure was explored by analyzing response scores with respect to the items, using principal component analysis followed by varimax rotation analysis. Principal component analysis revealed that the first factor accounted for 71% of the variance, with eigenvalue greater than one. Eigenvalues of the second factor was less than one. Application of screen test suggests only one factor was dominant. Mean score of six items among condom users was 20.45 and that among nonusers was 16.67, which was statistically significant (P<0.01). Cornbach's alpha coefficient was 0.92. This tailor-made attitude-toward-condom-use scale, targeted for most vulnerable people in India, can be included in any rapid survey for assessing the existing beliefs and attitudes toward condoms and also for evaluating efficacy of an intervention program.

Exploratory Development Research of U.S. Navy Marine Corps Personnel, Phase 1. Factors Affecting Attrition

DTIC Science & Technology

1977-09-30

havior. He has taught courses in research and has had con- siderable experience in the design and analysis of qualitative and quantitative research...name, serial number, unit, rank, or other identifying information was asked. Research pesign The research design was developed to determine if causes of...attrition have similar impach on men in various situations. The design includes three principal components. First, both attriters and adjusted men

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;

Description and typology of intensive Chios dairy sheep farms in Greece.

PubMed

Gelasakis, A I; Valergakis, G E; Arsenos, G; Banos, G

2012-06-01

The aim was to assess the intensified dairy sheep farming systems of the Chios breed in Greece, establishing a typology that may properly describe and characterize them. The study included the total of the 66 farms of the Chios sheep breeders' cooperative Macedonia. Data were collected using a structured direct questionnaire for in-depth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices. A multivariate statistical analysis was used on the data to obtain the most appropriate typology. Initially, principal component analysis was used to produce uncorrelated variables (principal components), which would be used for the consecutive cluster analysis. The number of clusters was decided using hierarchical cluster analysis, whereas, the farms were allocated in 4 clusters using k-means cluster analysis. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main differences were evident on land availability and use, facility and equipment availability and type, expansion rates, and application of preventive flock health programs. In general, cluster 1 included newly established, intensive, well-equipped, specialized farms and cluster 2 included well-established farms with balanced sheep and feed/crop production. In cluster 3 were assigned small flock farms focusing more on arable crops than on sheep farming with a tendency to evolve toward cluster 2, whereas cluster 4 included farms representing a rather conservative form of Chios sheep breeding with low/intermediate inputs and choosing not to focus on feed/crop production. In the studied set of farms, 4 different farmer attitudes were evident: 1) farming disrupts sheep breeding; feed should be purchased and economies of scale will decrease costs (mainly cluster 1), 2) only exercise/pasture land is necessary; at least part of the feed (pasture) must be home-grown to decrease costs (clusters 1 and 4), 3) providing pasture to sheep is essential; on-farm feed production decreases costs (mainly cluster 3), and 4) large-scale farming (feed production and cash crops) does not disrupt sheep breeding; all feed must be produced on-farm to decrease costs (mainly cluster 3). Conducting a profitability analysis among different clusters, exploring and discovering the most beneficial levels of intensified management and capital investment should now be considered. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Feature extraction across individual time series observations with spikes using wavelet principal component analysis.

PubMed

Røislien, Jo; Winje, Brita

2013-09-20

Clinical studies frequently include repeated measurements of individuals, often for long periods. We present a methodology for extracting common temporal features across a set of individual time series observations. In particular, the methodology explores extreme observations within the time series, such as spikes, as a possible common temporal phenomenon. Wavelet basis functions are attractive in this sense, as they are localized in both time and frequency domains simultaneously, allowing for localized feature extraction from a time-varying signal. We apply wavelet basis function decomposition of individual time series, with corresponding wavelet shrinkage to remove noise. We then extract common temporal features using linear principal component analysis on the wavelet coefficients, before inverse transformation back to the time domain for clinical interpretation. We demonstrate the methodology on a subset of a large fetal activity study aiming to identify temporal patterns in fetal movement (FM) count data in order to explore formal FM counting as a screening tool for identifying fetal compromise and thus preventing adverse birth outcomes. Copyright © 2013 John Wiley & Sons, Ltd.

Genetic structure in the Sherpa and neighboring Nepalese populations.

PubMed

Cole, Amy M; Cox, Sean; Jeong, Choongwon; Petousi, Nayia; Aryal, Dhana R; Droma, Yunden; Hanaoka, Masayuki; Ota, Masao; Kobayashi, Nobumitsu; Gasparini, Paolo; Montgomery, Hugh; Robbins, Peter; Di Rienzo, Anna; Cavalleri, Gianpiero L

2017-01-19

We set out to describe the fine-scale population structure across the Eastern region of Nepal. To date there is relatively little known about the genetic structure of the Sherpa residing in Nepal and their genetic relationship with the Nepalese. We assembled dense genotype data from a total of 1245 individuals representing Nepal and a variety of different populations resident across the greater Himalayan region including Tibet, China, India, Pakistan, Kazakhstan, Uzbekistan, Tajikistan and Kirghizstan. We performed analysis of principal components, admixture and homozygosity. We identified clear substructure across populations resident in the Himalayan arc, with genetic structure broadly mirroring geographical features of the region. Ethnic subgroups within Nepal show distinct genetic structure, on both admixture and principal component analysis. We detected differential proportions of ancestry from northern Himalayan populations across Nepalese subgroups, with the Nepalese Rai, Magar and Tamang carrying the greatest proportions of Tibetan ancestry. We show that populations dwelling on the Himalayan plateau have had a clear impact on the Northern Indian gene pool. We illustrate how the Sherpa are a remarkably isolated population, with little gene flow from surrounding Nepalese populations.

Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis

USGS Publications Warehouse

Szabo, J.K.; Fedriani, E.M.; Segovia-Gonzalez, M. M.; Astheimer, L.B.; Hooper, M.J.

2010-01-01

This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.

Principal component analysis study of visual and verbal metaphoric comprehension in children with autism and learning disabilities.

PubMed

Mashal, Nira; Kasirer, Anat

2012-01-01

This research extends previous studies regarding the metaphoric competence of autistic and learning disable children on different measures of visual and verbal non-literal language comprehension, as well as cognitive abilities that include semantic knowledge, executive functions, similarities, and reading fluency. Thirty seven children with autism (ASD), 20 children with learning disabilities (LD), and 21 typically developed (TD) children participated in the study. Principal components analysis was used to examine the interrelationship among the various tests in each group. Results showed different patterns in the data according to group. In particular, the results revealed that there is no dichotomy between visual and verbal metaphors in TD children but rather metaphor are classified according to their familiarity level. In the LD group visual metaphors were classified independently of the verbal metaphors. Verbal metaphoric understanding in the ASD group resembled the LD group. In addition, our results revealed the relative weakness of the ASD and LD children in suppressing irrelevant information. Copyright © 2011 Elsevier Ltd. All rights reserved.

Discrimination of Geographical Origin of Asian Garlic Using Isotopic and Chemical Datasets under Stepwise Principal Component Analysis.

PubMed

Liu, Tsang-Sen; Lin, Jhen-Nan; Peng, Tsung-Ren

2018-01-16

Isotopic compositions of δ 2 H, δ 18 O, δ 13 C, and δ 15 N and concentrations of 22 trace elements from garlic samples were analyzed and processed with stepwise principal component analysis (PCA) to discriminate garlic's country of origin among Asian regions including South Korea, Vietnam, Taiwan, and China. Results indicate that there is no single trace-element concentration or isotopic composition that can accomplish the study's purpose and the stepwise PCA approach proposed does allow for discrimination between countries on a regional basis. Sequentially, Step-1 PCA distinguishes garlic's country of origin among Taiwanese, South Korean, and Vietnamese samples; Step-2 PCA discriminates Chinese garlic from South Korean garlic; and Step-3 and Step-4 PCA, Chinese garlic from Vietnamese garlic. In model tests, countries of origin of all audit samples were correctly discriminated by stepwise PCA. Consequently, this study demonstrates that stepwise PCA as applied is a simple and effective approach to discriminating country of origin among Asian garlics. © 2018 American Academy of Forensic Sciences.

Transforming Graph Data for Statistical Relational Learning

DTIC Science & Technology

2012-10-01

Jordan, 2003), PLSA (Hofmann, 1999), ? Classification via RMN (Taskar et al., 2003) or SVM (Hasan, Chaoji, Salem , & Zaki, 2006) ? Hierarchical...dimensionality reduction methods such as Principal 407 Rossi, McDowell, Aha, & Neville Component Analysis (PCA), Principal Factor Analysis ( PFA ), and...clustering algorithm. Journal of the Royal Statistical Society. Series C, Applied statistics, 28, 100–108. Hasan, M. A., Chaoji, V., Salem , S., & Zaki, M

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

ERIC Educational Resources Information Center

Lawson, J. S.; Inglis, James

1984-01-01

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

Classification of white wine aromas with an electronic nose.

PubMed

Lozano, J; Santos, J P; Horrillo, M C

2005-09-15

This paper reports the use of a tin dioxide multisensor array based electronic nose for recognition of 29 typical aromas in white wine. Headspace technique has been used to extract aroma of the wine. Multivariate analysis, including principal component analysis (PCA) as well as probabilistic neural networks (PNNs), has been used to identify the main aroma added to the wine. The results showed that in spite of the strong influence of ethanol and other majority compounds of wine, the system could discriminate correctly the aromatic compounds added to the wine with a minimum accuracy of 97.2%.

Laboratory spectroscopy of meteorite samples at UV-vis-NIR wavelengths: Analysis and discrimination by principal components analysis

NASA Astrophysics Data System (ADS)

Penttilä, Antti; Martikainen, Julia; Gritsevich, Maria; Muinonen, Karri

2018-02-01

Meteorite samples are measured with the University of Helsinki integrating-sphere UV-vis-NIR spectrometer. The resulting spectra of 30 meteorites are compared with selected spectra from the NASA Planetary Data System meteorite spectra database. The spectral measurements are transformed with the principal component analysis, and it is shown that different meteorite types can be distinguished from the transformed data. The motivation is to improve the link between asteroid spectral observations and meteorite spectral measurements.

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

Analysis of environmental variation in a Great Plains reservoir using principal components analysis and geographic information systems

USGS Publications Warehouse

Long, J.M.; Fisher, W.L.

2006-01-01

We present a method for spatial interpretation of environmental variation in a reservoir that integrates principal components analysis (PCA) of environmental data with geographic information systems (GIS). To illustrate our method, we used data from a Great Plains reservoir (Skiatook Lake, Oklahoma) with longitudinal variation in physicochemical conditions. We measured 18 physicochemical features, mapped them using GIS, and then calculated and interpreted four principal components. Principal component 1 (PC1) was readily interpreted as longitudinal variation in water chemistry, but the other principal components (PC2-4) were difficult to interpret. Site scores for PC1-4 were calculated in GIS by summing weighted overlays of the 18 measured environmental variables, with the factor loadings from the PCA as the weights. PC1-4 were then ordered into a landscape hierarchy, an emergent property of this technique, which enabled their interpretation. PC1 was interpreted as a reservoir scale change in water chemistry, PC2 was a microhabitat variable of rip-rap substrate, PC3 identified coves/embayments and PC4 consisted of shoreline microhabitats related to slope. The use of GIS improved our ability to interpret the more obscure principal components (PC2-4), which made the spatial variability of the reservoir environment more apparent. This method is applicable to a variety of aquatic systems, can be accomplished using commercially available software programs, and allows for improved interpretation of the geographic environmental variability of a system compared to using typical PCA plots. ?? Copyright by the North American Lake Management Society 2006.

Using Cognitive Coaching to Build School Leadership Capacity: A Case Study in Alberta

ERIC Educational Resources Information Center

Rogers, W. Todd; Hauserman, Cal P.; Skytt, Jacqueline

2016-01-01

The impact of Cognitive Coaching? included as part of the Leader2Leader (L2L) Leadership Pilot Program for beginning principals in Alberta, Canada, was evaluated in the present study. Fifteen qualified principals (coaches) and 23 new principals completed the L2L Pilot Program that took place over 18 months. Questionnaires for coaches and new…

A Study of Perceived Leadership Styles as It Affects the Decision-Making Process Employed by Eleven Catholic School Principals in South Texas

ERIC Educational Resources Information Center

Agbakoba, Mary Olivia

2017-01-01

Catholic School principals play an important role in the development of students' spiritual, social, and academic wellbeing. Consequently, in order to improve students' spiritual, social, and academic skill, it is vital to study the perceived leadership styles and decision-making of Catholic School Principals. Research questions include: "Is…

Principal Self-Government and Subjectification: The Exercise of Principal Autonomy in the Western Australian Independent Public Schools Programme

ERIC Educational Resources Information Center

Gobby, Brad

2013-01-01

The launch of the Independent Public Schools (IPS) programme in Western Australia (WA) in 2010 reflects the neoliberal policy discourse of decentralisation and school self-management sweeping across many of the world's education systems. IPS provides WA state school principals with decision-making authority in a range of areas, including the…

12 CFR 215.9 - Disclosure of credit from member banks to executive officers and principal shareholders.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 2 2010-01-01 2010-01-01 false Disclosure of credit from member banks to executive officers and principal shareholders. 215.9 Section 215.9 Banks and Banking FEDERAL RESERVE SYSTEM... includes a person that controls a principal shareholder (e.g., a person that controls a bank holding...

A manual for microcomputer image analysis

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

Rich, P.M.; Ranken, D.M.; George, J.S.

1989-12-01

This manual is intended to serve three basic purposes: as a primer in microcomputer image analysis theory and techniques, as a guide to the use of IMAGE{copyright}, a public domain microcomputer program for image analysis, and as a stimulus to encourage programmers to develop microcomputer software suited for scientific use. Topics discussed include the principals of image processing and analysis, use of standard video for input and display, spatial measurement techniques, and the future of microcomputer image analysis. A complete reference guide that lists the commands for IMAGE is provided. IMAGE includes capabilities for digitization, input and output of images,more » hardware display lookup table control, editing, edge detection, histogram calculation, measurement along lines and curves, measurement of areas, examination of intensity values, output of analytical results, conversion between raster and vector formats, and region movement and rescaling. The control structure of IMAGE emphasizes efficiency, precision of measurement, and scientific utility. 18 refs., 18 figs., 2 tabs.« less

Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

NASA Astrophysics Data System (ADS)

Schelkanova, Irina; Toronov, Vladislav

2011-07-01

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

A Hybrid Color Space for Skin Detection Using Genetic Algorithm Heuristic Search and Principal Component Analysis Technique

PubMed Central

2015-01-01

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination variations, various camera characteristics and diversity in skin color tones has remained an open issue. This research proposes a new three-dimensional hybrid color space termed SKN by employing the Genetic Algorithm heuristic and Principal Component Analysis to find the optimal representation of human skin color in over seventeen existing color spaces. Genetic Algorithm heuristic is used to find the optimal color component combination setup in terms of skin detection accuracy while the Principal Component Analysis projects the optimal Genetic Algorithm solution to a less complex dimension. Pixel wise skin detection was used to evaluate the performance of the proposed color space. We have employed four classifiers including Random Forest, Naïve Bayes, Support Vector Machine and Multilayer Perceptron in order to generate the human skin color predictive model. The proposed color space was compared to some existing color spaces and shows superior results in terms of pixel-wise skin detection accuracy. Experimental results show that by using Random Forest classifier, the proposed SKN color space obtained an average F-score and True Positive Rate of 0.953 and False Positive Rate of 0.0482 which outperformed the existing color spaces in terms of pixel wise skin detection accuracy. The results also indicate that among the classifiers used in this study, Random Forest is the most suitable classifier for pixel wise skin detection applications. PMID:26267377

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

PubMed

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

2018-05-22

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

Mapping and Modeling Web Portal to Advance Global Monitoring and Climate Research

NASA Astrophysics Data System (ADS)

Chang, G.; Malhotra, S.; Bui, B.; Sadaqathulla, S.; Goodale, C. E.; Ramirez, P.; Kim, R. M.; Rodriguez, L.; Law, E.

2011-12-01

Today, the principal investigators of NASA Earth Science missions develop their own software to manipulate, visualize, and analyze the data collected from Earth, space, and airborne observation instruments. There is very little, if any, collaboration among these principal investigators due to the lack of collaborative tools, which would allow these scientists to share data and results. At NASA's Jet Propulsion Laboratory (JPL), under the Lunar Mapping and Modeling Project (LMMP), we have built a web portal that exposes a set of common services to users to allow search, visualization, subset, and download lunar science data. Users also have access to a set of tools that visualize, analyze and annotate the data. These services are developed according to industry standards for data access and manipulation, such REST and Open Geospatial Consortium (OGC) web services. As a result, users can access the datasets through custom written applications or off-the-shelf applications such as Google Earth. Even though it's currently used to store and process lunar data, this web portal infrastructure has been designed to support other solar system bodies such as asteroids and planets, including Earth. The infrastructure uses a combination of custom, commercial, and open-source software as well as off-the-shelf hardware and pay-by-use cloud computing services. The use of standardized web service interfaces facilitates platform and application-independent access to the services and data. For instance, we have software clients for the LMMP portal that provide a rich browsing and analysis experience from a variety of platforms including iOS and Android mobile platforms and large screen multi-touch displays with 3-D terrain viewing functions. The service-oriented architecture and design principles utilized in the implementation of the portal lends itself to be reusable and scalable and could naturally be extended to include a collaborative environment that enables scientists and principal investigators to share their research and analysis seamlessly. In addition, this extension will allow users to easily share their tools and data, and to enrich their mapping and analysis experiences. In this talk, we will describe the advanced data management and portal technologies used to power this collaborative environment. We will further illustrate how this environment can enable, enhance and advance global monitoring and climate research.

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.

Rural livestock asset portfolio in northern Ethiopia: a microeconomic analysis of choice and accumulation.

PubMed

Tegebu, Fredu Nega; Mathijs, Erik; Deckers, Jozef; Haile, Mitiku; Nyssen, Jan; Tollens, Eric

2012-01-01

Livestock fulfill different functions. Depending on their livelihood strategies, households differ in their choice of what type of animal to keep and on accumulation of the chosen animal overtime. Using a panel data of 385 rural households in a mixed farming system in northern Ethiopia, this paper investigates the dynamic behavior of rural households' livestock holding to identify determinants of choice and accumulation of livestock overtime. Choice is analyzed for a principal animal, the animal that constituted the largest value of livestock assets a household possessed, using a multinomial logit model. Results indicate that rural households differ in their choice of what type of animal to keep. Agro-climatic conditions, sex and age of household head, presence of an adult male member in a household, and liquidity are the major factors that influence the type of principal animal households keep. Conditional on the principal animal selected, we analyzed the factors that determine the accumulation of the chosen animals by correcting for selection bias. Area of land cultivated is the most significant factor that explains the number of animals households keep. Other factors include sex of household head, diversification into nonfarm self-employment, and shocks.

[Ecological adaptability evaluation of peanut cultivars based on biomass and nutrient accumulation].

PubMed

Wang, Xue; Cui, Shao-xiong; Sun, Zhi-mei; Mu, Guo-jun; Cui, Shun-li; Wang, Peng-chao; Liu, Li-feng

2015-07-01

To identify the good peanut cultivars with the properties of high yield, high nutrient use efficiency and wide adaptability, 19 selected peanut cultivars were planted in the low champaign area and piedmont plain area of Hebei Province. By using principal component analysis, the adaptability of these 19 cultivars was evaluated for different ecological regions through comparing their 16 main traits including biomass and nutrient parameters. According to the critical value of principal component (>1.0), the 16 biomass and nutrient characteristics were integrated into 4 principal components which accounted for 85% of the original information. The results indicated that there were obvious differences in yield and nutrient use efficiency for the peanut cultivars in different ecological regions. The 19 peanut cultivars were classified into 2 groups according to their ecological adaptability, and the cultivars from the group with wide adaptability could further be divided into 3 categories according to their yield and nutrient use efficiency. Among these cultivars, Yuhua 9719, Jihua 0212-4, Weihua 10, Yuhua 15, Puhua 28 and Jihua 10 were selected as the better peanut cultivars with the properties of high yield, high nutrient use efficiency and wide adaptability.

A New Tool for Nutrition App Quality Evaluation (AQEL): Development, Validation, and Reliability Testing.

PubMed

DiFilippo, Kristen Nicole; Huang, Wenhao; Chapman-Novakofski, Karen M

2017-10-27

The extensive availability and increasing use of mobile apps for nutrition-based health interventions makes evaluation of the quality of these apps crucial for integration of apps into nutritional counseling. The goal of this research was the development, validation, and reliability testing of the app quality evaluation (AQEL) tool, an instrument for evaluating apps' educational quality and technical functionality. Items for evaluating app quality were adapted from website evaluations, with additional items added to evaluate the specific characteristics of apps, resulting in 79 initial items. Expert panels of nutrition and technology professionals and app users reviewed items for face and content validation. After recommended revisions, nutrition experts completed a second AQEL review to ensure clarity. On the basis of 150 sets of responses using the revised AQEL, principal component analysis was completed, reducing AQEL into 5 factors that underwent reliability testing, including internal consistency, split-half reliability, test-retest reliability, and interrater reliability (IRR). Two additional modifiable constructs for evaluating apps based on the age and needs of the target audience as selected by the evaluator were also tested for construct reliability. IRR testing using intraclass correlations (ICC) with all 7 constructs was conducted, with 15 dietitians evaluating one app. Development and validation resulted in the 51-item AQEL. These were reduced to 25 items in 5 factors after principal component analysis, plus 9 modifiable items in two constructs that were not included in principal component analysis. Internal consistency and split-half reliability of the following constructs derived from principal components analysis was good (Cronbach alpha >.80, Spearman-Brown coefficient >.80): behavior change potential, support of knowledge acquisition, app function, and skill development. App purpose split half-reliability was .65. Test-retest reliability showed no significant change over time (P>.05) for all but skill development (P=.001). Construct reliability was good for items assessing age appropriateness of apps for children, teens, and a general audience. In addition, construct reliability was acceptable for assessing app appropriateness for various target audiences (Cronbach alpha >.70). For the 5 main factors, ICC (1,k) was >.80, with a P value of <.05. When 15 nutrition professionals evaluated one app, ICC (2,15) was .98, with a P value of <.001 for all 7 constructs when the modifiable items were specified for adults seeking weight loss support. Our preliminary effort shows that AQEL is a valid, reliable instrument for evaluating nutrition apps' qualities for clinical interventions by nutrition clinicians, educators, and researchers. Further efforts in validating AQEL in various contexts are needed. ©Kristen Nicole DiFilippo, Wenhao Huang, Karen M. Chapman-Novakofski. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 27.10.2017.

The role of the elementary school principal — as perceived by Israeli principals an attempt at role analysis

NASA Astrophysics Data System (ADS)

Kremer, Lya

1983-03-01

The study aimed to define the role of principalship, necessary because of the conflicting loyalties and responsibilities inherent in this role. Four `facets' were used to classify areas of principals' activities, from which a questionnaire was constructed. Ninety principals, representing most of those in the northern part of Israel, participated in the project. On the basis of the questionnaire, they related their role activities to the degree of autonomy they felt they were granted. The findings identify the main factors in the role of the principal and show that principals' activities may be defined according to (a) the degree to which they have been planned in advance or carried out ad hoc; (b) their professional or bureaucratic character; (c) the goals which they are meant to serve and whether their aim is task/product-or person-orientated. In all of these areas the principal can act with varying degrees of autonomy. The techniques employed in obtaining and analyzing the results offer a means of creating and comparing principals' profiles, hence also of indicating the position of the principal in the more general system; producing a typology of administrative styles; and identifying personal styles of principalship.

Self organising maps for visualising and modelling

PubMed Central

2012-01-01

The paper describes the motivation of SOMs (Self Organising Maps) and how they are generally more accessible due to the wider available modern, more powerful, cost-effective computers. Their advantages compared to Principal Components Analysis and Partial Least Squares are discussed. These allow application to non-linear data, are not so dependent on least squares solutions, normality of errors and less influenced by outliers. In addition there are a wide variety of intuitive methods for visualisation that allow full use of the map space. Modern problems in analytical chemistry include applications to cultural heritage studies, environmental, metabolomic and biological problems result in complex datasets. Methods for visualising maps are described including best matching units, hit histograms, unified distance matrices and component planes. Supervised SOMs for classification including multifactor data and variable selection are discussed as is their use in Quality Control. The paper is illustrated using four case studies, namely the Near Infrared of food, the thermal analysis of polymers, metabolomic analysis of saliva using NMR, and on-line HPLC for pharmaceutical process monitoring. PMID:22594434

Application of time series analysis on molecular dynamics simulations of proteins: a study of different conformational spaces by principal component analysis.

PubMed

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C

2004-09-08

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of alpha-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Calpha coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of alpha-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of alpha-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins. Copyright 2004 American Institute of Physics

Application of time series analysis on molecular dynamics simulations of proteins: A study of different conformational spaces by principal component analysis

NASA Astrophysics Data System (ADS)

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

2004-09-01

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of α-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Cα coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of α-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of α-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins.

Identification and visualization of dominant patterns and anomalies in remotely sensed vegetation phenology using a parallel tool for principal components analysis

Treesearch

Richard Tran Mills; Jitendra Kumar; Forrest M. Hoffman; William W. Hargrove; Joseph P. Spruce; Steven P. Norman

2013-01-01

We investigated the use of principal components analysis (PCA) to visualize dominant patterns and identify anomalies in a multi-year land surface phenology data set (231 m × 231 m normalized difference vegetation index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS)) used for detecting threats to forest health in the conterminous...

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.

Phytoplankton across Tropical and Subtropical Regions of the Atlantic, Indian and Pacific Oceans

PubMed Central

Estrada, Marta; Delgado, Maximino; Blasco, Dolors; Latasa, Mikel; Cabello, Ana María; Benítez-Barrios, Verónica; Fraile-Nuez, Eugenio; Mozetič, Patricija; Vidal, Montserrat

2016-01-01

We examine the large-scale distribution patterns of the nano- and microphytoplankton collected from 145 oceanic stations, at 3 m depth, the 20% light level and the depth of the subsurface chlorophyll maximum, during the Malaspina-2010 Expedition (December 2010-July 2011), which covered 15 biogeographical provinces across the Atlantic, Indian and Pacific oceans, between 35°N and 40°S. In general, the water column was stratified, the surface layers were nutrient-poor and the nano- and microplankton (hereafter phytoplankton, for simplicity, although it included also heterotrophic protists) community was dominated by dinoflagellates, other flagellates and coccolithophores, while the contribution of diatoms was only important in zones with shallow nutriclines such as the equatorial upwelling regions. We applied a principal component analysis to the correlation matrix among the abundances (after logarithmic transform) of the 76 most frequent taxa to synthesize the information contained in the phytoplankton data set. The main trends of variability identified consisted of: 1) A contrast between the community composition of the upper and the lower parts of the euphotic zone, expressed respectively by positive or negative scores of the first principal component, which was positively correlated with taxa such as the dinoflagellates Oxytoxum minutum and Scrippsiella spp., and the coccolithophores Discosphaera tubifera and Syracosphaera pulchra (HOL and HET), and negatively correlated with taxa like Ophiaster hydroideus (coccolithophore) and several diatoms, 2) a general abundance gradient between phytoplankton-rich regions with high abundances of dinoflagellate, coccolithophore and ciliate taxa, and phytoplankton-poor regions (second principal component), 3) differences in dominant phytoplankton and ciliate taxa among the Atlantic, the Indian and the Pacific oceans (third principal component) and 4) the occurrence of a diatom-dominated assemblage (the fourth principal component assemblage), including several pennate taxa, Planktoniella sol, Hemiaulus hauckii and Pseudo-nitzschia spp., in the divergence regions. Our findings indicate that consistent assemblages of co-occurring phytoplankton taxa can be identified and that their distribution is best explained by a combination in different degrees of both environmental and historical influences. PMID:26982180

Phytoplankton across Tropical and Subtropical Regions of the Atlantic, Indian and Pacific Oceans.

PubMed

Estrada, Marta; Delgado, Maximino; Blasco, Dolors; Latasa, Mikel; Cabello, Ana María; Benítez-Barrios, Verónica; Fraile-Nuez, Eugenio; Mozetič, Patricija; Vidal, Montserrat

2016-01-01

We examine the large-scale distribution patterns of the nano- and microphytoplankton collected from 145 oceanic stations, at 3 m depth, the 20% light level and the depth of the subsurface chlorophyll maximum, during the Malaspina-2010 Expedition (December 2010-July 2011), which covered 15 biogeographical provinces across the Atlantic, Indian and Pacific oceans, between 35°N and 40°S. In general, the water column was stratified, the surface layers were nutrient-poor and the nano- and microplankton (hereafter phytoplankton, for simplicity, although it included also heterotrophic protists) community was dominated by dinoflagellates, other flagellates and coccolithophores, while the contribution of diatoms was only important in zones with shallow nutriclines such as the equatorial upwelling regions. We applied a principal component analysis to the correlation matrix among the abundances (after logarithmic transform) of the 76 most frequent taxa to synthesize the information contained in the phytoplankton data set. The main trends of variability identified consisted of: 1) A contrast between the community composition of the upper and the lower parts of the euphotic zone, expressed respectively by positive or negative scores of the first principal component, which was positively correlated with taxa such as the dinoflagellates Oxytoxum minutum and Scrippsiella spp., and the coccolithophores Discosphaera tubifera and Syracosphaera pulchra (HOL and HET), and negatively correlated with taxa like Ophiaster hydroideus (coccolithophore) and several diatoms, 2) a general abundance gradient between phytoplankton-rich regions with high abundances of dinoflagellate, coccolithophore and ciliate taxa, and phytoplankton-poor regions (second principal component), 3) differences in dominant phytoplankton and ciliate taxa among the Atlantic, the Indian and the Pacific oceans (third principal component) and 4) the occurrence of a diatom-dominated assemblage (the fourth principal component assemblage), including several pennate taxa, Planktoniella sol, Hemiaulus hauckii and Pseudo-nitzschia spp., in the divergence regions. Our findings indicate that consistent assemblages of co-occurring phytoplankton taxa can be identified and that their distribution is best explained by a combination in different degrees of both environmental and historical influences.

Convergence of sampling in protein simulations

NASA Astrophysics Data System (ADS)

Hess, Berk

2002-03-01

With molecular dynamics protein dynamics can be simulated in atomic detail. Current computers are not fast enough to probe all available conformations, but fluctuations around one conformation can be sampled to a reasonable extent. The motions with the largest fluctuations can be filtered out of a simulation using covariance or principal component analysis. A problem with this analysis is that random diffusion can appear as correlated motion. An analysis is presented of how long a simulation should be to obtain relevant results for global motions. The analysis reveals that the cosine content of the principal components is a good indicator for bad sampling.

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

A Study of Strengths and Weaknesses of Descriptive Assessment from Principals, Teachers and Experts Points of View in Chaharmahal and Bakhteyari Primary Schools

ERIC Educational Resources Information Center

Sharief, Mostafa; Naderi, Mahin; Hiedari, Maryam Shoja; Roodbari, Omolbanin; Jalilvand, Mohammad Reza

2012-01-01

The aim of current study is to determine the strengths and weaknesses of descriptive evaluation from the viewpoint of principals, teachers and experts of Chaharmahal and Bakhtiari province. A descriptive survey was performed. Statistical population includes 208 principals, 303 teachers, and 100 executive experts of descriptive evaluation scheme in…

Enhancement of TEM Data and Noise Characterization by Principal Component Analysis

DTIC Science & Technology

2010-05-01

include simply thresholding a noise level and ignoring any signal below the chosen value ( Pasion and Oldenburg, 2001b), stacking, and median filters...to de-trend the data ( Pasion and Oldenburg, 2001a). To date, there has not been a concentrated research effort focused on separating the various...Negative values not displayed) 27 Magnetic soil at Kaho’olawe (and in general) exhibits a t−1 decay in TEM surveys ( Pasion et al., 2002). This signal

Trapped Electron Model 2 (TEM-2)

DTIC Science & Technology

2010-04-25

density and computes sample correlations : 9t = ft-{ft)T, («6) £T = (stsf)T, («7) RT = {9t9j+i)r- (88) We have made the very safe...such as solar wind correlation studies, initial and boundary conditions for numerical simulations, and principal component analysis. We...O’Brien 19b. TELEPHONE NUMBER (include area code ) 571-307-3978 Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. 239.18 Ackmowledgments This work

[Study of near infrared spectral preprocessing and wavelength selection methods for endometrial cancer tissue].

PubMed

Zhao, Li-Ting; Xiang, Yu-Hong; Dai, Yin-Mei; Zhang, Zhuo-Yong

2010-04-01

Near infrared spectroscopy was applied to measure the tissue slice of endometrial tissues for collecting the spectra. A total of 154 spectra were obtained from 154 samples. The number of normal, hyperplasia, and malignant samples was 36, 60, and 58, respectively. Original near infrared spectra are composed of many variables, for example, interference information including instrument errors and physical effects such as particle size and light scatter. In order to reduce these influences, original spectra data should be performed with different spectral preprocessing methods to compress variables and extract useful information. So the methods of spectral preprocessing and wavelength selection have played an important role in near infrared spectroscopy technique. In the present paper the raw spectra were processed using various preprocessing methods including first derivative, multiplication scatter correction, Savitzky-Golay first derivative algorithm, standard normal variate, smoothing, and moving-window median. Standard deviation was used to select the optimal spectral region of 4 000-6 000 cm(-1). Then principal component analysis was used for classification. Principal component analysis results showed that three types of samples could be discriminated completely and the accuracy almost achieved 100%. This study demonstrated that near infrared spectroscopy technology and chemometrics method could be a fast, efficient, and novel means to diagnose cancer. The proposed methods would be a promising and significant diagnosis technique of early stage cancer.