Modeling vertebrate diversity in Oregon using satellite imagery

NASA Astrophysics Data System (ADS)

Cablk, Mary Elizabeth

Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.

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 an evaluation of the hemiplegic subject based on the Bobath approach.

PubMed

Corriveau, H; Arsenault, A B; Dutil, E; Lepage, Y

1992-01-01

An evaluation based on the Bobath approach to treatment has previously been developed and partially validated. The purpose of the present study was to verify the content validity of this evaluation with the use of a statistical approach known as principal components analysis. Thirty-eight hemiplegic subjects participated in the study. Analysis of the scores on each of six parameters (sensorium, active movements, muscle tone, reflex activity, postural reactions, and pain) was evaluated on three occasions across a 2-month period. Each time this produced three factors that contained 70% of the variation in the data set. The first component mainly reflected variations in mobility, the second mainly variations in muscle tone, and the third mainly variations in sensorium and pain. The results of such exploratory analysis highlight the fact that some of the parameters are not only important but also interrelated. These results seem to partially support the conceptual framework substantiating the Bobath approach to treatment.

Beta Hebbian Learning as a New Method for Exploratory Projection Pursuit.

PubMed

Quintián, Héctor; Corchado, Emilio

2017-09-01

In this research, a novel family of learning rules called Beta Hebbian Learning (BHL) is thoroughly investigated to extract information from high-dimensional datasets by projecting the data onto low-dimensional (typically two dimensional) subspaces, improving the existing exploratory methods by providing a clear representation of data's internal structure. BHL applies a family of learning rules derived from the Probability Density Function (PDF) of the residual based on the beta distribution. This family of rules may be called Hebbian in that all use a simple multiplication of the output of the neural network with some function of the residuals after feedback. The derived learning rules can be linked to an adaptive form of Exploratory Projection Pursuit and with artificial distributions, the networks perform as the theory suggests they should: the use of different learning rules derived from different PDFs allows the identification of "interesting" dimensions (as far from the Gaussian distribution as possible) in high-dimensional datasets. This novel algorithm, BHL, has been tested over seven artificial datasets to study the behavior of BHL parameters, and was later applied successfully over four real datasets, comparing its results, in terms of performance, with other well-known Exploratory and projection models such as Maximum Likelihood Hebbian Learning (MLHL), Locally-Linear Embedding (LLE), Curvilinear Component Analysis (CCA), Isomap and Neural Principal Component Analysis (Neural PCA).

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

PubMed

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

2011-09-01

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

What School Leaders Are Doing to Support a Culture of Character: An Exploratory Study with Preschools in Singapore

ERIC Educational Resources Information Center

Carter, Margaret-Anne; Dasson, Merilyn

2017-01-01

This article discusses an exploratory study, reporting the practices of five principals leading character development in early childhood centers in Singapore. Acknowledging variations in leadership style, the pooled focus group findings show the common denominator is the principals' paradigm of authentic leadership informing a service-oriented…

Scale Development and Initial Tests of the Multidimensional Complex Adaptive Leadership Scale for School Principals: An Exploratory Mixed Method Study

ERIC Educational Resources Information Center

Özen, Hamit; Turan, Selahattin

2017-01-01

This study was designed to develop the scale of the Complex Adaptive Leadership for School Principals (CAL-SP) and examine its psychometric properties. This was an exploratory mixed method research design (ES-MMD). Both qualitative and quantitative methods were used to develop and assess psychometric properties of the questionnaire. This study…

[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.

Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test.

PubMed

Palmerini, Luca; Mellone, Sabato; Rocchi, Laura; Chiari, Lorenzo

2011-01-01

The Timed Up and Go is a clinical test to assess mobility in the elderly and in Parkinson's disease. Lately instrumented versions of the test are being considered, where inertial sensors assess motion. To improve the pervasiveness, ease of use, and cost, we consider a smartphone's accelerometer as the measurement system. Several parameters (usually highly correlated) can be computed from the signals recorded during the test. To avoid redundancy and obtain the features that are most sensitive to the locomotor performance, a dimensionality reduction was performed through principal component analysis (PCA). Forty-nine healthy subjects of different ages were tested. PCA was performed to extract new features (principal components) which are not redundant combinations of the original parameters and account for most of the data variability. They can be useful for exploratory analysis and outlier detection. Then, a reduced set of the original parameters was selected through correlation analysis with the principal components. This set could be recommended for studies based on healthy adults. The proposed procedure could be used as a first-level feature selection in classification studies (i.e. healthy-Parkinson's disease, fallers-non fallers) and could allow, in the future, a complete system for movement analysis to be incorporated in a smartphone.

[Priorization of facilitators for the implementation of medication review with follow-up service in Spanish community pharmacies through exploratory factor analysis].

PubMed

Gil, Modesta Inmaculada; Benrimoj, Shalom Isaac; Martínez-Martínez, Fernando; Cardero, Manuel; Gastelurrutia, Miguel Ángel

2013-01-01

to prioritize previously identified in Spain facilitators for the implementation of new Pharmaceutical Services that allow designing strategies for the implementation of Medication Review with follow-up (MRFup) service. Exploratory factor analysis (EFA). A draft of a questionnaire was performed based on a previous literature review and following the RAND/UCLA methodology. An expert panel worked with it and generated a definitive questionnaire which, after piloting, was used with a representative sample of pharmacists, owners or staff members, who were working in community pharmacy, using computer-assisted telephone interviewing (CATI) methodology. To understand underlying constructs in the questionnaire an EFA was performed. Different approaches were tested such as principal components factor analysis and principal axis factoring method. The best interpretability was achieved using the Factorization of Principal axis method with Direct Oblimin rotation, which explained the 40.0% of total variance. This produced four factors defined as: «Incentives», «External campaigns», «Expert in MRFup» and «Professionalism of the pharmacist». It can be stated that for implementation and sustainability of MRFup Service it is necessary being paid; also it must be explained to health professional and society in general. Practice of MRFup service demands pharmacists receiving a more clinical education and assuming more responsibilities as health professionals. Copyright © 2012 Elsevier España, S.L. All rights reserved.

Middle Level Principals' Parent Involvement Practices

ERIC Educational Resources Information Center

Tomichek-Michalowski, Tracie V.

2017-01-01

The purpose of the exploratory research study was to identify middle level principals' parent involvement practices. Parent involvement impacts students in positive ways, and a principal must have the ability to involve parents. The job description of a principal can be difficult to place on paper. Principals multitask throughout the day and often…

Genotype evaluation of cowpea seeds (Vigna unguiculata) using 1H qNMR combined with exploratory tools and solid-state NMR.

PubMed

Alves Filho, Elenilson G; Silva, Lorena M A; Teofilo, Elizita M; Larsen, Flemming H; de Brito, Edy S

2017-01-01

The ultimate aim of this study was to apply a non-targeted chemometric analysis (principal component analysis and hierarchical clustering analysis using the heat map approach) of NMR data to investigate the variability of organic compounds in nine genotype cowpea seeds, without any complex pre-treatment. In general, both exploratory tools show that Tvu 233, CE-584, and Setentão genotypes presented higher amount mainly of raffinose and Tvu 382 presented the highest content of choline and least content of raffinose. The evaluation of the aromatic region showed the Setentão genotype with highest content of niacin/vitamin B3 whereas Tvu 382 with lowest amount. To investigate rigid and mobile components in the seeds cotyledon, 13 C CP and SP/MAS solid-state NMR experiments were performed. The cotyledon of the cowpea comprised a rigid part consisting of starch as well as a soft portion made of starch, fatty acids, and protein. The variable contact time experiment suggests the presence of lipid-amylose complexes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

PubMed Central

Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-01-01

Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. PMID:24786942

Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

PubMed

Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-09-01

Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. © 2014 American Physical Therapy Association.

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…

Identity theft and consumers' reaction to preventive technological innovations.

PubMed

Ainscough, Thomas L; Brody, Richard G; Trocchia, Philip J

2007-08-01

The use of identification technology by commercial entities has broad and, for some consumers, disturbing social implications. This two-phase study was done to specify consumers' concerns regarding various identification technologies which may be encountered in retail environments. From the qualitative findings, a 26-item survey was constructed to quantify identified areas of concern with 303 survey participants (147 women and 156 men), whose mean age category was 30 to 39 years. Using exploratory factor analysis (principal components with varimax rotation), five dimensions of consumers' concern emerged: privacy, ethics, health, humanity, and complexity.

Cross-country Analysis of ICT and Education Indicators: An Exploratory Study

NASA Astrophysics Data System (ADS)

Pratama, Ahmad R.

2017-03-01

This paper explores the relationship between world ICT and education indicators by using the latest available data from World Bank and UNESCO in range of 2011-2014 with the help of different exploratory methods such as principal component analysis (PCA), factor analysis (FA), cluster analysis, and ordinary least square (OLS) regression. After dealing with all missing values, 119 countries were included in the final dataset. The findings show that most ICT and education indicators are highly associated with income of the respective country and therefore confirm the existence of digital divide in ICT utilization and participation gap in education between rich and poor countries. It also indicates that digital divide and participation gap is highly associated with each other. Finally, the findings also confirm reverse causality in ICT and education; higher participation rate in education increases technology utilization, which in turn helps promote better outcomes of education.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Job Stress and Coping Strategies of Elementary Principals: A Statewide Study

ERIC Educational Resources Information Center

Boyland, Lori

2011-01-01

The purpose of this exploratory study is to gather and examine data regarding the job-related stress of elementary public school principals in Indiana. Specific job issues that principals perceive as stressful are explored, as well as self-reported changes in the stress levels of experienced principals. Objectives of this research are to deepen…

The Relationship of Principal Resiliency to Job Satisfaction and Work Commitment: An Exploratory Study of K-12 Public School Principals in Florida

ERIC Educational Resources Information Center

Pepe, Jason

2011-01-01

The purpose of this study was to investigate characteristics associated with resilient school leaders. Principals juggle multiple responsibilities and work under increasingly stressful conditions. Despite recent role changes, added job responsibilities, and increased accountability, some principals remain remarkably resilient while working in a…

Principal Professional Development: A Multiple Case Exploratory Study of District-Led Aspiring Principal Programs through the Lens of Knowledge Management

ERIC Educational Resources Information Center

Barnes, Frank Derek

2015-01-01

Research establishes that a positive relationship exists between principal instructional leadership and student achievement (Brewer, 1993; Eberts and Stone, 1988; Hallinger and Heck, 1998; Leithwood, Seashore Louis, Anderson, and Wahlstrom, 2004). Likewise, research indicates that a principal's ability to influence the purpose and goals of a…

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…

Exploring the Relationships between Principals' Life Experiences and Transformational Leadership Behaviours

ERIC Educational Resources Information Center

Nash, Steve; Bangert, Art

2014-01-01

The primary objective of this research study was to explore the relationships between principals' life experiences and their transformational leadership behaviours. Over 212 public school principals completed both the lifetime leadership inventory (LLI) and the multifactor leadership questionnaire (MLQ). Exploratory and confirmatory factor…

Empowering Teachers: Characteristics, Strategies, and Practices of Successful Principals

ERIC Educational Resources Information Center

Ellis, Cailin Patrice

2012-01-01

This study implemented an exploratory mixed-methods design to better understand how the characteristics of a principal, specifically the strategies, behaviors, and actions, lead to the perception of empowerment as perceived by the teachers themselves. An expert panel identified three "highly successful" principals assigned to elementary…

An Examination of Principals' Leadership and Its Impact on Early Elementary Grades

ERIC Educational Resources Information Center

Hallissey, Megan

2017-01-01

This exploratory, qualitative multiple-site case study examined principals' expectations of teaching practices and children's learning for early elementary grade levels (K, 1st, 2nd, and 3rd). Specifically, this study investigated principals' understanding of developmentally appropriate practices regarding instructional methods, curriculum…

Principals' Perceptions of School Counselor Roles and Satisfaction with School Counseling Services

ERIC Educational Resources Information Center

Beesley, Denise; Frey, Lisa L.

2006-01-01

This study surveyed principals (N = 303) across the nation about their perceptions of school counselor roles and satisfaction with counseling services. Results from this exploratory study revealed that principals reported overall satisfaction with counseling services, although satisfaction varied across levels (elementary, middle school/junior…

Watch what happens: using a web-based multimedia platform to enhance intraoperative learning and development of clinical reasoning.

PubMed

Fingeret, Abbey L; Martinez, Rebecca H; Hsieh, Christine; Downey, Peter; Nowygrod, Roman

2016-02-01

We aim to determine whether observed operations or internet-based video review predict improved performance in the surgery clerkship. A retrospective review of students' usage of surgical videos, observed operations, evaluations, and examination scores were used to construct an exploratory principal component analysis. Multivariate regression was used to determine factors predictive of clerkship performance. Case log data for 231 students revealed a median of 25 observed cases. Students accessed the web-based video platform a median of 15 times. Principal component analysis yielded 4 factors contributing 74% of the variability with a Kaiser-Meyer-Olkin coefficient of .83. Multivariate regression predicted shelf score (P < .0001), internal clinical skills examination score (P < .0001), subjective evaluations (P < .001), and video website utilization (P < .001) but not observed cases to be significantly associated with overall performance. Utilization of a web-based operative video platform during a surgical clerkship is an independently associated with improved clinical reasoning, fund of knowledge, and overall evaluation. Thus, this modality can serve as a useful adjunct to live observation. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

An Examination of the Relationship between Principal Technology Leadership and Technology Integration in Urban Schools

ERIC Educational Resources Information Center

Draper, Kathryn L.

2013-01-01

The purpose of this exploratory/quantitative descriptive and correlational study was to examine the relationship between principal technology leadership and technology integration in urban schools. The technology activities of principals along with Organizational Health Instrument (OHI) survey outcomes perceived by their faculty were described and…

Mix and Match: What Principals Really Look for when Hiring Teachers

ERIC Educational Resources Information Center

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

2010-01-01

The vast majority of research and policy related to teacher quality focuses on the supply of teachers and ignores teacher demand. In particular, the important role of school principals in hiring teachers is rarely considered. Using interviews of school principals in a midsized Florida school district, we provide an exploratory mixed methods…

Emergence of Exploratory, Technical and Tactical Behavior in Small-Sided Soccer Games when Manipulating the Number of Teammates and Opponents.

PubMed

Torrents, Carlota; Ric, Angel; Hristovski, Robert; Torres-Ronda, Lorena; Vicente, Emili; Sampaio, Jaime

2016-01-01

The effects that different constraints have on the exploratory behavior, measured by the variety and quantity of different responses within a game situation, is of the utmost importance for successful performance in team sports. The aim of this study was to determine how the number of teammates and opponents affects the exploratory behavior of both professional and amateur players in small-sided soccer games. Twenty-two professional (age 25.6 ± 4.9 years) and 22 amateur (age 23.1 ± 0.7 years) male soccer players played three small-sided game formats (4 vs. 3, 4 vs. 5, and 4 vs. 7). These trials were video-recorded and a systematic observation instrument was used to notate the actions, which were subsequently analyzed by means of a principal component analysis and the dynamic overlap order parameter (measure to identify the rate and breadth of exploratory behavior on different time scales). Results revealed that a higher the number of opponents required for more frequent ball controls. Moreover, with a higher number of teammates, there were more defensive actions focused on protecting the goal, with more players balancing. In relation to attack, an increase in the number of opponents produced a decrease in passing, driving and controlling actions, while an increase in the number of teammates led to more time being spent in attacking situations. A numerical advantage led to less exploratory behavior, an effect that was especially clear when playing within a team of seven players against four opponents. All teams showed strong effects of the number of teammates on the exploratory behavior when comparing 5 vs 7 or 3 vs 7 teammates. These results seem to be independent of the players' level.

The Specific Level of Functioning Scale: construct validity, internal consistency and factor structure in a large Italian sample of people with schizophrenia living in the community.

PubMed

Mucci, Armida; Rucci, Paola; Rocca, Paola; Bucci, Paola; Gibertoni, Dino; Merlotti, Eleonora; Galderisi, Silvana; Maj, Mario

2014-10-01

The study aimed to assess the construct validity, internal consistency and factor structure of the Specific Levels of Functioning Scale (SLOF), a multidimensional instrument assessing real life functioning. The study was carried out in 895 Italian people with schizophrenia, all living in the community and attending the outpatient units of 26 university psychiatric clinics and/or community mental health departments. The construct validity of the SLOF was analyzed by means of the multitrait-multimethod approach, using the Personal and Social Performance (PSP) Scale as the gold standard. The factor structure of the SLOF was examined using both an exploratory principal component analysis and a confirmatory factor analysis. The six factors identified using exploratory principal component analysis explained 57.1% of the item variance. The examination of the multitrait-multimethod matrix revealed that the SLOF factors had high correlations with PSP factors measuring the same constructs and low correlations with PSP factors measuring different constructs. The confirmatory factor analysis (CFA) corroborated the 6-factor structure reported in the original validation study. Loadings were all significant and ranged from a minimum of 0.299 to a maximum of 0.803. The CFA model was adequately powered and had satisfactory goodness of fit indices (comparative fit index=0.927, Tucker-Lewis index=0.920 and root mean square error of approximation=0.047, 95% CI 0.045-0.049). The present study confirms, in a large sample of Italian people with schizophrenia living in the community, that the SLOF is a reliable and valid instrument for the assessment of social functioning. It has good construct validity and internal consistency, and a well-defined factor structure. Copyright © 2014 Elsevier B.V. All rights reserved.

Cenesthopathy and Subjective Cognitive Complaints: An Exploratory Study in Schizophrenia.

PubMed

Jimeno, Natalia; Vargas, Martin L

2018-01-01

Cenesthopathy is mainly associated with schizophrenia; however, its neurobiological basis is nowadays unclear. The general objective was to explore clinical correlates of cenesthopathy and subjective cognitive complaints in schizophrenia. Participants (n = 30) meeting DSM-IV criteria for psychotic disorder were recruited from a psychiatry unit and assessed with: Association for Methodology and Documentation in Psychiatry (AMDP) system, Positive and Negative Syndrome Scale, Frankfurt Complaint Questionnaire (FCQ), and the Bonn Scale for the Assessment of Basic Symptoms (BSABS). For quantitative variables, means and Spearman correlation coefficients were calculated. Linear regression following backward method and principal component analysis with varimax rotation were used. 83.3% of subjects (73.3% male, mean age, 31.5 years) presented any type of cenesthopathy; all types of cenesthetic basic symptoms were found. Cenesthetic basic symptoms significantly correlated with the AMDP category "fear and anancasm," FCQ total score, and BSABS cognitive thought disturbances. In the regression analysis only 1 predictor, cognitive thought disturbances, entered the model. In the principal component analysis, a main component which accounted for 22.69% of the variance was found. Cenesthopathy, as assessed with the Bonn Scale (BSABS), is mainly associated with cog-nitive abnormalities including disturbances of thought initiative and mental intentionality, of receptive speech, and subjective retardation or pressure of thoughts. © 2018 S. Karger AG, Basel.

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…

School Inspections Still in Dispute--An Exploratory Study of School Principals' Perceptions of School Inspections

ERIC Educational Resources Information Center

Bitan, Kristin; Haep, Anna; Steins, Gisela

2015-01-01

This paper assesses attitudes of principals from one German federal state toward school inspections. The discussion about school inspections and their acceptance can be imbedded into theoretical reflections on the design of and approach to feedback in social psychology. In our study, 50 school principals were interviewed about their attitudes…

An Exploratory Study on Principals' Conceptions about Their Role as School Leaders

ERIC Educational Resources Information Center

Devos, Geert; Bouckenooghe, Dave

2009-01-01

This inquiry, by means of the case study method, explored how principals' conceptions about their role as school leader contribute to a better understanding of their leadership behavior and how this is related to school climate. The results indicated that differences of how principals conceive their leadership role are related, indirectly through…

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

PubMed

Todhunter, Fern

2015-07-01

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

Existential Measurement: A Factor Analytic Study of Some Current Psychometric Instruments.

ERIC Educational Resources Information Center

Thauberger, Patrick C.; And Others

1982-01-01

Research in existentialism and ontology has given rise to several psychometric instruments. Used both exploratory and confirmatory principal-factor analyses to study relationships among 16 existential scales. Exploratory factor analysis provided some support of the theory that the avoidance of existential confrontation is a central function of…

Caring Leadership in Schools: Findings from Exploratory Analyses

ERIC Educational Resources Information Center

Louis, Karen Seashore; Murphy, Joseph; Smylie, Mark

2016-01-01

Purpose: This article (1) analyzes and synthesizes literatures from philosophy and education to propose a conceptual framework for caring in schools and caring school leadership and (2) reports the results of an exploratory analysis of the relationship of caring principal leadership to school-level supports for student academic learning.…

Counselor Education and Educational Administration: An Exploratory Survey of Collaboration

ERIC Educational Resources Information Center

Perusse, Rachelle; Goodnough, Gary E.; Bouknight, Tamisha

2007-01-01

One way to inform educational administration faculty and future school principals about the role of the school counselor is for counselor educators to collaborate with educational administration faculty. However, there are very few recommendations about how these faculty members might collaborate. In an exploratory national survey, counselor…

Exploratory Analysis of Exercise Adherence Patterns with Sedentary Pregnant Women

PubMed Central

Yeo, SeonAe; Cisewski, Jessi; Lock, Eric F.; Marron, J. S.

2010-01-01

Background It is not well understood how sedentary women who wish to engage in regular exercise adhere to interventions during pregnancy and what factors may influence adherence over time. Objective To examine longitudinal patterns of pregnant women’s adherence to exercise. Methods Exploratory secondary data analyses were carried out with 124 previously sedentary pregnant women (ages 31 ± 5 years; 85% non-Hispanic White) from a randomized controlled trial. Daily exercise logs (n = 92) from 18 through 35 weeks of gestation were explored using linear regression, functional data, and principal component analyses. Results Adherence decreased as gestation week increased (p < .001); the top adherers maintained levels of adherence, and the bottom adherers decreased levels of adherence; and adherence pattern was influenced by types of exercise throughout the study period. Discussion Exercise behavior patterns were explored in a randomized controlled trial study, using chronometric data on exercise attendance. A new analytic approach revealed that sedentary pregnant women may adopt exercise habits differently from other populations. PMID:20585224

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

An Exploratory Study of the Ways in Which Elementary School Principals Use Their Emotional Intelligence to Address Conflict in Their Educational Organizations

ERIC Educational Resources Information Center

Espinoza, Lorissa

2016-01-01

Purpose. This study described the knowledge, skills, behaviors, and strategies associated with emotional intelligence (EI) that elementary school principals used to address conflict in their organizations. This study also determined the impact EI had on elementary school principals' perceptions of their ability to lead their organizations. This…

School Counselors and Principals: Different Perceptions of Relationship, Leadership, and Training

ERIC Educational Resources Information Center

Armstrong, Stephen A.; MacDonald, Jane H.; Stillo, Sandy

2010-01-01

This study examined school counselors' and principals' perceptions of their relationship and the effectiveness of their respective professional preparation programs. An exploratory factor analysis (n = 615) revealed three salient factors: relationship quality, campus leadership and training satisfaction. Kruskal-Wallis tests revealed statistically…

Quantitative analysis of NMR spectra with chemometrics

NASA Astrophysics Data System (ADS)

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

2008-01-01

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

Measuring trust in nurses - Psychometric properties of the Trust in Nurses Scale in four countries.

PubMed

Stolt, Minna; Charalambous, Andreas; Radwin, Laurel; Adam, Christina; Katajisto, Jouko; Lemonidou, Chryssoula; Patiraki, Elisabeth; Sjövall, Katarina; Suhonen, Riitta

2016-12-01

The purpose of this study was to examine psychometric properties of three translated versions of the Trust in Nurses Scale (TNS) and cancer patients' perceptions of trust in nurses in a sample of cancer patients from four European countries. A cross-sectional, cross-cultural, multi-site survey design was used. The data were collected with the Trust in Nurses Scale from patients with different types of malignancies in 17 units within five clinical sites (n = 599) between 09/2012 and 06/2014. Data were analyzed using descriptive and inferential statistics, multivariate methods and psychometrics using exploratory factor analysis, Cronbach's alpha coefficients, item analysis and Rasch analysis. The psychometric properties of the data were consistent in all countries. Within the exploratory factor analysis the principal component analysis supported the one component structure (unidimensionality) of the TNS. The internal consistency reliability was acceptable. The Rasch analysis supported the unidimensionality of the TNS cross-culturally. All items of the TNS demonstrated acceptable goodness-of-fit to the Rasch model. Cancer patients trusted nurses to a great extent although between-country differences were found. The Trust in Nurses Scale proved to be a valid and reliable tool for measuring patients' trust in nurses in oncological settings in international contexts. Copyright © 2016 Elsevier Ltd. All rights reserved.

An Exploratory Study of the Relationship between Elementary Principals' Perceptions of Their Leadership Behaviors and the Impact on One Year of Reading Achievement Scores

ERIC Educational Resources Information Center

Smith, Debra

2009-01-01

The purpose of this study was to explore the relationship between principals' perceptions of their learning-centered leadership behaviors and one year of reading achievement scores. Perceptions of principals were gathered from 31 out of 42 elementary schools in a district located in Central Virginia. This study explored the relationship between…

Quality assurance of the clinical learning environment in Austria: Construct validity of the Clinical Learning Environment, Supervision and Nurse Teacher Scale (CLES+T scale).

PubMed

Mueller, Gerhard; Mylonas, Demetrius; Schumacher, Petra

2018-07-01

Within nursing education, the clinical learning environment is of a high importance in regards to the development of competencies and abilities. The organization, atmosphere, and supervision in the clinical learning environment are only a few factors that influence this development. In Austria there is currently no valid instrument available for the evaluation of influencing factors. The aim of the study was to test the construct validity with principal component analysis as well as the internal consistency of the German Clinical Learning Environment, Supervision and Teacher Scale (CLES+T scale) in Austria. The present validation study has a descriptive-quantitative cross-sectional design. The sample consisted of 385 nursing students from thirteen training institutions in Austria. The data collection was carried out online between March and April 2016. Starting with a polychoric correlation matrix, a parallel analysis with principal component extraction and promax rotation was carried out due to the ordinal data. The exploratory ordinal factor analysis supported a four-component solution and explained 73% of the total variance. The internal consistency of all 25 items reached a Cronbach's α of 0.95 and the four components ranged between 0.83 and 0.95. The German version of the CLES+T scale seems to be a useful instrument for identifying potential areas of improvement in clinical practice in order to derive specific quality measures for the practical learning environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Exploring Principals' Instructional Leadership Practices in Malaysia: Insights and Implications

ERIC Educational Resources Information Center

Harris, Alma; Jones, Michelle; Cheah, Kenny Soon Lee; Devadason, Edward; Adams, Donnie

2017-01-01

Purpose: The purpose of this paper is to outline the findings from a small-scale, exploratory, study of principals' instructional leadership practice in Malaysian primary schools. The dimensions and functions of instructional leadership, explicitly explored in this study, are those outlined in the Hallinger and Murphy's (1985) model.…

Latina/o School Principals as Instructional Leaders

ERIC Educational Resources Information Center

Niño, Juan Manuel; Hernandez, Frank; Valle, Fernando; McPhetres, Jon

2017-01-01

Focusing on the fundamental purpose of schools as student learning, this exploratory study attempts to better understand the role of Latino principals' activities that are centered on the teaching and learning process. Specifically, the authors were interested in comparing the instructional leadership literature (what do instructional leaders do)…

Effective Middle Level Teaching: Perceptions on the Preparedness of Newly Hired Teachers

ERIC Educational Resources Information Center

Howell, Penny B.; Cook, Chris; Faulkner, Shawn A.

2013-01-01

This interpretive, exploratory study utilized survey methodology to document middle level principals' perceptions of effective teaching practices and the preparedness of newly hired middle level teachers. The findings suggest that principals' descriptions of effective teaching differ from their descriptions of effective teachers. Additionally,…

Principals' Learning Mechanisms: Exploring an Emerging Construct

ERIC Educational Resources Information Center

Schechter, Chen; Qadach, Mowafaq

2016-01-01

This exploration of principal learning mechanisms (PLM) to support a learning-centered school aimed to develop, field-test, and validate a PLM-measuring instrument. Following exploratory and confirmatory factor analyses of items to examine factorial validity, the developed scale was correlated with other work-related established constructs (e.g.,…

Delusions in first-episode psychosis: Principal component analysis of twelve types of delusions and demographic and clinical correlates of resulting domains.

PubMed

Paolini, Enrico; Moretti, Patrizia; Compton, Michael T

2016-09-30

Although delusions represent one of the core symptoms of psychotic disorders, it is remarkable that few studies have investigated distinct delusional themes. We analyzed data from a large sample of first-episode psychosis patients (n=245) to understand relations between delusion types and demographic and clinical correlates. First, we conducted a principal component analysis (PCA) of the 12 delusion items within the Scale for the Assessment of Positive Symptoms (SAPS). Then, using the domains derived via PCA, we tested a priori hypotheses and answered exploratory research questions related to delusional content. PCA revealed five distinct components: Delusions of Influence, Grandiose/Religious Delusions, Paranoid Delusions, Negative Affect Delusions (jealousy, and sin or guilt), and Somatic Delusions. The most prevalent type of delusion was Paranoid Delusions, and such delusions were more common at older ages at onset of psychosis. The level of Delusions of Influence was correlated with the severity of hallucinations and negative symptoms. We ascertained a general relationship between different childhood adversities and delusional themes, and a specific relationship between Somatic Delusions and childhood neglect. Moreover, we found higher scores on Delusions of Influence and Negative Affect Delusions among cannabis and stimulant users. Our results support considering delusions as varied experiences with varying prevalences and correlates. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A construction and validation of a Freshman Stress Questionnaire: an exploratory study.

PubMed

Boujut, Emilie; Bruchon-Schweitzer, Marilou

2009-04-01

A stress questionnaire for freshmen was developed and administered to 1,102 French students at the beginning of the term (T1). A Principal Component Analysis of responses, followed by varimax and oblique rotations, yielded four factors accounting for 58% of the total variance. Factors were identified as academic stress, university's dysfunctions, feelings of loneliness, and problems with close relations. Associations were observed between scores on these factors and on personal variables measured at the same time (T1), namely, neuroticism, self-esteem, and two coping strategies, as well as variables measured at the end of the term (T2), depressive symptoms, eating disorders, somatic symptoms, and life satisfaction.

Principals' Perception and Self-Efficacy: Addressing Achievement in a Post Annual Yearly Progress Environment

ERIC Educational Resources Information Center

Staumont, John

2017-01-01

Purpose: The purpose of this single-case study was to explore principals' perceptions of self-efficacy beliefs as effective instructional leaders during a period of educational transition in a semiurban, unified school district in Southern California. Methodology: The researcher used exploratory case study, conducting semistructured, open-ended,…

Exploring Collaborative Culture and Leadership in Large High Schools

ERIC Educational Resources Information Center

Jeffers, Michael P.

2013-01-01

The purpose of this exploratory study was to analyze how high school principals approached developing a collaborative culture and providing collaborative leadership in a large high school setting. The population sample for this study was 82 principals of large comprehensive high schools of grades 9 through 12 or some combination thereof with…

Leadership Styles and Multicultural Education Approaches: An Exploration of Their Relationship

ERIC Educational Resources Information Center

Zembylas, Michalinos; Iasonos, Sotiroula

2010-01-01

This paper discusses the results of an exploratory study that sought to identify elementary school principals' perspectives of diversity and multiculturalism in relation to their leadership styles. In particular, we examine the approaches to multiculturalism of a group of principals who lead multicultural schools in Cyprus and analyse the findings…

Experiences of School Principals with Newcomers from War-Affected Countries in Africa

ERIC Educational Resources Information Center

Okoko, Janet Mola

2011-01-01

This article is based on the results of an exploratory study of experiences of 2 urban school principals about leading schools with immigrants from war-affected countries in Africa. It examines how they perceived their preparation for multicultural leadership, and explores lessons that leadership development institutions can learn from their…

What Are the Characteristics of Principals Identified As Effective by Teachers?

ERIC Educational Resources Information Center

Fowler, William J., Jr.

This exploratory study investigated which characteristics of a principal are identified as effective by teachers in the same school setting. The data were obtained from the Schools and Staffing Study of 1988, from the National Center for Education Statistics (NCES). The Teacher Questionnaire of the Schools and Staffing Survey (SASS) questioned…

Principals' Views on Teachers' Professional Development

ERIC Educational Resources Information Center

Nabhani, Mona; Nicolas, Maureen O'Day; Bahous, Rima

2014-01-01

This article is an account of a study that aimed to elicit the perceptions of school principals and middle managers in Lebanon on teachers' professional development (PD) and to promote an understanding of PD that extends beyond workshops. The study was qualitative and exploratory and used online interviewing to collect data. Questions were emailed…

Principals' Sensemaking of Coaching for Ambitious Reading Instruction in a High-Stakes Accountability Policy Environment

ERIC Educational Resources Information Center

Matsummura, Lindsay Clare; Wang, Elaine

2014-01-01

In the present exploratory qualitative study we examine the contextual factors that influenced the implementation of a multi-year comprehensive literacy-coaching program (Content-Focused Coaching, CFC). We argue that principals' sensemaking of the dialogic instructional strategies promoted by the program in light of high-stakes accountability…

Human Resource Support for School Principals in Two, Urban School Districts: An Exploratory Study

ERIC Educational Resources Information Center

Lochmiller, Chad R.

2010-01-01

School districts are increasingly focused on instructional practice in classrooms. Many urban school districts have shifted decision-making responsibility to school principals in order to improve instruction. This reform strategy has been referred to as decentralization or school-based management. Decentralization has a significant influence on…

How Principals Learn to Lead: The Comparative Influence of On-the-Job Experiences, Administrator Credential Programs, and the ISLLC Standards in the Development of Leadership Expertise among Urban Public School Principals

ERIC Educational Resources Information Center

Davis, Stephen H.; Leon, Ronald J.; Fultz, Miriam

2013-01-01

The purpose of this study was to examine the comparative influence of college administrator credential programs, on-the-job experiences, and the ISLLC Standards in the development of leadership expertise among urban public school principals. An exploratory, ex-post-facto research design used both quantitative and qualitative approaches. A survey…

Burnout Experience of Teachers Serving Students with Emotional Behavioral Disorders in Grades PreK-8 within Non-Public Special Education Day Schools

ERIC Educational Resources Information Center

Hill, Kendra A.

2011-01-01

This exploratory study examined the relationships between five predictor variables identified by the literature (age, years of special education teaching experience, level of emotional behavioral disorders (EBD) preparation, principal support, and principal feedback) and two higher order terms (age and years of special education teaching…

Developing School Leaders: Practitioner Growth during an Advanced Leadership Development Program for Principals and Administrator-Trained Teachers

ERIC Educational Resources Information Center

Browne-Ferrigno, Tricia

2007-01-01

This article shares findings from an exploratory case study about an advanced school leadership development program designed specifically for practicing principals and administrator-trained teachers. The program was designed to help a high-need rural district transform its principalship from school management into learner-center leadership while…

Urban School Principals and the "No Child Left Behind" Act

ERIC Educational Resources Information Center

Gardiner, Mary E.; Canfield-Davis, Kathy; Anderson, Keith LeMar

2009-01-01

This exploratory study investigated how six practicing school principals responded to the requirements of the No Child Left Behind law (United States Congress Public Law 107-110, 2002, January, No Child Left Behind Act, http://www.ed.gov/policy/elsec/leg/esea02/107-110.pdf ) in light of the multicultural leadership demands presented by an urban…

Early discrimination of nasopharyngeal carcinoma based on tissue deoxyribose nucleic acid surface-enhanced Raman spectroscopy analysis

NASA Astrophysics Data System (ADS)

Qiu, Sufang; Li, Chao; Lin, Jinyong; Xu, Yuanji; Lu, Jun; Huang, Qingting; Zou, Changyan; Chen, Chao; Xiao, Nanyang; Lin, Duo; Chen, Rong; Pan, Jianji; Feng, Shangyuan

2016-12-01

Surface-enhanced Raman spectroscopy (SERS) was employed to detect deoxyribose nucleic acid (DNA) variations associated with the development of nasopharyngeal carcinoma (NPC). Significant SERS spectral differences between the DNA extracted from early NPC, advanced NPC, and normal nasopharyngeal tissue specimens were observed at 678, 729, 788, 1337, 1421, 1506, and 1573 cm-1, which reflects the genetic variations in NPC. Principal component analysis combined with discriminant function analysis for early NPC discrimination yielded a diagnostic accuracy of 86.8%, 92.3%, and 87.9% for early NPC, advanced NPC, and normal nasopharyngeal tissue DNA, respectively. In this exploratory study, we demonstrated the potential of SERS for early detection of NPC based on the DNA molecular study of biopsy tissues.

Intrinsic and extrinsic motivation for smoking cessation.

PubMed

Curry, S; Wagner, E H; Grothaus, L C

1990-06-01

An intrinsic-extrinsic model of motivation for smoking cessation was evaluated with 2 samples (ns = 1.217 and 151) of smokers who requested self-help materials for smoking cessation. Exploratory and confirmatory principal components analysis on a 36-item Reasons for Quitting (RFQ) scale supported the intrinsic-extrinsic motivation distinction. A 4-factor model, with 2 intrinsic dimensions (concerns about health and desire for self-control) and 2 extrinsic dimensions (immediate reinforcement and social influence), was defined by 20 of the 36 RFQ items. The 20-item measure demonstrated moderate to high levels of internal consistency and convergent and discriminant validity. Logistic regression analyses indicated that smokers with higher levels of intrinsic relative to extrinsic motivation were more likely to achieve abstinence from smoking.

Development and psychometric properties of the Student Worry Questionnaire-30.

PubMed

Osman, A; Gutierrez, P M; Downs, W R; Kopper, B A; Barrios, F X; Haraburda, C M

2001-02-01

Described are the development and initial psychometric properties (Ns = 50 and 188) of a self-report measure, the Student Worry Questionnaire-30, for use with college undergraduates. Exploratory principal components analyses (Ns = 388, 350, and 396) with oblimin rotation indicated six domains of worrisome thinking, financial-related concerns, significant others' well-being, social adequacy concerns, academic concerns, and general anxiety symptoms. The total score and scale scores showed internal consistency of .80 to .94. Also, test-retest reliability analyses (.75 to .80) support consistency of responses over 4 wk. Strong evidence for convergent validity) was indicated. Confirmatory factor analysis confirmed the fit of the 6-factor oblique model. Limitations of the present studies, and directions for research are discussed.

A Multiple Case Study of the Literacy Instructional Leadership Behaviors of Elementary Principals in North Carolina

ERIC Educational Resources Information Center

Herridge, Robin Lea

2013-01-01

The purpose of this study was to explore the literacy instructional leadership behaviors of principals in two high poverty elementary schools in North Carolina who have experienced success with student growth in reading achievement over a three year period. This was a qualitative exploratory multiple case study. Data was gathered from 21…

K-12 School Leaders and School Crisis: An Exploration of Principals' School Crisis Competencies and Preparedness

ERIC Educational Resources Information Center

McCarty, Sean P.

2012-01-01

On any given day, principals could find themselves faced with a situation that could define their roles as crisis leaders. This dissertation research offers an exploratory study in the field of crisis response and educational leadership. From experts in the field of crisis response, the author compiled a list of crisis management competencies…

An Exploratory Investigation of the Roles and Responsibilities of Elementary and Secondary School Principal Supervisors

ERIC Educational Resources Information Center

Spence, Jane W.

2015-01-01

This study explored elementary and secondary versions of a new principal supervisor role in order to determine whether there might be marked differences in the functions and responsibilities at each level. The new iteration of this role, which is becoming increasingly popular in large urban school districts, requires those occupying it not only to…

Lower risk taking and exploratory behavior in alcohol-preferring sP rats than in alcohol non-preferring sNP rats in the multivariate concentric square field (MCSF) test.

PubMed

Roman, Erika; Colombo, Giancarlo

2009-12-14

The present investigation continues previous behavioral profiling studies of selectively bred alcohol-drinking and alcohol non-drinking rats. In this study, alcohol-naïve adult Sardinian alcohol-preferring (sP) and non-preferring (sNP) rats were tested in the multivariate concentric square field (MCSF) test. The MCSF test has an ethoexperimental approach and measures general activity, exploration, risk assessment, risk taking, and shelter seeking in laboratory rodents. The multivariate design enables behavioral profiling in one and the same test situation. Age-matched male Wistar rats were included as a control group. Five weeks after the first MCSF trial, a repeated testing was done to explore differences in acquired experience. The results revealed distinct differences in exploratory strategies and behavioral profiles between sP and sNP rats. The sP rats were characterized by lower activity, lower exploratory drive, higher risk assessment, and lower risk taking behavior than in sNP rats. In the repeated trial, risk-taking behavior was almost abolished in sP rats. When comparing the performance of sP and sNP rats with that of Wistar rats, the principal component analysis revealed that the sP rats were the most divergent group. The vigilant behavior observed in sP rats with low exploratory drive and low risk-taking behavior is interpreted here as high innate anxiety-related behaviors and may be related to their propensity for high voluntary alcohol intake and preference. We suggest that the different lines of alcohol-preferring rats with different behavioral characteristics constitute valuable animal models that mimic the heterogeneity in human alcohol dependence.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

The stress response and exploratory behaviour in Yucatan minipigs (Sus scrofa): Relations to sex and social rank.

PubMed

Adcock, Sarah J J; Martin, Gerard M; Walsh, Carolyn J

2015-12-01

According to the coping styles hypothesis, an individual demonstrates an integrated behavioural and physiological response to environmental challenge that is consistent over time and across situations. Individual consistency in behavioural responses to challenge has been documented across the animal kingdom. Comparatively few studies, however, have examined inter-individual variation in the physiological response, namely glucocorticoid and catecholamine levels, the stress hormones secreted by the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system, respectively. Variation in coping styles between individuals may be explained in part by differences in social rank and sex. Using 20 Yucatan minipigs (Sus scrofa) we: (1) investigated the existence of consistent inter-individual variation in exploratory behaviour and the hormonal stress response, and tested for correlations as predicted by the coping styles hypothesis; and (2) evaluated whether inter-individual behavioural and hormonal variation is related to social rank and sex. Salivary stress biomarkers (cortisol, alpha-amylase, chromogranin A) were assessed in the presence and absence of a stressor consisting of social isolation in a crate for 10 min. Principal components analysis on a set of behavioural variables revealed two traits, which we labelled exploratory tendency and neophobia. Neither exploratory tendency nor neophobia predicted the physiological stress response. Subordinate pigs exhibited higher catecholamine levels compared to dominant conspecifics. We observed sex differences in the repeatability of salivary stress markers and reactivity of the stress systems. The results do not provide support for the existence of behavioural-physiological coping styles in pigs. Sex is an important determinant of the physiological stress response and warrants consideration in research addressing behavioural and hormonal variation. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploratory Research and Development Fund, FY 1990

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

Not Available

1992-05-01

The Lawrence Berkeley Laboratory Exploratory R D Fund FY 1990 report is compiled from annual reports submitted by principal investigators following the close of the fiscal year. This report describes the projects supported and summarizes their accomplishments. It constitutes a part of an Exploratory R D Fund (ERF) planning and documentation process that includes an annual planning cycle, projection selection, implementation, and review. The research areas covered in this report are: Accelerator and fusion research; applied science; cell and molecular biology; chemical biodynamics; chemical sciences; earth sciences; engineering; information and computing sciences; materials sciences; nuclear science; physics and research medicinemore » and radiation biophysics.« less

Staff Perceptions of Professional Development and Empowerment as Long-Term Leadership Tasks of School Principals in South African Schools: An Exploratory Study

ERIC Educational Resources Information Center

van Niekerk, Eldridge; Muller, Hélène

2017-01-01

This article reports on the perceptions of school staff of professional development and empowerment as part of the long-term leadership task of principals. The long-term leadership model was used as a theoretical framework to quantitatively determine the perceptions of 118 teachers and education managers in approximately 100 schools throughout…

Inhibitors and facilitators of willingness to participate (WTP) in an HIV vaccine trial: construction and initial validation of the Inhibitors and Facilitators of Willingness to Participate Scale (WPS) among women at risk for HIV infection.

PubMed

Fincham, Dylan; Kagee, Ashraf; Swartz, Leslie

2010-04-01

A psychometric scale assessing inhibitors and facilitators of willingness to participate (WTP) in an HIV vaccine trial has not yet been developed. This study aimed to construct and derive the exploratory factor structure of such a scale. The 35-item Inhibitors and Facilitators of Willingness to Participate Scale (WPS) was developed and administered to a convenience sample of 264 Black females between the ages of 16 and 49 years living in an urban-informal settlement near Cape Town. The subscales of the WPS demonstrated good internal consistency with Cronbach's alpha coefficients ranging between 0.69 and 0.82. A principal components exploratory factor analysis revealed the presence of five latent factors. The factors, which accounted for 45.93% of the variance in WTP, were (1) personal costs, (2) safety and convenience, (3) stigmatisation, (4) personal gains and (5) social approval and trust. Against the backdrop of the study limitations, these results provide initial support for the reliability and construct validity of the WPS among the most eligible trial participants in the Western Cape of South Africa.

Using Structural Equation Modeling To Fit Models Incorporating Principal Components.

ERIC Educational Resources Information Center

Dolan, Conor; Bechger, Timo; Molenaar, Peter

1999-01-01

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

Prediction With Dimension Reduction of Multiple Molecular Data Sources for Patient Survival.

PubMed

Kaplan, Adam; Lock, Eric F

2017-01-01

Predictive modeling from high-dimensional genomic data is often preceded by a dimension reduction step, such as principal component analysis (PCA). However, the application of PCA is not straightforward for multisource data, wherein multiple sources of 'omics data measure different but related biological components. In this article, we use recent advances in the dimension reduction of multisource data for predictive modeling. In particular, we apply exploratory results from Joint and Individual Variation Explained (JIVE), an extension of PCA for multisource data, for prediction of differing response types. We conduct illustrative simulations to illustrate the practical advantages and interpretability of our approach. As an application example, we consider predicting survival for patients with glioblastoma multiforme from 3 data sources measuring messenger RNA expression, microRNA expression, and DNA methylation. We also introduce a method to estimate JIVE scores for new samples that were not used in the initial dimension reduction and study its theoretical properties; this method is implemented in the R package R.JIVE on CRAN, in the function jive.predict.

Psychometric analysis of the Brisbane Practice Environment Measure (B-PEM).

PubMed

Flint, Anndrea; Farrugia, Charles; Courtney, Mary; Webster, Joan

2010-03-01

To undertake rigorous psychometric testing of the newly developed contemporary work environment measure (the Brisbane Practice Environment Measure [B-PEM]) using exploratory factor analysis and confirmatory factor analysis. Content validity of the 33-item measure was established by a panel of experts. Initial testing involved 195 nursing staff using principal component factor analysis with varimax rotation (orthogonal) and Cronbach's alpha coefficients. Confirmatory factor analysis was conducted using data from a further 983 nursing staff. Principal component factor analysis yielded a four-factor solution with eigenvalues greater than 1 that explained 52.53% of the variance. These factors were then verified using confirmatory factor analysis. Goodness-of-fit indices showed an acceptable fit overall with the full model, explaining 21% to 73% of the variance. Deletion of items took place throughout the evolution of the instrument, resulting in a 26-item, four-factor measure called the Brisbane Practice Environment Measure-Tested. The B-PEM has undergone rigorous psychometric testing, providing evidence of internal consistency and goodness-of-fit indices within acceptable ranges. The measure can be utilised as a subscale or total score reflective of a contemporary nursing work environment. An up-to-date instrument to measure practice environment may be useful for nursing leaders to monitor the workplace and to assist in identifying areas for improvement, facilitating greater job satisfaction and retention.

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

PubMed

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

2016-11-28

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

A Multilevel Exploratory Study of the Relationship between Teachers' Perceptions of Principals' Instructional Support and Group Norms for Instruction in Elementary Schools

ERIC Educational Resources Information Center

Goddard, Yvonne L.; Neumerski, Christine M.; Goddard, Roger D.; Salloum, Serena J.; Berebitsky, Daniel

2010-01-01

At a time when educators and policy makers are focused on improving outcomes for all children, we believe it is essential to understand better the ways in which principals may influence instructional norms in their schools. Our literature review led us to believe that a combination of leadership approaches is important for supporting teachers' use…

Emotionality in growing pigs: is the open field a valid test?

PubMed

Donald, Ramona D; Healy, Susan D; Lawrence, Alistair B; Rutherford, Kenneth M D

2011-10-24

The ability to assess emotionality is important within animal welfare research. Yet, for farm animals, few tests of emotionality have been well validated. Here we investigated the construct validity of behavioural measures of pig emotionality in an open-field test by manipulating the experiences of pigs in three ways. In Experiment One (pharmacological manipulation), pigs pre-treated with Azaperone, a drug used to reduce stress in commercial pigs, were more active, spent more time exploring and vocalised less than control pigs. In Experiment Two (social manipulation), pigs that experienced the open-field arena with a familiar companion were also more exploratory, spent less time behaviourally idle, and were less vocal than controls although to a lesser degree than in Experiment One. In Experiment Three (novelty manipulation), pigs experiencing the open field for a second time were less active, explored less and vocalised less than they had done in the first exposure to the arena. A principal component analysis was conducted on data from all three trials. The first two components could be interpreted as relating to the form (cautious to exploratory) and magnitude (low to high arousal) of the emotional response to open-field testing. Based on these dimensions, in Experiment One, Azaperone pigs appeared to be less fearful than saline-treated controls. However, in Experiment Two, exposure to the arena with a conspecific did not affect the first two dimensions but did affect a third behavioural dimension, relating to oro-nasal exploration of the arena floor. In Experiment Three, repeat exposure altered the form but not the magnitude of emotional response: pigs were less exploratory in the second test. In conclusion, behavioural measures taken from pigs in an open-field test are sensitive to manipulations of their prior experience in a manner that suggests they reflect underlying emotionality. Behavioural measures taken during open-field exposure can be useful for making assessments of both pig emotionality and of their welfare. Copyright © 2011 Elsevier Inc. All rights reserved.

Exploratory Research and Development Fund, FY 1990. Report on Lawrence Berkeley Laboratory

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

Not Available

1992-05-01

The Lawrence Berkeley Laboratory Exploratory R&D Fund FY 1990 report is compiled from annual reports submitted by principal investigators following the close of the fiscal year. This report describes the projects supported and summarizes their accomplishments. It constitutes a part of an Exploratory R&D Fund (ERF) planning and documentation process that includes an annual planning cycle, projection selection, implementation, and review. The research areas covered in this report are: Accelerator and fusion research; applied science; cell and molecular biology; chemical biodynamics; chemical sciences; earth sciences; engineering; information and computing sciences; materials sciences; nuclear science; physics and research medicine and radiationmore » biophysics.« less

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

USGS Publications Warehouse

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

1981-01-01

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

Shipboard Crew Fatigue, Safety and Reduced Manning

DOT National Transportation Integrated Search

1990-11-01

This report describes an exploratory first phase of an investigation of human stress and : fatigue in the merchant marine. Its principal purposes were to: survey the effects of : fatigue on human performance in the transportation industries; describe...

Principal component regression analysis with SPSS.

PubMed

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

2003-06-01

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

The Effects of Training on a Young Child with Cortical Visual Impairment: An Exploratory Study.

ERIC Educational Resources Information Center

Lueck, Amanda Hall; Dornbusch, Helen; Hart, Jeri

1999-01-01

This exploratory study investigated the effects of the components of visual environmental management, visual skills training, and visually dependent task training on the performance of visual behaviors of a toddler with multiple disabilities including cortical visual impairment. Training components were implemented by the mother during daily…

A Progress Report on an Exploratory Mathematics Course: Incorporating a Programming Component

ERIC Educational Resources Information Center

Goldberg, Robert; Waxman, Jerry

2004-01-01

This paper reports on an ongoing effort to incorporate a programming component into exploratory mathematics courses and analyzes some of the many practical considerations required for successfully managing such a course in large lecture hall classes. Two pedagogical paradigms (top-down and bottom-up) are compared and contrasted for teaching Visual…

A Comparison of Human Narrative Coding of Redemption and Automated Linguistic Analysis for Understanding Life Stories.

PubMed

Weston, Sara J; Cox, Keith S; Condon, David M; Jackson, Joshua J

2016-10-01

The majority of life narrative research is performed using trained human coders. In contrast, automated linguistic analysis is oft employed in the study of verbal behaviors. These two methodological approaches are directly compared to determine the utility of automated linguistic analysis for the study of life narratives. In a study of in-person interviews (N = 158) and a second study of life stories collected online (N = 242), redemption scores are compared to the output of the Linguistic Inquiry and Word Count (Pennebaker, Francis & Booth, 2001). Additionally, patterns of language are found using exploratory principal components analysis. In both studies, redemption scores are modestly correlated with some LIWC categories and unassociated with the components. Patterns of language do not replicate across samples, indicating that the structure of language does not extend to a broader population. Redemption scores and linguistic components are independent predictors of life satisfaction up to 3 years later. These studies converge on the finding that human-coded redemption and automated linguistic analysis are complementary and nonredundant methods of analyzing life narratives, and considerations for the study of life narratives are discussed. © 2015 Wiley Periodicals, Inc.

A Qualitative Analysis and Comparison of the Educational Technology Diffusion and Attitudes toward Adopting Computing Technologies, of the Ministry of Education, Principals/Vice-Principals, and Teachers, in Jamaican Public Primary and Secondary Schools

ERIC Educational Resources Information Center

White, Kerry-Ann

2012-01-01

Given the lack of computer diffusion studies in the Caribbean, and coupled with the necessity to understand Jamaica in efforts to get a clearer global representation of the digital divide, this study takes an exploratory approach and examines the differences of the computer technology adoption and diffusion attitudes and viewpoints between the…

Exploratory subsetting of autism families based on savant skills improves evidence of genetic linkage to 15q11-q13.

PubMed

Nurmi, Erika L; Dowd, Michael; Tadevosyan-Leyfer, Ovsanna; Haines, Jonathan L; Folstein, Susan E; Sutcliffe, James S

2003-07-01

Autism displays a remarkably high heritability but a complex genetic etiology. One approach to identifying susceptibility loci under these conditions is to define more homogeneous subsets of families on the basis of genetically relevant phenotypic or biological characteristics that vary from case to case. The authors performed a principal components analysis, using items from the Autism Diagnostic Interview, which resulted in six clusters of variables, five of which showed significant sib-sib correlation. The utility of these phenotypic subsets was tested in an exploratory genetic analysis of the autism candidate region on chromosome 15q11-q13. When the Collaborative Linkage Study of Autism sample was divided, on the basis of mean proband score for the "savant skills" cluster, the heterogeneity logarithm of the odds under a recessive model at D15S511, within the GABRB3 gene, increased from 0.6 to 2.6 in the subset of families in which probands had greater savant skills. These data are consistent with the genetic contribution of a 15q locus to autism susceptibility in a subset of affected individuals exhibiting savant skills. Similar types of skills have been noted in individuals with Prader-Willi syndrome, which results from deletions of this chromosomal region.

An exploratory risk perception study of attitudes toward homeland security systems.

PubMed

Sanquist, Thomas F; Mahy, Heidi; Morris, Frederic

2008-08-01

Understanding the issues surrounding public acceptance of homeland security systems is important for balancing security needs and potential civil liberties infringements. A psychometric survey was used in an exploratory study of attitudes regarding homeland security systems. Psychometric rating data were obtained from 182 respondents on psychological attributes associated with 12 distinct types of homeland security systems. An inverse relationship was observed for the overall rating attributes of acceptability and risk of civil liberties infringement. Principal components analysis (PCA) yielded a two-factor solution with the rating scale loading pattern suggesting factors of perceived effectiveness and perceived intrusiveness. These factors also showed an inverse relationship. The 12 different homeland security systems showed significantly different scores on the rating scales and PCA factors. Of the 12 systems studied, airport screening, canine detectors, and radiation monitoring at borders were found to be the most acceptable, while email monitoring, data mining, and global positioning satellite (GPS) tracking were found to be least acceptable. Students rated several systems as more effective than professionals, but the overall pattern of results for both types of subjects was similar. The data suggest that risk perception research and the psychometric paradigm are useful approaches for quantifying attitudes regarding homeland security systems and policies and can be used to anticipate potentially significant public acceptance issues.

Revising and Updating the Plant Science Components of the Connecticut Vocational Agriculture Curriculum.

ERIC Educational Resources Information Center

Connecticut Univ., Storrs. Dept. of Educational Leadership.

This curriculum guide provides the plant science components of the vocational agriculture curriculum for Regional Vocational Agriculture Centers. The curriculum is divided into exploratory units for students in the 9th and 10th grades and specialized units for students in grades 11 and 12. The five exploratory units are: agricultural pest control;…

Development and psychometric evaluation of the Impact of Health Information Technology (I-HIT) scale.

PubMed

Dykes, Patricia C; Hurley, Ann; Cashen, Margaret; Bakken, Suzanne; Duffy, Mary E

2007-01-01

The use of health information technology (HIT) for the support of communication processes and data and information access in acute care settings is a relatively new phenomenon. A means of evaluating the impact of HIT in hospital settings is needed. The purpose of this research was to design and psychometrically evaluate the Impact of Health Information Technology scale (I-HIT). I-HIT was designed to measure the perception of nurses regarding the ways in which HIT influences interdisciplinary communication and workflow patterns and nurses' satisfaction with HIT applications and tools. Content for a 43-item tool was derived from the literature, and supported theoretically by the Coiera model and by nurse informaticists. Internal consistency reliability analysis using Cronbach's alpha was conducted on the 43-item scale to initiate the item reduction process. Items with an item total correlation of less than 0.35 were removed, leaving a total of 29 items. Item analysis, exploratory principal component analysis and internal consistency reliability using Cronbach's alpha were used to confirm the 29-item scale. Principal components analysis with Varimax rotation produced a four-factor solution that explained 58.5% of total variance (general advantages, information tools to support information needs, information tools to support communication needs, and workflow implications). Internal consistency of the total scale was 0.95 and ranged from 0.80-0.89 for four subscales. I-HIT demonstrated psychometric adequacy and is recommended to measure the impact of HIT on nursing practice in acute care settings.

Performance-based measures associate with frailty in patients with end-stage liver disease

PubMed Central

Lai, Jennifer C.; Volk, Michael L; Strasburg, Debra; Alexander, Neil

2016-01-01

Background Physical frailty, as measured by the Fried Frailty Index, is increasingly recognized as a critical determinant of outcomes in cirrhotics. However, its utility is limited by the inclusion of self-reported components. We aimed to identify performance-based measures associated with frailty in patients with cirrhosis. Methods Cirrhotics ≥50 years underwent: 6-minute walk test (6MWT, cardiopulmonary endurance), chair stands in 30 seconds (muscle endurance), isometric knee extension (lower extremity strength), unipedal stance time (static balance), and maximal step length (dynamic balance/coordination). Linear regression associated each physical performance test with frailty. Principal components exploratory factor analysis evaluated the inter-relatedness of frailty and the 5 physical performance tests. Results Of forty cirrhotics, with a median age of 64 years and Model for End-stage Liver Disease (MELD) MELD of 12,10 (25%) were frail by Fried Frailty Index ≥3. Frail cirrhotics had poorer performance in 6MWT distance (231 vs. 338 meters), 30 second chair stands (7 vs. 10), isometric knee extension (86 vs. 122 Newton meters), and maximal step length (22 vs. 27 inches) [p≤0.02 for each]. Each physical performance test was significantly associated with frailty (p<0.01), even after adjustment for MELD or hepatic encephalopathy. Principal component factor analysis demonstrated substantial, but unique, clustering of each physical performance test to a single factor – frailty. Conclusion Frailty in cirrhosis is a multi-dimensional construct that is distinct from liver dysfunction and incorporates endurance, strength, and balance. Our data provide specific targets for prehabilitation interventions aimed at reducing frailty in cirrhotics in preparation for liver transplantation. PMID:27495749

Performance-Based Measures Associate With Frailty in Patients With End-Stage Liver Disease.

PubMed

Lai, Jennifer C; Volk, Michael L; Strasburg, Debra; Alexander, Neil

2016-12-01

Physical frailty, as measured by the Fried Frailty Index, is increasingly recognized as a critical determinant of outcomes in patients with cirrhosis. However, its utility is limited by the inclusion of self-reported components. We aimed to identify performance-based measures associated with frailty in patients with cirrhosis. Patients with cirrhosis, aged 50 years or older, underwent: 6-minute walk test (cardiopulmonary endurance), chair stands in 30 seconds (muscle endurance), isometric knee extension (lower extremity strength), unipedal stance time (static balance), and maximal step length (dynamic balance/coordination). Linear regression associated each physical performance test with frailty. Principal components exploratory factor analysis evaluated the interrelatedness of frailty and the 5 physical performance tests. Of 40 patients with cirrhosis, with a median age of 64 years and Model for End-stage Liver Disease (MELD) MELD of 12.10 (25%) were frail by Fried Frailty Index ≥3. Frail patients with cirrhosis had poorer performance in 6-minute walk test distance (231 vs 338 m), 30-second chair stands (7 vs 10), isometric knee extension (86 vs 122 Newton meters), and maximal step length (22 vs 27 in. (P ≤ 0.02 for each). Each physical performance test was significantly associated with frailty (P < 0.01), even after adjustment for MELD or hepatic encephalopathy. Principal component factor analysis demonstrated substantial, but unique, clustering of each physical performance test to a single factor-frailty. Frailty in cirrhosis is a multidimensional construct that is distinct from liver dysfunction and incorporates endurance, strength, and balance. Our data provide specific targets for prehabilitation interventions aimed at reducing frailty in patients with cirrhosis in preparation for liver transplantation.

An Exploratory Contingency Model for Schools.

ERIC Educational Resources Information Center

Whorton, David M.

In an application of contingency theory, data from 45 Arizona schools were analyzed to determine the relationships between three sets of independent variables (organizational structure, leadership style, and environmental characteristics) and the dependent variable (organizational effectiveness as perceived by principals and teachers). Contingency…

Evaluation Study of the Exploratory Visit: An Innovative Outreach Activity of the ILGWU's Friendly Visiting Program

ERIC Educational Resources Information Center

Wright, Holly; And Others

1977-01-01

The exploratory visit to recent retirees, an outreach component of the International Ladies Garment Workers Union Friendly Visiting Program, was evaluated. A post-test only control group effect study revealed exploratory visits were effective in establishing a link between the program and the retiree. (Author)

Psychometric properties of the Exercise Benefits/Barriers Scale in Mexican elderly women

PubMed Central

Enríquez-Reyna, María Cristina; Cruz-Castruita, Rosa María; Ceballos-Gurrola, Oswaldo; García-Cadena, Cirilo Humberto; Hernández-Cortés, Perla Lizeth; Guevara-Valtier, Milton Carlos

2017-01-01

ABSTRACT Objective: analyze and assess the psychometric properties of the subscales in the Spanish version of the Exercise Benefits/Barriers Scale in an elderly population in the Northeast of Mexico. Method: methodological study. The sample consisted of 329 elderly associated with one of the five public centers for senior citizens in the metropolitan area of Northeast Mexico. The psychometric properties included the assessment of the Cronbach's alpha coefficient, the Kaiser Meyer Olkin coefficient, the inter-item correlation, exploratory and confirmatory factor analysis. Results: in the principal components analysis, two components were identified based on the 43 items in the scale. The item-total correlation coefficient of the exercise benefits subscale was good. Nevertheless, the coefficient for the exercise barriers subscale revealed inconsistencies. The reliability and validity were acceptable. The confirmatory factor analysis revealed that the elimination of items improved the goodness of fit of the baseline scale, without affecting its validity or reliability. Conclusion: the Exercise Benefits/Barriers subscale presented satisfactory psychometric properties for the Mexican context. A 15-item short version is presented with factorial structure, validity and reliability similar to the complete scale. PMID:28591306

Personality in sanctuary-housed chimpanzees: A comparative approach of psychobiological and penta-factorial human models.

PubMed

Úbeda, Yulán; Llorente, Miquel

2015-02-18

We evaluate a sanctuary chimpanzee sample (N = 11) using two adapted human assessment instruments: the Five-Factor Model (FFM) and Eysenck's Psychoticism-Extraversion-Neuroticism (PEN) model. The former has been widely used in studies of animal personality, whereas the latter has never been used to assess chimpanzees. We asked familiar keepers and scientists (N = 28) to rate 38 (FFM) and 12 (PEN) personality items. The personality surveys showed reliability in all of the items for both instruments. These were then analyzed in a principal component analysis and a regularized exploratory factor analysis, which revealed four and three components, respectively. The results indicate that both questionnaires show a clear factor structure, with characteristic factors not just for the species, but also for the sample type. However, due to its brevity, the PEN may be more suitable for assessing personality in a sanctuary, where employees do not have much time to devote to the evaluation process. In summary, both models are sensitive enough to evaluate the personality of a group of chimpanzees housed in a sanctuary.

On the Fallibility of Principal Components in Research

ERIC Educational Resources Information Center

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

2017-01-01

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

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.

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

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

PubMed

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

2018-02-01

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

Exploratory Application of Neuropharmacometabolomics in Severe Childhood Traumatic Brain Injury.

PubMed

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

2018-05-07

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

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

PubMed

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

2016-08-01

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

Occurrence and transport of pesticides and alkylphenols in water samples along the Ebro River Basin

NASA Astrophysics Data System (ADS)

Navarro, Alícia; Tauler, Romà; Lacorte, Sílvia; Barceló, Damià

2010-03-01

SummaryWe report the temporal and geographical variations of a set of 30 pesticides (including triazines, organophosphorus and acetanilides) and industrial compounds in surface waters along the Ebro River during the period 2004-2006. Using descriptive statistics we found that the compounds with industrial origin (tributylphosphate, octylphenol and nonylphenol) appeared in over 60% of the samples analyzed and at very high concentrations, while pesticides had a point source origin in the Ebro delta area and overall low-levels, between 0.005 and 2.575 μg L -1. Correlations among pollutants and their distributions were studied using Principal Component Analysis (PCA), a multivariate exploratory data analysis technique which permitted us to discern between agricultural and industrial source contamination. Over a 3 years period a seasonal trend revealed highest concentrations of pesticides over the spring-summer period following pesticide application.

Has your ancient stamp been regummed with synthetic glue? A FT-NIR and FT-Raman study.

PubMed

Simonetti, Remo; Oliveri, Paolo; Henry, Adrien; Duponchel, Ludovic; Lanteri, Silvia

2016-01-01

The potential of FT-NIR and FT-Raman spectroscopies to characterise the gum applied on the backside of ancient stamps was investigated for the first time. This represents a very critical issue for the collectors' market, since gum conditions heavily influence stamp quotations, and fraudulent application of synthetic gum onto damaged stamp backsides to increase their desirability is a well-documented practice. Spectral data were processed by exploratory pattern recognition tools. In particular, application of principal component analysis (PCA) revealed that both of the spectroscopic techniques provide information useful to characterise stamp gum. Examination of PCA loadings and their chemical interpretation confirmed the robustness of the outcomes. Fusion of FT-NIR and FT-Raman spectral data was performed, following both a low-level and a mid-level procedure. The results were critically compared with those obtained separately for the two spectroscopic techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Geographical identification of saffron (Crocus sativus L.) by linear discriminant analysis applied to the UV-visible spectra of aqueous extracts.

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna

2017-03-15

We attempted geographical classification of saffron using UV-visible spectroscopy, conventionally adopted for quality grading according to the ISO Normative 3632. We investigated 81 saffron samples produced in L'Aquila, Città della Pieve, Cascia, and Sardinia (Italy) and commercial products purchased in various supermarkets. Exploratory principal component analysis applied to the UV-vis spectra of saffron aqueous extracts revealed a clear differentiation of the samples belonging to different quality categories, but a poor separation according to the geographical origin of the spices. On the other hand, linear discriminant analysis based on 8 selected absorbance values, concentrated near 279, 305 and 328nm, allowed a good distinction of the spices coming from different sites. Under severe validation conditions (30% and 50% of saffron samples in the evaluation set), correct predictions were 85 and 83%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Stop Using the Modified Work APGAR to Measure Job Satisfaction

PubMed Central

Mielenz, Thelma J.; DeVellis, Robert F.; Battie, Michele C.; Carey, Timothy S.

2011-01-01

Background. The psychometric properties of the Modified Work APGAR (MWA) scale are not established, yet researchers use this scale as an overall measure of job satisfaction. Objective. Perform psychometric analyses on the MWA scale using data from two populations. Methods. A landmark occupational cohort and a clinical cohort are populations with low back pain studied. The first five items of the MWA scale measure social support from coworkers, one item measures dissatisfaction with job tasks, and the sixth item measures lack of social support from a supervisor. Exploratory principal components analyses were conducted in both cohorts. Results. In both cohorts, the first five items of the MWA scale loaded consistently onto one factor, social support from coworkers subscale. Conclusions. Unless researchers are interested in measuring social support from coworkers only, future studies should use other reliable and valid instruments to measure a broad range of psychosocial work characteristics. PMID:22191021

A Pilot Study: Testing of the Psychological Conditions Scale Among Hospital Nurses.

PubMed

Fountain, Donna M; Thomas-Hawkins, Charlotte

2016-11-01

The aim of this study was to test the reliability and validity of the Psychological Conditions Scale (PCS), a measure of drivers of engagement in hospital-based nurses. Research suggests drivers of engagement are positive links to patient, employee, and hospital outcomes. Although this scale has been used in other occupations, it has not been tested in nursing. A cross-sectional, methodological study using a convenience sample of 200 nurses in a large Magnet® hospital in New Jersey. Cronbach's α's ranged from .64 to .95. Principal components exploratory factor analysis with oblique rotation revealed that 13 items loaded unambiguously in 3 domains and explained 76% of the variance. Mean PCS scores ranged from 3.62 to 4.68 on a 5-point Likert scale. The scale is an adequate measure of drivers of engagement in hospital-based nurses. Leadership efforts to promote the facilitators of engagement are recommended.

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

PubMed

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

2012-05-01

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

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.

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.

Parent-School Councils in Beijing, China

ERIC Educational Resources Information Center

Lewis, Wayne D.; Bjork, Lars G.; Zhao, Yuru; Chi, Bin

2011-01-01

This exploratory study examines how schools in Beijing have responded to a Chinese national policy mandate to establish and maintain parent councils. We surveyed principals and parent council members across schools in the Beijing municipality about the establishment and functions of their schools' parent councils. Survey results provide insights…

An Exploratory Study in School Counselor Consultation Engagement

ERIC Educational Resources Information Center

Perera-Diltz, Dilani M.; Moe, Jeffry L.; Mason, Kimberly L.

2011-01-01

Consultation, an indirect school counselor service, is provided by 79% (n = 998) school counselor currently. Most frequently consultation occurs with teachers, parents, and principals. MANOVA and post hoc analysis indicate differences in consultation practices across academic levels. Choosing a consultation model based on the type of service…

The Impact of Accounting Education Research

ERIC Educational Resources Information Center

Sangster, Alan; Fogarty, Tim; Stoner, Greg; Marriott, Neil

2015-01-01

This paper presents an exploratory study into the nature and patterns of usage of accounting education research. The study adopts the most accessible metric, "Google Advanced Scholar" citations, to analyse the impact of research published in the six principal English-language accounting education journals. The analysis reveals a global…

A Factor Analytic Investigation of the Person-in-Recovery and Provider Versions of the Revised Recovery Self-Assessment (RSA-R).

PubMed

Konkolÿ Thege, Barna; Ham, Elke; Ball, Laura C

2017-12-01

Recovery is understood as living a life with hope, purpose, autonomy, productivity, and community engagement despite a mental illness. The aim of this study was to provide further information on the psychometric properties of the Person-in-Recovery and Provider versions of the Revised Recovery Self-Assessment (RSA-R), a widely used measure of recovery orientation. Data from 654 individuals were analyzed, 519 of whom were treatment providers (63.6% female), while 135 were inpatients (10.4% female) of a Canadian tertiary-level psychiatric hospital. Confirmatory and exploratory techniques were used to investigate the factor structure of both versions of the instrument. Results of the confirmatory factor analyses showed that none of the four theoretically plausible models fit the data well. Principal component analyses could not replicate the structure obtained by the scale developers either and instead resulted in a five-component solution for the Provider and a four-component solution for the Person-in-Recovery version. When considering the results of a parallel analysis, the number of components to retain dropped to two for the Provider version and one for the Person-in-Recovery version. We can conclude that the RSA-R requires further revision to become a psychometrically sound instrument for assessing recovery-oriented practices in an inpatient mental health-care setting.

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.

Executive Dysfunction Among Children With Reading Comprehension Deficits

PubMed Central

Locascio, Gianna; Mahone, E. Mark; Eason, Sarah H.; Cutting, Laurie E.

2010-01-01

Emerging research supports the contribution of executive function (EF) to reading comprehension; however, a unique pattern has not been established for children who demonstrate comprehension difficulties despite average word recognition ability (specific reading comprehension deficit; S-RCD). To identify particular EF components on which children with S-RCD struggle, a range of EF skills was compared among 86 children, ages 10 to 14, grouped by word reading and comprehension abilities: 24 average readers, 44 with word recognition deficits (WRD), and 18 S-RCD. An exploratory principal components analysis of EF tests identified three latent factors, used in subsequent group comparisons: Planning/Spatial Working Memory, Verbal Working Memory, and Response Inhibition. The WRD group exhibited deficits (relative to controls) on Verbal Working Memory and Inhibition factors; S-RCD children performed more poorly than controls on the Planning factor. Further analyses suggested the WRD group’s poor performance on EF factors was a by-product of core deficits linked to WRD (after controlling for phonological processing, this group no longer showed EF deficits). In contrast, the S-RCD group’s poor performance on the planning component remained significant after controlling for phonological processing. Findings suggest reading comprehension difficulties are linked to executive dysfunction; in particular, poor strategic planning/organizing may lead to reading comprehension problems. PMID:20375294

Executive dysfunction among children with reading comprehension deficits.

PubMed

Locascio, Gianna; Mahone, E Mark; Eason, Sarah H; Cutting, Laurie E

2010-01-01

Emerging research supports the contribution of executive function (EF) to reading comprehension; however, a unique pattern has not been established for children who demonstrate comprehension difficulties despite average word recognition ability (specific reading comprehension deficit; S-RCD). To identify particular EF components on which children with S-RCD struggle, a range of EF skills was compared among 86 children, ages 10 to 14, grouped by word reading and comprehension abilities: 24 average readers, 44 with word recognition deficits (WRD), and 18 S-RCD. An exploratory principal components analysis of EF tests identified three latent factors, used in subsequent group comparisons: Planning/ Spatial Working Memory, Verbal Working Memory, and Response Inhibition. The WRD group exhibited deficits (relative to controls) on Verbal Working Memory and Inhibition factors; S-RCD children performed more poorly than controls on the Planning factor. Further analyses suggested the WRD group's poor performance on EF factors was a by-product of core deficits linked to WRD (after controlling for phonological processing, this group no longer showed EF deficits). In contrast, the S-RCD group's poor performance on the planning component remained significant after controlling for phonological processing. Findings suggest reading comprehension difficulties are linked to executive dysfunction; in particular, poor strategic planning/organizing may lead to reading comprehension problems.

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

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

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

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

NASA Astrophysics Data System (ADS)

Rietmeijer, F. J. M.

1996-03-01

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

Single-Sex Education in Public School Settings

ERIC Educational Resources Information Center

Crawford-Ferre, Heather Glynn; Wiest, Lynda R.

2013-01-01

Although researchers have studied the effectiveness of single-sex education (SSE), the findings have been mixed. This exploratory study reports the perceived goals and effectiveness of single-sex education based on interviews with a small group of educators involved with SSE in various ways. Research participants included a school principal and…

Characteristics of Teachers as Change Agents

ERIC Educational Resources Information Center

van der Heijden, H. R. M. A.; Geldens, J. J. M.; Beijaard, D.; Popeijus, H. L.

2015-01-01

Teachers play a key role in realizing successful changes in education. Among them are real "change agents" at both classroom and school level. To obtain insights into what characterizes these teachers, an exploratory study has been conducted by interviewing external experts, principals, and teachers (n = 20). An analysis of data resulted…

Examining the Cultural Validity of a College Student Engagement Survey for Latinos

ERIC Educational Resources Information Center

Hernandez, Ebelia; Mobley, Michael; Coryell, Gayle; Yu, En-Hui; Martinez, Gladys

2013-01-01

Using critical race theory and quantitative criticalist stance, this study examines the construct validity of an engagement survey, "Student Experiences in the Research University" (SERU) for Latino college students through exploratory factor analysis. Results support the principal seven-factor SERU model. However subfactors exhibited…

The Trust Imperative in the School Principalship: The Canadian Perspective

ERIC Educational Resources Information Center

Kutsyuruba, Benjamin; Walker, Keith; Noonan, Brian

2016-01-01

As a fundamental concept in human interactions, trust is important for understanding and mediating the social structures in schools. The instrumental work of cultivating, brokering, and maintaining trust in schools lies within the role of the school administrator. Our exploratory study examined the Canadian school principals' perceptions of their…

Underlying Reading-Related Skills and Abilities among Adult Learners

ERIC Educational Resources Information Center

Mellard, Daryl F.; Woods, Kari L.; Md Desa, Z. Deana; Vuyk, M. Alexandra

2015-01-01

This exploratory study identified underlying skill and ability differences among subgroups of adolescent and young adult struggling readers (N = 290) overall and in relation to a fluency-based instructional grouping method. We used principal axis factoring of participants' scores on 18 measures of reading-related skills and abilities identified in…

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.

Petroleum developments in Middle East countries in 1969

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

Mason, J.F.; Moore, Q.M.

1970-08-01

Petroleum production in Middle East countries in 1969 totaled 4,525,475,000 bbl at an average rate of 12,398,561 bpd, compared with 4,113,838,000 bbl or 11,239,995 bpd in 1968. The principal production increases were in Iran, Kuwait, Saudi Arabia, Abu Dhabi, and Oman. New fields were found in Iraq, Iran, and Abu Dhabi. There were no exploratory activities in Bahrain, Qatar, Sharjah, Ajman, Umm al Qawain, Dhofar, Hadhramaut, Aden-Kamaran islands, Yemen, or Lebanon. The main areas of exploratory work were in Iran, Iraq, Saudi Arabia-Red Sea, and the S. Gulf (both on shore and off shore). (67 refs.)

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

PubMed

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

2008-02-01

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

An Exploratory Case Study of How Middle School Principals of Small Rural Schools Address Cyberbullying

ERIC Educational Resources Information Center

Force, Christina Marie

2013-01-01

Cyberbullying affects almost half of the teenagers in America (National Crime Prevention Council [NCPC], 2010). The effects of cyberbullying can be detrimental to teens and may include withdrawal from school activities, illness, depression, eating disorders, or suicidal ideations (Dehue, Bolman, & Vollink, 2008; Mason, 2008). In order to…

Conceptualising Teachers' Professional Learning with Web 2.0

ERIC Educational Resources Information Center

Burden, Kevin John

2010-01-01

Purpose: This paper seeks to identify and develop an exploratory framework for conceptualising how teachers might use the affordances of Web 2.0 technologies to support their own professional learning. Design/methodology/approach: The paper draws on a large corpus of literature and recent research evidence to identify the principal elements and…

Sexuality and HIV Education in Charter Schools: An Exploratory Study with Principals in San Diego County, California

ERIC Educational Resources Information Center

Walsh-Buhi, Eric R.; Dao, Brandon; Salgin, Linda; Marshall, James; Miller, Rachel; Fisher, Doug; Walsh-Buhi, Margaret

2017-01-01

Background: Schools can address critical sexual and reproductive health (SRH) issues among youth. However, little is known about SRH education being implemented in charter schools. Thus, our purpose was to explore implementation of SRH education in charter schools. Methods: Using purposive sampling, semistructured telephone interviews were…

Development and Initial Validation of the Intimate Violence Responsibility Scale (IVRS)

ERIC Educational Resources Information Center

Yun, Sung Hyun; Vonk, M. Elizabeth

2011-01-01

The present study demonstrates the development and initial examination of psychometric properties of the Intimate Violence Responsibility Scale (IVRS) in a community-based sample (N = 527). The underlying factor structure of the IVRS was tested by the exploratory factor analysis (Principal Axis Factoring), which identifies the four factors:…

Promoting Children's Mental, Emotional and Social Health through Contact with Nature: A Model

ERIC Educational Resources Information Center

Maller, Cecily Jane

2009-01-01

Purpose: This paper aims to determine educators' perceptions about the benefits of contact with nature for children's mental, emotional and social health. Design/methodology/approach: The approach was exploratory using qualitative methods. Face-to-face interviews were conducted with school principals and teachers as well as professionals from the…

Implementing the Early Childhood Development Teacher Training Framework in Uganda: Gains and Challenges

ERIC Educational Resources Information Center

Ejuu, Godfrey

2012-01-01

Training of quality early childhood development (ECD) teachers is paramount in ensuring quality ECD service provision. This exploratory study focuses on the gains and challenges met in the implementation of the Uganda ECD teacher training framework. Data were obtained using questionnaires and interviews from principals and tutors of ECD teacher…

Nonlinear Principal Components Analysis: Introduction and Application

ERIC Educational Resources Information Center

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

2007-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Similarities between principal components of protein dynamics and random diffusion

NASA Astrophysics Data System (ADS)

Hess, Berk

2000-12-01

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

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

PubMed Central

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

2015-01-01

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

An Introductory Application of Principal Components to Cricket Data

ERIC Educational Resources Information Center

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

2013-01-01

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

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

ERIC Educational Resources Information Center

Olson, Jeffery E.

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

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

USDA-ARS?s Scientific Manuscript database

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

An Exploratory Study on Using Principal-Component Analysis and Confirmatory Factor Analysis to Identify Bolt-On Dimensions: The EQ-5D Case Study.

PubMed

Finch, Aureliano Paolo; Brazier, John Edward; Mukuria, Clara; Bjorner, Jakob Bue

2017-12-01

Generic preference-based measures such as the EuroQol five-dimensional questionnaire (EQ-5D) are used in economic evaluation, but may not be appropriate for all conditions. When this happens, a possible solution is adding bolt-ons to expand their descriptive systems. Using review-based methods, studies published to date claimed the relevance of bolt-ons in the presence of poor psychometric results. This approach does not identify the specific dimensions missing from the Generic preference-based measure core descriptive system, and is inappropriate for identifying dimensions that might improve the measure generically. This study explores the use of principal-component analysis (PCA) and confirmatory factor analysis (CFA) for bolt-on identification in the EQ-5D. Data were drawn from the international Multi-Instrument Comparison study, which is an online survey on health and well-being measures in five countries. Analysis was based on a pool of 92 items from nine instruments. Initial content analysis provided a theoretical framework for PCA results interpretation and CFA model development. PCA was used to investigate the underlining dimensional structure and whether EQ-5D items were represented in the identified constructs. CFA was used to confirm the structure. CFA was cross-validated in random halves of the sample. PCA suggested a nine-component solution, which was confirmed by CFA. This included psychological symptoms, physical functioning, and pain, which were covered by the EQ-5D, and satisfaction, speech/cognition,relationships, hearing, vision, and energy/sleep which were not. These latter factors may represent relevant candidate bolt-ons. PCA and CFA appear useful methods for identifying potential bolt-ons dimensions for an instrument such as the EQ-5D. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Insomnia, Sleep Quality, and Quality of Life in Mild to Moderate Parkinson's Disease.

PubMed

Shafazand, Shirin; Wallace, Douglas M; Arheart, Kristopher L; Vargas, Silvia; Luca, Corneliu C; Moore, Henry; Katzen, Heather; Levin, Bonnie; Singer, Carlos

2017-03-01

Sleep disorders are prevalent in Parkinson's disease but underreported in clinical settings. The contribution of sleep disorders to health-related quality of life (HRQOL) for patients with this degenerative neurological disease are not well known. To evaluate the impact of insomnia symptoms, obstructive sleep apnea (OSA), and poor sleep quality on HRQOL in a cohort of patients with idiopathic Parkinson's disease. We enrolled a convenience sample of 66 adults seen in the University of Miami Movement Disorders Clinic between July 2011 and June 2013. Participants completed validated questionnaires to determine insomnia symptoms, OSA risk, depression, anxiety, and HRQOL. All patients underwent unattended polysomnography to confirm OSA. Results were compared for those with and without insomnia symptoms. Principal component and regression analyses were performed to evaluate determinants of HRQOL. Participants were predominately Hispanic males with mild to moderate Parkinson's disease. Insomnia symptoms were reported for 46% of the study subjects. OSA (apnea-hypopnea index, ≥5) was noted in 47%, with a mean apnea-hypopnea index of 8.3 ± 11.0. Fairly bad to very bad sleep quality was reported by 21% of the participants. Insomnia (r = 0.71; P < 0.001), daytime sleepiness (r = 0.36; P = 0.003), depression symptoms (r =  0.44; P < 0.001), and anxiety symptoms (r = 0.33; P = 0.006) were significant correlates of poor sleep quality. OSA, severity of Parkinson's disease, and dopaminergic therapy were not. In the principal component analysis, sleep quality was a significant component of the "psychological factor" that in turn was a significant determinant of overall HRQOL. Insomnia symptoms, OSA, and subsequent poor sleep quality are prevalent in Parkinson's disease. In this single-center, exploratory study, we found that insomnia and poor sleep quality, but not OSA, play important roles in determining overall quality of life for patients with this disease. Clinical trial registered with www.clinicaltrials.gov (NCT02034357).

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Constructivism in Practice: an Exploratory Study of Teaching Patterns and Student Motivation in Physics Classrooms in Finland, Germany and Switzerland

NASA Astrophysics Data System (ADS)

Beerenwinkel, Anne; von Arx, Matthias

2017-04-01

For the last three decades, moderate constructivism has become an increasingly prominent perspective in science education. Researchers have defined characteristics of constructivist-oriented science classrooms, but the implementation of such science teaching in daily classroom practice seems difficult. Against this background, we conducted a sub-study within the tri-national research project Quality of Instruction in Physics (QuIP) analysing 60 videotaped physics classes involving a large sample of students ( N = 1192) from Finland, Germany and Switzerland in order to investigate the kinds of constructivist components and teaching patterns that can be found in regular classrooms without any intervention. We applied a newly developed coding scheme to capture constructivist facets of science teaching and conducted principal component and cluster analyses to explore which components and patterns were most prominent in the classes observed. Two underlying components were found, resulting in two scales—Structured Knowledge Acquisition and Fostering Autonomy—which describe key aspects of constructivist teaching. Only the first scale was rather well established in the lessons investigated. Classes were clustered based on these scales. The analysis of the different clusters suggested that teaching physics in a structured way combined with fostering students' autonomy contributes to students' motivation. However, our regression models indicated that content knowledge is a more important predictor for students' motivation, and there was no homogeneous pattern for all gender- and country-specific subgroups investigated. The results are discussed in light of recent discussions on the feasibility of constructivism in practice.

Medical information on the internet: a tool for measuring consumer perception of quality aspects.

PubMed

Dubowicz, Arthur; Schulz, Peter J

2015-03-30

Most of adult Internet users have searched for health information on the Internet. The Internet has become one of the most important sources for health information and treatment advice. In most cases, the information found is not verified with a medical doctor, but judged by the "online-diagnosers" independently. Facing this situation, public health authorities raise concern over the quality of medical information laypersons can find on the Internet. The objective of the study was aimed at developing a measure to evaluate the credibility of websites that offer medical advice and information. The measure was tested in a quasi-experimental study on two sleeping-disorder websites of different quality. There were 45 survey items for rating the credibility of websites that were tested in a quasi-experimental study with a random assignment of 454 participants to either a high- or a low-quality website exposure. Using principal component analysis, the original items were reduced to 13 and sorted into the factors: trustworthiness, textual deficits of the content, interferences (external links on the Web site), and advertisements. The first two factors focus more on the provided content itself, while the other two describe the embedding of the content into the website. The 45 survey items had been designed previously using exploratory observations and literature research. The final scale showed adequate power and reliability for all factors. The loadings of the principal component analysis ranged satisfactorily (.644 to .854). Significant differences at P<.001 were found between the low- and high-quality groups. Advertisements on the website were rated as disturbing in both experimental conditions, meaning that they do not differentiate between good and bad information. The scale reliably distinguished high- and low-quality of medical advice given on websites.

Leadership competencies for medical education and healthcare professions: population-based study

PubMed Central

Çitaku, Fadil; Beran, Tanya; Donnon, Tyrone; Hecker, Kent; Cawthorpe, David

2012-01-01

Objective To identify and empirically investigate the dimensions of leadership in medical education and healthcare professions. Design A population-based design with a focus group and a survey were used to identify the perceived competencies for effective leadership in medical education. Setting The focus group, consisting of five experts from three countries (Austria n=1; Germany n=2; Switzerland n=2), was conducted (all masters of medical education), and the survey was sent to health professionals from medical schools and teaching hospitals in six countries (Austria, Canada, Germany, Switzerland, the UK and the USA). Participants The participants were educators, physicians, nurses and other health professionals who held academic positions in medical education. A total of 229 completed the survey: 135 (59.0%) women (mean age=50.3 years) and 94 (41.0%) men (mean age=51.0 years). Measures A 63-item survey measuring leadership competencies was developed and administered via electronic mail to participants. Results Exploratory principal component analyses yielded five factors accounting for 51.2% of the variance: (1) social responsibility, (2) innovation, (3) self-management, (4) task management and (5) justice orientation. There were significant differences between physicians and other health professionals on some factors (Wilk's λ=0.93, p<0.01). Social responsibility was rated higher by other health professionals (M=71.09) than by physicians (M=67.12), as was innovation (health professionals M=80.83; physicians M=76.20) and justice orientation (health professionals M=21.27; physicians M=20.46). Conclusions The results of the principal component analyses support the theoretical meaningfulness of these factors, their coherence, internal consistency and parsimony in explaining the variance of the data. Although there are some between-group differences, the competencies appear to be stable and coherent. PMID:22457482

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

PubMed

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

2015-08-01

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

Petroleum developments in Middle East countries in 1968

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

Mason, J.F.; Moore, Q.M.

1969-08-01

Petroleum production in Middle East countries in 1968 totaled 4,113,838,000 bbl at an average rate of 11,239,995 bpd. This compares with 3,679,506,000 bbl or 10,080,838 bpd in 1967. The principal production increases were in Iraq, Iran, Saudi Arabia, Abu Dhabi, and Oman. New fields were found in offshore Iran, offshore and onshore Saudi Arabia, and Turkey. There were no exploratory activities in Bahrain, Qatar, Sharjah-Ajman-Umm al Qawain, Dhofar, Hadhramaut, Aden-Kamaran Islands, Yemen, Lebanon, and Cyprus The main areas of exploratory work were in Iran, Saudi Arabia, Neutral Zone, and the S. Gulf (both on shore and off shore). (30 refs.)

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

Code of Federal Regulations, 2010 CFR

2010-07-01

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

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

Code of Federal Regulations, 2010 CFR

2010-07-01

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

Psychometric Properties of the Canadian Nurse Informatics Competency Assessment Scale.

PubMed

Kleib, Manal; Nagle, Lynn

2018-04-10

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

A Survey on Conflict Resolution Mechanisms in Public Secondary Schools: A Case of Nairobi Province, Kenya

ERIC Educational Resources Information Center

Ramani, Ken; Zhimin, Liu

2010-01-01

The broad objective of the study was to determine various mechanisms applied in resolving conflicts within public secondary schools in Nairobi province. This study used descriptive and exploratory research design. A sample comprising of principals, representatives of Boards of Governors (BoG's), class teachers, students and education officers was…

Development of Science Anxiety Scale for Primary School Students

ERIC Educational Resources Information Center

Guzeller, Cem Oktay; Dogru, Mustafa

2012-01-01

The principal aim of the study is to develop a new scale Science Anxiety Scale and to examine its the psychometric properties and construct validity of the Science Anxiety Scale in a sample of 797 primary school students. Exploratory factor analysis was applied and found to have a two-dimensional structure. Confirmatory factor analyses provide…

The Relationship between Principal Beliefs about Effective Leadership Practices and the Enactment of Those Beliefs Related to Literacy Instruction

ERIC Educational Resources Information Center

Harrison, Sonya Elaine Somerville

2012-01-01

This exploratory study was prompted by mandated curricular change within the School District of Philadelphia (SDP) Empowerment Schools. Empowerment Schools are schools that receive highly targeted instructional and non-instructional resources to improve student learning. Supports and services are concentrated in four areas: instruction, student…

The Logic of Hong Kong Teachers: An Exploratory Study of Their Teaching Culturally Diverse Students

ERIC Educational Resources Information Center

Chong, Stella

2005-01-01

This study aims to report how Hong Kong teachers handle a seemingly conventional, orderly schooling phenomenon--the teaching of the newly arrived children (NAC) migrated from mainland China. Semi-structured interviews with ten teachers from nine primary schools were conducted. The principal findings are that the teachers are not prepared for the…

Values and Actions: An Exploratory Study of School Principals in the Mainland of China

ERIC Educational Resources Information Center

Pisapia, John R.; Lin, Ying

2011-01-01

This paper explores the relationship between leader values and actions in the Chinese context. The Chinese Value Instrument (CVI) and the Strategic Leadership Questionnaire (SLQ) were used as the primary data collection tools. The CVI was used to measure the presence of ten values: (1) social harmony, (2) benevolence and honesty, (3) initiative…

Testing the Feasibility of Developmental Asset Measures on College Students to Guide Health Promotion Efforts

ERIC Educational Resources Information Center

Zullig, Keith J.; Ward, Rose Marie; King, Keith A.; Patton, Jon M.; Murray, Karen A.

2009-01-01

The purpose of this investigation was to assess the reliability and validity of eight developmental asset measures among a stratified, random sample (N = 540) of college students to guide health promotion efforts. The sample was randomly split to produce exploratory and confirmatory samples for factor analysis using principal axis factoring and…

Decision-Making Style among Adolescents: Relationship with Sensation Seeking and Locus of Control

ERIC Educational Resources Information Center

Baiocco, Roberto; Laghi, Fiorenzo; D'Alessio, Maria

2009-01-01

The principal aim of the study was to examine the psychometric properties and construct validity of the General Decision-Making Scale (GDMS) in a sample of 700 adolescents (aged 15-19 years). Confirmatory and exploratory factor analyses provide evidence for a solid five-dimension structure reflecting the theorized construct: rational, intuitive,…

Exploratory Trial of a School-Based Alcohol Prevention Intervention with a Family Component

ERIC Educational Resources Information Center

Segrott, Jeremy; Rothwell, Heather; Pignatelli, Ilaria; Playle, Rebecca; Hewitt, Gillian; Huang, Chao; Murphy, Simon; Hickman, Matthew; Reed, Hayley; Moore, Laurence

2016-01-01

Purpose: Involvement of parents/carers may increase effectiveness of primary school-based alcohol-misuse prevention projects through strengthening family-based protective factors, but rates of parental engagement are typically low. This paper reports findings from an exploratory trial of a school-based prevention intervention--Kids, Adults…

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.

Psychometric Evaluation of an Instrument for Measuring Organizational Climate for Quality: Evidence From a National Sample of Infection Preventionists.

PubMed

Pogorzelska-Maziarz, Monika; Nembhard, Ingrid M; Schnall, Rebecca; Nelson, Shanelle; Stone, Patricia W

2016-09-01

In recent years, there has been increased interest in measuring the climate for infection prevention; however, reliable and valid instruments are lacking. This study tested the psychometric properties of the Leading a Culture of Quality for Infection Prevention (LCQ-IP) instrument measuring the infection prevention climate in a sample of 972 infection preventionists from acute care hospitals. An exploratory principal component analysis showed that the instrument had structural validity and captured 4 factors related to the climate for infection prevention: Psychological Safety, Prioritization of Quality, Supportive Work Environment, and Improvement Orientation. LCQ-IP exhibited excellent internal consistency, with a Cronbach α of .926. Criterion validity was supported with overall LCQ-IP scores, increasing with the number of evidence-based prevention policies in place (P = .047). This psychometrically sound instrument may be helpful to researchers and providers in assessing climate for quality related to infection prevention. © The Author(s) 2015.

Health Professionals' Explanations of Suicidal Behaviour: Effects of Professional Group, Theoretical Intervention Model, and Patient Suicide Experience.

PubMed

Rothes, Inês Areal; Henriques, Margarida Rangel

2017-12-01

In a help relation with a suicidal person, the theoretical models of suicidality can be essential to guide the health professional's comprehension of the client/patient. The objectives of this study were to identify health professionals' explanations of suicidal behaviors and to study the effects of professional group, theoretical intervention models, and patient suicide experience in professionals' representations. Two hundred and forty-two health professionals filled out a self-report questionnaire. Exploratory principal components analysis was used. Five explanatory models were identified: psychological suffering, affective cognitive, sociocommunicational, adverse life events, and psychopathological. Results indicated that the psychological suffering and psychopathological models were the most valued by the professionals, while the sociocommunicational was seen as the least likely to explain suicidal behavior. Differences between professional groups were found. We concluded that training and reflection on theoretical models in general and in communicative issues in particular are needed in the education of health professionals.

Application of a voltammetric electronic tongue and near infrared spectroscopy for a rapid umami taste assessment.

PubMed

Bagnasco, Lucia; Cosulich, M Elisabetta; Speranza, Giovanna; Medini, Luca; Oliveri, Paolo; Lanteri, Silvia

2014-08-15

The relationships between sensory attribute and analytical measurements, performed by electronic tongue (ET) and near-infrared spectroscopy (NIRS), were investigated in order to develop a rapid method for the assessment of umami taste. Commercially available umami products and some aminoacids were submitted to sensory analysis. Results were analysed in comparison with the outcomes of analytical measurements. Multivariate exploratory analysis was performed by principal component analysis (PCA). Calibration models for prediction of the umami taste on the basis of ET and NIR signals were obtained using partial least squares (PLS) regression. Different approaches for merging data from the two different analytical instruments were considered. Both of the techniques demonstrated to provide information related with umami taste. In particular, ET signals showed the higher correlation with umami attribute. Data fusion was found to be slightly beneficial - not so significantly as to justify the coupled use of the two analytical techniques. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrated Primary Care Readiness and Behaviors Scale: Development and validation in behavioral health professionals.

PubMed

Blaney, Cerissa L; Redding, Colleen A; Paiva, Andrea L; Rossi, Joseph S; Prochaska, James O; Blissmer, Bryan; Burditt, Caitlin T; Nash, Justin M; Bayley, Keri Dotson

2018-03-01

Although integrated primary care (IPC) is growing, several barriers remain. Better understanding of behavioral health professionals' (BHPs') readiness for and engagement in IPC behaviors could improve IPC research and training. This study developed measures of IPC behaviors and stage of change. The sample included 319 licensed, practicing BHPs with a range of interests and experience with IPC. Sequential measurement development procedures, with split-half cross-validation were conducted. Exploratory principal components analyses (N = 152) and confirmatory factor analyses (N = 167) yielded a 12-item scale with 2 factors: consultation/practice management (CPM) and intervention/knowledge (IK). A higher-order Integrated Primary Care Behavior Scale (IPCBS) model showed good fit to the data, and excellent internal consistencies. The multivariate analysis of variance (MANOVA) on the IPCBS demonstrated significant large-sized differences across stage and behavior groups. The IPCBS demonstrated good psychometric properties and external validation, advancing research, education, and training for IPC practice. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Examining the factor structure of MUIS-C scale among baby boomers with hepatitis C.

PubMed

Reinoso, Humberto; Türegün, Mehmet

2016-11-01

Baby boomers account for two out of every three cases of hepatitis C infection in the U.S. To conduct an exploratory factor analysis directed at supporting the use of the MUIS-C as a reliable instrument in measuring illness uncertainty among baby boomers with hepatitis C. The steps of conducting a typical principal component analysis (PCA) with an oblique rotation were used on a sample of 146 participants, the sampling adequacy of items was examined via the Kaiser-Meyer-Olkin (KMO) measure, and the Bartlett's sphericity test was used for appropriateness of conducting a factor analysis. A two-factor structure was obtained by using Horn's parallel analysis method. The two factors explained a cumulative total of 45.8% of the variance. The results of the analyses indicated that the MUIS-C was a valid and reliable instrument and potentially suitable for use in baby boomer population diagnosed with hepatitis C. Published by Elsevier Inc.

Gas Chromatography Data Classification Based on Complex Coefficients of an Autoregressive Model

DOE PAGES

Zhao, Weixiang; Morgan, Joshua T.; Davis, Cristina E.

2008-01-01

This paper introduces autoregressive (AR) modeling as a novel method to classify outputs from gas chromatography (GC). The inverse Fourier transformation was applied to the original sensor data, and then an AR model was applied to transform data to generate AR model complex coefficients. This series of coefficients effectively contains a compressed version of all of the information in the original GC signal output. We applied this method to chromatograms resulting from proliferating bacteria species grown in culture. Three types of neural networks were used to classify the AR coefficients: backward propagating neural network (BPNN), radial basis function-principal component analysismore » (RBF-PCA) approach, and radial basis function-partial least squares regression (RBF-PLSR) approach. This exploratory study demonstrates the feasibility of using complex root coefficient patterns to distinguish various classes of experimental data, such as those from the different bacteria species. This cognition approach also proved to be robust and potentially useful for freeing us from time alignment of GC signals.« less

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Psychometric properties of the DASS-Depression scale among a Brazilian population with chronic pain.

PubMed

Sardá, Jamir; Nicholas, Michael K; Pimenta, Cibele A M; Asghari, Ali

2008-01-01

Depression is a common contributor to suffering and disability in people with chronic pain. However, the assessment of depression in this population has been hampered by the presence of a number of somatic symptoms that are shared between chronic pain, treatment side-effects and traditional concepts of depression. As a result, the use of depression measures that do not contain somatic items has been encouraged. This study examined the psychometric properties of the Depression sub-scale of the Depression Anxiety and Stress Scales (DASS) in a Brazilian chronic pain patient population. Data on a number of measures were collected from 348 participants attending pain facilities. Principal components and exploratory factor analyses indicated the presence of only one factor. Item analyses indicated adequate item-scale correlations. The Cronbach alpha was .96, which suggests an excellent internal consistency. The DASS-Depression scale has adequate psychometric properties and its further use with Brazilian chronic pain populations can now be supported.

STRUCTURE OF THE UNIVERSITY PERSONALITY INVENTORY FOR CHINESE COLLEGE STUDENTS.

PubMed

Zhang, Jieting; Lanza, Stephanie; Zhang, Minqiang; Su, Binyuan

2015-06-01

The University Personality Inventory, a mental health instrument for college students, is frequently used for screening in China. However, its unidimensionality has been questioned. This study examined its dimensions to provide more information about the specific mental problems for students at risk. Four subsamples were randomly created from a sample (N = 6,110; M age = 19.1 yr.) of students at a university in China. Principal component analysis with Promax rotation was applied on the first two subsamples to explore dimension of the inventory. Confirmatory factor analysis was conducted on the third subsample to verify the exploratory dimensions. Finally, the identified factors were compared to the Symptom Checklist-90 (SCL-90) to support validity, and sex differences were examined, based on the fourth subsample. Five factors were identified: Physical Symptoms, Cognitive Symptoms, Emotional Vulnerability, Social Avoidance, and Interpersonal Sensitivity, accounting for 60.3% of the variance. All the five factors were significantly correlated with the SCL-90. Women scored significantly higher than men on Cognitive Symptoms and Interpersonal Sensitivity.

Paper spray mass spectrometry and chemometric tools for a fast and reliable identification of counterfeit blended Scottish whiskies.

PubMed

Teodoro, Janaína Aparecida Reis; Pereira, Hebert Vinicius; Sena, Marcelo Martins; Piccin, Evandro; Zacca, Jorge Jardim; Augusti, Rodinei

2017-12-15

A direct method based on the application of paper spray mass spectrometry (PS-MS) combined with a chemometric supervised method (partial least square discriminant analysis, PLS-DA) was developed and applied to the discrimination of authentic and counterfeit samples of blended Scottish whiskies. The developed methodology employed the negative ion mode MS, included 44 authentic whiskies from diverse brands and batches and 44 counterfeit samples of the same brands seized during operations of the Brazilian Federal Police, totalizing 88 samples. An exploratory principal component analysis (PCA) model showed a reasonable discrimination of the counterfeit whiskies in PC2. In spite of the samples heterogeneity, a robust, reliable and accurate PLS-DA model was generated and validated, which was able to correctly classify the samples with nearly 100% success rate. The use of PS-MS also allowed the identification of the main marker compounds associated with each type of sample analyzed: authentic or counterfeit. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cross-cultural adaptation, validation and reliability of the brazilian version of the Richmond Compulsive Buying Scale.

PubMed

Leite, Priscilla; Rangé, Bernard; Kukar-Kiney, Monika; Ridgway, Nancy; Monroe, Kent; Ribas Junior, Rodolfo; Landeira Fernandez, J; Nardi, Antonio Egidio; Silva, Adriana

2013-03-01

To present the process of transcultural adaptation of the Richmond Compulsive Buying Scale to Brazilian Portuguese. For the semantic adaptation step, the scale was translated to Portuguese and then back-translated to English by two professional translators and one psychologist, without any communication between them. The scale was then applied to 20 participants from the general population for language adjustments. For the construct validation step, an exploratory factor analysis was performed, using the scree plot test, principal component analysis for factor extraction, and Varimax rotation. For convergent validity, the correlation matrix was analyzed through Pearson's coefficient. The scale showed easy applicability, satisfactory internal consistency (Cronbach's alpha=.87), and a high correlation with other rating scales for compulsive buying disorder, indicating that it is suitable to be used in the assessment and diagnosis of compulsive buying disorder, as it presents psychometric validity. The Brazilian Portuguese version of the Richmond Compulsive Buying Scale has good validity and reliability.

The relationship between the INTERMED patient complexity instrument and Level of Care Utilisation System (LOCUS).

PubMed

Thurber, Steven; Wilson, Ann; Realmuto, George; Specker, Sheila

2018-03-01

To investigate the concurrent and criterion validity of two independently developed measurement instruments, INTERMED and LOCUS, designed to improve the treatment and clinical management of patients with complex symptom manifestations. Participants (N = 66) were selected from hospital records based on the complexity of presenting symptoms, with tripartite diagnoses across biological, psychiatric and addiction domains. Biopsychosocial information from hospital records were submitted to INTERMED and LOCUS grids. In addition, Global Assessment of Functioning (GAF) ratings were gathered for statistical analyses. The product moment correlation between INTERMED and LOCUS was 0.609 (p = .01). Inverse zero-order correlations for INTERMED and LOCUS total score and GAF were obtained. However, only the beta weight for LOCUS and GAF was significant. An exploratory principal components analysis further illuminated areas of convergence between the instruments. INTERMED and LOCUS demonstrated shared variance. INTERMED appeared more sensitive to complex medical conditions and severe physiological reactions, whereas LOCUS findings are more strongly related to psychiatric symptoms. Implications are discussed.

Nine Constructs of Cultural Competence for Curriculum Development

PubMed Central

Brookover, Cecile; Kennedy, Kathleen

2010-01-01

Objective To examine the self-administered Clinical Cultural Competency Questionnaire (CCCQ) and assess the perceived level of cultural competence of students in Xavier University of Louisiana College of Pharmacy to guide curriculum development within the 4-year academic program. Methods The CCCQ was administrated to each class of pharmacy students during spring 2009. Exploratory factor analysis with principal components and varimax rotation was conducted to build the constructs explaining the factors measuring students' self-assessment of cultural competence. Results Nine factors, including 46 items extracted from the CCCQ and explaining 79% of the total variance, were found as the best fit to measure students' self-assessment of cultural competence. Conclusions The CCCQ was found to be a practical, valid, and reliable self-assessment instrument to measure the perceived level of pharmacy students' knowledge, skills, attitudes, and encounters in cross-cultural environments. The questionnaire allowed the identification of students' needs for training in cultural competence and the development of a curriculum tailored to satisfy those needs. PMID:21436922

Non-invasive optical detection of HBV based on serum surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Zheng, Zuci; Wang, Qiwen; Weng, Cuncheng; Lin, Xueliang; Lin, Yao; Feng, Shangyuan

2016-10-01

An optical method of surface-enhanced Raman spectroscopy (SERS) was developed for non-invasive detection of hepatitis B surface virus (HBV). Hepatitis B virus surface antigen (HBsAg) is an established serological marker that is routinely used for the diagnosis of acute or chronic hepatitis B virus(HBV) infection. Utilizing SERS to analyze blood serum for detecting HBV has not been reported in previous literature. SERS measurements were performed on two groups of serum samples: one group for 50 HBV patients and the other group for 50 healthy volunteers. Blood serum samples are collected from healthy control subjects and patients diagnosed with HBV. Furthermore, principal components analysis (PCA) combined with linear discriminant analysis (LDA) were employed to differentiate HBV patients from healthy volunteer and achieved sensitivity of 80.0% and specificity of 74.0%. This exploratory work demonstrates that SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of HBV.

Validation of the Turkish version of the Breast Reduction Assessed Severity Scale.

PubMed

Kececi, Yavuz; Sir, Emin; Zengel, Baha

2013-01-01

Measuring patient-reported outcomes has become increasingly important in cosmetic and reconstructive breast surgery. There is no validated questionnaire in Turkish to evaluate quality-of-life issues for patients with mammary hypertrophy. The authors describe the reliability and validity of a translated Breast Reduction Assessed Severity Scale (BRASS) in evaluating Turkish patients. The BRASS, developed by Sigurdson et al, was translated into Turkish adhering strictly to the guidelines of questionnaire translations. Statistical analysis was carried out with Cronbach's α to test the internal consistency and intraclass correlation coefficient for test-retest reliability. Exploratory factor analysis was carried out using principal component analysis with oblimin rotation to test its construct validity. Correlations between subscales identified in the factor analysis and corresponding domains in the Short Form-36 and Rosenberg Self-Esteem Scale were analyzed. The total instrument was found to have an α coefficient of 0.92 and subscale α coefficients ranging from 0.76 to 0.87. Intraclass correlation coefficient was 0.93 for the total scale and ranged from 0.81 to 0.91 for the subscales. Exploratory factor analysis resulted in a 5-factor structure: physical implications, body pain, physical appearance, poor self-concept, and negative social interactions. With this study, the reliability and validity of the Turkish version of the BRASS were revealed. This translated version can be used to evaluate the effect of mammary hypertrophy on quality of life in Turkish patients.

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Occurrence and multivariate exploratory analysis of the natural radioactivity anomaly in the south coastal region of Kenya

NASA Astrophysics Data System (ADS)

Kaniu, M. I.; Angeyo, K. H.; Darby, I. G.

2018-05-01

Characterized by a variety of rock formations, namely alkaline, igneous and sedimentary that contain significant deposits of monazite and pyrochlore ores, the south coastal region of Kenya may be regarded as highly heterogeneous with regard to its geochemistry, mineralogy as well as geological morphology. The region is one of the several alkaline carbonatite complexes of Kenya that are associated with high natural background radiation and therefore radioactivity anomaly. However, this high background radiation (HBR) anomaly has hardly been systematically assessed and delineated with regard to the spatial, geological, geochemical as well as anthropogenic variability and co-dependencies. We conducted wide-ranging in-situ gamma-ray spectrometric measurements in this area. The goal of the study was to assess the radiation exposure as well as determine the underlying natural radioactivity levels in the region. In this paper we report the occurrence, exploratory analysis and modeling to assess the multivariate geo-dependence and spatial variability of the radioactivity and associated radiation exposure. Unsupervised principal component analysis and ternary plots were utilized in the study. It was observed that areas which exhibit HBR anomalies are located along the south coast paved road and in the Mrima-Kiruku complex. These areas showed a trend towards enhanced levels of 232Th and 238U and low 40K. The spatial variability of the radioactivity anomaly was found to be mainly constrained by anthropogenic activities, underlying geology and geochemical processes in the terrestrial environment.

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

PubMed Central

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

2015-01-01

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

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

ERIC Educational Resources Information Center

Oplatka, Izhar

2017-01-01

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

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

PubMed

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

2018-02-01

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

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

PubMed

Saccenti, Edoardo; Timmerman, Marieke E

2017-03-01

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

Insight into dementia care management using social-behavioral theory and mixed methods.

PubMed

Connor, Karen; McNeese-Smith, Donna; van Servellen, Gwen; Chang, Betty; Lee, Martin; Cheng, Eric; Hajar, Abdulrahman; Vickrey, Barbara G

2009-01-01

For health organizations (private and public) to advance their care-management programs, to use resources effectively and efficiently, and to improve patient outcomes, it is germane to isolate and quantify care-management activities and to identify overarching domains. The aims of this study were to identify and report on an application of mixed methods of qualitative statistical techniques, based on a theoretical framework, and to construct variables for factor analysis and exploratory factor analytic steps for identifying domains of dementia care management. Care-management activity data were extracted from the care plans of 181 pairs of individuals (with dementia and their informal caregivers) who had participated in the intervention arm of a randomized controlled trial of a dementia care-management program. Activities were organized into types, using card-sorting methods, influenced by published theoretical constructs on self-efficacy and general strain theory. These activity types were mapped in the initial data set to construct variables for exploratory factor analysis. Principal components extraction with varimax and promax rotations was used to estimate the number of factors. Cronbach's alpha was calculated for the items in each factor to assess internal consistency reliability. The two-phase card-sorting technique yielded 45 activity types out of 450 unique activities. Exploratory factor analysis produced four care-management domains (factors): behavior management, clinical strategies and caregiver support, community agency, and safety. Internal consistency reliability (Cronbach's alpha) of items for each factor ranged from.63 for the factor "safety" to.89 for the factor "behavior management" (Factor 1). Applying a systematic method to a large set of care-management activities can identify a parsimonious number of higher order categories of variables and factors to guide the understanding of dementia care-management processes. Further application of this methodology in outcome analyses and to other data sets is necessary to test its practicality.

Realist explanatory theory building method for social epidemiology: a protocol for a mixed method multilevel study of neighbourhood context and postnatal depression.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A

2014-01-01

A recent criticism of social epidemiological studies, and multi-level studies in particular has been a paucity of theory. We will present here the protocol for a study that aims to build a theory of the social epidemiology of maternal depression. We use a critical realist approach which is trans-disciplinary, encompassing both quantitative and qualitative traditions, and that assumes both ontological and hierarchical stratification of reality. We describe a critical realist Explanatory Theory Building Method comprising of an: 1) emergent phase, 2) construction phase, and 3) confirmatory phase. A concurrent triangulated mixed method multilevel cross-sectional study design is described. The Emergent Phase uses: interviews, focus groups, exploratory data analysis, exploratory factor analysis, regression, and multilevel Bayesian spatial data analysis to detect and describe phenomena. Abductive and retroductive reasoning will be applied to: categorical principal component analysis, exploratory factor analysis, regression, coding of concepts and categories, constant comparative analysis, drawing of conceptual networks, and situational analysis to generate theoretical concepts. The Theory Construction Phase will include: 1) defining stratified levels; 2) analytic resolution; 3) abductive reasoning; 4) comparative analysis (triangulation); 5) retroduction; 6) postulate and proposition development; 7) comparison and assessment of theories; and 8) conceptual frameworks and model development. The strength of the critical realist methodology described is the extent to which this paradigm is able to support the epistemological, ontological, axiological, methodological and rhetorical positions of both quantitative and qualitative research in the field of social epidemiology. The extensive multilevel Bayesian studies, intensive qualitative studies, latent variable theory, abductive triangulation, and Inference to Best Explanation provide a strong foundation for Theory Construction. The study will contribute to defining the role that realism and mixed methods can play in explaining the social determinants and developmental origins of health and disease.

Factor analysis methods and validity evidence: A systematic review of instrument development across the continuum of medical education

NASA Astrophysics Data System (ADS)

Wetzel, Angela Payne

Previous systematic reviews indicate a lack of reporting of reliability and validity evidence in subsets of the medical education literature. Psychology and general education reviews of factor analysis also indicate gaps between current and best practices; yet, a comprehensive review of exploratory factor analysis in instrument development across the continuum of medical education had not been previously identified. Therefore, the purpose for this study was critical review of instrument development articles employing exploratory factor or principal component analysis published in medical education (2006--2010) to describe and assess the reporting of methods and validity evidence based on the Standards for Educational and Psychological Testing and factor analysis best practices. Data extraction of 64 articles measuring a variety of constructs that have been published throughout the peer-reviewed medical education literature indicate significant errors in the translation of exploratory factor analysis best practices to current practice. Further, techniques for establishing validity evidence tend to derive from a limited scope of methods including reliability statistics to support internal structure and support for test content. Instruments reviewed for this study lacked supporting evidence based on relationships with other variables and response process, and evidence based on consequences of testing was not evident. Findings suggest a need for further professional development within the medical education researcher community related to (1) appropriate factor analysis methodology and reporting and (2) the importance of pursuing multiple sources of reliability and validity evidence to construct a well-supported argument for the inferences made from the instrument. Medical education researchers and educators should be cautious in adopting instruments from the literature and carefully review available evidence. Finally, editors and reviewers are encouraged to recognize this gap in best practices and subsequently to promote instrument development research that is more consistent through the peer-review process.

Exploratory Long-Range Models to Estimate Summer Climate Variability over Southern Africa.

NASA Astrophysics Data System (ADS)

Jury, Mark R.; Mulenga, Henry M.; Mason, Simon J.

1999-07-01

Teleconnection predictors are explored using multivariate regression models in an effort to estimate southern African summer rainfall and climate impacts one season in advance. The preliminary statistical formulations include many variables influenced by the El Niño-Southern Oscillation (ENSO) such as tropical sea surface temperatures (SST) in the Indian and Atlantic Oceans. Atmospheric circulation responses to ENSO include the alternation of tropical zonal winds over Africa and changes in convective activity within oceanic monsoon troughs. Numerous hemispheric-scale datasets are employed to extract predictors and include global indexes (Southern Oscillation index and quasi-biennial oscillation), SST principal component scores for the global oceans, indexes of tropical convection (outgoing longwave radiation), air pressure, and surface and upper winds over the Indian and Atlantic Oceans. Climatic targets include subseasonal, area-averaged rainfall over South Africa and the Zambezi river basin, and South Africa's annual maize yield. Predictors and targets overlap in the years 1971-93, the defined training period. Each target time series is fitted by an optimum group of predictors from the preceding spring, in a linear multivariate formulation. To limit artificial skill, predictors are restricted to three, providing 17 degrees of freedom. Models with colinear predictors are screened out, and persistence of the target time series is considered. The late summer rainfall models achieve a mean r2 fit of 72%, contributed largely through ENSO modulation. Early summer rainfall cross validation correlations are lower (61%). A conceptual understanding of the climate dynamics and ocean-atmosphere coupling processes inherent in the exploratory models is outlined.Seasonal outlooks based on the exploratory models could help mitigate the impacts of southern Africa's fluctuating climate. It is believed that an advance warning of drought risk and seasonal rainfall prospects will improve the economic growth potential of southern Africa and provide additional security for food and water supplies.

An exploratory study of air emissions associated with shale gas development and production in the Barnett Shale.

PubMed

Rich, Alisa; Grover, James P; Sattler, Melanie L

2014-01-01

Information regarding air emissions from shale gas extraction and production is critically important given production is occurring in highly urbanized areas across the United States. Objectives of this exploratory study were to collect ambient air samples in residential areas within 61 m (200 feet) of shale gas extraction/production and determine whether a "fingerprint" of chemicals can be associated with shale gas activity. Statistical analyses correlating fingerprint chemicals with methane, equipment, and processes of extraction/production were performed. Ambient air sampling in residential areas of shale gas extraction and production was conducted at six counties in the Dallas/Fort Worth (DFW) Metroplex from 2008 to 2010. The 39 locations tested were identified by clients that requested monitoring. Seven sites were sampled on 2 days (typically months later in another season), and two sites were sampled on 3 days, resulting in 50 sets of monitoring data. Twenty-four-hour passive samples were collected using summa canisters. Gas chromatography/mass spectrometer analysis was used to identify organic compounds present. Methane was present in concentrations above laboratory detection limits in 49 out of 50 sampling data sets. Most of the areas investigated had atmospheric methane concentrations considerably higher than reported urban background concentrations (1.8-2.0 ppm(v)). Other chemical constituents were found to be correlated with presence of methane. A principal components analysis (PCA) identified multivariate patterns of concentrations that potentially constitute signatures of emissions from different phases of operation at natural gas sites. The first factor identified through the PCA proved most informative. Extreme negative values were strongly and statistically associated with the presence of compressors at sample sites. The seven chemicals strongly associated with this factor (o-xylene, ethylbenzene, 1,2,4-trimethylbenzene, m- and p-xylene, 1,3,5-trimethylbenzene, toluene, and benzene) thus constitute a potential fingerprint of emissions associated with compression. Information regarding air emissions from shale gas development and production is critically important given production is now occurring in highly urbanized areas across the United States. Methane, the primary shale gas constituent, contributes substantially to climate change; other natural gas constituents are known to have adverse health effects. This study goes beyond previous Barnett Shale field studies by encompassing a wider variety of production equipment (wells, tanks, compressors, and separators) and a wider geographical region. The principal components analysis, unique to this study, provides valuable information regarding the ability to anticipate associated shale gas chemical constituents.

Elementary Principals' Perception of Response to Intervention (RtI) Implementation in North Carolina: An Exploratory Study

ERIC Educational Resources Information Center

Buckner, Jerry W.

2013-01-01

Conceptually, Response to Intervention (RtI) is a multi-tiered problem solving process rooted in special education yet designed as a framework for early and on-going instructional interventions for students across a continuum of academic need. In recent years, however, RtI has become an increasingly significant part of the discourse on school…

Social Justice Leadership in Multicultural Schools: The Case of an Ethnically Divided Society

ERIC Educational Resources Information Center

Zembylas, Michalinos; Iasonos, Sotiroula

2017-01-01

This paper reports on the results of an exploratory study focusing on the perceptions of elementary school principals who espouse a critical multicultural approach and show signs of a social justice leadership style. The study has taken place in an ethnically divided society (Cyprus) in which the political situation seems to influence the ways in…

Adolescent Future Expectations of Work, Education, Family, and Community: Development of a New Measure

ERIC Educational Resources Information Center

McWhirter, Ellen Hawley; McWhirter, Benedict T.

2008-01-01

The development and validation of a measure of adolescent future expectations associated with work, education, family, health, and church/community participation is presented. The 25-item measure was administered to a sample of 389 7th- to 12th-grade urban poor and working-class Chilean students. Results of an exploratory principal axis factor…

School Leadership and School Mental Health: An Exploratory Study of SMH Content in the Preparation of Principals

ERIC Educational Resources Information Center

Caparelli, Sielke M.

2012-01-01

The increasing prevalence of K-12 students with mental health disorders is of great concern because research has shown that these children are at increased risk for academic failure. Accordingly, this study explored two intersecting fields of study - school mental health (SMH) and education administration, first examining the literature on the…

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.

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.

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

PubMed

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

2003-01-01

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

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

PubMed

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

2016-07-12

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

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

Code of Federal Regulations, 2010 CFR

2010-07-01

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

Integrating the philosophy and psychology of aesthetic experience: development of the aesthetic experience scale.

PubMed

Stamatopoulou, Despina

2004-10-01

This study assessed the dynamic relationship between person and object in aesthetic experience. Patterns of the structure of aesthetic experience were derived from a conceptual model based on philosophical and psychological ideas. These patterns were further informed by interviewing individuals with extensive involvement in aesthetic activities and 25 secondary students. Accordingly, patterns were tested by developing a large pool of items attempting to identify measurable structural components of aesthetic experience. Refined first in a pilot study, the 36-item questionnaire was administered to 652 Greek students, aged from 13 to 15 years. Correlation matrices and exploratory factor analyses on principal components were used to examine internal structural relationships. The obliquely rotated five-factor solution of the refined instrument accounted for the 44.1% of the total variance and was combatible with the conceptual model of aesthetic experience, indicating the plausibility of both. The internal consistency of the items was adequate and external correlational analysis offered preliminary support for subsequent development of a self-report measure that serves to operationalize the major constructs of aesthetic experience in the general adolescent population. The results also raise theoretical issues for those interested in empirical aesthetics, suggesting that in experiential functioning, expressive perception and affect may play a more constructive role in cognitive processes than is generally acknowledged.

Computerised Analysis of Telemonitored Respiratory Sounds for Predicting Acute Exacerbations of COPD.

PubMed

Fernandez-Granero, Miguel Angel; Sanchez-Morillo, Daniel; Leon-Jimenez, Antonio

2015-10-23

Chronic obstructive pulmonary disease (COPD) is one of the commonest causes of death in the world and poses a substantial burden on healthcare systems and patients' quality of life. The largest component of the related healthcare costs is attributable to admissions due to acute exacerbation (AECOPD). The evidence that might support the effectiveness of the telemonitoring interventions in COPD is limited partially due to the lack of useful predictors for the early detection of AECOPD. Electronic stethoscopes and computerised analyses of respiratory sounds (CARS) techniques provide an opportunity for substantial improvement in the management of respiratory diseases. This exploratory study aimed to evaluate the feasibility of using: (a) a respiratory sensor embedded in a self-tailored housing for ageing users; (b) a telehealth framework; (c) CARS and (d) machine learning techniques for the remote early detection of the AECOPD. In a 6-month pilot study, 16 patients with COPD were equipped with a home base-station and a sensor to daily record their respiratory sounds. Principal component analysis (PCA) and a support vector machine (SVM) classifier was designed to predict AECOPD. 75.8% exacerbations were early detected with an average of 5 ± 1.9 days in advance at medical attention. The proposed method could provide support to patients, physicians and healthcare systems.

Internal Structure and Development of Keyboard Skills in Spanish-Speaking Primary-School Children With and Without LD in Writing.

PubMed

Jiménez, Juan E; Marco, Isaac; Suárez, Natalia; González, Desirée

This study had two purposes: examining the internal structure of the Test Estandarizado para la Evaluación Inicial de la Escritura con Teclado (TEVET; Spanish Keyboarding Writing Test), and analyzing the development of keyboarding skills in Spanish elementary school children with and without learning disabilities (LD) in writing. A group of 1,168 elementary school children carried out the following writing tasks: writing the alphabet in order from memory, allograph selection, word copying, writing dictated words with inconsistent spelling, writing pseudowords from dictation, and independent composition of sentence. For this purpose, exploratory factor analysis for the TEVET was conducted. Principal component analysis with a varimax rotation identified three factors with eigenvalues greater than 1.0. Based on factorial analysis, we analyzed the keyboarding skills across grades in Spanish elementary school children with and without LD (i.e., poor handwriters compared with poor spellers, who in turn were compared with mixed compared with typically achieving writers). The results indicated that poor handwriters did not differ from typically achieving writers in phonological processing, visual-orthographic processing, and sentence production components by keyboarding. The educational implications of the findings are analyzed with regard to acquisition of keyboarding skills in children with and without LD in transcription.

Temporal dynamics of the HPA axis linked to exploratory behavior in a wild European songbird (Parus major).

PubMed

Baugh, Alexander T; Davidson, Sarah C; Hau, Michaela; van Oers, Kees

2017-09-01

Variation in the reactivity of the endocrine stress axis is thought to underlie aspects of persistent individual differences in behavior (i.e. animal personality). Previous studies, however, have focused largely on estimating baseline or peak levels of glucocorticoids (CORT), often in captive animals. In contrast, the temporal dynamics of the HPA axis-how quickly it turns on and off, for example-may better indicate how an individual copes with stressors. Moreover, these HPA components might be correlated, thereby representing endocrine suites. Using wild-caught great tits (Parus major) we tested birds for exploratory behavior using a standardized novel environment assay that serves as a validated proxy for personality. We then re-captured a subset of these birds (n=85) and characterized four components of HPA physiology: baseline, endogenous stress response, a dexamethasone (DEX) challenge to estimate the strength of negative feedback, and an adrenocorticotropic hormone (ACTH) challenge to estimate adrenal capacity. We predicted that these four HPA responses would be positively correlated and that less exploratory birds would have a more rapid onset of the stress response (a CORT elevation during the baseline bleed) and weaker negative feedback (higher CORT after DEX). We found support for the first two predictions but not the third. All four components were positively correlated with each other and less exploratory birds exhibited an elevation in CORT during the baseline bleed (<3min from capture). Less exploratory birds, however, did not exhibit weaker negative feedback following the DEX challenge, but did exhibit weaker adrenal capacity. Together, our findings provide partial support for the hypothesis that the temporal reactivity of the HPA axis is linked with consistent individual differences in behavior, with more cautious (slower exploring) individuals exhibiting a faster CORT response. Copyright © 2017 Elsevier Inc. All rights reserved.

Around the World: Japan. An Exploratory Unit for Middle School Students.

ERIC Educational Resources Information Center

Galloway, Vicki; And Others

One of the units developed as part of the "Around the World" exploratory language program in South Carolina, this unit on Japan aims to develop in students an awareness of Japanese culture through experiential language and cultural activities. The guide has the following components: (1) a list of general and special interest books, and…

Around the World: Peru. An Exploratory Unit for Middle School Students.

ERIC Educational Resources Information Center

Galloway, Vicki; And Others

One of the units developed as part of the "Around the World" exploratory language program in South Carolina, this unit on Peru aims to develop in students an awareness of Peruvian culture through experiential language and cultural activities. The unit guide has six components: (1) a list of resource books, special interest areas, and…

The 1980 US/Canada wheat and barley exploratory experiment. Volume 2: Addenda

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Prior, H. L.; Payne, R. W.; Disler, J. M.

1983-01-01

Three study areas supporting the U.S./Canada Wheat and Barley Exploratory Experiment are discussed including an evaluation of the experiment shakedown test analyst labeling results, an evaluation of the crop proportion estimate procedure 1A component, and the evaluation of spring wheat and barley crop calendar models for the 1979 crop year.

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.

Developing and testing an instrument to measure the presence of conditions for successful implementation of quality improvement collaboratives.

PubMed

Dückers, Michel L A; Wagner, Cordula; Groenewegen, Peter P

2008-08-11

In quality improvement collaboratives (QICs) teams of practitioners from different health care organizations are brought together to systematically improve an aspect of patient care. Teams take part in a series of meetings to learn about relevant best practices, quality methods and change ideas, and share experiences in making changes in their own local setting. The purpose of this study was to develop an instrument for measuring team organization, external change agent support and support from the team's home institution in a Dutch national improvement and dissemination programme for hospitals based on several QICs. The exploratory methodological design included two phases: a) content development and assessment, resulting in an instrument with 15 items, and b) field testing (N = 165). Internal consistency reliability was tested via Cronbach's alpha coefficient. Principal component analyses were used to identify underlying constructs. Tests of scaling assumptions according to the multi trait/multi-item matrix, were used to confirm the component structure. Three components were revealed, explaining 65% of the variability. The components were labelled 'organizational support', 'team organization' and 'external change agent support'. One item not meeting item-scale criteria was removed. This resulted in a 14 item instrument. Scale reliability ranged from 0.77 to 0.91. Internal item consistency and divergent validity were satisfactory. On the whole, the instrument appears to be a promising tool for assessing team organization and internal and external support during QIC implementation. The psychometric properties were good and warrant application of the instrument for the evaluation of the national programme and similar improvement programmes.

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…

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

PubMed

Nguyen, Phuong H

2007-05-15

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

Appearance and Reality in the World of Personnel in a Stressful Educational Setting: Practices Inhibiting School Effectiveness in an Israeli Boarding School.

ERIC Educational Resources Information Center

Aviram, Ovadia

Contrast between the appearances and the reality of several aspects of a school environment, including a participative management style, a democratic leadership style, the principal's image as democratic, and attentiveness to student needs is discussed as related to a boarding school in Israel. During an exploratory case study, observations were…

[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.

Critical Factors Explaining the Leadership Performance of High-Performing Principals

ERIC Educational Resources Information Center

Hutton, Disraeli M.

2018-01-01

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

Molecular dynamics in principal component space.

PubMed

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

2012-07-26

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

Optimized principal component analysis on coronagraphic images of the fomalhaut system

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

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

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

Where did Roman masons get their material from? A preliminary DRIFTS/PCA investigation on mortar aggregates from X Regio buildings in the Veneto area (NE Italy) and their potential sources.

PubMed

De Lorenzi Pezzolo, Alessandra; Colombi, Michela; Mazzocchin, Gian Antonio

2018-05-22

In this work, preliminary results are presented of an ongoing investigation aiming to identify the possible material sources employed by ancient Romans in their building activity in the X Regio, the European region corresponding to present north-eastern Italy and Istria (Croatia and Slovenia). The 63-420 μm fraction of the aggregate component recovered from eleven mortar fragments of buildings located in the Veneto area (in or close to Lio Piccolo, Vicenza, and Padua) is studied by diffuse reflection infrared Fourier transform spectroscopy and compared through principal component analysis to samples collected from local potential sources of raw materials. In this regard, the investigated samples from Lio Piccolo present a distinctive complexity, being this site located within the Venice lagoon, an area that has since been undergoing dramatic changes both due to natural and anthropic causes. The Vicenza and Padua sites were considered for comparison sake because they are or were located close to two rivers, the Bacchiglione and the Brenta, that in ancient times flowed into the Venice lagoon. As expected, from the exploratory investigation reported here, no firm conclusions can be obtained for the mortar samples collected in Lio Piccolo, whereas the likely provenance of the aggregate component of the samples from Vicenza and Padova from the Bacchiglione and the Brenta riverbeds, respectively, is confirmed.

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

PubMed

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

2010-04-01

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

Around the World: India. An Exploratory Unit for Middle School Students.

ERIC Educational Resources Information Center

Galloway, Vicki; And Others

One of the units developed as part of the "Around the World" exploratory language program in South Carolina, this unit on India aims to develop in students an awareness of the culture of the country through experiential language and cultural activities. The guide has the following components: (1) a list of resource books and films; (2)…

Exploratory behavior and withdrawal signs in crayfish: chronic central morphine injections and termination effects.

PubMed

Imeh-Nathaniel, Adebobola; Okon, Marvin; Huber, Robert; Nathaniel, Thomas I

2014-05-01

Functional and evolutionary conservation of neural circuits of reward seeking >is a symbol of survival. It is found in most animals from insects to humans. Exploration is a component of a wide range of drug-elicited behaviors that reflects an appetitive motivational state when animals seek natural rewards such as food, water, and shelter for survival. Not only does the characterization of exploratory behaviors indicate the specific components of appetitive motor patterns, it also reveals how exploratory behavioral patterns are implemented via increased incentive salience of environmental stimuli. The current work demonstrates that novel stimuli appear to directly augment exploration in crayfish, while injections of morphine directly into the brain of crayfish enhanced robust arousal resulting in increased locomotion and exploration of the environment. Elimination of morphine suppressed exploratory motor patterns. Crayfish displayed atypical behavioral changes evident of withdrawal-like states when saline is injected into the brain. With proven evidence of rewarding to the exposure to mammalian drugs of abuse, modularly organized and experimentally accessible nervous system makes crayfish exceptionally suitable for characterizing the central workings of addiction at its key behavioral and neuroanatomic locations. Published by Elsevier B.V.

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

PubMed

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

2017-10-01

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

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Constrained Principal Component Analysis: Various Applications.

ERIC Educational Resources Information Center

Hunter, Michael; Takane, Yoshio

2002-01-01

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

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.

Exploratory factor analysis of the Clinical Learning Environment, Supervision and Nurse Teacher Scale (CLES+T).

PubMed

Watson, Paul Barry; Seaton, Philippa; Sims, Deborah; Jamieson, Isabel; Mountier, Jane; Whittle, Rose; Saarikoski, Mikko

2014-01-01

The Clinical Learning Environment, Supervision and Nurse Teacher (CLES+T) scale measures student nurses' perceptions of clinical learning environments. This study evaluates the construct validity and internal reliability of the CLES+T in hospital settings in New Zealand. Comparisons are made between New Zealand and Finnish data. The CLES+T scale was completed by 416 Bachelor of Nursing students following hospital clinical placements between October 2008 and December 2009. Construct validity and internal reliability were assessed using exploratory factor analysis and Cronbach's alpha. Exploratory factor analysis supports 4 factors. Cronbach's alpha ranged from .82 to .93. All items except 1 loaded on the same factors found in unpublished Finnish data. The first factor combined 2 previous components from the published Finnish component analysis and was renamed: connecting with, and learning in, communities of clinical practice. The remaining 3 factors (Nurse teacher, Supervisory relationship, and Leadership style of the manager) corresponded to previous components and their conceptualizations. The CLES+T has good internal reliability and a consistent factor structure across samples. The consistency across international samples supports faculties and hospitals using the CLES+T to benchmark the quality of clinical learning environments provided to students.

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

PubMed

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

2018-06-01

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

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

PubMed

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

2017-12-01

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

Initial Principal Readiness to Interconnect Positive Behavioral Interventions and Supports and School Mental Health: A Sequential Multivariate Exploratory Analysis

ERIC Educational Resources Information Center

Ecker, Andrew Joseph

2017-01-01

Approximately 20% of youth in the U.S. are experiencing a mental health challenge; a rate that is said to increase by more than 50% by 2020. Schools are the largest provider of mental health services to youth, yet two of schools' most efficacious evidence-based systems, Positive Behavioral Interventions and Supports (PBIS) and school mental health…

SA54. The Structure of Embodied Emotions in Schizophrenia

PubMed Central

Hong, Seok Jin; Snodgress, Matthew A.; Nichols, Heathman S.; Nummenmaa, Lauri; Glerean, Enrico; Park, Sohee

2017-01-01

Abstract Background: Past research suggests a disconnection between experienced emotions and bodily sensations in individuals with schizophrenia (SZ), but mechanisms underlying abnormal embodiment of emotions in SZ are unknown. There might be an overall reduction in emotion-related bodily sensations, but it is also possible that the spatial distribution of bodily sensations associated with emotions may be altered in SZ. We hypothesized the presence of a more coherent underlying structure giving rise to embodied emotions in healthy controls (HC) compared to SZ. Methods: Fifteen SZ and 15 demographically matched HC (bootstrapped from a possible 300 HC) were asked to complete the emBODY task (Nummenmaa et al., 2014). In the emBODY task, participants were asked to shade in where they felt sensations (activation and deactivation) on the outline of a human body when presented with an emotion word. Fourteen emotion words were presented sequentially. From activation and deactivation data, body maps of emotions were generated and 2 separate principal components analyses (PCA) were conducted, one for each group to determine the multivariate structure of embodied emotions. Results: The pattern of principal components for HC differed significantly from that of the SZ group. SZ showed more diffuse components with lesser magnitude than the HC. Moreover, the variance that accounts for these dimensions was significantly reduced for SZ. This suggests anomalous embodied emotion in SZ. In this PCA framework, a particular set of innate constructs is thought to yield the activation and deactivation maps of emotions on the body. Our results imply that the complexity of this set in SZ is highly deviant from that of the HC. Conclusion: Quantitative modeling of the underlying structure of self-reported embodied emotion provided novel insight into altered emotional experience in SZ. Our findings illustrate radically different bodily maps of emotions in SZ compared to HC. Bodily sensations are not only different in intensity but also in where they are felt in SZ. While an important first step, our analysis was exploratory and limited by the small sample size. Future direction includes probing the specific contents of the underlying dimensions that give rise to embodied emotions.

Exploratory factor analysis of borderline personality disorder criteria in hospitalized adolescents.

PubMed

Becker, Daniel F; McGlashan, Thomas H; Grilo, Carlos M

2006-01-01

The authors examined the factor structure of borderline personality disorder (BPD) in hospitalized adolescents and also sought to add to the theoretical and clinical understanding of any homogeneous components by determining whether they may be related to specific forms of Axis I pathology. Subjects were 123 adolescent inpatients, who were reliably assessed with structured diagnostic interviews for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition Axes I and II disorders. Exploratory factor analysis identified BPD components, and logistic regression analyses tested whether these components were predictive of specific Axis I disorders. Factor analysis revealed a 4-factor solution that accounted for 67.0% of the variance. Factor 1 ("suicidal threats or gestures" and "emptiness or boredom") predicted depressive disorders and alcohol use disorders. Factor 2 ("affective instability," "uncontrolled anger," and "identity disturbance") predicted anxiety disorders and oppositional defiant disorder. Factor 3 ("unstable relationships" and "abandonment fears") predicted only anxiety disorders. Factor 4 ("impulsiveness" and "identity disturbance") predicted conduct disorder and substance use disorders. Exploratory factor analysis of BPD criteria in adolescent inpatients revealed 4 BPD factors that appear to differ from those reported for similar studies of adults. The factors represent components of self-negation, irritability, poorly modulated relationships, and impulsivity--each of which is associated with characteristic Axis I pathology. These findings shed light on the nature of BPD in adolescents and may also have implications for treatment.

Source Apportionment and Risk Assessment of Emerging Contaminants: An Approach of Pharmaco-Signature in Water Systems

PubMed Central

Jiang, Jheng Jie; Lee, Chon Lin; Fang, Meng Der; Boyd, Kenneth G.; Gibb, Stuart W.

2015-01-01

This paper presents a methodology based on multivariate data analysis for characterizing potential source contributions of emerging contaminants (ECs) detected in 26 river water samples across multi-scape regions during dry and wet seasons. Based on this methodology, we unveil an approach toward potential source contributions of ECs, a concept we refer to as the “Pharmaco-signature.” Exploratory analysis of data points has been carried out by unsupervised pattern recognition (hierarchical cluster analysis, HCA) and receptor model (principal component analysis-multiple linear regression, PCA-MLR) in an attempt to demonstrate significant source contributions of ECs in different land-use zone. Robust cluster solutions grouped the database according to different EC profiles. PCA-MLR identified that 58.9% of the mean summed ECs were contributed by domestic impact, 9.7% by antibiotics application, and 31.4% by drug abuse. Diclofenac, ibuprofen, codeine, ampicillin, tetracycline, and erythromycin-H2O have significant pollution risk quotients (RQ>1), indicating potentially high risk to aquatic organisms in Taiwan. PMID:25874375

STRUCTURE OF THE UNIVERSITY PERSONALITY INVENTORY FOR CHINESE COLLEGE STUDENTS1,2

PubMed Central

ZHANG, JIETING; LANZA, STEPHANIE; ZHANG, MINQIANG; SU, BINYUAN

2016-01-01

Summary The University Personality Inventory, a mental health instrument for college students, is frequently used for screening in China. However, its unidimensionality has been questioned. This study examined its dimensions to provide more information about the specific mental problems for students at risk. Four subsamples were randomly created from a sample (N = 6,110; M age = 19.1 yr.) of students at a university in China. Principal component analysis with Promax rotation was applied on the first two subsamples to explore dimension of the inventory. Confirmatory factor analysis was conducted on the third subsample to verify the exploratory dimensions. Finally, the identified factors were compared to the Sympton Checklist–90 (SCL–90) to support validity, and sex differences were examined, based on the fourth subsample. Five factors were identified: Physical Symptoms, Cognitive Symptoms, Emotional Vulnerability, Social Avoidance, and Interpersonal Sensitivity, accounting for 60.3% of the variance. All the five factors were significantly correlated with the SCL–90. Women significantly scored higher than men on Cognitive Symptoms and Interpersonal Sensitivity. PMID:25933045

Assessment of knowledge of nurses regarding bioethics.

PubMed

Saini, Radha; Saini, Parvesh; Alagh, Preety

2014-01-01

Nurses involved in research, whether as a principal investigator, a study coordinator, clinical trials nurse, or as a staff nurse caring for patients who are research subjects have a responsibility to promote the ethical conduct of clinical research. Will a registered nurse be ever able to challenge and infact unearth the unscrupulous medical practices which make poor patients guinea pigs in pharmaceutical company-sponsored clinical trials? Keeping this in view an exploratory study was carried out to assess the knowledge of bioethics among MSc Nursing students studying in recognised Nursing Colleges of North India. 92 percent of MSc nursing students scored below average knowledge regarding bioethics even after studying ethics in MSc (N) 1st year and B.Sc. Nursing degree programme. This research study strongly recommends the Indian Nursing Council-the statutory licensing body of nurses in India to ensure strict compliance of all researches (at masters as well as bachelors level) in nursing education with all the principles and components of bioethics. Need of the hour is to include at least one clinical nurse in the Institutional Ethics Committee in every medical and research institution.

Managers' perceptions of customers' satisfactions with their hospital cafeteria services.

PubMed

Johnston, C M; Upton, E M

1991-01-01

It is important that hospital cafeterias deliver products that create customer satisfaction so that financial objectives are met. An exploratory descriptive survey of 12 selected hospital cafeterias used a self-administered questionnaire to determine how satisfied customers were with services provided. It also asked cafeteria managers to give their perceptions of their customers' relative satisfaction/dissatisfaction with the service. Principal components analysis, followed by varimax rotation, identified four underlying constructs of the 15 pre-selected foodservice characteristics used to measure relative satisfaction. A multiple regression model, controlling for country, hospital size and customer demographics, in which the dependent variable was overall rating, found that the independent variables, the underlying rating constructs--food and service--made a much greater impact on overall rating than environment and accessibility. Most cafeteria managers' predictions about their customers' satisfaction were within two standard deviations of their customers' mean scores of satisfaction. While the managers' close association with their service may have accounted for this, it does not necessarily follow that they have the power to implement policy and product improvements.

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

PubMed

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

2015-02-25

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

Raman spectroscopy of bio fluids: an exploratory study for oral cancer detection

NASA Astrophysics Data System (ADS)

Brindha, Elumalai; Rajasekaran, Ramu; Aruna, Prakasarao; Koteeswaran, Dornadula; Ganesan, Singaravelu

2016-03-01

ion for various disease diagnosis including cancers. Oral cancer is one of the most common cancers in India and it accounts for one third of the global oral cancer burden. Raman spectroscopy of tissues has gained much attention in the diagnostic oncology, as it provides unique spectral signature corresponding to metabolic alterations under different pathological conditions and micro-environment. Based on these, several studies have been reported on the use of Raman spectroscopy in the discrimination of diseased conditions from their normal counterpart at cellular and tissue level but only limited studies were available on bio-fluids. Recently, optical characterization of bio-fluids has also geared up for biomarker identification in the disease diagnosis. In this context, an attempt was made to study the metabolic variations in the blood, urine and saliva of oral cancer patients and normal subjects using Raman spectroscopy. Principal Component based Linear Discriminant Analysis (PC-LDA) followed by Leave-One-Out Cross-Validation (LOOCV) was employed to find the statistical significance of the present technique in discriminating the malignant conditions from normal subjects.

Development of the Sri Lankan early teenagers' violence inventory: an instrument to measure peer violence in schools.

PubMed

Wijeratne, Monika; Seneviratne, Rohini; Gunawardena, Nalika; Østbye, Truls; Lynch, Catherine; Sandøy, Ingvild Fossgard

2014-01-01

This study was designed to develop an inventory to measure peer violence among early teens (13-15 years of age) in schools in Sri Lanka. Development of SLETVI was carried out in two phases. In phase I, development of an operational definition for peer violence, identification, and finalizing violent acts for inventory was done by a combination of qualitative methods: a comprehensive literature review, focus group discussions among 13-15-year-old adolescents, their teachers and parents, and consultative meetings with experts in the field. Inventory was then pretested. In phase II, elaboration of SLETVI was carried out by administering it to a sample of 1700 adolescents (13-15 years old). Exploratory factor analysis using principal component analysis was performed separately for experiences of victimization and perpetration. Test-retest reliability of SLETVI was assessed. SLETVI included 37 items in three factors: "less severe violence," "severe physical," and "severe relational" violence. Combined use of qualitative and quantitative methods enabled development of a culturally valid and reliable operational inventory to assess early teenagers' peer violence in Sri Lankan and other South Asian schools.

Software for Displaying Data from Planetary Rovers

NASA Technical Reports Server (NTRS)

Powell, Mark; Backers, Paul; Norris, Jeffrey; Vona, Marsette; Steinke, Robert

2003-01-01

Science Activity Planner (SAP) DownlinkBrowser is a computer program that assists in the visualization of processed telemetric data [principally images, image cubes (that is, multispectral images), and spectra] that have been transmitted to Earth from exploratory robotic vehicles (rovers) on remote planets. It is undergoing adaptation to (1) the Field Integrated Design and Operations (FIDO) rover (a prototype Mars-exploration rover operated on Earth as a test bed) and (2) the Mars Exploration Rover (MER) mission. This program has evolved from its predecessor - the Web Interface for Telescience (WITS) software - and surpasses WITS in the processing, organization, and plotting of data. SAP DownlinkBrowser creates Extensible Markup Language (XML) files that organize data files, on the basis of content, into a sortable, searchable product database, without the overhead of a relational database. The data-display components of SAP DownlinkBrowser (descriptively named ImageView, 3DView, OrbitalView, PanoramaView, ImageCubeView, and SpectrumView) are designed to run in a memory footprint of at least 256MB on computers that utilize the Windows, Linux, and Solaris operating systems.

Surface Enhanced Raman Spectroscopy (SERS) and multivariate analysis as a screening tool for detecting Sudan I dye in culinary spices

NASA Astrophysics Data System (ADS)

Di Anibal, Carolina V.; Marsal, Lluís F.; Callao, M. Pilar; Ruisánchez, Itziar

2012-02-01

Raman spectroscopy combined with multivariate analysis was evaluated as a tool for detecting Sudan I dye in culinary spices. Three Raman modalities were studied: normal Raman, FT-Raman and SERS. The results show that SERS is the most appropriate modality capable of providing a proper Raman signal when a complex matrix is analyzed. To get rid of the spectral noise and background, Savitzky-Golay smoothing with polynomial baseline correction and wavelet transform were applied. Finally, to check whether unadulterated samples can be differentiated from samples adulterated with Sudan I dye, an exploratory analysis such as principal component analysis (PCA) was applied to raw data and data processed with the two mentioned strategies. The results obtained by PCA show that Raman spectra need to be properly treated if useful information is to be obtained and both spectra treatments are appropriate for processing the Raman signal. The proposed methodology shows that SERS combined with appropriate spectra treatment can be used as a practical screening tool to distinguish samples suspicious to be adulterated with Sudan I dye.

Multi-wavelength HPLC fingerprints from complex substances: An exploratory chemometrics study of the Cassia seed example.

PubMed

Ni, Yongnian; Lai, Yanhua; Brandes, Sarina; Kokot, Serge

2009-08-11

Multi-wavelength fingerprints of Cassia seed, a traditional Chinese medicine (TCM), were collected by high-performance liquid chromatography (HPLC) at two wavelengths with the use of diode array detection. The two data sets of chromatograms were combined by the data fusion-based method. This data set of fingerprints was compared separately with the two data sets collected at each of the two wavelengths. It was demonstrated with the use of principal component analysis (PCA), that multi-wavelength fingerprints provided a much improved representation of the differences in the samples. Thereafter, the multi-wavelength fingerprint data set was submitted for classification to a suite of chemometrics methods viz. fuzzy clustering (FC), SIMCA and the rank ordering MCDM PROMETHEE and GAIA. Each method highlighted different properties of the data matrix according to the fingerprints from different types of Cassia seeds. In general, the PROMETHEE and GAIA MCDM methods provided the most comprehensive information for matching and discrimination of the fingerprints, and appeared to be best suited for quality assurance purposes for these and similar types of sample.

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

PubMed Central

Meyer, Karin; Kirkpatrick, Mark

2005-01-01

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

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

USGS Publications Warehouse

Morin, R.H.

1997-01-01

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

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

PubMed

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

2018-05-10

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

Dascălu, Cristina Gena; Antohe, Magda Ecaterina

2009-01-01

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

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

ERIC Educational Resources Information Center

Mugrage, Beverly; And Others

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

A Note on McDonald's Generalization of Principal Components Analysis

ERIC Educational Resources Information Center

Shine, Lester C., II

1972-01-01

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

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

PubMed Central

Peterson, Leif E

2002-01-01

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

The Complexity of Human Walking: A Knee Osteoarthritis Study

PubMed Central

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

2014-01-01

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

Principal Components Analysis of a JWST NIRSpec Detector Subsystem

NASA Technical Reports Server (NTRS)

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

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

PubMed

Ghosh, Debasree; Chattopadhyay, Parimal

2012-06-01

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

Contribution to the understanding of how principal component analysis-derived dietary patterns emerge from habitual data on food consumption.

PubMed

Schwedhelm, Carolina; Iqbal, Khalid; Knüppel, Sven; Schwingshackl, Lukas; Boeing, Heiner

2018-02-01

Principal component analysis (PCA) is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet. Such dietary patterns seem to originate from intakes on multiple days and eating occasions. Therefore, analyzing food intake of study populations with different levels of food consumption can provide additional insights as to how habitual dietary patterns are formed. We analyzed the food intake data of German adults in terms of the relations among food groups from three 24-h dietary recalls (24hDRs) on the habitual, single-day, and main-meal levels, and investigated the contribution of each level to the formation of PCA-derived habitual dietary patterns. Three 24hDRs were collected in 2010-2012 from 816 adults for an European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam subcohort study. We identified PCA-derived habitual dietary patterns and compared cross-sectional food consumption data in terms of correlation (Spearman), consistency (intraclass correlation coefficient), and frequency of consumption across all days and main meals. Contribution to the formation of the dietary patterns was obtained through Spearman correlation of the dietary pattern scores. Among the meals, breakfast appeared to be the most consistent eating occasion within individuals. Dinner showed the strongest correlations with "Prudent" (Spearman correlation = 0.60), "Western" (Spearman correlation = 0.59), and "Traditional" (Spearman correlation = 0.60) dietary patterns identified on the habitual level, and lunch showed the strongest correlations with the "Cereals and legumes" (Spearman correlation = 0.60) habitual dietary pattern. Higher meal consistency was related to lower contributions to the formation of PCA-derived habitual dietary patterns. Absolute amounts of food consumption did not strongly conform to the habitual dietary patterns by meals, suggesting that these patterns are formed by complex combinations of variable food consumption across meals. Dinner showed the highest contribution to the formation of habitual dietary patterns. This study provided information about how PCA-derived dietary patterns are formed and how they could be influenced.

Probabilisitc Geobiological Classification Using Elemental Abundance Distributions and Lossless Image Compression in Recent and Modern Organisms

NASA Technical Reports Server (NTRS)

Storrie-Lombardi, Michael C.; Hoover, Richard B.

2005-01-01

Last year we presented techniques for the detection of fossils during robotic missions to Mars using both structural and chemical signatures[Storrie-Lombardi and Hoover, 2004]. Analyses included lossless compression of photographic images to estimate the relative complexity of a putative fossil compared to the rock matrix [Corsetti and Storrie-Lombardi, 2003] and elemental abundance distributions to provide mineralogical classification of the rock matrix [Storrie-Lombardi and Fisk, 2004]. We presented a classification strategy employing two exploratory classification algorithms (Principal Component Analysis and Hierarchical Cluster Analysis) and non-linear stochastic neural network to produce a Bayesian estimate of classification accuracy. We now present an extension of our previous experiments exploring putative fossil forms morphologically resembling cyanobacteria discovered in the Orgueil meteorite. Elemental abundances (C6, N7, O8, Na11, Mg12, Ai13, Si14, P15, S16, Cl17, K19, Ca20, Fe26) obtained for both extant cyanobacteria and fossil trilobites produce signatures readily distinguishing them from meteorite targets. When compared to elemental abundance signatures for extant cyanobacteria Orgueil structures exhibit decreased abundances for C6, N7, Na11, All3, P15, Cl17, K19, Ca20 and increases in Mg12, S16, Fe26. Diatoms and silicified portions of cyanobacterial sheaths exhibiting high levels of silicon and correspondingly low levels of carbon cluster more closely with terrestrial fossils than with extant cyanobacteria. Compression indices verify that variations in random and redundant textural patterns between perceived forms and the background matrix contribute significantly to morphological visual identification. The results provide a quantitative probabilistic methodology for discriminating putatitive fossils from the surrounding rock matrix and &om extant organisms using both structural and chemical information. The techniques described appear applicable to the geobiological analysis of meteoritic samples or in situ exploration of the Mars regolith. Keywords: cyanobacteria, microfossils, Mars, elemental abundances, complexity analysis, multifactor analysis, principal component analysis, hierarchical cluster analysis, artificial neural networks, paleo-biosignatures

Genome Data Exploration Using Correspondence Analysis

PubMed Central

Tekaia, Fredj

2016-01-01

Recent developments of sequencing technologies that allow the production of massive amounts of genomic and genotyping data have highlighted the need for synthetic data representation and pattern recognition methods that can mine and help discovering biologically meaningful knowledge included in such large data sets. Correspondence analysis (CA) is an exploratory descriptive method designed to analyze two-way data tables, including some measure of association between rows and columns. It constructs linear combinations of variables, known as factors. CA has been used for decades to study high-dimensional data, and remarkable inferences from large data tables were obtained by reducing the dimensionality to a few orthogonal factors that correspond to the largest amount of variability in the data. Herein, I review CA and highlight its use by considering examples in handling high-dimensional data that can be constructed from genomic and genetic studies. Examples in amino acid compositions of large sets of species (viruses, phages, yeast, and fungi) as well as an example related to pairwise shared orthologs in a set of yeast and fungal species, as obtained from their proteome comparisons, are considered. For the first time, results show striking segregations between yeasts and fungi as well as between viruses and phages. Distributions obtained from shared orthologs show clusters of yeast and fungal species corresponding to their phylogenetic relationships. A direct comparison with the principal component analysis method is discussed using a recently published example of genotyping data related to newly discovered traces of an ancient hominid that was compared to modern human populations in the search for ancestral similarities. CA offers more detailed results highlighting links between modern humans and the ancient hominid and their characterizations. Compared to the popular principal component analysis method, CA allows easier and more effective interpretation of results, particularly by the ability of relating individual patterns with their corresponding characteristic variables. PMID:27279736

When Contact Is Not Enough: Affecting First Year Medical Students’ Image towards Older Persons

PubMed Central

van Fenema, Esther; Polman-van Stratum, Eugenie C. F.; Achterberg, Wilco; Westendorp, Rudi G. J.

2017-01-01

Context Many medical schools have initiated care internships to familiarize their students with older persons and to instil a professional attitude. Objective To examine the impact of care internships on the image that first-year medical students have of older persons and to explore the underlying concepts that may play a role in shaping this image. Design Survey before and after a two-week compulsory care internship using the Aging Semantic Differential (ASD; 32 adjectives) and the Attitudes toward Old People (AOP; 34 positions) questionnaires. Participants Before and after a care internship involving interpersonal contact, 252 and 244 first-year medical students at the Leiden University Medical Centre (LUMC) in the academic year 2012–2013 participated. Method Descriptive statistics, analyses of variance, and principal component analysis were used; clusters of adjectives and positions were reduced into concepts to examine dominant patterns of views. Changes in image were investigated as mean differences of the total and concept scores. Results Both the ASD and the AOP questionnaires showed a poor general image of older persons that significantly worsened after the care internship (p < 0.01). The percentage of students considering over 75 years as being old increased from 17.2% to 31.2% (p < 0.01) and those who thought they would find as much satisfaction in care for older as for younger patients decreased from 78.5% to 62.1% (p < 0.001). Exploratory principal component analysis showed particularly low scores on ‘comportment’ and ‘pleasurable interaction’ whereas the scores on ‘personality traits’ and ‘habitual behaviour’ significantly deteriorated (both p < 0.001). These patterns were irrespective of the student’s gender and previous contact experience. Conclusion Medical schools should carefully consider care internships to ensure that students do not worsen their views on older patients, which may occur due to inadequate contact depth and quality within a rather unsupportive context. PMID:28107400

Exploratory factor analysis of borderline personality disorder criteria in monolingual Hispanic outpatients with substance use disorders†

PubMed Central

Becker, Daniel F.; Añez, Luis Miguel; Paris, Manuel; Grilo, Carlos M.

2009-01-01

This study examined the factor structure of the DSM-IV criteria for borderline personality disorder (BPD) in Hispanic patients. Subjects were 130 monolingual Hispanic adults who had been admitted to a specialty outpatient clinic that provides psychiatric and substance abuse services to Spanish-speaking individuals. All were reliably assessed with the Spanish-Language Version of the Diagnostic Interview for DSM-IV Personality Disorders. After evaluating internal consistency of the BPD criterion set, an exploratory factor analysis was performed using principal axis factoring. Results suggested a unidimensional structure, and were consistent with similar studies of the DSM-IV criteria for BPD in non-Hispanic samples. These findings have implications for understanding borderline psychopathology in this population, and for the overall validity of the DSM-IV BPD construct. PMID:20472296

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

NASA Astrophysics Data System (ADS)

Lim, Hoong-Ta; Murukeshan, Vadakke Matham

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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.

Understanding Coordination of Care from the Consumer's Perspective in a Regional Health System

PubMed Central

Harrison, Alexandra; Verhoef, Marja

2002-01-01

Objective To understand and develop a model about the meaning of coordination to consumers who experienced a transition from acute care to home care. Study Design A qualitative, exploratory study using Grounded Theory. Data Sources/Analysis Thirty-three consumers in the Calgary Regional Health Authority who had experienced the transition from an acute care hospital back into the community with home care support were interviewed. They were asked to describe their transition experience and what aspects of coordination were important to them. Interviews were recorded, transcribed, and analyzed using constant comparison. The coding and retrieval of information was facilitated by the computer software program Nud*ist. Principal Findings The resulting model has four components: (1) the meaning of coordination to consumers; (2) aspects of health care system support that are important for coordination; (3) elements that prepared consumers to return home; and (4) the components of a successful transition experience. Consumers appeared to play a crucial role in spanning organizational boundaries by participating in the coordination of their own care. Conclusions Consumers must be included in health care decisions as recipients of services and major players in the transition processes related to their care. Health care providers need to ensure that consumers are prepared to carry out their coordination role and managers need to foster a culture that values the consumer “voice” in organizational processes. PMID:12236382

The scale on community care perceptions (scope) for nursing students: A development and psychometric validation study.

PubMed

van Iersel, Margriet; de Vos, Rien; Latour, Corine; Kirschner, Paul A; Scholte Op Reimer, Wilma

2018-05-11

The aim of this study was to develop a valid instrument to measure student nurses' perceptions of community care (SCOPE). DeVellis' staged model for instrument development and validation was used. Scale construction of SCOPE was based on existing literature. Evaluation of its psychometric properties included exploratory factor analysis and reliability analysis. After pilot-testing, 1062 bachelor nursing students from six institutions in the Netherlands (response rate 81%) took part in the study. SCOPE is a 35-item scale containing: background variables, 11 measuring the affective component, 5 measuring community care perception as a placement, 17 as a future profession, and 2 on the reasons underlying student preference. Principal axis factoring yielded two factors in the affective component scale reflecting 'enjoyment' and 'utility', two in the placement scale reflecting 'learning possibilities' and 'personal satisfaction', and four in the profession scale: 'professional development', 'collaboration', 'caregiving', and 'complexity and workload'. Cronbach's α of the complete scale was 0.892 and of the subscales 0.862, 0.696, and 0.810 respectively. SCOPE is a psychometrically sound instrument for measuring students' perceptions of community care. By determining these perceptions, it becomes possible to positively influence them with targeted curriculum redesign, eventually contributing to decreasing the workforce shortage in community nursing. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Psychometric properties of the Generalized Anxiety Disorder Inventory in a Canadian sample.

PubMed

Henderson, Leigh C; Antony, Martin M; Koerner, Naomi

2014-05-01

The Generalized Anxiety Disorder Inventory is a recently developed self-report measure that assesses symptoms of generalized anxiety disorder. Its psychometric properties have not been investigated further since its original development. The current study investigated its psychometric properties in a Canadian student/community sample. Exploratory principal component analysis replicated the original three-component structure. The total scale and subscales demonstrated excellent internal consistency reliability (α = 0.84-0.94) and correlated strongly with the Penn State Worry Questionnaire (r = 0.41-0.74, all ps <0.001) and Generalized Anxiety Disorder-7 (r = 0.55-0.84, all ps <0.001). However, only the total scale and cognitive subscale (r = 0.48-0.49, all ps <0.05) significantly predicted generalized anxiety disorder diagnosis established by diagnostic interview. The somatic subscale in particular may require revision to improve predictive validity. Revision may also be necessary given changes in required somatic symptoms for generalized anxiety disorder diagnostic criteria in more recent versions of the Diagnostic and Statistical Manual of Mental Disorders (i.e. although major changes occurred from Diagnostic and Statistical Manual of Mental Disorders-III-R to Diagnostic and Statistical Manual of Mental Disorders-IV, changes in Diagnostic and Statistical Manual of Mental Disorders-5 were minimal) and the possibility of changes in the upcoming 11th revision of the International Classification of Diseases.

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.

The Provision of Sexual and Reproductive Health Education to Children in a Remote Mountainous Commune in Rural Vietnam: An Exploratory Study of Parents' Views

ERIC Educational Resources Information Center

Ha, Tran Thi Thu; Fisher, Jane R. W.

2011-01-01

The purpose of this study was to explore the expectations of parents in a remote mountainous commune in Vietnam about sexual and reproductive health (SRH) education for their children. Separate in-depth interviews were conducted with 34 parents of eight-year-old children and key informants including a principal, a teacher and staff of the Youth…

Exploratory Study to Determine the Feasibility of a Comprehensive Program for the Development of Special Education Services for Emotionally Disturbed Children in Arizona, Nevada, New Mexico, and Utah. Final Report.

ERIC Educational Resources Information Center

Holmberg, Gerald R.

Group conferences, individual study groups, personal visitations, and communication by the principal investigator were utilized to determine the availability and suitability of services for emotionally disturbed children in the four-state area o f Arizona, New Mexico, Utah, and Nevada which has a low incidence of population in vast territorial…

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

PubMed Central

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

PubMed

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

2014-03-01

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

Principal components of wrist circumduction from electromagnetic surgical tracking.

PubMed

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

2017-02-01

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

Multidimensional structure of a questionnaire to assess barriers to and motivators of physical activity in recipients of solid organ transplantation.

PubMed

van Adrichem, Edwin J; Krijnen, Wim P; Dekker, Rienk; Ranchor, Adelita V; Dijkstra, Pieter U; van der Schans, Cees P

2017-11-01

To explore the underlying dimensions of the Barriers and Motivators Questionnaire that is used to assess barriers to and motivators of physical activity experienced by recipients of solid organ transplantation and thereby improve the application in research and clinical settings. A cross-sectional study was performed in recipients of solid organ transplantation (n = 591; median (IQR) age = 59 (49; 66); 56% male). The multidimensional structure of the questionnaire was analyzed by exploratory principal component analysis. Cronbach's α was calculated to determine internal consistency of the entire questionnaire and individual components. The barriers scale had a Cronbach's α of 0.86 and was subdivided into four components; α of the corresponding subscales varied between 0.80 and 0.66. The motivator scale had an α of 0.91 and was subdivided into four components with an α between 0.88 to 0.70. Nine of the original barrier items and two motivator items were not included in the component structure. A four-dimensional structure for both the barriers and motivators scale of the questionnaire is supported. The use of the indicated subscales increases the usability in research and clinical settings compared to the overall scores and provide opportunities to identify modifiable constructs to be targeted in interventions. Implications for rehabilitation Organ transplant recipients are less active than the general population despite established health benefits of physical activity. A multidimensional structure is shown in the Barriers and Motivators Questionnaire, the use of the identified subscales increases applicability in research and clinical settings. The use of the questionnaire with its component structure in the clinical practice of a rehabilitation physician could result in a faster assessment of problem areas in daily practice and result in a higher degree of clarity as opposed to the use of the individual items of the questionnaire.

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

Treesearch

J. G. Isebrands; Thomas R. Crow

1975-01-01

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

Principal component analysis of phenolic acid spectra

USDA-ARS?s Scientific Manuscript database

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

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

NASA Astrophysics Data System (ADS)

Ueki, Kenta; Iwamori, Hikaru

2017-10-01

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

Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals

PubMed Central

Dicke, Theresa; Marsh, Herbert W.; Riley, Philip; Parker, Philip D.; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals (N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors. PMID:29760670

Validating the Copenhagen Psychosocial Questionnaire (COPSOQ-II) Using Set-ESEM: Identifying Psychosocial Risk Factors in a Sample of School Principals.

PubMed

Dicke, Theresa; Marsh, Herbert W; Riley, Philip; Parker, Philip D; Guo, Jiesi; Horwood, Marcus

2018-01-01

School principals world-wide report high levels of strain and attrition resulting in a shortage of qualified principals. It is thus crucial to identify psychosocial risk factors that reflect principals' occupational wellbeing. For this purpose, we used the Copenhagen Psychosocial Questionnaire (COPSOQ-II), a widely used self-report measure covering multiple psychosocial factors identified by leading occupational stress theories. We evaluated the COPSOQ-II regarding factor structure and longitudinal, discriminant, and convergent validity using latent structural equation modeling in a large sample of Australian school principals ( N = 2,049). Results reveal that confirmatory factor analysis produced marginally acceptable model fit. A novel approach we call set exploratory structural equation modeling (set-ESEM), where cross-loadings were only allowed within a priori defined sets of factors, fit well, and was more parsimonious than a full ESEM. Further multitrait-multimethod models based on the set-ESEM confirm the importance of a principal's psychosocial risk factors; Stressors and depression were related to demands and ill-being, while confidence and autonomy were related to wellbeing. We also show that working in the private sector was beneficial for showing a low psychosocial risk, while other demographics have little effects. Finally, we identify five latent risk profiles (high risk to no risk) of school principals based on all psychosocial factors. Overall the research presented here closes the theory application gap of a strong multi-dimensional measure of psychosocial risk-factors.

Sexuality and HIV Education in Charter Schools: An Exploratory Study With Principals in San Diego County, California.

PubMed

Walsh-Buhi, Eric R; Dao, Brandon; Salgin, Linda; Marshall, James; Miller, Rachel; Fisher, Doug; Walsh-Buhi, Margaret

2017-04-01

Schools can address critical sexual and reproductive health (SRH) issues among youth. However, little is known about SRH education being implemented in charter schools. Thus, our purpose was to explore implementation of SRH education in charter schools. Using purposive sampling, semistructured telephone interviews were conducted with 20 charter school principals in San Diego County, California. Questions were guided by the Kaiser Family Foundation National Survey of Public Secondary School Principals. Analyses followed a case-oriented approach, examining aspects within each case (ie, a principal), and then a comparative analysis of a small number of cases (ie, all principals). Overall, 17 principals acknowledged offering sexuality education in the previous 2 years. Over half of these schools had provided content on: sexually transmitted diseases/human immunodeficiency virus/acquired immune deficiency syndrome (STDs/HIV/AIDS), reproduction/pregnancy/birth, pregnancy prevention methods, delaying sex, and managing sexual pressure. Condom use, sexual assault, sexual orientation, talking with partners about STD/pregnancy prevention, talking with parents about relationships/sex, and using/where to get contraception were less commonly taught. Abortion was not addressed. When asked the grade they would assign to their schools' sexuality/HIV instruction, principals assigned 1 A, 7 Bs, 7 Cs, and 1 D. Consistency between our findings and what has been reported elsewhere varies. As charter schools often have greater curricular flexibility than traditional schools, this study provides unique preliminary data to inform future innovative, or strengthen existing, SRH programming. © 2017, American School Health Association.

Multicollinearity in prognostic factor analyses using the EORTC QLQ-C30: identification and impact on model selection.

PubMed

Van Steen, Kristel; Curran, Desmond; Kramer, Jocelyn; Molenberghs, Geert; Van Vreckem, Ann; Bottomley, Andrew; Sylvester, Richard

2002-12-30

Clinical and quality of life (QL) variables from an EORTC clinical trial of first line chemotherapy in advanced breast cancer were used in a prognostic factor analysis of survival and response to chemotherapy. For response, different final multivariate models were obtained from forward and backward selection methods, suggesting a disconcerting instability. Quality of life was measured using the EORTC QLQ-C30 questionnaire completed by patients. Subscales on the questionnaire are known to be highly correlated, and therefore it was hypothesized that multicollinearity contributed to model instability. A correlation matrix indicated that global QL was highly correlated with 7 out of 11 variables. In a first attempt to explore multicollinearity, we used global QL as dependent variable in a regression model with other QL subscales as predictors. Afterwards, standard diagnostic tests for multicollinearity were performed. An exploratory principal components analysis and factor analysis of the QL subscales identified at most three important components and indicated that inclusion of global QL made minimal difference to the loadings on each component, suggesting that it is redundant in the model. In a second approach, we advocate a bootstrap technique to assess the stability of the models. Based on these analyses and since global QL exacerbates problems of multicollinearity, we therefore recommend that global QL be excluded from prognostic factor analyses using the QLQ-C30. The prognostic factor analysis was rerun without global QL in the model, and selected the same significant prognostic factors as before. Copyright 2002 John Wiley & Sons, Ltd.

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

ERIC Educational Resources Information Center

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

1997-01-01

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

Time series analysis of collective motions in proteins

NASA Astrophysics Data System (ADS)

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

2004-01-01

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

Staff preparedness for providing palliative and end-of-life care in long-term care homes: Instrument development and validation.

PubMed

Chan, Helen Yl; Chun, Gloria Km; Man, C W; Leung, Edward Mf

2018-05-01

Although much attention has been on integrating the palliative care approach into services of long-term care homes for older people living with frailty and progressive diseases, little is known about the staff preparedness for these new initiatives. The present study aimed to develop and test the psychometric properties of an instrument for measuring care home staff preparedness in providing palliative and end-of-life care. A 16-item instrument, covering perceived knowledge, skill and psychological readiness, was developed. A total of 247 staff members of different ranks from four care homes participated in the study. Exploratory factor analysis using the principal component analysis extraction method with varimax rotation was carried out for initial validation. Known group comparison was carried out to examine its discriminant validity. Reliability of the instrument was assessed based on test-retest reliability of a subsample of 20 participants and the Cronbach's alpha of the items. Exploratory factor analysis showed that the instrument yielded a three-factor solution, which cumulatively accounted for 68.5% of the total variance. Three subscales, namely, willingness, capability and resilience, showed high internal consistency and test-retest reliability. It also showed good discriminant validity between staff members of professional and non-professional groups. This is a brief, valid and reliable scale for measuring care home staff preparedness for providing palliative and end-of-life care. It can be used to identify their concerns and training needs in providing palliative and end-of-life care, and as an outcome measure to evaluate the effects of interventional studies for capacity building in this regard. Geriatr Gerontol Int 2018; 18: 745-749. © 2018 Japan Geriatrics Society.

Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

PubMed

Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

2013-01-01

Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

Factor structure and diagnostic efficiency of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for avoidant personality disorder in Hispanic men and women with substance use disorders.

PubMed

Becker, Daniel F; Añez, Luis Miguel; Paris, Manuel; Bedregal, Luis; Grilo, Carlos M

2009-01-01

This study examined the internal consistency, factor structure, and diagnostic efficiency of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), criteria for avoidant personality disorder (AVPD) and the extent to which these metrics may be affected by sex. Subjects were 130 monolingual Hispanic adults (90 men, 40 women) who had been admitted to a specialty clinic that provides psychiatric and substance abuse services to Spanish-speaking patients. All were reliably assessed with the Spanish-Language Version of the Diagnostic Interview for DSM-IV Personality Disorders. The AVPD diagnosis was determined by the best-estimate method. After evaluating internal consistency of the AVPD criterion set, an exploratory factor analysis was performed using principal components extraction. Afterward, diagnostic efficiency indices were calculated for all AVPD criteria. Subsequent analyses examined men and women separately. For the overall group, internal consistency of AVPD criteria was good. Exploratory factor analysis revealed a 1-factor solution (accounting for 70% of the variance), supporting the unidimensionality of the AVPD criterion set. The best inclusion criterion was "reluctance to take risks," whereas "interpersonally inhibited" was the best exclusion criterion and the best predictor overall. When men and women were examined separately, similar results were obtained for both internal consistency and factor structure, with slight variations noted between sexes in the patterning of diagnostic efficiency indices. These psychometric findings, which were similar for men and women, support the construct validity of the DSM-IV criteria for AVPD and may also have implications for the treatment of this particular clinical population.

Factor Analysis via Components Analysis

ERIC Educational Resources Information Center

Bentler, Peter M.; de Leeuw, Jan

2011-01-01

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…

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

EPA Science Inventory

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

EVALUATION OF ACID DEPOSITION MODELS USING PRINCIPAL COMPONENT SPACES

EPA Science Inventory

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

Algorithm Classes for Architecture Research (ACAR)

DTIC Science & Technology

2010-03-01

Project Engineer BRADLEY J. PAUL , Chief Advanced Sensor Components Branch Advanced Sensor Components Branch Aerospace Components Division...establish the need for and the value of innovative research on domain-specific architectures, applications, and tools based on the challenges posed by...California / Information Sciences Institute (USC/ISI) conducted exploratory studies to establish the need for and the value of innovative research on domain

The UMO (University of Maine, Orono) Teacher Training Program: A Case Study and a Model.

ERIC Educational Resources Information Center

Miller, James R.; McNally, Harry

This case study presents a model of the University of Maine, Orono, pre-service program for preparing secondary social studies teachers. Focus is on the Foundations Component and the Methods Component, either of which can function independently of the other. Only brief mention is made of either the Exploratory Field Experience Component or 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.

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

PubMed

Nguyen, Phuong H

2006-12-01

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

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

PubMed

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

2016-04-19

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

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

NASA Astrophysics Data System (ADS)

Li, Jiangtong; Luo, Yongdao; Dai, Honglin

2018-01-01

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

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

PubMed

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

2017-06-01

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

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

PubMed

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

2013-06-01

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

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

PubMed

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

2015-02-01

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

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

PubMed

Putilov, Arcady A; Donskaya, Olga G

2016-01-01

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

Effects of natural enrichment materials on stress, memory and exploratory behavior in mice.

PubMed

Acklin, Casey J; Gault, Ruth A

2015-07-01

Environmental enrichment is an essential component of laboratory animal housing that allows animals to engage in natural behaviors in an otherwise artificial setting. Previous research by the authors suggested that, compared with synthetic enrichment materials, natural materials were associated with lower stress levels in mice. Here, the authors compare the effects of different enrichment materials on stress, memory and exploratory behavior in Swiss Webster mice. Mice that were provided with natural enrichment materials had lower stress levels, better memory and greater exploratory behavior than did mice provided with synthetic enrichment materials or with no enrichment materials. These findings suggest that provision of natural enrichment materials can improve well-being of laboratory mice.

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

NASA Astrophysics Data System (ADS)

Wojciechowski, Adam

2017-04-01

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

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

EPA Science Inventory

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

Rosacea assessment by erythema index and principal component analysis segmentation maps

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Multilevel sparse functional principal component analysis.

PubMed

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

2014-01-29

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

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

PubMed

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

2015-03-01

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

Visualizing Hyolaryngeal Mechanics in Swallowing Using Dynamic MRI

PubMed Central

Pearson, William G.; Zumwalt, Ann C.

2013-01-01

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

The Individual Regulation Component of Group Emotional Intelligence: Measure Development and Validation

ERIC Educational Resources Information Center

Peterson, Christina Hamme

2012-01-01

Counseling work is increasingly conducted in team format. The methods counseling teams use to manage the emotional component of their group life, or their group emotional intelligence, have been proposed as significantly contributing to group member trust, cooperation, and ultimate performance. Item development, exploratory factor analysis, and…

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

PubMed

Bagley, C

1980-03-01

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

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

ERIC Educational Resources Information Center

McCormick, Ernest J.; And Others

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

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

ERIC Educational Resources Information Center

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

2012-01-01

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

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

PubMed

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

2017-09-19

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

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

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

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

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Information extraction from multivariate images

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

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

PubMed

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

2016-10-01

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

Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

ERIC Educational Resources Information Center

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

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

Analysis of the principal component algorithm in phase-shifting interferometry.

PubMed

Vargas, J; Quiroga, J Antonio; Belenguer, T

2011-06-15

We recently presented a new asynchronous demodulation method for phase-sampling interferometry. The method is based in the principal component analysis (PCA) technique. In the former work, the PCA method was derived heuristically. In this work, we present an in-depth analysis of the PCA demodulation method.

Psychometric Measurement Models and Artificial Neural Networks

ERIC Educational Resources Information Center

Sese, Albert; Palmer, Alfonso L.; Montano, Juan J.

2004-01-01

The study of measurement models in psychometrics by means of dimensionality reduction techniques such as Principal Components Analysis (PCA) is a very common practice. In recent times, an upsurge of interest in the study of artificial neural networks apt to computing a principal component extraction has been observed. Despite this interest, the…

Burst and Principal Components Analyses of MEA Data for 16 Chemicals Describe at Least Three Effects Classes.

EPA Science Inventory

Microelectrode arrays (MEAs) detect drug and chemical induced changes in neuronal network function and have been used for neurotoxicity screening. As a proof-•of-concept, the current study assessed the utility of analytical "fingerprinting" using Principal Components Analysis (P...

Incremental principal component pursuit for video background modeling

DOEpatents

Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt

2017-03-14

An incremental Principal Component Pursuit (PCP) algorithm for video background modeling that is able to process one frame at a time while adapting to changes in background, with a computational complexity that allows for real-time processing, having a low memory footprint and is robust to translational and rotational jitter.

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.

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.

A Critical Analysis of Football Bowl Subdivision Coaching Contract Components

ERIC Educational Resources Information Center

Nichols, Justin Keith

2012-01-01

This exploratory study is designed to inventory and analyze contract components used by Football Bowl Subdivision (FBS) institutions in the National Collegiate Athletic Association (NCAA) to further contribute to the body research. The FBS is comprised of 120 institutions and 94 of those institutions submitted contracts to "USA Today"…

An Exploratory Qualitative Inquiry of Key Indicators on IT Disaster Recovery Planning

ERIC Educational Resources Information Center

Gardner, Brian

2016-01-01

Disaster recovery planning is a crucial component to maintaining a business's economic stability. However, it is unclear how key performance indicators (KPIs) are perceived in the emergency medical service (EMS) industry during the disaster recover planning process. The problem addressed in this study was to understand KPIs and their components.…

Rotation in the Dynamic Factor Modeling of Multivariate Stationary Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2001-01-01

Proposes a special rotation procedure for the exploratory dynamic factor model for stationary multivariate time series. The rotation procedure applies separately to each univariate component series of a q-variate latent factor series and transforms such a component, initially represented as white noise, into a univariate moving-average.…

Application of principal component analysis in protein unfolding: an all-atom molecular dynamics simulation study.

PubMed

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-28

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide-ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

Application of principal component analysis in protein unfolding: An all-atom molecular dynamics simulation study

NASA Astrophysics Data System (ADS)

Das, Atanu; Mukhopadhyay, Chaitali

2007-10-01

We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide—ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.

SAS program for quantitative stratigraphic correlation by principal components

USGS Publications Warehouse

Hohn, M.E.

1985-01-01

A SAS program is presented which constructs a composite section of stratigraphic events through principal components analysis. The variables in the analysis are stratigraphic sections and the observational units are range limits of taxa. The program standardizes data in each section, extracts eigenvectors, estimates missing range limits, and computes the composite section from scores of events on the first principal component. Provided is an option of several types of diagnostic plots; these help one to determine conservative range limits or unrealistic estimates of missing values. Inspection of the graphs and eigenvalues allow one to evaluate goodness of fit between the composite and measured data. The program is extended easily to the creation of a rank-order composite. ?? 1985.

Implementation of an integrating sphere for the enhancement of noninvasive glucose detection using quantum cascade laser spectroscopy

NASA Astrophysics Data System (ADS)

Werth, Alexandra; Liakat, Sabbir; Dong, Anqi; Woods, Callie M.; Gmachl, Claire F.

2018-05-01

An integrating sphere is used to enhance the collection of backscattered light in a noninvasive glucose sensor based on quantum cascade laser spectroscopy. The sphere enhances signal stability by roughly an order of magnitude, allowing us to use a thermoelectrically (TE) cooled detector while maintaining comparable glucose prediction accuracy levels. Using a smaller TE-cooled detector reduces form factor, creating a mobile sensor. Principal component analysis has predicted principal components of spectra taken from human subjects that closely match the absorption peaks of glucose. These principal components are used as regressors in a linear regression algorithm to make glucose concentration predictions, over 75% of which are clinically accurate.

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

PubMed

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

2017-01-01

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

Principals' Perceptions of Collegial Support as a Component of Administrative Inservice.

ERIC Educational Resources Information Center

Daresh, John C.

To address the problem of increasing professional isolation of building administrators, the Principals' Inservice Project helps establish principals' collegial support groups across the nation. The groups are typically composed of 6 to 10 principals who meet at least once each month over a 2-year period. One collegial support group of seven…

Training the Trainers: Learning to Be a Principal Supervisor

ERIC Educational Resources Information Center

Saltzman, Amy

2017-01-01

While most principal supervisors are former principals themselves, few come to the role with specific training in how to do the job effectively. For this reason, both the Washington, D.C., and Tulsa, Oklahoma, principal supervisor programs include a strong professional development component. In this article, the author takes a look inside these…

Use of Geochemistry Data Collected by the Mars Exploration Rover Spirit in Gusev Crater to Teach Geomorphic Zonation through Principal Components Analysis

ERIC Educational Resources Information Center

Rodrigue, Christine M.

2011-01-01

This paper presents a laboratory exercise used to teach principal components analysis (PCA) as a means of surface zonation. The lab was built around abundance data for 16 oxides and elements collected by the Mars Exploration Rover Spirit in Gusev Crater between Sol 14 and Sol 470. Students used PCA to reduce 15 of these into 3 components, which,…

Infrared imaging spectroscopy and chemometric tools for in situ analysis of an imiquimod pharmaceutical preparation presented as cream

NASA Astrophysics Data System (ADS)

Carneiro, Renato Lajarim; Poppi, Ronei Jesus

2014-01-01

In the present work the homogeneity of a pharmaceutical formulation presented as a cream was studied using infrared imaging spectroscopy and chemometric methodologies such as principal component analysis (PCA) and multivariate curve resolution with alternating least squares (MCR-ALS). A cream formulation, presented as an emulsion, was prepared using imiquimod as the active pharmaceutical ingredient (API) and the excipients: water, vaseline, an emulsifier and a carboxylic acid in order to dissolve the API. After exposure at 45 °C during 3 months to perform accelerated stability test, the presence of some crystals was observed, indicating homogeneity problems in the formulation. PCA exploratory analysis showed that the crystal composition was different from the composition of the emulsion, since the score maps presented crystal structures in the emulsion. MCR-ALS estimated the spectra of the crystals and the emulsion. The crystals presented amine and C-H bands, suggesting that the precipitate was a salt formed by carboxylic acid and imiquimod. These results indicate the potential of infrared imaging spectroscopy in conjunction with chemometric methodologies as an analytical tool to ensure the quality of cream formulations in the pharmaceutical industry.

Safety leadership in the teaching laboratories of electrical and electronic engineering departments at Taiwanese Universities.

PubMed

Wu, Tsung-Chih

2008-01-01

Safety has always been one of the principal goals in teaching laboratories. Laboratories cannot serve their educational purpose when accidents occur. The leadership of department heads has a major impact on laboratory safety, so this study discusses the factors affecting safety leadership in teaching laboratories. This study uses a mail survey to explore the perceived safety leadership in electrical and electronic engineering departments at Taiwanese universities. An exploratory factor analysis shows that there are three main components of safety leadership, as measured on a safety leadership scale: safety controlling, safety coaching, and safety caring. The descriptive statistics also reveals that among faculty, the perception of department heads' safety leadership is in general positive. A two-way MANOVA shows that there are interaction effects on safety leadership between university size and instructor age; there are also interaction effects between presence of a safety committee and faculty gender and faculty age. It is therefore necessary to assess organizational factors when determining whether individual factors are the cause of differing perceptions among faculty members. The author also presents advice on improving safety leadership for department heads at small universities and at universities without safety committees.

Factor structure of the Korean version of illness intrusiveness rating scale: cross-cultural implications.

PubMed

Kim, Daeho; Kim, Kwang-iel; Lee, Haewon; Choi, Joonho; Park, Yong-Chon

2005-04-01

The Illness Intrusiveness Rating Scale (IIRS) measures illness-induced disruptions to 13 domains of lifestyles, activities, and interests. A stable three-factor structure has been well documented; however, the cross-cultural validity of this scale needs to be tested. This study investigated the factor structure of the Korean version of IIRS in 712 outpatients at a university medical center. A predominant diagnosis of the patients was rheumatoid arthritis (47%). The Center for Epidemiological Studies-Depression Scale (CES-D), and Health Assessment Questionnaire (HAQ) were also administered. Exploratory Principal Component Analysis identified a two-factor structure, "Relationships and Personal Development (RPD)" and "Instrumental", accounting for 57% of the variance. Confirmatory analyses extracted an identical factor structure. However, a goodness-of-the fit test failed to support two-factor solution (chi(2)=138.2, df=43, p<.001). Two factors had high internal consistency (RPD, alpha=.89; Instrumental, alpha=.75) and significantly correlated with scores of HAQ (RPD, r=.53, p<.001; Instrumental, .r=44, p<.001) and CES-D (RPD, .r=55, p<.001; Instrumental, .r=43, p<.001). These findings supported construct validity of the Korean version of IIRS, but did not support cross-cultural equivalence of the factor structure.

Determinants of personal protective equipment (PPE) use in UK motorcyclists: exploratory research applying an extended theory of planned behaviour.

PubMed

Norris, Emma; Myers, Lynn

2013-11-01

Despite evident protective value of motorcycle personal protective equipment (PPE), no research has assessed considerations behind its uptake in UK riders. A cross-sectional online questionnaire design was employed, with riders (n=268) recruited from online motorcycle forums. Principal component analysis found four PPE behavioural outcomes. Theoretical factors of intentions, attitudes, injunctive and descriptive subjective norms, risk perceptions, anticipated regret, benefits and habit were also identified for further analysis. High motorcycle jacket, trousers and boots wear, middling high-visibility wear and low non-Personal Protective Equipment wear were found. Greater intentions, anticipated regret and perceived benefits were significantly associated with increased motorcycle jacket, trousers and boots wear, with habit presence and scooter use significantly associated with increased high-visibility wear. Lower intentions, anticipated regret and risk perceptions, being female, not holding a car licence and urban riding were significantly associated with increased non-PPE wear. A need for freedom of choice and mixed attitudes towards PPE use were evident in additional comments. PPE determinants in this sample provide a preliminary basis for future uptake interventions. Larger scale and qualitative research is needed to further investigate relevant constructs. Copyright © 2013 Elsevier Ltd. All rights reserved.

Determinants of job stress in chemical process industry: A factor analysis approach.

PubMed

Menon, Balagopal G; Praveensal, C J; Madhu, G

2015-01-01

Job stress is one of the active research domains in industrial safety research. The job stress can result in accidents and health related issues in workers in chemical process industries. Hence it is important to measure the level of job stress in workers so as to mitigate the same to avoid the worker's safety related problems in the industries. The objective of this study is to determine the job stress factors in the chemical process industry in Kerala state, India. This study also aims to propose a comprehensive model and an instrument framework for measuring job stress levels in the chemical process industries in Kerala, India. The data is collected through a questionnaire survey conducted in chemical process industries in Kerala. The collected data out of 1197 surveys is subjected to principal component and confirmatory factor analysis to develop the job stress factor structure. The factor analysis revealed 8 factors that influence the job stress in process industries. It is also found that the job stress in employees is most influenced by role ambiguity and the least by work environment. The study has developed an instrument framework towards measuring job stress utilizing exploratory factor analysis and structural equation modeling.

Eating Disorder Quality of Life Scale (EDQLS) in ethnically diverse college women: an exploratory factor analysis.

PubMed

Akoury, Liya M; Rozalski, Vincent; Barchard, Kimberly A; Warren, Cortney S

2018-03-01

Extant research suggests that disordered eating is common in college women and is associated with decreased quality of life. The Eating Disorder Quality of Life Scale (EDQLS) examines impairment to disordered eating-related quality of life, but has not been validated in college women. Accordingly, the purpose of this study was to examine the reliability, validity, and factor structure of the EDQLS in a diverse sample of 971 college women. Students from a large United States university completed questionnaires examining disordered eating and the EDQLS online. The EDQLS demonstrated excellent internal consistency and good convergent validity with the Eating Disorder Examination Questionnaire (EDEQ). Contrary to the original 12-domain design of the EDQLS, principal component analyses suggested five factors that mapped onto the following constructs: (1) Positive Emotionality; (2) Body/Weight Dissatisfaction; (3) Disordered Eating Behaviors; (4) Negative Emotionality; and (5) Social Engagement. However, 15 of the 40 items loaded onto multiple factors. Total scores on the EDQLS are reliable and valid when used with diverse samples of college women, but some revisions are needed to create subscales than can justifiably be used in clinical practice.

Classification and quantitation of milk powder by near-infrared spectroscopy and mutual information-based variable selection and partial least squares

NASA Astrophysics Data System (ADS)

Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

2018-01-01

Milk is among the most popular nutrient source worldwide, which is of great interest due to its beneficial medicinal properties. The feasibility of the classification of milk powder samples with respect to their brands and the determination of protein concentration is investigated by NIR spectroscopy along with chemometrics. Two datasets were prepared for experiment. One contains 179 samples of four brands for classification and the other contains 30 samples for quantitative analysis. Principal component analysis (PCA) was used for exploratory analysis. Based on an effective model-independent variable selection method, i.e., minimal-redundancy maximal-relevance (MRMR), only 18 variables were selected to construct a partial least-square discriminant analysis (PLS-DA) model. On the test set, the PLS-DA model based on the selected variable set was compared with the full-spectrum PLS-DA model, both of which achieved 100% accuracy. In quantitative analysis, the partial least-square regression (PLSR) model constructed by the selected subset of 260 variables outperforms significantly the full-spectrum model. It seems that the combination of NIR spectroscopy, MRMR and PLS-DA or PLSR is a powerful tool for classifying different brands of milk and determining the protein content.

Development of the Sri Lankan Early Teenagers' Violence Inventory: An Instrument to Measure Peer Violence in Schools

PubMed Central

Seneviratne, Rohini; Østbye, Truls; Lynch, Catherine; Sandøy, Ingvild Fossgard

2014-01-01

This study was designed to develop an inventory to measure peer violence among early teens (13–15 years of age) in schools in Sri Lanka. Development of SLETVI was carried out in two phases. In phase I, development of an operational definition for peer violence, identification, and finalizing violent acts for inventory was done by a combination of qualitative methods: a comprehensive literature review, focus group discussions among 13–15-year-old adolescents, their teachers and parents, and consultative meetings with experts in the field. Inventory was then pretested. In phase II, elaboration of SLETVI was carried out by administering it to a sample of 1700 adolescents (13–15 years old). Exploratory factor analysis using principal component analysis was performed separately for experiences of victimization and perpetration. Test-retest reliability of SLETVI was assessed. SLETVI included 37 items in three factors: “less severe violence,” “severe physical,” and “severe relational” violence. Combined use of qualitative and quantitative methods enabled development of a culturally valid and reliable operational inventory to assess early teenagers' peer violence in Sri Lankan and other South Asian schools. PMID:25061607

Development and validation of sustainability criteria of administrative green schools in Iran.

PubMed

Meiboudi, Hossein; Lahijanian, Akramolmolok; Shobeiri, Seyed Mohammad; Jozi, Seyed Ali; Azizinezhad, Reza

2017-07-15

Environmental responsibility in school has led to the emergence of a variety of criteria to administer green schools' contributions to sustainability. Sustainability criteria of administrative green schools need validity, reliability and norms. The aim of the current study was to develop and validate assessment criteria for green schools in Iran based on the role of academia. A national survey was conducted to obtain data on sustainability criteria initiatives for green schools and the Iranian profile was defined. An initial pool of 71 items was generated and after its first edition, 63 items were selected to comprise the sustainability criteria. Engineering-architectural and behavioral aspects of this sustainability criteria were evaluated through a sample of 1218 graduate students with environmental degrees from Iran's universities. Exploratory factor analysis using principal components and promax rotation method showed that these 9 criteria have simple structures and are consistent with the theoretical framework. The reliability coefficients of subscales ranged between 0.62 (participation) and 0.84 (building location and position). The study's survey of correlation coefficients between items and subscales illustrated that those coefficients varied between 0.24 and 0.68. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development and validation of the pro-environmental behaviour scale for women's health.

PubMed

Kim, HyunKyoung

2017-05-01

This study was aimed to develop and test the Pro-environmental Behavior Scale for Women's Health. Women adopt sustainable behaviours and alter their life styles to protect the environment and their health from environmental pollution. The conceptual framework of pro-environmental behaviours was based on Rogers' protection motivation theory and Weinstein's precaution adoption process model. The cross-sectional design was used for instrument development. The instrument development process consisted of a literature review, personal depth interviews and focus group interviews. The sample comprised 356 adult women recruited in April-May 2012 in South Korea using quota sampling. For construct validity, exploratory factor analysis was conducted to examine the factor structure, after which convergent and discriminant validity and known-group comparisons were tested. Principal component analysis yielded 17 items with four factors, including 'women's health protection,' 'chemical exposure prevention,' 'alternative consumption,' and 'community-oriented behaviour'. The Cronbach's α was 0·81. Convergent and discriminant validity were supported by performing correlations with other environmental-health and health-behaviour measures. Nursing professionals can reliably use the instrument to assess women's behaviours, which protect their health and the environment. © 2016 John Wiley & Sons Ltd.

Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms

NASA Astrophysics Data System (ADS)

Li, Shaoxin; Li, Linfang; Zeng, Qiuyao; Zhang, Yanjiao; Guo, Zhouyi; Liu, Zhiming; Jin, Mei; Su, Chengkang; Lin, Lin; Xu, Junfa; Liu, Songhao

2015-05-01

This study aims to characterize and classify serum surface-enhanced Raman spectroscopy (SERS) spectra between bladder cancer patients and normal volunteers by genetic algorithms (GAs) combined with linear discriminate analysis (LDA). Two group serum SERS spectra excited with nanoparticles are collected from healthy volunteers (n = 36) and bladder cancer patients (n = 55). Six diagnostic Raman bands in the regions of 481-486, 682-687, 1018-1034, 1313-1323, 1450-1459 and 1582-1587 cm-1 related to proteins, nucleic acids and lipids are picked out with the GAs and LDA. By the diagnostic models built with the identified six Raman bands, the improved diagnostic sensitivity of 90.9% and specificity of 100% were acquired for classifying bladder cancer patients from normal serum SERS spectra. The results are superior to the sensitivity of 74.6% and specificity of 97.2% obtained with principal component analysis by the same serum SERS spectra dataset. Receiver operating characteristic (ROC) curves further confirmed the efficiency of diagnostic algorithm based on GA-LDA technique. This exploratory work demonstrates that the serum SERS associated with GA-LDA technique has enormous potential to characterize and non-invasively detect bladder cancer through peripheral blood.

Understanding Skill in EVA Mass Handling. Volume 1; Theoretical and Operational Foundations

NASA Technical Reports Server (NTRS)

Riccio, Gary; McDonald, Vernon; Peters, Brian; Layne, Charles; Bloomberg, Jacob

1997-01-01

This report describes the theoretical and operational foundations for our analysis of skill in extravehicular mass handling. A review of our research on postural control, human-environment interactions, and exploratory behavior in skill acquisition is used to motivate our analysis. This scientific material is presented within the context of operationally valid issues concerning extravehicular mass handling. We describe the development of meaningful empirical measures that are relevant to a special class of nested control systems: manual interactions between an individual and the substantial environment. These measures are incorporated into a unique empirical protocol implemented on NASA's principal mass handling simulator, the precision air-bearing floor, in order to evaluate skill in extravehicular mass handling. We discuss the components of such skill with reference to the relationship between postural configuration and controllability of an orbital replacement unit, the relationship between orbital replacement unit control and postural stability, the relationship between antecedent and consequent movements of an orbital replacement unit, and the relationship between antecedent and consequent postural movements. Finally, we describe our expectations regarding the operational relevance of the empirical results as it pertains to extravehicular activity tools, training, monitoring, and planning.

Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, paranoid personality disorder diagnosis: a unitary or a two-dimensional construct?

PubMed

Falkum, Erik; Pedersen, Geir; Karterud, Sigmund

2009-01-01

This article examines reliability and validity aspects of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) paranoid personality disorder (PPD) diagnosis. Patients with personality disorders (n = 930) from the Norwegian network of psychotherapeutic day hospitals, of which 114 had PPD, were included in the study. Frequency distribution, chi(2), correlations, reliability statistics, exploratory, and confirmatory factor analyses were performed. The distribution of PPD criteria revealed no distinct boundary between patients with and without PPD. Diagnostic category membership was obtained in 37 of 64 theoretically possible ways. The PPD criteria formed a separate factor in a principal component analysis, whereas a confirmatory factor analysis indicated that the DSM-IV PPD construct consists of 2 separate dimensions as follows: suspiciousness and hostility. The reliability of the unitary PPD scale was only 0.70, probably partly due to the apparent 2-dimensionality of the construct. Persistent unwarranted doubts about the loyalty of friends had the highest diagnostic efficiency, whereas unwarranted accusations of infidelity of partner had particularly poor indicator properties. The reliability and validity of the unitary PPD construct may be questioned. The 2-dimensional PPD model should be further explored.

Development of a new multidimensional individual and interpersonal resilience measure for older adults.

PubMed

Martin, A'verria Sirkin; Distelberg, Brian; Palmer, Barton W; Jeste, Dilip V

2015-01-01

Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Cross-sectional, self-report data from 1006 older adults were analyzed in two steps. The total sample was split into two subsamples and the first step identified the underlying latent structure through principal component exploratory factor analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through confirmatory factor analysis (CFA). EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the multidimensional individual and interpersonal resilience measure, a broad assessment of resilience for older adults. This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature.

Development of a New Multidimensional Individual and Interpersonal Resilience Measure for Older Adults

PubMed Central

Martin, A’verria Sirkin; Distelberg, Brian; Palmer, Barton W.; Jeste, Dilip V.

2015-01-01

Objectives Develop an empirically grounded measure that can be used to assess family and individual resilience in a population of older adults (aged 50-99). Methods Cross-sectional, self-report data from 1,006 older adults were analyzed in two steps. The total sample was split into two sub-samples and the first step identified the underlying latent structure through principal component Exploratory Factor Analysis (EFA). The second step utilized the second half of the sample to validate the derived latent structure through Confirmatory Factor Analysis (CFA). Results EFA produced an eight-factor structure that appeared clinically relevant for measuring the multidimensional nature of resilience. Factors included self-efficacy, access to social support network, optimism, perceived economic and social resources, spirituality and religiosity, relational accord, emotional expression and communication, and emotional regulation. CFA confirmed the eight-factor structure previously achieved with covariance between each of the factors. Based on these analyses we developed the Multidimensional Individual and Interpersonal Resilience Measure (MIIRM), a broad assessment of resilience for older adults. Conclusion This study highlights the multidimensional nature of resilience and introduces an individual and interpersonal resilience measure developed for older adults which is grounded in the individual and family resilience literature. PMID:24787701

Instrument to measure psychological contract violation in pharmacy students.

PubMed

Spies, Alan R; Wilkin, Noel E; Bentley, John P; Bouldin, Alicia S; Wilson, Marvin C; Holmes, Erin R

2010-08-10

To adapt and evaluate an instrument that measures perceived psychological contract violations in pharmacy students by schools and colleges of pharmacy. A psychological contract violations measure was developed from existing literature and the 1997 ACPE Guidelines and pilot-tested with second-year pharmacy students at 2 schools of pharmacy. A revised measure then was administered to second-year pharmacy students at 6 schools of pharmacy. Using a 5-point Likert-type scale, participants were asked to indicate the level of obligations they received compared to what was promised by the school of pharmacy. Exploratory factor analysis on the psychological contract violations measure was conducted using principal components analysis resulting in 7 factors, which led to a revised measure with 26 items. Using a sample of 339 students, the proposed 7-factor measurement model was tested using confirmatory factor analysis. In general, the results supported the hypothesized model. The final 23-item scale demonstrated both reliability and validity. Some students perceived certain aspects of the psychological contract that exists with their school of pharmacy were being violated. The psychological contract violations measure may serve as a valuable tool in helping to identify areas where their students believe that schools/colleges of pharmacy have not fulfilled promised obligations.

Alcohol Consumption Decisions among Nonabusing Drinkers Diagnosed with Hepatitis C: An Exploratory Sequential Mixed Methods Study

PubMed Central

Stoller, Eleanor Palo; Webster, Noah J.; Blixen, Carol E.; McCormick, Richard A.; Hund, Andrew J.; Perzynski, Adam T.; Kanuch, Stephanie W.; Thomas, Charles L.; Kercher, Kyle; Dawson, Neal V.

2009-01-01

Most studies of decisions to curtail alcohol consumption reflect experiences of abusing drinkers. We employ an exploratory sequential research design to explore the applicability of this research to the experience of nonabusing drinkers advised to curtail alcohol consumption after a Hepatitis C diagnosis. A qualitative component identified 17 new decision factors not reflected in an inventory of factors based on synthesis of existing scales. We triangulated qualitative data by supplementing semi-structured interviews with Internet postings. A quantitative component estimated prevalence and association with current drinking of these new decision factors. Patients who quit drinking tended to attribute post-diagnosis drinking to occasional triggers, whereas patients who were still drinking were more likely to endorse rationales not tied to specific triggers. PMID:20046861

A Principal Components Analysis and Validation of the Coping with the College Environment Scale (CWCES)

ERIC Educational Resources Information Center

Ackermann, Margot Elise; Morrow, Jennifer Ann

2008-01-01

The present study describes the development and initial validation of the Coping with the College Environment Scale (CWCES). Participants included 433 college students who took an online survey. Principal Components Analysis (PCA) revealed six coping strategies: planning and self-management, seeking support from institutional resources, escaping…

Wavelet based de-noising of breath air absorption spectra profiles for improved classification by principal component analysis

NASA Astrophysics Data System (ADS)

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

2015-11-01

The comparison results of different mother wavelets used for de-noising of model and experimental data which were presented by profiles of absorption spectra of exhaled air are presented. The impact of wavelets de-noising on classification quality made by principal component analysis are also discussed.

Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

NASA Astrophysics Data System (ADS)

Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

2013-06-01

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

Stability of Nonlinear Principal Components Analysis: An Empirical Study Using the Balanced Bootstrap

ERIC Educational Resources Information Center

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

2007-01-01

Principal components analysis (PCA) is used to explore the structure of data sets containing linearly related numeric variables. Alternatively, nonlinear PCA can handle possibly nonlinearly related numeric as well as nonnumeric variables. For linear PCA, the stability of its solution can be established under the assumption of multivariate…

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

Code of Federal Regulations, 2012 CFR

2012-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

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

Code of Federal Regulations, 2014 CFR

2014-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

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

Code of Federal Regulations, 2011 CFR

2011-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

40 CFR 60.1580 - What are the principal components of the model rule?

Code of Federal Regulations, 2010 CFR

2010-07-01

... the model rule? 60.1580 Section 60.1580 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines..., 1999 Use of Model Rule § 60.1580 What are the principal components of the model rule? The model rule...

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

Code of Federal Regulations, 2013 CFR

2013-07-01

... the model rule? 60.2998 Section 60.2998 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) STANDARDS OF PERFORMANCE FOR NEW STATIONARY SOURCES Emission Guidelines... December 9, 2004 Model Rule-Use of Model Rule § 60.2998 What are the principal components of the model rule...

Students' Perceptions of Teaching and Learning Practices: A Principal Component Approach

ERIC Educational Resources Information Center

Mukorera, Sophia; Nyatanga, Phocenah

2017-01-01

Students' attendance and engagement with teaching and learning practices is perceived as a critical element for academic performance. Even with stipulated attendance policies, students still choose not to engage. The study employed a principal component analysis to analyze first- and second-year students' perceptions of the importance of the 12…

Principal Perspectives about Policy Components and Practices for Reducing Cyberbullying in Urban Schools

ERIC Educational Resources Information Center

Hunley-Jenkins, Keisha Janine

2012-01-01

This qualitative study explores large, urban, mid-western principal perspectives about cyberbullying and the policy components and practices that they have found effective and ineffective at reducing its occurrence and/or negative effect on their schools' learning environments. More specifically, the researcher was interested in learning more…

Principal Component Analysis: Resources for an Essential Application of Linear Algebra

ERIC Educational Resources Information Center

Pankavich, Stephen; Swanson, Rebecca

2015-01-01

Principal Component Analysis (PCA) is a highly useful topic within an introductory Linear Algebra course, especially since it can be used to incorporate a number of applied projects. This method represents an essential application and extension of the Spectral Theorem and is commonly used within a variety of fields, including statistics,…

Learning Principal Component Analysis by Using Data from Air Quality Networks

ERIC Educational Resources Information Center

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

2017-01-01

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

Applications of Nonlinear Principal Components Analysis to Behavioral Data.

ERIC Educational Resources Information Center

Hicks, Marilyn Maginley

1981-01-01

An empirical investigation of the statistical procedure entitled nonlinear principal components analysis was conducted on a known equation and on measurement data in order to demonstrate the procedure and examine its potential usefulness. This method was suggested by R. Gnanadesikan and based on an early paper of Karl Pearson. (Author/AL)

Relationships between Association of Research Libraries (ARL) Statistics and Bibliometric Indicators: A Principal Components Analysis

ERIC Educational Resources Information Center

Hendrix, Dean

2010-01-01

This study analyzed 2005-2006 Web of Science bibliometric data from institutions belonging to the Association of Research Libraries (ARL) and corresponding ARL statistics to find any associations between indicators from the two data sets. Principal components analysis on 36 variables from 103 universities revealed obvious associations between…

Principal component analysis for protein folding dynamics.

PubMed

Maisuradze, Gia G; Liwo, Adam; Scheraga, Harold A

2009-01-09

Protein folding is considered here by studying the dynamics of the folding of the triple beta-strand WW domain from the Formin-binding protein 28. Starting from the unfolded state and ending either in the native or nonnative conformational states, trajectories are generated with the coarse-grained united residue (UNRES) force field. The effectiveness of principal components analysis (PCA), an already established mathematical technique for finding global, correlated motions in atomic simulations of proteins, is evaluated here for coarse-grained trajectories. The problems related to PCA and their solutions are discussed. The folding and nonfolding of proteins are examined with free-energy landscapes. Detailed analyses of many folding and nonfolding trajectories at different temperatures show that PCA is very efficient for characterizing the general folding and nonfolding features of proteins. It is shown that the first principal component captures and describes in detail the dynamics of a system. Anomalous diffusion in the folding/nonfolding dynamics is examined by the mean-square displacement (MSD) and the fractional diffusion and fractional kinetic equations. The collisionless (or ballistic) behavior of a polypeptide undergoing Brownian motion along the first few principal components is accounted for.

Principal Component 2-D Long Short-Term Memory for Font Recognition on Single Chinese Characters.

PubMed

Tao, Dapeng; Lin, Xu; Jin, Lianwen; Li, Xuelong

2016-03-01

Chinese character font recognition (CCFR) has received increasing attention as the intelligent applications based on optical character recognition becomes popular. However, traditional CCFR systems do not handle noisy data effectively. By analyzing in detail the basic strokes of Chinese characters, we propose that font recognition on a single Chinese character is a sequence classification problem, which can be effectively solved by recurrent neural networks. For robust CCFR, we integrate a principal component convolution layer with the 2-D long short-term memory (2DLSTM) and develop principal component 2DLSTM (PC-2DLSTM) algorithm. PC-2DLSTM considers two aspects: 1) the principal component layer convolution operation helps remove the noise and get a rational and complete font information and 2) simultaneously, 2DLSTM deals with the long-range contextual processing along scan directions that can contribute to capture the contrast between character trajectory and background. Experiments using the frequently used CCFR dataset suggest the effectiveness of PC-2DLSTM compared with other state-of-the-art font recognition methods.

Dynamic of consumer groups and response of commodity markets by principal component analysis

NASA Astrophysics Data System (ADS)

Nobi, Ashadun; Alam, Shafiqul; Lee, Jae Woo

2017-09-01

This study investigates financial states and group dynamics by applying principal component analysis to the cross-correlation coefficients of the daily returns of commodity futures. The eigenvalues of the cross-correlation matrix in the 6-month timeframe displays similar values during 2010-2011, but decline following 2012. A sharp drop in eigenvalue implies the significant change of the market state. Three commodity sectors, energy, metals and agriculture, are projected into two dimensional spaces consisting of two principal components (PC). We observe that they form three distinct clusters in relation to various sectors. However, commodities with distinct features have intermingled with one another and scattered during severe crises, such as the European sovereign debt crises. We observe the notable change of the position of two dimensional spaces of groups during financial crises. By considering the first principal component (PC1) within the 6-month moving timeframe, we observe that commodities of the same group change states in a similar pattern, and the change of states of one group can be used as a warning for other group.

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

PubMed

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

2017-06-01

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

[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.

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

Hyperspectral optical imaging of human iris in vivo: characteristics of reflectance spectra

NASA Astrophysics Data System (ADS)

Medina, José M.; Pereira, Luís M.; Correia, Hélder T.; Nascimento, Sérgio M. C.

2011-07-01

We report a hyperspectral imaging system to measure the reflectance spectra of real human irises with high spatial resolution. A set of ocular prosthesis was used as the control condition. Reflectance data were decorrelated by the principal-component analysis. The main conclusion is that spectral complexity of the human iris is considerable: between 9 and 11 principal components are necessary to account for 99% of the cumulative variance in human irises. Correcting image misalignments associated with spontaneous ocular movements did not influence this result. The data also suggests a correlation between the first principal component and different levels of melanin present in the irises. It was also found that although the spectral characteristics of the first five principal components were not affected by the radial and angular position of the selected iridal areas, they affect the higher-order ones, suggesting a possible influence of the iris texture. The results show that hyperspectral imaging in the iris, together with adequate spectroscopic analyses provide more information than conventional colorimetric methods, making hyperspectral imaging suitable for the characterization of melanin and the noninvasive diagnosis of ocular diseases and iris color.

Seeing wholes: The concept of systems thinking and its implementation in school leadership

NASA Astrophysics Data System (ADS)

Shaked, Haim; Schechter, Chen

2013-12-01

Systems thinking (ST) is an approach advocating thinking about any given issue as a whole, emphasising the interrelationships between its components rather than the components themselves. This article aims to link ST and school leadership, claiming that ST may enable school principals to develop highly performing schools that can cope successfully with current challenges, which are more complex than ever before in today's era of accountability and high expectations. The article presents the concept of ST - its definition, components, history and applications. Thereafter, its connection to education and its contribution to school management are described. The article concludes by discussing practical processes including screening for ST-skilled principal candidates and developing ST skills among prospective and currently performing school principals, pinpointing three opportunities for skills acquisition: during preparatory programmes; during their first years on the job, supported by veteran school principals as mentors; and throughout their entire career. Such opportunities may not only provide school principals with ST skills but also improve their functioning throughout the aforementioned stages of professional development.

A modified procedure for mixture-model clustering of regional geochemical data

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David B.; Horton, John D.

2014-01-01

A modified procedure is proposed for mixture-model clustering of regional-scale geochemical data. The key modification is the robust principal component transformation of the isometric log-ratio transforms of the element concentrations. This principal component transformation and the associated dimension reduction are applied before the data are clustered. The principal advantage of this modification is that it significantly improves the stability of the clustering. The principal disadvantage is that it requires subjective selection of the number of clusters and the number of principal components. To evaluate the efficacy of this modified procedure, it is applied to soil geochemical data that comprise 959 samples from the state of Colorado (USA) for which the concentrations of 44 elements are measured. The distributions of element concentrations that are derived from the mixture model and from the field samples are similar, indicating that the mixture model is a suitable representation of the transformed geochemical data. Each cluster and the associated distributions of the element concentrations are related to specific geologic and anthropogenic features. In this way, mixture model clustering facilitates interpretation of the regional geochemical data.

Temporal evolution of financial-market correlations.

PubMed

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

2011-08-01

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

Temporal evolution of financial-market correlations

NASA Astrophysics Data System (ADS)

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

2011-08-01

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

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

NASA Astrophysics Data System (ADS)

Russo, A.; Trigo, R. M.

2003-04-01

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

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

PubMed

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

2017-03-01

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

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Chemical Structure and Molecular Dimension As Controls on the Inherent Stability of Charcoal in Boreal Forest Soil

NASA Astrophysics Data System (ADS)

Hockaday, W. C.; Kane, E. S.; Ohlson, M.; Huang, R.; Von Bargen, J.; Davis, R.

2014-12-01

Efforts have been made by various scientific disciplines to study hyporheic zones and characterize their associated processes. One way to approach the study of the hyporheic zone is to define facies, which are elements of a (hydrobio) geologic classification scheme that groups components of a complex system with high variability into a manageable set of discrete classes. In this study, we try to classify the hyporheic zone based on the geology, geochemistry, microbiology, and understand their interactive influences on the integrated biogeochemical distributions and processes. A number of measurements have been taken for 21 freeze core samples along the Columbia River bank in the Hanford 300 Area, and unique datasets have been obtained on biomass, pH, number of microbial taxa, percentage of N/C/H/S, microbial activity parameters, as well as microbial community attributes/modules. In order to gain a complete understanding of the geological control on these variables and processes, the explanatory variables are set to include quantitative gravel/sand/mud/silt/clay percentages, statistical moments of grain size distributions, as well as geological (e.g., Folk-Wentworth) and statistical (e.g., hierarchical) clusters. The dominant factors for major microbial and geochemical variables are identified and summarized using exploratory data analysis approaches (e.g., principal component analysis, hierarchical clustering, factor analysis, multivariate analysis of variance). The feasibility of extending the facies definition and its control of microbial and geochemical properties to larger scales is discussed.

Microbial facies distribution and its geological and geochemical controls at the Hanford 300 area

NASA Astrophysics Data System (ADS)

Hou, Z.; Nelson, W.; Stegen, J.; Murray, C. J.; Arntzen, E.

2015-12-01

Efforts have been made by various scientific disciplines to study hyporheic zones and characterize their associated processes. One way to approach the study of the hyporheic zone is to define facies, which are elements of a (hydrobio) geologic classification scheme that groups components of a complex system with high variability into a manageable set of discrete classes. In this study, we try to classify the hyporheic zone based on the geology, geochemistry, microbiology, and understand their interactive influences on the integrated biogeochemical distributions and processes. A number of measurements have been taken for 21 freeze core samples along the Columbia River bank in the Hanford 300 Area, and unique datasets have been obtained on biomass, pH, number of microbial taxa, percentage of N/C/H/S, microbial activity parameters, as well as microbial community attributes/modules. In order to gain a complete understanding of the geological control on these variables and processes, the explanatory variables are set to include quantitative gravel/sand/mud/silt/clay percentages, statistical moments of grain size distributions, as well as geological (e.g., Folk-Wentworth) and statistical (e.g., hierarchical) clusters. The dominant factors for major microbial and geochemical variables are identified and summarized using exploratory data analysis approaches (e.g., principal component analysis, hierarchical clustering, factor analysis, multivariate analysis of variance). The feasibility of extending the facies definition and its control of microbial and geochemical properties to larger scales is discussed.

Spanish validation of Bad Sobernheim Stress Questionnaire (BSSQ (brace).es) for adolescents with braces

PubMed Central

2010-01-01

Background As a result of scientific and medical professionals gaining interest in Stress and Health Related Quality of Life (HRQL), the aim of our research is, thus, to validate into Spanish the German questionnaire Bad Sobernheim Stress Questionnaire (BSSQ) (mit Korsett), for adolescents wearing braces. Methods The methodology used adheres to literature on trans-cultural adaptation by doing a translation and a back translation; it involved 35 adolescents, ages ranging between 10 and 16, with Adolescent Idiopathic Scoliosis (AIS) and wearing the same kind of brace (Rigo System Chêneau Brace). The materials used were a socio-demographics data questionnaire, the SRS-22 and the Spanish version of BSSQ(brace).es. The statistical analysis calculated the reliability (test-retest reliability and internal consistency) and the validity (convergent and construct validity) of the BSSQ (brace).es. Results BSSQ(brace).es is reliable because of its satisfactory internal consistency (Cronbach's alpha coefficient was 0.809, p < 0.001) and temporal stability (test-retest method with a Pearson correlation coefficient of 0.902 (p < 0.01)). It demonstrated convergent validity with SRS-22 since the Pearson correlation coefficient was 0.656 (p < 0.01). By undertaking an Exploratory Principal Components Analysis, a latent structure was found based on two Components which explicate the variance at 60.8%. Conclusions BSSQ (brace).es is reliable and valid and can be used with Spanish adolescents to assess the stress level caused by the brace. PMID:20633253

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

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.

Principal component reconstruction (PCR) for cine CBCT with motion learning from 2D fluoroscopy.

PubMed

Gao, Hao; Zhang, Yawei; Ren, Lei; Yin, Fang-Fang

2018-01-01

This work aims to generate cine CT images (i.e., 4D images with high-temporal resolution) based on a novel principal component reconstruction (PCR) technique with motion learning from 2D fluoroscopic training images. In the proposed PCR method, the matrix factorization is utilized as an explicit low-rank regularization of 4D images that are represented as a product of spatial principal components and temporal motion coefficients. The key hypothesis of PCR is that temporal coefficients from 4D images can be reasonably approximated by temporal coefficients learned from 2D fluoroscopic training projections. For this purpose, we can acquire fluoroscopic training projections for a few breathing periods at fixed gantry angles that are free from geometric distortion due to gantry rotation, that is, fluoroscopy-based motion learning. Such training projections can provide an effective characterization of the breathing motion. The temporal coefficients can be extracted from these training projections and used as priors for PCR, even though principal components from training projections are certainly not the same for these 4D images to be reconstructed. For this purpose, training data are synchronized with reconstruction data using identical real-time breathing position intervals for projection binning. In terms of image reconstruction, with a priori temporal coefficients, the data fidelity for PCR changes from nonlinear to linear, and consequently, the PCR method is robust and can be solved efficiently. PCR is formulated as a convex optimization problem with the sum of linear data fidelity with respect to spatial principal components and spatiotemporal total variation regularization imposed on 4D image phases. The solution algorithm of PCR is developed based on alternating direction method of multipliers. The implementation is fully parallelized on GPU with NVIDIA CUDA toolbox and each reconstruction takes about a few minutes. The proposed PCR method is validated and compared with a state-of-art method, that is, PICCS, using both simulation and experimental data with the on-board cone-beam CT setting. The results demonstrated the feasibility of PCR for cine CBCT and significantly improved reconstruction quality of PCR from PICCS for cine CBCT. With a priori estimated temporal motion coefficients using fluoroscopic training projections, the PCR method can accurately reconstruct spatial principal components, and then generate cine CT images as a product of temporal motion coefficients and spatial principal components. © 2017 American Association of Physicists in Medicine.

Cultivating an Environment that Contributes to Teaching and Learning in Schools: High School Principals' Actions

ERIC Educational Resources Information Center

Lin, Mind-Dih

2012-01-01

Improving principal leadership is a vital component to the success of educational reform initiatives that seek to improve whole-school performance, as principal leadership often exercises positive but indirect effects on student learning. Because of the importance of principals within the field of school improvement, this article focuses on…

Measuring Principals' Effectiveness: Results from New Jersey's First Year of Statewide Principal Evaluation. REL 2016-156

ERIC Educational Resources Information Center

Herrmann, Mariesa; Ross, Christine

2016-01-01

States and districts across the country are implementing new principal evaluation systems that include measures of the quality of principals' school leadership practices and measures of student achievement growth. Because these evaluation systems will be used for high-stakes decisions, it is important that the component measures of the evaluation…

The Views of Novice and Late Career Principals Concerning Instructional and Organizational Leadership within Their Evaluation

ERIC Educational Resources Information Center

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

2015-01-01

This study examined the perspectives of novice and late career principals concerning instructional and organizational leadership within their performance evaluations. An online survey was sent to 251 principals with a return rate of 49%. Instructional leadership components of the evaluation that were most important to all principals were:…

Delineating Components of Emotion and Its Dysregulation in Anxiety and Mood Psychopathology

ERIC Educational Resources Information Center

Mennin, Douglas S.; Holaway, Robert M.; Fresco, David M.; Moore, Michael T.; Heimberg, Richard G.

2007-01-01

Two studies sought to elucidate the components of emotion and its dysregulation and examine their role in both the overlap and distinctness of the symptoms of 3 highly comorbid anxiety and mood disorders (i.e., generalized anxiety disorder, major depression, and social anxiety disorder). In Study 1, exploratory factor analyses demonstrated that 4…

Evaluating fire-damaged components of historic covered bridges

Treesearch

Brian Kukay; Charles Todd; Tyler Jahn; Jenson Sannon; Logan Dunlap; Robert White; Mark Dietenberger

2016-01-01

Arson continues to claim many historic covered bridges. Site-specific, post-fire evaluations of the structural integrity of a bridge are often necessary in a fire’s aftermath. Decisions on whether individual wood components can be rehabilitated, reconstructed, or replaced must be made. This report includes coverage of existing approaches and exploratory approaches that...

Evaluation of a modified 16-item Readiness for Interprofessional Learning Scale (RIPLS): Exploratory and confirmatory factor analyses.

PubMed

Yu, Tzu-Chieh; Jowsey, Tanisha; Henning, Marcus

2018-04-18

The Readiness for Interprofessional Learning Scale (RIPLS) was developed to assess undergraduate readiness for engaging in interprofessional education (IPE). It has become an accepted and commonly used instrument. To determine utility of a modified 16-item RIPLS instrument, exploratory and confirmatory factor analyses were performed. Data used were collected from a pre- and post-intervention study involving 360 New Zealand undergraduate students from one university. Just over half of the participants were enrolled in medicine (51%) while the remainder were in pharmacy (27%) and nursing (22%). The intervention was a two-day simulation-based IPE course focused on managing unplanned acute medical problems in hospital wards ("ward calls"). Immediately prior to the course, 288 RIPLS were collected and immediately afterwards, 322 (response rates 80% and 89%, respectively). Exploratory factor analysis involving principal axis factoring with an oblique rotation method was conducted using pre-course data. The scree plot suggested a three-factor solution over two- and four-factor solutions. Subsequent confirmatory factor analysis performed using post-course data demonstrated partial goodness-of-fit for this suggested three-factor model. Based on these findings, further robust psychometric testing of the RIPLS or modified versions of it is recommended before embarking on its use in evaluative research in various healthcare education settings.

Checking Dimensionality in Item Response Models with Principal Component Analysis on Standardized Residuals

ERIC Educational Resources Information Center

Chou, Yeh-Tai; Wang, Wen-Chung

2010-01-01

Dimensionality is an important assumption in item response theory (IRT). Principal component analysis on standardized residuals has been used to check dimensionality, especially under the family of Rasch models. It has been suggested that an eigenvalue greater than 1.5 for the first eigenvalue signifies a violation of unidimensionality when there…

Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Singh, Renu; Steinley, Douglas

2009-01-01

The selection of a subset of variables from a pool of candidates is an important problem in several areas of multivariate statistics. Within the context of principal component analysis (PCA), a number of authors have argued that subset selection is crucial for identifying those variables that are required for correct interpretation of the…

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

PubMed

Mitsutake, Ayori; Iijima, Hiromitsu; Takano, Hiroshi

2011-10-28

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

Matrix partitioning and EOF/principal component analysis of Antarctic Sea ice brightness temperatures

NASA Technical Reports Server (NTRS)

Murray, C. W., Jr.; Mueller, J. L.; Zwally, H. J.

1984-01-01

A field of measured anomalies of some physical variable relative to their time averages, is partitioned in either the space domain or the time domain. Eigenvectors and corresponding principal components of the smaller dimensioned covariance matrices associated with the partitioned data sets are calculated independently, then joined to approximate the eigenstructure of the larger covariance matrix associated with the unpartitioned data set. The accuracy of the approximation (fraction of the total variance in the field) and the magnitudes of the largest eigenvalues from the partitioned covariance matrices together determine the number of local EOF's and principal components to be joined by any particular level. The space-time distribution of Nimbus-5 ESMR sea ice measurement is analyzed.

Fast principal component analysis for stacking seismic data

NASA Astrophysics Data System (ADS)

Wu, Juan; Bai, Min

2018-04-01

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

Multivariate analyses of salt stress and metabolite sensing in auto- and heterotroph Chenopodium cell suspensions.

PubMed

Wongchai, C; Chaidee, A; Pfeiffer, W

2012-01-01

Global warming increases plant salt stress via evaporation after irrigation, but how plant cells sense salt stress remains unknown. Here, we searched for correlation-based targets of salt stress sensing in Chenopodium rubrum cell suspension cultures. We proposed a linkage between the sensing of salt stress and the sensing of distinct metabolites. Consequently, we analysed various extracellular pH signals in autotroph and heterotroph cell suspensions. Our search included signals after 52 treatments: salt and osmotic stress, ion channel inhibitors (amiloride, quinidine), salt-sensing modulators (proline), amino acids, carboxylic acids and regulators (salicylic acid, 2,4-dichlorphenoxyacetic acid). Multivariate analyses revealed hirarchical clusters of signals and five principal components of extracellular proton flux. The principal component correlated with salt stress was an antagonism of γ-aminobutyric and salicylic acid, confirming involvement of acid-sensing ion channels (ASICs) in salt stress sensing. Proline, short non-substituted mono-carboxylic acids (C2-C6), lactic acid and amiloride characterised the four uncorrelated principal components of proton flux. The proline-associated principal component included an antagonism of 2,4-dichlorphenoxyacetic acid and a set of amino acids (hydrophobic, polar, acidic, basic). The five principal components captured 100% of variance of extracellular proton flux. Thus, a bias-free, functional high-throughput screening was established to extract new clusters of response elements and potential signalling pathways, and to serve as a core for quantitative meta-analysis in plant biology. The eigenvectors reorient research, associating proline with development instead of salt stress, and the proof of existence of multiple components of proton flux can help to resolve controversy about the acid growth theory. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

The Yoruba version of the Beck Hopelessness Scale: psychometric characteristics and correlates of hopelessness in a sample of Nigerian psychiatric outpatients.

PubMed

Aloba, Olutayo; Akinsulore, Adesanmi; Mapayi, Boladale; Oloniniyi, Ibiduniyi; Mosaku, Kolawole; Alimi, Taiwo; Esan, Olufemi

2015-01-01

Previous studies from the developed western countries have repeatedly demonstrated that hopelessness positively correlates with an increased risk of suicide in the context of chronic mental disorders such as schizophrenia and affective disorders. Despite this persistently strong association, the construct of hopelessness in terms of its factorial structure and correlates has not been explored among Nigerian psychiatric outpatients. The aim of this present study is to examine the psychometric characteristics of the Yoruba language culturally adapted version of the Beck Hopelessness Scale in a cross-sectional sample of psychiatric outpatients in South-western Nigeria. The participants were 327 Nigerian adult outpatients receiving treatment for schizophrenia, bipolar and depressive disorders, consecutively recruited from the outpatient psychiatric clinics of a university teaching hospital in South-western Nigeria. The outpatients were recruited over a one year period. They completed the Yoruba translated version of the Beck Hopelessness Scale (BHS-Y), a sociodemographic and illness-related questionnaire, the Beck Depression Inventory-II (BDI-II). Their level of functioning was assessed with the Global Assessment of Functioning Scale (GAF), psychopathology was evaluated with the Positive and Negative Syndrome Scale (PANSS) and the level of disability measured with the World Health Organization Disability Assessment Schedule (WHODAS-II). Suicidality and confirmation of the diagnoses of schizophrenia, bipolar and depressive disorders were evaluated with the Mini International Neuropsychiatric Interview (MINI). The construct of hopelessness in terms of factorial structure, reliability, validity and correlates was explored. Exploratory Factor Analysis using Principal Component Analysis with Varimax rotation was used to examine the factorial structure of the BHS-Y. Internal consistency was examined with Cronbach's alpha, and the construct validity of the scale was assessed using correlational analyses with the MINI suicidality module, BDI-II, GAF and WHODAS-II domain scores. We also tested the hypothesis that a shortened version of the BHS-Y will possess psychometric properties similar to the 20 item version. Exploratory Factor Analysis using Principal Component Analysis with Varimax rotation showed that the construct of hopelessness among our outpatients was best explained by a 3 factor model. Reliability of the translated version of the scale was adequate as indicated by a Cronbach's alpha of 0.92. Construct validity was also satisfactory as reflected by the strong correlations with MINI suicidality, Beck Depression Inventory-II and Global Assessment of Functioning scores. The shortened 4 item single factor BHS-Y composed of items 8, 9, 13 and 15 demonstrated psychometric properties similar to those of the full item version. The Beck Hopelessness Scale (Yoruba Version) demonstrated satisfactory reliability and validity and therefore may be useful in measuring the construct of hopelessness and in clinical suicide risk assessments among Nigerian psychiatric outpatients. There is the need for more studies to further explore the psychometric features and correlates of this scale among other Nigerian ethnic groups in addition to other medical patients' populations. Copyright © 2014 Elsevier Inc. All rights reserved.

[The application of the multidimensional statistical methods in the evaluation of the influence of atmospheric pollution on the population's health].

PubMed

Surzhikov, V D; Surzhikov, D V

2014-01-01

The search and measurement of causal relationships between exposure to air pollution and health state of the population is based on the system analysis and risk assessment to improve the quality of research. With this purpose there is applied the modern statistical analysis with the use of criteria of independence, principal component analysis and discriminate function analysis. As a result of analysis out of all atmospheric pollutants there were separated four main components: for diseases of the circulatory system main principal component is implied with concentrations of suspended solids, nitrogen dioxide, carbon monoxide, hydrogen fluoride, for the respiratory diseases the main c principal component is closely associated with suspended solids, sulfur dioxide and nitrogen dioxide, charcoal black. The discriminant function was shown to be used as a measure of the level of air pollution.

Priority of VHS Development Based in Potential Area using Principal Component Analysis

NASA Astrophysics Data System (ADS)

Meirawan, D.; Ana, A.; Saripudin, S.

2018-02-01

The current condition of VHS is still inadequate in quality, quantity and relevance. The purpose of this research is to analyse the development of VHS based on the development of regional potential by using principal component analysis (PCA) in Bandung, Indonesia. This study used descriptive qualitative data analysis using the principle of secondary data reduction component. The method used is Principal Component Analysis (PCA) analysis with Minitab Statistics Software tool. The results of this study indicate the value of the lowest requirement is a priority of the construction of development VHS with a program of majors in accordance with the development of regional potential. Based on the PCA score found that the main priority in the development of VHS in Bandung is in Saguling, which has the lowest PCA value of 416.92 in area 1, Cihampelas with the lowest PCA value in region 2 and Padalarang with the lowest PCA value.

Comparison of dimensionality reduction methods to predict genomic breeding values for carcass traits in pigs.

PubMed

Azevedo, C F; Nascimento, M; Silva, F F; Resende, M D V; Lopes, P S; Guimarães, S E F; Glória, L S

2015-10-09

A significant contribution of molecular genetics is the direct use of DNA information to identify genetically superior individuals. With this approach, genome-wide selection (GWS) can be used for this purpose. GWS consists of analyzing a large number of single nucleotide polymorphism markers widely distributed in the genome; however, because the number of markers is much larger than the number of genotyped individuals, and such markers are highly correlated, special statistical methods are widely required. Among these methods, independent component regression, principal component regression, partial least squares, and partial principal components stand out. Thus, the aim of this study was to propose an application of the methods of dimensionality reduction to GWS of carcass traits in an F2 (Piau x commercial line) pig population. The results show similarities between the principal and the independent component methods and provided the most accurate genomic breeding estimates for most carcass traits in pigs.

Performance-Based Preparation of Principals: A Framework for Improvement. A Special Report of the NASSP Consortium for the Performance-Based Preparation of Principals.

ERIC Educational Resources Information Center

National Association of Secondary School Principals, Reston, VA.

Preparation programs for principals should have excellent academic and performance based components. In examining the nature of performance based principal preparation this report finds that school administration programs must bridge the gap between conceptual learning in the classroom and the requirements of professional practice. A number of…

Principal component greenness transformation in multitemporal agricultural Landsat data

NASA Technical Reports Server (NTRS)

Abotteen, R. A.

1978-01-01

A data compression technique for multitemporal Landsat imagery which extracts phenological growth pattern information for agricultural crops is described. The principal component greenness transformation was applied to multitemporal agricultural Landsat data for information retrieval. The transformation was favorable for applications in agricultural Landsat data analysis because of its physical interpretability and its relation to the phenological growth of crops. It was also found that the first and second greenness eigenvector components define a temporal small-grain trajectory and nonsmall-grain trajectory, respectively.

Hard water softening effect of a baby cleanser

PubMed Central

Walters, Russel M; Anim-Danso, Emmanuel; Amato, Stephanie M; Capone, Kimberly A; Mack, M Catherine; Telofski, Lorena S; Mays, David A

2016-01-01

Background Hard water is associated with atopic dermatitis (eczema). We wanted to determine if a baby cleanser and its individual components altered free ionized calcium (Ca2+) in a simulated hard water baby bath. For these studies, an in vitro determination of free Ca2+ in a simulated hard water baby bath, and an in vivo exploratory study of free Ca2+ absorption into skin from hard water were performed. Methods Free Ca2+ was measured with an ion-sensitive electrode in vitro in hard water (100–500 ppm, Ca2+) before and after addition of the cleanser and/or its components. In an exploratory study, absorption of Ca2+ into skin from hard water was determined in three female participants (aged 21–29 years). Results At an in-use dilution of 1%, the test cleanser reduced free Ca2+ from ~500 ppm to <200 ppm; a 10% in-use dilution bound virtually all free Ca2+. The anionic surfactant component contributed the most to this effect. In the exploratory in vivo study, we measured a reduction of ~15% in free Ca2+ from simulated hard water over 10 minutes. Conclusion Baby cleansers can bind free Ca2+ and reduce the effective water hardness of bath water. Reducing the amount of free Ca2+ in the water will reduce the availability of the ion for binding to the skin. Altering or reducing free Ca2+ concentrations in bath water may be an important parameter in creating the ideal baby bath. PMID:27789967

Prediction of genomic breeding values for dairy traits in Italian Brown and Simmental bulls using a principal component approach.

PubMed

Pintus, M A; Gaspa, G; Nicolazzi, E L; Vicario, D; Rossoni, A; Ajmone-Marsan, P; Nardone, A; Dimauro, C; Macciotta, N P P

2012-06-01

The large number of markers available compared with phenotypes represents one of the main issues in genomic selection. In this work, principal component analysis was used to reduce the number of predictors for calculating genomic breeding values (GEBV). Bulls of 2 cattle breeds farmed in Italy (634 Brown and 469 Simmental) were genotyped with the 54K Illumina beadchip (Illumina Inc., San Diego, CA). After data editing, 37,254 and 40,179 single nucleotide polymorphisms (SNP) were retained for Brown and Simmental, respectively. Principal component analysis carried out on the SNP genotype matrix extracted 2,257 and 3,596 new variables in the 2 breeds, respectively. Bulls were sorted by birth year to create reference and prediction populations. The effect of principal components on deregressed proofs in reference animals was estimated with a BLUP model. Results were compared with those obtained by using SNP genotypes as predictors with either the BLUP or Bayes_A method. Traits considered were milk, fat, and protein yields, fat and protein percentages, and somatic cell score. The GEBV were obtained for prediction population by blending direct genomic prediction and pedigree indexes. No substantial differences were observed in squared correlations between GEBV and EBV in prediction animals between the 3 methods in the 2 breeds. The principal component analysis method allowed for a reduction of about 90% in the number of independent variables when predicting direct genomic values, with a substantial decrease in calculation time and without loss of accuracy. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Identifying sources of emerging organic contaminants in a mixed use watershed using principal components analysis.

PubMed

Karpuzcu, M Ekrem; Fairbairn, David; Arnold, William A; Barber, Brian L; Kaufenberg, Elizabeth; Koskinen, William C; Novak, Paige J; Rice, Pamela J; Swackhamer, Deborah L

2014-01-01

Principal components analysis (PCA) was used to identify sources of emerging organic contaminants in the Zumbro River watershed in Southeastern Minnesota. Two main principal components (PCs) were identified, which together explained more than 50% of the variance in the data. Principal Component 1 (PC1) was attributed to urban wastewater-derived sources, including municipal wastewater and residential septic tank effluents, while Principal Component 2 (PC2) was attributed to agricultural sources. The variances of the concentrations of cotinine, DEET and the prescription drugs carbamazepine, erythromycin and sulfamethoxazole were best explained by PC1, while the variances of the concentrations of the agricultural pesticides atrazine, metolachlor and acetochlor were best explained by PC2. Mixed use compounds carbaryl, iprodione and daidzein did not specifically group with either PC1 or PC2. Furthermore, despite the fact that caffeine and acetaminophen have been historically associated with human use, they could not be attributed to a single dominant land use category (e.g., urban/residential or agricultural). Contributions from septic systems did not clarify the source for these two compounds, suggesting that additional sources, such as runoff from biosolid-amended soils, may exist. Based on these results, PCA may be a useful way to broadly categorize the sources of new and previously uncharacterized emerging contaminants or may help to clarify transport pathways in a given area. Acetaminophen and caffeine were not ideal markers for urban/residential contamination sources in the study area and may need to be reconsidered as such in other areas as well.

Sparse modeling of spatial environmental variables associated with asthma

PubMed Central

Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.

2014-01-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437

Sparse modeling of spatial environmental variables associated with asthma.

PubMed

Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

2015-02-01

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Experimental Investigation of Principal Residual Stress and Fatigue Performance for Turned Nickel-Based Superalloy Inconel 718.

PubMed

Hua, Yang; Liu, Zhanqiang

2018-05-24

Residual stresses of turned Inconel 718 surface along its axial and circumferential directions affect the fatigue performance of machined components. However, it has not been clear that the axial and circumferential directions are the principle residual stress direction. The direction of the maximum principal residual stress is crucial for the machined component service life. The present work aims to focuses on determining the direction and magnitude of principal residual stress and investigating its influence on fatigue performance of turned Inconel 718. The turning experimental results show that the principal residual stress magnitude is much higher than surface residual stress. In addition, both the principal residual stress and surface residual stress increase significantly as the feed rate increases. The fatigue test results show that the direction of the maximum principal residual stress increased by 7.4%, while the fatigue life decreased by 39.4%. The maximum principal residual stress magnitude diminished by 17.9%, whereas the fatigue life increased by 83.6%. The maximum principal residual stress has a preponderant influence on fatigue performance as compared to the surface residual stress. The maximum principal residual stress can be considered as a prime indicator for evaluation of the residual stress influence on fatigue performance of turned Inconel 718.

Principal component analysis for designed experiments.

PubMed

Konishi, Tomokazu

2015-01-01

Principal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit. The effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes. Together, these introduced options result in improved generality and objectivity of the analytical results. The methodology has thus become more like a set of multiple regression analyses that find independent models that specify each of the axes.

Coping with Multicollinearity: An Example on Application of Principal Components Regression in Dendroecology

Treesearch

B. Desta Fekedulegn; J.J. Colbert; R.R., Jr. Hicks; Michael E. Schuckers

2002-01-01

The theory and application of principal components regression, a method for coping with multicollinearity among independent variables in analyzing ecological data, is exhibited in detail. A concrete example of the complex procedures that must be carried out in developing a diagnostic growth-climate model is provided. We use tree radial increment data taken from breast...

Application of Principal Component Analysis (PCA) to Reduce Multicollinearity Exchange Rate Currency of Some Countries in Asia Period 2004-2014

ERIC Educational Resources Information Center

Rahayu, Sri; Sugiarto, Teguh; Madu, Ludiro; Holiawati; Subagyo, Ahmad

2017-01-01

This study aims to apply the model principal component analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hong Kong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield…

Radiative Transfer Modeling and Retrievals for Advanced Hyperspectral Sensors

NASA Technical Reports Server (NTRS)

Liu, Xu; Zhou, Daniel K.; Larar, Allen M.; Smith, William L., Sr.; Mango, Stephen A.

2009-01-01

A novel radiative transfer model and a physical inversion algorithm based on principal component analysis will be presented. Instead of dealing with channel radiances, the new approach fits principal component scores of these quantities. Compared to channel-based radiative transfer models, the new approach compresses radiances into a much smaller dimension making both forward modeling and inversion algorithm more efficient.

Principal component analysis of Raman spectra for TiO2 nanoparticle characterization

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

PubMed Central

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

2013-01-01

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

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.

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

USGS Publications Warehouse

Mahler, Barbara J.

2008-01-01

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

Edge Principal Components and Squash Clustering: Using the Special Structure of Phylogenetic Placement Data for Sample Comparison

PubMed Central

Matsen IV, Frederick A.; Evans, Steven N.

2013-01-01

Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used techniques for analyzing the differences between nucleic acid sequence samples taken from a given environment. They have led to many insights regarding the structure of microbial communities. We have developed two new complementary methods that leverage how this microbial community data sits on a phylogenetic tree. Edge principal components analysis enables the detection of important differences between samples that contain closely related taxa. Each principal component axis is a collection of signed weights on the edges of the phylogenetic tree, and these weights are easily visualized by a suitable thickening and coloring of the edges. Squash clustering outputs a (rooted) clustering tree in which each internal node corresponds to an appropriate “average” of the original samples at the leaves below the node. Moreover, the length of an edge is a suitably defined distance between the averaged samples associated with the two incident nodes, rather than the less interpretable average of distances produced by UPGMA, the most widely used hierarchical clustering method in this context. We present these methods and illustrate their use with data from the human microbiome. PMID:23505415

Time Management Ideas for Assistant Principals.

ERIC Educational Resources Information Center

Cronk, Jerry

1987-01-01

Prioritizing the use of time, effective communication, delegating authority, having detailed job descriptions, and good secretarial assistance are important components of time management for assistant principals. (MD)

The principal components model: a model for advancing spirituality and spiritual care within nursing and health care practice.

PubMed

McSherry, Wilfred

2006-07-01

The aim of this study was to generate a deeper understanding of the factors and forces that may inhibit or advance the concepts of spirituality and spiritual care within both nursing and health care. This manuscript presents a model that emerged from a qualitative study using grounded theory. Implementation and use of this model may assist all health care practitioners and organizations to advance the concepts of spirituality and spiritual care within their own sphere of practice. The model has been termed the principal components model because participants identified six components as being crucial to the advancement of spiritual health care. Grounded theory was used meaning that there was concurrent data collection and analysis. Theoretical sampling was used to develop the emerging theory. These processes, along with data analysis, open, axial and theoretical coding led to the identification of a core category and the construction of the principal components model. Fifty-three participants (24 men and 29 women) were recruited and all consented to be interviewed. The sample included nurses (n=24), chaplains (n=7), a social worker (n=1), an occupational therapist (n=1), physiotherapists (n=2), patients (n=14) and the public (n=4). The investigation was conducted in three phases to substantiate the emerging theory and the development of the model. The principal components model contained six components: individuality, inclusivity, integrated, inter/intra-disciplinary, innate and institution. A great deal has been written on the concepts of spirituality and spiritual care. However, rhetoric alone will not remove some of the intrinsic and extrinsic barriers that are inhibiting the advancement of the spiritual dimension in terms of theory and practice. An awareness of and adherence to the principal components model may assist nurses and health care professionals to engage with and overcome some of the structural, organizational, political and social variables that are impacting upon spiritual care.

Facial anthropometric differences among gender, ethnicity, and age groups.

PubMed

Zhuang, Ziqing; Landsittel, Douglas; Benson, Stacey; Roberge, Raymond; Shaffer, Ronald

2010-06-01

The impact of race/ethnicity upon facial anthropometric data in the US workforce, on the development of personal protective equipment, has not been investigated to any significant degree. The proliferation of minority populations in the US workforce has increased the need to investigate differences in facial dimensions among these workers. The objective of this study was to determine the face shape and size differences among race and age groups from the National Institute for Occupational Safety and Health survey of 3997 US civilian workers. Survey participants were divided into two gender groups, four racial/ethnic groups, and three age groups. Measurements of height, weight, neck circumference, and 18 facial dimensions were collected using traditional anthropometric techniques. A multivariate analysis of the data was performed using Principal Component Analysis. An exploratory analysis to determine the effect of different demographic factors had on anthropometric features was assessed via a linear model. The 21 anthropometric measurements, body mass index, and the first and second principal component scores were dependent variables, while gender, ethnicity, age, occupation, weight, and height served as independent variables. Gender significantly contributes to size for 19 of 24 dependent variables. African-Americans have statistically shorter, wider, and shallower noses than Caucasians. Hispanic workers have 14 facial features that are significantly larger than Caucasians, while their nose protrusion, height, and head length are significantly shorter. The other ethnic group was composed primarily of Asian subjects and has statistically different dimensions from Caucasians for 16 anthropometric values. Nineteen anthropometric values for subjects at least 45 years of age are statistically different from those measured for subjects between 18 and 29 years of age. Workers employed in manufacturing, fire fighting, healthcare, law enforcement, and other occupational groups have facial features that differ significantly than those in construction. Statistically significant differences in facial anthropometric dimensions (P < 0.05) were noted between males and females, all racial/ethnic groups, and the subjects who were at least 45 years old when compared to workers between 18 and 29 years of age. These findings could be important to the design and manufacture of respirators, as well as employers responsible for supplying respiratory protective equipment to their employees.

Developing and evaluating an instrument to measure Recovery After INtensive care: the RAIN instrument.

PubMed

Bergbom, Ingegerd; Karlsson, Veronika; Ringdal, Mona

2018-01-01

Measuring and evaluating patients' recovery, following intensive care, is essential for assessing their recovery process. By using a questionnaire, which includes spiritual and existential aspects, possibilities for identifying appropriate nursing care activities may be facilitated. The study describes the development and evaluation of a recovery questionnaire and its validity and reliability. A questionnaire consisting of 30 items on a 5-point Likert scale was completed by 169 patients (103 men, 66 women), 18 years or older (m=69, SD 12.5) at 2, 6, 12 or 24 months following discharge from an ICU. An exploratory factor analysis, including a principal component analysis with orthogonal varimax rotation, was conducted. Ten initial items, with loadings below 0.40, were removed. The internal item/scale structure obtained in the principal component analysis was tested in relation to convergent and discrimination validity with a multi-trait analysis. Items consistency and reliability were assessed by Cronbach's alpha and internal item consistency. Test of scale quality, the proportion of missing values and respondents' scoring at maximum and minimum levels were also conducted. A total of 20 items in six factors - forward looking, supporting relations, existential ruminations, revaluation of life, physical and mental strength and need of social support were extracted with eigen values above one. Together, they explained 75% of the variance. The half-scale criterion showed that the proportion of incomplete scale scores ranged from 0% to 4.3%. When testing the scale's ability to differentiate between levels of the assessed concept, we found that the observed range of scale scores covered the theoretical range. Substantial proportions of respondents, who scored at the ceiling for forward looking and supporting relations and at floor for the need of social support, were found. These findings should be further investigated. The factor analysis, including discriminant validity and the mean value for the item correlations, was found to be excellent. The RAIN instrument could be used to assess recovery following intensive care. It could provide post-ICU clinics and community/primary healthcare nurses with valuable information on which areas patients may need more support.

Exploratory and Confirmatory Factor Analyses in Reading-Related Cognitive Component among Grade Four Students in Thailand

ERIC Educational Resources Information Center

Liao, Chen-Huei; Kuo, Bor-Chen; Deenang, Exkarach; Mok, Magdalena Mo Ching

2016-01-01

This study aimed to investigate the structure and the validity of the cognitive components of reading in Thai, which is a language with a high degree of grapheme-phoneme correspondence. The participants were 1181 fourth-grade students in 29 schools in Thailand, divided into two subsamples for data analysis. Phoneme isolation, rapid colour naming,…

High area rate reconnaissance (HARR) and mine reconnaissance/hunter (MR/H) exploratory development programs

NASA Astrophysics Data System (ADS)

Lathrop, John D.

1995-06-01

This paper describes the sea mine countermeasures developmental context, technology goals, and progress to date of the two principal Office of Naval Research exploratory development programs addressing sea mine reconnaissance and minehunting technology development. The first of these programs, High Area Rate Reconnaissance, is developing toroidal volume search sonar technology, sidelooking sonar technology, and associated signal processing technologies (motion compensation, beamforming, and computer-aided detection and classification) for reconnaissance and hunting against volume mines and proud bottom mines from 21-inch diameter vehicles operating in deeper waters. The second of these programs, Amphibious Operation Area Mine Reconnaissance/Hunter, is developing a suite of sensor technologies (synthetic aperture sonar, ahead-looking sonar, superconducting magnetic field gradiometer, and electro-optic sensor) and associated signal processing technologies for reconnaissance and hunting against all mine types (including buried mines) in shallow water and very shallow water from 21-inch diameter vehicles. The technologies under development by these two programs must provide excellent capabilities for mine detection, mine classification, and discrimination against false targets.

Principal component analysis of the nonlinear coupling of harmonic modes in heavy-ion collisions

NASA Astrophysics Data System (ADS)

BoŻek, Piotr

2018-03-01

The principal component analysis of flow correlations in heavy-ion collisions is studied. The correlation matrix of harmonic flow is generalized to correlations involving several different flow vectors. The method can be applied to study the nonlinear coupling between different harmonic modes in a double differential way in transverse momentum or pseudorapidity. The procedure is illustrated with results from the hydrodynamic model applied to Pb + Pb collisions at √{sN N}=2760 GeV. Three examples of generalized correlations matrices in transverse momentum are constructed corresponding to the coupling of v22 and v4, of v2v3 and v5, or of v23,v33 , and v6. The principal component decomposition is applied to the correlation matrices and the dominant modes are calculated.

Analysis and improvement measures of flight delay in China

NASA Astrophysics Data System (ADS)

Zang, Yuhang

2017-03-01

Firstly, this paper establishes the principal component regression model to analyze the data quantitatively, based on principal component analysis to get the three principal component factors of flight delays. Then the least square method is used to analyze the factors and obtained the regression equation expression by substitution, and then found that the main reason for flight delays is airlines, followed by weather and traffic. Aiming at the above problems, this paper improves the controllable aspects of traffic flow control. For reasons of traffic flow control, an adaptive genetic queuing model is established for the runway terminal area. This paper, establish optimization method that fifteen planes landed simultaneously on the three runway based on Beijing capital international airport, comparing the results with the existing FCFS algorithm, the superiority of the model is proved.

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

PubMed

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

2016-01-01

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

Polyhedral gamut representation of natural objects based on spectral reflectance database and its application

NASA Astrophysics Data System (ADS)

Haneishi, Hideaki; Sakuda, Yasunori; Honda, Toshio

2002-06-01

Spectral reflectance of most reflective objects such as natural objects and color hardcopy is relatively smooth and can be approximated by several numbers of principal components with high accuracy. Though the subspace spanned by those principal components represents a space in which reflective objects can exist, it dos not provide the bound in which the samples distribute. In this paper we propose to represent the gamut of reflective objects in more distinct form, i.e., as a polyhedron in the subspace spanned by several principal components. Concept of the polyhedral gamut representation and its application to calculation of metamer ensemble are described. Color-mismatch volume caused by different illuminant and/or observer for a metamer ensemble is also calculated and compared with theoretical one.

Evaluation of Low-Voltage Distribution Network Index Based on Improved Principal Component Analysis

NASA Astrophysics Data System (ADS)

Fan, Hanlu; Gao, Suzhou; Fan, Wenjie; Zhong, Yinfeng; Zhu, Lei

2018-01-01

In order to evaluate the development level of the low-voltage distribution network objectively and scientifically, chromatography analysis method is utilized to construct evaluation index model of low-voltage distribution network. Based on the analysis of principal component and the characteristic of logarithmic distribution of the index data, a logarithmic centralization method is adopted to improve the principal component analysis algorithm. The algorithm can decorrelate and reduce the dimensions of the evaluation model and the comprehensive score has a better dispersion degree. The clustering method is adopted to analyse the comprehensive score because the comprehensive score of the courts is concentrated. Then the stratification evaluation of the courts is realized. An example is given to verify the objectivity and scientificity of the evaluation method.

Online signature recognition using principal component analysis and artificial neural network

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Hydraulic-fracturing measurmements in two boreholes near the Spent Fuel Test-Climax, Climax Stock, Nevada Test Site

USGS Publications Warehouse

Ellis, William L.

1983-01-01

Hydraulic-fracturing measurements are used to infer the magnitude of the least principal stress in the vicinity of the Spent Fuel Test-Climax, located in the Climax stock at the Nevada Test Site. The measurements, made at various depths in two exploratory boreholes, suggest that the local stress field is not uniform. Estimates of the least principal stress magnitude vary over distances of a few tens of meters, with the smaller values averaging 2.9 MPa and the larger values averaging 5.5 MPa. The smaller values are in agreement with the minimum-stress magnitude of 2.8 MPa determined in a nearby drift in 1979, using an overcoring technique. Jointing in the granitic rock mass and (or) the influence of nearby faults may account for the apparent variation in minimum-stress magnitude indicated by the hydrofracture data.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

The Artistic Nature of the High School Principal.

ERIC Educational Resources Information Center

Ritschel, Robert E.

The role of high school principals can be compared to that of composers of music. For instance, composers put musical components together into a coherent whole; similarly, principals organize high schools by establishing class schedules, assigning roles to subordinates, and maintaining a safe and orderly learning environment. Second, composers…

Collaborative Relationships between Principals and School Counselors: Facilitating a Model for Developing a Working Alliance

ERIC Educational Resources Information Center

Odegard-Koester, Melissa A.; Watkins, Paul

2016-01-01

The working relationship between principals and school counselors have received some attention in the literature, however, little empirical research exists that examines specifically the components that facilitate a collaborative working relationship between the principal and school counselor. This qualitative case study examined the unique…

The Retention and Attrition of Catholic School Principals

ERIC Educational Resources Information Center

Durow, W. Patrick; Brock, Barbara L.

2004-01-01

This article reports the results of a study of the retention of principals in Catholic elementary and secondary schools in one Midwestern diocese. Findings revealed that personal needs, career advancement, support from employer, and clearly defined role expectations were key factors in principals' retention decisions. A profile of components of…

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…

Perturbation analyses of intermolecular interactions

NASA Astrophysics Data System (ADS)

Koyama, Yohei M.; Kobayashi, Tetsuya J.; Ueda, Hiroki R.

2011-08-01

Conformational fluctuations of a protein molecule are important to its function, and it is known that environmental molecules, such as water molecules, ions, and ligand molecules, significantly affect the function by changing the conformational fluctuations. However, it is difficult to systematically understand the role of environmental molecules because intermolecular interactions related to the conformational fluctuations are complicated. To identify important intermolecular interactions with regard to the conformational fluctuations, we develop herein (i) distance-independent and (ii) distance-dependent perturbation analyses of the intermolecular interactions. We show that these perturbation analyses can be realized by performing (i) a principal component analysis using conditional expectations of truncated and shifted intermolecular potential energy terms and (ii) a functional principal component analysis using products of intermolecular forces and conditional cumulative densities. We refer to these analyses as intermolecular perturbation analysis (IPA) and distance-dependent intermolecular perturbation analysis (DIPA), respectively. For comparison of the IPA and the DIPA, we apply them to the alanine dipeptide isomerization in explicit water. Although the first IPA principal components discriminate two states (the α state and PPII (polyproline II) + β states) for larger cutoff length, the separation between the PPII state and the β state is unclear in the second IPA principal components. On the other hand, in the large cutoff value, DIPA eigenvalues converge faster than that for IPA and the top two DIPA principal components clearly identify the three states. By using the DIPA biplot, the contributions of the dipeptide-water interactions to each state are analyzed systematically. Since the DIPA improves the state identification and the convergence rate with retaining distance information, we conclude that the DIPA is a more practical method compared with the IPA. To test the feasibility of the DIPA for larger molecules, we apply the DIPA to the ten-residue chignolin folding in explicit water. The top three principal components identify the four states (native state, two misfolded states, and unfolded state) and their corresponding eigenfunctions identify important chignolin-water interactions to each state. Thus, the DIPA provides the practical method to identify conformational states and their corresponding important intermolecular interactions with distance information.

Perturbation analyses of intermolecular interactions.

PubMed

Koyama, Yohei M; Kobayashi, Tetsuya J; Ueda, Hiroki R

2011-08-01

Conformational fluctuations of a protein molecule are important to its function, and it is known that environmental molecules, such as water molecules, ions, and ligand molecules, significantly affect the function by changing the conformational fluctuations. However, it is difficult to systematically understand the role of environmental molecules because intermolecular interactions related to the conformational fluctuations are complicated. To identify important intermolecular interactions with regard to the conformational fluctuations, we develop herein (i) distance-independent and (ii) distance-dependent perturbation analyses of the intermolecular interactions. We show that these perturbation analyses can be realized by performing (i) a principal component analysis using conditional expectations of truncated and shifted intermolecular potential energy terms and (ii) a functional principal component analysis using products of intermolecular forces and conditional cumulative densities. We refer to these analyses as intermolecular perturbation analysis (IPA) and distance-dependent intermolecular perturbation analysis (DIPA), respectively. For comparison of the IPA and the DIPA, we apply them to the alanine dipeptide isomerization in explicit water. Although the first IPA principal components discriminate two states (the α state and PPII (polyproline II) + β states) for larger cutoff length, the separation between the PPII state and the β state is unclear in the second IPA principal components. On the other hand, in the large cutoff value, DIPA eigenvalues converge faster than that for IPA and the top two DIPA principal components clearly identify the three states. By using the DIPA biplot, the contributions of the dipeptide-water interactions to each state are analyzed systematically. Since the DIPA improves the state identification and the convergence rate with retaining distance information, we conclude that the DIPA is a more practical method compared with the IPA. To test the feasibility of the DIPA for larger molecules, we apply the DIPA to the ten-residue chignolin folding in explicit water. The top three principal components identify the four states (native state, two misfolded states, and unfolded state) and their corresponding eigenfunctions identify important chignolin-water interactions to each state. Thus, the DIPA provides the practical method to identify conformational states and their corresponding important intermolecular interactions with distance information.

Fimbria-Fornix Lesions Disrupt the Dead Reckoning (Homing) Component of Exploratory Behavior in Mice

PubMed Central

Gorny, Joanna H.; Gorny, Bogdan; Wallace, Douglas G.; Whishaw, Ian Q.

2002-01-01

Exploration is the primary way in which rodents gather information about their spatial surroundings. Thus, spatial theories propose that damage to the hippocampus, a structure thought to play a fundamental role in spatial behavior, should disrupt exploration. Exploration in rats is organized. The animals create home bases that are central to exploratory excursions and returns, and hippocampal formation damage alters the organization of exploration by disrupting returns. Mice do not appear to readily establish home bases in novel environments, thus, for this species, it is more difficult to establish the contribution of the hippocampus to exploration. The purpose of the present study was threefold: develop a task in which mice center their exploration from a home base, determine whether the exploratory behavior is organized, and evaluate the role of fimbria-fornix lesions on exploration. Mice were given a novel exploratory task in which their nesting material was placed on a large circular table. Video records of control and fimbria-fornix mice were made in both light and dark (infrared light) conditions. Exploration patterns (outward trips, stops, and homeward trips) were reconstructed from the video records. Control mice centered their activity on their bedding, from which they made circuitous outward trips marked by many stops, and periodic direct returns. The bedding-centered behavior and outward trips of the fimbria-fornix mice were similar to those of the control mice, but significantly fewer direct return trips occurred. The direct homeward trips observed under light and dark conditions were consistent with a dead-reckoning strategy, in which an animal computes its present position and homeward trajectory from self-movement cues generated on the outward trip. Because the fimbria-fornix lesions disrupted the homeward component of exploratory trips, we conclude that the fimbria-fornix may contribute to dead reckoning in mice. The results also show that the home-bedding methodology facilitates the establishment of a home base by mice, thus providing a useful methodology for studies with mice. PMID:12464698

[Role of school lunch in primary school education: a trial analysis of school teachers' views using an open-ended questionnaire].

PubMed

Inayama, T; Kashiwazaki, H; Sakamoto, M

1998-12-01

We tried to analyze synthetically teachers' view points associated with health education and roles of school lunch in primary education. For this purpose, a survey using an open-ended questionnaire consisting of eight items relating to health education in the school curriculum was carried out in 100 teachers of ten public primary schools. Subjects were asked to describe their view regarding the following eight items: 1) health and physical guidance education, 2) school lunch guidance education, 3) pupils' attitude toward their own health and nutrition, 4) health education, 5) role of school lunch in education, 6) future subjects of health education, 7) class room lesson related to school lunch, 8) guidance in case of pupil with unbalanced dieting and food avoidance. Subjects described their own opinions on an open-ended questionnaire response sheet. Keywords in individual descriptions were selected, rearranged and classified into categories according to their own meanings, and each of the selected keywords were used as the dummy variable. To assess individual opinions synthetically, a principal component analysis was then applied to the variables collected through the teachers' descriptions, and four factors were extracted. The results were as follows. 1) Four factors obtained from the repeated principal component analysis were summarized as; roles of health education and school lunch program (the first principal component), cooperation with nurse-teachers and those in charge of lunch service (the second principal component), time allocation for health education in home-room activity and lunch time (the third principal component) and contents of health education and school lunch guidance and their future plan (the fourth principal component). 2) Teachers regarded the role of school lunch in primary education as providing daily supply of nutrients, teaching of table manners and building up friendships with classmates, health education and food and nutrition education, and developing food preferences through eating lunch together with classmates. 3) Significant positive correlation was observed between "the teachers' opinion about the role of school lunch of providing opportunity to learn good behavior for food preferences through eating lunch together with classmates" and the first principal component "roles of health education and school lunch program" (r = 0.39, p < 0.01). The variable "the role of school lunch is health education and food and nutrition education" showed positive correlation with the principle component "cooperation with nurse-teachers and those in charge of lunch service" (r = 0.27, p < 0.01). Interesting relationships obtained were that teachers with longer educational experience tended to place importance in health education and food and nutrition education as the role of school lunch, and that male teachers regarded the roles of school lunch more importantly for future education in primary education than female teachers did.

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.

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

PubMed

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

2003-01-01

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

HT-FRTC: a fast radiative transfer code using kernel regression

NASA Astrophysics Data System (ADS)

Thelen, Jean-Claude; Havemann, Stephan; Lewis, Warren

2016-09-01

The HT-FRTC is a principal component based fast radiative transfer code that can be used across the electromagnetic spectrum from the microwave through to the ultraviolet to calculate transmittance, radiance and flux spectra. The principal components cover the spectrum at a very high spectral resolution, which allows very fast line-by-line, hyperspectral and broadband simulations for satellite-based, airborne and ground-based sensors. The principal components are derived during a code training phase from line-by-line simulations for a diverse set of atmosphere and surface conditions. The derived principal components are sensor independent, i.e. no extra training is required to include additional sensors. During the training phase we also derive the predictors which are required by the fast radiative transfer code to determine the principal component scores from the monochromatic radiances (or fluxes, transmittances). These predictors are calculated for each training profile at a small number of frequencies, which are selected by a k-means cluster algorithm during the training phase. Until recently the predictors were calculated using a linear regression. However, during a recent rewrite of the code the linear regression was replaced by a Gaussian Process (GP) regression which resulted in a significant increase in accuracy when compared to the linear regression. The HT-FRTC has been trained with a large variety of gases, surface properties and scatterers. Rayleigh scattering as well as scattering by frozen/liquid clouds, hydrometeors and aerosols have all been included. The scattering phase function can be fully accounted for by an integrated line-by-line version of the Edwards-Slingo spherical harmonics radiation code or approximately by a modification to the extinction (Chou scaling).

Spectral decomposition of asteroid Itokawa based on principal component analysis

NASA Astrophysics Data System (ADS)

Koga, Sumire C.; Sugita, Seiji; Kamata, Shunichi; Ishiguro, Masateru; Hiroi, Takahiro; Tatsumi, Eri; Sasaki, Sho

2018-01-01

The heliocentric stratification of asteroid spectral types may hold important information on the early evolution of the Solar System. Asteroid spectral taxonomy is based largely on principal component analysis. However, how the surface properties of asteroids, such as the composition and age, are projected in the principal-component (PC) space is not understood well. We decompose multi-band disk-resolved visible spectra of the Itokawa surface with principal component analysis (PCA) in comparison with main-belt asteroids. The obtained distribution of Itokawa spectra projected in the PC space of main-belt asteroids follows a linear trend linking the Q-type and S-type regions and is consistent with the results of space-weathering experiments on ordinary chondrites and olivine, suggesting that this trend may be a space-weathering-induced spectral evolution track for S-type asteroids. Comparison with space-weathering experiments also yield a short average surface age (< a few million years) for Itokawa, consistent with the cosmic-ray-exposure time of returned samples from Itokawa. The Itokawa PC score distribution exhibits asymmetry along the evolution track, strongly suggesting that space weathering has begun saturated on this young asteroid. The freshest spectrum found on Itokawa exhibits a clear sign for space weathering, indicating again that space weathering occurs very rapidly on this body. We also conducted PCA on Itokawa spectra alone and compared the results with space-weathering experiments. The obtained results indicate that the first principal component of Itokawa surface spectra is consistent with spectral change due to space weathering and that the spatial variation in the degree of space weathering is very large (a factor of three in surface age), which would strongly suggest the presence of strong regional/local resurfacing process(es) on this small asteroid.

Vocal babbling in songbirds requires the basal ganglia-recipient motor thalamus but not the basal ganglia

PubMed Central

Goldberg, Jesse H.

2011-01-01

Young songbirds produce vocal “babbling,” and the variability of their songs is thought to underlie a process of trial-and-error vocal learning. It is known that this exploratory variability requires the “cortical” component of a basal ganglia (BG) thalamocortical loop, but less understood is the role of the BG and thalamic components in this behavior. We found that large bilateral lesions to the songbird BG homolog Area X had little or no effect on song variability during vocal babbling. In contrast, lesions to the BG-recipient thalamic nucleus DLM (medial portion of the dorsolateral thalamus) largely abolished normal vocal babbling in young birds and caused a dramatic increase in song stereotypy. These findings support the idea that the motor thalamus plays a key role in the expression of exploratory juvenile behaviors during learning. PMID:21430276

Principal component analysis and neurocomputing-based models for total ozone concentration over different urban regions of India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Goutami; Chattopadhyay, Surajit; Chakraborthy, Parthasarathi

2012-07-01

The present study deals with daily total ozone concentration time series over four metro cities of India namely Kolkata, Mumbai, Chennai, and New Delhi in the multivariate environment. Using the Kaiser-Meyer-Olkin measure, it is established that the data set under consideration are suitable for principal component analysis. Subsequently, by introducing rotated component matrix for the principal components, the predictors suitable for generating artificial neural network (ANN) for daily total ozone prediction are identified. The multicollinearity is removed in this way. Models of ANN in the form of multilayer perceptron trained through backpropagation learning are generated for all of the study zones, and the model outcomes are assessed statistically. Measuring various statistics like Pearson correlation coefficients, Willmott's indices, percentage errors of prediction, and mean absolute errors, it is observed that for Mumbai and Kolkata the proposed ANN model generates very good predictions. The results are supported by the linearly distributed coordinates in the scatterplots.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Leadership Coaching: A Multiple-Case Study of Urban Public Charter School Principals' Experiences

ERIC Educational Resources Information Center

Lackritz, Anne D.

2017-01-01

This multi-case study seeks to understand the experiences of New York City and Washington, DC public charter school principals who have experienced leadership coaching, a component of leadership development, beyond their novice years. The research questions framing this study address how experienced public charter school principals describe the…

The View from the Principal's Office: An Observation Protocol Boosts Literacy :eadership

ERIC Educational Resources Information Center

Novak, Sandi; Houck, Bonnie

2016-01-01

The Minnesota Elementary School Principals' Association offered Minnesota principals professional learning that placed a high priority on literacy instruction and developing a collegial culture. A key component is the literacy classroom visit, an observation protocol used to gather data to determine the status of literacy teaching and student…

Administrative Obstacles to Technology Use in West Virginia Public Schools: A Survey of West Virginia Principals

ERIC Educational Resources Information Center

Agnew, David W.

2011-01-01

Public school principals must meet many challenges and make decisions concerning financial obligations while providing the best learning environment for students. A major challenge to principals is implementing technological components successfully while providing teachers the 21st century instructional skills needed to enhance students'…

Differential principal component analysis of ChIP-seq.

PubMed

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

2013-04-23

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

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.

Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy TOPSIS: A Case Study from 30 Provinces, China

PubMed Central

Liang, Xuedong; Liu, Canmian; Li, Zhi

2017-01-01

In connection with the sustainable development of scenic spots, this paper, with consideration of resource conditions, economic benefits, auxiliary industry scale and ecological environment, establishes a comprehensive measurement model of the sustainable capacity of scenic spots; optimizes the index system by principal components analysis to extract principal components; assigns the weight of principal components by entropy method; analyzes the sustainable capacity of scenic spots in each province of China comprehensively in combination with TOPSIS method and finally puts forward suggestions aid decision-making. According to the study, this method provides an effective reference for the study of the sustainable development of scenic spots and is very significant for considering the sustainable development of scenic spots and auxiliary industries to establish specific and scientific countermeasures for improvement. PMID:29271947

The variance needed to accurately describe jump height from vertical ground reaction force data.

PubMed

Richter, Chris; McGuinness, Kevin; O'Connor, Noel E; Moran, Kieran

2014-12-01

In functional principal component analysis (fPCA) a threshold is chosen to define the number of retained principal components, which corresponds to the amount of preserved information. A variety of thresholds have been used in previous studies and the chosen threshold is often not evaluated. The aim of this study is to identify the optimal threshold that preserves the information needed to describe a jump height accurately utilizing vertical ground reaction force (vGRF) curves. To find an optimal threshold, a neural network was used to predict jump height from vGRF curve measures generated using different fPCA thresholds. The findings indicate that a threshold from 99% to 99.9% (6-11 principal components) is optimal for describing jump height, as these thresholds generated significantly lower jump height prediction errors than other thresholds.

Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy TOPSIS: A Case Study from 30 Provinces, China.

PubMed

Liang, Xuedong; Liu, Canmian; Li, Zhi

2017-12-22

In connection with the sustainable development of scenic spots, this paper, with consideration of resource conditions, economic benefits, auxiliary industry scale and ecological environment, establishes a comprehensive measurement model of the sustainable capacity of scenic spots; optimizes the index system by principal components analysis to extract principal components; assigns the weight of principal components by entropy method; analyzes the sustainable capacity of scenic spots in each province of China comprehensively in combination with TOPSIS method and finally puts forward suggestions aid decision-making. According to the study, this method provides an effective reference for the study of the sustainable development of scenic spots and is very significant for considering the sustainable development of scenic spots and auxiliary industries to establish specific and scientific countermeasures for improvement.

Model-free fMRI group analysis using FENICA.

PubMed

Schöpf, V; Windischberger, C; Robinson, S; Kasess, C H; Fischmeister, F PhS; Lanzenberger, R; Albrecht, J; Kleemann, A M; Kopietz, R; Wiesmann, M; Moser, E

2011-03-01

Exploratory analysis of functional MRI data allows activation to be detected even if the time course differs from that which is expected. Independent Component Analysis (ICA) has emerged as a powerful approach, but current extensions to the analysis of group studies suffer from a number of drawbacks: they can be computationally demanding, results are dominated by technical and motion artefacts, and some methods require that time courses be the same for all subjects or that templates be defined to identify common components. We have developed a group ICA (gICA) method which is based on single-subject ICA decompositions and the assumption that the spatial distribution of signal changes in components which reflect activation is similar between subjects. This approach, which we have called Fully Exploratory Network Independent Component Analysis (FENICA), identifies group activation in two stages. ICA is performed on the single-subject level, then consistent components are identified via spatial correlation. Group activation maps are generated in a second-level GLM analysis. FENICA is applied to data from three studies employing a wide range of stimulus and presentation designs. These are an event-related motor task, a block-design cognition task and an event-related chemosensory experiment. In all cases, the group maps identified by FENICA as being the most consistent over subjects correspond to task activation. There is good agreement between FENICA results and regions identified in prior GLM-based studies. In the chemosensory task, additional regions are identified by FENICA and temporal concatenation ICA that we show is related to the stimulus, but exhibit a delayed response. FENICA is a fully exploratory method that allows activation to be identified without assumptions about temporal evolution, and isolates activation from other sources of signal fluctuation in fMRI. It has the advantage over other gICA methods that it is computationally undemanding, spotlights components relating to activation rather than artefacts, allows the use of familiar statistical thresholding through deployment of a higher level GLM analysis and can be applied to studies where the paradigm is different for all subjects. Copyright © 2010 Elsevier Inc. All rights reserved.

Internet Search Patterns of Human Immunodeficiency Virus and the Digital Divide in the Russian Federation: Infoveillance Study

PubMed Central

Quinn, Casey; Hercz, Daniel; Gillespie, James A

2013-01-01

Background Human immunodeficiency virus (HIV) is a serious health problem in the Russian Federation. However, the true scale of HIV in Russia has long been the subject of considerable debate. Using digital surveillance to monitor diseases has become increasingly popular in high income countries. But Internet users may not be representative of overall populations, and the characteristics of the Internet-using population cannot be directly ascertained from search pattern data. This exploratory infoveillance study examined if Internet search patterns can be used for disease surveillance in a large middle-income country with a dispersed population. Objective This study had two main objectives: (1) to validate Internet search patterns against national HIV prevalence data, and (2) to investigate the relationship between search patterns and the determinants of Internet access. Methods We first assessed whether online surveillance is a valid and reliable method for monitoring HIV in the Russian Federation. Yandex and Google both provided tools to study search patterns in the Russian Federation. We evaluated the relationship between both Yandex and Google aggregated search patterns and HIV prevalence in 2011 at national and regional tiers. Second, we analyzed the determinants of Internet access to determine the extent to which they explained regional variations in searches for the Russian terms for “HIV” and “AIDS”. We sought to extend understanding of the characteristics of Internet searching populations by data matching the determinants of Internet access (age, education, income, broadband access price, and urbanization ratios) and searches for the term “HIV” using principal component analysis (PCA). Results We found generally strong correlations between HIV prevalence and searches for the terms “HIV” and “AIDS”. National correlations for Yandex searches for “HIV” were very strongly correlated with HIV prevalence (Spearman rank-order coefficient [rs]=.881, P≤.001) and strongly correlated for “AIDS” (rs=.714, P≤.001). The strength of correlations varied across Russian regions. National correlations in Google for the term “HIV” (rs=.672, P=.004) and “AIDS” (rs=.584, P≤.001) were weaker than for Yandex. Second, we examined the relationship between the determinants of Internet access and search patterns for the term “HIV” across Russia using PCA. At the national level, we found Principal Component 1 loadings, including age (-0.56), HIV search (-0.533), and education (-0.479) contributed 32% of the variance. Principal Component 2 contributed 22% of national variance (income, -0.652 and broadband price, -0.460). Conclusions This study contributes to the methodological literature on search patterns in public health. Based on our preliminary research, we suggest that PCA may be used to evaluate the relationship between the determinants of Internet access and searches for health problems beyond high-income countries. We believe it is in middle-income countries that search methods can make the greatest contribution to public health. PMID:24220250

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...

Multivariate analysis of light scattering spectra of liquid dairy products

NASA Astrophysics Data System (ADS)

Khodasevich, M. A.

2010-05-01

Visible light scattering spectra from the surface layer of samples of commercial liquid dairy products are recorded with a colorimeter. The principal component method is used to analyze these spectra. Vectors representing the samples of dairy products in a multidimensional space of spectral counts are projected onto a three-dimensional subspace of principal components. The magnitudes of these projections are found to depend on the type of dairy product.

WALLY 1 ...A large, principal components regression program with varimax rotation of the factor weight matrix

Treesearch

James R. Wallis

1965-01-01

Written in Fortran IV and MAP, this computer program can handle up to 120 variables, and retain 40 principal components. It can perform simultaneous regression of up to 40 criterion variables upon the varimax rotated factor weight matrix. The columns and rows of all output matrices are labeled by six-character alphanumeric names. Data input can be from punch cards or...

Dihedral angle principal component analysis of molecular dynamics simulations.

PubMed

Altis, Alexandros; Nguyen, Phuong H; Hegger, Rainer; Stock, Gerhard

2007-06-28

It has recently been suggested by Mu et al. [Proteins 58, 45 (2005)] to use backbone dihedral angles instead of Cartesian coordinates in a principal component analysis of molecular dynamics simulations. Dihedral angles may be advantageous because internal coordinates naturally provide a correct separation of internal and overall motion, which was found to be essential for the construction and interpretation of the free energy landscape of a biomolecule undergoing large structural rearrangements. To account for the circular statistics of angular variables, a transformation from the space of dihedral angles {phi(n)} to the metric coordinate space {x(n)=cos phi(n),y(n)=sin phi(n)} was employed. To study the validity and the applicability of the approach, in this work the theoretical foundations underlying the dihedral angle principal component analysis (dPCA) are discussed. It is shown that the dPCA amounts to a one-to-one representation of the original angle distribution and that its principal components can readily be characterized by the corresponding conformational changes of the peptide. Furthermore, a complex version of the dPCA is introduced, in which N angular variables naturally lead to N eigenvalues and eigenvectors. Applying the methodology to the construction of the free energy landscape of decaalanine from a 300 ns molecular dynamics simulation, a critical comparison of the various methods is given.

Dihedral angle principal component analysis of molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Altis, Alexandros; Nguyen, Phuong H.; Hegger, Rainer; Stock, Gerhard

2007-06-01

It has recently been suggested by Mu et al. [Proteins 58, 45 (2005)] to use backbone dihedral angles instead of Cartesian coordinates in a principal component analysis of molecular dynamics simulations. Dihedral angles may be advantageous because internal coordinates naturally provide a correct separation of internal and overall motion, which was found to be essential for the construction and interpretation of the free energy landscape of a biomolecule undergoing large structural rearrangements. To account for the circular statistics of angular variables, a transformation from the space of dihedral angles {φn} to the metric coordinate space {xn=cosφn,yn=sinφn} was employed. To study the validity and the applicability of the approach, in this work the theoretical foundations underlying the dihedral angle principal component analysis (dPCA) are discussed. It is shown that the dPCA amounts to a one-to-one representation of the original angle distribution and that its principal components can readily be characterized by the corresponding conformational changes of the peptide. Furthermore, a complex version of the dPCA is introduced, in which N angular variables naturally lead to N eigenvalues and eigenvectors. Applying the methodology to the construction of the free energy landscape of decaalanine from a 300ns molecular dynamics simulation, a critical comparison of the various methods is given.

The rate of change in declining steroid hormones: a new parameter of healthy aging in men?

PubMed

Walther, Andreas; Philipp, Michel; Lozza, Niclà; Ehlert, Ulrike

2016-09-20

Research on healthy aging in men has increasingly focused on age-related hormonal changes. Testosterone (T) decline is primarily investigated, while age-related changes in other sex steroids (dehydroepiandrosterone [DHEA], estradiol [E2], progesterone [P]) are mostly neglected. An integrated hormone parameter reflecting aging processes in men has yet to be identified. 271 self-reporting healthy men between 40 and 75 provided both psychometric data and saliva samples for hormone analysis. Correlation analysis between age and sex steroids revealed negative associations for the four sex steroids (T, DHEA, E2, and P). Principal component analysis including ten salivary analytes identified a principal component mainly unifying the variance of the four sex steroid hormones. Subsequent principal component analysis including the four sex steroids extracted the principal component of declining steroid hormones (DSH). Moderation analysis of the association between age and DSH revealed significant moderation effects for psychosocial factors such as depression, chronic stress and perceived general health. In conclusion, these results provide further evidence that sex steroids decline in aging men and that the integrated hormone parameter DSH and its rate of change can be used as biomarkers for healthy aging in men. Furthermore, the negative association of age and DSH is moderated by psychosocial factors.

The rate of change in declining steroid hormones: a new parameter of healthy aging in men?

PubMed Central

Walther, Andreas; Philipp, Michel; Lozza, Niclà; Ehlert, Ulrike

2016-01-01

Research on healthy aging in men has increasingly focused on age-related hormonal changes. Testosterone (T) decline is primarily investigated, while age-related changes in other sex steroids (dehydroepiandrosterone [DHEA], estradiol [E2], progesterone [P]) are mostly neglected. An integrated hormone parameter reflecting aging processes in men has yet to be identified. 271 self-reporting healthy men between 40 and 75 provided both psychometric data and saliva samples for hormone analysis. Correlation analysis between age and sex steroids revealed negative associations for the four sex steroids (T, DHEA, E2, and P). Principal component analysis including ten salivary analytes identified a principal component mainly unifying the variance of the four sex steroid hormones. Subsequent principal component analysis including the four sex steroids extracted the principal component of declining steroid hormones (DSH). Moderation analysis of the association between age and DSH revealed significant moderation effects for psychosocial factors such as depression, chronic stress and perceived general health. In conclusion, these results provide further evidence that sex steroids decline in aging men and that the integrated hormone parameter DSH and its rate of change can be used as biomarkers for healthy aging in men. Furthermore, the negative association of age and DSH is moderated by psychosocial factors. PMID:27589836

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 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.

Relationship between regional population and healthcare delivery in Japan.

PubMed

Niga, Takeo; Mori, Maiko; Kawahara, Kazuo

2016-01-01

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

Performance evaluation of PCA-based spike sorting algorithms.

PubMed

Adamos, Dimitrios A; Kosmidis, Efstratios K; Theophilidis, George

2008-09-01

Deciphering the electrical activity of individual neurons from multi-unit noisy recordings is critical for understanding complex neural systems. A widely used spike sorting algorithm is being evaluated for single-electrode nerve trunk recordings. The algorithm is based on principal component analysis (PCA) for spike feature extraction. In the neuroscience literature it is generally assumed that the use of the first two or most commonly three principal components is sufficient. We estimate the optimum PCA-based feature space by evaluating the algorithm's performance on simulated series of action potentials. A number of modifications are made to the open source nev2lkit software to enable systematic investigation of the parameter space. We introduce a new metric to define clustering error considering over-clustering more favorable than under-clustering as proposed by experimentalists for our data. Both the program patch and the metric are available online. Correlated and white Gaussian noise processes are superimposed to account for biological and artificial jitter in the recordings. We report that the employment of more than three principal components is in general beneficial for all noise cases considered. Finally, we apply our results to experimental data and verify that the sorting process with four principal components is in agreement with a panel of electrophysiology experts.

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

PubMed

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

2016-03-15

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

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

PubMed Central

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

2012-01-01

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

Comparison of behavioral effects of the NMDA receptor channel blockers memantine and ketamine in rats

PubMed Central

Kotermanski, Shawn E.; Johnson, Jon W.; Thiels, Edda

2013-01-01

Memantine and ketamine block N-methyl-D-aspartate (NMDA) receptors with similar affinity and kinetics, yet their behavioral consequences differ: e.g., memantine is used to alleviate symptoms of Alzheimer’s disease, whereas ketamine reproduces symptoms of schizophrenia. The two drugs exhibit different pharmacokinetics, which may play a principal role in their differential behavioral effects. To gain insight into the drugs’ behavioral consequences, we treated adult male rats acutely with varying doses (0–40 mg/kg i.p.) of memantine or ketamine and assessed exploratory behavior and spatial working memory. To examine the importance of pharmacokinetics, we assessed behavior either 15 or 45 min after drug administration. Both drugs decreased ambulation, fine movements, and rearing at the beginning of the exploratory activity test; however, at the end of the test, high doses of only memantine increased ambulation and fine movements. High doses of both drugs disrupted spontaneous alternation, a measure of working memory, but high doses of only memantine elicited perseverative behavior. Surprisingly, ketamine’s effects were influenced by the delay between drug administration and testing no more frequently than were mematine’s. Our findings show that, regardless of test delay, memantine and ketamine evoke similar behavioral effects at lower doses, consistent with NMDA receptors being both drugs’ principal site of action, but can have divergent effects at higher doses. Our results suggest that the divergence of mematine’s and ketamine’s behavioral consequences is likely to result from differences in mechanisms of NMDA receptor antagonism or actions at other receptors. PMID:23665480

Psychometric properties of the Persian version of Social Adaptation Self-evaluation Scale in community-dwelling older adults.

PubMed

Farokhnezhad Afshar, Pouya; Foroughan, Mahshid; Vedadhir, AbouAli; Ghazi Tabatabaie, Mahmood

2017-01-01

The Social Adaptation Self-evaluation Scale (SASS) is used to measure social function and social motivation in depressed patients. There is little attention to social function in the treatment of depression. The aim of this study was to assess the validity and reliability of the Persian version of SASS (P-SASS) for older adults. This is a cross-sectional and methodological study. The participants were 550 community-dwelling older adults living in Tehran who were selected randomly from the primary health care centers. To assess the psychometric properties of SASS, we first did translation and cross-cultural adjustment on SASS and then used P-SASS and the Geriatric Depression Scale (GDS) for gathering data. A number of analyses, including Pearson's correlation, exploratory factor analysis, and Cronbach's α , and receiver operating characteristic curve were used to manage the data with the IBM SPSS Statistics V.22. The mean age of the participants was 66.09±6.67 years, and 58.9% of them were male. The Cronbach's α was 0.97. The test-retest reliability correlation coefficient was 0.78. Principal component analysis showed that P-SASS consists of two components. P-SASS score showed a significant negative correlation with GDS ( r =-0.91, P <0.01), which suggests good convergent validity. The P-SASS cutoff point was 28 (sensitivity: 0.97 and specificity: 0.94). P-SASS has good reliability and validity for older adults. So, it can be considered as an appropriate tool to evaluate the social function and social motivation of older persons with and without depression.

Bar and restaurant workers' attitudes towards Norway's comprehensive smoking ban: a growth curve analysis.

PubMed

Braverman, Marc T; Aarø, Leif Edvard; Bontempo, Daniel E; Hetland, Jørn

2010-06-01

Norway passed legislation banning smoking in restaurants, bars and other public spaces in 2004. This study tracks changes in hospitality workers' attitudes towards Norway's ban over three time points, using growth modelling analysis to examine predictors of attitude change. Participants were a national sample of 1525 bar and restaurant workers. Surveys were conducted, by phone or internet, one month before the ban's implementation and at 4 and 12 months thereafter. Exploratory principal components analysis of nine survey items revealed one primary attitude component. A latent growth model was fitted to the data to examine trajectories of attitude change and individual differences in rate of change. Respondents supported the ban before implementation and increased support at 4 months (p=0.021) and again at 12 months (p=0.001). Concern for one's job followed a quadratic trend, increasing at 4 months and decreasing at 12 months (p<0.001). All demographic categories were associated with attitude increase; rate of increase was greater for females than males. Two within-person variables--change in smoking status and change in job concern--strongly predicted (p<0.001) respondents' deviations from their predicted group trajectories, explaining over 70% of residual between-person slope variance. Norway's hospitality workers increased their support of the ban over its first year. The strong influence of the within-person variables leads to two primary policy recommendations. First, support should be provided to assist cessation efforts and prevent relapse. Second, informational campaigns should inform hospitality workers about evidence that smoking bans are not economic threats to the industry.

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

PubMed

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

2014-03-01

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

Development and validation of an Infertility Stigma Scale for Chinese women.

PubMed

Fu, Bing; Qin, Nan; Cheng, Li; Tang, Guanxiu; Cao, Yi; Yan, Chunli; Huang, Xin; Yan, Pingping; Zhu, Shujuan; Lei, Jun

2015-07-01

To develop and validate a scale of stigma for infertile Chinese women. Infertile women admitted to the Xiangya Hospital, the Second Xiangya Hospital, and the Third Xiangya Hospital of Central South University for treatment were approached to participate in this study. The Infertility Stigma Scale (ISS) development involved: [1] item generation based on literature, interview (experts/patients: N=5/N=20) and related scale; [2] pre-test questionnaire formation with both experts' ratings (N=9) and infertile women's feedbacks (N=30); [3] the component structure assessed by principal components analysis with varimax rotation (N=334); [4] convergent validity assessed with Social Support Rating scale, Self-Esteem scale, Family APGAR Index (N=334); and [5] reliability identified by internal consistency Cronbach's α (N=334), split-half reliability (N=334), test-retest reliability (N=20). This study yielded a 27-item ISS with 4 factors (self-devaluation, social withdrawal, public stigma, and family stigma). Exploratory factor analysis indicated that these 4 factors accounted for 58.17% of total variances. The Cronbach's α, split-half coefficient and test-retest correlation coefficient for the whole scale was 0.94, 0.90, and 0.91, respectively. The associations of the ISS with other measures suggested good convergent validity. The Content Validity Index (CVI) was 0.92. The ISS appears to be a reliable and valid measure to assess levels of stigma experienced by infertile Chinese women. It may be a useful tool to help identify infertile women at greater risks of distress. Copyright © 2014 Elsevier Inc. All rights reserved.

Exploratory factor analysis of the Research and Development Culture Index among qualified nurses.

PubMed

Watson, Bill; Clarke, Charlotte; Swallow, Vera; Forster, Stewart

2005-10-01

This paper presents the exploratory factor analysis of a rating instrument for assessing the strength of organizational Research and Development (R&D) culture. Despite nursing's limited research capacity, the discipline is capitalizing upon opportunities to become involved in research and is making strong progress. Within the context of the debate on nursing research capacity, the R&D Culture Index was developed as a means of appraising R&D culture within health care organizations. Factor analysis was carried out on data collected from 485 nursing staff. The method of extraction was Principal Components Analysis with oblique rotation. The Index was developed from the findings of qualitative research conducted with NHS staff. Eighteen items, encompassing the main themes from the data, were initially included in the Index. This pilot instrument was distributed to nursing staff within three different types of NHS Trust. Factor analysis resulted in rejection of two items and the analysis was repeated using the remaining 16 items. Three latent factors were extracted accounting for 58.0% of the variance in the data. The factors were: R&D Support, describing the perceived support within the working environment for R&D activity; Personal R&D Skills and Aptitude, describing an individual's perception of their ability towards R&D activity; and Personal R&D Intention, describing an individual's willingness to engage in R&D activity. Each factor had good internal reliability, as did the overall index. The R&D Culture Index provides an efficient means of assessing the strength of an organization's R&D culture in a way that captures the role of the individual practitioner and the organizational environment. These findings suggest that the continuing promotion of R&D within health care organizations is dependent upon a multi-faceted approach that addresses the learning needs of the organization as well as those of the individual practitioners.