Treatment Components and Their Relationships with Drug and Alcohol Abstinence.

ERIC Educational Resources Information Center

Orwin, Rob; Ellis, Bruce

This study evaluates the effect of treatment components through a secondary analysis of data from the National Treatment Improvement Evaluation Study (NTIES). The study examines the relationship between treatment components, client-level factors, and treatment outcomes, and how these relationships vary by treatment modality. It seeks to understand…

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

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

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

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

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

DOE PAGES

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

2017-12-28

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

ENVIRONMENTAL ANALYSIS OF GASOLINE BLENDING COMPONENTS THROUGH THEIR LIFE CYCLE

EPA Science Inventory

The purpose of this study is to access the contribution of the three major gasoline blending components to the potential environmental impacts (PEI), which are the reformate, alkylate and cracked gasoline. This study accounts for losses of the gasoline blending components due to...

ENVIRONMENTAL ANALYSIS OF GASOLINE BLENDING COMPONENTS THROUGH THEIR LIFE CYCLE

EPA Science Inventory

The purpose of this study is to assess the contribution of the three major gasoline blending components to the potential environmental impacts (PEI), which are the reformate, alkylate and cracked gasoline. This study accounts for losses of the gasoline blending components due to ...

Computational Fatigue Life Analysis of Carbon Fiber Laminate

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

A Study on Components of Internal Control-Based Administrative System in Secondary Schools

ERIC Educational Resources Information Center

Montri, Paitoon; Sirisuth, Chaiyuth; Lammana, Preeda

2015-01-01

The aim of this study was to study the components of the internal control-based administrative system in secondary schools, and make a Confirmatory Factor Analysis (CFA) to confirm the goodness of fit of empirical data and component model that resulted from the CFA. The study consisted of three steps: 1) studying of principles, ideas, and theories…

Understanding Oral Reading Fluency among Adults with Low Literacy: Dominance Analysis of Contributing Component Skills

ERIC Educational Resources Information Center

Mellard, Daryl F.; Anthony, Jason L.; Woods, Kari L.

2012-01-01

This study extends the literature on the component skills involved in oral reading fluency. Dominance analysis was applied to assess the relative importance of seven reading-related component skills in the prediction of the oral reading fluency of 272 adult literacy learners. The best predictors of oral reading fluency when text difficulty was…

Accuracy of the Parallel Analysis Procedure with Polychoric Correlations

ERIC Educational Resources Information Center

Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah

2009-01-01

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…

Probabilistic evaluation of SSME structural components

NASA Astrophysics Data System (ADS)

Rajagopal, K. R.; Newell, J. F.; Ho, H.

1991-05-01

The application is described of Composite Load Spectra (CLS) and Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) family of computer codes to the probabilistic structural analysis of four Space Shuttle Main Engine (SSME) space propulsion system components. These components are subjected to environments that are influenced by many random variables. The applications consider a wide breadth of uncertainties encountered in practice, while simultaneously covering a wide area of structural mechanics. This has been done consistent with the primary design requirement for each component. The probabilistic application studies are discussed using finite element models that have been typically used in the past in deterministic analysis studies.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

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

2008-05-12

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

Selection of independent components based on cortical mapping of electromagnetic activity

NASA Astrophysics Data System (ADS)

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

2012-10-01

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

Principal components analysis of the Neurobehavioral Symptom Inventory in a nonclinical civilian sample.

PubMed

Sullivan, Karen A; Lurie, Janine K

2017-01-01

The study examined the component structure of the Neurobehavioral Symptom Inventory (NSI) under five different models. The evaluated models comprised the full NSI (NSI-22) and the NSI-20 (NSI minus two orphan items). A civilian nonclinical sample was used. The 575 volunteers were predominantly university students who screened negative for mild TBI. The study design was cross-sectional, with questionnaires administered online. The main measure was the Neurobehavioral Symptom Inventory. Subscale, total and embedded validity scores were derived (the Validity-10, the LOW6, and the NIM5). In both models, the principal components analysis yielded two intercorrelated components (psychological and somatic/sensory) with acceptable internal consistency (alphas > 0.80). In this civilian nonclinical sample, the NSI had two underlying components. These components represent psychological and somatic/sensory neurobehavioral symptoms.

Comparing Independent Component Analysis with Principle Component Analysis in Detecting Alterations of Porphyry Copper Deposit (case Study: Ardestan Area, Central Iran)

NASA Astrophysics Data System (ADS)

Mahmoudishadi, S.; Malian, A.; Hosseinali, F.

2017-09-01

The image processing techniques in transform domain are employed as analysis tools for enhancing the detection of mineral deposits. The process of decomposing the image into important components increases the probability of mineral extraction. In this study, the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) has been evaluated for the visible and near-infrared (VNIR) and Shortwave infrared (SWIR) subsystems of ASTER data. Ardestan is located in part of Central Iranian Volcanic Belt that hosts many well-known porphyry copper deposits. This research investigated the propylitic and argillic alteration zones and outer mineralogy zone in part of Ardestan region. The two mentioned approaches were applied to discriminate alteration zones from igneous bedrock using the major absorption of indicator minerals from alteration and mineralogy zones in spectral rang of ASTER bands. Specialized PC components (PC2, PC3 and PC6) were used to identify pyrite and argillic and propylitic zones that distinguish from igneous bedrock in RGB color composite image. Due to the eigenvalues, the components 2, 3 and 6 account for 4.26% ,0.9% and 0.09% of the total variance of the data for Ardestan scene, respectively. For the purpose of discriminating the alteration and mineralogy zones of porphyry copper deposit from bedrocks, those mentioned percentages of data in ICA independent components of IC2, IC3 and IC6 are more accurately separated than noisy bands of PCA. The results of ICA method conform to location of lithological units of Ardestan region, as well.

Analysis of Extracted and Volatile Components in Blackstrap Molasses Feed as Candidate House Fly Attractants

DTIC Science & Technology

2007-01-01

found in this commodity. This conclusion is further supported by a study of sucrose pyrolysis products that listed furfural and 2-hydroxy-3-methyl-2...study that investigated the aroma compounds from citrus honey, and only furfural was found to be a major component in both sample matrices [40]. Analysis

Standardization and program effect analysis (Study 2.4). Volume 2: Equipment commonality analysis. [cost savings of using flight-proven components in designing spacecraft

NASA Technical Reports Server (NTRS)

Shiokari, T.

1975-01-01

The feasibility and cost savings of using flight-proven components in designing spacecraft were investigated. The components analyzed were (1) large space telescope, (2) stratospheric aerosol and gas equipment, (3) mapping mission, (4) solar maximum mission, and (5) Tiros-N. It is concluded that flight-proven hardware can be used with not-too-extensive modification, and significant savings can be realized. The cost savings for each component are presented.

The first report on transcriptome analysis of the venom gland of Iranian scorpion, Hemiscorpius lepturus.

PubMed

Kazemi-Lomedasht, Fatemeh; Khalaj, Vahid; Bagheri, Kamran Pooshang; Behdani, Mahdi; Shahbazzadeh, Delavar

2017-01-01

Hemiscorpius lepturus scorpion is one of the most venomous members of the Hemiscorpiidae family. H. lepturus is distributed in Iran, Iraq and Yemen. The prevalence and severity of scorpionism is high and health services are not able to control it. Scorpionism in Iran especially in the southern regions (Khuzestan, Sistan and Baluchestan, Hormozgan, Ilam) is one of the main health challenges. Due to the medical and health importance of scorpionism, the focus of various studies has been on the identification of H. lepturus venom components. Nevertheless, until now, only a few percent of H. lepturus venom components have been identified and there is no complete information about the venom components of H. lepturus. The current study reports transcriptome analysis of the venom gland of H. lepturus scorpion. Illumina Next Generation Sequencing results identified venom components of H. lepturus. When compared with other scorpion's venom, the venom of H. lepturus consists of mixtures of peptides, proteins and enzymes such as; phospholipases, metalloproteases, hyaluronidases, potassium channel toxins, calcium channel toxins, antimicrobial peptides (AMPs), venom proteins, venom toxins, allergens, La1-like peptides, proteases and scorpine-like peptides. Comparison of identified components of H. lepturus venom was carried out with venom components of reported scorpions and various identities and similarities between them were observed. With transcriptome analysis of H. lepturus venom unique sequences, coding venom components were investigated. Moreover, our study confirmed transcript expression of previously reported peptides; Hemitoxin, Hemicalcin and Hemilipin. The gene sequences of venom components were investigated employing transcriptome analysis of venom gland of H. lepturus. In summary, new bioactive molecules identified in this study, provide basis for venomics studies of scorpions of Hemiscorpiidae family and promises development of novel biotherapeutics. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-02-01

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

Valuing a Protected Tropical Forest: A Case Study in Madagascar

Treesearch

Randall Kramer; Mohan Munasinghe; Narendra Sharma; Evan Mercer; Priya Shyamsundar

1994-01-01

Economic analysis can provide useful infor­ mation for these difficult decisions. Of course, economic analysis should only constitute one component of the process of deciding whether to create a national park (other components would include sociopolitical and ecological considerations). Traditional economic cost-benefit analysis for national parks, how­ ever, is...

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.

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Function Invariant and Parameter Scale-Free Transformation Methods

ERIC Educational Resources Information Center

Bentler, P. M.; Wingard, Joseph A.

1977-01-01

A scale-invariant simple structure function of previously studied function components for principal component analysis and factor analysis is defined. First and second partial derivatives are obtained, and Newton-Raphson iterations are utilized. The resulting solutions are locally optimal and subjectively pleasing. (Author/JKS)

Textbooks Content Analysis of Social Studies and Natural Sciences of Secondary School Based on Emotional Intelligence Components

ERIC Educational Resources Information Center

Babaei, Bahare; Abdi, Ali

2014-01-01

The aim of this study is to analyze the content of social studies and natural sciences textbooks of the secondary school on the basis of the emotional intelligence components. In order to determine and inspect the emotional intelligence components all of the textbooks content (including texts, exercises, and illustrations) was examined based on…

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

PubMed

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

2018-05-11

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

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

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

2009-01-01

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

[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.

Rapidly differentiating grape seeds from different sources based on characteristic fingerprints using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics.

PubMed

Song, Yuqiao; Liao, Jie; Dong, Junxing; Chen, Li

2015-09-01

The seeds of grapevine (Vitis vinifera) are a byproduct of wine production. To examine the potential value of grape seeds, grape seeds from seven sources were subjected to fingerprinting using direct analysis in real time coupled with time-of-flight mass spectrometry combined with chemometrics. Firstly, we listed all reported components (56 components) from grape seeds and calculated the precise m/z values of the deprotonated ions [M-H](-) . Secondly, the experimental conditions were systematically optimized based on the peak areas of total ion chromatograms of the samples. Thirdly, the seven grape seed samples were examined using the optimized method. Information about 20 grape seed components was utilized to represent characteristic fingerprints. Finally, hierarchical clustering analysis and principal component analysis were performed to analyze the data. Grape seeds from seven different sources were classified into two clusters; hierarchical clustering analysis and principal component analysis yielded similar results. The results of this study lay the foundation for appropriate utilization and exploitation of grape seed samples. Due to the absence of complicated sample preparation methods and chromatographic separation, the method developed in this study represents one of the simplest and least time-consuming methods for grape seed fingerprinting. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

The relationship between metabolic syndrome, its components, and erectile dysfunction: a systematic review and a meta-analysis of observational studies.

PubMed

Besiroglu, Huseyin; Otunctemur, Alper; Ozbek, Emin

2015-06-01

The studies examining the association between metabolic syndrome (MetS), its components, and erectile dysfunction (ED) should be reevaluated to arrive at comprehensive results in this field. Our aim was to gather individual studies in order to achieve a more reliable conclusion regarding the relationship between MetS, its components, and ED. Three investigators searched the Pubmed-Medline and Embase databases using the key words "metabolic syndrome" and "erectile dysfunction." The individual studies were evaluated for selection of suitable studies. Eight studies that met all inclusion criteria were chosen, and a pooled analysis of odds ratio (ORs) between MetS and ED was calculated. The components of MetS to ED were also estimated. Eight observational studies with a total of 12,067 participants were examined. The overall analysis revealed a 2.6-fold increase in patients with MetS having ED (2.67[1.79-3.96]; P < 0.0001). All individual components of MetS except high-density lipoprotein level were also found to correlate with an increased prevalence of ED. Of those, fasting blood sugar was detected highest rate for ED with OR of 2.07 ([1.49-2.87]; P < 0.0001). Metabolic syndrome is associated with a high risk rate of ED, and patients with MetS should be informed about this association and encouraged to make lifestyle modifications to improve their general health and to limit cardiovascular risk as well as ED prevalence. However, manuscripts included in meta-analysis were observational studies that prohibits ascertainment of temporal associations and necessitates further prospective studies. © 2015 International Society for Sexual Medicine.

ENVIRONMENTAL ANALYSIS OF GASOLINE BLENDING COMPONENTS THROUGH THEIR LIFE CYCLE

EPA Science Inventory

The contributions of three major gasoline blending components (reformate, alkylate and cracked gasoline) to potential environmental impacts are assessed. This study estimates losses of the gasoline blending components due to evaporation and leaks through their life cycle, from pe...

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

The Utility of Job Dimensions Based on Form B of the Position Analysis Questionnaire (PAQ) in a Job Component Validation Model. Report No. 5.

ERIC Educational Resources Information Center

Marquardt, Lloyd D.; McCormick, Ernest J.

The study involved the use of a structured job analysis instrument called the Position Analysis Questionnaire (PAQ) as the direct basis for the establishment of the job component validity of aptitude tests (that is, a procedure for estimating the aptitude requirements for jobs strictly on the basis of job analysis data). The sample of jobs used…

[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.

Influence of running stride frequency in heart rate variability analysis during treadmill exercise testing.

PubMed

Bailón, Raquel; Garatachea, Nuria; de la Iglesia, Ignacio; Casajús, Jose Antonio; Laguna, Pablo

2013-07-01

The analysis and interpretation of heart rate variability (HRV) during exercise is challenging not only because of the nonstationary nature of exercise, the time-varying mean heart rate, and the fact that respiratory frequency exceeds 0.4 Hz, but there are also other factors, such as the component centered at the pedaling frequency observed in maximal cycling tests, which may confuse the interpretation of HRV analysis. The objectives of this study are to test the hypothesis that a component centered at the running stride frequency (SF) appears in the HRV of subjects during maximal treadmill exercise testing, and to study its influence in the interpretation of the low-frequency (LF) and high-frequency (HF) components of HRV during exercise. The HRV of 23 subjects during maximal treadmill exercise testing is analyzed. The instantaneous power of different HRV components is computed from the smoothed pseudo-Wigner-Ville distribution of the modulating signal assumed to carry information from the autonomic nervous system, which is estimated based on the time-varying integral pulse frequency modulation model. Besides the LF and HF components, the appearance is revealed of a component centered at the running SF as well as its aliases. The power associated with the SF component and its aliases represents 22±7% (median±median absolute deviation) of the total HRV power in all the subjects. Normalized LF power decreases as the exercise intensity increases, while normalized HF power increases. The power associated with the SF does not change significantly with exercise intensity. Consideration of the running SF component and its aliases is very important in HRV analysis since stride frequency aliases may overlap with LF and HF components.

Lexical and Indexical Conversational Components That Mediate Professional Noticing during Lesson Study

ERIC Educational Resources Information Center

Weiland Carter, Ingrid S.; Amador, Julie M.

2015-01-01

Previous research indicates that lesson study can support preservice teachers' abilities to professionally notice. This qualitative case study examined specific lexical and indexical conversational components of lesson study analysis meetings that afford or constrain elementary preservice teachers' incidences of professionally noticing students'…

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

PubMed

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

2017-01-01

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

A Cost-Utility Model of Care for Peristomal Skin Complications

PubMed Central

Inglese, Gary; Manson, Andrea; Townshend, Arden

2016-01-01

PURPOSE: The aim of this study was to evaluate the economic and humanistic implications of using ostomy components to prevent subsequent peristomal skin complications (PSCs) in individuals who experience an initial, leakage-related PSC event. DESIGN: Cost-utility analysis. METHODS: We developed a simple decision model to consider, from a payer's perspective, PSCs managed with and without the use of ostomy components over 1 year. The model evaluated the extent to which outcomes associated with the use of ostomy components (PSC events avoided; quality-adjusted life days gained) offset the costs associated with their use. RESULTS: Our base case analysis of 1000 hypothetical individuals over 1 year assumes that using ostomy components following a first PSC reduces recurrent events versus PSC management without components. In this analysis, component acquisition costs were largely offset by lower resource use for ostomy supplies (barriers; pouches) and lower clinical utilization to manage PSCs. The overall annual average resource use for individuals using components was about 6.3% ($139) higher versus individuals not using components. Each PSC event avoided yielded, on average, 8 additional quality-adjusted life days over 1 year. CONCLUSIONS: In our analysis, (1) acquisition costs for ostomy components were offset in whole or in part by the use of fewer ostomy supplies to manage PSCs and (2) use of ostomy components to prevent PSCs produced better outcomes (fewer repeat PSC events; more health-related quality-adjusted life days) over 1 year compared to not using components. PMID:26633166

Tibial component alignment and risk of loosening in unicompartmental knee arthroplasty: a radiographic and radiostereometric study.

PubMed

Barbadoro, P; Ensini, A; Leardini, A; d'Amato, M; Feliciangeli, A; Timoncini, A; Amadei, F; Belvedere, C; Giannini, S

2014-12-01

Unicompartmental knee arthroplasty (UKA) has shown a higher rate of revision compared with total knee arthroplasty. The success of UKA depends on prosthesis component alignment, fixation and soft tissue integrity. The tibial cut is the crucial surgical step. The hypothesis of the present study is that tibial component malalignment is correlated with its risk of loosening in UKA. This study was performed in twenty-three patients undergoing primary cemented unicompartmental knee arthroplasties. Translations and rotations of the tibial component and the maximum total point motion (MTPM) were measured using radiostereometric analysis at 3, 6, 12 and 24 months. Standard radiological evaluations were also performed immediately before and after surgery. Varus/valgus and posterior slope of the tibial component and tibial-femoral axes were correlated with radiostereometric micro-motion. A survival analysis was also performed at an average of 5.9 years by contacting patients by phone. Varus alignment of the tibial component was significantly correlated with MTPM, anterior tibial sinking, varus rotation and anterior and medial translations from radiostereometry. The posterior slope of the tibial component was correlated with external rotation. The survival rate at an average of 5.9 years was 89%. The two patients who underwent revision presented a tibial component varus angle of 10° for both. There is correlation between varus orientation of the tibial component and MTPM from radiostereometry in unicompartmental knee arthroplasties. Particularly, a misalignment in varus larger than 5° could lead to risk of loosening the tibial component. Prognostic studies-retrospective study, Level II.

RSA prediction of high failure rate for the uncoated Interax TKA confirmed by meta-analysis.

PubMed

Pijls, Bart G; Nieuwenhuijse, Marc J; Schoones, Jan W; Middeldorp, Saskia; Valstar, Edward R; Nelissen, Rob G H H

2012-04-01

In a previous radiostereometric (RSA) trial the uncoated, uncemented, Interax tibial components showed excessive migration within 2 years compared to HA-coated and cemented tibial components. It was predicted that this type of fixation would have a high failure rate. The purpose of this systematic review and meta-analysis was to investigate whether this RSA prediction was correct. We performed a systematic review and meta-analysis to determine the revision rate for aseptic loosening of the uncoated and cemented Interax tibial components. 3 studies were included, involving 349 Interax total knee arthroplasties (TKAs) for the comparison of uncoated and cemented fixation. There were 30 revisions: 27 uncoated and 3 cemented components. There was a 3-times higher revision rate for the uncoated Interax components than that for cemented Interax components (OR = 3; 95% CI: 1.4-7.2). This meta-analysis confirms the prediction of a previous RSA trial. The uncoated Interax components showed the highest migration and turned out to have the highest revision rate for aseptic loosening. RSA appears to enable efficient detection of an inferior design as early as 2 years postoperatively in a small group of patients.

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

PubMed

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

2017-09-11

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

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.

Deep overbite malocclusion: analysis of the underlying components.

PubMed

El-Dawlatly, Mostafa M; Fayed, Mona M Salah; Mostafa, Yehya A

2012-10-01

A deepbite malocclusion should not be approached as a disease entity; instead, it should be viewed as a clinical manifestation of underlying discrepancies. The aim of this study was to investigate the various skeletal and dental components of deep bite malocclusion, the significance of the contribution of each, and whether there are certain correlations between them. Dental and skeletal measurements were made on lateral cephalometric radiographs and study models of 124 patients with deepbite. These measurements were statistically analyzed. An exaggerated curve of Spee was the greatest shared dental component (78%), significantly higher than any other component (P = 0.0335). A decreased gonial angle was the greatest shared skeletal component (37.1%), highly significant compared with the other components (P = 0.0019). A strong positive correlation was found between the ramus/Frankfort horizontal angle and the gonial angle; weaker correlations were found between various components. An exaggerated curve of Spee and a decreased gonial angle were the greatest contributing components. This analysis of deepbite components could help clinicians design individualized mechanotherapies based on the underlying cause, rather than being biased toward predetermined mechanics when treating patients with a deepbite malocclusion. Copyright © 2012 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

[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.

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.

Hilbert-Huang transform analysis of dynamic and earthquake motion recordings

USGS Publications Warehouse

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

2003-01-01

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

A case study in nonconformance and performance trend analysis

NASA Technical Reports Server (NTRS)

Maloy, Joseph E.; Newton, Coy P.

1990-01-01

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

The contribution of aromatic components in Katsuobushi to preference formation and reinforcement effect.

PubMed

Amitsuka, Takahiko; Okamura, Maya; Mukuta, Kei; Shiibashi, Hiroko; Haraguchi, Kenji; Saito, Tsukasa; Inoue, Kazuo; Fushiki, Tohru

2017-08-01

Katsuodashi, a dried bonito broth, is very basic and indispensable in Japanese cuisine and contains taste-exhibiting components and unique aroma. We previously reported that its unique aroma contributes to the preference and reinforcement effect associated with dried bonito. This study aims to elucidate the contribution of aromatic components in Katsuobushi to preference formation and reinforcement effect. Volatile components obtained from dried bonito were fractionated and the fractions were subjected to two-bottle choice test. The fractionation test suggested that the component responsible for the preference is not one but comprises multiple components. In the GC-MS analysis/reconstruction test, solution with aromatic flavor narrowed down to 125 compounds had preference, and also had reinforcement effect. Moreover, GC-MS-olfactometry analysis narrowed down the candidate components to 28 out of 125. Mice showed preference for the test solution with aromatic flavor reconstructed with 28 components but did not show reinforcement behavior.

Aggregate blood pressure responses to serial dietary sodium and potassium intervention: defining responses using independent component analysis.

PubMed

Chen, Gengsheng; de las Fuentes, Lisa; Gu, Chi C; He, Jiang; Gu, Dongfeng; Kelly, Tanika; Hixson, James; Jacquish, Cashell; Rao, D C; Rice, Treva K

2015-06-20

Hypertension is a complex trait that often co-occurs with other conditions such as obesity and is affected by genetic and environmental factors. Aggregate indices such as principal components among these variables and their responses to environmental interventions may represent novel information that is potentially useful for genetic studies. In this study of families participating in the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) Study, blood pressure (BP) responses to dietary sodium interventions are explored. Independent component analysis (ICA) was applied to 20 variables indexing obesity and BP measured at baseline and during low sodium, high sodium and high sodium plus potassium dietary intervention periods. A "heat map" protocol that classifies subjects based on risk for hypertension is used to interpret the extracted components. ICA and heat map suggest four components best describe the data: (1) systolic hypertension, (2) general hypertension, (3) response to sodium intervention and (4) obesity. The largest heritabilities are for the systolic (64%) and general hypertension (56%) components. There is a pattern of higher heritability for the component response to intervention (40-42%) as compared to those for the traditional intervention responses computed as delta scores (24%-40%). In summary, the present study provides intermediate phenotypes that are heritable. Using these derived components may prove useful in gene discovery applications.

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…

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

ERIC Educational Resources Information Center

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

2007-01-01

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

Learning Principal Component Analysis by Using Data from Air Quality Networks

ERIC Educational Resources Information Center

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

2017-01-01

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

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…

SCADA alarms processing for wind turbine component failure detection

NASA Astrophysics Data System (ADS)

Gonzalez, E.; Reder, M.; Melero, J. J.

2016-09-01

Wind turbine failure and downtime can often compromise the profitability of a wind farm due to their high impact on the operation and maintenance (O&M) costs. Early detection of failures can facilitate the changeover from corrective maintenance towards a predictive approach. This paper presents a cost-effective methodology to combine various alarm analysis techniques, using data from the Supervisory Control and Data Acquisition (SCADA) system, in order to detect component failures. The approach categorises the alarms according to a reviewed taxonomy, turning overwhelming data into valuable information to assess component status. Then, different alarms analysis techniques are applied for two purposes: the evaluation of the SCADA alarm system capability to detect failures, and the investigation of the relation between components faults being followed by failure occurrences in others. Various case studies are presented and discussed. The study highlights the relationship between faulty behaviour in different components and between failures and adverse environmental conditions.

Global Analysis Reveals the Complexity of the Human Glomerular Extracellular Matrix

PubMed Central

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

2014-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

Bradonjic, Milan; Hagberg, Aric; Hengartner, Nick

We analyze component evolution in general random intersection graphs (RIGs) and give conditions on existence and uniqueness of the giant component. Our techniques generalize the existing methods for analysis on component evolution in RIGs. That is, we analyze survival and extinction properties of a dependent, inhomogeneous Galton-Watson branching process on general RIGs. Our analysis relies on bounding the branching processes and inherits the fundamental concepts from the study on component evolution in Erdos-Renyi graphs. The main challenge becomes from the underlying structure of RIGs, when the number of offsprings follows a binomial distribution with a different number of nodes andmore » different rate at each step during the evolution. RIGs can be interpreted as a model for large randomly formed non-metric data sets. Besides the mathematical analysis on component evolution, which we provide in this work, we perceive RIGs as an important random structure which has already found applications in social networks, epidemic networks, blog readership, or wireless sensor networks.« less

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.

Psychometric characteristics of the Mobility Inventory in a longitudinal study of anxiety disorders: Replicating and exploring a three component solution

PubMed Central

Rodriguez, Benjamin F.; Pagano, Maria E.; Keller, Martin B.

2008-01-01

Psychometric characteristics of the Mobility Inventory (MI) were examined in 216 outpatients diagnosed with panic disorder with agoraphobia participating in a longitudinal study of anxiety disorders. An exploratory principal components analysis replicated a three-component solution for the MI reported in prior studies, with components corresponding to avoidance of public spaces, avoidance of enclosed spaces, and avoidance of open spaces. Correlational analyses suggested that the components tap unique but related areas of avoidance that were remarkably stable across periods of 1,3, and 5 years between administrations. Implications of these results for future studies of agoraphobia are discussed. PMID:17079112

Robust LOD scores for variance component-based linkage analysis.

PubMed

Blangero, J; Williams, J T; Almasy, L

2000-01-01

The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.

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

PubMed Central

Gürgen, Fikret; Gürgen, Nurgül

2003-01-01

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

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

NASA Technical Reports Server (NTRS)

Olson, Erik D.

2016-01-01

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

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

PubMed

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

2008-09-01

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

Kinetics and mechanism of the oxidation process of two-component Fe-Al alloys

NASA Technical Reports Server (NTRS)

Przewlocka, H.; Siedlecka, J.

1982-01-01

The oxidation process of two-component Fe-Al alloys containing up to 7.2% Al and from 18 to 30% Al was studied. Kinetic measurements were conducted using the isothermal gravimetric method in the range of 1073-1223 K and 1073-1373 K for 50 hours. The methods used in studies of the mechanism of oxidation included: X-ray microanalysis, X-ray structural analysis, metallographic analysis and marker tests.

Geographic distribution of suicide and railway suicide in Belgium, 2008-2013: a principal component analysis.

PubMed

Strale, Mathieu; Krysinska, Karolina; Overmeiren, Gaëtan Van; Andriessen, Karl

2017-06-01

This study investigated the geographic distribution of suicide and railway suicide in Belgium over 2008--2013 on local (i.e., district or arrondissement) level. There were differences in the regional distribution of suicide and railway suicides in Belgium over the study period. Principal component analysis identified three groups of correlations among population variables and socio-economic indicators, such as population density, unemployment, and age group distribution, on two components that helped explaining the variance of railway suicide at a local (arrondissement) level. This information is of particular importance to prevent suicides in high-risk areas on the Belgian railway network.

Warthin tumor--morphological study of the stromal compartment.

PubMed

Dăguci, Luminiţa; Simionescu, Cristiana; Stepan, A; Munteanu, Cristina; Dăguci, C; Bătăiosu, Marilena

2011-01-01

Warthin tumor is the second most common benign tumors of the parotid gland, after pleomorphic adenoma. Our study was performed on 21 cases with Warthin tumor diagnosed between 2005-2010, which were analyzed clinically, histologically and immunohistochemically, using anti-CD20 and anti-CD45RO antibodies. The analysis of age distribution within the investigated cases indicated that Warthin tumor incidence is increasing in the seventh decade of life, most patients being male (M/F 5/2). Histopathological, the analysis report of stroma÷parenchyma in 14 cases revealed a balanced distribution of the two components, in four cases, the epithelial component was predominant and in three cases, the stromal component was predominant. Immunohistochemical study for the two specific lymphocyte proliferation markers indicated positivity for both epithelial component and stroma. Cell layout of CD45RO and CD20cy at the level of lymphoid stroma had a similar pattern with normal or reactive lymph nodes.

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

PubMed

Park, Gi-Pyo

2014-08-01

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

Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis

NASA Astrophysics Data System (ADS)

Dion, J.-L.; Tawfiq, I.; Chevallier, G.

2012-01-01

This work is a contribution in the field of Operational Modal Analysis to identify the modal parameters of mechanical structures using only measured responses. The study deals with structural responses coupled with harmonic components amplitude and frequency modulated in a short range, a common combination for mechanical systems with engines and other rotating machines in operation. These harmonic components generate misleading data interpreted erroneously by the classical methods used in OMA. The present work attempts to differentiate maxima in spectra stemming from harmonic components and structural modes. The detection method proposed is based on the so-called Optimized Spectral Kurtosis and compared with others definitions of Spectral Kurtosis described in the literature. After a parametric study of the method, a critical study is performed on numerical simulations and then on an experimental structure in operation in order to assess the method's performance.

Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error

PubMed Central

Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee

2017-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Analysis of Component of Aggression in the Stories of Elementary School Aggressive Children

ERIC Educational Resources Information Center

Chamandar, Fateme; Jabbari, D. Susan

2017-01-01

The purpose of this study is the content analysis of children's stories based on the components of aggression. Participants are 66 elementary school students (16 girls and 50 boys) selected from fourth and fifth grades, using the Relational and Overt Aggression Questionnaire; completed by the teachers. Draw a Story Test (Silver, 2005) is…

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.

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

PubMed

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

2017-10-01

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

Fast characterization of cheeses by dynamic headspace-mass spectrometry.

PubMed

Pérès, Christophe; Denoyer, Christian; Tournayre, Pascal; Berdagué, Jean-Louis

2002-03-15

This study describes a rapid method to characterize cheeses by analysis of their volatile fraction using dynamic headspace-mass spectrometry. Major factors governing the extraction and concentration of the volatile components were first studied. These components were extracted from the headspace of the cheeses in a stream of helium and concentrated on a Tenax TA trap. They were then desorbed by heating and injected directly into the source of a mass spectrometer via a short deactivated silica transfer line. The mass spectra of the mixture of volatile components were considered as fingerprints of the analyzed substances. Forward stepwise factorial discriminant analysis afforded a limited number of characteristic mass fragments that allowed a good classification of the batches of cheeses studied.

Measurement analysis of two radials with a common-origin point and its application.

PubMed

Liu, Zhenyao; Yang, Jidong; Zhu, Weiwei; Zhou, Shang; Tan, Xuanping

2017-08-01

In spectral analysis, a chemical component is usually identified by its characteristic spectra, especially the peaks. If two components have overlapping spectral peaks, they are generally considered to be indiscriminate in current analytical chemistry textbooks and related literature. However, if the intensities of the overlapping major spectral peaks are additive, and have different rates of change with respect to variations in the concentration of the individual components, a simple method, named the 'common-origin ray', for the simultaneous determination of two components can be established. Several case studies highlighting its applications are presented. Copyright © 2017 John Wiley & Sons, Ltd.

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

Science.gov Websites

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

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

Science.gov Websites

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

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

NASA Technical Reports Server (NTRS)

Scriven, M. C.

1979-01-01

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

Specialized data analysis of SSME and advanced propulsion system vibration measurements

NASA Technical Reports Server (NTRS)

Coffin, Thomas; Swanson, Wayne L.; Jong, Yen-Yi

1993-01-01

The basic objectives of this contract were to perform detailed analysis and evaluation of dynamic data obtained during Space Shuttle Main Engine (SSME) test and flight operations, including analytical/statistical assessment of component dynamic performance, and to continue the development and implementation of analytical/statistical models to effectively define nominal component dynamic characteristics, detect anomalous behavior, and assess machinery operational conditions. This study was to provide timely assessment of engine component operational status, identify probable causes of malfunction, and define feasible engineering solutions. The work was performed under three broad tasks: (1) Analysis, Evaluation, and Documentation of SSME Dynamic Test Results; (2) Data Base and Analytical Model Development and Application; and (3) Development and Application of Vibration Signature Analysis Techniques.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

[In vitro transdermal delivery of the active fraction of xiangfusiwu decoction based on principal component analysis].

PubMed

Li, Zhen-Hao; Liu, Pei; Qian, Da-Wei; Li, Wei; Shang, Er-Xin; Duan, Jin-Ao

2013-06-01

The objective of the present study was to establish a method based on principal component analysis (PCA) for the study of transdermal delivery of multiple components in Chinese medicine, and to choose the best penetration enhancers for the active fraction of Xiangfusiwu decoction (BW) with this method. Improved Franz diffusion cells with isolated rat abdomen skins were carried out to experiment on the transdermal delivery of six active components, including ferulic acid, paeoniflorin, albiflorin, protopine, tetrahydropalmatine and tetrahydrocolumbamine. The concentrations of these components were determined by LC-MS/MS, then the total factor scores of the concentrations at different times were calculated using PCA and were employed instead of the concentrations to compute the cumulative amounts and steady fluxes, the latter of which were considered as the indexes for optimizing penetration enhancers. The results showed that compared to the control group, the steady fluxes of the other groups increased significantly and furthermore, 4% azone with 1% propylene glycol manifested the best effect. The six components could penetrate through skin well under the action of penetration enhancers. The method established in this study has been proved to be suitable for the study of transdermal delivery of multiple components, and it provided a scientific basis for preparation research of Xiangfusiwu decoction and moreover, it could be a reference for Chinese medicine research.

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.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

NASA Astrophysics Data System (ADS)

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-04-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound.

Drug target identification using network analysis: Taking active components in Sini decoction as an example

PubMed Central

Chen, Si; Jiang, Hailong; Cao, Yan; Wang, Yun; Hu, Ziheng; Zhu, Zhenyu; Chai, Yifeng

2016-01-01

Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmacology and metabolomics to identify targets of active components in sini decoction (SND) simultaneously against heart failure. To begin with, 48 potential active components in SND against heart failure were predicted by serum pharmacochemistry, text mining and similarity match. Then, we employed network pharmacology including text mining and molecular docking to identify the potential targets of these components. The key enriched processes, pathways and related diseases of these target proteins were analyzed by STRING database. At last, network analysis was conducted to identify most possible targets of components in SND. Among the 25 targets predicted by network analysis, tumor necrosis factor α (TNF-α) was firstly experimentally validated in molecular and cellular level. Results indicated that hypaconitine, mesaconitine, higenamine and quercetin in SND can directly bind to TNF-α, reduce the TNF-α-mediated cytotoxicity on L929 cells and exert anti-myocardial cell apoptosis effects. We envisage that network analysis will also be useful in target identification of a bioactive compound. PMID:27095146

Bioactive components on immuno-enhancement effects in the traditional Chinese medicine Shenqi Fuzheng Injection based on relevance analysis between chemical HPLC fingerprints and in vivo biological effects.

PubMed

Wang, Jinxu; Tong, Xin; Li, Peibo; Liu, Menghua; Peng, Wei; Cao, Hui; Su, Weiwei

2014-08-08

Shenqi Fuzheng Injection (SFI) is an injectable traditional Chinese herbal formula comprised of two Chinese herbs, Radix codonopsis and Radix astragali, which were commonly used to improve immune functions against chronic diseases in an integrative and holistic way in China and other East Asian countries for thousands of years. This present study was designed to explore the bioactive components on immuno-enhancement effects in SFI using the relevance analysis between chemical fingerprints and biological effects in vivo. According to a four-factor, nine-level uniform design, SFI samples were prepared with different proportions of the four portions separated from SFI via high speed counter current chromatography (HSCCC). SFI samples were assessed with high performance liquid chromatography (HPLC) for 23 identified components. For the immunosuppressed murine experiments, biological effects in vivo were evaluated on spleen index (E1), peripheral white blood cell counts (E2), bone marrow cell counts (E3), splenic lymphocyte proliferation (E4), splenic natural killer cell activity (E5), peritoneal macrophage phagocytosis (E6) and the amount of interleukin-2 (E7). Based on the hypothesis that biological effects in vivo varied with differences in components, multivariate relevance analysis, including gray relational analysis (GRA), multi-linear regression analysis (MLRA) and principal component analysis (PCA), were performed to evaluate the contribution of each identified component. The results indicated that the bioactive components of SFI on immuno-enhancement activities were calycosin-7-O-β-d-glucopyranoside (P9), isomucronulatol-7,2'-di-O-glucoside (P11), biochanin-7-glucoside (P12), 9,10-dimethoxypterocarpan-3-O-xylosylglucoside (P15) and astragaloside IV (P20), which might have positive effects on spleen index (E1), splenic lymphocyte proliferation (E4), splenic natural killer cell activity (E5), peritoneal macrophage phagocytosis (E6) and the amount of interleukin-2 (E7), while 5-hydroxymethyl-furaldehyde (P5) and lobetyolin (P13) might have negative effects on E1, E4, E5, E6 and E7. Finally, the bioactive HPLC fingerprint of SFI based on its bioactive components on immuno-enhancement effects was established for quality control of SFI. In summary, this study provided a perspective to explore the bioactive components in a traditional Chinese herbal formula with a series of HPLC and animal experiments, which would be helpful to improve quality control and inspire further clinical studies of traditional Chinese medicines. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A comparison between plaque-based and vessel-based measurement for plaque component using volumetric intravascular ultrasound radiofrequency data analysis.

PubMed

Shin, Eun-Seok; Garcia-Garcia, Hector M; Garg, Scot; Serruys, Patrick W

2011-04-01

Although percent plaque components on plaque-based measurement have been used traditionally in previous studies, the impact of vessel-based measurement for percent plaque components have yet to be studied. The purpose of this study was therefore to correlate percent plaque components derived by plaque- and vessel-based measurement using intravascular ultrasound virtual histology (IVUS-VH). The patient cohort comprised of 206 patients with de novo coronary artery lesions who were imaged with IVUS-VH. Age ranged from 35 to 88 years old, and 124 patients were male. Whole pullback analysis was used to calculate plaque volume, vessel volume, and absolute and percent volumes of fibrous, fibrofatty, necrotic core, and dense calcium. The plaque and vessel volumes were well correlated (r = 0.893, P < 0.001). There was a strong correlation between percent plaque components volumes calculated by plaque and those calculated by vessel volumes (fibrous; r = 0.927, P < 0.001, fibrofatty; r = 0.972, P < 0.001, necrotic core; r = 0.964, P < 0.001, dense calcium; r = 0.980, P < 0.001,). Plaque and vessel volumes correlated well to the overall plaque burden. For percent plaque component volume, plaque-based measurement was also highly correlated with vessel-based measurement. Therefore, the percent plaque component volume calculated by vessel volume could be used instead of the conventional percent plaque component volume calculated by plaque volume.

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

PubMed

Watanabe, Asami

2009-04-01

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

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.

Comparison of three-dimensional fluorescence analysis methods for predicting formation of trihalomethanes and haloacetic acids.

PubMed

Peleato, Nicolás M; Andrews, Robert C

2015-01-01

This work investigated the application of several fluorescence excitation-emission matrix analysis methods as natural organic matter (NOM) indicators for use in predicting the formation of trihalomethanes (THMs) and haloacetic acids (HAAs). Waters from four different sources (two rivers and two lakes) were subjected to jar testing followed by 24hr disinfection by-product formation tests using chlorine. NOM was quantified using three common measures: dissolved organic carbon, ultraviolet absorbance at 254 nm, and specific ultraviolet absorbance as well as by principal component analysis, peak picking, and parallel factor analysis of fluorescence spectra. Based on multi-linear modeling of THMs and HAAs, principle component (PC) scores resulted in the lowest mean squared prediction error of cross-folded test sets (THMs: 43.7 (μg/L)(2), HAAs: 233.3 (μg/L)(2)). Inclusion of principle components representative of protein-like material significantly decreased prediction error for both THMs and HAAs. Parallel factor analysis did not identify a protein-like component and resulted in prediction errors similar to traditional NOM surrogates as well as fluorescence peak picking. These results support the value of fluorescence excitation-emission matrix-principal component analysis as a suitable NOM indicator in predicting the formation of THMs and HAAs for the water sources studied. Copyright © 2014. Published by Elsevier B.V.

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

PubMed Central

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

2016-01-01

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

Analysis of Performance of Jet Engine from Characteristics of Components II : Interaction of Components as Determined from Engine Operation

NASA Technical Reports Server (NTRS)

Goldstein, Arthur W; Alpert, Sumner; Beede, William; Kovach, Karl

1949-01-01

In order to understand the operation and the interaction of jet-engine components during engine operation and to determine how component characteristics may be used to compute engine performance, a method to analyze and to estimate performance of such engines was devised and applied to the study of the characteristics of a research turbojet engine built for this investigation. An attempt was made to correlate turbine performance obtained from engine experiments with that obtained by the simpler procedure of separately calibrating the turbine with cold air as a driving fluid in order to investigate the applicability of component calibration. The system of analysis was also applied to prediction of the engine and component performance with assumed modifications of the burner and bearing characteristics, to prediction of component and engine operation during engine acceleration, and to estimates of the performance of the engine and the components when the exhaust gas was used to drive a power turbine.

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

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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…

A photometric study of the eclipsing binary RX Hercules

NASA Technical Reports Server (NTRS)

Jeffreys, K. W.

1980-01-01

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

Novel Framework for Reduced Order Modeling of Aero-engine Components

NASA Astrophysics Data System (ADS)

Safi, Ali

The present study focuses on the popular dynamic reduction methods used in design of complex assemblies (millions of Degrees of Freedom) where numerous iterations are involved to achieve the final design. Aerospace manufacturers such as Rolls Royce and Pratt & Whitney are actively seeking techniques that reduce computational time while maintaining accuracy of the models. This involves modal analysis of components with complex geometries to determine the dynamic behavior due to non-linearity and complicated loading conditions. In such a case the sub-structuring and dynamic reduction techniques prove to be an efficient tool to reduce design cycle time. The components whose designs are finalized can be dynamically reduced to mass and stiffness matrices at the boundary nodes in the assembly. These matrices conserve the dynamics of the component in the assembly, and thus avoid repeated calculations during the analysis runs for design modification of other components. This thesis presents a novel framework in terms of modeling and meshing of any complex structure, in this case an aero-engine casing. In this study the affect of meshing techniques on the run time are highlighted. The modal analysis is carried out using an extremely fine mesh to ensure all minor details in the structure are captured correctly in the Finite Element (FE) model. This is used as the reference model, to compare against the results of the reduced model. The study also shows the conditions/criteria under which dynamic reduction can be implemented effectively, proving the accuracy of Criag-Bampton (C.B.) method and limitations of Static Condensation. The study highlights the longer runtime needed to produce the reduced matrices of components compared to the overall runtime of the complete unreduced model. Although once the components are reduced, the assembly run is significantly. Hence the decision to use Component Mode Synthesis (CMS) is to be taken judiciously considering the number of iterations that may be required during the design cycle.

Development of a scale to measure adherence to self-monitoring of blood glucose with latent variable measurement.

PubMed

Wagner, J A; Schnoll, R A; Gipson, M T

1998-07-01

Adherence to self-monitoring of blood glucose (SMBG) is problematic for many people with diabetes. Self-reports of adherence have been found to be unreliable, and existing paper-and-pencil measures have limitations. This study developed a brief measure of SMBG adherence with good psychometric properties and a useful factor structure that can be used in research and in practice. A total of 216 adults with diabetes responded to 30 items rated on a 9-point Likert scale that asked about blood monitoring habits. In part I of the study, items were evaluated and retained based on their psychometric properties. The sample was divided into exploratory and confirmatory halves. Using the exploratory half, items with acceptable psychometric properties were subjected to a principal components analysis. In part II of the study, structural equation modeling was used to confirm the component solution with the entire sample. Structural modeling was also used to test the relationship between these components. It was hypothesized that the scale would produce four correlated factors. Principal components analysis suggested a two-component solution, and confirmatory factor analysis confirmed this solution. The first factor measures the degree to which patients rely on others to help them test and thus was named "social influence." The second component measures the degree to which patients use physical symptoms of blood glucose levels to help them test and thus was named "physical influence." Results of the structural model show that the components are correlated and make up the higher-order latent variable adherence. The resulting 15-item scale provides a short, reliable way to assess patient adherence to SMBG. Despite the existence of several aspects of adherence, this study indicates that the construct consists of only two components. This scale is an improvement on previous measures of adherence because of its good psychometric properties, its interpretable factor structure, and its rigorous empirical development.

A Component Analysis of the Impact of Evaluative and Objective Feedback on Performance

ERIC Educational Resources Information Center

Johnson, Douglas A.

2013-01-01

Despite the frequency with which performance feedback interventions are used in organizational behavior management, component analyses of such feedback are rare. It has been suggested that evaluation of performance and objective details about performance are two necessary components for performance feedback. The present study was designed to help…

Lexical Sophistication as a Multidimensional Phenomenon: Relations to Second Language Lexical Proficiency, Development, and Writing Quality

ERIC Educational Resources Information Center

Kim, Minkyung; Crossley, Scott A.; Kyle, Kristopher

2018-01-01

This study conceptualizes lexical sophistication as a multidimensional phenomenon by reducing numerous lexical features of lexical sophistication into 12 aggregated components (i.e., dimensions) via a principal component analysis approach. These components were then used to predict second language (L2) writing proficiency levels, holistic lexical…

Study of advanced techniques for determining the long-term performance of components

NASA Technical Reports Server (NTRS)

1972-01-01

A study was conducted of techniques having the capability of determining the performance and reliability of components for spacecraft liquid propulsion applications for long term missions. The study utilized two major approaches; improvement in the existing technology, and the evolution of new technology. The criteria established and methods evolved are applicable to valve components. Primary emphasis was placed on the propellants oxygen difluoride and diborane combination. The investigation included analysis, fabrication, and tests of experimental equipment to provide data and performance criteria.

Research on design connotation of hair drier system

NASA Astrophysics Data System (ADS)

Li, Yongchuan; Wu, Qiong

2018-04-01

After the analysis and summary of the research on the design of hair drier system, the system design is focused on. Product system design is not only to study its entity, but also is recognized as the part, element and component with a systematic feature to deeply analyze the innovation way of product system design, which is taken as its concept to carry out the association analysis on the component elements of hair driers and the overall analysis and study on the system design process of hair dryers. The product life cycle is taken as the main goal, through system analysis, system synthesis and system optimization, to solve the problems of product design. It is of great practical significance.

Principle of maximum entropy for reliability analysis in the design of machine components

NASA Astrophysics Data System (ADS)

Zhang, Yimin

2018-03-01

We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy (PME). We used PME to select the statistical distribution that best fits the available information. We also established a probability density function (PDF) and a failure probability model for the parameters of mechanical components using the concept of entropy and the PME. We obtained the first four moments of the state function for reliability analysis and design. Furthermore, we attained an estimate of the PDF with the fewest human bias factors using the PME. This function was used to calculate the reliability of the machine components, including a connecting rod, a vehicle half-shaft, a front axle, a rear axle housing, and a leaf spring, which have parameters that typically follow a non-normal distribution. Simulations were conducted for comparison. This study provides a design methodology for the reliability of mechanical components for practical engineering projects.

Impact of Measurement Uncertainties on Receptor Modeling of Speciated Atmospheric Mercury.

PubMed

Cheng, I; Zhang, L; Xu, X

2016-02-09

Gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurement uncertainties could potentially affect the analysis and modeling of atmospheric mercury. This study investigated the impact of GOM measurement uncertainties on Principal Components Analysis (PCA), Absolute Principal Component Scores (APCS), and Concentration-Weighted Trajectory (CWT) receptor modeling results. The atmospheric mercury data input into these receptor models were modified by combining GOM and PBM into a single reactive mercury (RM) parameter and excluding low GOM measurements to improve the data quality. PCA and APCS results derived from RM or excluding low GOM measurements were similar to those in previous studies, except for a non-unique component and an additional component extracted from the RM dataset. The percent variance explained by the major components from a previous study differed slightly compared to RM and excluding low GOM measurements. CWT results were more sensitive to the input of RM than GOM excluding low measurements. Larger discrepancies were found between RM and GOM source regions than those between RM and PBM. Depending on the season, CWT source regions of RM differed by 40-61% compared to GOM from a previous study. No improvement in correlations between CWT results and anthropogenic mercury emissions were found.

Impact of Measurement Uncertainties on Receptor Modeling of Speciated Atmospheric Mercury

PubMed Central

Cheng, I.; Zhang, L.; Xu, X.

2016-01-01

Gaseous oxidized mercury (GOM) and particle-bound mercury (PBM) measurement uncertainties could potentially affect the analysis and modeling of atmospheric mercury. This study investigated the impact of GOM measurement uncertainties on Principal Components Analysis (PCA), Absolute Principal Component Scores (APCS), and Concentration-Weighted Trajectory (CWT) receptor modeling results. The atmospheric mercury data input into these receptor models were modified by combining GOM and PBM into a single reactive mercury (RM) parameter and excluding low GOM measurements to improve the data quality. PCA and APCS results derived from RM or excluding low GOM measurements were similar to those in previous studies, except for a non-unique component and an additional component extracted from the RM dataset. The percent variance explained by the major components from a previous study differed slightly compared to RM and excluding low GOM measurements. CWT results were more sensitive to the input of RM than GOM excluding low measurements. Larger discrepancies were found between RM and GOM source regions than those between RM and PBM. Depending on the season, CWT source regions of RM differed by 40–61% compared to GOM from a previous study. No improvement in correlations between CWT results and anthropogenic mercury emissions were found. PMID:26857835

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

NASA Astrophysics Data System (ADS)

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

2009-06-01

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

Pricing and components analysis of some key essential pediatric medicine in Odisha state.

PubMed

Samal, Satyajit; Swain, Trupti Rekha

2017-01-01

Study highlighting prices, i.e., the patients actually pay at ground level is important for interventions such as alternate procurement schemes or to expedite regulatory assessment of essential medicines for children. The present study was undertaken to study pricing and component analysis of few key essential medicines in Odisha state. Six child-specific medicines of different formulations were selected based on use in different disease condition and having widest pricing variation. Data were collected, entered, and analyzed in the price components data collection form of the World Health Organization-Health Action International (WHO-HAI) 2007 Workbook version 5 - Part II provided as part of the WHO/HAI methodology. The analysis includes the cumulative percent markup, total cumulative percent markup, and percent contribution of individual components to the final medicine price in both public and private sector of Odisha state. Add-on costs such as taxes, wholesale, and retail markups contribute substantially to the final price of medicines in private sector, particularly for branded-generic products. The largest contributor to add-on costs is at the level of retailer shop. Policy should be framed to achieve a greater transparency and uniformity of the pricing of medicines at different health sectors of Odisha.

Characterization of extracellular polymeric substances in biofilms under long-term exposure to ciprofloxacin antibiotic using fluorescence excitation-emission matrix and parallel factor analysis.

PubMed

Gu, Chaochao; Gao, Pin; Yang, Fan; An, Dongxuan; Munir, Mariya; Jia, Hanzhong; Xue, Gang; Ma, Chunyan

2017-05-01

The presence of antibiotic residues in the environment has been regarded as an emerging concern due to their potential adverse environmental consequences such as antibiotic resistance. However, the interaction between antibiotics and extracellular polymeric substances (EPSs) of biofilms in wastewater treatment systems is not entirely clear. In this study, the effect of ciprofloxacin (CIP) antibiotic on biofilm EPS matrix was investigated and characterized using fluorescence excitation-emission matrix (EEM) and parallel factor (PARAFAC) analysis. Physicochemical analysis showed that the proteins were the major EPS fraction, and their contents increased gradually with an increase in CIP concentration (0-300 μg/L). Based on the characterization of biofilm tightly bound EPS (TB-EPS) by EEM, three fluorescent components were identified by PARAFAC analysis. Component C1 was associated with protein-like substances, and components C2 and C3 belonged to humic-like substances. Component C1 exhibited an increasing trend as the CIP addition increased. Pearson's correlation results showed that CIP correlated significantly with the protein contents and component C1, while strong correlations were also found among UV 254 , dissolved organic carbon, humic acids, and component C3. A combined use of EEM-PARAFAC analysis and chemical measurements was demonstrated as a favorable approach for the characterization of variations in biofilm EPS in the presence of CIP antibiotic.

RELIABLE ASSAYS FOR DETERMINING ENDOGENOUS COMPONENTS OF HUMAN MILK

EPA Science Inventory

Healthy women from 18-38 years old (N=25) fasted for several hours and twice donated blood and milk (postpartum 2-7 weeks and 3-4 months) for the EPA's Methods Advancement for Milk Analysis study, a pilot for the National Children's Study (NCS). Endogenous components were chosen...

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…

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

PubMed

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

2010-12-01

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

Needle Trap Device as a New Sampling and Preconcentration Approach for Volatile Organic Compounds of Herbal Medicines and its Application to the Analysis of Volatile Components in Viola tianschanica.

PubMed

Qin, Yan; Pang, Yingming; Cheng, Zhihong

2016-11-01

The needle trap device (NTD) technique is a new microextraction method for sampling and preconcentration of volatile organic compounds (VOCs). Previous NTD studies predominantly focused on analysis of environmental volatile compounds in the gaseous and liquid phases. Little work has been done on its potential application in biological samples and no work has been reported on analysis of bioactive compounds in essential oils from herbal medicines. The main purpose of the present study is to develop a NTD sampling method for profiling VOCs in biological samples using herbal medicines as a case study. A combined method of NTD sample preparation and gas chromatography-mass spectrometry was developed for qualitative analysis of VOCs in Viola tianschanica. A 22-gauge stainless steel, triple-bed needle packed with Tenax, Carbopack X and Carboxen 1000 sorbents was used for analysis of VOCs in the herb. Furthermore, different parameters affecting the extraction efficiency and capacity were studied. The peak capacity obtained by NTDs was 104, more efficient than those of the static headspace (46) and hydrodistillation (93). This NTD method shows potential to trap a wide range of VOCs including the lower and higher volatile components, while the static headspace and hydrodistillation only detects lower volatile components, and semi-volatile and higher volatile components, respectively. The developed NTD sample preparation method is a more rapid, simpler, convenient, and sensitive extraction/desorption technique for analysis of VOCs in herbal medicines than the conventional methods such as static headspace and hydrodistillation. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

[Analysis of active components of evidence materials secured in the cases of drugs abuse associated with amphetamines and cannabis products].

PubMed

Wachowiak, Roman; Strach, Bogna

2006-01-01

The study takes advantage of the presently available effective physicochemical methods (isolation, crystallization, determination of melting point, TLC, GLC and UV spectrophotometry) for an objective and reliable qualitative and quantitative analysis of frequently abused drugs. The authors determined the conditions for qualitative and quantitative analysis of active components of the secured evidence materials containing amphetamine sulphate, methylamphetamine hydrochloride, 3,4-me-tylenedioxy-methamphetamine hydrochloride (MDMA, Ecstasy), as well as delta(9)-tetrahydrocannabinol (delta(9)-THC) as an active component of cannabis (marihuana, hashish). The usefulness of physicochemical tests of evidence materials for opinionating purposes is subject to a detailed forensic toxicological interpretation.

Development of STS/Centaur failure probabilities liftoff to Centaur separation

NASA Technical Reports Server (NTRS)

Hudson, J. M.

1982-01-01

The results of an analysis to determine STS/Centaur catastrophic vehicle response probabilities for the phases of vehicle flight from STS liftoff to Centaur separation from the Orbiter are presented. The analysis considers only category one component failure modes as contributors to the vehicle response mode probabilities. The relevant component failure modes are grouped into one of fourteen categories of potential vehicle behavior. By assigning failure rates to each component, for each of its failure modes, the STS/Centaur vehicle response probabilities in each phase of flight can be calculated. The results of this study will be used in a DOE analysis to ascertain the hazard from carrying a nuclear payload on the STS.

Computer analysis of the leaf movements of pinto beans.

PubMed

Hoshizaki, T; Hamner, K C

1969-07-01

Computer analysis was used for the detection of rhythmic components and the estimation of period length in leaf movement records. The results of this study indicated that spectral analysis can be profitably used to determine rhythmic components in leaf movements.In Pinto bean plants (Phaseolus vulgaris L.) grown for 28 days under continuous light of 750 ft-c and at a constant temperature of 28 degrees , there was only 1 highly significant rhythmic component in the leaf movements. The period of this rhythm was 27.3 hr. In plants grown at 20 degrees , there were 2 highly significant rhythmic components: 1 of 13.8 hr and a much stronger 1 of 27.3 hr. At 15 degrees , the highly significant rhythmic components were also 27.3 and 13.8 hr in length but were of equal intensity. Random movements less than 9 hr in length became very pronounced at this temperature. At 10 degrees , no significant rhythm was found in the leaf movements. At 5 degrees , the leaf movements ceased within 1 day.

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

PubMed

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

2016-01-01

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

Comparative study of human blood Raman spectra and biochemical analysis of patients with cancer

NASA Astrophysics Data System (ADS)

Shamina, Lyudmila A.; Bratchenko, Ivan A.; Artemyev, Dmitry N.; Myakinin, Oleg O.; Moryatov, Alexander A.; Orlov, Andrey E.; Kozlov, Sergey V.; Zakharov, Valery P.

2018-04-01

In this study we measured spectral features of blood by Raman spectroscopy. Correlation of the obtained spectral data and biochemical studies results is investigated. Analysis of specific spectra allows for identification of informative spectral bands proportional to components whose content is associated with body fluids homeostasis changes at various pathological conditions. Regression analysis of the obtained spectral data allows for discriminating the lung cancer from other tumors with a posteriori probability of 88.3%. The potentiality of applying surface-enhanced Raman spectroscopy with utilized experimental setup for further studies of the body fluids component composition was estimated. The greatest signal amplification was achieved for the gold substrate with a surface roughness of 1 μm. In general, the developed approach of body fluids analysis provides the basis of a useful and minimally invasive method of pathologies screening.

Inventory of File sref_em.t03z.pgrb212.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb132.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb221.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb132.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb243.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb243.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb221.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb212.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_nmm.t03z.pgrb216.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

Inventory of File sref_em.t03z.pgrb216.ctl.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 006 10 m above ground VGRD analysis V-Component of Wind [m/s of Wind [m/s] 018 250 mb VGRD analysis V-Component of Wind [m/s] 019 500 mb HGT analysis Geopotential Height [gpm] 020 500 mb UGRD analysis U-Component of Wind [m/s] 021 500 mb VGRD analysis V-Component of

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

NASA Astrophysics Data System (ADS)

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

2004-10-01

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

Principal components analysis of 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.

A Component-Centered Meta-Analysis of Family-Based Prevention Programs for Adolescent Substance Use

PubMed Central

Roseth, Cary J.; Fosco, Gregory M.; Lee, You-kyung; Chen, I-Chien

2016-01-01

Although research has documented the positive effects of family-based prevention programs, the field lacks specific information regarding why these programs are effective. The current study summarized the effects of family-based programs on adolescent substance use using a component-based approach to meta-analysis in which we decomposed programs into a set of key topics or components that were specifically addressed by program curricula (e.g., parental monitoring/behavior management, problem solving, positive family relations, etc.). Components were coded according to the amount of time spent on program services that targeted youth, parents, and the whole family; we also coded effect sizes across studies for each substance-related outcome. Given the nested nature of the data, we used hierarchical linear modeling to link program components (Level 2) with effect sizes (Level 1). The overall effect size across programs was .31, which did not differ by type of substance. Youth-focused components designed to encourage more positive family relationships and a positive orientation toward the future emerged as key factors predicting larger than average effect sizes. Our results suggest that, within the universe of family-based prevention, where components such as parental monitoring/behavior management are almost universal, adding or expanding certain youth-focused components may be able to enhance program efficacy. PMID:27064553

In situ X-ray diffraction analysis of (CF x) n batteries: signal extraction by multivariate analysis

DOE PAGES

Rodriguez, Mark A.; Keenan, Michael R.; Nagasubramanian, Ganesan

2007-11-10

In this study, (CF x) n cathode reaction during discharge has been investigated using in situ X-ray diffraction (XRD). Mathematical treatment of the in situ XRD data set was performed using multivariate curve resolution with alternating least squares (MCR–ALS), a technique of multivariate analysis. MCR–ALS analysis successfully separated the relatively weak XRD signal intensity due to the chemical reaction from the other inert cell component signals. The resulting dynamic reaction component revealed the loss of (CF x) n cathode signal together with the simultaneous appearance of LiF by-product intensity. Careful examination of the XRD data set revealed an additional dynamicmore » component which may be associated with the formation of an intermediate compound during the discharge process.« less

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.

The Influence Of Component Alignment On The Life Of Total Knee Prostheses

NASA Astrophysics Data System (ADS)

Bugariu, Delia; Bereteu, Liviu

2012-12-01

An arthritic knee affects the patient's life by causing pain and limiting movement. If the cartilage and the bone surfaces are severely affected, the natural joint is replaced with an artificial joint. The procedure is called total knee arthroplasty (TKA). Lately, the numbers of implanted total knee prostheses grow steadily. An important factor in TKA is the perfect alignment of the total knee prosthesis (TKP) components. Component misalignment can lead to the prosthesis loss by producing wear particles. The paper proposes a study on mechanical behaviors of a TKP based on numerical analysis, using ANSYS software. The numerical analysis is based on both the normal and the changed angle of the components alignment.

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

PubMed Central

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

2015-01-01

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

Factor analysis of metabolic syndrome components and predicting type 2 diabetes: Results of 10-year follow-up in a Middle Eastern population.

PubMed

Ayubi, Erfan; Khalili, Davood; Delpisheh, Ali; Hadaegh, Farzad; Azizi, Fereidoun

2015-11-01

The relationship among components of metabolic syndrome (MetS) and their association with diabetes is unclear in West Asia. The aim of the present study was to conduct factor analysis of MetS components and the effect these factors have on the incidence of type 2 diabetes (T2D) in a population-based cohort study of the Tehran Lipid and Glucose Study (TLGS). The present study enrolled 1861 men and 2706 women (20-60 years of age), from Tehran (Iran) who were free of diabetes at baseline and followed them for 10 years. A principal component analysis was performed to extract standardized factors from MetS components. Logistic regression was used to detect associations between the extracted factors and the incidence of diabetes. A propensity score was used to correct differential selection bias resulting from loss to follow-up. Factor analysis identified three factors (blood pressure, lipids and glycemia). Waist circumference was shared in three all factors. Blood pressure, lipids and glycemia were related to the incidence of diabetes with odds ratios (95% confidence intervals) of 2.23 (1.31-3.78), 1.89 (1.27-3.67), and 7.54 (4.09-13.91), respectively, in men and 2.13 (1.34-3.40), 2.06 (1.35-3.15), and 13.91 (7.29-26.51), respectively, in women for the third versus the first tertile of these standardized factors. Central adiposity may have a pivotal role in MetS linking other risk factors together. Glycemia had a high impact on the incidence of diabetes, whereas blood pressure and lipid had a similar moderate effect on the incidence of diabetes. © 2014 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Multi-Response Extraction Optimization Based on Anti-Oxidative Activity and Quality Evaluation by Main Indicator Ingredients Coupled with Chemometric Analysis on Thymus quinquecostatus Celak.

PubMed

Chang, Yan-Li; Shen, Meng; Ren, Xue-Yang; He, Ting; Wang, Le; Fan, Shu-Sheng; Wang, Xiu-Huan; Li, Xiao; Wang, Xiao-Ping; Chen, Xiao-Yi; Sui, Hong; She, Gai-Mei

2018-04-19

Thymus quinquecostatus Celak is a species of thyme in China and it used as condiment and herbal medicine for a long time. To set up the quality evaluation of T. quinquecostatus , the response surface methodology (RSM) based on its 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity was introduced to optimize the extraction condition, and the main indicator components were found through an UPLC-LTQ-Orbitrap MS n method. The ethanol concentration, solid-liquid ratio, and extraction time on optimum conditions were 42.32%, 1:17.51, and 1.8 h, respectively. 35 components having 12 phenolic acids and 23 flavonoids were unambiguously or tentatively identified both positive and negative modes to employ for the comprehensive analysis in the optimum anti-oxidative part. A simple, reliable, and sensitive HPLC method was performed for the multi-component quantitative analysis of T. quinquecostatus using six characteristic and principal phenolic acids and flavonoids as reference compounds. Furthermore, the chemometrics methods (principal components analysis (PCA) and hierarchical clustering analysis (HCA)) appraised the growing areas and harvest time of this herb closely relative to the quality-controlled. This study provided full-scale qualitative and quantitative information for the quality evaluation of T. quinquecostatus , which would be a valuable reference for further study and development of this herb and related laid the foundation of further study on its pharmacological efficacy.

Analysis of metabolic syndrome components in >15 000 african americans identifies pleiotropic variants: results from the population architecture using genomics and epidemiology study.

PubMed

Carty, Cara L; Bhattacharjee, Samsiddhi; Haessler, Jeff; Cheng, Iona; Hindorff, Lucia A; Aroda, Vanita; Carlson, Christopher S; Hsu, Chun-Nan; Wilkens, Lynne; Liu, Simin; Selvin, Elizabeth; Jackson, Rebecca; North, Kari E; Peters, Ulrike; Pankow, James S; Chatterjee, Nilanjan; Kooperberg, Charles

2014-08-01

Metabolic syndrome (MetS) refers to the clustering of cardiometabolic risk factors, including dyslipidemia, central adiposity, hypertension, and hyperglycemia, in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. Using the Metabochip array in 15 148 African Americans from the Population Architecture using Genomics and Epidemiology (PAGE) study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models that lack power when associations for MetS components are null or have opposite effects, Association-analysis-based-on-subsets uses 1-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With Association-analysis-based-on-subsets, we identify 27 single nucleotide polymorphisms in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, and APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P<2.5e-7, the Bonferroni adjusted P value. Three loci replicate in a Hispanic population, n=5172. A novel African American-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2, and CETP variants, many with opposing effects (eg, the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity). We highlight a method to increase power in large-scale genomic association analyses and report a novel variant associated with all MetS components in African Americans. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications. © 2014 American Heart Association, Inc.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Distinguishing response conflict and task conflict in the Stroop task: evidence from ex-Gaussian distribution analysis.

PubMed

Steinhauser, Marco; Hübner, Ronald

2009-10-01

It has been suggested that performance in the Stroop task is influenced by response conflict as well as task conflict. The present study investigated the idea that both conflict types can be isolated by applying ex-Gaussian distribution analysis which decomposes response time into a Gaussian and an exponential component. Two experiments were conducted in which manual versions of a standard Stroop task (Experiment 1) and a separated Stroop task (Experiment 2) were performed under task-switching conditions. Effects of response congruency and stimulus bivalency were used to measure response conflict and task conflict, respectively. Ex-Gaussian analysis revealed that response conflict was mainly observed in the Gaussian component, whereas task conflict was stronger in the exponential component. Moreover, task conflict in the exponential component was selectively enhanced under task-switching conditions. The results suggest that ex-Gaussian analysis can be used as a tool to isolate different conflict types in the Stroop task. PsycINFO Database Record (c) 2009 APA, all rights reserved.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

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

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

PubMed

Magallares, Alejandro; Schomerus, Georg

2015-01-01

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

Web-ware bioinformatical analysis and structure modelling of N-terminus of human multisynthetase complex auxiliary component protein p43.

PubMed

Deineko, Viktor

2006-01-01

Human multisynthetase complex auxiliary component, protein p43 is an endothelial monocyte-activating polypeptide II precursor. In this study, comprehensive sequence analysis of N-terminus has been performed to identify structural domains, motifs, sites of post-translation modification and other functionally important parameters. The spatial structure model of full-chain protein p43 is obtained.

[Herbalism, botany and components analysis study on original plants of frankincense].

PubMed

Sun, Lei; Xu, Jimin; Jin, Hongyu; Tian, Jingai; Lin, Ruichao

2011-01-01

In order to clarify original plants of traditional Chinese medicine (TCM) frankincense, a GC method for determination essential oils and a HPLC method for determination boswellic acids were carried out together with analysis of herbalism, botany, components and pharmacology papers of frankincense. It was concluded that original plants of TCM frankincense include at least Boswellia sacra, B. papyrifera and B. serrata.

Chiral Chlordane Components in Environmental Matrices

EPA Science Inventory

Chlordane, a persistent, bioaccumulative and toxic organochlorine pesticide, has been studied for many years. Since the advent of chiral analysis for environmental samples, over 2,400 measurements have been made of various chiral chlordane components. Chlordane enantiomer fractio...

Metal-backed versus all-polyethylene tibial components in primary total knee arthroplasty

PubMed Central

2011-01-01

Background and purpose The choice of either all-polyethylene (AP) tibial components or metal-backed (MB) tibial components in total knee arthroplasty (TKA) remains controversial. We therefore performed a meta-analysis and systematic review of randomized controlled trials that have evaluated MB and AP tibial components in primary TKA. Methods The search strategy included a computerized literature search (Medline, EMBASE, Scopus, and the Cochrane Central Register of Controlled Trials) and a manual search of major orthopedic journals. A meta-analysis and systematic review of randomized or quasi-randomized trials that compared the performance of tibial components in primary TKA was performed using a fixed or random effects model. We assessed the methodological quality of studies using Detsky quality scale. Results 9 randomized controlled trials (RCTs) published between 2000 and 2009 met the inclusion quality standards for the systematic review. The mean standardized Detsky score was 14 (SD 3). We found that the frequency of radiolucent lines in the MB group was significantly higher than that in the AP group. There were no statistically significant differences between the MB and AP tibial components regarding component positioning, knee score, knee range of motion, quality of life, and postoperative complications. Interpretation Based on evidence obtained from this study, the AP tibial component was comparable with or better than the MB tibial component in TKA. However, high-quality RCTs are required to validate the results. PMID:21895503

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

ERIC Educational Resources Information Center

Miller, Regina M.; And Others

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

Heritability of somatotype components from early adolescence into young adulthood: a multivariate analysis on a longitudinal twin study.

PubMed

Peeters, M W; Thomis, M A; Claessens, A L; Loos, R J F; Maes, H H M; Lysens, R; Vanden Eynde, B; Vlietinck, R; Beunen, G

2003-01-01

Several studies with different designs have attempted to estimate the heritability of somatotype components. However they often ignore the covariation between the three components as well as possible sex and age effects. Shared environmental factors are not always controlled for. This study explores the pattern of genetic and environmental determination of the variation in Heath-Carter somatotype components from early adolescence into young adulthood. Data from the Leuven Longitudinal Twin Study, a longitudinal sample of Belgian same-aged twins followed from 10 to 18 years (n = 105 pairs, equally divided over five zygosity groups), is entered into a multivariate path analysis. Thus the covariation between the somatotype components is taken into account, gender heterogeneity can be tested, common environmental influences can be distinguished from genetic effects and age effects are controlled for. Heritability estimates from 10 to 18 years range from 0.21 to 0.88, 0.46 to 0.76 and 0.16 to 0.73 for endomorphy, mesomorphy and ectomorphy in boys. In girls, heritability estimates range from 0.76 to 0.89, 0.36 to 0.57 and 0.57 to 0.76 for the respective somatotype components. Sex differences are significant from 14 years onwards. More than half of the variance in all somatotype components for both sexes at all time points is explained by factors the three components have in common. The finding of substantial genetic influence on the variability of somatotype components is further supported. The need to consider somatotype as a whole is stressed as well as the need for sex- and perhaps age-specific analyses. Further multivariate analyses are needed to confirm the present findings.

Interpreting the results of chemical stone analysis in the era of modern stone analysis techniques

PubMed Central

Gilad, Ron; Williams, James C.; Usman, Kalba D.; Holland, Ronen; Golan, Shay; Ruth, Tor; Lifshitz, David

2017-01-01

Introduction and Objective Stone analysis should be performed in all first-time stone formers. The preferred analytical procedures are Fourier-transform infrared spectroscopy (FT-IR) or X-ray diffraction (XRD). However, due to limited resources, chemical analysis (CA) is still in use throughout the world. The aim of the study was to compare FT-IR and CA in well matched stone specimens and characterize the pros and cons of CA. Methods In a prospective bi-center study, urinary stones were retrieved from 60 consecutive endoscopic procedures. In order to assure that identical stone samples were sent for analyses, the samples were analyzed initially by micro-computed tomography to assess uniformity of each specimen before submitted for FTIR and CA. Results Overall, the results of CA did not match with the FTIR results in 56% of the cases. In 16% of the cases CA missed the major stone component and in 40% the minor stone component. 37 of the 60 specimens contained CaOx as major component by FTIR, and CA reported major CaOx in 47/60, resulting in high sensitivity, but very poor specificity. CA was relatively accurate for UA and cystine. CA missed struvite and calcium phosphate as a major component in all cases. In mixed stones the sensitivity of CA for the minor component was poor, generally less than 50%. Conclusions Urinary stone analysis using CA provides only limited data that should be interpreted carefully. Urinary stone analysis using CA is likely to result in clinically significant errors in its assessment of stone composition. Although the monetary costs of CA are relatively modest, this method does not provide the level of analytical specificity required for proper management of patients with metabolic stones. PMID:26956131

Screening of patients with bronchopulmonary diseases using methods of infrared laser photoacoustic spectroscopy and principal component analysis

NASA Astrophysics Data System (ADS)

Kistenev, Yury V.; Karapuzikov, Alexander I.; Kostyukova, Nadezhda Yu.; Starikova, Marina K.; Boyko, Andrey A.; Bukreeva, Ekaterina B.; Bulanova, Anna A.; Kolker, Dmitry B.; Kuzmin, Dmitry A.; Zenov, Konstantin G.; Karapuzikov, Alexey A.

2015-06-01

A human exhaled air analysis by means of infrared (IR) laser photoacoustic spectroscopy is presented. Eleven healthy nonsmoking volunteers (control group) and seven patients with chronic obstructive pulmonary disease (COPD, target group) were involved in the study. The principal component analysis method was used to select the most informative ranges of the absorption spectra of patients' exhaled air in terms of the separation of the studied groups. It is shown that the data of the profiles of exhaled air absorption spectrum in the informative ranges allow identifying COPD patients in comparison to the control group.

Data Base Reexamination as Part of IDS Secondary Analysis.

ERIC Educational Resources Information Center

Curry, Blair H.; And Others

Data reexamination is a critical component for any study. The complexity of the study, the time available for data base development and analysis, and the relationship of the study to educational policy-making can all increase the criticality of such reexamination. Analysis of the error levels in the National Institute of Education's Instructional…

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

PubMed

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

2013-08-01

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

A feasibility study on age-related factors of wrist pulse using principal component analysis.

PubMed

Jang-Han Bae; Young Ju Jeon; Sanghun Lee; Jaeuk U Kim

2016-08-01

Various analysis methods for examining wrist pulse characteristics are needed for accurate pulse diagnosis. In this feasibility study, principal component analysis (PCA) was performed to observe age-related factors of wrist pulse from various analysis parameters. Forty subjects in the age group of 20s and 40s were participated, and their wrist pulse signal and respiration signal were acquired with the pulse tonometric device. After pre-processing of the signals, twenty analysis parameters which have been regarded as values reflecting pulse characteristics were calculated and PCA was performed. As a results, we could reduce complex parameters to lower dimension and age-related factors of wrist pulse were observed by combining-new analysis parameter derived from PCA. These results demonstrate that PCA can be useful tool for analyzing wrist pulse signal.

Linkage Analysis of Urine Arsenic Species Patterns in the Strong Heart Family Study

PubMed Central

Gribble, Matthew O.; Voruganti, Venkata Saroja; Cole, Shelley A.; Haack, Karin; Balakrishnan, Poojitha; Laston, Sandra L.; Tellez-Plaza, Maria; Francesconi, Kevin A.; Goessler, Walter; Umans, Jason G.; Thomas, Duncan C.; Gilliland, Frank; North, Kari E.; Franceschini, Nora; Navas-Acien, Ana

2015-01-01

Arsenic toxicokinetics are important for disease risks in exposed populations, but genetic determinants are not fully understood. We examined urine arsenic species patterns measured by HPLC-ICPMS among 2189 Strong Heart Study participants 18 years of age and older with data on ∼400 genome-wide microsatellite markers spaced ∼10 cM and arsenic speciation (683 participants from Arizona, 684 from Oklahoma, and 822 from North and South Dakota). We logit-transformed % arsenic species (% inorganic arsenic, %MMA, and %DMA) and also conducted principal component analyses of the logit % arsenic species. We used inverse-normalized residuals from multivariable-adjusted polygenic heritability analysis for multipoint variance components linkage analysis. We also examined the contribution of polymorphisms in the arsenic metabolism gene AS3MT via conditional linkage analysis. We localized a quantitative trait locus (QTL) on chromosome 10 (LOD 4.12 for %MMA, 4.65 for %DMA, and 4.84 for the first principal component of logit % arsenic species). This peak was partially but not fully explained by measured AS3MT variants. We also localized a QTL for the second principal component of logit % arsenic species on chromosome 5 (LOD 4.21) that was not evident from considering % arsenic species individually. Some other loci were suggestive or significant for 1 geographical area but not overall across all areas, indicating possible locus heterogeneity. This genome-wide linkage scan suggests genetic determinants of arsenic toxicokinetics to be identified by future fine-mapping, and illustrates the utility of principal component analysis as a novel approach that considers % arsenic species jointly. PMID:26209557

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…

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

PubMed

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

2018-02-08

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

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.

The Relationship between Parent-Reported Coping, Stress, and Mental Health in a Preschool Population

ERIC Educational Resources Information Center

Kiernan, Neisha; Frydenberg, Erica; Deans, Jan; Liang, Rachel

2017-01-01

The present study explored the component structure of coping in preschoolers as measured by the Children's Coping Scale-Revised (CCS-R) through principal component analysis (PCA). The study also examined the relationship between different coping patterns and mental health (as measured by the Strengths and Diffculties Questionnaire; SDQ) in…

Preliminary Analysis of Interteaching's Frequent Examinations Component in the Community College Classroom

ERIC Educational Resources Information Center

Felderman, Theresa A.

2014-01-01

Interteaching has shown to be an effective alternative to traditional lecture in a number of studies, but thorough analyses of its components, including frequent exams, is limited. Research suggests that increasing the frequency of exams may improve student learning. This study assessed the effectiveness of interteaching's frequent exams component…

No difference in mechanical alignment and femoral component placement between patient-specific instrumentation and conventional instrumentation in TKA.

PubMed

Fu, Huichao; Wang, Jiaxing; Zhou, Shenyuan; Cheng, Tao; Zhang, Wen; Wang, Qi; Zhang, Xianlong

2015-11-01

There is a rising interest in the use of patient-specific instrumentation (PSI) during total knee arthroplasty (TKA). The goal of this meta-analysis was to compare PSI with conventional instrumentation (CI) in patients undergoing TKA. A literature search was performed in PubMed, Embase, Springer, Ovid, China National Knowledge Infrastructure, and the Cochrane Library. A total of 10 randomized controlled studies involving 837 knees comparing outcomes of PSI TKAs with CI TKAs were included in the present analysis. Outcomes of interest included component alignment, surgical time, blood loss, and hospital stay. The results presented no significant differences between the two instrumentations in terms of restoring a neutral mechanical axis and femoral component placement. However, their differences have been noted regarding the alignment of the tibial component in coronal and sagittal planes. Also, 3 min less surgical time was used in PSI patients. Based on these findings, PSI appeared not to be superior to CI in terms of the post-operative mechanical axis of the limb or femoral component placement. Despite a statistical difference for operative duration, the benefit of a small reduction in surgical time with PSI is clinically irrelevant. Therapeutic study (systematic review and meta-analysis), Level I.

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

PubMed

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

2018-04-01

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

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.

Application of time series analysis on molecular dynamics simulations of proteins: a study of different conformational spaces by principal component analysis.

PubMed

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C

2004-09-08

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of alpha-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Calpha coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of alpha-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of alpha-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins. Copyright 2004 American Institute of Physics

Application of time series analysis on molecular dynamics simulations of proteins: A study of different conformational spaces by principal component analysis

NASA Astrophysics Data System (ADS)

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

2004-09-01

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of α-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Cα coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of α-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of α-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins.

Impacts of a flash flood on drinking water quality: case study of areas most affected by the 2012 Beijing flood.

PubMed

Sun, Rubao; An, Daizhi; Lu, Wei; Shi, Yun; Wang, Lili; Zhang, Can; Zhang, Ping; Qi, Hongjuan; Wang, Qiang

2016-02-01

In this study, we present a method for identifying sources of water pollution and their relative contributions in pollution disasters. The method uses a combination of principal component analysis and factor analysis. We carried out a case study in three rural villages close to Beijing after torrential rain on July 21, 2012. Nine water samples were analyzed for eight parameters, namely turbidity, total hardness, total dissolved solids, sulfates, chlorides, nitrates, total bacterial count, and total coliform groups. All of the samples showed different degrees of pollution, and most were unsuitable for drinking water as concentrations of various parameters exceeded recommended thresholds. Principal component analysis and factor analysis showed that two factors, the degree of mineralization and agricultural runoff, and flood entrainment, explained 82.50% of the total variance. The case study demonstrates that this method is useful for evaluating and interpreting large, complex water-quality data sets.

Job Performance as Multivariate Dynamic Criteria: Experience Sampling and Multiway Component Analysis.

PubMed

Spain, Seth M; Miner, Andrew G; Kroonenberg, Pieter M; Drasgow, Fritz

2010-08-06

Questions about the dynamic processes that drive behavior at work have been the focus of increasing attention in recent years. Models describing behavior at work and research on momentary behavior indicate that substantial variation exists within individuals. This article examines the rationale behind this body of work and explores a method of analyzing momentary work behavior using experience sampling methods. The article also examines a previously unused set of methods for analyzing data produced by experience sampling. These methods are known collectively as multiway component analysis. Two archetypal techniques of multimode factor analysis, the Parallel factor analysis and the Tucker3 models, are used to analyze data from Miner, Glomb, and Hulin's (2010) experience sampling study of work behavior. The efficacy of these techniques for analyzing experience sampling data is discussed as are the substantive multimode component models obtained.

Space tug propulsion system failure mode, effects and criticality analysis

NASA Technical Reports Server (NTRS)

Boyd, J. W.; Hardison, E. P.; Heard, C. B.; Orourke, J. C.; Osborne, F.; Wakefield, L. T.

1972-01-01

For purposes of the study, the propulsion system was considered as consisting of the following: (1) main engine system, (2) auxiliary propulsion system, (3) pneumatic system, (4) hydrogen feed, fill, drain and vent system, (5) oxygen feed, fill, drain and vent system, and (6) helium reentry purge system. Each component was critically examined to identify possible failure modes and the subsequent effect on mission success. Each space tug mission consists of three phases: launch to separation from shuttle, separation to redocking, and redocking to landing. The analysis considered the results of failure of a component during each phase of the mission. After the failure modes of each component were tabulated, those components whose failure would result in possible or certain loss of mission or inability to return the Tug to ground were identified as critical components and a criticality number determined for each. The criticality number of a component denotes the number of mission failures in one million missions due to the loss of that component. A total of 68 components were identified as critical with criticality numbers ranging from 1 to 2990.

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Modulation by EEG features of BOLD responses to interictal epileptiform discharges

PubMed Central

LeVan, Pierre; Tyvaert, Louise; Gotman, Jean

2013-01-01

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

Analysis of the Environmental Impact on Remanufacturing Wind Turbines

NASA Astrophysics Data System (ADS)

Sosa Skrainka, Manuel R.

To deliver clean energy the use of wind turbines is essential. In June 2011 there was an installed wind capacity equivalent to 211,000MW world-wide (WWEA, 2011). By the end of the year 2009 the U.S. had 35,100MW of wind energy installed capacity to generate electricity (AWEA, 2010). This industry has grown in recent years and is expected to grow even more in the future. The environmental impacts that will arise from the increased number of wind turbines and their end-of-life should be addressed, as large amounts of resources will be required to satisfy the current and future market demands for wind turbines. Since future 10MW wind turbines are expected to be as heavy as 1000 tons each, the study of the environmental response of profitable retirement strategies, such as remanufacturing for these machines, must be considered. Because of the increased number of wind turbines and the materials used, this study provides a comparison between the environmental impacts from remanufacturing the components installed inside the nacelle of multi-megawatt wind turbines and wind turbines manufactured using new components. The study methodology is the following: • Describe the life-cycle and the materials and processes employed for the manufacture and remanufacturing for components inside the nacelle. • Identify remanufacturing alternatives for the components inside the nacelle at the end of the expected life-time service of wind turbines. • Evaluate the environmental impacts from the remanufactured components and compare the results with the impacts of the manufacturing of new components using SimaPro. • Conduct sensitivity analysis over the critical parameters of the life cycle assessment • Propose the most environmentally friendly options for the retirement of each major component of wind turbines. After an analysis of the scenarios the goal of the study is to evaluate remanufacturing as an end-of-life option from an environmental perspective for commercial multi-megawatt wind turbines targeted for secondary wind turbine markets.

Interaction of dissolution, sorption and biodegradation on transport of BTEX in a saturated groundwater system: Numerical modeling and spatial moment analysis

NASA Astrophysics Data System (ADS)

Valsala, Renu; Govindarajan, Suresh Kumar

2018-06-01

Interaction of various physical, chemical and biological transport processes plays an important role in deciding the fate and migration of contaminants in groundwater systems. In this study, a numerical investigation on the interaction of various transport processes of BTEX in a saturated groundwater system is carried out. In addition, the multi-component dissolution from a residual BTEX source under unsteady flow conditions is incorporated in the modeling framework. The model considers Benzene, Toluene, Ethyl Benzene and Xylene dissolving from the residual BTEX source zone to undergo sorption and aerobic biodegradation within the groundwater aquifer. Spatial concentration profiles of dissolved BTEX components under the interaction of various sorption and biodegradation conditions have been studied. Subsequently, a spatial moment analysis is carried out to analyze the effect of interaction of various transport processes on the total dissolved mass and the mobility of dissolved BTEX components. Results from the present numerical study suggest that the interaction of dissolution, sorption and biodegradation significantly influence the spatial distribution of dissolved BTEX components within the saturated groundwater system. Mobility of dissolved BTEX components is also found to be affected by the interaction of these transport processes.

The Value of Distributed Solar Electric Generation to San Antonio

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

Jones, Nic; Norris, Ben; Meyer, Lisa

2013-02-14

This report presents an analysis of value provided by grid-connected, distributed PV in San Antonio from a utility perspective. The study quantified six value components, summarized in Table ES- 1. These components represent the benefits that accrue to the utility, CPS Energy, in accepting solar onto the grid. This analysis does not treat the compensation of value, policy objectives, or cost-effectiveness from the retail consumer perspective.

Inventory of File sref.t03z.pgrb216.mean_3hrly.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] wt ens-mean 002 10 m above ground VGRD analysis V-Component of Wind [m/s] wt ens-mean 003 1000 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 004 850 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 005 700 mb UGRD analysis U-Component of Wind [m/s] wt ens

Inventory of File sref.t03z.pgrb212.spread_3hrly.grib2

Science.gov Websites

ground UGRD analysis U-Component of Wind [m/s] std dev 002 10 m above ground VGRD analysis V-Component of Wind [m/s] std dev 003 1000 mb UGRD analysis U-Component of Wind [m/s] std dev 004 850 mb UGRD analysis U-Component of Wind [m/s] std dev 005 700 mb UGRD analysis U-Component of Wind [m/s] std dev 006 600

Inventory of File sref.t03z.pgrb243.mean_3hrly.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] wt ens-mean 002 10 m above ground VGRD analysis V-Component of Wind [m/s] wt ens-mean 003 1000 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 004 850 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 005 700 mb UGRD analysis U-Component of Wind [m/s] wt ens

Inventory of File sref.t03z.pgrb216.spread_3hrly.grib2

Science.gov Websites

ground UGRD analysis U-Component of Wind [m/s] std dev 002 10 m above ground VGRD analysis V-Component of Wind [m/s] std dev 003 1000 mb UGRD analysis U-Component of Wind [m/s] std dev 004 850 mb UGRD analysis U-Component of Wind [m/s] std dev 005 700 mb UGRD analysis U-Component of Wind [m/s] std dev 006 600

Inventory of File sref.t03z.pgrb243.spread_3hrly.grib2

Science.gov Websites

ground UGRD analysis U-Component of Wind [m/s] std dev 002 10 m above ground VGRD analysis V-Component of Wind [m/s] std dev 003 1000 mb UGRD analysis U-Component of Wind [m/s] std dev 004 850 mb UGRD analysis U-Component of Wind [m/s] std dev 005 700 mb UGRD analysis U-Component of Wind [m/s] std dev 006 600

Inventory of File sref.t03z.pgrb212.mean_3hrly.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] wt ens-mean 002 10 m above ground VGRD analysis V-Component of Wind [m/s] wt ens-mean 003 1000 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 004 850 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 005 700 mb UGRD analysis U-Component of Wind [m/s] wt ens

Inventory of File sref.t03z.pgrb132.spread_3hrly.grib2

Science.gov Websites

ground UGRD analysis U-Component of Wind [m/s] std dev 002 10 m above ground VGRD analysis V-Component of Wind [m/s] std dev 003 1000 mb UGRD analysis U-Component of Wind [m/s] std dev 004 850 mb UGRD analysis U-Component of Wind [m/s] std dev 005 700 mb UGRD analysis U-Component of Wind [m/s] std dev 006 600

Inventory of File sref.t03z.pgrb132.mean_3hrly.grib2

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] wt ens-mean 002 10 m above ground VGRD analysis V-Component of Wind [m/s] wt ens-mean 003 1000 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 004 850 mb UGRD analysis U-Component of Wind [m/s] wt ens-mean 005 700 mb UGRD analysis U-Component of Wind [m/s] wt ens

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

PubMed

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

2017-09-01

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

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

PubMed

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

2016-11-22

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

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

PubMed Central

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

2016-01-01

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

Application of principal component analysis for the optimisation of lead(II) biosorption.

PubMed

Wajda, Łukasz; Duda-Chodak, Aleksandra; Tarko, Tomasz; Kamiński, Paweł

2017-10-03

Current study was focused on optimising lead(II) biosorption carried out by living cells of Arthrospira platensis using Principal Component Analysis. Various experimental conditions were considered: initial metal concentration (50 and 100 mg/l), solution pH (4.0, 4.5, 5.0, 5.5) and contact time (10, 20, 30, 40, 50 and 60 min) at constant rotary speed 200 rpm. It was found that when the biomass was separated from experimental solutions by the filtration, almost 50% of initial metal dose was removed by the filter paper. Moreover, pH was the most important parameter influencing examined processes. The Principal Component Analysis indicated that the most optimum conditions for lead(II) biosorption were metal initial concentration 100 mg/l, pH 4.5 and time 60 min. According to the analysis of the first component it might be stated that the lead(II) uptake increases in time. In overall, it was found to be useful for analysing data obtained in biosorption experiments and eliminating insignificant experimental conditions. Experimental data fitted Langmuir and Dubinin-Radushkevich models indicating that physical and chemical absorption take place at the same time. Further studies are necessary to verify how sorption-desorption cycles affect A. platensis cells.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Effect of rotational alignment on outcome of total knee arthroplasty

PubMed Central

Breugem, Stefan J; van den Bekerom, Michel PJ; Tuinebreijer, Willem E; van Geenen, Rutger C I

2015-01-01

Background and purpose Poor outcomes have been linked to errors in rotational alignment of total knee arthroplasty components. The aims of this study were to determine the correlation between rotational alignment and outcome, to review the success of revision for malrotated total knee arthroplasty, and to determine whether evidence-based guidelines for malrotated total knee arthroplasty can be proposed. Patients and methods We conducted a systematic review including all studies reporting on both rotational alignment and functional outcome. Comparable studies were used in a correlation analysis and results of revision were analyzed separately. Results 846 studies were identified, 25 of which met the inclusion criteria. From this selection, 11 studies could be included in the correlation analysis. A medium positive correlation (ρ = 0.44, 95% CI: 0.27–0.59) and a large positive correlation (ρ = 0.68, 95% CI: 0.64–0.73) were found between external rotation of the tibial component and the femoral component, respectively, and the Knee Society score. Revision for malrotation gave positive results in all 6 studies in this field. Interpretation Medium and large positive correlations were found between tibial and femoral component rotational alignment on the one hand and better functional outcome on the other. Revision of malrotated total knee arthroplasty may be successful. However, a clear cutoff point for revision for malrotated total knee arthroplasty components could not be identified. PMID:25708694

Analysis of CYP3A inhibitory components of star fruit (Averrhoa carambola L.) using liquid chromatography-mass spectrometry.

PubMed

Hosoi, Shinzo; Shimizu, Eri; Arimori, Kazuhiko; Okumura, Manabu; Hidaka, Muneaki; Yamada, Mitsuko; Sakushima, Akiyo

2008-07-01

In this study, we analyzed the CYP3A inhibitory components of star fruit Averrhoa carambola L., using liquid chromatography-mass spectrometry (LC-MS). The stereoisomer of procyanidin B1 and B2 and/or the trimer consisting of catechin and/or epicatechin were suggested to be potent inhibitory components.

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

PubMed

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

2011-01-01

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

Component Analyses Using Single-Subject Experimental Designs: A Review

ERIC Educational Resources Information Center

Ward-Horner, John; Sturmey, Peter

2010-01-01

A component analysis is a systematic assessment of 2 or more independent variables or components that comprise a treatment package. Component analyses are important for the analysis of behavior; however, previous research provides only cursory descriptions of the topic. Therefore, in this review the definition of "component analysis" is discussed,…

QUINCE System; State-of-the-Art Review

DTIC Science & Technology

1978-06-01

linguistic data base in terms of semantic feature set, interlingual transfer component, contrastive lexical/syntactic studies and contextual analysis ...and Syntactical Studies 3.3.1 Contrastlve Lexical Studies 3.3.2 Contrastlve Syntactic Studies 3.4 Contextual Analysis 3.4.1 Elided Subjects...and English, combined with contextual analysis of language- specific characteristics of Chinese ^re offered as the most promising solutions In this

A component-centered meta-analysis of family-based prevention programs for adolescent substance use.

PubMed

Van Ryzin, Mark J; Roseth, Cary J; Fosco, Gregory M; Lee, You-Kyung; Chen, I-Chien

2016-04-01

Although research has documented the positive effects of family-based prevention programs, the field lacks specific information regarding why these programs are effective. The current study summarized the effects of family-based programs on adolescent substance use using a component-based approach to meta-analysis in which we decomposed programs into a set of key topics or components that were specifically addressed by program curricula (e.g., parental monitoring/behavior management,problem solving, positive family relations, etc.). Components were coded according to the amount of time spent on program services that targeted youth, parents, and the whole family; we also coded effect sizes across studies for each substance-related outcome. Given the nested nature of the data, we used hierarchical linear modeling to link program components (Level 2) with effect sizes (Level 1). The overall effect size across programs was .31, which did not differ by type of substance. Youth-focused components designed to encourage more positive family relationships and a positive orientation toward the future emerged as key factors predicting larger than average effect sizes. Our results suggest that, within the universe of family-based prevention, where components such as parental monitoring/behavior management are almost universal, adding or expanding certain youth-focused components may be able to enhance program efficacy. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comparison of short term radiological alignment outcomes of the patient specific and standard instrumentation for primary total knee arthroplasty: A systematic review and meta-analysis.

PubMed

Alcelik, Ilhan; Blomfield, Mark; Öztürk, Cenk; Soni, Ashish; Charity, Richard; Acornley, Alex

2017-05-01

The aim of this study was to review the radiological alignment outcomes of patient Specific (PS) cutting blocks and Standard Instrumentation in Primary Total Knee Arthroplasty. We hypothesized that the use of PS techniques would significantly improve sagittal, coronal and rotational alignment of the prosthesis on short term. We performed a systematic review and a meta-analysis including all the randomised controlled trials (RCT) using PS and standard (ST) total knee arthroplasty to date. A total of 538 PS TKA and 549 ST TKA were included in the study. Statistical analysis of the outliers for femoral component sagittal, coronal and rotational positioning, tibial component sagittal and coronal positioning and the overall mechanical axis were assessed. We found that there was no significant benefit from using PS instrumentation in primary knee arthroplasty to aid in the positioning of either the tibial or femoral components. Furthermore sagittal plane tibial component positioning was worse in the PS than the traditional ST group. Our results suggest that at present PS instrumentation is not superior to ST instrumentation in primary total knee arthroplasty. Level 1, Systematic review of therapeutic studies. Copyright © 2017 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Pricing and components analysis of some key essential pediatric medicine in Odisha state

PubMed Central

Samal, Satyajit; Swain, Trupti Rekha

2017-01-01

Objective: Study highlighting prices, i.e., the patients actually pay at ground level is important for interventions such as alternate procurement schemes or to expedite regulatory assessment of essential medicines for children. The present study was undertaken to study pricing and component analysis of few key essential medicines in Odisha state. Methodology: Six child-specific medicines of different formulations were selected based on use in different disease condition and having widest pricing variation. Data were collected, entered, and analyzed in the price components data collection form of the World Health Organization-Health Action International (WHO-HAI) 2007 Workbook version 5 – Part II provided as part of the WHO/HAI methodology. The analysis includes the cumulative percent markup, total cumulative percent markup, and percent contribution of individual components to the final medicine price in both public and private sector of Odisha state. Results: Add-on costs such as taxes, wholesale, and retail markups contribute substantially to the final price of medicines in private sector, particularly for branded-generic products. The largest contributor to add-on costs is at the level of retailer shop. Conclusion: Policy should be framed to achieve a greater transparency and uniformity of the pricing of medicines at different health sectors of Odisha. PMID:28458429

NHEXAS PHASE I MARYLAND STUDY--LIST OF AVAILABLE DOCUMENTS: PROTOCOLS AND SOPS

EPA Science Inventory

This document lists available protocols and SOPs for the NHEXAS Phase I Maryland study. It identifies protocols and SOPs for the following study components: (1) Sample collection and field operations, (2) Sample analysis and general laboratory procedures, (3) Data Analysis Proced...

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae

PubMed Central

2014-01-01

Background The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Results Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. Conclusion In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus. PMID:24961398

Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae.

PubMed

Liu, Lifang; Feizi, Amir; Österlund, Tobias; Hjort, Carsten; Nielsen, Jens

2014-06-24

The koji mold, Aspergillus oryzae is widely used for the production of industrial enzymes due to its particularly high protein secretion capacity and ability to perform post-translational modifications. However, systemic analysis of its secretion system is lacking, generally due to the poorly annotated proteome. Here we defined a functional protein secretory component list of A. oryzae using a previously reported secretory model of S. cerevisiae as scaffold. Additional secretory components were obtained by blast search with the functional components reported in other closely related fungal species such as Aspergillus nidulans and Aspergillus niger. To evaluate the defined component list, we performed transcriptome analysis on three α-amylase over-producing strains with varying levels of secretion capacities. Specifically, secretory components involved in the ER-associated processes (including components involved in the regulation of transport between ER and Golgi) were significantly up-regulated, with many of them never been identified for A. oryzae before. Furthermore, we defined a complete list of the putative A. oryzae secretome and monitored how it was affected by overproducing amylase. In combination with the transcriptome data, the most complete secretory component list and the putative secretome, we improved the systemic understanding of the secretory machinery of A. oryzae in response to high levels of protein secretion. The roles of many newly predicted secretory components were experimentally validated and the enriched component list provides a better platform for driving more mechanistic studies of the protein secretory pathway in this industrially important fungus.

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.

Analysis of truss, beam, frame, and membrane components. [composite structures

NASA Technical Reports Server (NTRS)

Knoell, A. C.; Robinson, E. Y.

1975-01-01

Truss components are considered, taking into account composite truss structures, truss analysis, column members, and truss joints. Beam components are discussed, giving attention to composite beams, laminated beams, and sandwich beams. Composite frame components and composite membrane components are examined. A description is given of examples of flat membrane components and examples of curved membrane elements. It is pointed out that composite structural design and analysis is a highly interactive, iterative procedure which does not lend itself readily to characterization by design or analysis function only.-

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.

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.

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

PubMed

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

2000-06-01

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

Micrometer-scale particle sizing by laser diffraction: critical impact of the imaginary component of refractive index.

PubMed

Beekman, Alice; Shan, Daxian; Ali, Alana; Dai, Weiguo; Ward-Smith, Stephen; Goldenberg, Merrill

2005-04-01

This study evaluated the effect of the imaginary component of the refractive index on laser diffraction particle size data for pharmaceutical samples. Excipient particles 1-5 microm in diameter (irregular morphology) were measured by laser diffraction. Optical parameters were obtained and verified based on comparison of calculated vs. actual particle volume fraction. Inappropriate imaginary components of the refractive index can lead to inaccurate results, including false peaks in the size distribution. For laser diffraction measurements, obtaining appropriate or "effective" imaginary components of the refractive index was not always straightforward. When the recommended criteria such as the concentration match and the fit of the scattering data gave similar results for very different calculated size distributions, a supplemental technique, microscopy with image analysis, was used to decide between the alternatives. Use of effective optical parameters produced a good match between laser diffraction data and microscopy/image analysis data. The imaginary component of the refractive index can have a major impact on particle size results calculated from laser diffraction data. When performed properly, laser diffraction and microscopy with image analysis can yield comparable results.

Components of Environmental Literacy in Elementary Science Education Curriculum in Bulgaria and Turkey

ERIC Educational Resources Information Center

Erdogan, Mehmet; Kostova, Zdravka; Marcinkowski, Thomas

2009-01-01

The purpose of this study was to analyze the extent to which science education objectives in elementary schools addressed to the six basic components of environmental literacy (EL), and how this attention differed from Bulgaria to Turkey. The main method in the study involved comparative content analysis of these objectives. The courses sampled…

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Temperament and problem solving in a population of adolescent guide dogs.

PubMed

Bray, Emily E; Sammel, Mary D; Seyfarth, Robert M; Serpell, James A; Cheney, Dorothy L

2017-09-01

It is often assumed that measures of temperament within individuals are more correlated to one another than to measures of problem solving. However, the exact relationship between temperament and problem-solving tasks remains unclear because large-scale studies have typically focused on each independently. To explore this relationship, we tested 119 prospective adolescent guide dogs on a battery of 11 temperament and problem-solving tasks. We then summarized the data using both confirmatory factor analysis and exploratory principal components analysis. Results of confirmatory analysis revealed that a priori separation of tests as measuring either temperament or problem solving led to weak results, poor model fit, some construct validity, and no predictive validity. In contrast, results of exploratory analysis were best summarized by principal components that mixed temperament and problem-solving traits. These components had both construct and predictive validity (i.e., association with success in the guide dog training program). We conclude that there is complex interplay between tasks of "temperament" and "problem solving" and that the study of both together will be more informative than approaches that consider either in isolation.

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.

Electroencephalographic dynamics of musical emotion perception revealed by independent spectral components.

PubMed

Lin, Yuan-Pin; Duann, Jeng-Ren; Chen, Jyh-Horng; Jung, Tzyy-Ping

2010-04-21

This study explores the electroencephalographic (EEG) correlates of emotional experience during music listening. Independent component analysis and analysis of variance were used to separate statistically independent spectral changes of the EEG in response to music-induced emotional processes. An independent brain process with equivalent dipole located in the fronto-central region exhibited distinct δ-band and θ-band power changes associated with self-reported emotional states. Specifically, the emotional valence was associated with δ-power decreases and θ-power increases in the frontal-central area, whereas the emotional arousal was accompanied by increases in both δ and θ powers. The resultant emotion-related component activations that were less interfered by the activities from other brain processes complement previous EEG studies of emotion perception to music.

New preparation method of {beta}{double_prime}-alumina and application for AMTEC

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

Nishi, Toshiro; Tsuru, Yasuhiko; Yamamoto, Hirokazu

1995-12-31

The Alkali Metal Thermo-Electric Converter(AMTEC) is an energy conversion system that converts heat to electrical energy with high efficiency. The {beta}{double_prime}-alumina solid electrolyte (BASE) is the most important component in the AMTEC system. In this paper, the relationship among the conduction property, the microstructure and the amount of chemical component for BASE is studied. As an analysis of the chemical reaction for each component, the authors established a new BASE preparation method rather than using the conventional method. They also report the AMTFC cell performance using this electrolyte tube on which Mo or TiC electrode is filmed by the screenmore » printing method. Then, an electrochemical analysis and a heat cycle test of AMTEC cell are studied.« less

Revealing the Structural Complexity of Component Interactions of Topic-Specific PCK when Planning to Teach

NASA Astrophysics Data System (ADS)

Mavhunga, Elizabeth

2018-04-01

Teaching pedagogical content knowledge (PCK) at a topic-specific level requires clarity on the content-specific nature of the components employed, as well as the specific features that bring about the desirable depth in teacher explanations. Such understanding is often hazy; yet, it influences the nature of teacher tasks and learning opportunities afforded to pre-service teachers in a teaching program. The purpose of this study was twofold: firstly, to illuminate the emerging complexity when content-specific components of PCK interact when planning to teach a chemistry topic; and secondly, to identify the kinds of teacher tasks that promote the emergence of such complexity. Data collected were content representations (CoRes) in chemical equilibrium accompanied by expanded lesson outlines from 15 pre-service teachers in their final year of study towards a first degree in teaching (B Ed). The analysis involved extraction of episodes that exhibited component interaction by using a qualitative in-depth analysis method. The results revealed the structure in which the components of PCK in a topic interact among each other to be linear, interwoven, or a combination of the two. The interwoven interactions contained multiple components that connected explanations on different aspects of a concept, all working in a complementary manner. The most sophisticated component interactions emerged from teacher tasks on descriptions of a lesson sequence and a summary of a lesson. Recommendations in this study highlight core practices for making pedagogical transformation of topic content knowledge more accessible.

Convection equation modeling: A non-iterative direct matrix solution algorithm for use with SINDA

NASA Technical Reports Server (NTRS)

Schrage, Dean S.

1993-01-01

The determination of the boundary conditions for a component-level analysis, applying discrete finite element and finite difference modeling techniques often requires an analysis of complex coupled phenomenon that cannot be described algebraically. For example, an analysis of the temperature field of a coldplate surface with an integral fluid loop requires a solution to the parabolic heat equation and also requires the boundary conditions that describe the local fluid temperature. However, the local fluid temperature is described by a convection equation that can only be solved with the knowledge of the locally-coupled coldplate temperatures. Generally speaking, it is not computationally efficient, and sometimes, not even possible to perform a direct, coupled phenomenon analysis of the component-level and boundary condition models within a single analysis code. An alternative is to perform a disjoint analysis, but transmit the necessary information between models during the simulation to provide an indirect coupling. For this approach to be effective, the component-level model retains full detail while the boundary condition model is simplified to provide a fast, first-order prediction of the phenomenon in question. Specifically for the present study, the coldplate structure is analyzed with a discrete, numerical model (SINDA) while the fluid loop convection equation is analyzed with a discrete, analytical model (direct matrix solution). This indirect coupling allows a satisfactory prediction of the boundary condition, while not subjugating the overall computational efficiency of the component-level analysis. In the present study a discussion of the complete analysis of the derivation and direct matrix solution algorithm of the convection equation is presented. Discretization is analyzed and discussed to extend of solution accuracy, stability and computation speed. Case studies considering a pulsed and harmonic inlet disturbance to the fluid loop are analyzed to assist in the discussion of numerical dissipation and accuracy. In addition, the issues of code melding or integration with standard class solvers such as SINDA are discussed to advise the user of the potential problems to be encountered.

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

PubMed

Flanagan, Sarah P; Jones, Adam G

2017-04-01

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

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.

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

PubMed

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

2015-01-01

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

Chemical information obtained from Auger depth profiles by means of advanced factor analysis (MLCFA)

NASA Astrophysics Data System (ADS)

De Volder, P.; Hoogewijs, R.; De Gryse, R.; Fiermans, L.; Vennik, J.

1993-01-01

The advanced multivariate statistical technique "maximum likelihood common factor analysis (MLCFA)" is shown to be superior to "principal component analysis (PCA)" for decomposing overlapping peaks into their individual component spectra of which neither the number of components nor the peak shape of the component spectra is known. An examination of the maximum resolving power of both techniques, MLCFA and PCA, by means of artificially created series of multicomponent spectra confirms this finding unambiguously. Substantial progress in the use of AES as a chemical-analysis technique is accomplished through the implementation of MLCFA. Chemical information from Auger depth profiles is extracted by investigating the variation of the line shape of the Auger signal as a function of the changing chemical state of the element. In particular, MLCFA combined with Auger depth profiling has been applied to problems related to steelcord-rubber tyre adhesion. MLCFA allows one to elucidate the precise nature of the interfacial layer of reaction products between natural rubber vulcanized on a thin brass layer. This study reveals many interesting chemical aspects of the oxi-sulfidation of brass undetectable with classical AES.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

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

PubMed

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

2008-12-01

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

Relationship between Metabolic Syndrome Components and Periodontal Disease in a Japanese General Population: the Suita Study.

PubMed

Kikui, Miki; Kokubo, Yoshihiro; Ono, Takahiro; Kida, Momoyo; Kosaka, Takayuki; Yamamoto, Masaaki; Watanabe, Makoto; Maeda, Yoshinobu; Miyamoto, Yoshihiro

2017-05-01

A positive association between metabolic syndrome (MetS) and periodontal status has recently been noted. However, no study has evaluated the relationship by sex and in a general urban population using the uniform definition proposed in the 2009 Joint Interim Statement. The aim of this study was to clarify the relationship between MetS and periodontal status using the uniform definition in a general urban Japanese population. A total of 1,856 Japanese men and women (mean age: 66.4 years) were studied using data from the Suita study. Periodontal status was evaluated by the Community Periodontal Index (CPI). MetS was defined using the 2009 Joint Interim Statement. The associations of the MetS and its components with periodontal disease were investigated using multiple logistic regression analysis adjusting for age, drinking, and smoking. Among the components of the MetS, low HDL cholesterol level was significantly associated with periodontal disease in men and women [odds ratios (OR)=2.39 and 1.53; 95% confidence intervals=1.36-4.19 and 1.06-2.19]. Furthermore, the risk of periodontal disease showed 1.43-, 1.42-, and 1.89-fold increases in those with 2, 3, and ≥4 components, respectively, compared with those having no components (P trend ＜0.001). For the analysis by sex, the risk of periodontal disease was increased 2.27- and 1.76-fold in those with ≥4 components in men and women, respectively (both P trend =0.001). These findings suggest that MetS and lower HDL cholesterol are associated with periodontal disease. Subjects with two or more MetS components had a significantly higher prevalence of periodontal disease.

Relationship between Metabolic Syndrome Components and Periodontal Disease in a Japanese General Population: the Suita Study

PubMed Central

Kikui, Miki; Kokubo, Yoshihiro; Kida, Momoyo; Kosaka, Takayuki; Yamamoto, Masaaki; Watanabe, Makoto; Maeda, Yoshinobu; Miyamoto, Yoshihiro

2017-01-01

Aim: A positive association between metabolic syndrome (MetS) and periodontal status has recently been noted. However, no study has evaluated the relationship by sex and in a general urban population using the uniform definition proposed in the 2009 Joint Interim Statement. The aim of this study was to clarify the relationship between MetS and periodontal status using the uniform definition in a general urban Japanese population. Methods: A total of 1,856 Japanese men and women (mean age: 66.4 years) were studied using data from the Suita study. Periodontal status was evaluated by the Community Periodontal Index (CPI). MetS was defined using the 2009 Joint Interim Statement. The associations of the MetS and its components with periodontal disease were investigated using multiple logistic regression analysis adjusting for age, drinking, and smoking. Results: Among the components of the MetS, low HDL cholesterol level was significantly associated with periodontal disease in men and women [odds ratios (OR) = 2.39 and 1.53; 95% confidence intervals = 1.36–4.19 and 1.06–2.19]. Furthermore, the risk of periodontal disease showed 1.43-, 1.42-, and 1.89-fold increases in those with 2, 3, and ≥ 4 components, respectively, compared with those having no components (Ptrend < 0.001). For the analysis by sex, the risk of periodontal disease was increased 2.27- and 1.76-fold in those with ≥ 4 components in men and women, respectively (both Ptrend = 0.001). Conclusion: These findings suggest that MetS and lower HDL cholesterol are associated with periodontal disease. Subjects with two or more MetS components had a significantly higher prevalence of periodontal disease. PMID:27725400

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

PubMed

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

2014-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

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.

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

PubMed

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

2015-12-01

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

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

PubMed

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

2018-06-19

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

Comparative study on fast classification of brick samples by combination of principal component analysis and linear discriminant analysis using stand-off and table-top laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Vítková, Gabriela; Prokeš, Lubomír; Novotný, Karel; Pořízka, Pavel; Novotný, Jan; Všianský, Dalibor; Čelko, Ladislav; Kaiser, Jozef

2014-11-01

Focusing on historical aspect, during archeological excavation or restoration works of buildings or different structures built from bricks it is important to determine, preferably in-situ and in real-time, the locality of bricks origin. Fast classification of bricks on the base of Laser-Induced Breakdown Spectroscopy (LIBS) spectra is possible using multivariate statistical methods. Combination of principal component analysis (PCA) and linear discriminant analysis (LDA) was applied in this case. LIBS was used to classify altogether the 29 brick samples from 7 different localities. Realizing comparative study using two different LIBS setups - stand-off and table-top it is shown that stand-off LIBS has a big potential for archeological in-field measurements.

Metabolite profiling of soy sauce using gas chromatography with time-of-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis.

PubMed

Yamamoto, Shinya; Bamba, Takeshi; Sano, Atsushi; Kodama, Yukako; Imamura, Miho; Obata, Akio; Fukusaki, Eiichiro

2012-08-01

Soy sauces, produced from different ingredients and brewing processes, have variations in components and quality. Therefore, it is extremely important to comprehend the relationship between components and the sensory attributes of soy sauces. The current study sought to perform metabolite profiling in order to devise a method of assessing the attributes of soy sauces. Quantitative descriptive analysis (QDA) data for 24 soy sauce samples were obtained from well selected sensory panelists. Metabolite profiles primarily concerning low-molecular-weight hydrophilic components were based on gas chromatography with time-of-flightmass spectrometry (GC/TOFMS). QDA data for soy sauces were accurately predicted by projection to latent structure (PLS), with metabolite profiles serving as explanatory variables and QDA data set serving as a response variable. Moreover, analysis of correlation between matrices of metabolite profiles and QDA data indicated contributing compounds that were highly correlated with QDA data. Especially, it was indicated that sugars are important components of the tastes of soy sauces. This new approach which combines metabolite profiling with QDA is applicable to analysis of sensory attributes of food as a result of the complex interaction between its components. This approach is effective to search important compounds that contribute to the attributes. Copyright © 2012 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Economic sustainability assessment in semi-steppe rangelands.

PubMed

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

2018-05-08

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

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

Profiling study of the major and minor components of kaffir lime oil (Citrus hystrix DC.) in the fractional distillation process.

PubMed

Warsito, Warsito; Palungan, Maimunah Hindun; Utomo, Edy Priyo

2017-01-01

Essential oil is consisting of complex component. It is divided into major and minor component. Therefore, this study aims to examine the distribution of major and minor components on Kaffir lime oil by using fractional distillation. Fractional distillation and distributional analysis of components within fractions have been performed on kaffir lime oil ( Citrus hystrix DC .). Fractional distillation was performed by using PiloDist 104-VTU, column length of 2 m (number of plate 120), the system pressure was set on 5 and 10 mBar, while the reflux ratio varied on 10/10, 20/10 and 60/10, and the chemical composition analysis was done by using GC-MS. Chemical composition of the distillated lime oil consisted of mix-twigs and leaves that composed of 20 compounds, with five main components β-citronellal (46.40%), L-linalool (13.11%), β-citronellol (11.03%), citronelyl acetate (6.76%) and sabinen (5.91%). The optimum conditions for fractional distillation were obtained at 5 mBar pressure with reflux ratio of 10/10. Components of β -citronellal and L-linalool were distributed in the fraction-1 to fraction 9, hydrocarbon monoterpenes components were distributed only on the fraction-1 to fraction 4, while the oxygenated monoterpenes components dominated the fraction-5 to fraction-9. The highest level of β-citronellal was 84.86% (fraction-7), L-linalool 20.13% (fraction-5), sabinen 19.83% (fraction-1), and the component level of 4-terpeneol, β-citronellol and sitronelyl acetate respectively 7.16%; 12.27%; 5.22% (fraction-9).

Integrated Droplet-Based Microextraction with ESI-MS for Removal of Matrix Interference in Single-Cell Analysis.

PubMed

Zhang, Xiao-Chao; Wei, Zhen-Wei; Gong, Xiao-Yun; Si, Xing-Yu; Zhao, Yao-Yao; Yang, Cheng-Dui; Zhang, Si-Chun; Zhang, Xin-Rong

2016-04-29

Integrating droplet-based microfluidics with mass spectrometry is essential to high-throughput and multiple analysis of single cells. Nevertheless, matrix effects such as the interference of culture medium and intracellular components influence the sensitivity and the accuracy of results in single-cell analysis. To resolve this problem, we developed a method that integrated droplet-based microextraction with single-cell mass spectrometry. Specific extraction solvent was used to selectively obtain intracellular components of interest and remove interference of other components. Using this method, UDP-Glc-NAc, GSH, GSSG, AMP, ADP and ATP were successfully detected in single MCF-7 cells. We also applied the method to study the change of unicellular metabolites in the biological process of dysfunctional oxidative phosphorylation. The method could not only realize matrix-free, selective and sensitive detection of metabolites in single cells, but also have the capability for reliable and high-throughput single-cell analysis.

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

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1998-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Empirical studies of solar flares: Comparison of X-ray and H alpha filtergrams and analysis of the energy balance of the X-ray plasma

NASA Technical Reports Server (NTRS)

Moore, R. L.

1979-01-01

The physics of solar flares was investigated through a combined analysis of X-ray filtergrams of the high temperature coronal component of flares and H alpha filtergrams of the low temperature chromospheric component. The data were used to study the magnetic field configuration and its changes in solar flares, and to examine the chromospheric location and structure of X-ray bright points (XPB) and XPB flares. Each topic and the germane data are discussed. The energy balance of the thermal X-ray plasma in flares, while not studied, is addressed.

Building energy analysis tool

DOEpatents

Brackney, Larry; Parker, Andrew; Long, Nicholas; Metzger, Ian; Dean, Jesse; Lisell, Lars

2016-04-12

A building energy analysis system includes a building component library configured to store a plurality of building components, a modeling tool configured to access the building component library and create a building model of a building under analysis using building spatial data and using selected building components of the plurality of building components stored in the building component library, a building analysis engine configured to operate the building model and generate a baseline energy model of the building under analysis and further configured to apply one or more energy conservation measures to the baseline energy model in order to generate one or more corresponding optimized energy models, and a recommendation tool configured to assess the one or more optimized energy models against the baseline energy model and generate recommendations for substitute building components or modifications.

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.

Modeling of power electronic systems with EMTP

NASA Technical Reports Server (NTRS)

Tam, Kwa-Sur; Dravid, Narayan V.

1989-01-01

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

Cell module and fuel conditioner development

NASA Technical Reports Server (NTRS)

Feret, J. M.

1981-01-01

A phosphoric acid fuel cell (PAFC) stack design having a 10 kW power rating for operation at higher than atmospheric pressure based on the existing Mark II design configuration is described. Functional analysis, trade studies and thermodynamic cycle analysis for requirements definition and system operating parameter selection purposes were performed. Fuel cell materials and components, and performance testing and evaluation of the repeating electrode components were characterized. The state of the art manufacturing technology for all fuel cell components and the fabrication of short stacks of various sites were established. A 10 kW PAFC stack design for higher pressure operation utilizing the top down systems engineering aproach was developed.

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

PAH Baselines for Amazonic Surficial Sediments: A Case of Study in Guajará Bay and Guamá River (Northern Brazil).

PubMed

Rodrigues, Camila Carneiro Dos Santos; Santos, Ewerton; Ramos, Brunalisa Silva; Damasceno, Flaviana Cardoso; Correa, José Augusto Martins

2018-06-01

The 16 priority PAH were determined in sediment samples from the insular zone of Guajará Bay and Guamá River (Southern Amazon River mouth). Low hydrocarbon levels were observed and naphthalene was the most representative PAH. The low molecular weight PAH represented 51% of the total PAH. Statistical analysis showed that the sampling sites are not significantly different. Source analysis by PAH ratios and principal component analysis revealed that PAH are primary from a few rate of fossil fuel combustion, mainly related to the local small community activity. All samples presented no biological stress or damage potencial according to the sediment quality guidelines. This study discuss baselines for PAH in surface sediments from Amazonic aquatic systems based on source determination by PAH ratios and principal component analysis, sediment quality guidelines and through comparison with previous studies data.

Raman structural study of melt-mixed blends of isotactic polypropylene with polyethylene of various densities

NASA Astrophysics Data System (ADS)

Prokhorov, K. A.; Nikolaeva, G. Yu; Sagitova, E. A.; Pashinin, P. P.; Guseva, M. A.; Shklyaruk, B. F.; Gerasin, V. A.

2018-04-01

We report a Raman structural study of melt-mixed blends of isotactic polypropylene with two grades of polyethylene: linear high-density and branched low-density polyethylenes. Raman methods, which had been suggested for the analysis of neat polyethylene and isotactic polypropylene, were modified in this study for quantitative analysis of polyethylene/polypropylene blends. We revealed the dependence of the degree of crystallinity and conformational composition of macromolecules in the blends on relative content of the blend components and preparation conditions (quenching or annealing). We suggested a simple Raman method for evaluation of the relative content of the components in polyethylene/polypropylene blends. The degree of crystallinity of our samples, evaluated by Raman spectroscopy, is in good agreement with the results of analysis by differential scanning calorimetry.

Does the Component Processes Task Assess Text-Based Inferences Important for Reading Comprehension? A Path Analysis in Primary School Children

PubMed Central

Wassenburg, Stephanie I.; de Koning, Björn B.; de Vries, Meinou H.; van der Schoot, Menno

2016-01-01

Using a component processes task (CPT) that differentiates between higher-level cognitive processes of reading comprehension provides important advantages over commonly used general reading comprehension assessments. The present study contributes to further development of the CPT by evaluating the relative contributions of its components (text memory, text inferencing, and knowledge integration) and working memory to general reading comprehension within a single study using path analyses. Participants were 173 third- and fourth-grade children. As hypothesized, knowledge integration was the only component of the CPT that directly contributed to reading comprehension, indicating that the text-inferencing component did not assess inferential processes related to reading comprehension. Working memory was a significant predictor of reading comprehension over and above the component processes. Future research should focus on finding ways to ensure that the text-inferencing component taps into processes important for reading comprehension. PMID:27378989

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

PubMed

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

2017-05-31

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

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

PubMed Central

Fleisch, Elgar

2017-01-01

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

Inventory of File gfs.t06z.pgrb2b.0p25.f000

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 005 1 mb VGRD analysis V-Component of Wind [m/s] 006 1 mb ABSV Temperature [K] 011 2 mb RH analysis Relative Humidity [%] 012 2 mb UGRD analysis U-Component of Wind [m/s ] 013 2 mb VGRD analysis V-Component of Wind [m/s] 014 2 mb ABSV analysis Absolute Vorticity [1/s] 015 2

Inventory of File gfs.t06z.pgrb2b.1p00.f000

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 005 1 mb VGRD analysis V-Component of Wind [m/s] 006 1 mb ABSV Temperature [K] 011 2 mb RH analysis Relative Humidity [%] 012 2 mb UGRD analysis U-Component of Wind [m/s ] 013 2 mb VGRD analysis V-Component of Wind [m/s] 014 2 mb ABSV analysis Absolute Vorticity [1/s] 015 2

Inventory of File gfs.t06z.pgrb2b.0p50.f000

Science.gov Websites

UGRD analysis U-Component of Wind [m/s] 005 1 mb VGRD analysis V-Component of Wind [m/s] 006 1 mb ABSV Temperature [K] 011 2 mb RH analysis Relative Humidity [%] 012 2 mb UGRD analysis U-Component of Wind [m/s ] 013 2 mb VGRD analysis V-Component of Wind [m/s] 014 2 mb ABSV analysis Absolute Vorticity [1/s] 015 2

What Are the Real Procedural Costs of Bariatric Surgery? A Systematic Literature Review of Published Cost Analyses.

PubMed

Doble, Brett; Wordsworth, Sarah; Rogers, Chris A; Welbourn, Richard; Byrne, James; Blazeby, Jane M

2017-08-01

This review aims to evaluate the current literature on the procedural costs of bariatric surgery for the treatment of severe obesity. Using a published framework for the conduct of micro-costing studies for surgical interventions, existing cost estimates from the literature are assessed for their accuracy, reliability and comprehensiveness based on their consideration of seven 'important' cost components. MEDLINE, PubMed, key journals and reference lists of included studies were searched up to January 2017. Eligible studies had to report per-case, total procedural costs for any type of bariatric surgery broken down into two or more individual cost components. A total of 998 citations were screened, of which 13 studies were included for analysis. Included studies were mainly conducted from a US hospital perspective, assessed either gastric bypass or adjustable gastric banding procedures and considered a range of different cost components. The mean total procedural costs for all included studies was US$14,389 (range, US$7423 to US$33,541). No study considered all of the recommended 'important' cost components and estimation methods were poorly reported. The accuracy, reliability and comprehensiveness of the existing cost estimates are, therefore, questionable. There is a need for a comparative cost analysis of the different approaches to bariatric surgery, with the most appropriate costing approach identified to be micro-costing methods. Such an analysis will not only be useful in estimating the relative cost-effectiveness of different surgeries but will also ensure appropriate reimbursement and budgeting by healthcare payers to ensure barriers to access this effective treatment by severely obese patients are minimised.

Multimodal Narrative Inquiry: Six Teacher Candidates Respond

ERIC Educational Resources Information Center

Morawski, Cynthia M.; Rottmann, Jennifer

2016-01-01

In this paper we present findings of a study on the implementation of a multimodal teacher narrative inquiry component, theoretically grounded by Rosenblatt's theory of transaction analysis, methodologically supported by action research and practically enacted by narrative inquiry and multimodal learning. In particular, the component offered…

Inventory of File nam.t00z.grbgrd00.tm00.grib2

Science.gov Websites

Humidity [kg/kg] 009.1 1 hybrid level UGRD analysis U-Component of Wind [m/s] 009.2 1 hybrid level VGRD analysis V-Component of Wind [m/s] 010 1 hybrid level TKE analysis Turbulent Kinetic Energy [J/kg] 011.1 2 hybrid level UGRD analysis U-Component of Wind [m/s] 011.2 2 hybrid level VGRD analysis V-Component of

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

PubMed

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

2017-11-01

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

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.

Authentication of virgin olive oil by a novel curve resolution approach combined with visible spectroscopy.

PubMed

Ferreiro-González, Marta; Barbero, Gerardo F; Álvarez, José A; Ruiz, Antonio; Palma, Miguel; Ayuso, Jesús

2017-04-01

Adulteration of olive oil is not only a major economic fraud but can also have major health implications for consumers. In this study, a combination of visible spectroscopy with a novel multivariate curve resolution method (CR), principal component analysis (PCA) and linear discriminant analysis (LDA) is proposed for the authentication of virgin olive oil (VOO) samples. VOOs are well-known products with the typical properties of a two-component system due to the two main groups of compounds that contribute to the visible spectra (chlorophylls and carotenoids). Application of the proposed CR method to VOO samples provided the two pure-component spectra for the aforementioned families of compounds. A correlation study of the real spectra and the resolved component spectra was carried out for different types of oil samples (n=118). LDA using the correlation coefficients as variables to discriminate samples allowed the authentication of 95% of virgin olive oil samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biochemometrics for Natural Products Research: Comparison of Data Analysis Approaches and Application to Identification of Bioactive Compounds.

PubMed

Kellogg, Joshua J; Todd, Daniel A; Egan, Joseph M; Raja, Huzefa A; Oberlies, Nicholas H; Kvalheim, Olav M; Cech, Nadja B

2016-02-26

A central challenge of natural products research is assigning bioactive compounds from complex mixtures. The gold standard approach to address this challenge, bioassay-guided fractionation, is often biased toward abundant, rather than bioactive, mixture components. This study evaluated the combination of bioassay-guided fractionation with untargeted metabolite profiling to improve active component identification early in the fractionation process. Key to this methodology was statistical modeling of the integrated biological and chemical data sets (biochemometric analysis). Three data analysis approaches for biochemometric analysis were compared, namely, partial least-squares loading vectors, S-plots, and the selectivity ratio. Extracts from the endophytic fungi Alternaria sp. and Pyrenochaeta sp. with antimicrobial activity against Staphylococcus aureus served as test cases. Biochemometric analysis incorporating the selectivity ratio performed best in identifying bioactive ions from these extracts early in the fractionation process, yielding altersetin (3, MIC 0.23 μg/mL) and macrosphelide A (4, MIC 75 μg/mL) as antibacterial constituents from Alternaria sp. and Pyrenochaeta sp., respectively. This study demonstrates the potential of biochemometrics coupled with bioassay-guided fractionation to identify bioactive mixture components. A benefit of this approach is the ability to integrate multiple stages of fractionation and bioassay data into a single analysis.

[Quality evaluation of rhubarb dispensing granules based on multi-component simultaneous quantitative analysis and bioassay].

PubMed

Tan, Peng; Zhang, Hai-Zhu; Zhang, Ding-Kun; Wu, Shan-Na; Niu, Ming; Wang, Jia-Bo; Xiao, Xiao-He

2017-07-01

This study attempts to evaluate the quality of Chinese formula granules by combined use of multi-component simultaneous quantitative analysis and bioassay. The rhubarb dispensing granules were used as the model drug for demonstrative study. The ultra-high performance liquid chromatography (UPLC) method was adopted for simultaneously quantitative determination of the 10 anthraquinone derivatives (such as aloe emodin-8-O-β-D-glucoside) in rhubarb dispensing granules; purgative biopotency of different batches of rhubarb dispensing granules was determined based on compound diphenoxylate tablets-induced mouse constipation model; blood activating biopotency of different batches of rhubarb dispensing granules was determined based on in vitro rat antiplatelet aggregation model; SPSS 22.0 statistical software was used for correlation analysis between 10 anthraquinone derivatives and purgative biopotency, blood activating biopotency. The results of multi-components simultaneous quantitative analysisshowed that there was a great difference in chemical characterizationand certain differences inpurgative biopotency and blood activating biopotency among 10 batches of rhubarb dispensing granules. The correlation analysis showed that the intensity of purgative biopotency was significantly correlated with the content of conjugated anthraquinone glycosides (P<0.01), and the intensity of blood activating biopotency was significantly correlated with the content of free anthraquinone (P<0.01). In summary, the combined use of multi-component simultaneous quantitative analysis and bioassay can achieve objective quantification and more comprehensive reflection on overall quality difference among different batches of rhubarb dispensing granules. Copyright© by the Chinese Pharmaceutical Association.

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

NASA Astrophysics Data System (ADS)

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

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

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

PubMed

Xie, Hong-Bo; Dokos, Socrates

2013-06-01

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

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

Empirical evaluation of grouping of lower urinary tract symptoms: principal component analysis of Tampere Ageing Male Urological Study data.

PubMed

Pöyhönen, Antti; Häkkinen, Jukka T; Koskimäki, Juha; Hakama, Matti; Tammela, Teuvo L J; Auvinen, Anssi

2013-03-01

WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: The ICS has divided LUTS into three groups: storage, voiding and post-micturition symptoms. The classification is based on anatomical, physiological and urodynamic considerations of a theoretical nature. We used principal component analysis (PCA) to determine the inter-correlations of various LUTS, which is a novel approach to research and can strengthen existing knowledge of the phenomenology of LUTS. After we had completed our analyses, another study was published that used a similar approach and results were very similar to those of the present study. We evaluated the constellation of LUTS using PCA of the data from a population-based study that included >4000 men. In our analysis, three components emerged from the 12 LUTS: voiding, storage and incontinence components. Our results indicated that incontinence may be separate from the other storage symptoms and post-micturition symptoms should perhaps be regarded as voiding symptoms. To determine how lower urinary tract symptoms (LUTS) relate to each other and assess if the classification proposed by the International Continence Society (ICS) is consistent with empirical findings. The information on urinary symptoms for this population-based study was collected using a self-administered postal questionnaire in 2004. The questionnaire was sent to 7470 men, aged 30-80 years, from Pirkanmaa County (Finland), of whom 4384 (58.7%) returned the questionnaire. The Danish Prostatic Symptom Score-1 questionnaire was used to evaluate urinary symptoms. Principal component analysis (PCA) was used to evaluate the inter-correlations among various urinary symptoms. The PCA produced a grouping of 12 LUTS into three categories consisting of voiding, storage and incontinence symptoms. Post-micturition symptoms were related to voiding symptoms, but incontinence symptoms were separate from storage symptoms. In the analyses by age group, similar categorization was found at ages 40, 50, 60 and 80 years, but only two groups of symptoms emerged among men aged 70 years. The prevalence among men aged 30 was too low for meaningful analysis. This population-based study suggests that LUTS can be divided into three subgroups consisting of voiding, storage and incontinence symptoms based on their inter-correlations. Our empirical findings suggest an alternative grouping of LUTS. The potential utility of such an approach requires careful consideration. © 2012 BJU International.

Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy

PubMed Central

2014-01-01

Background The primary cell wall of fruits and vegetables is a structure mainly composed of polysaccharides (pectins, hemicelluloses, cellulose). Polysaccharides are assembled into a network and linked together. It is thought that the percentage of components and of plant cell wall has an important influence on mechanical properties of fruits and vegetables. Results In this study the Raman microspectroscopy technique was introduced to the visualization of the distribution of polysaccharides in cell wall of fruit. The methodology of the sample preparation, the measurement using Raman microscope and multivariate image analysis are discussed. Single band imaging (for preliminary analysis) and multivariate image analysis methods (principal component analysis and multivariate curve resolution) were used for the identification and localization of the components in the primary cell wall. Conclusions Raman microspectroscopy supported by multivariate image analysis methods is useful in distinguishing cellulose and pectins in the cell wall in tomatoes. It presents how the localization of biopolymers was possible with minimally prepared samples. PMID:24917885

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

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.

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.

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

PubMed

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

2006-03-01

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

Analysis of Pulsating Components in the Eclipsing Binary Systems LT Herculis, RZ Microscopii, LY Puppis, V632 Scorpii, and V638 Scorpii

NASA Astrophysics Data System (ADS)

Streamer, M.; Bohlsen, T.; Ogmen, Y.

2016-06-01

Eclipsing binary stars are especially valuable for studies of stellar evolution. If pulsating components are also present then the stellar interior can be studied using asteroseismology techniques. We present photometric data and the analysis of the delta Scuti pulsations that we have discovered in five eclipsing binary systems. The systems are: LT Herculis, RZ Microscopii, LY Puppis, V632 Scorpii and V638 Scorpii. The dominant pulsation frequencies range between 13 - 29 cycles per day with semi-amplitudes of 4 - 20 millimagnitudes.

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

PubMed

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

2018-05-17

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

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

PubMed

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

2011-12-01

The fingerprints of artificial Calculus bovis extracts from different solvents were established by ultra-performance liquid chromatography (UPLC) and the anti-bacterial activities of artificial C. bovis extracts on Staphylococcus aureus (S. aureus) growth were studied by microcalorimetry. The UPLC fingerprints were evaluated using hierarchical clustering analysis. Some quantitative parameters obtained from the thermogenic curves of S. aureus growth affected by artificial C. bovis extracts were analyzed using principal component analysis. The spectrum-effect relationships between UPLC fingerprints and anti-bacterial activities were investigated using multi-linear regression analysis. The results showed that peak 1 (taurocholate sodium), peak 3 (unknown compound), peak 4 (cholic acid), and peak 6 (chenodeoxycholic acid) are more significant than the other peaks with the standard parameter estimate 0.453, -0.166, 0.749, 0.025, respectively. So, compounds cholic acid, taurocholate sodium, and chenodeoxycholic acid might be the major anti-bacterial components in artificial C. bovis. Altogether, this work provides a general model of the combination of UPLC chromatography and anti-bacterial effect to study the spectrum-effect relationships of artificial C. bovis extracts, which can be used to discover the main anti-bacterial components in artificial C. bovis or other Chinese herbal medicines with anti-bacterial effects. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Using qualitative comparative analysis in a systematic review of a complex intervention.

PubMed

Kahwati, Leila; Jacobs, Sara; Kane, Heather; Lewis, Megan; Viswanathan, Meera; Golin, Carol E

2016-05-04

Systematic reviews evaluating complex interventions often encounter substantial clinical heterogeneity in intervention components and implementation features making synthesis challenging. Qualitative comparative analysis (QCA) is a non-probabilistic method that uses mathematical set theory to study complex phenomena; it has been proposed as a potential method to complement traditional evidence synthesis in reviews of complex interventions to identify key intervention components or implementation features that might explain effectiveness or ineffectiveness. The objective of this study was to describe our approach in detail and examine the suitability of using QCA within the context of a systematic review. We used data from a completed systematic review of behavioral interventions to improve medication adherence to conduct two substantive analyses using QCA. The first analysis sought to identify combinations of nine behavior change techniques/components (BCTs) found among effective interventions, and the second analysis sought to identify combinations of five implementation features (e.g., agent, target, mode, time span, exposure) found among effective interventions. For each substantive analysis, we reframed the review's research questions to be designed for use with QCA, calibrated sets (i.e., transformed raw data into data used in analysis), and identified the necessary and/or sufficient combinations of BCTs and implementation features found in effective interventions. Our application of QCA for each substantive analysis is described in detail. We extended the original review findings by identifying seven combinations of BCTs and four combinations of implementation features that were sufficient for improving adherence. We found reasonable alignment between several systematic review steps and processes used in QCA except that typical approaches to study abstraction for some intervention components and features did not support a robust calibration for QCA. QCA was suitable for use within a systematic review of medication adherence interventions and offered insights beyond the single dimension stratifications used in the original completed review. Future prospective use of QCA during a review is needed to determine the optimal way to efficiently integrate QCA into existing approaches to evidence synthesis of complex interventions.

Model reduction by weighted Component Cost Analysis

NASA Technical Reports Server (NTRS)

Kim, Jae H.; Skelton, Robert E.

1990-01-01

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

[A new approach to urinary stone analysis according to the combination of the components: experience with 7949 cases].

PubMed

Millán, F; Gracia, S; Sánchez-Martín, F M; Angerri, O; Rousaud, F; Villavicencio, H

2011-03-01

To evaluate a new approach to urinary stone analysis according to the combination of the components. A total of 7949 stones were analysed and their main components and combinations of components were classified according to gender and age. Statistical analysis was performed using the chi-square test. Calcium oxalate monohydrate (COM) was the most frequent component in both males (39%) and females (37.4%), followed by calcium oxalate dihydrate (COD) (28%) and uric acid (URI) (14.6%) in males and by phosphate (PHO) (22.2%) and COD (19.6%) in females (p=0.0001). In young people, COD and PHO were the most frequent components in males and females respectively (p=0.0001). In older patients, COM and URI (in that order) were the most frequent components in both genders (p=0.0001). COM is oxalate dependent and is related to diets with a high oxalate content and low water intake. The progressive increase in URI with age is related mainly to overweight and metabolic syndrome. Regarding the combinations of components, the most frequent were COM (26.3%), COD+Apatite (APA) (15.5%), URI (10%) and COM+COD (7.5%) (p=0.0001). This study reports not only the composition of stones but also the main combinations of components according to age and gender. The results prove that stone composition is related to the changes in dietary habits and life-style that occur over a lifetime, and the morphological structure of stones is indicative of the aetiopathogenic mechanisms. Copyright © 2010 AEU. Published by Elsevier Espana. All rights reserved.

Use of Raman microscopy and band-target entropy minimization analysis to identify dyes in a commercial stamp. Implications for authentication and counterfeit detection.

PubMed

Widjaja, Effendi; Garland, Marc

2008-02-01

Raman microscopy was used in mapping mode to collect more than 1000 spectra in a 100 microm x 100 microm area from a commercial stamp. Band-target entropy minimization (BTEM) was then employed to unmix the mixture spectra in order to extract the pure component spectra of the samples. Three pure component spectral patterns with good signal-to-noise ratios were recovered, and their spatial distributions were determined. The three pure component spectral patterns were then identified as copper phthalocyanine blue, calcite-like material, and yellow organic dye material by comparison to known spectral libraries. The present investigation, consisting of (1) advanced curve resolution (blind-source separation) followed by (2) spectral data base matching, readily suggests extensions to authenticity and counterfeit studies of other types of commercial objects. The presence or absence of specific observable components form the basis for assessment. The present spectral analysis (BTEM) is applicable to highly overlapping spectral information. Since a priori information such as the number of components present and spectral libraries are not needed in BTEM, and since minor signals arising from trace components can be reconstructed, this analysis offers a robust approach to a wide variety of material problems involving authenticity and counterfeit issues.

COMPUTATIONAL ANALYSIS OF SWALLOWING MECHANICS UNDERLYING IMPAIRED EPIGLOTTIC INVERSION

PubMed Central

Pearson, William G.; Taylor, Brandon K; Blair, Julie; Martin-Harris, Bonnie

2015-01-01

Objective Determine swallowing mechanics associated with the first and second epiglottic movements, that is, movement to horizontal and full inversion respectively, in order to provide a clinical interpretation of impaired epiglottic function. Study Design Retrospective cohort study. Methods A heterogeneous cohort of patients with swallowing difficulties was identified (n=92). Two speech-language pathologists reviewed 5ml thin and 5ml pudding videofluoroscopic swallow studies per subject, and assigned epiglottic component scores of 0=complete inversion, 1=partial inversion, and 2=no inversion forming three groups of videos for comparison. Coordinates mapping minimum and maximum excursion of the hyoid, pharynx, larynx, and tongue base during pharyngeal swallowing were recorded using ImageJ software. A canonical variate analysis with post-hoc discriminant function analysis of coordinates was performed using MorphoJ software to evaluate mechanical differences between groups. Eigenvectors characterizing swallowing mechanics underlying impaired epiglottic movements were visualized. Results Nineteen of 184 video-swallows were rejected for poor quality (n=165). A Goodman-Kruskal index of predictive association showed no correlation between epiglottic component scores and etiologies of dysphagia (λ=.04). A two-way analysis of variance by epiglottic component scores showed no significant interaction effects between sex and age (f=1.4, p=.25). Discriminant function analysis demonstrated statistically significant mechanical differences between epiglottic component scores: 1&2, representing the first epiglottic movement (Mahalanobis distance=1.13, p=.0007); and, 0&1, representing the second epiglottic movement (Mahalanobis distance=0.83, p=.003). Eigenvectors indicate that laryngeal elevation and tongue base retraction underlie both epiglottic movements. Conclusion Results suggest that reduced tongue base retraction and laryngeal elevation underlie impaired first and second epiglottic movements. The styloglossus, hyoglossus and long pharyngeal muscles are implicated as targets for rehabilitation in dysphagic patients with impaired epiglottic inversion. PMID:27426940

Joint Procrustes Analysis for Simultaneous Nonsingular Transformation of Component Score and Loading Matrices

ERIC Educational Resources Information Center

Adachi, Kohei

2009-01-01

In component analysis solutions, post-multiplying a component score matrix by a nonsingular matrix can be compensated by applying its inverse to the corresponding loading matrix. To eliminate this indeterminacy on nonsingular transformation, we propose Joint Procrustes Analysis (JPA) in which component score and loading matrices are simultaneously…

An Analysis of Corporal Punishment Practices in the State of Mississippi

ERIC Educational Resources Information Center

Williams-Damond, Twyla A.

2014-01-01

The focus of this research mainly centers on a quantitative descriptive overview of corporal punishment practices in the state of Mississippi, but this study also includes a legal document analysis component. This study forms the Mississippi portion of a comprehensive analysis of the demographics of corporal punishment in the public schools of the…

The Application of Structured Job Analysis Information Based on the Position Analysis Questionnaire (PAQ). Final Report No. 9.

ERIC Educational Resources Information Center

McCormick, Ernest J.

The Position Analysis Questionnaire (PAQ) is a job analysis instrument consisting of 187 job elements organized into six divisions. The PAQ was used in the eight studies summarized in this final report. The studies were: (1) ratings of the attribute requirements of PAQ job elements, (2) a series of principal components analyses of these attribute…

Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake.

PubMed

Mimura, Natsuki; Isogai, Atsuko; Iwashita, Kazuhiro; Bamba, Takeshi; Fukusaki, Eiichiro

2014-10-01

Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Scenario Analysis: An Integrative Study and Guide to Implementation in the United States Air Force

DTIC Science & Technology

1994-09-01

Environmental Analysis ................................ 3-3 Classifications of Environments ......................... 3-5 Characteristics of... Environments ........................ 3-8 iii Page Components of the Environmental Analysis Process ........... 3-12 Forecasting... Environmental Analysis ...................... 3-4 3-2 Model of the Industry Environment ......................... 3-6 3-3 Model of Macroenvironment

An Analysis of the Cosmetology Occupation.

ERIC Educational Resources Information Center

Cappelli, Annette; And Others

This occupational analysis data was assembled to help cosmetology instructors develop a course of study. Following a job description for a cosmetologist, the remainder of the content in standard task analysis format presents an analysis of twelve cosmetologist duties (tasks). Each of the twelve duties is broken down into its components (one or…

A comparative study of volatile components in Dianhong teas from fresh leaves of four tea cultivars by using chromatography-mass spectrometry, multivariate data analysis, and descriptive sensory analysis.

PubMed

Wang, Chao; Zhang, Chenxia; Kong, Yawen; Peng, Xiaopei; Li, Changwen; Liu, Shunhang; Du, Liping; Xiao, Dongguang; Xu, Yongquan

2017-10-01

Dianhong teas produced from fresh leaves of different tea cultivars (YK is Yunkang No. 10, XY is Xueya 100, CY is Changyebaihao, SS is Shishengmiao), were compared in terms of volatile compounds and descriptive sensory analysis. A total of 73 volatile compounds in 16 tea samples were tentatively identified. YK, XY, CY, and SS contained 55, 53, 49, and 51 volatile compounds, respectively. Partial least squares-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were used to classify the samples, and 40 key components were selected based on variable importance in the projection. Moreover, 11 flavor attributes, namely, floral, fruity, grass/green, woody, sweet, roasty, caramel, mellow and thick, bitter, astringent, and sweet aftertaste were identified through descriptive sensory analysis (DSA). In generally, innate differences among the tea varieties significantly affected the intensities of most of the key sensory attributes of Dianhong teas possibly because of the different amounts of aroma-active and taste components in Dianhong teas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Shuttle filter study. Volume 2: Contaminant generation and sensitivity studies

NASA Technical Reports Server (NTRS)

1974-01-01

Contaminant generation studies were conducted at the component level using two different methods, radioactive tracer technique and gravimetric analysis test procedure. Both of these were reduced to practice during this program. In the first of these methods, radioactively tagged components typical of those used in spacecraft were studied to determine their contaminant generation characteristics under simulated operating conditions. Because the purpose of the work was: (1) to determine the types and quantities of contaminants generated; and (2) to evaluate improved monitoring and detection schemes, no attempt was made to evaluate or qualify specific components. The components used in this test program were therefore not flight hardware items. Some of them had been used in previous tests; some were obsolete; one was an experimental device. In addition to the component tests, various materials of interest to contaminant and filtration studies were irradiated and evaluated for use as autotracer materials. These included test dusts, plastics, valve seat materials, and bearing cage materials.

Incipient fault detection study for advanced spacecraft systems

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Black, Michael C.; Hovenga, J. Mike; Mcclure, Paul F.

1986-01-01

A feasibility study to investigate the application of vibration monitoring to the rotating machinery of planned NASA advanced spacecraft components is described. Factors investigated include: (1) special problems associated with small, high RPM machines; (2) application across multiple component types; (3) microgravity; (4) multiple fault types; (5) eight different analysis techniques including signature analysis, high frequency demodulation, cepstrum, clustering, amplitude analysis, and pattern recognition are compared; and (6) small sample statistical analysis is used to compare performance by computation of probability of detection and false alarm for an ensemble of repeated baseline and faulted tests. Both detection and classification performance are quantified. Vibration monitoring is shown to be an effective means of detecting the most important problem types for small, high RPM fans and pumps typical of those planned for the advanced spacecraft. A preliminary monitoring system design and implementation plan is presented.

Chemometric expertise of the quality of groundwater sources for domestic use.

PubMed

Spanos, Thomas; Ene, Antoaneta; Simeonova, Pavlina

2015-01-01

In the present study 49 representative sites have been selected for the collection of water samples from central water supplies with different geographical locations in the region of Kavala, Northern Greece. Ten physicochemical parameters (pH, electric conductivity, nitrate, chloride, sodium, potassium, total alkalinity, total hardness, bicarbonate and calcium) were analyzed monthly, in the period from January 2010 to December 2010. Chemometric methods were used for monitoring data mining and interpretation (cluster analysis, principal components analysis and source apportioning by principal components regression). The clustering of the chemical indicators delivers two major clusters related to the water hardness and the mineral components (impacted by sea, bedrock and acidity factors). The sampling locations are separated into three major clusters corresponding to the spatial distribution of the sites - coastal, lowland and semi-mountainous. The principal components analysis reveals two latent factors responsible for the data structures, which are also an indication for the sources determining the groundwater quality of the region (conditionally named "mineral" factor and "water hardness" factor). By the apportionment approach it is shown what the contribution is of each of the identified sources to the formation of the total concentration of each one of the chemical parameters. The mean values of the studied physicochemical parameters were found to be within the limits given in the 98/83/EC Directive. The water samples are appropriate for human consumption. The results of this study provide an overview of the hydrogeological profile of water supply system for the studied area.

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

NASA Astrophysics Data System (ADS)

Rui, Zhenhua

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

Daily rainfall forecasting for one year in a single run using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

Effective modelling and prediction of smaller time step rainfall is reported to be very difficult owing to its highly erratic nature. Accurate forecast of daily rainfall for longer duration (multi time step) may be exceptionally helpful in the efficient planning and management of water resources systems. Identification of inherent patterns in a rainfall time series is also important for an effective water resources planning and management system. In the present study, Singular Spectrum Analysis (SSA) is utilized to forecast the daily rainfall time series pertaining to Koyna watershed in Maharashtra, India, for 365 days after extracting various components of the rainfall time series such as trend, periodic component, noise and cyclic component. In order to forecast the time series for longer time step (365 days-one window length), the signal and noise components of the time series are forecasted separately and then added together. The results of the study show that the method of SSA could extract the various components of the time series effectively and could also forecast the daily rainfall time series for longer duration such as one year in a single run with reasonable accuracy.

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...

Profiling study of the major and minor components of kaffir lime oil (Citrus hystrix DC.) in the fractional distillation process

PubMed Central

Warsito, Warsito; Palungan, Maimunah Hindun; Utomo, Edy Priyo

2017-01-01

Introduction Essential oil is consisting of complex component. It is divided into major and minor component. Therefore, this study aims to examine the distribution of major and minor components on Kaffir lime oil by using fractional distillation. Fractional distillation and distributional analysis of components within fractions have been performed on kaffir lime oil (Citrus hystrix DC.). Methods Fractional distillation was performed by using PiloDist 104-VTU, column length of 2 m (number of plate 120), the system pressure was set on 5 and 10 mBar, while the reflux ratio varied on 10/10, 20/10 and 60/10, and the chemical composition analysis was done by using GC-MS. Chemical composition of the distillated lime oil consisted of mix-twigs and leaves that composed of 20 compounds, with five main components β-citronellal (46.40%), L-linalool (13.11%), β-citronellol (11.03%), citronelyl acetate (6.76%) and sabinen (5.91%). Results The optimum conditions for fractional distillation were obtained at 5 mBar pressure with reflux ratio of 10/10. Components of β -citronellal and L-linalool were distributed in the fraction-1 to fraction 9, hydrocarbon monoterpenes components were distributed only on the fraction-1 to fraction 4, while the oxygenated monoterpenes components dominated the fraction-5 to fraction-9. Conclusion The highest level of β-citronellal was 84.86% (fraction-7), L-linalool 20.13% (fraction-5), sabinen 19.83% (fraction-1), and the component level of 4-terpeneol, β-citronellol and sitronelyl acetate respectively 7.16%; 12.27%; 5.22% (fraction-9). PMID:29187951

Effect of psycho-educational interventions on quality of life in patients with implantable cardioverter defibrillators: a meta-analysis of randomized controlled trials.

PubMed

Kao, Chi-Wen; Chen, Miao-Yi; Chen, Ting-Yu; Lin, Pai-Hui

2016-09-30

Implantable cardioverter defibrillators (ICD) were developed for primary and secondary prevention of sudden cardiac death. However, ICD recipients' mortality is significantly predicted by their quality of life (QOL). The aim of this meta-analysis was to evaluate the effects of psycho-educational interventions on QOL in patients with ICDs. We systematically searched PubMed, Medline, Cochrane Library, and CINAHL through April 2015 and references of relevant articles. Studies were reviewed if they met following criteria: (1) randomized controlled trial, (2) participants were adults with an ICD, and (3) data were sufficient to evaluate the effect of psychological or educational interventions on QOL measured by the SF-36 or SF-12. Studies were independently selected and their data were extracted by two reviewers. Study quality was evaluated using a modified Jadad scale. The meta-analysis was conducted using the Cochrane Collaboration's Review Manager Software Package (RevMan 5). Study heterogeneity was assessed by Q statistics and I 2 statistic. Depending on heterogeneity, data were pooled across trials using fixed-effect or random-effect modeling. Seven randomized controlled trials fulfilled the inclusion and exclusion criteria, and included 1017 participants. The psycho-educational interventions improved physical component summary (PCS) scores in the intervention groups more than in control groups (mean difference 2.08, 95 % CI 0.86 to 3.29, p < 0.001), but did not significantly affect mental component summary (MCS) scores (mean difference 0.84, 95 % CI -1.68 to 3.35, p = 0.52). Our meta-analysis demonstrates that psycho-educational interventions improved the physical component, but not the mental component of QOL in patients with ICDs.

[Extraction and analysis of chemical components of essential oil in Thymus vulgaris of tissue culture].

PubMed

Li, Xiao-Dong; Yang, Li; Xu, Shi-Qian; Li, Jian-Guo; Cheng, Zhi-Hui; Dang, Jian-Zhang

2011-10-01

To extract the essential oils from the Seedlings, the Aseptic Seedlings and the Tissue Culture Seedlings of Thymus vulgaris and analyze their chemical components and the relative contents. The essential oils were extracted by steam distillation, the chemical components and the relative contents were identified and analyzed by gas chromatography-mass spectrometry (GC/MS) and peak area normalization method. The main chemical components of essential oil in these three samples had no significant difference, they all contained the main components of essential oil in Thymus vulgaris: Thymol, Carvacrol, o-Cymene, gamma-Terpinene, Caryophyllene et al. and only had a slight difference in the relative content. This study provides important theoretical foundation and data reference for further study on production of essential oil in thyme by tissue culture technology.

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

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

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

Building Block Approach' for Structural Analysis of Thermoplastic Composite Components for Automotive Applications

NASA Astrophysics Data System (ADS)

Carello, M.; Amirth, N.; Airale, A. G.; Monti, M.; Romeo, A.

2017-12-01

Advanced thermoplastic prepreg composite materials stand out with regard to their ability to allow complex designs with high specific strength and stiffness. This makes them an excellent choice for lightweight automotive components to reduce mass and increase fuel efficiency, while maintaining the functionality of traditional thermosetting prepreg (and mechanical characteristics) and with a production cycle time and recyclability suited to mass production manufacturing. Currently, the aerospace and automotive sectors struggle to carry out accurate Finite Elements (FE) component analyses and in some cases are unable to validate the obtained results. In this study, structural Finite Elements Analysis (FEA) has been done on a thermoplastic fiber reinforced component designed and manufactured through an integrated injection molding process, which consists in thermoforming the prepreg laminate and overmolding the other parts. This process is usually referred to as hybrid molding, and has the provision to reinforce the zones subjected to additional stresses with thermoformed themoplastic prepreg as required and overmolded with a shortfiber thermoplastic resin in single process. This paper aims to establish an accurate predictive model on a rational basis and an innovative methodology for the structural analysis of thermoplastic composite components by comparison with the experimental tests results.

1 H NMR study and multivariate data analysis of reindeer skin tanning methods.

PubMed

Zhu, Lizheng; Ilott, Andrew J; Del Federico, Eleonora; Kehlet, Cindie; Klokkernes, Torunn; Jerschow, Alexej

2017-04-01

Reindeer skin clothing has been an essential component in the lives of indigenous people of the arctic and sub-arctic regions, keeping them warm during harsh winters. However, the skin processing technology, which often conveys the history and tradition of the indigenous group, has not been well documented. In this study, NMR spectra and relaxation behaviors of reindeer skin samples treated with a variety of vegetable tannin extracts, oils and fatty substances are studied and compared. With the assistance of principal component analysis (PCA), one can recognize patterns and identify groupings of differently treated samples. These methods could be important aids in efforts to conserve museum leather artifacts with unknown treatment methods and in the analysis of reindeer skin tanning processes. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

PubMed

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

2013-07-03

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

Proposed Models of Appropriate Website and Courseware for E-Learning in Higher Education: Research Based Design Models

ERIC Educational Resources Information Center

Khlaisang, Jintavee

2010-01-01

The purpose of this study was to investigate proper website and courseware for e-learning in higher education. Methods used in this study included the data collection, the analysis surveys, the experts' in-depth interview, and the experts' focus group. Results indicated that there were 16 components for website, as well as 16 components for…

Effect of Minerals on Intestinal IgA Production Using Deep Sea Water Drinks.

PubMed

Shiraishi, Hisashi; Fujino, Maho; Shirakawa, Naoki; Ishida, Nanao; Funato, Hiroki; Hirata, Ayumu; Abe, Noriaki; Iizuka, Michiro; Jobu, Kohei; Yokota, Junko; Miyamura, Mitsuhiko

2017-01-01

Minerals are essential for life, as they are a vital part of protein constituents, enzyme cofactors, and other components in living organisms. Deep sea water is characterized by its cleanliness and stable low temperature, and its possible health- and medical benefits are being studied. However, no study has yet evaluated the physical properties of the numerous commercially available deep sea water products, which have varying water sources and production methods. We analyzed these products' mineral content and investigated their effect on living organism, focusing on immune functions, and investigated the relation between physiological immunoactivities and mineral intake. We qualitatively analyzed the mineral compositions of the deep sea water drinks and evaluated the drinks' physical properties using principal component analysis, a type of multivariate analysis, of their mineral content. We create an iron and copper-deficient rat model and administered deep sea water drinks for 8 weeks. We then measured their fecal immunoglobulin A (IgA) to evaluate immune function. Principal component analysis suggested that physical properties of deep sea water drinks could be determined by their sources. Administration of deep sea water drinks increased fecal IgA, thus tending to stimulate immune function, but the extent of this effect varied by drink. Of the minerals contained in deep sea water, iron showed positive correlations with the fecal IgA. The principal component analysis used in this study is suitable for evaluating deep sea water containing many minerals, and our results form a useful basis for comparative evaluations of deep sea water's bioactivity.

Career Interests of Students in Psychology Specialties Degrees: Psychometric Evidence and Correlations with the RIASEC Dimensions

ERIC Educational Resources Information Center

Ferreira, Aristides I.; Rodrigues, Rosa I.; da Costa Ferreira, Paula

2016-01-01

In this study, we present the development of a vocational interest scale for university students studying psychology. Three dimensions were extracted through principal component analysis, namely, organizational, educational, and clinical psychology. A second study with confirmatory factor analysis replicated the same three factors obtained in the…

Quantitative Synthesis and Component Analysis of Single-Participant Studies on the Picture Exchange Communication System

ERIC Educational Resources Information Center

Tincani, Matt; Devis, Kathryn

2011-01-01

The "Picture Exchange Communication System" (PECS) has emerged as the augmentative communication intervention of choice for individuals with autism spectrum disorder (ASD), with a supporting body of single-participant studies. This report describes a meta-analysis of 16 single-participant studies on PECS with percentage of nonoverlapping data…

Developing techniques for cause-responsibility analysis of occupational accidents.

PubMed

Jabbari, Mousa; Ghorbani, Roghayeh

2016-11-01

The aim of this study was to specify the causes of occupational accidents, determine social responsibility and the role of groups involved in work-related accidents. This study develops occupational accidents causes tree, occupational accidents responsibility tree, and occupational accidents component-responsibility analysis worksheet; based on these methods, it develops cause-responsibility analysis (CRA) techniques, and for testing them, analyzes 100 fatal/disabling occupational accidents in the construction setting that were randomly selected from all the work-related accidents in Tehran, Iran, over a 5-year period (2010-2014). The main result of this study involves two techniques for CRA: occupational accidents tree analysis (OATA) and occupational accidents components analysis (OACA), used in parallel for determination of responsible groups and responsibilities rate. From the results, we find that the management group of construction projects has 74.65% responsibility of work-related accidents. The developed techniques are purposeful for occupational accidents investigation/analysis, especially for the determination of detailed list of tasks, responsibilities, and their rates. Therefore, it is useful for preventing work-related accidents by focusing on the responsible group's duties. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Energy Efficient Engine Low Pressure Subsystem Aerodynamic Analysis

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Classification of fMRI resting-state maps using machine learning techniques: A comparative study

NASA Astrophysics Data System (ADS)

Gallos, Ioannis; Siettos, Constantinos

2017-11-01

We compare the efficiency of Principal Component Analysis (PCA) and nonlinear learning manifold algorithms (ISOMAP and Diffusion maps) for classifying brain maps between groups of schizophrenia patients and healthy from fMRI scans during a resting-state experiment. After a standard pre-processing pipeline, we applied spatial Independent component analysis (ICA) to reduce (a) noise and (b) spatial-temporal dimensionality of fMRI maps. On the cross-correlation matrix of the ICA components, we applied PCA, ISOMAP and Diffusion Maps to find an embedded low-dimensional space. Finally, support-vector-machines (SVM) and k-NN algorithms were used to evaluate the performance of the algorithms in classifying between the two groups.

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.

Sex differences in the association of phospholipids with components of the metabolic syndrome in young adults.

PubMed

Rauschert, Sebastian; Uhl, Olaf; Koletzko, Berthold; Mori, Trevor A; Beilin, Lawrence J; Oddy, Wendy H; Hellmuth, Christian

2017-01-01

There are differences in the prevalence and severity of diseases between males, females not taking hormonal contraceptives (non-HC females) and females taking hormonal contraceptives (HC females). The aim of this study was to identify sex-specific differences in the metabolome and its relation to components of the metabolic syndrome in a young adult population. The subjects analysed are from the 20-year follow-up of the Western Australian Pregnancy Cohort (Raine) Study. Two hundred fifteen plasma metabolites were analysed in 1021 fasted plasma samples by a targeted liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) metabolomics approach. Principal component analysis between males ( n  = 550), non-HC females ( n  = 199) and HC females ( n  = 269) was applied. Regression analysis with a sex × metabolite concentration interaction was performed on components of the MetS, namely waist circumference, systolic blood pressure, and plasma HDL-C, triglycerides and glucose concentration, as outcome to select the significant metabolites of the interaction. Those selected metabolites were used as predictors in a sex group stratified analysis to compare the different β coefficients and therefore the sex group-dependent associations. Principal component analysis between males, non-HC females, and HC females showed a general discriminating trend between males and HC females. One hundred twenty-seven metabolites were significantly different between males and non-HC females, whereas 97 differed between non-HC females and HC females. Males and non-HC females mainly differed in sphingomyelin, lyso-phosphatidylcholine, acyl-carnitine and amino acid species, whilst non-HC females and HC females mainly differed in phosphatidylcholine, lyso-phosphatidylcholine and acyl-carnitine concentrations. Forty-one metabolites (phosphatidylcholines, sphingomyelines, lyso-phosphatidylcholine) were significantly differently associated with the MetS factors in the different groups. We have shown clear differences between plasma metabolite concentrations in males, and HC or non-HC females, especially in lyso-phosphatidylcholine, sphingomyelin and phosphatidylcholine, which have been shown to associate with obesity in other studies. The association of these metabolites differed between sexes with components of the metabolic syndrome, which means that development of diseases like obesity and diabetes may differ between the sexes. Our findings highlight the importance of considering sex differences when conducting a metabolomics study and the need to account for the effect of HC usage in females in future studies.

Vehicle for Space Transfer and Recovery (VSTAR), volume 2: Substantiating analyses and data

NASA Technical Reports Server (NTRS)

1988-01-01

The Vehicle Space Transfer and Recovery (VSTAR) system is designed as a manned orbital transfer vehicle (MOTV) with the primary mission of Satellite Launch and Repair (SLR). Reference materials, calculations and trade studies used in the analysis and selection of VSTAR components. Each major VSTAR system is examined separately. Simple graphs and tables are used to make qualitative comparisons of various VSTAR component candidates. Equations and/or calculations used for a particular analysis are also included where applicable.

Case for Deploying Complex Systems Utilizing Commodity Components

NASA Technical Reports Server (NTRS)

Bryant, Barry S.; Pitts, R. Lee; Ritter, George

2003-01-01

This viewgraph representation presents a study of the transition of computer networks and software engineering at the Huntsville Operations Support Center (HOSC) from a client/server UNIX based system to a client/server system based on commodity priced and open system components. Topics covered include: an overview of HOSC ground support systems, an analysis for changes to the existing ground support system, an analysis of options considered for the transition to a new system, and a consideration of goals for a new system.

Hologram interferometry in automotive component vibration testing

NASA Astrophysics Data System (ADS)

Brown, Gordon M.; Forbes, Jamie W.; Marchi, Mitchell M.; Wales, Raymond R.

1993-02-01

An ever increasing variety of automotive component vibration testing is being pursued at Ford Motor Company, U.S.A. The driving force for use of hologram interferometry in these tests is the continuing need to design component structures to meet more stringent functional performance criteria. Parameters such as noise and vibration, sound quality, and reliability must be optimized for the lightest weight component possible. Continually increasing customer expectations and regulatory pressures on fuel economy and safety mandate that vehicles be built from highly optimized components. This paper includes applications of holographic interferometry for powertrain support structure tuning, body panel noise reduction, wiper system noise and vibration path analysis, and other vehicle component studies.

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)

Evaluation of methodologies for assessing the overall diet: dietary quality scores and dietary pattern analysis.

PubMed

Ocké, Marga C

2013-05-01

This paper aims to describe different approaches for studying the overall diet with advantages and limitations. Studies of the overall diet have emerged because the relationship between dietary intake and health is very complex with all kinds of interactions. These cannot be captured well by studying single dietary components. Three main approaches to study the overall diet can be distinguished. The first method is researcher-defined scores or indices of diet quality. These are usually based on guidelines for a healthy diet or on diets known to be healthy. The second approach, using principal component or cluster analysis, is driven by the underlying dietary data. In principal component analysis, scales are derived based on the underlying relationships between food groups, whereas in cluster analysis, subgroups of the population are created with people that cluster together based on their dietary intake. A third approach includes methods that are driven by a combination of biological pathways and the underlying dietary data. Reduced rank regression defines linear combinations of food intakes that maximally explain nutrient intakes or intermediate markers of disease. Decision tree analysis identifies subgroups of a population whose members share dietary characteristics that influence (intermediate markers of) disease. It is concluded that all approaches have advantages and limitations and essentially answer different questions. The third approach is still more in an exploration phase, but seems to have great potential with complementary value. More insight into the utility of conducting studies on the overall diet can be gained if more attention is given to methodological issues.

Identification and apportionment of hazardous elements in the sediments in the Yangtze River estuary.

PubMed

Wang, Jiawei; Liu, Ruimin; Wang, Haotian; Yu, Wenwen; Xu, Fei; Shen, Zhenyao

2015-12-01

In this study, positive matrix factorization (PMF) and principal components analysis (PCA) were combined to identify and apportion pollution-based sources of hazardous elements in the surface sediments in the Yangtze River estuary (YRE). Source identification analysis indicated that PC1, including Al, Fe, Mn, Cr, Ni, As, Cu, and Zn, can be defined as a sewage component; PC2, including Pb and Sb, can be considered as an atmospheric deposition component; and PC3, containing Cd and Hg, can be considered as an agricultural nonpoint component. To better identify the sources and quantitatively apportion the concentrations to their sources, eight sources were identified with PMF: agricultural/industrial sewage mixed (18.6 %), mining wastewater (15.9 %), agricultural fertilizer (14.5 %), atmospheric deposition (12.8 %), agricultural nonpoint (10.6 %), industrial wastewater (9.8 %), marine activity (9.0 %), and nickel plating industry (8.8 %). Overall, the hazardous element content seems to be more connected to anthropogenic activity instead of natural sources. The PCA results laid the foundation for the PMF analysis by providing a general classification of sources. PMF resolves more factors with a higher explained variance than PCA; PMF provided both the internal analysis and the quantitative analysis. The combination of the two methods can provide more reasonable and reliable results.

Component resolved bleaching study in natural calcium fluoride using CW-OSL, LM-OSL and residual TL glow curves after bleaching.

PubMed

Angeli, Vasiliki; Polymeris, George S; Sfampa, Ioanna K; Tsirliganis, Nestor C; Kitis, George

2017-04-01

Natural calcium fluoride has been commonly used as thermoluminescence (TL) dosimeter due to its high luminescence intensity. The aim of this work includes attempting a correlation between specific TL glow curves after bleaching and components of linearly modulated optically stimulated luminescence (LM-OSL) as well as continuous wave OSL (CW-OSL). A component resolved analysis was applied to both integrated intensity of the RTL glow curves and all OSL decay curves, by using a Computerized Glow-Curve De-convolution (CGCD) procedure. All CW-OSL and LM-OSL components are correlated to the decay components of the integrated RTL signal, apart from two RTL components which cannot be directly correlated with either LM-OSL or CW-OSL component. The unique, stringent criterion for this correlation deals with the value of the decay constant λ of each bleaching component. There is only one, unique bleaching component present in all three luminescence entities which were the subject of the present study, indicating that each TL trap yields at least three different bleaching components; different TL traps can indicate bleaching components with similar values. According to the data of the present work each RTL bleaching component receives electrons from at least two peaks. The results of the present study strongly suggest that the traps that contribute to TL and OSL are the same. Copyright © 2017 Elsevier Ltd. All rights reserved.

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

Factors affecting medication adherence in community-managed patients with hypertension based on the principal component analysis: evidence from Xinjiang, China.

PubMed

Zhang, Yuji; Li, Xiaoju; Mao, Lu; Zhang, Mei; Li, Ke; Zheng, Yinxia; Cui, Wangfei; Yin, Hongpo; He, Yanli; Jing, Mingxia

2018-01-01

The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis. A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ 2 -test and a binary logistic regression model. This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications. Community management plays an important role in improving the patients' medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers.

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults.

PubMed

Azcárate, T; Mendoza, B

2017-09-01

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

Influence of geomagnetic activity and atmospheric pressure in hypertensive adults

NASA Astrophysics Data System (ADS)

Azcárate, T.; Mendoza, B.

2017-09-01

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

Computing Lives And Reliabilities Of Turboprop Transmissions

NASA Technical Reports Server (NTRS)

Coy, J. J.; Savage, M.; Radil, K. C.; Lewicki, D. G.

1991-01-01

Computer program PSHFT calculates lifetimes of variety of aircraft transmissions. Consists of main program, series of subroutines applying to specific configurations, generic subroutines for analysis of properties of components, subroutines for analysis of system, and common block. Main program selects routines used in analysis and causes them to operate in desired sequence. Series of configuration-specific subroutines put in configuration data, perform force and life analyses for components (with help of generic component-property-analysis subroutines), fill property array, call up system-analysis routines, and finally print out results of analysis for system and components. Written in FORTRAN 77(IV).

The Relationship of Social Engagement and Social Support With Sense of Community.

PubMed

Tang, Fengyan; Chi, Iris; Dong, Xinqi

2017-07-01

We aimed to investigate the relationship of engagement in social and cognitive activities and social support with the sense of community (SOC) and its components among older Chinese Americans. The Sense of Community Index (SCI) was used to measure SOC and its four component factors: membership, influence, needs fulfillment, and emotional connection. Social engagement was assessed with 16 questions. Social support included positive support and negative strain. Principal component analysis was used to identify the SCI components. Linear regression analysis was used to detect the contribution of social engagement and social support to SOC and its components. After controlling for sociodemographics and self-rated health, social activity engagement and positive social support were positively related to SOC and its components. This study points to the importance of social activity engagement and positive support from family and friends in increasing the sense of community. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Componential distribution analysis of food using near infrared ray image

NASA Astrophysics Data System (ADS)

Yamauchi, Hiroki; Kato, Kunihito; Yamamoto, Kazuhiko; Ogawa, Noriko; Ohba, Kimie

2008-11-01

The components of the food related to the "deliciousness" are usually evaluated by componential analysis. The component content and type of components in the food are determined by this analysis. However, componential analysis is not able to analyze measurements in detail, and the measurement is time consuming. We propose a method to measure the two-dimensional distribution of the component in food using a near infrared ray (IR) image. The advantage of our method is to be able to visualize the invisible components. Many components in food have characteristics such as absorption and reflection of light in the IR range. The component content is measured using subtraction between two wavelengths of near IR light. In this paper, we describe a method to measure the component of food using near IR image processing, and we show an application to visualize the saccharose in the pumpkin.

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.

Spatiotemporal analysis of single-trial EEG of emotional pictures based on independent component analysis and source location

NASA Astrophysics Data System (ADS)

Liu, Jiangang; Tian, Jie

2007-03-01

The present study combined the Independent Component Analysis (ICA) and low-resolution brain electromagnetic tomography (LORETA) algorithms to identify the spatial distribution and time course of single-trial EEG record differences between neural responses to emotional stimuli vs. the neutral. Single-trial multichannel (129-sensor) EEG records were collected from 21 healthy, right-handed subjects viewing the emotion emotional (pleasant/unpleasant) and neutral pictures selected from International Affective Picture System (IAPS). For each subject, the single-trial EEG records of each emotional pictures were concatenated with the neutral, and a three-step analysis was applied to each of them in the same way. First, the ICA was performed to decompose each concatenated single-trial EEG records into temporally independent and spatially fixed components, namely independent components (ICs). The IC associated with artifacts were isolated. Second, the clustering analysis classified, across subjects, the temporally and spatially similar ICs into the same clusters, in which nonparametric permutation test for Global Field Power (GFP) of IC projection scalp maps identified significantly different temporal segments of each emotional condition vs. neutral. Third, the brain regions accounted for those significant segments were localized spatially with LORETA analysis. In each cluster, a voxel-by-voxel randomization test identified significantly different brain regions between each emotional condition vs. the neutral. Compared to the neutral, both emotional pictures elicited activation in the visual, temporal, ventromedial and dorsomedial prefrontal cortex and anterior cingulated gyrus. In addition, the pleasant pictures activated the left middle prefrontal cortex and the posterior precuneus, while the unpleasant pictures activated the right orbitofrontal cortex, posterior cingulated gyrus and somatosensory region. Our results were well consistent with other functional imaging studies, while revealed temporal dynamics of emotional processing of specific brain structure with high temporal resolution.

Selective impact of disease on short-term and long-term components of self-reported memory: a population-based HUNT study

PubMed Central

Almkvist, Ove; Bosnes, Ole; Bosnes, Ingunn; Stordal, Eystein

2017-01-01

Background Subjective memory is commonly considered to be a unidimensional measure. However, theories of performance-based memory suggest that subjective memory could be divided into more than one dimension. Objective To divide subjective memory into theoretically related components of memory and explore the relationship to disease. Methods In this study, various aspects of self-reported memory were studied with respect to demographics and diseases in the third wave of the HUNT epidemiological study in middle Norway. The study included all individuals 55 years of age or older, who responded to a nine-item questionnaire on subjective memory and questionnaires on health (n=18 633). Results A principle component analysis of the memory items resulted in two memory components; the criterion used was an eigenvalue above 1, which accounted for 54% of the total variance. The components were interpreted as long-term memory (LTM; the first component; 43% of the total variance) and short-term memory (STM; the second component; 11% of the total variance). Memory impairment was significantly related to all diseases (except Bechterew’s disease), most strongly to brain infarction, heart failure, diabetes, cancer, chronic obstructive pulmonary disease and whiplash. For most diseases, the STM component was more affected than the LTM component; however, in cancer, the opposite pattern was seen. Conclusions Subjective memory impairment as measured in HUNT contained two components, which were differentially associated with diseases. PMID:28490551

In Quest of the Alanine R3 Radical: Multivariate EPR Spectral Analyses of X-Irradiated Alanine in the Solid State.

PubMed

Jåstad, Eirik O; Torheim, Turid; Villeneuve, Kathleen M; Kvaal, Knut; Hole, Eli O; Sagstuen, Einar; Malinen, Eirik; Futsaether, Cecilia M

2017-09-28

The amino acid l-α-alanine is the most commonly used material for solid-state electron paramagnetic resonance (EPR) dosimetry, due to the formation of highly stable radicals upon irradiation, with yields proportional to the radiation dose. Two major alanine radical components designated R1 and R2 have previously been uniquely characterized from EPR and electron-nuclear double resonance (ENDOR) studies as well as from quantum chemical calculations. There is also convincing experimental evidence of a third minor radical component R3, and a tentative radical structure has been suggested, even though no well-defined spectral signature has been observed experimentally. In the present study, temperature dependent EPR spectra of X-ray irradiated polycrystalline alanine were analyzed using five multivariate methods in further attempts to understand the composite nature of the alanine dosimeter EPR spectrum. Principal component analysis (PCA), maximum likelihood common factor analysis (MLCFA), independent component analysis (ICA), self-modeling mixture analysis (SMA), and multivariate curve resolution (MCR) were used to extract pure radical spectra and their fractional contributions from the experimental EPR spectra. All methods yielded spectral estimates resembling the established R1 spectrum. Furthermore, SMA and MCR consistently predicted both the established R2 spectrum and the shape of the R3 spectrum. The predicted shape of the R3 spectrum corresponded well with the proposed tentative spectrum derived from spectrum simulations. Thus, results from two independent multivariate data analysis techniques strongly support the previous evidence that three radicals are indeed present in irradiated alanine samples.

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.

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

PubMed

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

2007-01-01

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

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

PubMed

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

2018-01-01

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

Spectral and Geological Characterization of Beach Components in Northern Puerto Rico

NASA Astrophysics Data System (ADS)

Caraballo Álvarez, I. O.; Torres-Perez, J. L.; Barreto, M.

2015-12-01

Understanding how changes in beach components may reflect beach processes is essential since variations along beach profiles can shed light on river and ocean processes influencing beach sedimentation and beachrock formation. It is likely these influences are related to beach proximity within the Río Grande de Manatí river mouth. Therefore, this study focuses on characterizing beach components at two sites in Manatí, Puerto Rico. Playa Machuca and Playa Tombolo, which are separated by eolianites, differ greatly in sediment size, mineralogy, and beachrock morphology. Several approaches were taken to geologically and spectrally characterize main beach components at each site. These approaches included field and microscopic laboratory identification, granulometry, and a comparison between remote sensing reflectance (Rrs) obtained with a field spectroradiometer and pre-existing spectral library signatures. Preliminary results indicate a positive correlation between each method. This study may help explore the possibility of using only Rrs to characterize beach and shallow submarine components for detailed image analysis and management of coastal features.This study focuses on characterizing beach components at two sites in Manatí, Puerto Rico. Playa Machuca and Playa Tombolo, two beaches that are separated by eolianites, differ greatly in sediment size and mineralogy, as well as in beachrock morphology. Understanding how changes in beach components may reflect beach processes is essential, since it is likely that differences are mostly related to each beaches' proximity to the Río Grande de Manatí river mouth. Hence, changes in components along beach profiles can shed light on the river's and the ocean's influence on beach sedimentation and beachrock formation. Several approaches were taken to properly geologically and spectrally characterize the main beach components at each site. These approaches included field and microscopic laboratory identification, granulometry, and a comparison between remote sensing reflectance (Rrs) obtained with a field spectroradiometer and the ENVI spectral library. Preliminary results show a positive correlation between each method. This study may help explore the possibility of using only Rrs to characterize beach and shallow submarine components for detailed image analysis and management of coastal features.

An Analysis of Digital Inclusion Projects: Three Crucial Factors and Four Key Components

ERIC Educational Resources Information Center

Smith, Chris

2015-01-01

This paper provides an in-depth analysis into two case studies aimed at addressing the digital divide in two developing countries. A detailed description is provided for each case study along with an analysis of how successful the two projects were at addressing the digital divide in Siyabuswa, South Africa and Ennis, Ireland. The two case studies…

Validation of Shared and Specific Independent Component Analysis (SSICA) for Between-Group Comparisons in fMRI

PubMed Central

Maneshi, Mona; Vahdat, Shahabeddin; Gotman, Jean; Grova, Christophe

2016-01-01

Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named “shared and specific independent component analysis” (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i.e., components that could be considered “specific” for a group or condition. Here, we investigated the performance of SSICA on realistic simulations, and task fMRI data and compared the results with one of the state-of-the-art group ICA approaches to infer between-group differences. We examined SSICA robustness with respect to the number of allowable extracted specific components and between-group orthogonality assumptions. Furthermore, we proposed a modified formulation of the back-reconstruction method to generate group-level t-statistics maps based on SSICA results. We also evaluated the consistency and specificity of the extracted specific components by SSICA. The results on realistic simulated and real fMRI data showed that SSICA outperforms the regular group ICA approach in terms of reconstruction and classification performance. We demonstrated that SSICA is a powerful data-driven approach to detect patterns of differences in functional connectivity across groups/conditions, particularly in model-free designs such as resting-state fMRI. Our findings in task fMRI show that SSICA confirms results of the general linear model (GLM) analysis and when combined with clustering analysis, it complements GLM findings by providing additional information regarding the reliability and specificity of networks. PMID:27729843

Inventory of File sref_nmb.t03z.pgrb221.ctl.grib2

Science.gov Websites

006 10 m above ground UGRD analysis U-Component of Wind [m/s] ENS=low-res ctl 007 10 m above ground VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl 008 surface WEASD analysis Water Equivalent of -Component of Wind [m/s] ENS=low-res ctl 021 250 mb VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl

Inventory of File sref_nmb.t03z.pgrb132.ctl.grib2

Science.gov Websites

006 10 m above ground UGRD analysis U-Component of Wind [m/s] ENS=low-res ctl 007 10 m above ground VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl 008 surface WEASD analysis Water Equivalent of -Component of Wind [m/s] ENS=low-res ctl 021 250 mb VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl

Inventory of File sref_nmb.t03z.pgrb243.ctl.grib2

Science.gov Websites

006 10 m above ground UGRD analysis U-Component of Wind [m/s] ENS=low-res ctl 007 10 m above ground VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl 008 surface WEASD analysis Water Equivalent of -Component of Wind [m/s] ENS=low-res ctl 021 250 mb VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl

Inventory of File sref_nmb.t03z.pgrb216.ctl.grib2

Science.gov Websites

006 10 m above ground UGRD analysis U-Component of Wind [m/s] ENS=low-res ctl 007 10 m above ground VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl 008 surface WEASD analysis Water Equivalent of -Component of Wind [m/s] ENS=low-res ctl 021 250 mb VGRD analysis V-Component of Wind [m/s] ENS=low-res ctl

Latent effects decision analysis

DOEpatents

Cooper, J Arlin [Albuquerque, NM; Werner, Paul W [Albuquerque, NM

2004-08-24

Latent effects on a system are broken down into components ranging from those far removed in time from the system under study (latent) to those which closely effect changes in the system. Each component is provided with weighted inputs either by a user or from outputs of other components. A non-linear mathematical process known as `soft aggregation` is performed on the inputs to each component to provide information relating to the component. This information is combined in decreasing order of latency to the system to provide a quantifiable measure of an attribute of a system (e.g., safety) or to test hypotheses (e.g., for forensic deduction or decisions about various system design options).

A Second Look at Dwyer's Studies by Means of Meta-Analysis: The Effects of Pictorial Realism on Text Comprehension and Vocabulary.

ERIC Educational Resources Information Center

Reinwein, Joachim; Huberdeau, Lucie

A meta-analysis examined a series of studies by F.M. Dwyer on the effect of illustrations on text comprehension. Principal component analysis was used to reduce the four posttests used by Dwyer to more fundamental factors of learning, followed by analyses of variance. All nine studies (involving secondary-school and college students) in which…

Proceedings: Economic and Social Analysis Workshop Held at St. Louis, Missouri on 25-29 October 1982,

DTIC Science & Technology

1983-10-01

institutional factors for determining the discount rate. For instance tax impact analysis is particularly troublesome. According to one recent study ...STAND-ALONE TECHNICAL REPORT. THE FOLLOWING COMPONENT PART NUMBERS COMPRISE THE COMPILATION REPORT: AW: TIILE: AD-P002 631 National Waterways Study ...for Military Programs: The Fort -;1uchanan, Puerto Rico, Realignment Study . AD-P002 646 Economic Analysis of Alternative Military Housing

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.

funRNA: a fungi-centered genomics platform for genes encoding key components of RNAi.

PubMed

Choi, Jaeyoung; Kim, Ki-Tae; Jeon, Jongbum; Wu, Jiayao; Song, Hyeunjeong; Asiegbu, Fred O; Lee, Yong-Hwan

2014-01-01

RNA interference (RNAi) is involved in genome defense as well as diverse cellular, developmental, and physiological processes. Key components of RNAi are Argonaute, Dicer, and RNA-dependent RNA polymerase (RdRP), which have been functionally characterized mainly in model organisms. The key components are believed to exist throughout eukaryotes; however, there is no systematic platform for archiving and dissecting these important gene families. In addition, few fungi have been studied to date, limiting our understanding of RNAi in fungi. Here we present funRNA http://funrna.riceblast.snu.ac.kr/, a fungal kingdom-wide comparative genomics platform for putative genes encoding Argonaute, Dicer, and RdRP. To identify and archive genes encoding the abovementioned key components, protein domain profiles were determined from reference sequences obtained from UniProtKB/SwissProt. The domain profiles were searched using fungal, metazoan, and plant genomes, as well as bacterial and archaeal genomes. 1,163, 442, and 678 genes encoding Argonaute, Dicer, and RdRP, respectively, were predicted. Based on the identification results, active site variation of Argonaute, diversification of Dicer, and sequence analysis of RdRP were discussed in a fungus-oriented manner. funRNA provides results from diverse bioinformatics programs and job submission forms for BLAST, BLASTMatrix, and ClustalW. Furthermore, sequence collections created in funRNA are synced with several gene family analysis portals and databases, offering further analysis opportunities. funRNA provides identification results from a broad taxonomic range and diverse analysis functions, and could be used in diverse comparative and evolutionary studies. It could serve as a versatile genomics workbench for key components of RNAi.

Long Term Precipitation Pattern Identification and Derivation of Non Linear Precipitation Trend in a Catchment using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, Vinayakam

2017-04-01

Precipitation is the major component in the hydrologic cycle. Awareness of not only the total amount of rainfall pertaining to a catchment, but also the pattern of its spatial and temporal distribution are equally important in the management of water resources systems in an efficient way. Trend is the long term direction of a time series; it determines the overall pattern of a time series. Singular Spectrum Analysis (SSA) is a time series analysis technique that decomposes the time series into small components (eigen triples). This property of the method of SSA has been utilized to extract the trend component of the rainfall time series. In order to derive trend from the rainfall time series, we need to select components corresponding to trend from the eigen triples. For this purpose, periodogram analysis of the eigen triples have been proposed to be coupled with SSA, in the present study. In the study, seasonal data of England and Wales Precipitation (EWP) for a time period of 1766-2013 have been analyzed and non linear trend have been derived out of the precipitation data. In order to compare the performance of SSA in deriving trend component, Mann Kendall (MK) test is also used to detect trends in EWP seasonal series and the results have been compared. The result showed that the MK test could detect the presence of positive or negative trend for a significance level, whereas the proposed methodology of SSA could extract the non-linear trend present in the rainfall series along with its shape. We will discuss further the comparison of both the methodologies along with the results in the presentation.

A systematic analysis of the XMM-Newton background: I. Dataset and extraction procedures

NASA Astrophysics Data System (ADS)

Marelli, Martino; Salvetti, David; Gastaldello, Fabio; Ghizzardi, Simona; Molendi, Silvano; Luca, Andrea De; Moretti, Alberto; Rossetti, Mariachiara; Tiengo, Andrea

2017-12-01

XMM-Newton is the direct precursor of the future ESA ATHENA mission. A study of its particle-induced background provides therefore significant insight for the ATHENA mission design. We make use of ˜12 years of data, products from the third XMM-Newton catalog as well as FP7 EXTraS project to avoid celestial sources contamination and to disentangle the different components of the XMM-Newton particle-induced background. Within the ESA R&D AREMBES collaboration, we built new analysis pipelines to study the different components of this background: this covers time behavior as well as spectral and spatial characteristics.

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

PubMed

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

2011-11-01

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

Sources of hydrocarbons in urban road dust: Identification, quantification and prediction.

PubMed

Mummullage, Sandya; Egodawatta, Prasanna; Ayoko, Godwin A; Goonetilleke, Ashantha

2016-09-01

Among urban stormwater pollutants, hydrocarbons are a significant environmental concern due to their toxicity and relatively stable chemical structure. This study focused on the identification of hydrocarbon contributing sources to urban road dust and approaches for the quantification of pollutant loads to enhance the design of source control measures. The study confirmed the validity of the use of mathematical techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for source identification and principal component analysis/absolute principal component scores (PCA/APCS) receptor model for pollutant load quantification. Study outcomes identified non-combusted lubrication oils, non-combusted diesel fuels and tyre and asphalt wear as the three most critical urban hydrocarbon sources. The site specific variabilities of contributions from sources were replicated using three mathematical models. The models employed predictor variables of daily traffic volume (DTV), road surface texture depth (TD), slope of the road section (SLP), effective population (EPOP) and effective impervious fraction (EIF), which can be considered as the five governing parameters of pollutant generation, deposition and redistribution. Models were developed such that they can be applicable in determining hydrocarbon contributions from urban sites enabling effective design of source control measures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Detection of explosives on the surface of banknotes by Raman hyperspectral imaging and independent component analysis.

PubMed

Almeida, Mariana R; Correa, Deleon N; Zacca, Jorge J; Logrado, Lucio Paulo Lima; Poppi, Ronei J

2015-02-20

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50 μg cm(-2). Copyright © 2014 Elsevier B.V. All rights reserved.

Inventory of File gfs.t06z.pgrb2.1p00.f000

Science.gov Websites

analysis U-Component of Wind [m/s] 002 planetary boundary layer VGRD analysis V-Component of Wind [m/s] 003 planetary boundary layer VRATE analysis Ventilation Rate [m^2/s] 004 surface GUST analysis Wind Speed (Gust mb RH analysis Relative Humidity [%] 008 10 mb UGRD analysis U-Component of Wind [m/s] 009 10 mb VGRD

Inventory of File gfs.t06z.pgrb2.0p50.f000

Science.gov Websites

analysis U-Component of Wind [m/s] 002 planetary boundary layer VGRD analysis V-Component of Wind [m/s] 003 planetary boundary layer VRATE analysis Ventilation Rate [m^2/s] 004 surface GUST analysis Wind Speed (Gust mb RH analysis Relative Humidity [%] 008 10 mb UGRD analysis U-Component of Wind [m/s] 009 10 mb VGRD

Inventory of File gfs.t06z.pgrb2.0p25.f000

Science.gov Websites

analysis U-Component of Wind [m/s] 002 planetary boundary layer VGRD analysis V-Component of Wind [m/s] 003 planetary boundary layer VRATE analysis Ventilation Rate [m^2/s] 004 surface GUST analysis Wind Speed (Gust mb RH analysis Relative Humidity [%] 008 10 mb UGRD analysis U-Component of Wind [m/s] 009 10 mb VGRD

Inventory of File gfs.t06z.pgrb2.2p50.f000

Science.gov Websites

analysis U-Component of Wind [m/s] 002 planetary boundary layer VGRD analysis V-Component of Wind [m/s] 003 planetary boundary layer VRATE analysis Ventilation Rate [m^2/s] 004 surface GUST analysis Wind Speed (Gust mb RH analysis Relative Humidity [%] 008 10 mb UGRD analysis U-Component of Wind [m/s] 009 10 mb VGRD

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Molecular diversity of toxic components from the scorpion Heterometrus petersii venom revealed by proteomic and transcriptome analysis.

PubMed

Ma, Yibao; Zhao, Yong; Zhao, Ruiming; Zhang, Weiping; He, Yawen; Wu, Yingliang; Cao, Zhijian; Guo, Lin; Li, Wenxin

2010-07-01

Scorpion venoms contain a vast untapped reservoir of natural products, which have the potential for medicinal value in drug discovery. In this study, toxin components from the scorpion Heterometrus petersii venom were evaluated by transcriptome and proteome analysis.Ten known families of venom peptides and proteins were identified, which include: two families of potassium channel toxins, four families of antimicrobial and cytolytic peptides,and one family from each of the calcium channel toxins, La1-like peptides, phospholipase A2,and the serine proteases. In addition, we also identified 12 atypical families, which include the acid phosphatases, diuretic peptides, and ten orphan families. From the data presented here, the extreme diversity and convergence of toxic components in scorpion venom was uncovered. Our work demonstrates the power of combining transcriptomic and proteomic approaches in the study of animal venoms.

The effects of abdominal lipectomy in metabolic syndrome components and insulin sensitivity in females: A systematic review and meta-analysis.

PubMed

Seretis, Konstantinos; Goulis, Dimitrios G; Koliakos, Georgios; Demiri, Efterpi

2015-12-01

Adipose tissue is an endocrine organ, which is implicated in the pathogenesis of obesity, metabolic syndrome and diabetes. Lipectomy offers a unique opportunity to permanently reduce the absolute number of fat cells, though its functional role remains unclear. This systematic and meta-analysis review aims to assess the effect of abdominal lipectomy on metabolic syndrome components and insulin sensitivity in women. A predetermined protocol, established according to the Cochrane Handbook's recommendations, was used. An electronic search in MEDLINE, Scopus, the Cochrane Library and CENTRAL electronic databases was conducted from inception to May 14, 2015. This search was supplemented by a review of reference lists of potentially eligible studies and a manual search of key journals in the field of plastic surgery. Eligible studies were prospective studies with ≥1month of follow-up that included females only who underwent abdominal lipectomy and reported on parameters of metabolic syndrome and insulin sensitivity. The systematic review included 11 studies with a total of 271 individuals. Conflicting results were revealed, though most studies showed no significant metabolic effects after lipectomy. The meta-analysis included 4 studies with 140 subjects. No significant changes were revealed between lipectomy and control groups. This meta-analysis provides evidence that abdominal lipectomy in females does not affect significantly the components of metabolic syndrome and insulin sensitivity. Further high quality studies are needed to elucidate the potential metabolic effects of abdominal lipectomy. Systematic review registration PROSPERO CRD42015017564 (www.crd.york.ac.uk/PROSPERO). Copyright © 2015 Elsevier Inc. All rights reserved.

Impact analysis of composite aircraft structures

NASA Technical Reports Server (NTRS)

Pifko, Allan B.; Kushner, Alan S.

1993-01-01

The impact analysis of composite aircraft structures is discussed. Topics discussed include: background remarks on aircraft crashworthiness; comments on modeling strategies for crashworthiness simulation; initial study of simulation of progressive failure of an aircraft component constructed of composite material; and research direction in composite characterization for impact analysis.

Parametric Analysis to Study the Influence of Aerogel-Based Renders' Components on Thermal and Mechanical Performance.

PubMed

Ximenes, Sofia; Silva, Ana; Soares, António; Flores-Colen, Inês; de Brito, Jorge

2016-05-04

Statistical models using multiple linear regression are some of the most widely used methods to study the influence of independent variables in a given phenomenon. This study's objective is to understand the influence of the various components of aerogel-based renders on their thermal and mechanical performance, namely cement (three types), fly ash, aerial lime, silica sand, expanded clay, type of aerogel, expanded cork granules, expanded perlite, air entrainers, resins (two types), and rheological agent. The statistical analysis was performed using SPSS (Statistical Package for Social Sciences), based on 85 mortar mixes produced in the laboratory and on their values of thermal conductivity and compressive strength obtained using tests in small-scale samples. The results showed that aerial lime assumes the main role in improving the thermal conductivity of the mortars. Aerogel type, fly ash, expanded perlite and air entrainers are also relevant components for a good thermal conductivity. Expanded clay can improve the mechanical behavior and aerogel has the opposite effect.

Quantitative Surface Analysis of a Binary Drug Mixture—Suppression Effects in the Detection of Sputtered Ions and Post-Ionized Neutrals

NASA Astrophysics Data System (ADS)

Karras, Gabriel; Lockyer, Nicholas P.

2014-05-01

A systematic mass spectrometric study of two of the most common analgesic drugs, paracetamol and ibuprofen, is reported. The drugs were studied by means of secondary ion mass spectrometry (SIMS) and secondary neutral mass spectrometry (SNMS) using laser post-ionization (LPI) both in pure samples and in a two-component mixture. Ion suppression within the two-component system observed in SIMS mode is ameliorated using LPI under room temperature analysis. However, suppression effects are apparent in LPI mode on performing the analysis at cryogenic temperatures, which we attribute to changes in the desorption characteristics of sputtered molecules, which influences the subsequent post-ionization efficiency. This suggests different mechanisms of ion suppression in SIMS and LPI modes.

Reflecting on how we remember the personal past: missing components in the study of memory appraisal and theoretical implications.

PubMed

Foley, Mary Ann

2018-05-01

The current paper offers a selective review of the study of memory appraisal, focusing on recollections of the personal past, with the goal to bring attention to a missing component in this study. To date, memory appraisal studies have concentrated on participants' assessments of the content of their personal recollections (e.g., their perceptual detail and story-like feel), including beliefs about the accuracy of that content. Participants' assessments of reflection processes accompanying their recollections (e.g., a sense of piecing-together recollection fragments) have yet to be extensively examined. The lack of information on process-based appraisals is related to prior studies' procedural constraints (e.g., kinds of cue prompts and their timing, minimal opportunities for reflection). Reasons for addressing this missing component provide the central themes of the paper. The reasons emerge from the analysis of autobiographical cueing studies, including integration of narrative research studies and autobiographical works. The analysis leads to suggestions for future research involving the use of personal narratives that are intended to address critiques of reconstruction accounts and unresolved questions in the study of memory appraisal.

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"…

Decreasing Inappropriate Vocalizations Using Classwide Group Contingencies and Color Wheel Procedures: A Component Analysis

ERIC Educational Resources Information Center

Kirk, Emily R.; Becker, Jennifer A.; Skinner, Christopher H., Fearrington, Jamie Yarbr; McCane-Bowling, Sara J.; Amburn, Christie; Luna, Elisa; Greear, Corinne

2010-01-01

Teacher referrals for consultation resulted in two independent teams collecting evidence that allowed for a treatment component evaluation of color wheel (CW) procedures and/or interdependent group-oriented reward (IGOR) procedures on inappropriate vocalizations in one third- and one first-grade classroom. Both studies involved the application of…

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…

Analysing Normal and Partial Glossectomee Tongues Using Ultrasound

ERIC Educational Resources Information Center

Bressmann, Tim; Uy, Catherine; Irish, Jonathan C.

2005-01-01

The present study aimed at identifying underlying parameters that govern the shape of the tongue. A functional topography of the tongue surface was developed based on three-dimensional ultrasound scans of sustained speech sounds in ten normal subjects. A principal component analysis extracted three components that explained 89.2% of the variance…

Teachers Learning to Prepare Future Engineers: A Systemic Analysis Through Five Components of Development and Transfer

ERIC Educational Resources Information Center

Hardré, Patricia L.; Ling, Chen; Shehab, Randa L.; Nanny, Mark A.; Refai, Hazem; Nollert, Matthias U.; Ramseyer, Christopher; Wollega, Ebisa D.; Huang, Su-Min; Herron, Jason

2018-01-01

This study used a systemic perspective to examine a five-component experiential process of perceptual and developmental growth, and transfer-to-teaching. Nineteen secondary math and science teachers participated in a year-long, engineering immersion and support experience, with university faculty mentors. Teachers identified critical shifts in…

A Conceptual Framework for Analysis of Communication in Rural Social Systems.

ERIC Educational Resources Information Center

Axinn, George H.

This paper describes a five-component system with ten major internal linkages which may be used as a model for studying information flow in any rural agricultural social system. The major components are production, supply, marketing, research, and extension education. In addition, definitions are offered of the crucial variables affecting…

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…

Callings in Career: A Typological Approach to Essential and Optional Components

ERIC Educational Resources Information Center

Hirschi, Andreas

2011-01-01

A sense of calling in career is supposed to have positive implications for individuals and organizations but current theoretical development is plagued with incongruent conceptualizations of what does or does not constitute a calling. The present study used cluster analysis to identify essential and optional components of a presence of calling…

An Investigation of Curriculum Elements for the Enhancement of the Teaching-Learning Process

ERIC Educational Resources Information Center

Zohrabi, Mohammad

2011-01-01

Any curriculum consists of several components: goals, disposition, duration, needs analysis, learners and teachers, exercises and activities, resources, ways of learning, skills to be acquired, lexis, language structure, and ability assessment. Before setting up a program or course of study, these components should be determined and described in…

Self-selection of two diet components by Tennebrio molitor (Coleoptera: Tenebrionidae) larvae and its impact on fitness

USDA-ARS?s Scientific Manuscript database

We studied the ability of Tenebrio molitor L. (Coleoptera: Tenebrionidae) to self-select optimal ratios of two dietary components to approach nutritional balance and maximum fitness. Life table analysis was used to determine the fitness of T. molitor developing in diet mixtures comprised of four dif...

Investigating Predictors of Listening Comprehension in Third-, Seventh-, and Tenth-Grade Students: A Dominance Analysis Approach

ERIC Educational Resources Information Center

Tighe, Elizabeth L.; Spencer, Mercedes; Schatschneider, Christopher

2015-01-01

This study rank ordered the contributive importance of several predictors of listening comprehension for third, seventh, and tenth graders. Principal components analyses revealed that a three-factor solution with fluency, reasoning, and working memory components provided the best fit across grade levels. Dominance analyses indicated that fluency…

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

PubMed

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

2009-01-01

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

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

PubMed

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

2011-08-01

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

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

NASA Technical Reports Server (NTRS)

Hakim, Nabil S.

1986-01-01

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

Comparison between four dissimilar solar panel configurations

NASA Astrophysics Data System (ADS)

Suleiman, K.; Ali, U. A.; Yusuf, Ibrahim; Koko, A. D.; Bala, S. I.

2017-12-01

Several studies on photovoltaic systems focused on how it operates and energy required in operating it. Little attention is paid on its configurations, modeling of mean time to system failure, availability, cost benefit and comparisons of parallel and series-parallel designs. In this research work, four system configurations were studied. Configuration I consists of two sub-components arranged in parallel with 24 V each, configuration II consists of four sub-components arranged logically in parallel with 12 V each, configuration III consists of four sub-components arranged in series-parallel with 8 V each, and configuration IV has six sub-components with 6 V each arranged in series-parallel. Comparative analysis was made using Chapman Kolmogorov's method. The derivation for explicit expression of mean time to system failure, steady state availability and cost benefit analysis were performed, based on the comparison. Ranking method was used to determine the optimal configuration of the systems. The results of analytical and numerical solutions of system availability and mean time to system failure were determined and it was found that configuration I is the optimal configuration.

Identification and Quantification of Alkaloid in KHR98 and Fragmentation Pathways in HPLC-Q-TOF-MS.

PubMed

Long, Jiakun; Wang, Yang; Xu, Chen; Liu, Tingting; Duan, Gengli; Yu, Yingjia

2018-05-01

Uncaria rhynchophylla is woody climber plant distributed mainly in China and Japan, the stems and hooks of which can be collected as "Gou-Teng" for the treatment of hyperpyrexia, epilepsy and preeclampsia. Fudan University first manufactured KHR98, the extract of Uncaria rhynchophylla. In order to study the active components and structural information of KHR98, we established a HPLC coupled with quadrupole time-of-flight (Q-TOF)-MS method for rapid analysis of alkaloids. In qualitative analysis, a total of eight compounds, including four known alkaloids and four unknown components, were detected and identified. The fragmentation behaviors, such as the fragment ion information and the fragmentation pathways of the eight components were summarized simultaneously, and the concentration of the above components was determined by HPLC-MS method. The quantitative method was proved to be reproducible, precise and accurate. This study shed light on the standardization and quality control of the KHR98 and provided a foundation for the further research on pharmacology, follow-up clinical research and New Drug Applications.

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

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

PubMed

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

2009-11-01

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

Discrimination of healthy and osteoarthritic articular cartilage by Fourier transform infrared imaging and Fisher’s discriminant analysis

PubMed Central

Mao, Zhi-Hua; Yin, Jian-Hua; Zhang, Xue-Xi; Wang, Xiao; Xia, Yang

2016-01-01

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain the quantitative information of content and spatial distribution of principal components in cartilage by combining with chemometrics methods. In this study, FTIRI combining with principal component analysis (PCA) and Fisher’s discriminant analysis (FDA) was applied to identify the healthy and osteoarthritic (OA) articular cartilage samples. Ten 10-μm thick sections of canine cartilages were imaged at 6.25μm/pixel in FTIRI. The infrared spectra extracted from the FTIR images were imported into SPSS software for PCA and FDA. Based on the PCA result of 2 principal components, the healthy and OA cartilage samples were effectively discriminated by the FDA with high accuracy of 94% for the initial samples (training set) and cross validation, as well as 86.67% for the prediction group. The study showed that cartilage degeneration became gradually weak with the increase of the depth. FTIRI combined with chemometrics may become an effective method for distinguishing healthy and OA cartilages in future. PMID:26977354

Application of linear mixed-effects model with LASSO to identify metal components associated with cardiac autonomic responses among welders: a repeated measures study

PubMed Central

Zhang, Jinming; Cavallari, Jennifer M; Fang, Shona C; Weisskopf, Marc G; Lin, Xihong; Mittleman, Murray A; Christiani, David C

2017-01-01

Background Environmental and occupational exposure to metals is ubiquitous worldwide, and understanding the hazardous metal components in this complex mixture is essential for environmental and occupational regulations. Objective To identify hazardous components from metal mixtures that are associated with alterations in cardiac autonomic responses. Methods Urinary concentrations of 16 types of metals were examined and ‘acceleration capacity’ (AC) and ‘deceleration capacity’ (DC), indicators of cardiac autonomic effects, were quantified from ECG recordings among 54 welders. We fitted linear mixed-effects models with least absolute shrinkage and selection operator (LASSO) to identify metal components that are associated with AC and DC. The Bayesian Information Criterion was used as the criterion for model selection procedures. Results Mercury and chromium were selected for DC analysis, whereas mercury, chromium and manganese were selected for AC analysis through the LASSO approach. When we fitted the linear mixed-effects models with ‘selected’ metal components only, the effect of mercury remained significant. Every 1 µg/L increase in urinary mercury was associated with −0.58 ms (−1.03, –0.13) changes in DC and 0.67 ms (0.25, 1.10) changes in AC. Conclusion Our study suggests that exposure to several metals is associated with impaired cardiac autonomic functions. Our findings should be replicated in future studies with larger sample sizes. PMID:28663305

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

PubMed

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

2015-12-01

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

An Investigation of Strategic Decision Making in Service Marketing through Case Study Development and Analysis

ERIC Educational Resources Information Center

Rosetti, Joseph L.; Maceiko, Meghan

2009-01-01

Through the collaborative efforts of an undergraduate student and a professor of marketing, this paper focuses on a case study and corresponding teaching notes developed as a final component of an independent study in service marketing. The case utilizes the hospitality industry as the template for analysis of the appropriateness of marketing…

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

NASA Astrophysics Data System (ADS)

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

2012-07-01

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

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

PubMed

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

2012-07-01

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

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

PubMed

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

2014-09-01

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

What is reflection? A conceptual analysis of major definitions and a proposal of a five-component model.

PubMed

Nguyen, Quoc Dinh; Fernandez, Nicolas; Karsenti, Thierry; Charlin, Bernard

2014-12-01

Although reflection is considered a significant component of medical education and practice, the literature does not provide a consensual definition or model for it. Because reflection has taken on multiple meanings, it remains difficult to operationalise. A standard definition and model are needed to improve the development of practical applications of reflection. This study was conducted in order to identify, explore and analyse the most influential conceptualisations of reflection, and to develop a new theory-informed and unified definition and model of reflection. A systematic review was conducted to identify the 15 most cited authors in papers on reflection published during the period from 2008 to 2012. The authors' definitions and models were extracted. An exploratory thematic analysis was carried out and identified seven initial categories. Categories were clustered and reworded to develop an integrative definition and model of reflection, which feature core components that define reflection and extrinsic elements that influence instances of reflection. Following our review and analysis, five core components of reflection and two extrinsic elements were identified as characteristics of the reflective thinking process. Reflection is defined as the process of engaging the self (S) in attentive, critical, exploratory and iterative (ACEI) interactions with one's thoughts and actions (TA), and their underlying conceptual frame (CF), with a view to changing them and a view on the change itself (VC). Our conceptual model consists of the defining core components, supplemented with the extrinsic elements that influence reflection. This article presents a new theory-informed, five-component definition and model of reflection. We believe these have advantages over previous models in terms of helping to guide the further study, learning, assessment and teaching of reflection. © 2014 John Wiley & Sons Ltd.

Advanced Fingerprint Analysis Project Fingerprint Constituents

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

GM Mong; CE Petersen; TRW Clauss

The work described in this report was focused on generating fundamental data on fingerprint components which will be used to develop advanced forensic techniques to enhance fluorescent detection, and visualization of latent fingerprints. Chemical components of sweat gland secretions are well documented in the medical literature and many chemical techniques are available to develop latent prints, but there have been no systematic forensic studies of fingerprint sweat components or of the chemical and physical changes these substances undergo over time.

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

NASA Astrophysics Data System (ADS)

Wang, Ce; Zhai, Hui

2017-10-01

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

Neural network for photoplethysmographic respiratory rate monitoring

NASA Astrophysics Data System (ADS)

Johansson, Anders

2001-10-01

The photoplethysmographic signal (PPG) includes respiratory components seen as frequency modulation of the heart rate (respiratory sinus arrhythmia, RSA), amplitude modulation of the cardiac pulse, and respiratory induced intensity variations (RIIV) in the PPG baseline. The aim of this study was to evaluate the accuracy of these components in determining respiratory rate, and to combine the components in a neural network for improved accuracy. The primary goal is to design a PPG ventilation monitoring system. PPG signals were recorded from 15 healthy subjects. From these signals, the systolic waveform, diastolic waveform, respiratory sinus arrhythmia, pulse amplitude and RIIV were extracted. By using simple algorithms, the rates of false positive and false negative detection of breaths were calculated for each of the five components in a separate analysis. Furthermore, a simple neural network (NN) was tried out in a combined pattern recognition approach. In the separate analysis, the error rates (sum of false positives and false negatives) ranged from 9.7% (pulse amplitude) to 14.5% (systolic waveform). The corresponding value of the NN analysis was 9.5-9.6%.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Investigation of the anxiolytic effects of linalool, a lavender extract, in the male Sprague-Dawley rat.

PubMed

Cline, Michael; Taylor, John E; Flores, Jesus; Bracken, Samuel; McCall, Suzanne; Ceremuga, Thomas E

2008-02-01

The purpose of our study was to investigate the anxiolytic effects of linalool and its potential interaction with the GABAA receptor in Sprague-Dawley rats. Lavender has been used traditionally as an herbal remedy in the treatment of many medical conditions, including anxiety. Linalool is a major component of the essential oil of lavender. Forty-four rats were divided into 4 groups: control, linalool, midazolam (positive control), and flumazenil and linalool. The behavioral and the neurohormonal/physiological components of anxiety were evaluated. The behavioral component was examined by using the elevated plus maze (open arm time/total time) and the neurohormonal/physiological component by measuring serum catecholamine and corticosterone levels. Data analysis was performed using a 2-tailed Multivariate Analysis of Variance and Sheffe post-hoc test. Our data suggest that linalool does not produce anxiolysis by modulation of the GABAA receptor; however, linalool may modulate motor movements and locomotion.

Biosensors of bacterial cells.

PubMed

Burlage, Robert S; Tillmann, Joshua

2017-07-01

Biosensors are devices which utilize both an electrical component (transducer) and a biological component to study an environment. They are typically used to examine biological structures, organisms and processes. The field of biosensors has now become so large and varied that the technology can often seem impenetrable. Yet the principles which underlie the technology are uncomplicated, even if the details of the mechanisms are elusive. In this review we confine our analysis to relatively current advancements in biosensors for the detection of whole bacterial cells. This includes biosensors which rely on an added labeled component and biosensors which do not have a labeled component and instead detect the binding event or bound structure on the transducer. Methods to concentrate the bacteria prior to biosensor analysis are also described. The variety of biosensor types and their actual and potential uses are described. Copyright © 2016 Elsevier B.V. All rights reserved.

Lippia origanoides chemotype differentiation based on essential oil GC-MS and principal component analysis.

PubMed

Stashenko, Elena E; Martínez, Jairo R; Ruíz, Carlos A; Arias, Ginna; Durán, Camilo; Salgar, William; Cala, Mónica

2010-01-01

Chromatographic (GC/flame ionization detection, GC/MS) and statistical analyses were applied to the study of essential oils and extracts obtained from flowers, leaves, and stems of Lippia origanoides plants, growing wild in different Colombian regions. Retention indices, mass spectra, and standard substances were used in the identification of 139 substances detected in these essential oils and extracts. Principal component analysis allowed L. origanoides classification into three chemotypes, characterized according to their essential oil major components. Alpha- and beta-phellandrenes, p-cymene, and limonene distinguished chemotype A; carvacrol and thymol were the distinctive major components of chemotypes B and C, respectively. Pinocembrin (5,7-dihydroxyflavanone) was found in L. origanoides chemotype A supercritical fluid (CO(2)) extract at a concentration of 0.83+/-0.03 mg/g of dry plant material, which makes this plant an interesting source of an important bioactive flavanone with diverse potential applications in cosmetic, food, and pharmaceutical products.

Heart sound segmentation of pediatric auscultations using wavelet analysis.

PubMed

Castro, Ana; Vinhoza, Tiago T V; Mattos, Sandra S; Coimbra, Miguel T

2013-01-01

Auscultation is widely applied in clinical activity, nonetheless sound interpretation is dependent on clinician training and experience. Heart sound features such as spatial loudness, relative amplitude, murmurs, and localization of each component may be indicative of pathology. In this study we propose a segmentation algorithm to extract heart sound components (S1 and S2) based on it's time and frequency characteristics. This algorithm takes advantage of the knowledge of the heart cycle times (systolic and diastolic periods) and of the spectral characteristics of each component, through wavelet analysis. Data collected in a clinical environment, and annotated by a clinician was used to assess algorithm's performance. Heart sound components were correctly identified in 99.5% of the annotated events. S1 and S2 detection rates were 90.9% and 93.3% respectively. The median difference between annotated and detected events was of 33.9 ms.

Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis

PubMed Central

2011-01-01

Background Cochrane systematic reviews collate and summarise studies of the effects of healthcare interventions. The characteristics of these reviews and the meta-analyses and individual studies they contain provide insights into the nature of healthcare research and important context for the development of relevant statistical and other methods. Methods We classified every meta-analysis with at least two studies in every review in the January 2008 issue of the Cochrane Database of Systematic Reviews (CDSR) according to the medical specialty, the types of interventions being compared and the type of outcome. We provide descriptive statistics for numbers of meta-analyses, numbers of component studies and sample sizes of component studies, broken down by these categories. Results We included 2321 reviews containing 22,453 meta-analyses, which themselves consist of data from 112,600 individual studies (which may appear in more than one meta-analysis). Meta-analyses in the areas of gynaecology, pregnancy and childbirth (21%), mental health (13%) and respiratory diseases (13%) are well represented in the CDSR. Most meta-analyses address drugs, either with a control or placebo group (37%) or in a comparison with another drug (25%). The median number of meta-analyses per review is six (inter-quartile range 3 to 12). The median number of studies included in the meta-analyses with at least two studies is three (inter-quartile range 2 to 6). Sample sizes of individual studies range from 2 to 1,242,071, with a median of 91 participants. Discussion It is clear that the numbers of studies eligible for meta-analyses are typically very small for all medical areas, outcomes and interventions covered by Cochrane reviews. This highlights the particular importance of suitable methods for the meta-analysis of small data sets. There was little variation in number of studies per meta-analysis across medical areas, across outcome data types or across types of interventions being compared. PMID:22114982

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

NASA Technical Reports Server (NTRS)

Childs, D. W.

1984-01-01

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

Effective components of nurse-coordinated care to prevent recurrent coronary events: a systematic review and meta-analysis.

PubMed

Snaterse, Marjolein; Dobber, Jos; Jepma, Patricia; Peters, Ron J G; Ter Riet, Gerben; Boekholdt, S Matthijs; Buurman, Bianca M; Scholte op Reimer, Wilma J M

2016-01-01

Current guidelines on secondary prevention of cardiovascular disease recommend nurse-coordinated care (NCC) as an effective intervention. However, NCC programmes differ widely and the efficacy of NCC components has not been studied. To investigate the efficacy of NCC and its components in secondary prevention of coronary heart disease by means of a systematic review and meta-analysis of randomised controlled trials. 18 randomised trials (11 195 patients in total) using 15 components of NCC met the predefined inclusion criteria. These components were placed into three main intervention strategies: (1) risk factor management (13 studies); (2) multidisciplinary consultation (11 studies) and (3) shared decision making (10 studies). Six trials combined NCC components from all three strategies. In total, 30 outcomes were observed. We summarised observed outcomes in four outcome categories: (1) risk factor levels (16 studies); (2) clinical events (7 studies); (3) patient-perceived health (7 studies) and (4) guideline adherence (3 studies). Compared with usual care, NCC lowered systolic blood pressure (weighted mean difference (WMD) 2.96 mm Hg; 95% CI 1.53 to 4.40 mm Hg) and low-density lipoprotein cholesterol (WMD 0.23 mmol/L; 95% CI 0.10 to 0.36 mmol/L). NCC also improved smoking cessation rates by 25% (risk ratio 1.25; 95% CI 1.08 to 1.43). NCC demonstrated to have an effect on a small number of outcomes. NCC that incorporated blood pressure monitoring, cholesterol control and smoking cessation has an impact on the improvement of secondary prevention. Additionally, NCC is a heterogeneous concept. A shared definition of NCC may facilitate better comparisons of NCC content and outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

An Evaluation of the Effects of Variable Sampling on Component, Image, and Factor Analysis.

ERIC Educational Resources Information Center

Velicer, Wayne F.; Fava, Joseph L.

1987-01-01

Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Takane, Yoshio

2004-01-01

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…

Thermal characterization of three-dimensional printed components for light-emitting diode lighting system applications

NASA Astrophysics Data System (ADS)

Perera, Indika U.; Narendran, Nadarajah; Terentyeva, Valeria

2018-04-01

This study investigated the thermal properties of three-dimensional (3-D) printed components with the potential to be used for thermal management in light-emitting diode (LED) applications. Commercially available filament materials with and without a metal filler were characterized with changes to the print orientation. 3-D printed components with an in-plane orientation had >30 % better effective thermal conductivity compared with components printed with a cross-plane orientation. A finite-element analysis was modeled to understand the effective thermal conductivity changes in the 3-D printed components. A simple thermal resistance model was used to estimate the required effective thermal conductivity of the 3-D printed components to be a viable alternative in LED thermal management applications.

Correlation study between vibrational environmental and failure rates of civil helicopter components

NASA Technical Reports Server (NTRS)

Alaniz, O.

1979-01-01

An investigation of two selected helicopter types, namely, the Models 206A/B and 212, is reported. An analysis of the available vibration and reliability data for these two helicopter types resulted in the selection of ten components located in five different areas of the helicopter and consisting primarily of instruments, electrical components, and other noncritical flight hardware. The potential for advanced technology in suppressing vibration in helicopters was assessed. The are still several unknowns concerning both the vibration environment and the reliability of helicopter noncritical flight components. Vibration data for the selected components were either insufficient or inappropriate. The maintenance data examined for the selected components were inappropriate due to variations in failure mode identification, inconsistent reporting, or inaccurate informaton.

Independent component analysis decomposition of hospital emergency department throughput measures

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Henry

2016-05-01

We present a method adapted from medical sensor data analysis, viz. independent component analysis of electroencephalography data, to health system analysis. Timely and effective care in a hospital emergency department is measured by throughput measures such as median times patients spent before they were admitted as an inpatient, before they were sent home, before they were seen by a healthcare professional. We consider a set of five such measures collected at 3,086 hospitals distributed across the U.S. One model of the performance of an emergency department is that these correlated throughput measures are linear combinations of some underlying sources. The independent component analysis decomposition of the data set can thus be viewed as transforming a set of performance measures collected at a site to a collection of outputs of spatial filters applied to the whole multi-measure data. We compare the independent component sources with the output of the conventional principal component analysis to show that the independent components are more suitable for understanding the data sets through visualizations.

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

PubMed

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

2011-09-02

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

Non-destructive evaluation techniques, high temperature ceramic component parts for gas turbines

NASA Technical Reports Server (NTRS)

Reiter, H.; Hirsekorn, S.; Lottermoser, J.; Goebbels, K.

1984-01-01

This report concerns studies conducted on various tests undertaken on material without destroying the material. Tests included: microradiographic techniques, vibration analysis, high-frequency ultrasonic tests with the addition of evaluation of defects and structure through analysis of ultrasonic scattering data, microwave tests and analysis of sound emission.

Physics Metacognition Inventory Part Ii: Confirmatory Factor Analysis and Rasch Analysis

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-01-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition,…

Skill Components of Task Analysis

ERIC Educational Resources Information Center

Adams, Anne E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Some task analysis methods break down a task into a hierarchy of subgoals. Although an important tool of many fields of study, learning to create such a hierarchy (redescription) is not trivial. To further the understanding of what makes task analysis a skill, the present research examined novices' problems with learning Hierarchical Task…

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

PubMed

Kubayi, Alliance; Toriola, Abel; Didymus, Faye

2018-06-01

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

Cell module and fuel conditioner development

NASA Technical Reports Server (NTRS)

Feret, J. M.

1982-01-01

The efforts performed to develop a phosphoric acid fuel cell (PAFC) stack design having a 10 kW power rating for operation at higher than atmospheric pressure based on the existing Mark II design configuration are described. The work involves: (1) Performance of pertinent functional analysis, trade studies and thermodynamic cycle analysis for requirements definition and system operating parameter selection purposes, (2) characterization of fuel cell materials and components, and performance testing and evaluation of the repeating electrode components, (3) establishment of the state-of-the-art manufacturing technology for all fuel cell components at Westinghouse and the fabrication of short stacks of various sites, and (4) development of a 10 kW PAFC stack design for higher pressure operation utilizing the top down systems engineering approach.

Kmeans-ICA based automatic method for ocular artifacts removal in a motorimagery classification.

PubMed

Bou Assi, Elie; Rihana, Sandy; Sawan, Mohamad

2014-01-01

Electroencephalogram (EEG) recordings aroused as inputs of a motor imagery based BCI system. Eye blinks contaminate the spectral frequency of the EEG signals. Independent Component Analysis (ICA) has been already proved for removing these artifacts whose frequency band overlap with the EEG of interest. However, already ICA developed methods, use a reference lead such as the ElectroOculoGram (EOG) to identify the ocular artifact components. In this study, artifactual components were identified using an adaptive thresholding by means of Kmeans clustering. The denoised EEG signals have been fed into a feature extraction algorithm extracting the band power, the coherence and the phase locking value and inserted into a linear discriminant analysis classifier for a motor imagery classification.

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

PubMed

Schmidt, K; Witte, H

1999-11-01

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

A principal components analysis of dynamic spatial memory biases.

PubMed

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

2008-09-01

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

Clustering of leptin and physical activity with components of metabolic syndrome in Iranian population: an exploratory factor analysis.

PubMed

Esteghamati, Alireza; Zandieh, Ali; Khalilzadeh, Omid; Morteza, Afsaneh; Meysamie, Alipasha; Nakhjavani, Manouchehr; Gouya, Mohammad Mehdi

2010-10-01

Metabolic syndrome (MetS), manifested by insulin resistance, dyslipidemia, central obesity, and hypertension, is conceived to be associated with hyperleptinemia and physical activity. The aim of this study was to elucidate the factors underlying components of MetS and also to test the suitability of leptin and physical activity as additional components of this syndrome. Data of the individuals without history of diabetes mellitus, aged 25-64 years, from third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007), were analyzed. Performing factor analysis on waist circumference, homeostasis model assessment of insulin resistance, systolic blood pressure, triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) led to extraction of two factors which explained around 59.0% of the total variance in both genders. When TG and HDL-C were replaced by TG to HDL-C ratio, a single factor was obtained. In contrast to physical activity, addition of leptin was consistent with one-factor structure of MetS and improved the ability of suggested models to identify obesity (BMI≥30 kg/m2, P<0.01), using receiver-operator characteristics curve analysis. In general, physical activity loaded on the first identified factor. Our study shows that one underlying factor structure of MetS is also plausible and the inclusion of leptin does not interfere with this structure. Further, this study suggests that physical activity influences MetS components via modulation of the main underlying pathophysiologic pathway of this syndrome.

Tidal analysis of surface currents in the Porsanger fjord in northern Norway

NASA Astrophysics Data System (ADS)

Stramska, Malgorzata; Jankowski, Andrzej; Cieszyńska, Agata

2016-04-01

In this presentation we describe surface currents in the Porsanger fjord (Porsangerfjorden) located in the European Arctic in the vicinity of the Barents Sea. Our analysis is based on data collected in the summer of 2014 using High Frequency radar system. Our interest in this fjord comes from the fact that this is a region of high climatic sensitivity. One of our long-term goals is to develop an improved understanding of the undergoing changes and interactions between this fjord and the large-scale atmospheric and oceanic conditions. In order to derive a better understanding of the ongoing changes one must first improve the knowledge about the physical processes that create the environment of the fjord. The present study is the first step in this direction. Our main objective in this presentation is to evaluate the importance of tidal forcing. Tides in the Porsanger fjord are substantial, with tidal range on the order of about 3 meters. Tidal analysis attributes to tides about 99% of variance in sea level time series recorded in Honningsvåg. The most important tidal component based on sea level data is the M2 component (amplitude of ~90 cm). The S2 and N2 components (amplitude of ~ 20 cm) also play a significant role in the semidiurnal sea level oscillations. The most important diurnal component is K1 with amplitude of about 8 cm. Tidal analysis lead us to the conclusion that the most important tidal component in observed surface currents is also the M2 component. The second most important component is the S2 component. Our results indicate that in contrast to sea level, only about 10 - 20% of variance in surface currents can be attributed to tidal currents. This means that about 80-90% of variance can be credited to wind-induced and geostrophic currents. This work was funded by the Norway Grants (NCBR contract No. 201985, project NORDFLUX). Partial support for MS comes from the Institute of Oceanology (IO PAN).

Skill components of task analysis

PubMed Central

Rogers, Wendy A.; Fisk, Arthur D.

2017-01-01

Some task analysis methods break down a task into a hierarchy of subgoals. Although an important tool of many fields of study, learning to create such a hierarchy (redescription) is not trivial. To further the understanding of what makes task analysis a skill, the present research examined novices’ problems with learning Hierarchical Task Analysis and captured practitioners’ performance. All participants received a task description and analyzed three cooking and three communication tasks by drawing on their knowledge of those tasks. Thirty six younger adults (18–28 years) in Study 1 analyzed one task before training and five afterwards. Training consisted of a general handout that all participants received and an additional handout that differed between three conditions: a list of steps, a flow-diagram, and concept map. In Study 2, eight experienced task analysts received the same task descriptions as in Study 1 and demonstrated their understanding of task analysis while thinking aloud. Novices’ initial task analysis scored low on all coding criteria. Performance improved on some criteria but was well below 100 % on others. Practitioners’ task analyses were 2–3 levels deep but also scored low on some criteria. A task analyst’s purpose of analysis may be the reason for higher specificity of analysis. This research furthers the understanding of Hierarchical Task Analysis and provides insights into the varying nature of task analyses as a function of experience. The derived skill components can inform training objectives. PMID:29075044

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.« less

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

PubMed

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

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

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

PubMed Central

Batchelder, Laurie; Brosnan, Mark; Ashwin, Chris

2017-01-01

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

[The influence of tobacco-smoke components on alpha-ketopropionic acid in the pulp of front and rear teeth of chronic smokers].

PubMed

Zurabashvili, D; Chanturia, I; Kapanadze, L; Danelia, G

2010-02-01

The composition of cigarette-smoke is relatively well known in spite of its tremendous complexity. But the analysis of cigarette smoke toxicological influence on biochemical components of tooth enamel, dentine and pulpe is not completely study. The present study was designed to characterize the pulpe biochemical component (alpha-ketopropionic acide) by acute serous pulpit. The total number of 140 patients, age 35-40 (Tobacco-smokers 80, non-smokers - 60) have been investigated. The results suggested, that tobacco-smokers chisel tooth and molars contains less alpha-ketopropionic acide than non-smokers individuals. These studies support the hypothesis of cigarette smoke important role in the tooth support mechanisms. The biochemical activity and function of tooth proteins and amino acids composition must by compared to concentration of tobacco-smoke components.

Systematic review and meta-analysis of interventions targeting sleep and their impact on child body mass index, diet, and physical activity.

PubMed

Yoong, Sze Lin; Chai, Li Kheng; Williams, Christopher M; Wiggers, John; Finch, Meghan; Wolfenden, Luke

2016-05-01

This review aimed to examine the impact of interventions involving an explicit sleep component on child body mass index (BMI), diet, and physical activity. A systematic search was undertaken in six databases to identify randomized controlled trials examining the impact of interventions with a sleep component on child BMI, dietary intake, and/or physical activity. A random effects meta-analysis was conducted assessing the impact of included interventions on child BMI. Of the eight included trials, three enforced a sleep protocol and five targeted sleep as part of multicomponent behavioral interventions either exclusively or together with nutrition and physical activity. Meta-analysis of three studies found that multicomponent behavioral interventions involving a sleep component were not significantly effective in changing child BMI (n = 360,-0.04 kg/m(2) [-0.18, 0.11], I(2)  = 0%); however, only one study included in the meta-analysis successfully changed sleep duration in children. There were some reported improvements to adolescent diet, and only one trial examined the impact on child physical activity, where a significant effect was observed. Findings from the included studies suggest that where improvements in child sleep duration were achieved, a positive impact on child BMI, nutrition, and physical activity was also observed. © 2016 The Obesity Society.

Structures Division

NASA Technical Reports Server (NTRS)

1997-01-01

The NASA Lewis Research Center Structures Division is an international leader and pioneer in developing new structural analysis, life prediction, and failure analysis related to rotating machinery and more specifically to hot section components in air-breathing aircraft engines and spacecraft propulsion systems. The research consists of both deterministic and probabilistic methodology. Studies include, but are not limited to, high-cycle and low-cycle fatigue as well as material creep. Studies of structural failure are at both the micro- and macrolevels. Nondestructive evaluation methods related to structural reliability are developed, applied, and evaluated. Materials from which structural components are made, studied, and tested are monolithics and metal-matrix, polymer-matrix, and ceramic-matrix composites. Aeroelastic models are developed and used to determine the cyclic loading and life of fan and turbine blades. Life models are developed and tested for bearings, seals, and other mechanical components, such as magnetic suspensions. Results of these studies are published in NASA technical papers and reference publication as well as in technical society journal articles. The results of the work of the Structures Division and the bibliography of its publications for calendar year 1995 are presented.

Structures Division 1994 Annual Report

NASA Technical Reports Server (NTRS)

1996-01-01

The NASA Lewis Research Center Structures Division is an international leader and pioneer in developing new structural analysis, life prediction, and failure analysis related to rotating machinery and more specifically to hot section components in air-breathing aircraft engines and spacecraft propulsion systems. The research consists of both deterministic and probabilistic methodology. Studies include, but are not limited to, high-cycle and low-cycle fatigue as well as material creep. Studies of structural failure are at both the micro- and macrolevels. Nondestructive evaluation methods related to structural reliability are developed, applied, and evaluated. Materials from which structural components are made, studied, and tested are monolithics and metal-matrix, polymer-matrix, and ceramic-matrix composites. Aeroelastic models are developed and used to determine the cyclic loading and life of fan and turbine blades. Life models are developed and tested for bearings, seals, and other mechanical components, such as magnetic suspensions. Results of these studies are published in NASA technical papers and reference publication as well as in technical society journal articles. The results of the work of the Structures Division and the bibliography of its publications for calendar year 1994 are presented.

Work-related musculoskeletal disorders (WMDs) risk assessment at core assembly production of electronic components manufacturing company

NASA Astrophysics Data System (ADS)

Yahya, N. M.; Zahid, M. N. O.

2018-03-01

This study conducted to assess the work-related musculoskeletal disorders (WMDs) among the workers at core assembly production in an electronic components manufacturing company located in Pekan, Pahang, Malaysia. The study is to identify the WMDs risk factor and risk level. A set of questionnaires survey based on modified Nordic Musculoskeletal Disorder Questionnaires have been distributed to respective workers to acquire the WMDs risk factor identification. Then, postural analysis was conducted in order to measure the respective WMDs risk level. The analysis were based on two ergonomics assessment tools; Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA). The study found that 30 respondents out of 36 respondents suffered from WMDs especially at shoulder, wrists and lower back. The WMDs risk have been identified from unloading process, pressing process and winding process. In term of the WMDs risk level, REBA and RULA assessment tools have indicated high risk level to unloading and pressing process. Thus, this study had established the WMDs risk factor and risk level of core assembly production in an electronic components manufacturing company at Malaysia environment.

Modeling and Analysis of Mixed Synchronous/Asynchronous Systems

NASA Technical Reports Server (NTRS)

Driscoll, Kevin R.; Madl. Gabor; Hall, Brendan

2012-01-01

Practical safety-critical distributed systems must integrate safety critical and non-critical data in a common platform. Safety critical systems almost always consist of isochronous components that have synchronous or asynchronous interface with other components. Many of these systems also support a mix of synchronous and asynchronous interfaces. This report presents a study on the modeling and analysis of asynchronous, synchronous, and mixed synchronous/asynchronous systems. We build on the SAE Architecture Analysis and Design Language (AADL) to capture architectures for analysis. We present preliminary work targeted to capture mixed low- and high-criticality data, as well as real-time properties in a common Model of Computation (MoC). An abstract, but representative, test specimen system was created as the system to be modeled.

Development of a Rubber-Based Product Using a Mixture Experiment: A Challenging Case Study

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

Kaya, Yahya; Piepel, Gregory F.; Caniyilmaz, Erdal

2013-07-01

Many products used in daily life are made by blending two or more components. The properties of such products typically depend on the relative proportions of the components. Experimental design, modeling, and data analysis methods for mixture experiments provide for efficiently determining the component proportions that will yield a product with desired properties. This article presents a case study of the work performed to develop a new rubber formulation for an o-ring (a circular gasket) with requirements specified on 10 product properties. Each step of the study is discussed, including: 1) identifying the objective of the study and requirements formore » properties of the o-ring, 2) selecting the components to vary and specifying the component constraints, 3) constructing a mixture experiment design, 4) measuring the responses and assessing the data, 5) developing property-composition models, 6) selecting the new product formulation, and 7) confirming the selected formulation in manufacturing. The case study includes some challenging and new aspects, which are discussed in the article.« less

Inventory of File nam.t00z.awp21100.tm00.grib2

Science.gov Websites

analysis Pressure Reduced to MSL [Pa] 002 surface GUST analysis Wind Speed (Gust) [m/s] 003 100 mb HGT -Component of Wind [m/s] 007.2 100 mb VGRD analysis V-Component of Wind [m/s] 008 150 mb HGT analysis Wind [m/s] 012.2 150 mb VGRD analysis V-Component of Wind [m/s] 013 200 mb HGT analysis Geopotential

Response-Related Potentials during Semantic Priming: The Effect of a Speeded Button Response Task on ERPs

PubMed Central

van Vliet, Marijn; Manyakov, Nikolay V.; Storms, Gert; Fias, Wim; Wiersema, Jan R.; Van Hulle, Marc M.

2014-01-01

This study examines the influence of a button response task on the event-related potential (ERP) in a semantic priming experiment. Of particular interest is the N400 component. In many semantic priming studies, subjects are asked to respond to a stimulus as fast and accurately as possible by pressing a button. Response time (RT) is recorded in parallel with an electroencephalogram (EEG) for ERP analysis. In this case, the response occurs in the time window used for ERP analysis and response-related components may overlap with stimulus-locked ones such as the N400. This has led to a recommendation against such a design, although the issue has not been explored in depth. Since studies keep being published that disregard this issue, a more detailed examination of influence of response-related potentials on the ERP is needed. Two experiments were performed in which subjects pressed one of two buttons with their dominant hand in response to word-pairs with varying association strength (AS), indicating a personal judgement of association between the two words. In the first experiment, subjects were instructed to respond as fast and accurately as possible. In the second experiment, subjects delayed their button response to enforce a one second interval between the onset of the target word and the button response. Results show that in the first experiment a P3 component and motor-related potentials (MRPs) overlap with the N400 component, which can cause a misinterpretation of the latter. In order to study the N400 component, the button response should be delayed to avoid contamination of the ERP with response-related components. PMID:24516556

The study of theoretical and experimental feasibilities of the rocket fuel components ignition by laser radiation

NASA Astrophysics Data System (ADS)

Belyaev, Vadim S.; Guterman, Vitaly Y.; Ivanov, Anatoly V.

2004-06-01

The report presents the theoretical and experimental results obtained during the first year of the ISTC project No. 1926. The energy and temporal characteristics of the laser radiation necessary to ignite the working components mixture in a rocket engine combustion chamber have been predicted. Two approaches have been studied: the optical gas fuel laser-induced breakdown; the laser-initiated plasma torch on target surface. The possibilities and conditions of the rocket fuel components ignition by a laser beam in the differently designed combustion chambers have been estimated and studied. The comparative analysis shows that both the optical spark and light focusing on target techniques can ignite the mixture.

[Psychometric analysis of the AF5 multidimensional scale of self-concept in a sample of adolescents and adults in Catalonia].

PubMed

Malo Cerrato, Sara; Bataller Sallent, Sílvia; Casas Aznar, Ferran; Gras Pérez, Ma Eugenia; González Carrasco, Mònica

2011-11-01

The aim of this study is to carry out a psychometric study of the AF5 scale in a sample of 4.825 Catalan subjects from 11 to 63 years-old. They are students from secondary compulsory education (ESO), from high school, middle-level vocational training (CFGM) and from the university. Using a principal component analysis (PCA) the theoretical validity of the components is established and the reliability of the instrument is also analyzed. Differential analyses are performed by gender and normative group using a 2 x 6 factorial design. The normative group variable includes the different levels classified into 6 sub-groups: university, post-compulsory secondary education (high school and CFGM), 4th of ESO, 3rd of ESO, 2nd of ESO and 1st of ESO. The results indicate that the reliability of the Catalan version of the scale is similar to the original scale. The factorial structure also fits with the original model established beforehand. Significant differences by normative group in the four components of self-concept explored (social, family, academic/occupational and physical) are observed. By gender, significant differences appear in the component of physical self-concept, academic and social but not in the family component.

Phenomenological analysis of medical time series with regular and stochastic components

NASA Astrophysics Data System (ADS)

Timashev, Serge F.; Polyakov, Yuriy S.

2007-06-01

Flicker-Noise Spectroscopy (FNS), a general approach to the extraction and parameterization of resonant and stochastic components contained in medical time series, is presented. The basic idea of FNS is to treat the correlation links present in sequences of different irregularities, such as spikes, "jumps", and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study as main information carriers. The tools to extract and analyze the information are power spectra and difference moments (structural functions), which complement the information of each other. The structural function stochastic component is formed exclusively by "jumps" of the dynamic variable while the power spectrum stochastic component is formed by both spikes and "jumps" on every level of the hierarchy. The information "passport" characteristics that are determined by fitting the derived expressions to the experimental variations for the stochastic components of power spectra and structural functions are interpreted as the correlation times and parameters that describe the rate of "memory loss" on these correlation time intervals for different irregularities. The number of the extracted parameters is determined by the requirements of the problem under study. Application of this approach to the analysis of tremor velocity signals for a Parkinsonian patient is discussed.

Comprehensive two-dimensional HPLC to study the interaction of multiple components in Rheum palmatum L. with HSA by coupling a silica-bonded HSA column to a silica monolithic ODS column.

PubMed

Hu, Lianghai; Li, Xin; Feng, Shun; Kong, Liang; Su, Xingye; Chen, Xueguo; Qin, Feng; Ye, Mingliang; Zou, Hanfa

2006-04-01

A mode of comprehensive 2-D LC was developed by coupling a silica-bonded HSA column to a silica monolithic ODS column. This system combined the affinity property of the HSA column and the high-speed separation ability of the monolithic ODS column. The affinity chromatography with HSA-immobilized stationary phase was applied to study the interaction of multiple components in traditional Chinese medicines (TCMs) with HSA according to their affinity to protein in the first dimension. Then the unresolved components retained on the HSA column were further separated on the silica monolithic ODS column in the second dimension. By hyphenating the 2-D separation system to diode array detector and MS detectors, the UV and molecular weight information of the separated compounds can also be obtained. The developed separation system was applied to analysis of the extract of Rheum palmatum L., a number of low-abundant components can be separated on a single peak from the HSA column after normalization of peak heights. Six compounds were preliminarily identified according to their UV and MS spectra. It showed that this system was very useful for biological fingerprinting analysis of the components in TCMs and natural products.

Selective impact of disease on short-term and long-term components of self-reported memory: a population-based HUNT study.

PubMed

Almkvist, Ove; Bosnes, Ole; Bosnes, Ingunn; Stordal, Eystein

2017-05-09

Subjective memory is commonly considered to be a unidimensional measure. However, theories of performance-based memory suggest that subjective memory could be divided into more than one dimension. To divide subjective memory into theoretically related components of memory and explore the relationship to disease. In this study, various aspects of self-reported memory were studied with respect to demographics and diseases in the third wave of the HUNT epidemiological study in middle Norway. The study included all individuals 55 years of age or older, who responded to a nine-item questionnaire on subjective memory and questionnaires on health (n=18 633). A principle component analysis of the memory items resulted in two memory components; the criterion used was an eigenvalue above 1, which accounted for 54% of the total variance. The components were interpreted as long-term memory (LTM; the first component; 43% of the total variance) and short-term memory (STM; the second component; 11% of the total variance). Memory impairment was significantly related to all diseases (except Bechterew's disease), most strongly to brain infarction, heart failure, diabetes, cancer, chronic obstructive pulmonary disease and whiplash. For most diseases, the STM component was more affected than the LTM component; however, in cancer, the opposite pattern was seen. Subjective memory impairment as measured in HUNT contained two components, which were differentially associated with diseases. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

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

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

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

Mission definition study for Stanford relativity satellite. Volume 3: Appendices

NASA Technical Reports Server (NTRS)

1971-01-01

An analysis is presented for the cost of the mission as a function of the following variables: amount of redundancy in the spacecraft, amount of care taken in building the spacecraft (functional and environmental tests, screening of components, quality control, etc), and the number of flights necessary to accomplish the mission. Thermal analysis and mathematical models for the experimental components are presented. The results of computer structural and stress analyses for support and cylinders are discussed. Reliability, quality control, and control system simulation by computer are also considered.

Remembering the dynamic changes in pain intensity and unpleasantness: a psychophysical study.

PubMed

Khoshnejad, Mina; Fortin, Marie C; Rohani, Farzan; Duncan, Gary H; Rainville, Pierre

2014-03-01

This study investigated the short-term memory of dynamic changes in acute pain using psychophysical methods. Pain intensity or unpleasantness induced by painful contact-heat stimuli of 8, 9, or 10s was rated continuously during the stimulus or after a 14-s delay using an electronic visual analog scale in 10 healthy volunteers. Because the continuous visual analog scale time courses contained large amounts of redundant information, a principal component analysis was applied to characterize the main features inherent to both the concurrent rating and retrospective evaluations. Three components explained about 90% of the total variance across all trials and subjects, with the first component reflecting the global perceptual profile, and the second and third components explaining finer perceptual aspects (eg, changes in slope at onset and offset and shifts in peak latency). We postulate that these 3 principal components may provide some information about the structure of the mental representations of what one perceives, stores, and remembers during the course of few seconds. Analysis performed on the components confirmed significant memory distortions and revealed that the discriminative information about pain dimensions in concurrent ratings was partly or completely lost in retrospective ratings. Importantly, our results highlight individual differences affecting these memory processes. These results provide further evidence of the important transformations underlying the processing of pain in explicit memory and raise fundamental questions about the conversion of dynamic nociceptive signals into a mental representation of pain in perception and memory. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Comparative Analysis of Metabolic Syndrome Components in over 15,000 African Americans Identifies Pleiotropic Variants: Results from the PAGE Study

PubMed Central

Carty, Cara L.; Bhattacharjee, Samsiddhi; Haessler, Jeff; Cheng, Iona; Hindorff, Lucia A.; Aroda, Vanita; Carlson, Christopher S.; Hsu, Chun-Nan; Wilkens, Lynne; Liu, Simin; Selvin, Elizabeth; Jackson, Rebecca; North, Kari E.; Peters, Ulrike; Pankow, James S.; Chatterjee, Nilanjan; Kooperberg, Charles

2014-01-01

Background Metabolic syndrome (MetS) refers to the clustering of cardio-metabolic risk factors including dyslipidemia, central adiposity, hypertension and hyperglycemia in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS. Methods and Results Using the Metabochip array in 15,148 African Americans (AA) from the PAGE Study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models which lack power when associations for MetS components are null or have opposite effects, ASSET uses one-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With ASSET, we identify 27 SNPs in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, LPL, APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P< 2.5e-7, the Bonferroni adjusted P-value. Three loci replicate in a Hispanic population, n=5172. A novel AA-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2 and CETP variants, many with opposing effects; e.g. the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity. Conclusions We highlight a method to increase power in large-scale genomic association analyses, and report a novel variant associated with all MetS components in AA. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications. PMID:25023634

Analysis and visualization of single-trial event-related potentials

NASA Technical Reports Server (NTRS)

Jung, T. P.; Makeig, S.; Westerfield, M.; Townsend, J.; Courchesne, E.; Sejnowski, T. J.

2001-01-01

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

The Cuban scorpion Rhopalurus junceus (Scorpiones, Buthidae): component variations in venom samples collected in different geographical areas

PubMed Central

2013-01-01

Backgound The venom of the Cuban scorpion Rhopalurus junceus is poorly study from the point of view of their components at molecular level and the functions associated. The purpose of this article was to conduct a proteomic analysis of venom components from scorpions collected in different geographical areas of the country. Results Venom from the blue scorpion, as it is called, was collected separately from specimens of five distinct Cuban towns (Moa, La Poa, Limonar, El Chote and Farallones) of the Nipe-Sagua-Baracoa mountain massif and fractionated by high performance liquid chromatography (HPLC); the molecular masses of each fraction were ascertained by mass spectrometry analysis. At least 153 different molecular mass components were identified among the five samples analyzed. Molecular masses varied from 466 to 19755 Da. Scorpion HPLC profiles differed among these different geographical locations and the predominant molecular masses of their components. The most evident differences are in the relative concentration of the venom components. The most abundant components presented molecular weights around 4 kDa, known to be K+-channel specific peptides, and 7 kDa, known to be Na+-channel specific peptides, but with small molecular weight differences. Approximately 30 peptides found in venom samples from the different geographical areas are identical, supporting the idea that they all probably belong to the same species, with some interpopulational variations. Differences were also found in the presence of phospholipase, found in venoms from the Poa area (molecular weights on the order of 14 to 19 kDa). The only ubiquitous enzyme identified in the venoms from all five localities studied (hyaluronidase) presented the same 45 kD molecular mass, identified by gel electrophoresis analysis. Conclusions The venom of these scorpions from different geographical areas seem to be similar, and are rich in peptides that have of the same molecular masses of the peptides purified from other scorpions that affect ion-channel functions. PMID:23849540

Significant components of service brand equity in healthcare sector.

PubMed

Chahal, Hardeep; Bala, Madhu

2012-01-01

The purpose of the study is to examine three significant components of service brand equity--i.e. perceived service quality, brand loyalty, and brand image--and analyze relationships among the components of brand equity and also their relationship with brand equity, which is still to be theorized and developed in the healthcare literature. Effective responses were received from 206 respondents, selected conveniently from the localities of Jammu city. After scale item analysis, the data were analyzed using factor analysis, correlations, t-tests, multiple regression analysis and path modeling using SEM. The findings of the study support that service brand equity in the healthcare sector is greatly influenced by brand loyalty and perceived quality. However, brand image has an indirect effect on service brand equity through brand loyalty (mediating variable). The research can be criticized on the ground that data were selected conveniently from respondents residing in the city of Jammu, India. But at the same time the respondents were appropriate for the study as they have adequate knowledge about the hospitals, and were associated with the selected hospital for more than four years. Furthermore, the validity and reliability of the data are strong enough to take care of the limitations of the convenience sampling selection method. The study has unique value addition to the service marketing vis-à-vis healthcare literature, from both theoretical and managerial perspectives. The study establishes a direct and significant relationship between service brand equity and its two components, i.e. perceived service quality and brand loyalty in the healthcare sector. It also provides directions to healthcare service providers in creating, enhancing, and maintaining service brand equity through service quality and brand loyalty, to sustain competitive advantage.

40 CFR 1033.645 - Non-OEM component certification program.

Code of Federal Regulations, 2010 CFR

2010-07-01

... needs of your component. (iv) An engineering analysis (including test data in some cases) demonstrating to us that your component will not cause emissions to increase. The analysis must address both low-hour and end-of-useful life emissions. The amount of information required for this analysis is less...

40 CFR 1033.645 - Non-OEM component certification program.

Code of Federal Regulations, 2011 CFR

2011-07-01

... needs of your component. (iv) An engineering analysis (including test data in some cases) demonstrating to us that your component will not cause emissions to increase. The analysis must address both low-hour and end-of-useful life emissions. The amount of information required for this analysis is less...

Metabolomic and elemental analysis of camel and bovine urine by GC-MS and ICP-MS.

PubMed

Ahamad, Syed Rizwan; Alhaider, Abdul Qader; Raish, Mohammad; Shakeel, Faiyaz

2017-01-01

Recent studies from the author's laboratory indicated that camel urine possesses antiplatelet activity and anti-cancer activity which is not present in bovine urine. The objective of this study is to compare the volatile and elemental components of bovine and camel urine using GC-MS and ICP-MS analysis. We are interested to know the component that performs these biological activities. The freeze dried urine was dissolved in dichloromethane and then derivatization process followed by using BSTFA for GC-MS analysis. Thirty different compounds were analyzed by the derivatization process in full scan mode. For ICP-MS analysis twenty eight important elements were analyzed in both bovine and camel urine. The results of GC-MS and ICP-MS analysis showed marked difference in the urinary metabolites. GC-MS evaluation of camel urine finds a lot of products of metabolism like benzene propanoic acid derivatives, fatty acid derivatives, amino acid derivatives, sugars, prostaglandins and canavanine. Several research reports reveal the metabolomics studies on camel urine but none of them completely reported the pharmacology related metabolomics. The present data of GC-MS suggest and support the previous studies and activities related to camel urine.

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

PubMed

Winkler, Irene; Haufe, Stefan; Tangermann, Michael

2011-08-02

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

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

PubMed

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

2014-07-01

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

Effective Components of TORDIA Cognitive-Behavioral Therapy for Adolescent Depression: Preliminary Findings

ERIC Educational Resources Information Center

Kennard, Betsy D.; Clarke, Greg N.; Weersing, V. Robin; Asarnow, Joan Rosenbaum; Shamseddeen, Wael; Porta, Giovanna; Berk, Michele; Hughes, Jennifer L.; Spirito, Anthony; Emslie, Graham J.; Keller, Martin B.; Wagner, Karen D.; Brent, David A.

2009-01-01

In this report, we conducted a secondary analysis of the Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) study to explore the impact of specific cognitive-behavioral therapy (CBT) treatment components on outcome. In TORDIA, 334 youths (ages 12 to 18 years) with major depressive disorder who had failed to respond to an adequate…

Carrier Based Air Logistics Study: Maintenance Analysis.

DTIC Science & Technology

1982-01-01

MONITORING AGENCY NAME & ADDRESS(If dIierent loan Controling 01116.) 1S. SECURITY CLASS. (of Od. report) gel Unclassified IS&. DECL ASSI IlCATION/ OOWNGRAOIN...Management System AECL Avionics Equipment Configuration List AIMD Aircraft Intermediate Maintenance Department ASO Aviation Supply Office ASW...implementation. Component-specific data, and indentured[2] relationships between components extracted from the Aviation Supply Office ( ASO ) weapon

Subgroups of Adult Basic Education Learners with Different Profiles of Reading Skills

ERIC Educational Resources Information Center

MacArthur, Charles A.; Konold, Timothy R.; Glutting, Joseph J.; Alamprese, Judith A.

2012-01-01

The purpose of this study was to identify subgroups of adult basic education (ABE) learners with different profiles of skills in the core reading components of decoding, word recognition, spelling, fluency, and comprehension. The analysis uses factor scores of those 5 reading components from on a prior investigation of the reliability and…

Towards Solving the Mixing Problem in the Decomposition of Geophysical Time Series by Independent Component Analysis

NASA Technical Reports Server (NTRS)

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

2000-01-01

The use of the Principal Component Analysis technique for the analysis of geophysical time series has been questioned in particular for its tendency to extract components that mix several physical phenomena even when the signal is just their linear sum. We demonstrate with a data simulation experiment that the Independent Component Analysis, a recently developed technique, is able to solve this problem. This new technique requires the statistical independence of components, a stronger constraint, that uses higher-order statistics, instead of the classical decorrelation a weaker constraint, that uses only second-order statistics. Furthermore, ICA does not require additional a priori information such as the localization constraint used in Rotational Techniques.

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

PubMed

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

2016-04-01

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

Evaluation of the accuracy of patient-specific cutting blocks for total knee arthroplasty: a meta-analysis.

PubMed

Cavaignac, Etienne; Pailhé, Regis; Laumond, Gregoire; Murgier, Jérôme; Reina, Nicolas; Laffosse, Jean Michel; Bérard, Emilie; Chiron, Philippe

2015-08-01

Because published studies on the accuracy achieved with patient-specific guides during total knee arthroplasty (TKA) contradict each other, this systematic review and meta-analysis sought to compare radiological TKA outcomes when patient-specific cutting blocks (PSCB) were used to the outcomes when standard manual instrumentation was used. The meta-analysis was implemented according to PRISMA Statement Criteria. The primary endpoint was the hip-knee-ankle (HKA) angle, which represents the leg's mechanical axis. The accuracy of component placement in the coronal and sagittal planes, and the accuracy of femoral component rotation were also compiled. After testing for publication bias and heterogeneity across studies, data were aggregated random-effects modeling when necessary. Fifteen articles were included: 916 total knee arthroplasty cases in the PSCB group and 998 in the MI group. The mechanical axis did not differ between the two groups (weighted mean difference 0.07°; 95 % CI, -0.5° to 0.65°; p = 0.8). Risk ratio analysis revealed no protective effect of using PSCB relative to the appearance of HKA angle outliers (RR = 0.88; 95 % CI, 0.68-1.13; p = 0.3). There was a trend towards a protective effect with PSCB for the risk of femoral component outliers, but the opposite was observed for the tibial component. The implantation procedure was stopped in 30 cases because the surgeon-authors found excessive discrepancies between the intra-operative observations and the pre-operative plan. This meta-analysis found no evidence that using patient-specific cutting blocks provides superior accuracy to using manual instrumentation during TKA.

Methods of Collection of Biological Information for Fatigue Evaluation during Visual Display Terminals (VDT) Operation

NASA Astrophysics Data System (ADS)

Hachiya, Yuriko; Ogai, Harutoshi; Okazaki, Hiroko; Fujisaki, Takeshi; Uchida, Kazuhiko; Oda, Susumu; Wada, Futoshi; Mori, Koji

A method for the analysis of fatigue parameters has been rarely researched in VDT operation. Up to now, fatigue was evaluated by changing of biological information. If signals regarding fatigue are detected, fatigue can be measured. The purpose of this study proposed experiment and analysis method to extract parameters related to fatigue from the biological information during VDT operation using the Independent Component Analysis (ICA). An experiment had 11 subjects. As for the experiment were light loaded VDT operation and heavy loaded VDT operation. A measurement item were amount of work, a mistake number, subjective symptom, surface skin temperature (forehead and apex nasi), heart rate, skin blood flow of forearm and respiratory rate. In the heavy loaded operation group, mistake number and subjective symptom score were increased to compare with the other. And Two-factor ANOVA was used for analysis. The result of mistake number was confirmed that heavy loaded. After the moving averages of waveshape were calculated, it was made to extract independent components by using the ICA. The results of the ICA suggest that the independent components increase according to accumulation of fatigue. Thus, the independent components would be a possible parameter of fatigue. However, further experiments should continue in order to obtain the conclusive finding of our research.

MRM assay for quantitation of complement components in human blood plasma - a feasibility study on multiple sclerosis.

PubMed

Rezeli, Melinda; Végvári, Akos; Ottervald, Jan; Olsson, Tomas; Laurell, Thomas; Marko-Varga, György

2011-12-10

As a proof-of-principle study, a multiple reaction monitoring (MRM) assay was developed for quantitation of proteotypic peptides, representing seven plasma proteins associated with inflammation (complement components and C-reactive protein). The assay development and the sample analysis were performed on a linear ion trap mass spectrometer. We were able to quantify 5 of the 7 target proteins in depleted plasma digests with reasonable reproducibility over a 2 orders of magnitude linear range (RSD≤25%). The assay panel was utilized for the analysis of a small multiple sclerosis sample cohort with 10 diseased and 8 control patients. Copyright © 2011 Elsevier B.V. All rights reserved.

Modular thought in the circuit analysis

NASA Astrophysics Data System (ADS)

Wang, Feng

2018-04-01

Applied to solve the problem of modular thought, provides a whole for simplification's method, the complex problems have become of, and the study of circuit is similar to the above problems: the complex connection between components, make the whole circuit topic solution seems to be more complex, and actually components the connection between the have rules to follow, this article mainly tells the story of study on the application of the circuit modular thought. First of all, this paper introduces the definition of two-terminal network and the concept of two-terminal network equivalent conversion, then summarizes the common source resistance hybrid network modular approach, containing controlled source network modular processing method, lists the common module, typical examples analysis.

Fragman: an R package for fragment analysis

USDA-ARS?s Scientific Manuscript database

Determination of microsatellite lengths or other DNA fragment types is an important initial component of many genetic studies such as mutation detection, linkage and QTL mapping, genetic diversity, pedigree analysis, and detection of heterozygosity. A handful of commercial and freely available softw...

Augmented wedge-shaped glenoid component for the correction of glenoid retroversion: a finite element analysis.

PubMed

Hermida, Juan C; Flores-Hernandez, Cesar; Hoenecke, Heinz R; D'Lima, Darryl D

2014-03-01

This study undertook a computational analysis of a wedged glenoid component for correction of retroverted glenoid arthritic deformity to determine whether a wedge-shaped glenoid component design with a built-in correction for version reduces excessive stresses in the implant, cement, and glenoid bone. Recommendations for correcting retroversion deformity are asymmetric reaming of the anterior glenoid, bone grafting of the posterior glenoid, or a glenoid component with posterior augmentation. Eccentric reaming has the disadvantages of removing normal bone, reducing structural support for the glenoid component, and increasing the risk of bone perforation by the fixation pegs. Bone grafting to correct retroverted deformity does not consistently generate successful results. Finite element models of 2 scapulae models representing a normal and an arthritic retroverted glenoid were implanted with a standard glenoid component (in retroversion or neutral alignment) or a wedged component. Glenohumeral forces representing in vivo loading were applied and stresses and strains computed in the bone, cement, and glenoid component. The retroverted glenoid components generated the highest compressive stresses and decreased cyclic fatigue life predictions for trabecular bone. Correction of retroversion by the wedged glenoid component significantly decreased stresses and predicted greater bone fatigue life. The cement volume estimated to survive 10 million cycles was the lowest for the retroverted components and the highest for neutrally implanted glenoid components and for wedged components. A wedged glenoid implant is a viable option to correct severe arthritic retroversion, reducing the need for eccentric reaming and the risk for implant failure. Copyright © 2014 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Mosby, Inc. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Hoynant, G.

2007-12-01

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

Optimization benefits analysis in production process of fabrication components

NASA Astrophysics Data System (ADS)

Prasetyani, R.; Rafsanjani, A. Y.; Rimantho, D.

2017-12-01

The determination of an optimal number of product combinations is important. The main problem at part and service department in PT. United Tractors Pandu Engineering (shortened to PT.UTPE) Is the optimization of the combination of fabrication component products (known as Liner Plate) which influence to the profit that will be obtained by the company. Liner Plate is a fabrication component that serves as a protector of core structure for heavy duty attachment, such as HD Vessel, HD Bucket, HD Shovel, and HD Blade. The graph of liner plate sales from January to December 2016 has fluctuated and there is no direct conclusion about the optimization of production of such fabrication components. The optimal product combination can be achieved by calculating and plotting the amount of production output and input appropriately. The method that used in this study is linear programming methods with primal, dual, and sensitivity analysis using QM software for Windows to obtain optimal fabrication components. In the optimal combination of components, PT. UTPE provide the profit increase of Rp. 105,285,000.00 for a total of Rp. 3,046,525,000.00 per month and the production of a total combination of 71 units per unit variance per month.

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

PubMed

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

2015-05-01

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

Effect of Gender on the Knowledge of Medicinal Plants: Systematic Review and Meta-Analysis

PubMed Central

Torres-Avilez, Wendy; de Medeiros, Patrícia Muniz

2016-01-01

Knowledge of medicinal plants is not only one of the main components in the structure of knowledge in local medical systems but also one of the most studied resources. This study uses a systematic review and meta-analysis of a compilation of ethnobiological studies with a medicinal plant component and the variable of gender to evaluate whether there is a gender-based pattern in medicinal plant knowledge on different scales (national, continental, and global). In this study, three types of meta-analysis are conducted on different scales. We detect no significant differences on the global level; women and men have the same rich knowledge. On the national and continental levels, significant differences are observed in both directions (significant for men and for women), and a lack of significant differences in the knowledge of the genders is also observed. This finding demonstrates that there is no gender-based pattern for knowledge on different scales. PMID:27795730

Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

NASA Astrophysics Data System (ADS)

Huang, Liang; Ni, Xuan; Ditto, William L.; Spano, Mark; Carney, Paul R.; Lai, Ying-Cheng

2017-01-01

We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on-off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

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

PubMed

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

2008-09-01

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

The neural correlates of implicit self-relevant processing in low self-esteem: an ERP study.

PubMed

Yang, Juan; Guan, Lili; Dedovic, Katarina; Qi, Mingming; Zhang, Qinglin

2012-08-30

Previous neuroimaging studies have shown that implicit and explicit processing of self-relevant (schematic) material elicit activity in many of the same brain regions. Electrophysiological studies on the neural processing of explicit self-relevant cues have generally supported the view that P300 is an index of attention to self-relevant stimuli; however, there has been no study to date investigating the temporal course of implicit self-relevant processing. The current study seeks to investigate the time course involved in implicit self-processing by comparing processing of self-relevant with non-self-relevant words while subjects are making a judgment about color of the words in an implicit attention task. Sixteen low self-esteem participants were examined using event-related potentials technology (ERP). We hypothesized that this implicit attention task would involve P2 component rather than the P300 component. Indeed, P2 component has been associated with perceptual analysis and attentional allocation and may be more likely to occur in unconscious conditions such as this task. Results showed that latency of P2 component, which indexes the time required for perceptual analysis, was more prolonged in processing self-relevant words compared to processing non-self-relevant words. Our results suggested that the judgment of the color of the word interfered with automatic processing of self-relevant information and resulted in less efficient processing of self-relevant word. Together with previous ERP studies examining processing of explicit self-relevant cues, these findings suggest that the explicit and the implicit processing of self-relevant information would not elicit the same ERP components. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed

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

2016-08-01

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

A Network Pharmacology Approach to Determine the Active Components and Potential Targets of Curculigo Orchioides in the Treatment of Osteoporosis.

PubMed

Wang, Nani; Zhao, Guizhi; Zhang, Yang; Wang, Xuping; Zhao, Lisha; Xu, Pingcui; Shou, Dan

2017-10-27

BACKGROUND Osteoporosis is a complex bone disorder with a genetic predisposition, and is a cause of health problems worldwide. In China, Curculigo orchioides (CO) has been widely used as a herbal medicine in the prevention and treatment of osteoporosis. However, research on the mechanism of action of CO is still lacking. The aim of this study was to identify the absorbable components, potential targets, and associated treatment pathways of CO using a network pharmacology approach. MATERIAL AND METHODS We explored the chemical components of CO and used the five main principles of drug absorption to identify absorbable components. Targets for the therapeutic actions of CO were obtained from the PharmMapper server database. Pathway enrichment analysis was performed using the Comparative Toxicogenomics Database (CTD). Cytoscape was used to visualize the multiple components-multiple target-multiple pathways-multiple disease network for CO. RESULTS We identified 77 chemical components of CO, of which 32 components could be absorbed in the blood. These potential active components of CO regulated 83 targets and affected 58 pathways. Data analysis showed that the genes for estrogen receptor alpha (ESR1) and beta (ESR2), and the gene for 11 beta-hydroxysteroid dehydrogenase type 1, or cortisone reductase (HSD11B1) were the main targets of CO. Endocrine regulatory factors and factors regulating calcium reabsorption, steroid hormone biosynthesis, and metabolic pathways were related to these main targets and to ten corresponding compounds. CONCLUSIONS The network pharmacology approach used in our study has attempted to explain the mechanisms for the effects of CO in the prevention and treatment of osteoporosis, and provides an alternative approach to the investigation of the effects of this complex compound.

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

NASA Technical Reports Server (NTRS)

Ko, William L.

2005-01-01

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

Elbow stress indices using finite element analysis

NASA Astrophysics Data System (ADS)

Yu, Lixin

Section III of the ASME Boiler and Pressure Vessel Code (the Code) specifies rules for the design of nuclear power plant components. NB-3600 of the Code presents a simplified design method using stress indices---Scalar Coefficients used the modify straight pipe stress equations so that they can be applied to elbows, tees and other piping components. The stress indices of piping components are allowed to be determined both analytically and experimentally. This study concentrates on the determination of B2 stress indices for elbow components using finite element analysis (FEA). First, the previous theoretical, numerical and experimental investigations on elbow behavior were comprehensively reviewed, as was the philosophy behind the use of stress indices. The areas of further research was defined. Then, a comprehensive investigation was carried out to determine how the finite element method should be used to correctly simulate an elbow's structural behavior. This investigation included choice of element type, convergence of mesh density, use of boundary restraint and a reconciliation study between FEA and laboratory experiments or other theoretical formulations in both elastic and elasto-plastic domain. Results from different computer programs were also compared. Reasonably good reconciliation was obtained. Appendix II of the Code describes the experimental method to determine B2 stress indices based on load-deflection curves. This procedure was used to compute the B2 stress indices for various loading modes on one particular elbow configuration. The B2 stress indices thus determined were found to be about half of the value calculated from the Code equation. Then the effect on B2 stress indices of those factors such as internal pressure and flange attachments were studied. Finally, the investigation was extended to other configurations of elbow components. A parametric study was conducted on different elbow sizes and schedules. Regression analysis was then used to obtain a modified coefficient and exponent for the Code equation used to calculate B2 index for elbows.

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

PubMed

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

2011-11-01

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

Preparation and analysis of a two-components breath figure at the nanoscale

NASA Astrophysics Data System (ADS)

Kofman, R.; Allione, M.; Celestini, F.; Barkay, Z.; Lereah, Y.

2008-12-01

Solid/liquid two-components Ga-Pb structures in isolated nanometer sized particles have been produced and studied by electron microscopy. Production is based on the breath figure technique and we investigate the way the two components are distributed. We clearly identify two growth regimes associated with the two different ways a Pb atom incorporates into a Ga nanodrop. Using TEM and SEM, the shape and microstructure of the nanoparticles are studied and the results obtained are in good agreement with the proposed model. The experimental technique used appears to be appropriate to produce Pb nanocrystals in liquid Ga nano-containers.

Analysis of symptoms and their potential associations with e-liquids' components: a social media study.

PubMed

Li, Qiudan; Zhan, Yongcheng; Wang, Lei; Leischow, Scott J; Zeng, Daniel Dajun

2016-07-30

The electronic cigarette (e-cigarette) market has grown rapidly in recent years. However, causes of e-cigarette related symptoms among users and their impact on health remain uncertain. This research aims to mine the potential relationships between symptoms and e-liquid components, such as propylene glycol (PG), vegetable glycerine (VG), flavor extracts, and nicotine, using user-generated data collected from Reddit. A total of 3605 e-liquid related posts from January 1st, 2011 to June 30th, 2015 were collected from Reddit. Then the patterns of VG/PG distribution among different flavors were analyzed. Next, the relationship between throat hit, which was a typical symptom of e-cigarette use, and e-liquid components was studied. Finally, other symptoms were examined based on e-liquid components and user sentiment. We discovered 3 main sets of findings: 1) We identified three groups of flavors in terms of VG/PG ratios. Fruits, cream, and nuts flavors were similar. Sweet, menthol, and seasonings flavors were classified into one group. Tobacco and beverages flavors were the third group. 2) Throat hit was analyzed and we found that menthol and tobacco flavors, as well as high ratios of PG and nicotine level, could produce more throat hit. 3) A total of 9 systems of 25 symptoms were identified and analyzed. Components including VG/PG ratio, flavor, and nicotine could be possible reasons for these symptoms. E-liquid components shown to be associated with e-cigarette use symptomology were VG/PG ratios, flavors, and nicotine levels. Future analysis could be conducted based on the structure of e-liquid components categories built in this study. Information revealed in this study could be utilized by e-cigarette users to understand the relationship between e-liquid type and symptoms experienced, by vendors to choose appropriate recipes of e-liquid, and by policy makers to develop new regulations.

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.

Tracking variations in fluorescent-dissolved organic matter in an aerobic submerged membrane bioreactor using excitation-emission matrix spectra combined with parallel factor analysis.

PubMed

Hur, Jin; Shin, Jaewon; Kang, Minsun; Cho, Jinwoo

2014-08-01

In this study, the variations in the fluorescent components of dissolved organic matter (DOM) were tracked for an aerobic submerged membrane bioreactor (MBR) at three different operation stages (cake layer formation, condensation, and after cleaning). The fluorescent DOM was characterized using excitation-emission matrix (EEM) spectroscopy combined with parallel factor analysis (PARAFAC). Non-aromatic carbon structures appear to be actively involved in the membrane fouling for the cake layer formation stage as revealed by much higher UV-absorbing DOM per organic carbon found in the effluent versus those inside the reactor. Four fluorescent components were successfully identified from the reactor and the effluent DOMs by EEM-PARAFAC modeling. Among those in the reactor, microbial humic-like fluorescence was the most abundant component at the cake layer formation stage and tryptophan-like fluorescence at the condensation stage. In contrast to the reactor, relatively similar composition of the PARAFAC components was exhibited for the effluent at all three stages. Tryptophan-like fluorescence displayed the largest difference between the reactor and the effluent, suggesting that this component could be a good tracer for membrane fouling. It appears that the fluorescent DOM was involved in membrane fouling by cake layer formation rather than by internal pore adsorption because its difference between the reactor and the effluent was the highest among all the four components, even after the membrane cleaning. Our study provided an insight into the fate and the behavior fluorescent DOM components for an MBR system, which could be an indicator of the membrane fouling.

Evaluation of automated sample preparation, retention time locked gas chromatography-mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species.

PubMed

Gu, Qun; David, Frank; Lynen, Frédéric; Rumpel, Klaus; Dugardeyn, Jasper; Van Der Straeten, Dominique; Xu, Guowang; Sandra, Pat

2011-05-27

In this paper, automated sample preparation, retention time locked gas chromatography-mass spectrometry (GC-MS) and data analysis methods for the metabolomics study were evaluated. A miniaturized and automated derivatisation method using sequential oximation and silylation was applied to a polar extract of 4 types (2 types×2 ages) of Arabidopsis thaliana, a popular model organism often used in plant sciences and genetics. Automation of the derivatisation process offers excellent repeatability, and the time between sample preparation and analysis was short and constant, reducing artifact formation. Retention time locked (RTL) gas chromatography-mass spectrometry was used, resulting in reproducible retention times and GC-MS profiles. Two approaches were used for data analysis. XCMS followed by principal component analysis (approach 1) and AMDIS deconvolution combined with a commercially available program (Mass Profiler Professional) followed by principal component analysis (approach 2) were compared. Several features that were up- or down-regulated in the different types were detected. Copyright © 2011 Elsevier B.V. All rights reserved.

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

PubMed

Nguyen, Hang Vo-Minh; Choi, Jung Hyun

2015-06-01

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

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

Silva, F. S.

Functionally graded components exhibit spatial variations of mechanical properties in contrast with, and as an alternative to, purely homogeneous components. A large class of graded materials, however, are in fact mostly homogeneous materials with property variations (chemical or mechanical) restricted to a specific area or layer produced by applying for example a coating or by introducing sub-surface residual stresses. However, it is also possible to obtain graded materials with a smooth transition of mechanical properties along the entire component, for example in a 40 mm component. This is possible, for example, by using centrifugal casting technique or incremental melting andmore » solidification technique. In this paper we will study fully metallic functionally graded components with a smooth gradient, focusing on fatigue crack propagation. Fatigue propagation will be assessed in the direction parallel to the gradation (in different homogeneous layers of the functionally graded component) to assess what would be fatigue crack propagation on the direction perpendicular to the gradation. Fatigue crack growth rate (standard mode I fatigue crack growth) will be correlated to the mode I stress intensity factor range. Other mechanical properties of different layers of the component (Young's modulus) will also be considered in this analysis. The effect of residual stresses along the component gradation on crack propagation will also be taken into account. A qualitative analysis of the effects of some important features, present in functionally graded materials, will be made based on the obtained results.« less

[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.

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,…

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

PubMed

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

2013-04-01

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

Comparison of cemented and uncemented fixation in total knee arthroplasty.

PubMed

Brown, Thomas E; Harper, Benjamin L; Bjorgul, Kristian

2013-05-01

As a result of reading this article, physicians should be able to :1. Understand the rationale behind using uncemented fixation in total knee arthroplasty.2.Discuss the current literature comparing cemented and uncemented total knee arthroplasty3. Describe the value of radiostereographic analysis in assessing implant stability.4. Appreciate the limitations in the available literature advocating 1 mode of fixation in total knee arthroplasty. Total knee arthroplasty performed worldwide uses either cemented, cementless, or hybrid (cementless femur with a cemented tibia) fixation of the components. No recent literature review concerning the outcomes of cemented vs noncemented components has been performed. Noncemented components offer the potential advantage of a biologic interface between the bone and implants, which could demonstrate the greatest advantage in long-term durable fixation in the follow-up of young patients undergoing arthroplasty. Several advances have been made in the backing of the tibial components that have not been available long enough to yield long-term comparative follow-up studies. Short-term radiostereographic analysis studies have yielded differing results. Although long-term, high-quality studies are still needed, material advances in biologic fixation surfaces, such as trabecular metal and hydroxyapatite, may offer promising results for young and active patients undergoing total knee arthroplasty when compared with traditional cemented options. Copyright 2013, SLACK Incorporated.

[Gene method for inconsistent hydrological frequency calculation. I: Inheritance, variability and evolution principles of hydrological genes].

PubMed

Xie, Ping; Wu, Zi Yi; Zhao, Jiang Yan; Sang, Yan Fang; Chen, Jie

2018-04-01

A stochastic hydrological process is influenced by both stochastic and deterministic factors. A hydrological time series contains not only pure random components reflecting its inheri-tance characteristics, but also deterministic components reflecting variability characteristics, such as jump, trend, period, and stochastic dependence. As a result, the stochastic hydrological process presents complicated evolution phenomena and rules. To better understand these complicated phenomena and rules, this study described the inheritance and variability characteristics of an inconsistent hydrological series from two aspects: stochastic process simulation and time series analysis. In addition, several frequency analysis approaches for inconsistent time series were compared to reveal the main problems in inconsistency study. Then, we proposed a new concept of hydrological genes origined from biological genes to describe the inconsistent hydrolocal processes. The hydrologi-cal genes were constructed using moments methods, such as general moments, weight function moments, probability weight moments and L-moments. Meanwhile, the five components, including jump, trend, periodic, dependence and pure random components, of a stochastic hydrological process were defined as five hydrological bases. With this method, the inheritance and variability of inconsistent hydrological time series were synthetically considered and the inheritance, variability and evolution principles were fully described. Our study would contribute to reveal the inheritance, variability and evolution principles in probability distribution of hydrological elements.

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.