Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

A survey about methods dedicated to epistasis detection.

PubMed

Niel, Clément; Sinoquet, Christine; Dina, Christian; Rocheleau, Ghislain

2015-01-01

During the past decade, findings of genome-wide association studies (GWAS) improved our knowledge and understanding of disease genetics. To date, thousands of SNPs have been associated with diseases and other complex traits. Statistical analysis typically looks for association between a phenotype and a SNP taken individually via single-locus tests. However, geneticists admit this is an oversimplified approach to tackle the complexity of underlying biological mechanisms. Interaction between SNPs, namely epistasis, must be considered. Unfortunately, epistasis detection gives rise to analytic challenges since analyzing every SNP combination is at present impractical at a genome-wide scale. In this review, we will present the main strategies recently proposed to detect epistatic interactions, along with their operating principle. Some of these methods are exhaustive, such as multifactor dimensionality reduction, likelihood ratio-based tests or receiver operating characteristic curve analysis; some are non-exhaustive, such as machine learning techniques (random forests, Bayesian networks) or combinatorial optimization approaches (ant colony optimization, computational evolution system).

Ideal discrimination of discrete clinical endpoints using multilocus genotypes.

PubMed

Hahn, Lance W; Moore, Jason H

2004-01-01

Multifactor Dimensionality Reduction (MDR) is a method for the classification and prediction of discrete clinical endpoints using attributes constructed from multilocus genotype data. Empirical studies with both real and simulated data suggest that MDR has good power for detecting gene-gene interactions in the absence of independent main effects. The purpose of this study is to develop an objective, theory-driven approach to evaluate the strengths and limitations of MDR. To accomplish this goal, we borrow concepts from ideal observer analysis used in visual perception to evaluate the theoretical limits of classifying and predicting discrete clinical endpoints using multilocus genotype data. We conclude that MDR ideally discriminates between low risk and high risk subjects using attributes constructed from multilocus genotype data. We also how that the classification approach used once a multilocus attribute is constructed is similar to that of a naive Bayes classifier. This study provides a theoretical foundation for the continued development, evaluation, and application of the MDR as a data mining tool in the domain of statistical genetics and genetic epidemiology.

Interactions among genetic variants in apoptosis pathway genes, reflux symptoms, body mass index, and smoking indicate two distinct etiologic patterns of esophageal adenocarcinoma.

PubMed

Zhai, Rihong; Chen, Feng; Liu, Geoffrey; Su, Li; Kulke, Matthew H; Asomaning, Kofi; Lin, Xihong; Heist, Rebecca S; Nishioka, Norman S; Sheu, Chau-Chyun; Wain, John C; Christiani, David C

2010-05-10

Apoptosis pathway, gastroesophageal reflux symptoms (reflux), higher body mass index (BMI), and tobacco smoking have been individually associated with esophageal adenocarcinoma (EA) development. However, how multiple factors jointly affect EA risk remains unclear. In total, 305 patients with EA and 339 age- and sex-matched controls were studied. High-order interactions among reflux, BMI, smoking, and functional polymorphisms in five apoptotic genes (FAS, FASL, IL1B, TP53BP, and BAT3) were investigated by entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional logistic regression (LR) models. In LR analysis, reflux, BMI, and smoking were significantly associated with EA risk, with reflux as the strongest individual factor. No individual single nucleotide polymorphism was associated with EA susceptibility. However, there was a two-way interaction between IL1B + 3954C>T and reflux (P = .008). In both CART and MDR analyses, reflux was also the strongest individual factor for EA risk. In individuals with reflux symptoms, CART analysis indicated that strongest interaction was among variant genotypes of IL1B + 3954C>T and BAT3S625P, higher BMI, and smoking (odds ratio [OR], 5.76; 95% CI, 2.48 to 13.38), a finding independently found using MDR analysis. In contrast, for participants without reflux symptoms, the strongest interaction was found between higher BMI and smoking (OR, 3.27; 95% CI, 1.88 to 5.68), also echoed by entropy-based MDR analysis. Although a history of reflux is an important risk for EA, multifactor interactions also play important roles in EA risk. Gene-environment interaction patterns differ between patients with and without reflux symptoms.

A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.

PubMed

Moore, Jason H; Gilbert, Joshua C; Tsai, Chia-Ti; Chiang, Fu-Tien; Holden, Todd; Barney, Nate; White, Bill C

2006-07-21

Detecting, characterizing, and interpreting gene-gene interactions or epistasis in studies of human disease susceptibility is both a mathematical and a computational challenge. To address this problem, we have previously developed a multifactor dimensionality reduction (MDR) method for collapsing high-dimensional genetic data into a single dimension (i.e. constructive induction) thus permitting interactions to be detected in relatively small sample sizes. In this paper, we describe a comprehensive and flexible framework for detecting and interpreting gene-gene interactions that utilizes advances in information theory for selecting interesting single-nucleotide polymorphisms (SNPs), MDR for constructive induction, machine learning methods for classification, and finally graphical models for interpretation. We illustrate the usefulness of this strategy using artificial datasets simulated from several different two-locus and three-locus epistasis models. We show that the accuracy, sensitivity, specificity, and precision of a naïve Bayes classifier are significantly improved when SNPs are selected based on their information gain (i.e. class entropy removed) and reduced to a single attribute using MDR. We then apply this strategy to detecting, characterizing, and interpreting epistatic models in a genetic study (n = 500) of atrial fibrillation and show that both classification and model interpretation are significantly improved.

Estimation and analysis of multifactor productivity in truck transportation : 1987 - 2003

DOT National Transportation Integrated Search

2009-02-01

The analysis has three objectives: 1) to estimate multifactor : productivity (MFP) in truck transportation during : 1987-2003; 2) to examine changes in multifactor productivity : in U.S. truck transportation, over time, and : to compare these changes...

A Guide to the Multifactored Evaluation (MFE).

ERIC Educational Resources Information Center

Ohio Coalition for the Education of Children with Disabilities, Marion.

This guide provides Ohio parents of children with disabilities with information on multifactored evaluations. It begins by discussing the Intervention Assistance Team and what occurs at the assistance team meeting. It also explains that to begin the multifactored evaluation process, the parent must complete a "Request for Parent Consent for…

Antioxidant Defense Enzyme Genes and Asthma Susceptibility: Gender-Specific Effects and Heterogeneity in Gene-Gene Interactions between Pathogenetic Variants of the Disease

PubMed Central

Polonikov, Alexey V.; Ivanov, Vladimir P.; Bogomazov, Alexey D.; Freidin, Maxim B.; Illig, Thomas; Solodilova, Maria A.

2014-01-01

Oxidative stress resulting from an increased amount of reactive oxygen species and an imbalance between oxidants and antioxidants plays an important role in the pathogenesis of asthma. The present study tested the hypothesis that genetic susceptibility to allergic and nonallergic variants of asthma is determined by complex interactions between genes encoding antioxidant defense enzymes (ADE). We carried out a comprehensive analysis of the associations between adult asthma and 46 single nucleotide polymorphisms of 34 ADE genes and 12 other candidate genes of asthma in Russian population using set association analysis and multifactor dimensionality reduction approaches. We found for the first time epistatic interactions between ADE genes underlying asthma susceptibility and the genetic heterogeneity between allergic and nonallergic variants of the disease. We identified GSR (glutathione reductase) and PON2 (paraoxonase 2) as novel candidate genes for asthma susceptibility. We observed gender-specific effects of ADE genes on the risk of asthma. The results of the study demonstrate complexity and diversity of interactions between genes involved in oxidative stress underlying susceptibility to allergic and nonallergic asthma. PMID:24895604

Multi-factor authentication using quantum communication

DOEpatents

Hughes, Richard John; Peterson, Charles Glen; Thrasher, James T.; Nordholt, Jane E.; Yard, Jon T.; Newell, Raymond Thorson; Somma, Rolando D.

2018-02-06

Multi-factor authentication using quantum communication ("QC") includes stages for enrollment and identification. For example, a user enrolls for multi-factor authentication that uses QC with a trusted authority. The trusted authority transmits device factor information associated with a user device (such as a hash function) and user factor information associated with the user (such as an encrypted version of a user password). The user device receives and stores the device factor information and user factor information. For multi-factor authentication that uses QC, the user device retrieves its stored device factor information and user factor information, then transmits the user factor information to the trusted authority, which also retrieves its stored device factor information. The user device and trusted authority use the device factor information and user factor information (more specifically, information such as a user password that is the basis of the user factor information) in multi-factor authentication that uses QC.

Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

PubMed

Naushad, Shaik Mohammad; Ramaiah, M Janaki; Pavithrakumari, Manickam; Jayapriya, Jaganathan; Hussain, Tajamul; Alrokayan, Salman A; Gottumukkala, Suryanarayana Raju; Digumarti, Raghunadharao; Kutala, Vijay Kumar

2016-04-15

In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 μg/day) and B12 (6 μg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1. Copyright © 2016 Elsevier B.V. All rights reserved.

CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.

PubMed

Yang, Cheng-Hong; Chuang, Li-Yeh; Lin, Yu-Da

2017-08-01

Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to detect the potential epistasis in large-scale SNP datasets. We propose a new algorithm which combines the differential evolution (DE) algorithm with a classification based multifactor-dimensionality reduction (CMDR), termed DECMDR. DECMDR uses the CMDR as a fitness measure to evaluate values of solutions in DE process for scanning the potential statistical epistasis in GWAS. The results indicated that DECMDR outperforms the existing algorithms in terms of detection success rate by the large simulation and real data obtained from the Wellcome Trust Case Control Consortium. For running time comparison, DECMDR can efficient to apply the CMDR to detect the significant association between cases and controls amongst all possible SNP combinations in GWAS. DECMDR is freely available at https://goo.gl/p9sLuJ . chuang@isu.edu.tw or e0955767257@yahoo.com.tw. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Capturing pair-wise epistatic effects associated with three agronomic traits in barley.

PubMed

Xu, Yi; Wu, Yajun; Wu, Jixiang

2018-04-01

Genetic association mapping has been widely applied to determine genetic markers favorably associated with a trait of interest and provide information for marker-assisted selection. Many association mapping studies commonly focus on main effects due to intolerable computing intensity. This study aims to select several sets of DNA markers with potential epistasis to maximize genetic variations of some key agronomic traits in barley. By doing so, we integrated a MDR (multifactor dimensionality reduction) method with a forward variable selection approach. This integrated approach was used to determine single nucleotide polymorphism pairs with epistasis effects associated with three agronomic traits: heading date, plant height, and grain yield in barley from the barley Coordinated Agricultural Project. Our results showed that four, seven, and five SNP pairs accounted for 51.06, 45.66 and 40.42% for heading date, plant height, and grain yield, respectively with epistasis being considered, while corresponding contributions to these three traits were 45.32, 31.39, 31.31%, respectively without epistasis being included. The results suggested that epistasis model was more effective than non-epistasis model in this study and can be more preferred for other applications.

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

PubMed

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

A primer on multifactor productivity : description, benefits, and uses

DOT National Transportation Integrated Search

2008-04-01

This primer presents a description of multifactor : productivity (MFP) and its calculation. Productivity : is an important measure of the state of the : economy at various levels: firm, industry, sectoral, : and the macroeconomic. The method describe...

An analysis of labor and multifactor productivity in air transportation : 1990 - 2001

DOT National Transportation Integrated Search

2002-01-01

The analysis has two main objectives: 1) to examine : labor productivity and multifactor productivity : (MFP) in U.S. air transportation during the 1990 : to 2001 period and to compare these measures to : those of two other transportation subsectors ...

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

NASA Astrophysics Data System (ADS)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

A comparison of linear and nonlinear statistical techniques in performance attribution.

PubMed

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Validation Results

Cancer.gov

Risk Factor Assessment Branch (RFAB) staff have assessed the validity of the Multifactor Screener in several studies: NCI's Observing Protein and Energy (OPEN) Study, the Eating at America's Table Study (EATS), and the joint NIH-AARP Diet and Health Study.

Summarizing techniques that combine three non-parametric scores to detect disease-associated 2-way SNP-SNP interactions.

PubMed

Sengupta Chattopadhyay, Amrita; Hsiao, Ching-Lin; Chang, Chien Ching; Lian, Ie-Bin; Fann, Cathy S J

2014-01-01

Identifying susceptibility genes that influence complex diseases is extremely difficult because loci often influence the disease state through genetic interactions. Numerous approaches to detect disease-associated SNP-SNP interactions have been developed, but none consistently generates high-quality results under different disease scenarios. Using summarizing techniques to combine a number of existing methods may provide a solution to this problem. Here we used three popular non-parametric methods-Gini, absolute probability difference (APD), and entropy-to develop two novel summary scores, namely principle component score (PCS) and Z-sum score (ZSS), with which to predict disease-associated genetic interactions. We used a simulation study to compare performance of the non-parametric scores, the summary scores, the scaled-sum score (SSS; used in polymorphism interaction analysis (PIA)), and the multifactor dimensionality reduction (MDR). The non-parametric methods achieved high power, but no non-parametric method outperformed all others under a variety of epistatic scenarios. PCS and ZSS, however, outperformed MDR. PCS, ZSS and SSS displayed controlled type-I-errors (<0.05) compared to GS, APDS, ES (>0.05). A real data study using the genetic-analysis-workshop 16 (GAW 16) rheumatoid arthritis dataset identified a number of interesting SNP-SNP interactions. © 2013 Elsevier B.V. All rights reserved.

No Association Between Variant N-acetyltransferase Genes, Cigarette Smoking and Prostate Cancer Susceptibility Among Men of African Descent

PubMed Central

Kidd, La Creis Renee; VanCleave, Tiva T.; Doll, Mark A.; Srivastava, Daya S.; Thacker, Brandon; Komolafe, Oyeyemi; Pihur, Vasyl; Brock, Guy N.; Hein, David W.

2011-01-01

Objective We evaluated the individual and combination effects of NAT1, NAT2 and tobacco smoking in a case-control study of 219 incident prostate cancer (PCa) cases and 555 disease-free men. Methods Allelic discriminations for 15 NAT1 and NAT2 loci were detected in germ-line DNA samples using Taqman polymerase chain reaction (PCR) assays. Single gene, gene-gene and gene-smoking interactions were analyzed using logistic regression models and multi-factor dimensionality reduction (MDR) adjusted for age and subpopulation stratification. MDR involves a rigorous algorithm that has ample statistical power to assess and visualize gene-gene and gene-environment interactions using relatively small samples sizes (i.e., 200 cases and 200 controls). Results Despite the relatively high prevalence of NAT1*10/*10 (40.1%), NAT2 slow (30.6%), and NAT2 very slow acetylator genotypes (10.1%) among our study participants, these putative risk factors did not individually or jointly increase PCa risk among all subjects or a subset analysis restricted to tobacco smokers. Conclusion Our data do not support the use of N-acetyltransferase genetic susceptibilities as PCa risk factors among men of African descent; however, subsequent studies in larger sample populations are needed to confirm this finding. PMID:21709725

Examination of association of genes in the serotonin system to autism.

PubMed

Anderson, B M; Schnetz-Boutaud, N C; Bartlett, J; Wotawa, A M; Wright, H H; Abramson, R K; Cuccaro, M L; Gilbert, J R; Pericak-Vance, M A; Haines, J L

2009-07-01

Autism is characterized as one of the pervasive developmental disorders, a spectrum of often severe behavioral and cognitive disturbances of early development. The high heritability of autism has driven multiple efforts to identify genetic variation that increases autism susceptibility. Numerous studies have suggested that variation in peripheral and central metabolism of serotonin (5-hydroxytryptamine) may play a role in the pathophysiology of autism. We screened 403 autism families for 45 single nucleotide polymorphisms in ten serotonin pathway candidate genes. Although genome-wide linkage scans in autism have provided support for linkage to various loci located within the serotonin pathway, our study does not provide strong evidence for linkage to any specific gene within the pathway. The most significant association (p = 0.0002; p = 0.02 after correcting for multiple comparisons) was found at rs1150220 (HTR3A) located on chromosome 11 ( approximately 113 Mb). To test specifically for multilocus effects, multifactor dimensionality reduction was employed, and a significant two-way interaction (p value = 0.01) was found between rs10830962, near MTNR1B (chromosome11; 92,338,075 bp), and rs1007631, near SLC7A5 (chromosome16; 86,413,596 bp). These data suggest that variation within genes on the serotonin pathway, particularly HTR3A, may have modest effects on autism risk.

PACSIN2 polymorphism is associated with thiopurine-induced hematological toxicity in children with acute lymphoblastic leukaemia undergoing maintenance therapy.

PubMed

Smid, Alenka; Karas-Kuzelicki, Natasa; Jazbec, Janez; Mlinaric-Rascan, Irena

2016-07-25

Adequate maintenance therapy for childhood acute lymphoblastic leukemia (ALL), with 6-mercaptopurine as an essential component, is necessary for retaining durable remission. Interruptions or discontinuations of the therapy due to drug-related toxicities, which can be life threatening, may result in an increased risk of relapse. In this retrospective study including 305 paediatric ALL patients undergoing maintenance therapy, we systematically investigated the individual and combined effects of genetic variants of folate pathway enzymes, as well as of polymorphisms in PACSIN2 and ITPA, on drug-induced toxicities by applying a multi-analytical approach including logistic regression (LR), classification and regression tree (CART) and generalized multifactor dimensionality reduction (GMDR). In addition to the TPMT genotype, confirmed to be a major determinant of drug related toxicities, we identified the PACSIN2 rs2413739TT genotype as being a significant risk factor for 6-MP-induced toxicity in wild-type TPMT patients. A gene-gene interaction between MTRR (rs1801394) and MTHFR (rs1801133) was detected by GMDR and proved to have an independent effect on the risk of stomatitis, as shown by LR analysis. To our knowledge, this is the first study showing PACSIN2 genotype association with hematological toxicity in ALL patients undergoing maintenance therapy.

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Overview

Cancer.gov

The Multifactor Screener may be useful to assess approximate intakes of fruits and vegetables, percentage energy from fat, and fiber. The screener asks respondents to report how frequently they consume foods in 16 categories. The screener also asks one question about the type of milk consumed.

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Uses of Screener Estimates

Cancer.gov

Dietary intake estimates derived from the Multifactor Screener are rough estimates of usual intake of fruits and vegetables, fiber, calcium, servings of dairy, and added sugar. These estimates are not as accurate as those from more detailed methods (e.g., 24-hour recalls).

Cautionary Note on Reporting Eta-Squared Values from Multifactor ANOVA Designs

ERIC Educational Resources Information Center

Pierce, Charles A.; Block, Richard A.; Aguinis, Herman

2004-01-01

The authors provide a cautionary note on reporting accurate eta-squared values from multifactor analysis of variance (ANOVA) designs. They reinforce the distinction between classical and partial eta-squared as measures of strength of association. They provide examples from articles published in premier psychology journals in which the authors…

Forest ecosystems of a Lower Gulf Coastal Plainlandscape: multifactor classification and analysis

Treesearch

P. Charles Goebel; Brian J. Palik; L. Katherine Kirkman; Mark B. Drew; Larry West; Dee C. Pederson

2001-01-01

The most common forestland classification techniques applied in the southeastern United States are vegetation-based. While not completely ignored, the application of multifactor, hierarchical ecosystem classifications are limited despite their widespread use in other regions of the eastern United States. We present one of the few truly integrated ecosystem...

A Multifactor Ecosystem Assessment of Wetlands Created Using a Novel Dredged Material Placement Technique in the Atchafalaya River, Louisiana: An Engineering With Nature Demonstration Project

DTIC Science & Technology

functions. The strategic placement of dredged materials in locations that mimic natural process promoted additional ecological benefits, especially...regarding wading bird and infaunal habitat, thus adhering to Engineering With Nature (EWN) processes. The multifactor approach improved the wetland

On the Interface of Probabilistic and PDE Methods in a Multifactor Term Structure Theory

ERIC Educational Resources Information Center

Mamon, Rogemar S.

2004-01-01

Within the general framework of a multifactor term structure model, the fundamental partial differential equation (PDE) satisfied by a default-free zero-coupon bond price is derived via a martingale-oriented approach. Using this PDE, a result characterizing a model belonging to an exponential affine class is established using only a system of…

Long-duration effect of multi-factor stresses on the cellular biochemistry, oil-yielding performance and morphology of Nannochloropsis oculata

PubMed Central

Wei, Likun; Huang, Xuxiong

2017-01-01

Microalga Nannochloropsis oculata is a promising alternative feedstock for biodiesel. Elevating its oil-yielding capacity is conducive to cost-saving biodiesel production. However, the regulatory processes of multi-factor collaborative stresses (MFCS) on the oil-yielding performance of N. oculata are unclear. The duration effects of MFCS (high irradiation, nitrogen deficiency and elevated iron supplementation) on N. oculata were investigated in an 18-d batch culture. Despite the reduction in cell division, the biomass concentration increased, resulting from the large accumulation of the carbon/energy-reservoir. However, different storage forms were found in different cellular storage compounds, and both the protein content and pigment composition swiftly and drastically changed. The analysis of four biodiesel properties using pertinent empirical equations indicated their progressive effective improvement in lipid classes and fatty acid composition. The variation curve of neutral lipid productivity was monitored with fluorescent Nile red and was closely correlated to the results from conventional methods. In addition, a series of changes in the organelles (e.g., chloroplast, lipid body and vacuole) and cell shape, dependent on the stress duration, were observed by TEM and LSCM. These changes presumably played an important role in the acclimation of N. oculata to MFCS and accordingly improved its oil-yielding performance. PMID:28346505

Measurement Invariance of Second-Order Factor Model of the Multifactor Leadership Questionnaire (MLQ) across K-12 Principal Gender

ERIC Educational Resources Information Center

Xu, Lihua; Wubbena, Zane; Stewart, Trae

2016-01-01

Purpose: The purpose of this paper is to investigate the factor structure and the measurement invariance of the Multifactor Leadership Questionnaire (MLQ) across gender of K-12 school principals (n=6,317) in the USA. Design/methodology/approach: Nine first-order factor models and four second-order factor models were tested using confirmatory…

Bullying among adolescents in North Cyprus and Turkey: testing a multifactor model.

PubMed

Bayraktar, Fatih

2012-04-01

Peer bullying has been studied since the 1970s. Therefore, a vast literature has accumulated about the various predictors of bullying. However, to date there has been no study which has combined individual-, peer-, parental-, teacher-, and school-related predictors of bullying within a model. In this sense, the main aim of this study was to test a multifactor model of bullying among adolescents in North Cyprus and Turkey. A total of 1,052 adolescents (554 girls, 498 boys) aged between 13 and 18 (M = 14.7, SD = 1.17) were recruited from North Cyprus and Turkey. Before testing the multifactor models, the measurement models were tested according to structural equation modeling propositions. Both models indicated that the psychological climate of the school, teacher attitudes within classroom, peer relationships, parental acceptance-rejection, and individual social competence factors had significant direct effects on bullying behaviors. Goodness-of-fit indexes indicated that the proposed multifactor model fitted both data well. The strongest predictors of bullying were the psychological climate of the school following individual social competence factors and teacher attitudes within classroom in both samples. All of the latent variables explained 44% and 51% of the variance in bullying in North Cyprus and Turkey, respectively.

Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

PubMed

Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2008-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points, the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2008-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Multi-factor authentication

DOEpatents

Hamlet, Jason R; Pierson, Lyndon G

2014-10-21

Detection and deterrence of spoofing of user authentication may be achieved by including a cryptographic fingerprint unit within a hardware device for authenticating a user of the hardware device. The cryptographic fingerprint unit includes an internal physically unclonable function ("PUF") circuit disposed in or on the hardware device, which generates a PUF value. Combining logic is coupled to receive the PUF value, combines the PUF value with one or more other authentication factors to generate a multi-factor authentication value. A key generator is coupled to generate a private key and a public key based on the multi-factor authentication value while a decryptor is coupled to receive an authentication challenge posed to the hardware device and encrypted with the public key and coupled to output a response to the authentication challenge decrypted with the private key.

Power of data mining methods to detect genetic associations and interactions.

PubMed

Molinaro, Annette M; Carriero, Nicholas; Bjornson, Robert; Hartge, Patricia; Rothman, Nathaniel; Chatterjee, Nilanjan

2011-01-01

Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM. Copyright © 2011 S. Karger AG, Basel.

Age-Based Differences in the Genetic Determinants of Glycemic Control: A Case of FOXO3 Variations.

PubMed

Sun, Liang; Hu, Caiyou; Qian, Yu; Zheng, Chenguang; Liang, Qinghua; Lv, Zeping; Huang, Zezhi; Qi, Keyan; Huang, Jin; Zhou, Qin; Yang, Ze

2015-01-01

Glucose homeostasis is a trait of healthy ageing and is crucial to the elderly, but less consideration has been given to the age composition in most studies involving genetics and hyperglycemia. Seven variants in FOXO3 were genotyped in three cohorts (n = 2037; LLI, MI_S and MI_N; mean age: 92.5 ± 3.6, 45.9 ± 8.2 and 46.8 ± 10.3, respectively) to compare the contribution of FOXO3 to fasting hyperglycemia (FH) between long-lived individuals (LLI, aged over 90 years) and middle-aged subjects (aged from 35-65 years). A different genetic predisposition of FOXO3 alleles to FH was observed between LLI and both of two middle-aged cohorts. In the LLI cohort, the longevity beneficial alleles of three variants with the haplotype "AGGC" in block 1 were significantly protective to FH, fasting glucose, hemoglobin A1C and HOMA-IR. Notably, combining multifactor dimensionality reduction and logistic regression, we identified a significant 3-factor interaction model (rs2802288, rs2802292 and moderate physical activity) associated with lower FH risk. However, not all of the findings were replicated in the two middle-aged cohorts. Our data provides a novel insight into the inconsistent genetic determinants between middle-aged and LLI subjects. FOXO3 might act as a shared genetic predisposition to hyperglycemia and lifespan.

Age-Based Differences in the Genetic Determinants of Glycemic Control: A Case of FOXO3 Variations

PubMed Central

Sun, Liang; Hu, Caiyou; Qian, Yu; Zheng, Chenguang; Liang, Qinghua; Lv, Zeping; Huang, Zezhi; Qi, Keyan; Huang, Jin; Zhou, Qin; Yang, Ze

2015-01-01

Background Glucose homeostasis is a trait of healthy ageing and is crucial to the elderly, but less consideration has been given to the age composition in most studies involving genetics and hyperglycemia. Methods Seven variants in FOXO3 were genotyped in three cohorts (n = 2037; LLI, MI_S and MI_N; mean age: 92.5±3.6, 45.9±8.2 and 46.8±10.3, respectively) to compare the contribution of FOXO3 to fasting hyperglycemia (FH) between long-lived individuals (LLI, aged over 90 years) and middle-aged subjects (aged from 35–65 years). Results A different genetic predisposition of FOXO3 alleles to FH was observed between LLI and both of two middle-aged cohorts. In the LLI cohort, the longevity beneficial alleles of three variants with the haplotype “AGGC” in block 1 were significantly protective to FH, fasting glucose, hemoglobin A1C and HOMA-IR. Notably, combining multifactor dimensionality reduction and logistic regression, we identified a significant 3-factor interaction model (rs2802288, rs2802292 and moderate physical activity) associated with lower FH risk. However, not all of the findings were replicated in the two middle-aged cohorts. Conclusion Our data provides a novel insight into the inconsistent genetic determinants between middle-aged and LLI subjects. FOXO3 might act as a shared genetic predisposition to hyperglycemia and lifespan. PMID:25993007

Identification of SNPs associated with variola virus virulence.

PubMed

Hoen, Anne Gatewood; Gardner, Shea N; Moore, Jason H

2013-02-14

Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity.

Association of VAMP5 and MCC genetic polymorphisms with increased risk of Hirschsprung disease susceptibility in Southern Chinese children.

PubMed

Zhao, Jinglu; Xie, Xiaoli; Yao, Yuxiao; He, Qiuming; Zhang, Ruizhong; Xia, Huimin; Zhang, Yan

2018-04-25

Hirschsprung disease (HSCR) is a genetic disorder characterized by the absence of neural crest cells in parts of the intestine. This study aims to investigate the association of vesicle-associated membrane protein 5 ( VAMP5 ) and mutated in colorectal cancer ( MCC ) genetic polymorphisms and their correlated risks with HSCR. We examined the association in four polymorphisms (rs10206961, rs1254900 and rs14242 in VAMP5 , rs11241200 in MCC ) and HSCR susceptibility in a Southern Chinese population composed of 1473 cases and 1469 controls. Two variants in VAMP5 were replicated as associated with HSCR. Interestingly, we clarified SNPs rs10206961 and rs1254900 in VAMP5 are more essential for patients with long-segment aganglionosis (LHSCR). Relatively high expression correlation was observed between VAMP5 and MCC using data from public database showing there may exist potential genetic interactions. SNP interaction was cross-examined by logistic regression and multifactor dimensionality reduction analysis revealing that VAMP5 rs1254900 and MCC rs11241200 were interacting significantly, thereby contributing to the risk of HSCR. The results suggest that significant associations of the rs10206961 and rs14242 in VAMP5 with an increased risk of HSCR in Southern Chinese, especially in LHSCR patients. This study provided new evidence of epistatic association of VAMP5 and MCC with increased risk of HSCR.

Multilocus family-based association analysis of seven candidate polymorphisms with essential hypertension in an african-derived semi-isolated brazilian population.

PubMed

Kimura, L; Angeli, C B; Auricchio, M T B M; Fernandes, G R; Pereira, A C; Vicente, J P; Pereira, T V; Mingroni-Netto, R C

2012-01-01

Background. It has been widely suggested that analyses considering multilocus effects would be crucial to characterize the relationship between gene variability and essential hypertension (EH). Objective. To test for the presence of multilocus effects between/among seven polymorphisms (six genes) on blood pressure-related traits in African-derived semi-isolated Brazilian populations (quilombos). Methods. Analyses were carried out using a family-based design in a sample of 652 participants (97 families). Seven variants were investigated: ACE (rs1799752), AGT (rs669), ADD2 (rs3755351), NOS3 (rs1799983), GNB3 (rs5441 and rs5443), and GRK4 (rs1801058). Sensitivity analyses were further performed under a case-control design with unrelated participants only. Results. None of the investigated variants were associated individually with both systolic and diastolic BP levels (SBP and DBP, respectively) or EH (as a binary outcome). Multifactor dimensionality reduction-based techniques revealed a marginal association of the combined effect of both GNB3 variants on DBP levels in a family-based design (P = 0.040), whereas a putative NOS3-GRK4 interaction also in relation to DBP levels was observed in the case-control design only (P = 0.004). Conclusion. Our results provide limited support for the hypothesis of multilocus effects between/among the studied variants on blood pressure in quilombos. Further larger studies are needed to validate our findings.

The interaction of combined effects of the BDNF and PRKCG genes and negative life events in major depressive disorder.

PubMed

Yang, Chunxia; Sun, Ning; Liu, Zhifen; Li, Xinrong; Xu, Yong; Zhang, Kerang

2016-03-30

Major depressive disorder (MDD) is a mental disorder that results from complex interplay between multiple and partially overlapping sets of susceptibility genes and environmental factors. The brain derived neurotrophic factor (BDNF) and Protein kinase C gamma type (PRKCG) are logical candidate genes in MDD. Among diverse environmental factors, negative life events have been suggested to exert a crucial impact on brain development. In the present study, we hypothesized that interactions between genetic variants in BDNF and PRKCG and negative life events may play an important role in the development of MDD. We recruited a total of 406 patients with MDD and 391 age- and gender-matched control subjects. Gene-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR). Under a dominant model, we observed a significant three-way interaction among BDNF rs6265, PRKCG rs3745406, and negative life events. The gene-environment combination of PRKCG rs3745406 C allele, BDNF rs6265 G allele and high level of negative life events (C-G-HN) was significantly associated with MDD (OR, 5.97; 95% CI, 2.71-13.15). To our knowledge, this is the first report of evidence that the BDNF-PRKCG interaction may modify the relationship between negative life events and MDD in the Chinese population. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Identification of SNPs associated with variola virus virulence

PubMed Central

2013-01-01

Background Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Findings Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. Conclusions We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity. PMID:23410064

The relationship between glucocorticoid receptor polymorphisms, stressful life events, social support, and post-traumatic stress disorder.

PubMed

Lian, Yulong; Xiao, Jing; Wang, Qian; Ning, Li; Guan, Suzhen; Ge, Hua; Li, Fuye; Liu, Jiwen

2014-08-12

It is debatable whether or not glucocorticoid receptor (GR) polymorphisms moderate susceptibility to PTSD. Our objective was to examine the effects of stressful life events, social support, GR genotypes, and gene-environment interactions on the etiology of PTSD. Three tag single nucleotide polymorphisms, trauma events, stressful life events, and social support were assessed in 460 patients with PTSD and 1158 control subjects from a Chinese Han population. Gene-environment interactions were analyzed by generalized multifactor dimensionality reduction (GMDR). Variation in GR at rs41423247 and rs258747, stressful life events, social support, and the number of traumatic events were each separately associated with the risk for PTSD. A gene-environment interaction among the polymorphisms, rs41423247 and rs258747, the number of traumatic events, stressful life events, and social support resulted in an increased risk for PTSD. High-risk individuals (a large number of traumatic events, G allele of rs258747 and rs41423247, high level stressful life events, and low social support) had a 3.26-fold increased risk of developing PTSD compared to low-risk individuals. The association was statistically significant in the sub-groups with and without childhood trauma. Our data support the notion that stressful life events, the number of trauma events, and social support may play a contributing role in the risk for PTSD by interacting with GR gene polymorphisms.

Application of Analytic Hierarchy Process (AHP) in the analysis of the fuel efficiency in the automobile industry with the utilization of Natural Fiber Polymer Composites (NFPC)

NASA Astrophysics Data System (ADS)

Jayamani, E.; Perera, D. S.; Soon, K. H.; Bakri, M. K. B.

2017-04-01

A systematic method of material analysis aiming for fuel efficiency improvement with the utilization of natural fiber reinforced polymer matrix composites in the automobile industry is proposed. A multi-factor based decision criteria with Analytical Hierarchy Process (AHP) was used and executed through MATLAB to achieve improved fuel efficiency through the weight reduction of vehicular components by effective comparison between two engine hood designs. The reduction was simulated by utilizing natural fiber polymer composites with thermoplastic polypropylene (PP) as the matrix polymer and benchmarked against a synthetic based composite component. Results showed that PP with 35% of flax fiber loading achieved a 0.4% improvement in fuel efficiency, and it was the highest among the 27 candidate fibers.

A Unique Computational Algorithm to Simulate Probabilistic Multi-Factor Interaction Model Complex Material Point Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2010-01-01

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points--the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

NASA Astrophysics Data System (ADS)

Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

Biometric Data Safeguarding Technologies Analysis and Best Practices

DTIC Science & Technology

2011-12-01

fuzzy vault” scheme proposed by Juels and Sudan. The scheme was designed to encrypt data such that it could be unlocked by similar but inexact matches... designed transform functions. Multifactor Key Generation Multifactor key generation combines a biometric with one or more other inputs, such as a...cooperative, off-angle iris images.  Since the commercialized system is designed for images acquired from a specific, paired acquisition system

Application of GA-SVM method with parameter optimization for landslide development prediction

NASA Astrophysics Data System (ADS)

Li, X. Z.; Kong, J. M.

2013-10-01

Prediction of landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. Support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of SVM model. In this study, we presented an application of GA-SVM method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in some hydro - electrical engineering area of Southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that, the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest RSME of 0.0009 and the biggest RI of 0.9992.

Multi-factor evaluation indicator method for the risk assessment of atmospheric and oceanic hazard group due to the attack of tropical cyclones

NASA Astrophysics Data System (ADS)

Qi, Peng; Du, Mei

2018-06-01

China's southeast coastal areas frequently suffer from storm surge due to the attack of tropical cyclones (TCs) every year. Hazards induced by TCs are complex, such as strong wind, huge waves, storm surge, heavy rain, floods, and so on. The atmospheric and oceanic hazards cause serious disasters and substantial economic losses. This paper, from the perspective of hazard group, sets up a multi-factor evaluation method for the risk assessment of TC hazards using historical extreme data of concerned atmospheric and oceanic elements. Based on the natural hazard dynamic process, the multi-factor indicator system is composed of nine natural hazard factors representing intensity and frequency, respectively. Contributing to the indicator system, in order of importance, are maximum wind speed by TCs, attack frequency of TCs, maximum surge height, maximum wave height, frequency of gusts ≥ Scale 8, rainstorm intensity, maximum tidal range, rainstorm frequency, then sea-level rising rate. The first four factors are the most important, whose weights exceed 10% in the indicator system. With normalization processing, all the single-hazard factors are superposed by multiplying their weights to generate a superposed TC hazard. The multi-factor evaluation indicator method was applied to the risk assessment of typhoon-induced atmospheric and oceanic hazard group in typhoon-prone southeast coastal cities of China.

Security enhanced multi-factor biometric authentication scheme using bio-hash function.

PubMed

Choi, Younsung; Lee, Youngsook; Moon, Jongho; Won, Dongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An's scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user's ID during login. Cao and Ge improved upon Younghwa An's scheme, but various security problems remained. This study demonstrates that Cao and Ge's scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge's scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost.

Computational Simulation of the Formation and Material Behavior of Ice

NASA Technical Reports Server (NTRS)

Tong, Michael T.; Singhal, Surendra N.; Chamis, Christos C.

1994-01-01

Computational methods are described for simulating the formation and the material behavior of ice in prevailing transient environments. The methodology developed at the NASA Lewis Research Center was adopted. A three dimensional finite-element heat transfer analyzer was used to predict the thickness of ice formed under prevailing environmental conditions. A multi-factor interaction model for simulating the material behavior of time-variant ice layers is presented. The model, used in conjunction with laminated composite mechanics, updates the material properties of an ice block as its thickness increases with time. A sample case of ice formation in a body of water was used to demonstrate the methodology. The results showed that the formation and the material behavior of ice can be computationally simulated using the available composites technology.

Probabilistic Usage of the Multi-Factor Interaction Model

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A Multi-Factor Interaction Model (MFIM) is used to predict the insulating foam mass expulsion during the ascending of a space vehicle. The exponents in the MFIM are evaluated by an available approach which consists of least squares and an optimization algorithm. These results were subsequently used to probabilistically evaluate the effects of the uncertainties in each participating factor in the mass expulsion. The probabilistic results show that the surface temperature dominates at high probabilities and the pressure which causes the mass expulsion at low probabil

Association of the ACE, GSTM1, IL-6, NOS3, and CYP1A1 polymorphisms with susceptibility of mycoplasma pneumoniae pneumonia in Chinese children

PubMed Central

Zhao, Jie; Zhang, Wen; Shen, Li; Yang, Xiaomeng; Liu, Yi; Gai, Zhongtao

2017-01-01

Abstract Mycoplasma pneumoniae is a common cause of community-acquired pneumonia (CAP) and the clinical presentation of mycoplasma pneumoniae pneumonia (MPP) varies widely. Genetic variability affecting the host response may also influence the susceptibility to MPP. Several studies have investigated the association between single nucleotide polymorphism (SNP) of some genes and the risks of CAP; however, the results were inconsistent. Here, we investigated the association of 5 functional genes and the risks of MPP, including ACE (rs4340), GSTM1 (Ins/del), IL-6 (rs1800795), NOS3 (rs1799983), and CYP1A1 (rs2606345) in a total of 715 subjects (415 cases, 300 controls) by using tetra-primer allele-specific polymerase chain reaction (PCR) and Sanger sequencing. The gene–gene interactions were analyzed using the Multifactor Dimensionality Reduction and cumulative genetic risk score approaches. Our results showed that 3 SNPs of ACE rs4340, IL-6 rs1800795, and NOS3 rs1799983 were significantly associated with the risks of MPP, while no differences were observed in genotype frequencies of GSTM1 (Ins/del) and CYP1A1 rs2606345 between both groups. The combinations of ACE rs4340D/NOS3 rs1799983T/CYP1A1 rs2606345G and ACE rs4340D/NOS3 rs1799983T contribute to the genetic susceptibility of MPP in Chinese children. PMID:28403117

Multilocus analysis reveals three candidate genes for Chinese migraine susceptibility.

PubMed

An, X-K; Fang, J; Yu, Z-Z; Lin, Q; Lu, C-X; Qu, H-L; Ma, Q-L

2017-08-01

Several genome-wide association studies (GWASs) in Caucasian populations have identified 12 loci that are significantly associated with migraine. More evidence suggests that serotonin receptors are also involved in migraine pathophysiology. In the present study, a case-control study was conducted in a cohort of 581 migraine cases and 533 ethnically matched controls among a Chinese population. Eighteen polymorphisms from serotonin receptors and GWASs were selected, and genotyping was performed using a Sequenom MALDI-TOF mass spectrometry iPLEX platform. The genotypic and allelic distributions of MEF2D rs2274316 and ASTN2 rs6478241 were significantly different between migraine patients and controls. Univariate and multivariate analysis revealed significant associations of polymorphisms in the MEF2D and ASTN2 genes with migraine susceptibility. MEF2D, PRDM16 and ASTN2 were also found to be associated with migraine without aura (MO) and migraine with family history. And, MEF2D and ASTN2 also served as genetic risk factors for the migraine without family history. The generalized multifactor dimensionality reduction analysis identified that MEF2D and HTR2E constituted the two-factor interaction model. Our study suggests that the MEF2D, PRDM16 and ASTN2 genes from GWAS are associated with migraine susceptibility, especially MO, among Chinese patients. It appears that there is no association with serotonin receptor related genes. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene-environment interaction between adiponectin gene polymorphisms and environmental factors on the risk of diabetic retinopathy.

PubMed

Li, Yuan; Wu, Qun Hong; Jiao, Ming Li; Fan, Xiao Hong; Hu, Quan; Hao, Yan Hua; Liu, Ruo Hong; Zhang, Wei; Cui, Yu; Han, Li Yuan

2015-01-01

To evaluate whether the adiponectin gene is associated with diabetic retinopathy (DR) risk and interaction with environmental factors modifies the DR risk, and to investigate the relationship between serum adiponectin levels and DR. Four adiponectin polymorphisms were evaluated in 372 DR cases and 145 controls. Differences in environmental factors between cases and controls were evaluated by unconditional logistic regression analysis. The model-free multifactor dimensionality reduction method and traditional multiple regression models were applied to explore interactions between the polymorphisms and environmental factors. Using the Bonferroni method, we found no significant associations between four adiponectin polymorphisms and DR susceptibility. Multivariate logistic regression found that physical activity played a protective role in the progress of DR, whereas family history of diabetes (odds ratio 1.75) and insulin therapy (odds ratio 1.78) were associated with an increased risk for DR. The interaction between the C-11377 G (rs266729) polymorphism and insulin therapy might be associated with DR risk. Family history of diabetes combined with insulin therapy also increased the risk of DR. No adiponectin gene polymorphisms influenced the serum adiponectin levels. Serum adiponectin levels did not differ between the DR group and non-DR group. No significant association was identified between four adiponectin polymorphisms and DR susceptibility after stringent Bonferroni correction. The interaction between C-11377G (rs266729) polymorphism and insulin therapy, as well as the interaction between family history of diabetes and insulin therapy, might be associated with DR susceptibility.

Examination of Association to Autism of Common Genetic Variation in Genes Related to Dopamine

PubMed Central

Anderson, B.M.; Schnetz-Boutaud, N.; Bartlett, J.; Wright, H.H.; Abramson, R.K.; Cuccaro, M.L.; Gilbert, J.R.; Pericak-Vance, M.A.; Haines, J.L.

2010-01-01

Autism is a severe neurodevelopmental disorder characterized by a triad of complications. Autistic individuals display significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Prevalence studies suggest that autism is more common than originally believed, with recent estimates citing a rate of one in 150. Although this genomic approach has yielded multiple suggestive regions, a specific risk locus has yet to be identified and widely confirmed. Because many etiologies have been suggested for this complex syndrome, we hypothesize that one of the difficulties in identifying autism genes is that multiple genetic variants may be required to significantly increase the risk of developing autism. Thus we took the alternative approach of examining 14 prominent dopamine pathway candidate genes for detailed study by genotyping 28 SNPs. Although we did observe a nominally significant association for rs2239535 (p=.008) on chromosome 20, single locus analysis did not reveal any results as significant after correction for multiple comparisons. No significant interaction was identified when Multifactor Dimensionality Reduction (MDR) was employed to test specifically for multilocus effects. Although genome-wide linkage scans in autism have provided support for linkage to various loci along the dopamine pathway, our study does not provide strong evidence of linkage or association to any specific gene or combination of genes within the pathway. These results demonstrate that common genetic variation within the tested genes located within this pathway at most play a minor to moderate role in overall autism pathogenesis. PMID:19360691

Security enhanced multi-factor biometric authentication scheme using bio-hash function

PubMed Central

Lee, Youngsook; Moon, Jongho

2017-01-01

With the rapid development of personal information and wireless communication technology, user authentication schemes have been crucial to ensure that wireless communications are secure. As such, various authentication schemes with multi-factor authentication have been proposed to improve the security of electronic communications. Multi-factor authentication involves the use of passwords, smart cards, and various biometrics to provide users with the utmost privacy and data protection. Cao and Ge analyzed various authentication schemes and found that Younghwa An’s scheme was susceptible to a replay attack where an adversary masquerades as a legal server and a user masquerading attack where user anonymity is not provided, allowing an adversary to execute a password change process by intercepting the user’s ID during login. Cao and Ge improved upon Younghwa An’s scheme, but various security problems remained. This study demonstrates that Cao and Ge’s scheme is susceptible to a biometric recognition error, slow wrong password detection, off-line password attack, user impersonation attack, ID guessing attack, a DoS attack, and that their scheme cannot provide session key agreement. Then, to address all weaknesses identified in Cao and Ge’s scheme, this study proposes a security enhanced multi-factor biometric authentication scheme and provides a security analysis and formal analysis using Burrows-Abadi-Needham logic. Finally, the efficiency analysis reveals that the proposed scheme can protect against several possible types of attacks with only a slightly high computational cost. PMID:28459867

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment

NASA Astrophysics Data System (ADS)

De Kauwe, M. G.; Medlyn, B.; Walker, A.; Zaehle, S.; Pendall, E.; Norby, R. J.

2017-12-01

Multifactor experiments are often advocated as important for advancing models, yet to date, such models have only been tested against single-factor experiments. We applied 10 models to the multifactor Prairie Heating and CO2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions: comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO2-induced water savings to extend the growing season length. Observed interactive (CO2 × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.

Association of single nucleotide polymorphisms in CACNA 1A/CACNA 1C/CACNA 1H calcium channel genes with diabetic peripheral neuropathy in Chinese population.

PubMed

Sun, Lin; Ma, Jun; Mao, Qian; Yang, Yun-Long; Ma, Lin-Lin; Niu, Ling; Liu, Li-Feng

2018-06-29

The present study was conducted to explore the correlations between single nucleotide polymorphisms (SNPs) in the calcium channel CACNA 1A, CACNA 1C, and CACNA 1H genes and diabetic peripheral neuropathy (DPN) amongst the Chinese population. In total, 281 patients diagnosed with type 2 diabetes participated in the present study. These patients were divided into the case group, which was subdivided into the DPN (143 cases) and the non-DPN groups (138 cases). Subsequently, 180 healthy individuals that had undergone routine health examinations were also recruited and assigned to the control group. PCR-restriction fragment length polymorphism (PCR-RFLP) was used to detect the genotype and allele frequencies of CACNA 1A, CACNA 1C, and CACNA 1H genes; logistic regression analysis to investigate the association of gene polymorphisms with DNP. Gene-gene interactions were then detected by generalized multifactor dimensionality reduction (GMDR). The results revealed that CACNA 1A rs2248069 and rsl6030, CACNA 1C rs216008 and rs2239050, and CACNA 1H rs3794619, and rs7191246 SNPs were all associated with DPN, while rs2248069, rsl6030, rs2239050, and rs7191246 polymorphisms were attributed to the susceptibility to DPN. It was also observed that the optimal models were three-, four- and five-dimensional models with a prediction accuracy of 61.05% and the greatest consistency of cross-validation was 10/10. In summary, these findings demonstrated that the SNPs in the CACNA 1A, CACNA 1C, and CACNA 1H genes were involved in the pathophysiology of DPN. In addition, polymorphisms in the CACNA 1A, CACNA 1C, and CACNA 1H genes and their interactions also had effects on DPN. © 2018 The Author(s).

On the source of stochastic volatility: Evidence from CAC40 index options during the subprime crisis

NASA Astrophysics Data System (ADS)

Slim, Skander

2016-12-01

This paper investigates the performance of time-changed Lévy processes with distinct sources of return volatility variation for modeling cross-sectional option prices on the CAC40 index during the subprime crisis. Specifically, we propose a multi-factor stochastic volatility model: one factor captures the diffusion component dynamics and two factors capture positive and negative jump variations. In-sample and out-of-sample tests show that our full-fledged model significantly outperforms nested lower-dimensional specifications. We find that all three sources of return volatility variation, with different persistence, are needed to properly account for market pricing dynamics across moneyness, maturity and volatility level. Besides, the model estimation reveals negative risk premium for both diffusive volatility and downward jump intensity whereas a positive risk premium is found to be attributed to upward jump intensity.

A graph-based approach to inequality assessment

NASA Astrophysics Data System (ADS)

Palestini, Arsen; Pignataro, Giuseppe

2016-08-01

In a population consisting of heterogeneous types, whose income factors are indicated by nonnegative vectors, policies aggregating different factors can be represented by coalitions in a cooperative game, whose characteristic function is a multi-factor inequality index. When it is not possible to form all coalitions, the feasible ones can be indicated by a graph. We redefine Shapley and Banzhaf values on graph games to deduce some properties involving the degrees of the graph vertices and marginal contributions to overall inequality. An example is finally provided based on a modified multi-factor Atkinson index.

Multi-Factor Analysis for Selecting Lunar Exploration Soft Landing Area and the best Cruise Route

NASA Astrophysics Data System (ADS)

Mou, N.; Li, J.; Meng, Z.; Zhang, L.; Liu, W.

2018-04-01

Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2), which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

The Human Performance Envelope: Past Research, Present Activities and Future Directions

NASA Technical Reports Server (NTRS)

Edwards, Tamsyn

2017-01-01

Air traffic controllers (ATCOs) must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur, and interact, to effect performance. However, multifactor influences and the association with performance are under-researched. This study utilized a high fidelity human in the loop enroute air traffic control simulation to investigate the relationship between workload, situation awareness and ATCO performance. The study aimed to replicate and extend Edwards, Sharples, Wilson and Kirwans (2012) previous study and confirm multifactor interactions with a participant sample of ex-controllers. The study also aimed to extend Edwards et als previous research by comparing multifactor relationships across 4 automation conditions. Results suggest that workload and SA may interact to produce a cumulative impact on controller performance, although the effect of the interaction on performance may be dependent on the context and amount of automation present. Findings have implications for human-automation teaming in air traffic control, and the potential prediction and support of ATCO performance.

Multi-Factor Impact Analysis of Agricultural Production in Bangladesh with Climate Change

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Major, David C.; Yu, Winston H.; Alam, Mozaharul; Hussain, Sk. Ghulam; Khan, Abu Saleh; Hassan, Ahmadul; Al Hossain, Bhuiya Md. Tamim; Goldberg, Richard; Horton, Radley M.;

Elevated air temperature alters an old-field insect community in a multi-factor climate change experiment

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

Villalpando, Sean; Williams, Ray; Norby, Richard J

To address how multiple, interacting climate drivers may affect plant-insect community associations, we sampled the insect community from a constructed old-field plant community grown under simultaneous [CO2], temperature, and water manipulation. Insects were identified to morphospecies, assigned to feeding guilds and abundance, richness and evenness quantified. Warming significantly increased Order Thysanoptera abundance and reduced overall morphospecies richness and evenness. Non-metric multidimensional scaling clearly supported the effect of warming on insect community composition. Reductions in richness for herbivores and parasitoids suggest trophic-level effects within the insect community. Analysis of dominant insects demonstrated the effects of warming were limited to a relativelymore » small number of morphospecies. Reported reductions in whole-community foliar N at elevated [CO2] unexpectedly did not result in any effects on herbivores. These results demonstrate climatic warming may alter certain insect communities via effects on insect species most responsive to higher temperature, contributing to a change in community structure.« less

A surrogate model for thermal characteristics of stratospheric airship

NASA Astrophysics Data System (ADS)

Zhao, Da; Liu, Dongxu; Zhu, Ming

2018-06-01

A simple and accurate surrogate model is extremely needed to reduce the analysis complexity of thermal characteristics for a stratospheric airship. In this paper, a surrogate model based on the Least Squares Support Vector Regression (LSSVR) is proposed. The Gravitational Search Algorithm (GSA) is used to optimize hyper parameters. A novel framework consisting of a preprocessing classifier and two regression models is designed to train the surrogate model. Various temperature datasets of the airship envelope and the internal gas are obtained by a three-dimensional transient model for thermal characteristics. Using these thermal datasets, two-factor and multi-factor surrogate models are trained and several comparison simulations are conducted. Results illustrate that the surrogate models based on LSSVR-GSA have good fitting and generalization abilities. The pre-treated classification strategy proposed in this paper plays a significant role in improving the accuracy of the surrogate model.

Examining the Factor Structure of the MLQ Transactional and Transformational Leadership Dimensions in Nursing Context.

PubMed

Boamah, Sheila A; Tremblay, Paul

2018-05-01

The Multifactor Leadership Questionnaire (MLQ) is the most widely used instrument for assessing dimensions of leadership style; yet, most studies have failed to reproduce the original MLQ factor structure. The current study evaluates the dimensionality and nomological validity of Bass's transactional and transformational leadership model using the MLQ in a sample of registered nurses working in acute care hospitals in Canada. A combination of exploratory and confirmatory factor analyses were used to evaluate the hypothetical factor structure of the MLQ consisting of five transformational factors, and three transactional factors. Results suggest that the eight-factor solution displayed best fit indices; however, two transactional factors should be extracted due to high interscale correlations and lack of differential relationships with the two leadership variables. The findings support a scale refinement and the need for new theory concerning the five transformational leadership and contingent reward dimensions of the MLQ.

The impact of high total cholesterol and high low-density lipoprotein on avascular necrosis of the femoral head in low-energy femoral neck fractures.

PubMed

Zeng, Xianshang; Zhan, Ke; Zhang, Lili; Zeng, Dan; Yu, Weiguang; Zhang, Xinchao; Zhao, Mingdong; Lai, Zhicheng; Chen, Runzhen

2017-02-17

Avascular necrosis of the femoral head (AVNFH) typically constitutes 5 to 15% of all complications of low-energy femoral neck fractures, and due to an increasingly ageing population and a rising prevalence of femoral neck fractures, the number of patients who develop AVNFH is increasing. However, there is no consensus regarding the relationship between blood lipid abnormalities and postoperative AVNFH. The purpose of this retrospective study was to investigate the relationship between blood lipid abnormalities and AVNFH following the femoral neck fracture operation among an elderly population. A retrospective, comparative study was performed at our institution. Between June 2005 and November 2009, 653 elderly patients (653 hips) with low-energy femoral neck fractures underwent closed reduction and internal fixation with cancellous screws (Smith and Nephew, Memphis, Tennessee). Follow-up occurred at 1, 6, 12, 18, 24, 30, and 36 months after surgery. Logistic multi-factor regression analysis was used to assess the risk factors of AVNFH and to determine the effect of blood lipid levels on AVNFH development. Inclusion and exclusion criteria were predetermined to focus on isolated freshly closed femoral neck fractures in the elderly population. The primary outcome was the blood lipid levels. The secondary outcome was the logistic multi-factor regression analysis. A total of 325 elderly patients with low-energy femoral neck fractures (AVNFH, n = 160; control, n = 165) were assessed. In the AVNFH group, the average TC, TG, LDL, and Apo-B values were 7.11 ± 3.16 mmol/L, 2.15 ± 0.89 mmol/L, 4.49 ± 1.38 mmol/L, and 79.69 ± 17.29 mg/dL, respectively; all of which were significantly higher than the values in the control group. Logistic multi-factor regression analysis showed that both TC and LDL were the independent factors influencing the postoperative AVNFH within femoral neck fractures. This evidence indicates that AVNFH was significantly associated with blood lipid abnormalities in elderly patients with low-energy femoral neck fractures. The findings of this pilot trial justify a larger study to determine whether the result is more generally applicable to a broader population.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO2 Enrichment experiment.

PubMed

De Kauwe, Martin G; Medlyn, Belinda E; Walker, Anthony P; Zaehle, Sönke; Asao, Shinichi; Guenet, Bertrand; Harper, Anna B; Hickler, Thomas; Jain, Atul K; Luo, Yiqi; Lu, Xingjie; Luus, Kristina; Parton, William J; Shu, Shijie; Wang, Ying-Ping; Werner, Christian; Xia, Jianyang; Pendall, Elise; Morgan, Jack A; Ryan, Edmund M; Carrillo, Yolima; Dijkstra, Feike A; Zelikova, Tamara J; Norby, Richard J

2017-09-01

Multifactor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date, such models have only been tested against single-factor experiments. We applied 10 TBMs to the multifactor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multifactor experiments can be used to constrain models and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2  yr -1 ). Comparison with data highlighted model failures particularly with respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against the observations from single-factors treatments was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the N cycle models, N availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they overestimated the effect of warming on leaf onset and did not allow CO 2 -induced water savings to extend the growing season length. Observed interactive (CO 2  × warming) treatment effects were subtle and contingent on water stress, phenology, and species composition. As the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. We outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change. © 2017 John Wiley & Sons Ltd.

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

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

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less

Challenging terrestrial biosphere models with data from the long-term multifactor Prairie Heating and CO 2 enrichment experiment

DOE PAGES

De Kauwe, Martin G.; Medlyn, Belinda E.; Walker, Anthony P.; ...

2017-02-01

Multi-factor experiments are often advocated as important for advancing terrestrial biosphere models (TBMs), yet to date such models have only been tested against single-factor experiments. We applied 10 TBMs to the multi-factor Prairie Heating and CO 2 Enrichment (PHACE) experiment in Wyoming, USA. Our goals were to investigate how multi-factor experiments can be used to constrain models, and to identify a road map for model improvement. We found models performed poorly in ambient conditions; there was a wide spread in simulated above-ground net primary productivity (range: 31-390 g C m -2 yr -1). Comparison with data highlighted model failures particularlymore » in respect to carbon allocation, phenology, and the impact of water stress on phenology. Performance against single-factors was also relatively poor. In addition, similar responses were predicted for different reasons across models: there were large differences among models in sensitivity to water stress and, among the nitrogen cycle models, nitrogen availability during the experiment. Models were also unable to capture observed treatment effects on phenology: they over-estimated the effect of warming on leaf onset and did not allow CO 2-induced water savings to extend growing season length. Observed interactive (CO 2 x warming) treatment effects were subtle and contingent on water stress, phenology and species composition. Since the models did not correctly represent these processes under ambient and single-factor conditions, little extra information was gained by comparing model predictions against interactive responses. Finally, we outline a series of key areas in which this and future experiments could be used to improve model predictions of grassland responses to global change.« less

[Influence of leptin receptor gene K109R polymorphism on the risk of nonalcoholic fatty liver disease and its interaction with PNPLA3 I148M polymorphism].

PubMed

An, B Q; Jiang, M; Cheng, Y T; Yuan, C; Lu, L L; Xin, Y N; Xuan, S Y

2016-05-20

To investigate the influence of leptin receptor (LEPR) gene K109R polymorphism on the risk of nonalcoholic fatty liver disease (NAFLD) and its interaction with PNPLA3 I148M polymorphism in the Han Chinese population in Qingdao, China. Blood samples were collected from 296 NAFLD patients and 321 healthy controls, and the genotypes of these patients were determined by PCR and genotyping. Related statistical analyses were performed to compare genotypes, alleles, and clinical data between the two groups. Generalized multifactor dimensionality reduction (GMDR) was used to investigate the interaction between LEPR K109R and PNPLA3 I148M genes. The distribution of LEPR K109R genotypes and alleles showed no significant differences between the NAFLD group and the control group (P > 0.05). PNPLA3 I148M gene polymorphisms were closely associated with the risk of NAFLD, and the risk of NAFLD in G mutant gene carriers was 2.07 times that in patients who did not carry this gene (OR = 2.07, 95% CI 1.423-3.013, P < 0.001). The joint action of LEPR K109R and PNPLA3 I148M significantly increased the risk of NAFL (OR = 3.393, 95% CI 1.856-6.201, P < 0.001). In the Han Chinese population in Qingdao, LEPR K109R gene polymorphism is not associated with the risk of NAFLD, but its interaction with PNPLA3 I148M polymorphism can significantly increase the risk of NAFLD.

Evaluation of the Obesity Genes FTO and MC4R for Contribution to the Risk of Large Artery Atherosclerotic Stroke in a Chinese Population

PubMed Central

Song, Zhi; Qiu, Lingling; Hu, Zhongyang; Liu, Jia; Liu, Ding; Hou, Deren

2016-01-01

Background Obesity is a well-established risk factor for large artery atherosclerotic (LAA) stroke. The aim of the study was to explore whether obesity genes, such as MC4R and FTO, contribute to LAA stroke risk in the Chinese Han population. Methods 322 LAA stroke patients and 473 controls were recruited. Gene polymorphism of MC4R (rs17782313) and FTO (rs8050136 and rs9939609) were genotyped. Results No differences were observed in genotype frequencies of variants of FTO (rs8050136 and rs9939609) or MC4R (rs17782313) between LAA stroke patients and control subjects. However, rs17782313 of the MC4R gene was associated with LAA stroke susceptibility in smokers (rs17782313: p = 0.020, OR (95s% CI) = 1.55 (1.07–2.23)) in the stratified analysis. Furthermore, multifactor dimensionality reduction analysis revealed that the combination of MC4R variant (rs17782313), hypertension and smoking habit was significantly associated with increased risk of LAA stroke (p < 0.0001, OR (95s% CI) = 6.57 (4.79–9.01)). Conclusion Our study indicated that the synergistic effects of MC4R variants, hypertension, and smoking habit contribute significantly to the risk of LAA stroke in the Chinese Han population. The finding revealed that obesity gene MC4R contribute to the risk of LAA stroke via a synergistic mechanism, which will provide new insight into the genetic architecture of LAA stroke. PMID:27701175

Evaluation of the Obesity Genes FTO and MC4R for Contribution to the Risk of Large Artery Atherosclerotic Stroke in a Chinese Population.

PubMed

Song, Zhi; Qiu, Lingling; Hu, Zhongyang; Liu, Jia; Liu, Ding; Hou, Deren

2016-01-01

Obesity is a well-established risk factor for large artery atherosclerotic (LAA) stroke. The aim of the study was to explore whether obesity genes, such as MC4R and FTO, contribute to LAA stroke risk in the Chinese Han population. 322 LAA stroke patients and 473 controls were recruited. Gene polymorphism of MC4R (rs17782313) and FTO (rs8050136 and rs9939609) were genotyped. No differences were observed in genotype frequencies of variants of FTO (rs8050136 and rs9939609) or MC4R (rs17782313) between LAA stroke patients and control subjects. However, rs17782313 of the MC4R gene was associated with LAA stroke susceptibility in smokers (rs17782313: p = 0.020, OR (95% CI) = 1.55 (1.07-2.23)) in the stratified analysis. Furthermore, multifactor dimensionality reduction analysis revealed that the combination of MC4R variant (rs17782313), hypertension and smoking habit was significantly associated with increased risk of LAA stroke (p < 0.0001, OR (95% CI) = 6.57 (4.79-9.01)). Our study indicated that the synergistic effects of MC4R variants, hypertension, and smoking habit contribute significantly to the risk of LAA stroke in the Chinese Han population. The finding revealed that obesity gene MC4R contribute to the risk of LAA stroke via a synergistic mechanism, which will provide new insight into the genetic architecture of LAA stroke. © 2016 The Author(s) Published by S. Karger GmbH, Freiburg.

Examination of association to autism of common genetic variationin genes related to dopamine.

PubMed

Anderson, B M; Schnetz-Boutaud, N; Bartlett, J; Wright, H H; Abramson, R K; Cuccaro, M L; Gilbert, J R; Pericak-Vance, M A; Haines, J L

2008-12-01

Autism is a severe neurodevelopmental disorder characterized by a triad of complications. Autistic individuals display significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Prevalence studies suggest that autism is more common than originally believed, with recent estimates citing a rate of one in 150. Although multiple genetic linkage and association studies have yielded multiple suggestive genes or chromosomal regions, a specific risk locus has yet to be identified and widely confirmed. Because many etiologies have been suggested for this complex syndrome, we hypothesize that one of the difficulties in identifying autism genes is that multiple genetic variants may be required to significantly increase the risk of developing autism. Thus, we took the alternative approach of examining 14 prominent dopamine pathway candidate genes for detailed study by genotyping 28 single nucleotide polymorphisms. Although we did observe a nominally significant association for rs2239535 (P=0.008) on chromosome 20, single-locus analysis did not reveal any results as significant after correction for multiple comparisons. No significant interaction was identified when Multifactor Dimensionality Reduction was employed to test specifically for multilocus effects. Although genome-wide linkage scans in autism have provided support for linkage to various loci along the dopamine pathway, our study does not provide strong evidence of linkage or association to any specific gene or combination of genes within the pathway. These results demonstrate that common genetic variation within the tested genes located within this pathway at most play a minor to moderate role in overall autism pathogenesis.

The role of genetic variation across IL-1β, IL-2, IL-6, and BDNF in antipsychotic-induced weight gain.

PubMed

Fonseka, Trehani M; Tiwari, Arun K; Gonçalves, Vanessa F; Lieberman, Jeffrey A; Meltzer, Herbert Y; Goldstein, Benjamin I; Kennedy, James L; Kennedy, Sidney H; Müller, Daniel J

2015-01-01

Antipsychotics with high weight gain-inducing propensities influence the expression of immune and neurotrophin genes, which have been independently related to obesity indices. Thus, we investigated whether variants in the genes encoding interleukin (IL)-1β, IL-2, and IL-6 and brain-derived neurotrophic factor (BDNF) Val66Met are associated with antipsychotic-induced weight gain (AIWG). Nineteen polymorphisms were genotyped using Taqman(®) assays in 188 schizophrenia patients on antipsychotic treatment for up to 14 weeks. Mean weight change (%) from baseline was compared across genotypic groups using analysis of covariance (ANCOVA). Epistatic effects between cytokine polymorphisms and BDNF Val66Met were tested using Model-Based Multifactor Dimensionality Reduction. In European patients, IL-1β rs16944*GA (P = 0.013, Pcorrected = 0.182), IL-1β rs1143634*G (P = 0.001, Pcorrected = 0.014), and BDNF Val66Met (Val/Val, P = 0.004, Pcorrected = 0.056) were associated with greater AIWG, as were IL-1β rs4849127*A (P = 0.049, Pcorrected = 0.784), and IL-1β rs16944*GA (P = 0.012, Pcorrected = 0.192) in African Americans. BDNF Val66Met interacted with both IL-1β rs13032029 (Val/Met+ TT, PPerm = 0.029), and IL-6 rs2069837 (Val/Val+ AA, PPerm = 0.021) in Europeans, in addition to IL-1β rs16944 (Val/Val+ GA, PPerm = 0.006) in African Americans. SNPs across IL-1β and BDNF Val66Met may influence AIWG. Replication of these findings in larger, independent samples is warranted.

Association between adiponectin polymorphisms and the risk of colorectal cancer.

PubMed

Guo, Xin; Liu, Jiaqi; You, Liuping; Li, Gang; Huang, Yuenan; Li, Yunlong

2015-01-01

To discuss the association between adiponectin (ADIPOQ) gene rs2241766 and rs1501299 polymorphisms and the risk of colorectal cancer, and to analyze the role of the interaction between these two loci and environmental factors in colorectal cancer pathogenesis. The case-control study was performed with a 1:1 match. A self-designed questionnaire was used to perform a face-to-face survey with 600 new primary colorectal cancer cases confirmed by histopathology as well as 600 cases of people receiving a physical examination at the same time. The general information, lifestyle, and diet habits, etc. were collected from two groups of study subjects. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used to identify ADIPOQ rs2241766 and rs1501299 genotypes. After adjusting for factors such as colorectal cancer family history, body-mass index (BMI), daily sedentary time, weekly red meat intake frequency, as well regular tea drinking, conditional logistic regression analysis indicated that rs2241766 TG+GG carriers had a higher risk of colorectal cancer than TT carriers (OR=1.433, 95% CI: 1.014-1.985); rs1501299 GT+TT carriers had a lower risk of colorectal cancer than GG carriers (OR=0.723, 95% CI: 0.531-0.902). Generalized multifactor dimensionality reduction analysis showed that ADIPOQ rs2241766 and rs1501299 could have interaction with red meat intake (p=0.001). ADIPOQ rs2241766 and rs1501299 single nucleotide polymorphisms (SNPs) could be associated with colorectal pathogenesis and could have interactions with red meat intake. Both factors impact colorectal cancer occurrence.

Artificial neural network model for predicting the bioavailability of tacrolimus in patients with renal transplantation

PubMed Central

Thishya, Kalluri; Vattam, Kiran Kumar; Naushad, Shaik Mohammad; Raju, Shree Bhushan

2018-01-01

The objective of the current study was to explore the role of ABCB1 and CYP3A5 genetic polymorphisms in predicting the bioavailability of tacrolimus and the risk for post-transplant diabetes. Artificial neural network (ANN) and logistic regression (LR) models were used to predict the bioavailability of tacrolimus and risk for post-transplant diabetes, respectively. The five-fold cross-validation of ANN model showed good correlation with the experimental data of bioavailability (r2 = 0.93–0.96). Younger age, male gender, optimal body mass index were shown to exhibit lower bioavailability of tacrolimus. ABCB1 1236 C>T and 2677G>T/A showed inverse association while CYP3A5*3 showed a positive association with the bioavailability of tacrolimus. Gender bias was observed in the association with ABCB1 3435 C>T polymorphism. CYP3A5*3 was shown to interact synergistically in increasing the bioavailability in combination with ABCB1 1236 TT or 2677GG genotypes. LR model showed an independent association of ABCB1 2677 G>T/A with post transplant diabetes (OR: 4.83, 95% CI: 1.22–19.03). Multifactor dimensionality reduction analysis (MDR) revealed that synergistic interactions between CYP3A5*3 and ABCB1 2677 G>T/A as the determinants of risk for post-transplant diabetes. To conclude, the ANN and MDR models explore both individual and synergistic effects of variables in modulating the bioavailability of tacrolimus and risk for post-transplant diabetes. PMID:29621269

The prevalence and structure of obsessive-compulsive personality disorder in Hispanic psychiatric outpatients

PubMed Central

Ansell, Emily B.; Pinto, Anthony; Crosby, Ross D.; Becker, Daniel F.; Añez, Luis M.; Paris, Manuel; Grilo, Carlos M.

2010-01-01

This study sought to confirm a multi-factor model of Obsessive-compulsive personality disorder (OCPD) in a Hispanic outpatient sample and to explore associations of the OCPD factors with aggression, depression, and suicidal thoughts. One hundred and thirty monolingual, Spanish-speaking participants were recruited from a community mental health center and were assessed by bilingual doctoral level clinicians. OCPD was highly prevalent (26%) in this sample. Multi-factor models of OCPD were tested and the two factors - perfectionism and interpersonal rigidity - provided the best model fit. Interpersonal rigidity was associated with aggression and anger while perfectionism was associated with depression and suicidal thoughts. PMID:20227063

A Multifactor Secure Authentication System for Wireless Payment

NASA Astrophysics Data System (ADS)

Sanyal, Sugata; Tiwari, Ayu; Sanyal, Sudip

Organizations are deploying wireless based online payment applications to expand their business globally, it increases the growing need of regulatory requirements for the protection of confidential data, and especially in internet based financial areas. Existing internet based authentication systems often use either the Web or the Mobile channel individually to confirm the claimed identity of the remote user. The vulnerability is that access is based on only single factor authentication which is not secure to protect user data, there is a need of multifactor authentication. This paper proposes a new protocol based on multifactor authentication system that is both secure and highly usable. It uses a novel approach based on Transaction Identification Code and SMS to enforce another security level with the traditional Login/password system. The system provides a highly secure environment that is simple to use and deploy with in a limited resources that does not require any change in infrastructure or underline protocol of wireless network. This Protocol for Wireless Payment is extended as a two way authentications system to satisfy the emerging market need of mutual authentication and also supports secure B2B communication which increases faith of the user and business organizations on wireless financial transaction using mobile devices.

The prevalence and structure of obsessive-compulsive personality disorder in Hispanic psychiatric outpatients.

PubMed

Ansell, Emily B; Pinto, Anthony; Crosby, Ross D; Becker, Daniel F; Añez, Luis M; Paris, Manuel; Grilo, Carlos M

2010-09-01

This study sought to confirm a multi-factor model of Obsessive-compulsive personality disorder (OCPD) in a Hispanic outpatient sample and to explore associations of the OCPD factors with aggression, depression, and suicidal thoughts. One hundred and thirty monolingual, Spanish-speaking participants were recruited from a community mental health center and were assessed by bilingual doctoral-level clinicians. OCPD was highly prevalent (26%) in this sample. Multi-factor models of OCPD were tested and the two factors - perfectionism and interpersonal rigidity - provided the best model fit. Interpersonal rigidity was associated with aggression and anger while perfectionism was associated with depression and suicidal thoughts. (c) 2010 Elsevier Ltd. All rights reserved.

What mental health teams want in their leaders.

PubMed

Corrigan, P W; Garman, A N; Lam, C; Leary, M

1998-11-01

The authors present the findings of the first phase of a 3-year study developing a skills training curriculum for mental health team leaders. A factor model empirically generated from clinical team members was compared to Bass' (1990) Multifactor Model of Leadership. Members of mental health teams generated individual responses to questions about effective leaders. Results from this survey were subsequently administered to a sample of mental health team members. Analysis of these data yielded six factors: Autocratic Leadership, Clear Roles and Goals, Reluctant Leadership, Vision, Diversity Issues, and Supervision. Additional analyses suggest Bass' Multifactor Model offers a useful paradigm for developing a curriculum specific to the needs of mental health team leaders.

Efficacy and safety of a multifactor intervention to improve therapeutic adherence in patients with chronic obstructive pulmonary disease (COPD): protocol for the ICEPOC study.

PubMed

Barnestein-Fonseca, Pilar; Leiva-Fernández, José; Vidal-España, Francisca; García-Ruiz, Antonio; Prados-Torres, Daniel; Leiva-Fernández, Francisca

2011-02-14

Low therapeutic adherence to medication is very common. Clinical effectiveness is related to dose rate and route of administration and so poor therapeutic adherence can reduce the clinical benefit of treatment. The therapeutic adherence of patients with chronic obstructive pulmonary disease (COPD) is extremely poor according to most studies. The research about COPD adherence has mainly focussed on quantifying its effect, and few studies have researched factors that affect non-adherence. Our study will evaluate the effectiveness of a multifactor intervention to improve the therapeutic adherence of COPD patients. A randomized controlled clinical trial with 140 COPD diagnosed patients selected by a non-probabilistic method of sampling. Subjects will be randomly allocated into two groups, using the block randomization technique. Every patient in each group will be visited four times during the year of the study. Motivational aspects related to adherence (beliefs and behaviour): group and individual interviews; cognitive aspects: information about illness; skills: inhaled technique training. Reinforcement of the cognitive-emotional aspects and inhaled technique training will be carried out in all visits of the intervention group. Adherence to a prescribed treatment involves a behavioural change. Cognitive, emotional and motivational aspects influence this change and so we consider the best intervention procedure to improve adherence would be a cognitive and emotional strategy which could be applied in daily clinical practice. Our hypothesis is that the application of a multifactor intervention (COPD information, dose reminders and reinforcing audiovisual material, motivational aspects and inhalation technique training) to COPD patients taking inhaled treatment will give a 25% increase in the number of patients showing therapeutic adherence in this group compared to the control group.We will evaluate the effectiveness of this multifactor intervention on patient adherence to inhaled drugs considering that it will be right and feasible to the clinical practice context. Current Controlled Trials ISRCTN18841601.

Association of IL-1β +3954 C/T and IL-10-1082 G/A cytokine gene polymorphisms with susceptibility to tuberculosis.

PubMed

Meenakshi, P; Ramya, S; Shruthi, T; Lavanya, J; Mohammed, H H; Mohammed, S A; Vijayalakshmi, V; Sumanlatha, G

2013-07-01

Tuberculosis (TB) constitutes the major cause of death due to infectious diseases. Cytokines play a major role in defence against Mycobacterium tuberculosis infection. Polymorphisms in the genes encoding various cytokines have been associated with tuberculosis susceptibility. Household contacts (HHC) are at increased risk of developing the disease. In this study, we examined the association of IL-1β and IL-10 cytokine gene polymorphisms with risk of developing tuberculosis in TB patients, their HHC and healthy controls (HC) using JavaStat and SPSS. Multifactor dimensionality reduction (MDR) analyses were performed to explore the potential gene-gene interactions. The genotype and allele frequencies of IL-1β +3954C/T polymorphism did not vary significantly between TB patients and HC. GG (P < 0.005, OR = 0.219 and 95% CI = 0.059-0.735) and GA (P < 0.0001, OR = 2.938 and 95% CI = 1.526-5.696) genotypes of IL-10-1082 G/A polymorphism were found to be significantly associated with patients versus HC. HHC with CC (P < 0.03, OR = 1.833 and 95% CI = 1.1-3.35) genotype in IL-1β and GA (P < 0.0001, OR = 4.612 and 95% CI = 2.225-9.702) genotype in IL-10 were at increased risk of developing tuberculosis. MDR tests revealed high-risk genotypes in IL-1β and IL-10 based on the association model. Our results demonstrate that the polymorphisms of IL-1β and IL-10 genes may be valuable markers to predict the risk for the development of TB in household contacts. © 2013 John Wiley & Sons Ltd.

New evidence for involvement of ESR1 gene in susceptibility to Chinese migraine.

PubMed

An, Xingkai; Fang, Jie; Lin, Qing; Lu, Congxia; Ma, Qilin; Qu, Hongli

2017-01-01

Migraine is a common and disabling nervous system disease with a significant genetic predisposition. The sex hormones play an important role in the pathogenesis of migraine. However, the conclusions of the previous genetic relation studies are conflicting. The aim of this study is to determine whether variants in genes involved in estrogen receptor and estrogen hormone metabolism are related to Chinese migraine. By employing a case-control approach, 8 SNPs in the ESR1, ESR2, and CYP19A1 genes are studied in a cohort of 494 migraine cases and 533 controls. In addition, genotyping is performed using Sequenom MALDI-TOF mass spectrometry iPLEX platform. Univariate and multivariate analyses are carried out by logistic regression. The corresponding haplotypes are studied with the Haploview software and gene-gene interaction is assessed using the Generalized Multifactor Dimensionality Reduction (GMDR) analysis. There are significant differences in allelic distributions for rs2234693 and rs9340799 in ESR1 gene between patients with migraine and control subjects. Univariate logistic analysis shows that rs2234693 and rs9340799 are risk factors for migraine, but multivariate analysis reveals that only rs2234693 is significant associated with migraine. In the subgroup analysis, rs2234693 in ESR1 gene is found associated with menstrually related migraine. Further haplotypic analysis shows that rs2234693-rs9340799 TA haplotype serves as risk haplotype for migraine. The GMDR analysis identifies rs2234693 in ESR1 alone to be a crucial candidate in migraine susceptibility. This study is in agreement with the previous studies that variants in the ESR1 gene are associated with migraine suggesting that it plays a role in the migraine process.

Evidence for gene-gene epistatic interactions among susceptibility loci for systemic lupus erythematosus.

PubMed

Hughes, Travis; Adler, Adam; Kelly, Jennifer A; Kaufman, Kenneth M; Williams, Adrienne H; Langefeld, Carl D; Brown, Elizabeth E; Alarcón, Graciela S; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Petri, Michelle; Boackle, Susan A; Stevens, Anne M; Reveille, John D; Sanchez, Elena; Martín, Javier; Niewold, Timothy B; Vilá, Luis M; Scofield, R Hal; Gilkeson, Gary S; Gaffney, Patrick M; Criswell, Lindsey A; Moser, Kathy L; Merrill, Joan T; Jacob, Chaim O; Tsao, Betty P; James, Judith A; Vyse, Timothy J; Alarcón-Riquelme, Marta E; Harley, John B; Richardson, Bruce C; Sawalha, Amr H

2012-02-01

Several confirmed genetic susceptibility loci for lupus have been described. To date, no clear evidence for genetic epistasis in lupus has been established. The aim of this study was to test for gene-gene interactions in a number of known lupus susceptibility loci. Eighteen single-nucleotide polymorphisms tagging independent and confirmed lupus susceptibility loci were genotyped in a set of 4,248 patients with lupus and 3,818 normal healthy control subjects of European descent. Epistasis was tested by a 2-step approach using both parametric and nonparametric methods. The false discovery rate (FDR) method was used to correct for multiple testing. We detected and confirmed gene-gene interactions between the HLA region and CTLA4, IRF5, and ITGAM and between PDCD1 and IL21 in patients with lupus. The most significant interaction detected by parametric analysis was between rs3131379 in the HLA region and rs231775 in CTLA4 (interaction odds ratio 1.19, Z = 3.95, P = 7.8 × 10(-5) [FDR ≤0.05], P for multifactor dimensionality reduction = 5.9 × 10(-45)). Importantly, our data suggest that in patients with lupus, the presence of the HLA lupus risk alleles in rs1270942 and rs3131379 increases the odds of also carrying the lupus risk allele in IRF5 (rs2070197) by 17% and 16%, respectively (P = 0.0028 and P = 0.0047, respectively). We provide evidence for gene-gene epistasis in systemic lupus erythematosus. These findings support a role for genetic interaction contributing to the complexity of lupus heritability. Copyright © 2012 by the American College of Rheumatology.

Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

PubMed

Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

2014-06-01

Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

Transforming growth factor beta-3 and environmental factors and cleft lip with/without cleft palate.

PubMed

Guo, Zeqiang; Huang, Chengle; Ding, Kaihong; Lin, Jianyan; Gong, Binzhong

2010-07-01

To identify the interactions among two loci (C641A and G15572-) of transforming growth factor beta 3 (TGFbeta3), and exposures in pregnancy with cleft lip with/without cleft palate (CL/P), a hospital-based case-control study was conducted. Associations among offspring polymorphisms of TGFbeta3 C641A and G15572-, paternal smoking, paternal high-risk drinking, maternal passive smoking, and maternal multivitamin supplement with CL/P were analyzed by logistic regression analysis, and the results showed that maternal passive smoking exposures and maternal multivitamin use were associated with the risk of CL/P but offspring polymorphisms of TGFbeta3 C641A and G15572-, paternal smoking, and paternal high-risk drinking were not. Interactions among these variables were analyzed using the multifactor dimensionality reduction method, and the results showed that the two-factor model, including maternal passive smoking and TGFbeta3 C641A, among all models evaluated had the best ability to predict CL/P risk with a maximum cross-validation consistency (9/10) and a maximum average testing accuracy (0.5892; p = 0.0010). These findings suggested that maternal passive smoking exposure is a risk factor for CL/P, whereas maternal multivitamin supplement is a protective factor. The polymorphism of TGFbeta3 C641A participates in interaction effect for CL/P with environmental exposures, although the polymorphism was not associated with CL/P in single-locus analysis, and synergistic effect of TGFbeta3 C641A and maternal passive smoking could provide a new tool for identifying high-risk individuals of CL/P and also an additional evidence that CL/P is determined by both genetic and environmental factors.

Association between oxytocin and receptor genetic polymorphisms and aggression in a northern Chinese Han population with alcohol dependence.

PubMed

Yang, Ling; Wang, Fan; Wang, Meiling; Han, Mei; Hu, Lufeng; Zheng, Minghua; Ma, Ji; Kang, Yimin; Wang, Pengxiang; Sun, Hongqiang; Zuo, Wei; Xie, Longteng; Wang, Aiju; Yu, Dongsheng; Liu, Yanlong

2017-01-01

Alcohol dependence (AD) is a common chronic brain disorder precipitated by complex interactions between biological, genetic, and environmental risk factors. Aggression often occurs in the context of AD. Previous studies have shown that Oxytocin (OXT) and OXT receptor (OXTR) are involved in the regulation of aggression. The present study investigated whether variations and interactions of OXT and OXTR genes were associated with AD-related aggression in a genetically homogeneous northern Chinese Han population. Three hundred and twenty-four male AD patients and 510 male healthy controls (HCs) were recruited. A Chinese version of the Buss-Perry Aggression Questionnaire was used as a subjective measurement of aggressive behavior. Three variations, rs2254298, rs53576, and rs6133010 were genotyped using TaqMan and ligase detection reaction for all subjects. Generalized Multifactor Dimensionality Reduction was used to detect interactions between genetic attributes and environmental attributes. The frequencies of alleles and genotypes of rs6133010 were significantly different between AD patients and HCs (p<0.001). In HCs, the effect of genotype GG of rs53576 on hostility aggression was significantly stronger than that of genotype AA and AG (p=0.001 and p=0.004, respectively), and the subjects with the interaction combination of rs6133010AA×rs2254298GG×rs53576AG exhibited significant effect on physical aggression (p=0.0107). The present study found that rs6133010 in the OXT gene is associated with AD in the northern Chinese Han population. The polymorphisms of OXT/R may play a key role in the susceptibility of AD-related aggression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Epistasis Analysis for Estrogen Metabolic and Signaling Pathway Genes on Young Ischemic Stroke Patients

PubMed Central

Hsieh, Yi-Chen; Jeng, Jiann-Shing; Lin, Huey-Juan; Hu, Chaur-Jong; Yu, Chia-Chen; Lien, Li-Ming; Peng, Giia-Sheun; Chen, Chin-I; Tang, Sung-Chun; Chi, Nai-Fang; Tseng, Hung-Pin; Chern, Chang-Ming; Hsieh, Fang-I; Bai, Chyi-Huey; Chen, Yi-Rhu; Chiou, Hung-Yi; Jeng, Jiann-Shing; Tang, Sung-Chun; Yeh, Shin-Joe; Tsai, Li-Kai; Kong, Shin; Lien, Li-Ming; Chiu, Hou-Chang; Chen, Wei-Hung; Bai, Chyi-Huey; Huang, Tzu-Hsuan; Chi-Ieong, Lau; Wu, Ya-Ying; Yuan, Rey-Yue; Hu, Chaur-Jong; Sheu, Jau- Jiuan; Yu, Jia-Ming; Ho, Chun-Sum; Chen, Chin-I; Sung, Jia-Ying; Weng, Hsing-Yu; Han, Yu-Hsuan; Huang, Chun-Ping; Chung, Wen-Ting; Ke, Der-Shin; Lin, Huey-Juan; Chang, Chia-Yu; Yeh, Poh-Shiow; Lin, Kao-Chang; Cheng, Tain-Junn; Chou, Chih-Ho; Yang, Chun-Ming; Peng, Giia-Sheun; Lin, Jiann-Chyun; Hsu, Yaw-Don; Denq, Jong-Chyou; Lee, Jiunn-Tay; Hsu, Chang-Hung; Lin, Chun-Chieh; Yen, Che-Hung; Cheng, Chun-An; Sung, Yueh-Feng; Chen, Yuan-Liang; Lien, Ming-Tung; Chou, Chung-Hsing; Liu, Chia-Chen; Yang, Fu-Chi; Wu, Yi-Chung; Tso, An-Chen; Lai, Yu- Hua; Chiang, Chun-I; Tsai, Chia-Kuang; Liu, Meng-Ta; Lin, Ying-Che; Hsu, Yu-Chuan; Chen, Chih-Hung; Sung, Pi-Shan; Chern, Chang-Ming; Hu, Han-Hwa; Wong, Wen-Jang; Luk, Yun-On; Hsu, Li-Chi; Chung, Chih-Ping; Tseng, Hung-Pin; Liu, Chin-Hsiung; Lin, Chun-Liang; Lin, Hung-Chih; Hu, Chaur-Jong

2012-01-01

Background Endogenous estrogens play an important role in the overall cardiocirculatory system. However, there are no studies exploring the hormone metabolism and signaling pathway genes together on ischemic stroke, including sulfotransferase family 1E (SULT1E1), catechol-O-methyl-transferase (COMT), and estrogen receptor α (ESR1). Methods A case-control study was conducted on 305 young ischemic stroke subjects aged ≦ 50 years and 309 age-matched healthy controls. SULT1E1 -64G/A, COMT Val158Met, ESR1 c.454−397 T/C and c.454−351 A/G genes were genotyped and compared between cases and controls to identify single nucleotide polymorphisms associated with ischemic stroke susceptibility. Gene-gene interaction effects were analyzed using entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional multiple regression models. Results COMT Val158Met polymorphism showed a significant association with susceptibility of young ischemic stroke among females. There was a two-way interaction between SULT1E1 -64G/A and COMT Val158Met in both MDR and CART analysis. The logistic regression model also showed there was a significant interaction effect between SULT1E1 -64G/A and COMT Val158Met on ischemic stroke of the young (P for interaction = 0.0171). We further found that lower estradiol level could increase the risk of young ischemic stroke for those who carry either SULT1E1 or COMT risk genotypes, showing a significant interaction effect (P for interaction = 0.0174). Conclusions Our findings support that a significant epistasis effect exists among estrogen metabolic and signaling pathway genes and gene-environment interactions on young ischemic stroke subjects. PMID:23112845

Interaction among variants in the SLC gene family (SLC6A14, SLC26A9, SLC11A1, and SLC9A3) and CFTR mutations with clinical markers of cystic fibrosis.

PubMed

Pereira, Stephanie V N; Ribeiro, Jose D; Bertuzzo, Carmen S; Marson, Fernando A L

2018-04-10

Cystic fibrosis (CF) is due to dysfunction of the CFTR channel and function of this channel is, in turn, affected by modifier genes that can impact the clinical phenotype. In this context, we analyzed the interaction among rs3788766*SLC6A14, rs7512462*SLC26A9, rs17235416*SLC11A1, and rs17563161*SLC9A3 variants, CFTR mutations and 40 CF severity markers by the Multifactor Dimensionality Reduction (MDR) model. A total of 164 patients with CF were included in the study. The variants in the modifier genes were identified by real-time PCR and the genotype of the CFTR gene in the diagnostic routine. Analysis of interaction between variants, CFTR mutations groupings and demographic, clinical and laboratory data were performed by the MDR. There were interaction between the rs3788766, rs7512462, rs17235416, and rs17563161 variants, and CFTR mutations with pancreatic insufficiency (PI), onset of digestive symptoms, and presence of mucoid Pseudomonas aeruginosa. Regarding PI, the interaction was observed for CFTR*rs17563161 (P-value = 0.015). Also, for onset of digestive symptoms the interaction was observed for CFTR*rs3788766*rs7512462*rs17235416*rs17563161 (P-value = 0.036). Considering the presence of mucoid P. aeruginosa, the interaction occurred for CFTR*rs3788766*rs7512462*rs17563161 (P-value = 0.035). Interaction between variants in the SLC family genes and the grouping for CFTR mutations were associated with PI, onset of digestive symptoms and mucoid P. aeruginosa, being important to determine one of the factors that may cause the diversity among the patients with CF. © 2018 Wiley Periodicals, Inc.

Interactions among variants in TXA2R, P2Y12 and GPIIIa are associated with carotid plaque vulnerability in Chinese population.

PubMed

Yi, Xingyang; Lin, Jing; Luo, Hua; Zhou, Ju; Zhou, Qiang; Wang, Yanfen; Wang, Chun

2018-04-03

The associations between variants in platelet activation-relevant genes and carotid plaque vulnerability are not fully understood. The aim of the present study was to investigate the associations of the variants in platelet activation-relevant genes and interactions among these variants with carotid plaque vulnerability. There were no significant differences in the frequencies of genotypes of the 11 variants between patients and controls. Among 396 patients, 102 patients had not carotid plaque, 106 had VP, and 188 had SP. The 11 variants were not independently associated with risk of carotid plaque vulnerability after adjusting for potential confounding variables. However, the GMDR analysis showed that there were synergistic effects of gene-gene interactions among TXA2Rr s1131882, GPIIIa rs2317676 and P2Y12 rs16863323 on carotid plaque vulnerability. The high-risk interactions among the three variants were associated with high platelet activation, and independently associated with the risk of carotid plaque vulnerability. Eleven variants in platelet activation-relevant genes were examined using mass spectrometry methods in 396 ischemic stroke patients and 291controls. Platelet-leukocyte aggregates and platelet aggregation were also measured. Carotid plaques were assessed by B-mode ultrasound. According to the results of ultrasound, the patients were stratified into three groups: non-plaque group, vulnerable plaque (VP) group and stable plaque (SP) group. Furthermore, gene-gene interactions were analyzed using generalized multifactor dimensionality reduction (GMDR) methods. The rs1131882, rs2317676, and rs16863323 three-loci interactions may confer a higher risk of carotid plaque vulnerability, and might be potential markers for plaque instability.

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

The association of 5-HTR2A-1438A/G, COMTVal158Met, MAOA-LPR, DATVNTR and 5-HTTVNTR gene polymorphisms and borderline personality disorder in female heroin-dependent Chinese subjects.

PubMed

Yang, Mei; Mamy, Jules; Wang, Qiang; Liao, Yan-Hui; Seewoobudul, Vasish; Xiao, Shui-Yuan; Hao, Wei

2014-04-03

To explore the association between the 5-HTR2A-1438A/G, COMTVal158Met, MAOA-LPR, DATVNTR and 5-HTTVNTR polymorphisms with co-morbid borderline personality disorder (BPD) in female heroin-dependent patients. In a case control study, we compared the polymorphic distributions of 5-HTR2A-1438A/G, COMTVal158Met, MAOA-LPR, DATVNTR and 5-HTTVNTR in 296 female heroin-dependent patients (including 61 patients with BPD and 235 without BPD) and 101 normal females by genotypes, alleles, and interaction between genes. Female heroin-dependent subjects with BPD have lower frequency of the high activity allele (L: 4 repeats (4R)) of MAOA-LPR than those female heroin-dependent subjects without BPD, and have higher 5-HTTVNTR 10R/10R genotype frequency than normal female controls, with adjusted P-value<0.05 (after adjusted for multiple testing by 1000-fold permutation tests) respectively. By MDR (Multifactor Dimensionality Reduction) analyses, the interactive effects between MAOA-LPR and 5-HTTVNTR, and among MAOA-LPR, 5-HTTVNTR and rs6311 were close to the significance level (P=0.05) in predicting the risk of co-morbidity of BPD and heroin dependence relative to normal female controls, with 1000-fold permutation testing P-value<0.06 however >0.05 respectively. 5-HTTVNTR and MAOA-LPR may have independent predictive effects on co-morbid BPD in female heroin-dependent patients; the gene-gene interactions between MAOA-LPR and 5-HTTVNTR, and among MAOA-LPR, 5-HTTVNTR and rs6311 might also be involved in the etiology of this co-morbidity. Copyright © 2013 Elsevier Inc. All rights reserved.

Impact of interaction between the G870A and EFEMP1 gene polymorphism on glioma risk in Chinese Han population.

PubMed

Yang, Libin; Qu, Bo; Xia, Xun; Kuang, Yongqin; Li, Jian; Fan, Kexia; Guo, Heng; Zheng, Hui; Ma, Yuan

2017-06-06

To investigate the impact of CCND1 and EFEMP1 gene polymorphism, and additional their gene-gene interactions and haplotype within EFEMP1 gene on glioma risk based on Chinese population. Logistic regression was performed to investigate association between single-nucleotide polymorphisms (SNP) and glioma risk and generalized multifactor dimensionality reduction (GMDR) was used to analyze the gene-gene interaction. Glioma risks were higher in carriers of homozygous mutant of rs603965 within CCND1 gene, rs1346787 and rs3791679 in EFEMP1 gene than those with wild-type homozygotes, OR (95%CI) were 1.67 (1.23-2.02), 1.59 (1.25-2.01) and 1.42 (1.15-1.82), respectively. GMDR analysis indicated a significant two-locus model (p=0.0010) involving rs603965 within CCND1 gene and rs1346787 within EFEMP1 gene. Overall, the cross-validation consistency of the two- locus models was 10\\ 10, and the testing accuracy is 60.17%. Participants with rs603965 - GA or AA and rs1346787- AG or GG genotype have the highest glioma risk, compared to participants with rs603965 - GG and rs1346787- AA genotype, OR (95%CI) was 3.65 (1.81-5.22). We conducted haplotype analysis for rs1346787 and rs3791679, because D' value between rs1346787 and rs3791679 was more than 0.8. The most common haplotype was rs1346787 - A and rs3791679- G haplotype, the frequency of which was 0.4905 and 0.4428 in case and control group. Polymorphism in rs603965 within CCND1 gene and rs1346787 within EFEMP1 gene and its gene- gene interaction were associated with increased glioma risk.

Haplotype-based gene-gene interaction of bone morphogenetic protein 4 and interferon regulatory factor 6 in the etiology of non-syndromic cleft lip with or without cleft palate in a Chilean population.

PubMed

Blanco, Rafael; Colombo, Alicia; Pardo, Rosa; Suazo, José

2017-04-01

Non-syndromic cleft lip with or without cleft palate (NSCL/P) is the most common craniofacial birth defect in humans, the etiology of which can be dependent on the interactions of multiple genes. We previously reported haplotype associations for polymorphic variants of interferon regulatory factor 6 (IRF6), msh homeobox 1 (MSX1), bone morphogenetic protein 4 (BMP4), and transforming growth factor beta 3 (TGFB3) in Chile. Here, we analyzed the haplotype-based gene-gene interaction for markers of these genes and NSCL/P risk in the Chilean population. We genotyped 15 single nucleoptide polymorphisms (SNPs) in 152 Chilean patients and 164 controls. Linkage disequilibrium (LD) blocks were determined using the Haploview software, and phase reconstruction was performed by the Phase program. Haplotype-based interactions were evaluated using the multifactor dimensionality reduction (MDR) method. We detected two LD blocks composed of two SNPs from BMP4 (Block 1) and three SNPs from IRF6 (Block 2). Although MDR showed no statistical significance for the global interaction model involving these blocks, we found four combinations conferring a statistically significantly increased NSCL/P risk (Block 1-Block 2): T-T/T-G C-G-T/G-A-T; T-T/T-G C-G-C/C-G-C; T-T/T-G G-A-T/G-A-T; and T-T/C-G G-A-T/G-A-T. These findings may reflect the presence of a genomic region containing potential causal variants interacting in the etiology of NSCL/P and may contribute to disentangling the complex etiology of this birth defect. © 2017 Eur J Oral Sci.

Association of Cytochrome P450 Genetic Variants with Clopidogrel Resistance and Outcomes in Acute Ischemic Stroke

PubMed Central

Yi, Xingyang; Wang, Yanfen; Zhou, Qiang; Wang, Chun; Cheng, Wen; Chi, Lifen

2016-01-01

Aims: Clopidogrel is an antiplatelet drug primarily used to treat or prevent acute ischemic stroke (IS) or myocardial infarction (MI). This prodrug requires biotransformation to an active metabolite by cytochrome P450 (CYP) enzymes, and CYP single nucleotide polymorphisms (SNPs) could affect the efficiency of such biotransformation. Methods: A total of 375 consecutive IS patients were genotyped for eight CYP SNPs using mass spectrometry. Platelet aggregation activity was measured before and after the 7 – 10 day treatment. Gene–gene interactions were analyzed using generalized multifactor dimensionality reduction (GMDR) analysis. All patients received clopidogrel therapy and were followed up for six months. Primary outcomes were evaluated as a composite of recurrent ischemic stroke (RIS), MI, and death. The secondary outcome was the modified Rankin Scale (mRS). Results: Clopidogrel resistance occurred in 153 patients (40.8%). The frequency of CYP3A5 (rs776746) GG/AG and CYP2C19*2 (rs4244285) AA/AG genotypes was significantly higher in clopidogrel-resistant patients than in sensitive patients. There was a significant gene-gene interaction between CYP3A5 (rs776746) and CYP2C19*2 (rs4244285). CYP2C19*2 AA and its interaction with CYP3A5 GG were independent predictors of clopidogrel resistance and affected the activity of platelet aggregation. Diabetes mellitus, CYP2C19*2 (rs4244285), clopidogrel resistance, and the interaction of CYP2C19*2 with CYP3A5 were all independent risk factors for the primary outcomes of clopidogrel treatment. Clopidogrel-resistant patients were more likely to have poor outcomes (mRS > 2 points) compared with clopidogrel-sensitive patients. Conclusion: CYP SNPs and their interactions are associated with drug resistance and outcomes in acute IS patients. PMID:26961113

Interaction of CYP2C19, P2Y12, and GPIIIa Variants Associates With Efficacy of Clopidogrel and Adverse Events on Patients With Ischemic Stroke.

PubMed

Yi, Xingyang; Wang, Yanfen; Lin, Jing; Cheng, Wen; Zhou, Qiang; Wang, Chun

2017-10-01

Clopidogrel is a clinically important oral antiplatelet agent for the treatment or prevention of cerebrovascular disease. However, different individuals have different sensitivities to clopidogrel. This study assessed variants of different genes for association with response to clopidogrel, clinical outcome, and side effects in patients with ischemic stroke (IS). We consecutively enrolled 375 patients with IS after they received clopidogrel therapy, and venous blood samples were subjected to genotyping allelic variants of genes modulating clopidogrel absorption (ATP binding cassette subfamily B1, ABCB1), metabolic activation (cytochrome P450[CYP] 3A and CYP2C19), and biologic activity (platelet membrane receptor [ P2Y12, P2Y1)], and glycoprotein IIIa [ GPIIIa]) and statistically analyzing their interactions with clopidogrel sensitivity (CS) and adverse events, risk of IS recurrence, myocardial infarction, and death during 6 months of follow-up. Adverse events occurred in 37 patients (31 had IS recurrence, 4 died, and 2 had myocardial infarction) during the first 6 months of follow-up. Single locus analysis showed that only the CYP2C19*2(rs4244285) variant was independently associated with CS and risk of adverse events after adjusting covariates. However, there was significant gene-gene interaction among CYP2C19*2(rs4244285), P2Y12(rs16863323), and GPIIIa (rs2317676) analyzed by generalized multifactor dimensionality reduction methods. The rate of adverse events among patients with the 3-loci interaction was 2.82 times the rate among those with no interaction (95% confidence interval: 2.04-8.63). Sensitivity of patients with IS to clopidogrel and clopidogrel-induced adverse clinical events may be multifactorial but is not determined by single gene polymorphisms.

Epistatic effect of plasminogen activator inhibitor 1 and beta-fibrinogen genes on risk of glomerular microthrombosis in lupus nephritis: interaction with environmental/clinical factors.

PubMed

Gong, Rujun; Liu, Zhihong; Li, Leishi

2007-05-01

Glomerular microthrombosis (GMT) is not uncommon in lupus nephritis and has been associated with active renal injury and progressive kidney destruction. We undertook this study to determine whether genetic variations of hemostasis factors, such as plasminogen activator inhibitor 1 (PAI-1) and fibrinogen, affect the risk of GMT. A cross-sectional cohort of 101 lupus nephritis patients with or without GMT was genotyped for PAI-1 -675 4G/5G and beta-fibrinogen (FGB) -455 G/A gene polymorphisms and analyzed. PAI-1 4G/4G homozygotes and FGB A allele carriers were both at increased risk for GMT. When the data were stratified for both gene polymorphisms, an epistatic effect was detected. The PAI-1 4G/4G genotype was found to predispose to GMT not equally in all lupus nephritis patients, but only in FGB A allele carriers. Likewise, the association between the FGB A allele and GMT was restricted to lupus nephritis patients homozygous for the PAI-1 4G allele. This epistatic effect was revalidated by the multifactor dimensionality reduction (MDR) analysis and further assessed by incorporating a variety of environmental and clinical factors into the MDR analysis. The most parsimonious model that had a cross-validation consistency of 100% included joint effects of PAI-1 and FGB gene polymorphisms and anticardiolipin antibody (aCL) status and yielded the best prediction of GMT, with 66.6% accuracy. Our findings suggest that risk of GMT in lupus nephritis is attributable, at least in part, to an epistatic effect of PAI-1 and FGB genes, likely via an interaction with environmental/clinical factors, such as aCL.

Heat shock protein 70 gene polymorphisms' influence on the electrophysiology of long QT syndrome.

PubMed

Ali, Altaf; Qureshi, Sameera F; Medikare, Veronica; Venkateshwari, Ananthapur; Calambur, Narsimhan; Rao, Hygriv; Jayakrishnan, M P; Shenthar, Jayaprakash; Thangaraj, Kumarasamy; Nallari, Pratibha

2016-03-01

Long QT syndrome (LQTS) is a rare cardiac disorder caused due to mutations in genes encoding ion channels responsible for generation of electrical impulses. The heat shock protein (HSP)-70 gene, expressed under conditions of stress, plays a cardioprotective role when overexpressed and helps in the proper folding of the nascent proteins synthesized by the cellular machinery. We aimed to identify the role played by HSP-70 gene polymorphisms in the pathogenesis of LQTS. Study included 49 LQTS patients, 71 family members, and 219 healthy individuals recruited from an ethnically matched population. Genotyping of the single-nucleotide polymorphisms (SNPs) rs1043618 (HSP-70-1, +190G/C), rs1061581 (HSP-70-2, +1267A/G), and rs2227956 (HSP-70-hom, +2437T/C) was performed by PCR-RFLP analysis, and the results were analyzed statistically at 95 % confidence interval and p ≤ 0. 05. The "C" allele of HSP-70-1 (+190G/C) and "G" allele of HSP-70-2 (+1267A/G) showed strong association with LQTS phenotype. The haplotype group C-G-T consisting of two risk alleles was significantly associated with the disease condition. Multifactor dimensionality reduction analysis further substantiated that the three-allele model influences the outcome of the phenotype highlighting the effect of modifiers in the etiology of LQTS. As HSP-70 influences the channel assembly and maturation/trafficking of the ion channel proteins, the alleles C of the HSP-70-1 and G of the HSP-70-2 loci and the haplotype group C-G-T could be considered a diagnostic biomarker in the identification of the LQTS phenotype with a potential to affect the progression and modification of the disease phenotype.

Interaction of CARD14, SENP1 and VEGFA polymorphisms on susceptibility to high altitude polycythemia in the Han Chinese population at the Qinghai-Tibetan Plateau.

PubMed

Chen, Yu; Jiang, Chunhua; Luo, Yongjun; Liu, Fuyu; Gao, Yuqi

2016-03-01

High altitude polycythemia (HAPC) is a serious public health problem among Han Chinese immigrants to the Qinghai-Tibetan Plateau. This study aims to explore the genetic basis of HAPC in the Han Chinese population. 484 male subjects (234 patients and 250 controls) were enrolled in this study. Genotyping was performed for polymorphisms of I/D in ACE, C1772T and G1790A in exon 12 of HIF-1α, rs2567206 in CYP1B1, rs726354 in SENP1, rs3025033 in VEGFA, rs7251432 in HAMP, rs2075800 in HSPA1L and rs8065364 in CARD14. Gene-gene interaction was assessed by multifactor dimensionality reduction. A significant association was seen between CARD14 polymorphism rs8065364 and risk of HAPC development in male Han Chinese, and the C allele of rs8065364 was a risk factor (odds ratio (OR)=1.59, 95% confidence interval (95% CI)=1.21-2.08). Gene-gene interaction analysis indicated that a synergistic relationship existed between rs3025033 and rs8065364 (1.00%), rs3025033 and rs726354 (0.18%), and rs726354 and rs8065364 (0.17%). The combination of rs8065364 in CARD14, rs3025033 in VEGFA and rs726354 in SENP1 was the best model to predict HAPC development in this study (testing accuracy=0.6183, p=0.0010, cross-validated consistency=10/10). Genetic interactions of SNPs in CARD14, SENP1 and VEGFA might represent a functional mechanism in the pathogenesis of HAPC. Copyright © 2015 Elsevier Inc. All rights reserved.

Molecular insights into the association of obesity with breast cancer risk: relevance to xenobiotic metabolism and CpG island methylation of tumor suppressor genes.

PubMed

Naushad, Shaik Mohammad; Hussain, Tajamul; Al-Attas, Omar S; Prayaga, Aruna; Digumarti, Raghunadha Rao; Gottumukkala, Suryanarayana Raju; Kutala, Vijay Kumar

2014-07-01

Obesity, genetic polymorphisms of xenobiotic metabolic pathway, hypermethylation of tumor suppressor genes, and hypomethylation of proapoptotic genes are known to be independent risk factors for breast cancer. The objective of this study is to evaluate the combined effect of these environmental, genetic, and epigenetic risk factors on the susceptibility to breast cancer. PCR-RFLP and multiplex PCR were used for the genetic analysis of six variants of xenobiotic metabolic pathway. Methylation-specific PCR was used for the epigenetic analysis of four genetic loci. Multifactor dimensionality reduction analysis revealed a significant interaction between the body mass index (BMI) and catechol-O-methyl transferase H108L variant alone or in combination with cytochrome P450 (CYP) 1A1m1 variant. Women with "Luminal A" breast cancer phenotype had higher BMI compared to other phenotypes and healthy controls. There was no association between the BMI and tumor grade. The post-menopausal obese women exhibited lower glutathione levels. BMI showed a positive association with the methylation of extracellular superoxide dismutase (r = 0.21, p < 0.05), Ras-association (RalGDS/AF-6) domain family member 1 (RASSF1A) (r = 0.31, p < 0.001), and breast cancer type 1 susceptibility protein (r = 0.19, p < 0.05); and inverse association with methylation of BNIP3 (r = -0.48, p < 0.0001). To conclude based on these results, obesity increases the breast cancer susceptibility by two possible mechanisms: (i) by interacting with xenobiotic genetic polymorphisms in inducing increased oxidative DNA damage and (ii) by altering the methylome of several tumor suppressor genes.

CYP1A1, GCLC, AGT, AGTR1 gene-gene interactions in community-acquired pneumonia pulmonary complications.

PubMed

Salnikova, Lyubov E; Smelaya, Tamara V; Golubev, Arkadiy M; Rubanovich, Alexander V; Moroz, Viktor V

2013-11-01

This study was conducted to establish the possible contribution of functional gene polymorphisms in detoxification/oxidative stress and vascular remodeling pathways to community-acquired pneumonia (CAP) susceptibility in the case-control study (350 CAP patients, 432 control subjects) and to predisposition to the development of CAP complications in the prospective study. All subjects were genotyped for 16 polymorphic variants in the 14 genes of xenobiotics detoxification CYP1A1, AhR, GSTM1, GSTT1, ABCB1, redox-status SOD2, CAT, GCLC, and vascular homeostasis ACE, AGT, AGTR1, NOS3, MTHFR, VEGFα. Risk of pulmonary complications (PC) in the single locus analysis was associated with CYP1A1, GCLC and AGTR1 genes. Extra PC (toxic shock syndrome and myocarditis) were not associated with these genes. We evaluated gene-gene interactions using multi-factor dimensionality reduction, and cumulative gene risk score approaches. The final model which included >5 risk alleles in the CYP1A1 (rs2606345, rs4646903, rs1048943), GCLC, AGT, and AGTR1 genes was associated with pleuritis, empyema, acute respiratory distress syndrome, all PC and acute respiratory failure (ARF). We considered CYP1A1, GCLC, AGT, AGTR1 gene set using Set Distiller mode implemented in GeneDecks for discovering gene-set relations via the degree of sharing descriptors within a given gene set. N-acetylcysteine and oxygen were defined by Set Distiller as the best descriptors for the gene set associated in the present study with PC and ARF. Results of the study are in line with literature data and suggest that genetically determined oxidative stress exacerbation may contribute to the progression of lung inflammation.

A computational intelligent approach to multi-factor analysis of violent crime information system

NASA Astrophysics Data System (ADS)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Probabilistic lifetime strength of aerospace materials via computational simulation

NASA Technical Reports Server (NTRS)

Boyce, Lola; Keating, Jerome P.; Lovelace, Thomas B.; Bast, Callie C.

1991-01-01

The results of a second year effort of a research program are presented. The research included development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic phenomenological constitutive relationship, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects of primitive variables. These primitive variables often originate in the environment and may include stress from loading, temperature, chemical, or radiation attack. This multifactor interaction constitutive equation is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the constitutive equation using actual experimental materials data together with the multiple linear regression of that data.

Multifactor Screener in OPEN: Scoring Procedures & Results

Cancer.gov

Scoring procedures were developed to convert a respondent's screener responses to estimates of individual dietary intake for percentage energy from fat, grams of fiber, and servings of fruits and vegetables.

[Energy Conservation and Emissions Reduction Benefits Analysis for Battery Electric Buses Based on Travel Services].

PubMed

Lin, Xiao-dan; Tian, Liang; Lü, Bin; Yang, Jian-xin

2015-09-01

Battery Electric Bus (BEB) has become one of prior options of urban buses for its "zero emission" during the driving stage. However, the environmental performance of electric buses is affected by multi-factors from the point of whole life cycle. In practice, carrying capacity of BEB and power generation structures can both implement evident effects on the energy consumption and pollutants emission of BEB. Therefore, take the above factors into consideration, in this article, Life Cycle Assessment is employed to evaluate the energy conservation and emissions reduction benefits of BEB. Results indicate that, travel service is more reasonable as the functional unit, rather than mileage, since the carrying capacity of BEB is 15% lower than the diesel buses. Moreover, compared with diesel buses, the energy conservation and emissions reduction benefits of battery electric buses are all different due to different regional power structures. Specifically, the energy benefits are 7. 84%, 11. 91%, 26. 90%, 11. 15%, 19. 55% and 20. 31% respectively in Huabei, Huadong, Huazhong, Dongbei, Xibei and Nanfang power structure. From the point of comprehensive emissions reduction benefits, there is no benefit in Huabei power structure, as it depends heavily on coal. But in other areas, the comprehensive emissions reduction benefits of BEB are separately 3. 46%, 26. 81%, 1. 17%, 13. 74% and 17. 48% in Huadong, Huazhong, Dongbei, Xibei and Nanfang. Therefore, it suggests that, enlargement of carrying capacity should be taken as the most prior technology innovation direction for BEB, and the grids power structure should be taken into consideration when the development of BEB is in planning.

Dimensionality reduction of collective motion by principal manifolds

NASA Astrophysics Data System (ADS)

Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.

2015-01-01

While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.

Adjunctive dental therapy via tooth plaque reduction and gingivitis treatment by blue light-emitting diodes tooth brushing

NASA Astrophysics Data System (ADS)

Genina, Elina A.; Titorenko, Vladimir A.; Belikov, Andrey V.; Bashkatov, Alexey N.; Tuchin, Valery V.

2015-12-01

The efficacy of blue light-emitting toothbrushes (B-LETBs) (405 to 420 nm, power density 2 mW/cm2) for reduction of dental plaques and gingival inflammation has been evaluated. Microbiological study has shown the multifactor therapeutic action of the B-LETBs on oral pathological microflora: in addition to partial mechanical removal of bacteria, photodynamic action suppresses them up to 97.5%. In the pilot clinical studies, subjects with mild to moderate gingivitis have been randomly divided into two groups: a treatment group that used the B-LETBs and a control group that used standard toothbrushes. Indices of plaque, gingival bleeding, and inflammation have been evaluated. A significant improvement of all dental indices in comparison with the baseline (by 59%, 66%, and 82% for plaque, gingival bleeding, and inflammation, respectively) has been found. The treatment group has demonstrated up to 50% improvement relative to the control group. We have proposed the B-LETBs to serve for prevention of gingivitis or as an alternative to conventional antibiotic treatment of this disease due to their effectiveness and the absence of drug side effects and bacterial resistance.

Adjunctive dental therapy via tooth plaque reduction and gingivitis treatment by blue light-emitting diodes tooth brushing.

PubMed

Genina, Elina A; Titorenko, Vladimir A; Belikov, Andrey V; Bashkatov, Alexey N; Tuchin, Valery V

2015-01-01

The efficacy of blue light-emitting toothbrushes (B-LETBs) (405 to 420 nm, power density 2  mW/cm(2)) for reduction of dental plaques and gingival inflammation has been evaluated. Microbiological study has shown the multifactor therapeutic action of the B-LETBs on oral pathological microflora: in addition to partial mechanical removal of bacteria, photodynamic action suppresses them up to 97.5%. In the pilot clinical studies, subjects with mild to moderate gingivitis have been randomly divided into two groups: a treatment group that used the B-LETBs and a control group that used standard toothbrushes. Indices of plaque, gingival bleeding, and inflammation have been evaluated. A significant improvement of all dental indices in comparison with the baseline (by 59%, 66%, and 82% for plaque, gingival bleeding, and inflammation, respectively) has been found. The treatment group has demonstrated up to 50% improvement relative to the control group. We have proposed the B-LETBs to serve for prevention of gingivitis or as an alternative to conventional antibiotic treatment of this disease due to their effectiveness and the absence of drug side effects and bacterial resistance.

Wing download reduction using vortex trapping plates

NASA Technical Reports Server (NTRS)

Light, Jeffrey S.; Stremel, Paul M.; Bilanin, Alan J.

1994-01-01

A download reduction technique using spanwise plates on the upper and lower wing surfaces has been examined. Experimental and analytical techniques were used to determine the download reduction obtained using this technique. Simple two-dimensional wind tunnel testing confirmed the validity of the technique for reducing two-dimensional airfoil drag. Computations using a two-dimensional Navier-Stokes analysis provided insight into the mechanism causing the drag reduction. Finally, the download reduction technique was tested using a rotor and wing to determine the benefits for a semispan configuration representative of a tilt rotor aircraft.

Leveraging Commercially Issued Multi-Factor Identification Credentials

NASA Technical Reports Server (NTRS)

Baldridge, Tim W.

2010-01-01

This slide presentation reviews the Identity, Credential and Access Management (ICAM) system. This system is a complete system of identity management, access to desktops and applications, use of smartcards, and building access throughout NASA.

Fukunaga-Koontz transform based dimensionality reduction for hyperspectral imagery

NASA Astrophysics Data System (ADS)

Ochilov, S.; Alam, M. S.; Bal, A.

2006-05-01

Fukunaga-Koontz Transform based technique offers some attractive properties for desired class oriented dimensionality reduction in hyperspectral imagery. In FKT, feature selection is performed by transforming into a new space where feature classes have complimentary eigenvectors. Dimensionality reduction technique based on these complimentary eigenvector analysis can be described under two classes, desired class and background clutter, such that each basis function best represent one class while carrying the least amount of information from the second class. By selecting a few eigenvectors which are most relevant to desired class, one can reduce the dimension of hyperspectral cube. Since the FKT based technique reduces data size, it provides significant advantages for near real time detection applications in hyperspectral imagery. Furthermore, the eigenvector selection approach significantly reduces computation burden via the dimensionality reduction processes. The performance of the proposed dimensionality reduction algorithm has been tested using real-world hyperspectral dataset.

A Fourier dimensionality reduction model for big data interferometric imaging

NASA Astrophysics Data System (ADS)

Vijay Kartik, S.; Carrillo, Rafael E.; Thiran, Jean-Philippe; Wiaux, Yves

2017-06-01

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging methods to the big data setting of the next-generation telescopes. This article sheds new light on dimensionality reduction from the perspective of the compressed sensing theory and studies its interplay with imaging algorithms designed in the context of convex optimization. We propose a post-gridding linear data embedding to the space spanned by the left singular vectors of the measurement operator, providing a dimensionality reduction below image size. This embedding preserves the null space of the measurement operator and hence its sampling properties are also preserved in light of the compressed sensing theory. We show that this can be approximated by first computing the dirty image and then applying a weighted subsampled discrete Fourier transform to obtain the final reduced data vector. This Fourier dimensionality reduction model ensures a fast implementation of the full measurement operator, essential for any iterative image reconstruction method. The proposed reduction also preserves the independent and identically distributed Gaussian properties of the original measurement noise. For convex optimization-based imaging algorithms, this is key to justify the use of the standard ℓ2-norm as the data fidelity term. Our simulations confirm that this dimensionality reduction approach can be leveraged by convex optimization algorithms with no loss in imaging quality relative to reconstructing the image from the complete visibility data set. Reconstruction results in simulation settings with no direction dependent effects or calibration errors show promising performance of the proposed dimensionality reduction. Further tests on real data are planned as an extension of the current work. matlab code implementing the proposed reduction method is available on GitHub.

A Corresponding Lie Algebra of a Reductive homogeneous Group and Its Applications

NASA Astrophysics Data System (ADS)

Zhang, Yu-Feng; Wu, Li-Xin; Rui, Wen-Juan

2015-05-01

With the help of a Lie algebra of a reductive homogeneous space G/K, where G is a Lie group and K is a resulting isotropy group, we introduce a Lax pair for which an expanding (2+1)-dimensional integrable hierarchy is obtained by applying the binormial-residue representation (BRR) method, whose Hamiltonian structure is derived from the trace identity for deducing (2+1)-dimensional integrable hierarchies, which was proposed by Tu, et al. We further consider some reductions of the expanding integrable hierarchy obtained in the paper. The first reduction is just right the (2+1)-dimensional AKNS hierarchy, the second-type reduction reveals an integrable coupling of the (2+1)-dimensional AKNS equation (also called the Davey-Stewartson hierarchy), a kind of (2+1)-dimensional Schrödinger equation, which was once reobtained by Tu, Feng and Zhang. It is interesting that a new (2+1)-dimensional integrable nonlinear coupled equation is generated from the reduction of the part of the (2+1)-dimensional integrable coupling, which is further reduced to the standard (2+1)-dimensional diffusion equation along with a parameter. In addition, the well-known (1+1)-dimensional AKNS hierarchy, the (1+1)-dimensional nonlinear Schrödinger equation are all special cases of the (2+1)-dimensional expanding integrable hierarchy. Finally, we discuss a few discrete difference equations of the diffusion equation whose stabilities are analyzed by making use of the von Neumann condition and the Fourier method. Some numerical solutions of a special stationary initial value problem of the (2+1)-dimensional diffusion equation are obtained and the resulting convergence and estimation formula are investigated. Supported by the Innovation Team of Jiangsu Province hosted by China University of Mining and Technology (2014), the National Natural Science Foundation of China under Grant No. 11371361, the Fundamental Research Funds for the Central Universities (2013XK03), and the Natural Science Foundation of Shandong Province under Grant No. ZR2013AL016

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors.

PubMed

Liu, Xueqin; Li, Ning; Yuan, Shuai; Xu, Ning; Shi, Wenqin; Chen, Weibin

2015-12-15

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. Copyright © 2015 Elsevier B.V. All rights reserved.

Applying the methodology of Design of Experiments to stability studies: a Partial Least Squares approach for evaluation of drug stability.

PubMed

Jordan, Nika; Zakrajšek, Jure; Bohanec, Simona; Roškar, Robert; Grabnar, Iztok

2018-05-01

The aim of the present research is to show that the methodology of Design of Experiments can be applied to stability data evaluation, as they can be seen as multi-factor and multi-level experimental designs. Linear regression analysis is usually an approach for analyzing stability data, but multivariate statistical methods could also be used to assess drug stability during the development phase. Data from a stability study for a pharmaceutical product with hydrochlorothiazide (HCTZ) as an unstable drug substance was used as a case example in this paper. The design space of the stability study was modeled using Umetrics MODDE 10.1 software. We showed that a Partial Least Squares model could be used for a multi-dimensional presentation of all data generated in a stability study and for determination of the relationship among factors that influence drug stability. It might also be used for stability predictions and potentially for the optimization of the extent of stability testing needed to determine shelf life and storage conditions, which would be time and cost-effective for the pharmaceutical industry.

Prediction of passenger ride quality in a multifactor environment

NASA Technical Reports Server (NTRS)

Dempsey, T. K.; Leatherwood, J. D.

1976-01-01

A model being developed, permits the understanding and prediction of passenger discomfort in a multifactor environment with particular emphasis upon combined noise and vibration. The model has general applicability to diverse transportation systems and provides a means of developing ride quality design criteria as well as a diagnostic tool for identifying the vibration and/or noise stimuli causing discomfort. Presented are: (1) a review of the basic theoretical and mathematical computations associated with the model, (2) a discussion of methodological and criteria investigations for both the vertical and roll axes of vibration, (3) a description of within-axis masking of discomfort responses for the vertical axis, thereby allowing prediction of the total discomfort due to any random vertical vibration, (4) a discussion of initial data on between-axis masking, and (5) discussion of a study directed towards extension of the vibration model to the more general case of predicting ride quality in the combined noise and vibration environments.

An overview of a multifactor-system theory of personality and individual differences: III. Life span development and the heredity-environment issue.

PubMed

Powell, A; Royce, J R

1981-12-01

In Part III of this three-part series on multifactor-system theory, multivariate, life-span development is approached from the standpoint of a quantitative and qualitative analysis of the ontogenesis of factors in each of the six systems. The pattern of quantitative development (described via the Gompertz equation and three developmental parameters) involves growth, stability, and decline, and qualitative development involves changes in the organization of factors (e.g., factor differentiation and convergence). Hereditary and environmental sources of variation are analyzed via the factor gene model and the concept of heredity-dominant factors, and the factor-learning model and environment-dominant factors. It is hypothesized that the sensory and motor systems are heredity dominant, that the style and value systems are environment dominant, and that the cognitive and affective systems are partially heredity dominant.

Management of suicidal and self-harming behaviors in prisons: systematic literature review of evidence-based activities.

PubMed

Barker, Emma; Kõlves, Kairi; De Leo, Diego

2014-01-01

The purpose of this study was to systematically analyze existing literature testing the effectiveness of programs involving the management of suicidal and self-harming behaviors in prisons. For the study, 545 English-language articles published in peer reviewed journals were retrieved using the terms "suicid*," "prevent*," "prison," or "correctional facility" in SCOPUS, MEDLINE, PROQUEST, and Web of Knowledge. In total, 12 articles were relevant, with 6 involving multi-factored suicide prevention programs, and 2 involving peer focused programs. Others included changes to the referral and care of suicidal inmates, staff training, legislation changes, and a suicide prevention program for inmates with Borderline Personality Disorder. Multi-factored suicide prevention programs appear most effective in the prison environment. Using trained inmates to provide social support to suicidal inmates is promising. Staff attitudes toward training programs were generally positive.

Entropy measure of credit risk in highly correlated markets

NASA Astrophysics Data System (ADS)

Gottschalk, Sylvia

2017-07-01

We compare the single and multi-factor structural models of corporate default by calculating the Jeffreys-Kullback-Leibler divergence between their predicted default probabilities when asset correlations are either high or low. Single-factor structural models assume that the stochastic process driving the value of a firm is independent of that of other companies. A multi-factor structural model, on the contrary, is built on the assumption that a single firm's value follows a stochastic process correlated with that of other companies. Our main results show that the divergence between the two models increases in highly correlated, volatile, and large markets, but that it is closer to zero in small markets, when asset correlations are low and firms are highly leveraged. These findings suggest that during periods of financial instability, when asset volatility and correlations increase, one of the models misreports actual default risk.

The Research on Tunnel Surrounding Rock Classification Based on Geological Radar and Probability Theory

NASA Astrophysics Data System (ADS)

Xiao Yong, Zhao; Xin, Ji Yong; Shuang Ying, Zuo

2018-03-01

In order to effectively classify the surrounding rock types of tunnels, a multi-factor tunnel surrounding rock classification method based on GPR and probability theory is proposed. Geological radar was used to identify the geology of the surrounding rock in front of the face and to evaluate the quality of the rock face. According to the previous survey data, the rock uniaxial compressive strength, integrity index, fissure and groundwater were selected for classification. The related theories combine them into a multi-factor classification method, and divide the surrounding rocks according to the great probability. Using this method to classify the surrounding rock of the Ma’anshan tunnel, the surrounding rock types obtained are basically the same as those of the actual surrounding rock, which proves that this method is a simple, efficient and practical rock classification method, which can be used for tunnel construction.

Spectroscopically Enhanced Method and System for Multi-Factor Biometric Authentication

NASA Astrophysics Data System (ADS)

Pishva, Davar

This paper proposes a spectroscopic method and system for preventing spoofing of biometric authentication. One of its focus is to enhance biometrics authentication with a spectroscopic method in a multifactor manner such that a person's unique ‘spectral signatures’ or ‘spectral factors’ are recorded and compared in addition to a non-spectroscopic biometric signature to reduce the likelihood of imposter getting authenticated. By using the ‘spectral factors’ extracted from reflectance spectra of real fingers and employing cluster analysis, it shows how the authentic fingerprint image presented by a real finger can be distinguished from an authentic fingerprint image embossed on an artificial finger, or molded on a fingertip cover worn by an imposter. This paper also shows how to augment two widely used biometrics systems (fingerprint and iris recognition devices) with spectral biometrics capabilities in a practical manner and without creating much overhead or inconveniencing their users.

Coupled dimensionality reduction and classification for supervised and semi-supervised multilabel learning

PubMed Central

Gönen, Mehmet

2014-01-01

Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F1, and micro F1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks. PMID:24532862

Coupled dimensionality reduction and classification for supervised and semi-supervised multilabel learning.

PubMed

Gönen, Mehmet

2014-03-01

Coupled training of dimensionality reduction and classification is proposed previously to improve the prediction performance for single-label problems. Following this line of research, in this paper, we first introduce a novel Bayesian method that combines linear dimensionality reduction with linear binary classification for supervised multilabel learning and present a deterministic variational approximation algorithm to learn the proposed probabilistic model. We then extend the proposed method to find intrinsic dimensionality of the projected subspace using automatic relevance determination and to handle semi-supervised learning using a low-density assumption. We perform supervised learning experiments on four benchmark multilabel learning data sets by comparing our method with baseline linear dimensionality reduction algorithms. These experiments show that the proposed approach achieves good performance values in terms of hamming loss, average AUC, macro F 1 , and micro F 1 on held-out test data. The low-dimensional embeddings obtained by our method are also very useful for exploratory data analysis. We also show the effectiveness of our approach in finding intrinsic subspace dimensionality and semi-supervised learning tasks.

Metric dimensional reduction at singularities with implications to Quantum Gravity

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

Stoica, Ovidiu Cristinel, E-mail: holotronix@gmail.com

2014-08-15

A series of old and recent theoretical observations suggests that the quantization of gravity would be feasible, and some problems of Quantum Field Theory would go away if, somehow, the spacetime would undergo a dimensional reduction at high energy scales. But an identification of the deep mechanism causing this dimensional reduction would still be desirable. The main contribution of this article is to show that dimensional reduction effects are due to General Relativity at singularities, and do not need to be postulated ad-hoc. Recent advances in understanding the geometry of singularities do not require modification of General Relativity, being justmore » non-singular extensions of its mathematics to the limit cases. They turn out to work fine for some known types of cosmological singularities (black holes and FLRW Big-Bang), allowing a choice of the fundamental geometric invariants and physical quantities which remain regular. The resulting equations are equivalent to the standard ones outside the singularities. One consequence of this mathematical approach to the singularities in General Relativity is a special, (geo)metric type of dimensional reduction: at singularities, the metric tensor becomes degenerate in certain spacetime directions, and some properties of the fields become independent of those directions. Effectively, it is like one or more dimensions of spacetime just vanish at singularities. This suggests that it is worth exploring the possibility that the geometry of singularities leads naturally to the spontaneous dimensional reduction needed by Quantum Gravity. - Highlights: • The singularities we introduce are described by finite geometric/physical objects. • Our singularities are accompanied by dimensional reduction effects. • They affect the metric, the measure, the topology, the gravitational DOF (Weyl = 0). • Effects proposed in other approaches to Quantum Gravity are obtained naturally. • The geometric dimensional reduction obtained opens new ways for Quantum Gravity.« less

A sparse grid based method for generative dimensionality reduction of high-dimensional data

NASA Astrophysics Data System (ADS)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Transformational, transactional, and passive-avoidant leadership characteristics of a surgical resident cohort: analysis using the multifactor leadership questionnaire and implications for improving surgical education curriculums.

PubMed

Horwitz, Irwin B; Horwitz, Sujin K; Daram, Pallavi; Brandt, Mary L; Brunicardi, F Charles; Awad, Samir S

2008-07-01

The need for leadership training has become recognized as being highly important to improving medical care, and should be included in surgical resident education curriculums. Surgical residents (n = 65) completed the 5x-short version of the Multifactor Leadership Questionnaire as a means of identifying leadership areas most in need of training among medical residents. The leadership styles of the residents were measured on 12 leadership scales. Comparisons between gender and postgraduate year (PGY) and comparisons to national norms were conducted. Of 12 leadership scales, the residents as a whole had significantly higher management by exception active and passive scores than those of the national norm (t = 6.6, P < 0.01, t = 2.8, P < 0.01, respectively), and significantly lower individualized consideration scores than the norm (t = 2.7, P < 0.01). Only one score, management by exception active was statistically different and higher among males than females (t = 2.12, P < 0.05). PGY3-5 had significantly lower laissez-faire scores than PGY1-2 (t = 2.20, P < 0.05). Principal component analysis revealed two leadership factors with eigenvalues over 1.0. Hierarchical regression found evidence of an augmentation effect for transformational leadership. Areas of resident leadership strengths and weaknesses were identified. The Multifactor Leadership Questionnaire was demonstrated to be a valuable tool for identifying specific areas where leadership training would be most beneficial in the educational curriculum. The future use of this instrument could prove valuable to surgical education training programs.

Development and validation of a multifactor mindfulness scale in youth: The Comprehensive Inventory of Mindfulness Experiences-Adolescents (CHIME-A).

PubMed

Johnson, Catherine; Burke, Christine; Brinkman, Sally; Wade, Tracey

2017-03-01

Mindfulness-based interventions show consistent benefits in adults for a range of pathologies, but exploration of these approaches in youth is an emergent field, with limited measures of mindfulness for this population. This study aimed to investigate whether multifactor scales of mindfulness can be used in adolescents. A series of studies are presented assessing the performance of a recently developed adult measure, the Comprehensive Inventory of Mindfulness Experiences (CHIME) in 4 early adolescent samples. Study 1 was an investigation of how well the full adult measure (37 items) was understood by youth (N = 292). Study 2 piloted a revision of items in child friendly language with a small group (N = 48). The refined questionnaire for adolescents (CHIME-A) was then tested in Study 3 in a larger sample (N = 461) and subjected to exploratory factor analysis and a range of external validity measures. Study 4 was a confirmatory factor analysis in a new sample (N = 498) with additional external validity measures. Study 5 tested temporal stability (N = 120). Results supported an 8-factor 25-item measure of mindfulness in adolescents, with excellent model fit indices and sound internal consistency for the 8 subscales. Although the CFA supported an overarching factor, internal reliability of a combined total score was poor. The development of a multifactor measure represents a first step toward testing developmental models of mindfulness in young people. This in turn will aid construction of evidence based interventions that are not simply downward derivations of adult mindfulness programs. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Confounding Problems in Multifactor AOV When Using Several Organismic Variables of Limited Reliability

ERIC Educational Resources Information Center

Games, Paul A.

1975-01-01

A brief introduction is presented on how multiple regression and linear model techniques can handle data analysis situations that most educators and psychologists think of as appropriate for analysis of variance. (Author/BJG)

Interactions between above- and belowground organisms modified in climate change experiments

NASA Astrophysics Data System (ADS)

Stevnbak, Karen; Scherber, Christoph; Gladbach, David J.; Beier, Claus; Mikkelsen, Teis N.; Christensen, Søren

2012-11-01

Climate change has been shown to affect ecosystem process rates and community composition, with direct and indirect effects on belowground food webs. In particular, altered rates of herbivory under future climate can be expected to influence above-belowground interactions. Here, we use a multifactor, field-scale climate change experiment and independently manipulate atmospheric CO2 concentration, air and soil temperature and drought in all combinations since 2005. We show that changes in these factors modify the interaction between above- and belowground organisms. We use an insect herbivore to experimentally increase aboveground herbivory in grass phytometers exposed to all eight combinations of climate change factors for three years. Aboveground herbivory increased the abundance of belowground protozoans, microbial growth and microbial nitrogen availability. Increased CO2 modified these links through a reduction in herbivory and cascading effects through the soil food web. Interactions between CO2, drought and warming can affect belowground protozoan abundance. Our findings imply that climate change affects aboveground-belowground interactions through changes in nutrient availability.

[The clinical significance of hepcidin detection in the patients with anemia and rheumatoid arthritis].

PubMed

Galushko, E A

2014-01-01

The prevalence of anemia in patients with rheumatoid arthritis (RA) varies from 30 to 70%. 25% of the cases are diagnosed within 1 year after onset of the disease. On the whole, anemia in RA is described as anemia of a chronic disease (ACD). Pathogenesis ofACD is a multifactor process underlain by an immune mechanism: cytokines and cells ofthe reticuloendothelial system cause changes in iron homeostasis, proliferation of erythroid precursors, erythropoietin production and lifespan of erythrocytes. The key pathogenetic factor is disordered iron metabolism. IL-6 increasing hepatic production acute-phase protein (hepcidin) is the most important cytokine involved in ACD pathogenesis. Hence the necessity to measure its serum level for differential diagnostics of anemic syndrome in patients with RA and the choice of effective basal therapy. Recent data on the therapeutic potency of tocilizumab (IL-6 receptor inhibitor) demonstrate not its safety and sustainable beneficial clinical effect in combination with the favourable action on hemoglobin profile and reduction offatigue.

Connecting to HPC Systems | High-Performance Computing | NREL

Science.gov Websites

one of the following methods, which use multi-factor authentication. First, you will need to set up If you just need access to a command line on an HPC system, use one of the following methods

A trace ratio maximization approach to multiple kernel-based dimensionality reduction.

PubMed

Jiang, Wenhao; Chung, Fu-lai

2014-01-01

Most dimensionality reduction techniques are based on one metric or one kernel, hence it is necessary to select an appropriate kernel for kernel-based dimensionality reduction. Multiple kernel learning for dimensionality reduction (MKL-DR) has been recently proposed to learn a kernel from a set of base kernels which are seen as different descriptions of data. As MKL-DR does not involve regularization, it might be ill-posed under some conditions and consequently its applications are hindered. This paper proposes a multiple kernel learning framework for dimensionality reduction based on regularized trace ratio, termed as MKL-TR. Our method aims at learning a transformation into a space of lower dimension and a corresponding kernel from the given base kernels among which some may not be suitable for the given data. The solutions for the proposed framework can be found based on trace ratio maximization. The experimental results demonstrate its effectiveness in benchmark datasets, which include text, image and sound datasets, for supervised, unsupervised as well as semi-supervised settings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

PubMed Central

Cowley, Benjamin R.; Doiron, Brent; Kohn, Adam

2016-01-01

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure. PMID:27926936

Genetic variants of JNK and p38α pathways and risk of non-small cell lung cancer in an Eastern Chinese population.

PubMed

Jia, Ming; Zhu, Meiling; Zhou, Fei; Wang, Mengyun; Sun, Menghong; Yang, Yajun; Wang, Xiaofeng; Wang, Jiucun; Jin, Li; Xiang, Jiaqing; Zhang, Yawei; Chang, Jianhua; Wei, Qingyi

2017-02-15

The JNK and p38α pathways play an important role in carcinogenesis. Therefore, we hypothesize that single nucleotide polymorphisms (SNPs) of genes involved in these pathways are associated with risk of lung cancer. We first selected and genotyped 11 independent SNPs of the JNK and p38α pathway-related genes in a discovery set of 1,002 non-small cell lung cancer (NSCLC) cases and 1,025 cancer-free controls of Eastern Chinese. Then, we validated those significant SNPs in a replication set of 1,333 NSCLC cases and 1,339 cancer-free controls of Eastern Chinese. Multifactor dimensionality reduction (MDR) and classification and regression tree (CART) analyses were used to identify interactions between significant SNPs and other covariates. In both discovery and replication as well as their pooled analysis, carriers of GADD45G rs8252T variant genotypes had a significantly lower risk of NSCLC (adjusted OR = 0.81 and 0.79, 95% CI = 0.72-0.92 and 0.64-0.99 and p = 0.001 and 0.040 for dominant and recessive genetic models, respectively) and carriers of MAP2K7 rs3679T variant genotypes had an increased risk of NSCLC (adjusted OR = 1.19 and 1.29, 95% CI = 1.05-1.34 and 1.09-1.54 and p = 0.005 and 0.004 for dominant and recessive genetic models, respectively). Furthermore, rs8252 variant CT/TT carriers showed significantly higher levels of GADD45G mRNA expression than CC carriers in the target tissues. We observed some evidence of interactions between rs8252 genotypes and sex in NSCLC risk. These results indicate that GADD45G rs8252 and MAP2K7 rs3679 SNPs may be susceptibility biomarkers for NSCLC in Eastern Chinese populations. © 2016 UICC.

Role of Sequence Variations in AhR Gene Towards Modulating Smoking Induced Lung Cancer Susceptibility in North Indian Population: A Multiple Interaction Analysis.

PubMed

Budhwar, Sneha; Bahl, Charu; Sharma, Siddharth; Singh, Navneet; Behera, Digambar

2018-05-01

AhR, a ubiquitously expressed ligand-activated transcription factor, upon its encounter with the foreign ligands activates the transcriptional machinery of genes encoding for bio-transformation enzymes like CYP1A1 hence, mediating the metabolism of Poly aromatic hydrocarbons and nitrosamines which account for the maximally found carcinogen in cigarette smoke. Polymorphic variants of AhR play a significant role and are held responsible for disposing the individuals with greater chances of acquiring lung cancer. To study the role of AhR variants (rs2282885, rs10250822, rs7811989, rs2066853) in affect-ing lung cancer susceptibility. 297 cases and 320 controls have been genotyped using PCR-RFLP technique. In order to find out the association, unconditional logistic regression approach was used. To analyze high order in-teractions Multifactor Dimensionality Reduction and Classification and regression tree was used. Subjects carrying the variant genotype for AhR rs7811989 showed a two-fold risk (p=0.007) and a marginal risk was also seen in case of individuals carrying either single or double copy of suscep-tible allele for rs102550822 (p=0.02). Whereas the variant allele for rs2066853 showcased a strong pro-tective effect (p=0.003). SQCC individuals with mutant genotype of rs2066853 also exhibited a protec-tive effect towards lung cancer (OR=0.30, p=0.0013). The association of rs7811989 mutant genotype and rs10250822 mutant genotype was evident especially in smokers as compared to non-smokers. AhR rs2066853 showed a decreased risk in smokers with mutant genotype (p=0.002). MDR approach gave the best interaction model of AhR rs2066853 and smoking (CVC=10/10, prediction error=0.42). AhR polymorphic variations can significantly contribute towards lung cancer predisposi-tion.

Contribution of susceptibility locus at HLA class I region and environmental factors to occurrence of nasopharyngeal cancer in Northeast India.

PubMed

Lakhanpal, Meena; Singh, Laishram Chandreshwor; Rahman, Tashnin; Sharma, Jagnnath; Singh, M Madhumangal; Kataki, Amal Chandra; Verma, Saurabh; Chauhan, Pradeep Singh; Singh, Y Mohan; Wajid, Saima; Kapur, Sujala; Saxena, Sunita

2015-04-01

High incidence of nasopharyngeal carcinoma (NPC) has been reported from China, Southeast Asia and Northeast (NE) region of India. Populations at geographic regions having higher incidence of NPC display human leukocyte antigen (HLA) distribution patterns different from areas having low incidence. The current study has investigated the contribution of environmental risk factors and ethnic variation of microsatellite markers in HLA region for the high incidence of NPC in NE India. Genotyping of HLA region using 33 microsatellite markers by fragment length analysis was done in 220 study subjects (120 NPC patients and 100 healthy controls). Association analysis showed two adjacent microsatellite markers HL003 (allele 121) and D6S2704 (allele 218) in the HLA class I region having association with high risk of NPC while allele 127 of HL003 and allele 255 of D6S2678 conferred a protective effect. The environmental factors mainly use of firewood (odds ratio (OR) = 3.797385, confidence interval (CI) = 1.97-7.30, P < 0), living in mud house (OR = 3.46, CI = 1.19-10.08, P = 0.022) and consumption of alcohol (OR = 2.11, CI = 1.02-4.37, P = 0.043) were found as major risk factors for NPC. Higher-order interaction showed combination of smoked food consumption and firewood use for cooking in multifactor dimensionality reduction (MDR) analysis and interaction of non-firewood users, non-ventilated houses and residence in mud houses in classification and regression tree (CART) analysis as the significant risk factors for NPC. Expression of Epstein-Barr virus (EBV) RNA was found in 92% (23/25) of NPC cases suggesting its significant role in NPC aetiopathogenesis. This study identified association of NPC with a susceptibility locus in the HLA class I region which has complex interaction with viral DNA and environmental factors.

The combined effects of the 5-HTTLPR and 5-HTR1A genes modulates the relationship between negative life events and major depressive disorder in a Chinese population.

PubMed

Zhang, Kerang; Xu, Qi; Xu, Yong; Yang, Hong; Luo, Jinxiu; Sun, Yan; Sun, Ning; Wang, Shan; Shen, Yan

2009-04-01

Serotonin transporter (5-HTT) and 5-HT receptor (5-HTR) involved in the neurotransmission of 5-HT may play an important role in the development of major depression disorder (MDD). Several lines of evidence suggested that the gene-environment interaction may confer susceptibility to depression. The aim of this study is to analyze the combined effect of four serotonin-related genes and two environmental factors on MDD in a Chinese population. This study recruited a total of 401 patients with MDD and 391 age- and gender-matched control subjects. They were all Chinese Han origin. Negative life events and objective social supports were assessed using standard rating scales. Six polymorphisms in the four serotonin-related genes (5-HTT, 5-HTR1A, 5-HTR1B and 5-HTR2A) were selected to detect. The analyses of the gene-environment interactions were performed by the Multifactor Dimensionality Reduction (MDR). Allelic associations between patients with MDD and controls were observed for the polymorphism of 5-HTTLPR and for rs6295 at the 5-HTR1A locus. The 5-HTTLPR polymorphism was associated with negative life events on MDD. A three-way interaction between the 5-HTTLPR polymorphism, rs6295 and negative life events on MDD was found in the individuals aged from 20 years to 29 years. In addition, the individuals carrying the L/L genotype of 5-HTTLPR could be susceptible to MDD when exposed to negative life events. The 5-HTTLPR polymorphism may modify the interaction between negative life events and MDD in the Chinese population. To our knowledge, this is the first report on the combined effect for the 5-HTTLPR polymorphism and 5-HTR1A genes on modifying the response to negative life events conferring susceptibility to MDD in the 20-29 year group.

Genome-wide search followed by replication reveals genetic interaction of CD80 and ALOX5AP associated with systemic lupus erythematosus in Asian populations.

PubMed

Zhang, Yan; Yang, Jing; Zhang, Jing; Sun, Liangdan; Hirankarn, Nattiya; Pan, Hai-Feng; Lau, Chak Sing; Chan, Tak Mao; Lee, Tsz Leung; Leung, Alexander Moon Ho; Mok, Chi Chiu; Zhang, Lu; Wang, Yongfei; Shen, Jiangshan Jane; Wong, Sik Nin; Lee, Ka Wing; Ho, Marco Hok Kung; Lee, Pamela Pui Wah; Chung, Brian Hon-Yin; Chong, Chun Yin; Wong, Raymond Woon Sing; Mok, Mo Yin; Wong, Wilfred Hing Sang; Tong, Kwok Lung; Tse, Niko Kei Chiu; Li, Xiang-Pei; Avihingsanon, Yingyos; Rianthavorn, Pornpimol; Deekajorndej, Thavatchai; Suphapeetiporn, Kanya; Shotelersuk, Vorasuk; Ying, Shirley King Yee; Fung, Samuel Ka Shun; Lai, Wai Ming; Wong, Chun-Ming; Ng, Irene Oi Lin; Garcia-Barcelo, Maria-Merce; Cherny, Stacey S; Cui, Yong; Sham, Pak Chung; Yang, Sen; Ye, Dong-Qing; Zhang, Xue-Jun; Lau, Yu Lung; Yang, Wanling

2016-05-01

Genetic interaction has been considered as a hallmark of the genetic architecture of systemic lupus erythematosus (SLE). Based on two independent genome-wide association studies (GWAS) on Chinese populations, we performed a genome-wide search for genetic interactions contributing to SLE susceptibility. The study involved a total of 1 659 cases and 3 398 controls in the discovery stage and 2 612 cases and 3 441 controls in three cohorts for replication. Logistic regression and multifactor dimensionality reduction were used to search for genetic interaction. Interaction of CD80 (rs2222631) and ALOX5AP (rs12876893) was found to be significantly associated with SLE (OR_int=1.16, P_int_all=7.7E-04 at false discovery rate<0.05). Single nuclear polymorphism rs2222631 was found associated with SLE with genome-wide significance (P_all=4.5E-08, OR=0.86) and is independent of rs6804441 in CD80, whose association was reported previously. Significant correlation was observed between expression of these two genes in healthy controls and SLE cases, together with differential expression of these genes between cases and controls, observed from individuals from the Hong Kong cohort. Genetic interactions between BLK (rs13277113) and DDX6 (rs4639966), and between TNFSF4 (rs844648) and PXK (rs6445975) were also observed in both GWAS data sets. Our study represents the first genome-wide evaluation of epistasis interactions on SLE and the findings suggest interactions and independent variants may help partially explain missing heritability for complex diseases. 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/

Epistatic interactions between thiopurine methyltransferase (TPMT) and inosine triphosphate pyrophosphatase (ITPA) variations determine 6-mercaptopurine toxicity in Indian children with acute lymphoblastic leukemia.

PubMed

Dorababu, Patchva; Nagesh, Narayana; Linga, Vijay Gandhi; Gundeti, Sadashivudu; Kutala, Vijay Kumar; Reddanna, Pallu; Digumarti, Raghunadharao

2012-04-01

To explore the role of genetic variants of thiopurine methyltransferase (TPMT) and inosine triphosphate pyrophosphatase (ITPA) in 6-mercaptopurine (6-MP)-induced toxicity in Indian children with acute lymphoblastic leukemia (ALL). Children with ALL receiving 6-MP in maintenance phase of treatment (n = 90) were enrolled in the study. Bidirectional sequencing of TPMT (whole gene) and ITPA (exon 2, exon 3, and intron 2) was undertaken, and correlation between genotype and 6-MP toxicity was assessed. Five variations were observed in TPMT, including two exonic variations, TPMT*12 (374 C > T) and TPMT*3C (719A > G), and three intronic, intron 3 (12356 C > T), intron 4 (16638 C > T), and TPMT rs2842949. Two exonic, ITPA exon -2 (94 C → A) and exon 3 of ITPA (138 G > A), and one intronic, ITPA intron 2 (A→C), variations were observed in ITPA. Multifactor dimensionality reduction analysis of all the genetic variants showed independent association of ITPA 94 C→A as well as synergic epistatic interactions, i.e., TPMT*12 × ITPA ex3, ITPA ex2 × TPMT*12 × ITPA ex3, and TPMT*3C × ITPA ex2 × TPMT*12 × ITPA ex3, in determining hematological toxicity. This is further substantiated by a multiple linear regression model, which showed moderate predictability of toxicity with these variants (area under the curve = 0.70, p = 0.004). Our results suggest that apart from the individual effect of ITPA 94 C→A, epistatic interactions between the variations of TPMT (*3C, *12) and ITPA (ex2, ex3) are associated with the 6-MP toxicity. Testing these variants facilitates tailoring of the 6-MP therapy in children with ALL.

Multilocus analyses of seven candidate genes suggest interacting pathways for obesity-related traits in Brazilian populations.

PubMed

Angeli, Cláudia B; Kimura, Lilian; Auricchio, Maria T; Vicente, João P; Mattevi, Vanessa S; Zembrzuski, Verônica M; Hutz, Mara H; Pereira, Alexandre C; Pereira, Tiago V; Mingroni-Netto, Regina C

2011-06-01

We investigated whether variants in major candidate genes for food intake and body weight regulation contribute to obesity-related traits under a multilocus perspective. We studied 375 Brazilian subjects from partially isolated African-derived populations (quilombos). Seven variants displaying conflicting results in previous reports and supposedly implicated in the susceptibility of obesity-related phenotypes were investigated: β2-adrenergic receptor (ADRB2) (Arg16Gly), insulin induced gene 2 (INSIG2) (rs7566605), leptin (LEP) (A19G), LEP receptor (LEPR) (Gln223Arg), perilipin (PLIN) (6209T > C), peroxisome proliferator-activated receptor-γ (PPARG) (Pro12Ala), and resistin (RETN) (-420 C > G). Regression models as well as generalized multifactor dimensionality reduction (GMDR) were employed to test the contribution of individual effects and higher-order interactions to BMI and waist-hip ratio (WHR) variation and risk of overweight/obesity. The best multilocus association signal identified in the quilombos was further examined in an independent sample of 334 Brazilian subjects of European ancestry. In quilombos, only the PPARG polymorphism displayed significant individual effects (WHR variation, P = 0.028). No association was observed either with the risk of overweight/obesity (BMI ≥ 25 kg/m2), risk of obesity alone (BMI ≥ 30 kg/m2) or BMI variation. However, GMDR analyses revealed an interaction between the LEPR and ADRB2 polymorphisms (P = 0.009) as well as a third-order effect involving the latter two variants plus INSIG2 (P = 0.034) with overweight/obesity. Assessment of the LEPR-ADRB2 interaction in the second sample indicated a marginally significant association (P = 0.0724), which was further verified to be limited to men (P = 0.0118). Together, our findings suggest evidence for a two-locus interaction between the LEPR Gln223Arg and ADRB2 Arg16Gly variants in the risk of overweight/obesity, and highlight further the importance of multilocus effects in the genetic component of obesity.

Interactions of central obesity with rs3918242 on risk of non-alcoholic fat liver disease: a preliminary case-control study.

PubMed

Wu, Pengbo; Hua, Yonglong; Tan, Shiyun; Li, Ming; Shu, Yongxiang; Fang, Guo

2015-01-01

NAFLD is a complex disease characterized by inflammation and insulin resistance which is determined by an interaction of genetics and environmental factors. MMP gene has been implicated in relation to inflammation and insulin resistance. The preliminary case-control study aimed to investigate the association between Matrix metalloproteinase (MMP)-9-1562C/T (rs3918242), MMP-2-1306C/T (rs243865) and risk of NAFLD and to further evaluate the interactions of central obesity with rs3918242 and rs243865. Two variants, rs3918242 and rs243865, were genotyped by polymerase chain reaction -restriction fragment length polymorphism. Gene-environment interactions on risk of NAFLD was preliminarily investigated by generalized multifactor dimensionality reduction (GMDR) and further confirmed by unconditional logistic regression methods. After adjusting for covariates, increased risk of NAFLD were observed in subjects carrying TT/CT genotypes in rs3918242 ((Adjust)OR=1.64, 95% CI: 1.24, 2.11, P=0.006). However, decreased risk of non-alcoholic fat liver disease was found when MMP-2 rs243865 (TT/CT) genotype carriers compared with CC carrier ((Adjust)OR=0.65, 95% CI: 0.47, 0.72, P=0.000).Interactions of central obesity with rs3918242 was preliminarily found by GMDR, with a maximum prediction accuracy (67.61%) and a maximum Cross-validation Consistency (10/10).The unconditional logistic regression method indicated central obesity-positive subject with genotype TT/CT had 4.54 times risk of NAFLD compared to central obesity-negative subjects with genotype CC (OR(add)(a)=4.54, 95% CI: 2.81, 7.21, P(add)(a)=0.000), which further confirmed the interactions. The results indicate that both rs3918242 and rs243865 is associated with risk of NAFLD. Furthermore, rs3918242 and central obesity have synergistic effects on risk of NAFLD.

Interleukin-10 family cytokines pathway: genetic variants and psoriasis.

PubMed

Galimova, E; Rätsep, R; Traks, T; Kingo, K; Escott-Price, V; Kõks, S

2017-06-01

Interleukin (IL)-10 family cytokines IL-10, IL-19, IL-20 and IL-24 have been implicated in autoimmune diseases and we have previously reported that genetic variants in the IL10 gene cluster were associated with psoriasis. To analyse the relationship between genetic polymorphisms in the IL10 gene cluster and psoriasis. This study also explores whether there are gene-gene interactions among these genetic polymorphisms. A total of 377 patients with psoriasis and 403 matched healthy controls were enrolled to carry out a case-control study for 48 single-nucleotide polymorphisms (SNPs) of the IL10 gene cluster. Genotyping for the SNPs was conducted on the Applied Biosystems 3730 DNA Analyzer using SNPlex ® technology. Generalized multifactor dimensionality reduction (GMDR) analysis was applied to discover a likely gene-gene interaction model among the SNPs. The results showed that the allele distributions of IL10 gene cluster SNPs are significantly different between the case and control groups. Carriers of the IL10 T allele (rs1554286) and the IL20 T allele (rs1400986) conferred protection from psoriasis [odds ratio (OR) = 0·63, corrected P-value (Pc) = 0·007; OR = 0·62, Pc = 0·038, respectively]. GMDR analysis displayed a significant gene-gene interaction between IL10 (rs1554286) and IL20 (rs1518108) variants. The strongest protective effect was found with the block 1 haplotype ACATA in the IL10 gene (Pc = 0·004). This study presents a novel finding that the combination of the two SNPs, IL10 (rs1554286) and IL20 (rs1518108), is associated with a reduced risk of psoriasis. Our results indicate that genetic variants of the immunomodulatory IL10 and IL20 genes may offer a protective effect in Europeans from Russia. Independent studies are required to verify the results and find a possible functional explanation. © 2017 British Association of Dermatologists.

Genetic polymorphisms in DNA double-strand break repair genes XRCC5, XRCC6 and susceptibility to hepatocellular carcinoma.

PubMed

Li, Rui; Yang, Yuan; An, Yu; Zhou, Yun; Liu, Yanhong; Yu, Qing; Lu, Daru; Wang, Hongyang; Jin, Li; Zhou, Weiping; Qian, Ji; Shugart, Yin Yao

2011-04-01

Environmental risk factors cause DNA damages. Imprecise DNA repair leads to chromosome aberrations, genome destabilization and hepatocarcinogenesis. Ku is a key DNA double-strand break repair protein. We hypothesized that the genetic variants in Ku subunits encoding genes, XRCC5/XRCC6, may contribute to hepatocellular carcinoma (HCC) susceptibility. We genotyped 13 common single nucleotide polymorphisms (SNPs) in XRCC5 and XRCC6 and evaluated their associations with HCC risk in 689 pathologically confirmed cases and 690 cancer-free controls from a Chinese population. We found that a significantly reduced risk for HCC was associated with XRCC5 rs16855458 [odds ratio (OR)=0.59; 95% confidence interval (CI)=0.43-0.81; CA+AA versus CC] and a significantly increased risk for HCC was associated with XRCC5 rs9288516 (OR=2.02; 95% CI=1.42-2.86; TA+AA versus TT) even after Bonferroni correction (Pcorrected=0.026 and 0.002, respectively). The effects of rs16855458 (OR=0.57; 95% CI=0.37-0.86, P=0.008) and rs9288516 (OR=1.86; 95% CI=1.19-2.90, P=0.007) were more significant in hepatitis B surface antigen-infected subjects than non-infected subjects. The haplotype-based analysis revealed that in XRCC5, AA in block 1 (OR=0.63; 95% CI=0.48-0.83) and CGGTT in block 2 (OR=0.52; 95% CI=0.39-0.69) were associated with decreased HCC risk (Pcorrected=0.013 and <0.001, respectively). The aforementioned two SNPs exhibited a significant cumulative risk effect (Ptrend<0.001). Additionally, potential interaction among XRCC5 rs9288516 and rs2267437, rs5751131 in XRCC6 was indicated by the multifactor dimensionality reduction analysis. In conclusion, XRCC5 variants may play a role in determining individual's HCC susceptibility, which warranted validation in larger studies.

Predictive models to assess risk of type 2 diabetes, hypertension and comorbidity: machine-learning algorithms and validation using national health data from Kuwait--a cohort study.

PubMed

Farran, Bassam; Channanath, Arshad Mohamed; Behbehani, Kazem; Thanaraj, Thangavel Alphonse

2013-05-14

We build classification models and risk assessment tools for diabetes, hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We model the increased proneness in diabetic patients to develop hypertension and vice versa. We ascertain the importance of ethnicity (and natives vs expatriate migrants) and of using regional data in risk assessment. Retrospective cohort study. Four machine-learning techniques were used: logistic regression, k-nearest neighbours (k-NN), multifactor dimensionality reduction and support vector machines. The study uses fivefold cross validation to obtain generalisation accuracies and errors. Kuwait Health Network (KHN) that integrates data from primary health centres and hospitals in Kuwait. 270 172 hospital visitors (of which, 89 858 are diabetic, 58 745 hypertensive and 30 522 comorbid) comprising Kuwaiti natives, Asian and Arab expatriates. Incident type 2 diabetes, hypertension and comorbidity. Classification accuracies of >85% (for diabetes) and >90% (for hypertension) are achieved using only simple non-laboratory-based parameters. Risk assessment tools based on k-NN classification models are able to assign 'high' risk to 75% of diabetic patients and to 94% of hypertensive patients. Only 5% of diabetic patients are seen assigned 'low' risk. Asian-specific models and assessments perform even better. Pathological conditions of diabetes in the general population or in hypertensive population and those of hypertension are modelled. Two-stage aggregate classification models and risk assessment tools, built combining both the component models on diabetes (or on hypertension), perform better than individual models. Data on diabetes, hypertension and comorbidity from the cosmopolitan State of Kuwait are available for the first time. This enabled us to apply four different case-control models to assess risks. These tools aid in the preliminary non-intrusive assessment of the population. Ethnicity is seen significant to the predictive models. Risk assessments need to be developed using regional data as we demonstrate the applicability of the American Diabetes Association online calculator on data from Kuwait.

Association between polymorphisms in renin-angiotensin system genes and primary ovarian insufficiency in Korean women.

PubMed

Jung, Yong Wook; Jeon, Young Joo; Park, Hye Mi; Lee, Bo Eun; Rah, Hyungchul; Lee, Woo Sik; Yoon, Tae Ki; Kim, Nam Keun

2013-05-01

The purpose of this study was to evaluate the relationship between angiotensin-converting enzyme (ACE; insertion/deletion), angiotensinogen (AGT M235T), and angiotensin II type 1 receptor (AT1R 1166A>C) and the prevalence of primary ovarian insufficiency (POI) in Korean women. A total of 133 women with POI and 238 controls were genotyped for polymorphic sites in each gene using polymerase chain reaction-restriction fragment length polymorphism analysis. ACE ID and ID + II variants occurred more frequently in women with POI than in controls (odds ratio [OR], 1.830; 95% CI, 1.040-3.221; P = 0.040; and OR, 1.797; 95% CI, 1.055-3.060; P = 0.031, respectively). The AT1R 1166AC genotype occurred more frequently in participants with POI than in controls (OR, 3.171; 95% CI, 1.562-6.436; P = 0.002). Comparing the combined genotype frequencies of ACE/AT1R revealed that the frequencies of ID/AA, ID/AC, and II/AC were higher in participants than in controls (OR, 1.916; 95% CI, 1.053-3.485; P = 0.043; OR, 3.544; 95% CI, 1.207-10.407; P = 0.036; and OR, 7.875; 95% CI, 2.224-27.881; P = 0.001, respectively). The TT/AC genotype for combined genotyping of AGT/AT1R was more frequently observed in the POI group than in the control group (OR, 3.472; 95% CI, 1.450-8.313; P = 0.006). In multifactor dimensionality reduction-based haplotype analysis, the I-T-C genotype of ACE/AGT/AT1R was a possible predisposing factor for POI (OR, 4.678; 95% CI, 1.721-12.717; P = 0.002). This study demonstrates that polymorphisms in the renin-angiotensin system are related to the prevalence of POI. Thus, these renin-angiotensin system genes may serve as a novel marker for predicting the development of POI.

Relationship of polymorphisms and haplotype in interleukin-16 and adiponectin gene with late-onset Alzheimer’s disease risk

PubMed Central

Yin, Honglei; Zhang, Yuzhen; Hua, Linlin; Li, Jinfeng; Zeng, Zhilei; Yang, Xiaopeng; Gong, Bin; Geng, Shuang; Liu, Yajun; Zhang, Hui; Liu, Yanqiu; Zhao, Jing; Wang, Yunliang

2017-01-01

Aims To investigate the impact of Interleukin-16 (IL- 16) and Adiponectin (ANP) gene single nucleotide polymorphisms (SNPs), gene- gene interactions and haplotype on late-onset Alzheimer’s disease (LOAD) risk. Methods Hardy-Weinberg equilibrium (HWE), haplotype and pairwise linkage disequilibrium (LD) analysis were investigated by using SNPstats (available online at http://bioinfo.iconcologia.net/SNPstats). Generalized multifactor dimensionality reduction (GMDR) was used to examine interaction among 4 SNPs, odds ratio (OR) and 95% confident interval (95%CI) were calculated by logistic regression model. Results LOAD risk was significantly higher in carriers of rs266729- G allele than those with CC genotype (CG+ GG versus CC), OR (95%CI) =1.61 (1.26-1.96), and higher in carriers of rs1501299- T allele, OR (95%CI) = 1.62 (1.32-2.12), lower in carriers of rs4072111- T allele, adjusted OR (95%CI) =0.65 (0.44-0.93). We also found a significant gene- gene interaction between rs266729 and rs4072111. Participants with CG or GG of rs266729 and CC of rs4072111 genotype have the highest LOAD risk, OR (95%CI) = 2.62 (1.64 -3.58). Haplotype containing the rs266729- G and rs1501299- T alleles were associated with increased LOAD risk, OR (95%CI)= 1.83 (1.32- 2.43), and haplotype containing the rs1131445- C and rs4072111- T alleles were associated with decreased LOAD risk, OR (95%CI)= 0.53 (0.18- 0.95). Conclusions We concluded that rs266729 and rs1501299 minor alleles were associated with increased LOAD risk, but rs4072111 minor allele was associated with decreased LOAD risk. We also found that interaction involving rs266729 and rs4072111, and haplotype combinations were associated with LOAD risk. PMID:29108295

Sex hormone pathway gene polymorphisms are associated with risk of advanced hepatitis C-related liver disease in males.

PubMed

White, Donna L; Liu, Yanhong; Garcia, Jose; El-Serag, Hashem B; Jiao, Li; Tsavachidis, Spiridon; Franco, Luis M; Lee, Ju-Seog; Tavakoli-Tabasi, Shahriar; Moore, David; Goldman, Radoslav; Kuzniarek, Jill; Ramsey, David J; Kanwal, Fasiha; Marcelli, Marco

2014-01-01

Males have excess advanced liver disease and cirrhosis risk including from chronic hepatitis C virus (HCV) infection though the reasons are unclear. To examine the role variants in genes involved in androgen and estrogen biosynthesis and metabolism play in HCV-related liver disease risk in males. We performed a cross-sectional study evaluating single nucleotide polymorphisms (SNPs) in 16 candidate genes involved in androgen and estrogen ligand and receptor synthesis and risk of advanced hepatic fibrosis (F3/F4-F4) and inflammation (A2/A3-A3). We calculated adjusted odds ratios (ORs) using logistic regression and used multifactor dimensionality reduction (MDR) analysis to assess for gene-environment interaction. Among 466 chronically HCV-infected males, 59% (n = 274) had advanced fibrosis and 54% (n = 252) had advanced inflammation. Nine of 472 SNPs were significantly associated with fibrosis risk; 4 in AKR1C3 (e.g., AKR1C3 rs2186174: ORadj = 2.04, 95% CI 1.38-3.02), 1 each in AKR1C2 and ESR1, and 1 in HSD17B6. Four SNPs were associated with inflammation risk, 2 in SRD5A1 (e.g., SRD5A1 rs248800: ORadj = 1.86, 95% CI 1.20-2.88) and 1 each in AKR1C2 and AKR1C3. MDR analysis identified a single AKR1C3 locus (rs2186174) as the best model for advanced fibrosis; while a 4-locus model with diabetes, AKR1C2 rs12414884, SRD5A1 rs6555406, and SRD5A1 rs248800 was best for inflammation. The consistency of our findings suggests AKR1C isoenzymes 2 and 3, and potentially SRD5A1, may play a role in progression of HCV-related liver disease in males. Future studies are needed to validate these findings and to assess if similar associations exist in females.

Association of Interleukin-10 gene promoter polymorphisms with obstructive sleep apnea.

PubMed

Özdaş, Sibel; Özdaş, Talih; Acar, Mustafa; Erbek, Selim S; Köseoğlu, Sabri; Göktürk, Gökhan; Izbirak, Afife

2016-05-01

Interleukin-10 (IL) is an anti-inflammatory cytokine that regulates normal sleep patterns, and recent studies have reported that it is a potential useful biomarker to identify presence and severity of sleep apnea syndrome (OSAS). Promoter polymorphisms of IL-10 gene have been associated with altered expression levels, which contributes to OSAS. The aim of this study was to determine the prevalence of -1082 G/A, -819 C/T, and -592 C/A promoter polymorphisms of IL-10 gene in individuals with OSAS and controls. An open-label study was performed in the Otorhinolaryngology and Sleep Disorders Outpatient Clinics. One hundred four cases with OSAS were included as the study group, and 78 individuals without OSAS were included as the controls. DNAs were extracted from peripheral blood leukocytes, and the sites that encompassed those polymorphisms were identified by DNA sequencing analyses. Data were analyzed with SNPStats and multifactor dimensionality reduction (MDR) software. The prevalence of OSAS was higher in males in the study group when compared to controls (P = 0.0003). The IL-10-1082 G/A, -819 C/T, and -592 C/A SNPs, and their minor alleles were associated with a significantly increased risk for OSAS compared to the controls (P ˂ 0.05 for all). Furthermore, ATA haplotype frequency was significantly higher in the study group compared to the control group, but the GCC haplotype frequency was lower (P = 0.0001 and P = 0.0001). As indicated in MDR analysis, combinations of IL-10 gene were associated with OSAS in single-, double-, and triple-locus analyses. The prevalences of the IL-10 gene promoter polymorphisms were different in OSAS patients and the controls in Turkish population. IL-10 gene polymorphisms may lead to altered inflammatory cascade, which might contribute to OSAS. Further studies on larger cohorts are needed to validate our findings.

Systematic study of association of four GABAergic genes: glutamic acid decarboxylase 1 gene, glutamic acid decarboxylase 2 gene, GABA(B) receptor 1 gene and GABA(A) receptor subunit beta2 gene, with schizophrenia using a universal DNA microarray.

PubMed

Zhao, Xu; Qin, Shengying; Shi, Yongyong; Zhang, Aiping; Zhang, Jing; Bian, Li; Wan, Chunling; Feng, Guoyin; Gu, Niufan; Zhang, Guangqi; He, Guang; He, Lin

2007-07-01

Several studies have suggested the dysfunction of the GABAergic system as a risk factor in the pathogenesis of schizophrenia. In the present study, case-control association analysis was conducted in four GABAergic genes: two glutamic acid decarboxylase genes (GAD1 and GAD2), a GABA(A) receptor subunit beta2 gene (GABRB2) and a GABA(B) receptor 1 gene (GABBR1). Using a universal DNA microarray procedure we genotyped a total of 20 SNPs on the above four genes in a study involving 292 patients and 286 controls of Chinese descent. Statistically significant differences were observed in the allelic frequencies of the rs187269C/T polymorphism in the GABRB2 gene (P=0.0450, chi(2)=12.40, OR=1.65) and the -292A/C polymorphism in the GAD1 gene (P=0.0450, chi(2)=14.64 OR=1.77). In addition, using an electrophoretic mobility shift assay (EMSA), we discovered differences in the U251 nuclear protein binding to oligonucleotides representing the -292 SNP on the GAD1 gene, which suggests that the -292C allele has reduced transcription factor binding efficiency compared with the 292A allele. Using the multifactor-dimensionality reduction method (MDR), we found that the interactions among the rs187269C/T polymorphism in the GABRB2 gene, the -243A/G polymorphism in the GAD2 gene and the 27379C/T and 661C/T polymorphisms in the GAD1 gene revealed a significant association with schizophrenia (P<0.001). These findings suggest that the GABRB2 and GAD1 genes alone and the combined effects of the polymorphisms in the four GABAergic system genes may confer susceptibility to the development of schizophrenia in the Chinese population.

Microarray-based SNP genotyping to identify genetic risk factors of triple-negative breast cancer (TNBC) in South Indian population.

PubMed

Aravind Kumar, M; Singh, Vineeta; Naushad, Shaik Mohammad; Shanker, Uday; Lakshmi Narasu, M

2018-05-01

In the view of aggressive nature of Triple-Negative Breast cancer (TNBC) due to the lack of receptors (ER, PR, HER2) and high incidence of drug resistance associated with it, a case-control association study was conducted to identify the contributing genetic risk factors for Triple-negative breast cancer (TNBC). A total of 30 TNBC patients and 50 age and gender-matched controls of Indian origin were screened for 9,00,000 SNP markers using microarray-based SNP genotyping approach. The initial PLINK association analysis (p < 0.01, MAF 0.14-0.44, OR 10-24) identified 28 non-synonymous SNPs and one stop gain mutation in the exonic region as possible determinants of TNBC risk. All the 29 SNPs were annotated using ANNOVAR. The interactions between these markers were evaluated using Multifactor dimensionality reduction (MDR) analysis. The interactions were in the following order: exm408776 > exm1278309 > rs316389 > rs1651654 > rs635538 > exm1292477. Recursive partitioning analysis (RPA) was performed to construct decision tree useful in predicting TNBC risk. As shown in this analysis, rs1651654 and exm585172 SNPs are found to be determinants of TNBC risk. Artificial neural network model was used to generate the Receiver operating characteristic curves (ROC), which showed high sensitivity and specificity (AUC-0.94) of these markers. To conclude, among the 9,00,000 SNPs tested, CCDC42 exm1292477, ANXA3 exm408776, SASH1 exm585172 are found to be the most significant genetic predicting factors for TNBC. The interactions among exm408776, exm1278309, rs316389, rs1651654, rs635538, exm1292477 SNPs inflate the risk for TNBC further. Targeted analysis of these SNPs and genes alone also will have similar clinical utility in predicting TNBC.

Lie symmetry analysis and reduction for exact solution of (2+1)-dimensional Bogoyavlensky-Konopelchenko equation by geometric approach

NASA Astrophysics Data System (ADS)

Ray, S. Saha

2018-04-01

In this paper, the symmetry analysis and similarity reduction of the (2+1)-dimensional Bogoyavlensky-Konopelchenko (B-K) equation are investigated by means of the geometric approach of an invariance group, which is equivalent to the classical Lie symmetry method. Using the extended Harrison and Estabrook’s differential forms approach, the infinitesimal generators for (2+1)-dimensional B-K equation are obtained. Firstly, the vector field associated with the Lie group of transformation is derived. Then the symmetry reduction and the corresponding explicit exact solution of (2+1)-dimensional B-K equation is obtained.

Outdoor Leaders' Emotional Intelligence and Transformational Leadership

ERIC Educational Resources Information Center

Hayashi, Aya; Ewert, Alan

2006-01-01

This study explored the concept of outdoor leadership from the perspectives of emotional intelligence and transformational leadership. Levels of emotional intelligence, multifactor leadership, outdoor experience, and social desirability were examined using 46 individuals designated as outdoor leaders. The results revealed a number of unique…

75 FR 67776 - Comment Request; Review of Productivity Statistics

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-03

... DEPARTMENT OF LABOR Bureau of Labor Statistics Comment Request; Review of Productivity Statistics... Statistics (BLS) is responsible for publishing measures of labor productivity and multifactor productivity..., Office of Productivity and Technology, Bureau of Labor Statistics, Room 2150, 2 Massachusetts Avenue, NE...

Regularized Embedded Multiple Kernel Dimensionality Reduction for Mine Signal Processing.

PubMed

Li, Shuang; Liu, Bing; Zhang, Chen

2016-01-01

Traditional multiple kernel dimensionality reduction models are generally based on graph embedding and manifold assumption. But such assumption might be invalid for some high-dimensional or sparse data due to the curse of dimensionality, which has a negative influence on the performance of multiple kernel learning. In addition, some models might be ill-posed if the rank of matrices in their objective functions was not high enough. To address these issues, we extend the traditional graph embedding framework and propose a novel regularized embedded multiple kernel dimensionality reduction method. Different from the conventional convex relaxation technique, the proposed algorithm directly takes advantage of a binary search and an alternative optimization scheme to obtain optimal solutions efficiently. The experimental results demonstrate the effectiveness of the proposed method for supervised, unsupervised, and semisupervised scenarios.

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

PubMed

Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Optimal dimensionality reduction of complex dynamics: The chess game as diffusion on a free-energy landscape

NASA Astrophysics Data System (ADS)

Krivov, Sergei V.

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game—the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Four-dimensional \\mathcal{N} = 2 supersymmetric theory with boundary as a two-dimensional complex Toda theory

NASA Astrophysics Data System (ADS)

Luo, Yuan; Tan, Meng-Chwan; Vasko, Petr; Zhao, Qin

2017-05-01

We perform a series of dimensional reductions of the 6d, \\mathcal{N} = (2, 0) SCFT on S 2 × Σ × I × S 1 down to 2d on Σ. The reductions are performed in three steps: (i) a reduction on S 1 (accompanied by a topological twist along Σ) leading to a supersymmetric Yang-Mills theory on S 2 × Σ × I, (ii) a further reduction on S 2 resulting in a complex Chern-Simons theory defined on Σ × I, with the real part of the complex Chern-Simons level being zero, and the imaginary part being proportional to the ratio of the radii of S 2 and S 1, and (iii) a final reduction to the boundary modes of complex Chern-Simons theory with the Nahm pole boundary condition at both ends of the interval I, which gives rise to a complex Toda CFT on the Riemann surface Σ. As the reduction of the 6d theory on Σ would give rise to an \\mathcal{N} = 2 supersymmetric theory on S 2 × I × S 1, our results imply a 4d-2d duality between four-dimensional \\mathcal{N} = 2 supersymmetric theory with boundary and two-dimensional complex Toda theory.

You Have What? Personality! Traits That Predict Leadership Styles for Elementary Administrators

ERIC Educational Resources Information Center

Garcia, Melinda

2013-01-01

This research explored relationships between followers' perceptions of elementary school principals' Big Five Personality Traits, using the "International Personality Item Pool" (IPIP) (Goldberg, 1999), and principals' Leadership Styles, using the "Multi-factor Leadership Questionnaire" (MLQ) (Bass & Avolio, 2004). A sample…

Understanding the Supplemental Instruction Leader

ERIC Educational Resources Information Center

James, Adrian; Moore, Lori

2018-01-01

This article explored the learning styles and leadership styles of Supplemental Instruction (SI) leaders at Texas A&M University, and the impact of those preferences on recurring attendance to their sessions. The Learning Style Inventory, the Multifactor Leadership Questionnaire, and a demographic instrument were administered to SI leaders…

Factorial Design: An Eight Factor Experiment Using Paper Helicopters

NASA Technical Reports Server (NTRS)

Kozma, Michael

1996-01-01

The goal of this paper is to present the analysis of the multi-factor experiment (factorial design) conducted in EG490, Junior Design at Loyola College in Maryland. The discussion of this paper concludes the experimental analysis and ties the individual class papers together.

The Multiple Component Alternative for Gifted Education.

ERIC Educational Resources Information Center

Swassing, Ray

1984-01-01

The Multiple Component Model (MCM) of gifted education includes instruction which may overlap in literature, history, art, enrichment, languages, science, physics, math, music, and dance. The model rests on multifactored identification and requires systematic development and selection of components with ongoing feedback and evaluation. (CL)

Nonlinear dimensionality reduction methods for synthetic biology biobricks' visualization.

PubMed

Yang, Jiaoyun; Wang, Haipeng; Ding, Huitong; An, Ning; Alterovitz, Gil

2017-01-19

Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of biobricks are tested. The visualization graphs illustrate discriminated biobricks and inappropriately labeled biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of biobricks could be discriminated and inappropriately labeled biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases' quality, and make biobricks selection.

On the reduction of 4d $$ \\mathcal{N}=1 $$ theories on $$ {\\mathbb{S}}^2 $$

DOE PAGES

Gadde, Abhijit; Razamat, Shlomo S.; Willett, Brian

2015-11-24

Here, we discuss reductions of generalmore » $$ \\mathcal{N}=1 $$ four dimensional gauge theories on $$ {\\mathbb{S}}^2 $$. The effective two dimensional theory one obtains depends on the details of the coupling of the theory to background fields, which can be translated to a choice of R-symmetry. We argue that, for special choices of R-symmetry, the resulting two dimensional theory has a natural interpretation as an $$ \\mathcal{N}(0,2) $$ gauge theory. As an application of our general observations, we discuss reductions of $$ \\mathcal{N}=1 $$ and $$ \\mathcal{N}=2 $$ dualities and argue that they imply certain two dimensional dualities.« less

Research on accuracy analysis of laser transmission system based on Zemax and Matlab

NASA Astrophysics Data System (ADS)

Chen, Haiping; Liu, Changchun; Ye, Haixian; Xiong, Zhao; Cao, Tingfen

2017-05-01

Laser transmission system is important in high power solid-state laser facilities and its function is to transfer and focus the light beam in accordance with the physical function of the facility. This system is mainly composed of transmission mirror modules and wedge lens module. In order to realize the precision alignment of the system, the precision alignment of the system is required to be decomposed into the allowable range of the calibration error of each module. The traditional method is to analyze the error factors of the modules separately, and then the linear synthesis is carried out, and the influence of the multi-module and multi-factor is obtained. In order to analyze the effect of the alignment error of each module on the beam center and focus more accurately, this paper aims to combine with the Monte Carlo random test and ray tracing, analyze influence of multi-module and multi-factor on the center of the beam, and evaluate and optimize the results of accuracy decomposition.

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, High-Cycle and Low-Cycle Mechanical Fatigue, Creep and Thermal Fatigue Effects

NASA Technical Reports Server (NTRS)

Bast, Callie C.; Boyce, Lola

1995-01-01

The development of methodology for a probabilistic material strength degradation is described. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes five effects that typically reduce lifetime strength: high temperature, high-cycle mechanical fatigue, low-cycle mechanical fatigue, creep and thermal fatigue. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing predictions of high-cycle mechanical fatigue and high temperature effects with experiments are presented. Results from this limited verification study strongly supported that material degradation can be represented by randomized multifactor interaction models.

A Study on the Assessment of Multi-Factors Affecting Urban Floods Using Satellite Image: A Case Study in Nakdong Basin, S. Korea

NASA Astrophysics Data System (ADS)

Kwak, Youngjoo; Kondoh, Akihiko

2010-05-01

Floods are also related to the changes in social economic conditions and land use. Recently, floods increased due to rapid urbanization and human activity in the lowland. Therefore, integrated management of total basin system is necessary to get the secure society. Typhoon ‘Rusa’ swept through eastern and southern parts of South Korea in the 2002. This pity experience gave us valuable knowledge that could be used to mitigate the future flood hazards. The purpose of this study is to construct the digital maps of the multi-factors related to urban flood concerning geomorphologic characteristics, land cover, and surface wetness. Parameters particularly consider geomorphologic functional unit, geomorphologic parameters derived from DEM (digital elevation model), and land use. The research area is Nakdong River Basin in S. Korea. As a result of preliminary analysis for Pusan area, the vulnerability map and the flood-prone areas can be extracted by applying spatial analysis on GIS (geographic information system).

A review on the multivariate statistical methods for dimensional reduction studies

NASA Astrophysics Data System (ADS)

Aik, Lim Eng; Kiang, Lam Chee; Mohamed, Zulkifley Bin; Hong, Tan Wei

2017-05-01

In this research study we have discussed multivariate statistical methods for dimensional reduction, which has been done by various researchers. The reduction of dimensionality is valuable to accelerate algorithm progression, as well as really may offer assistance with the last grouping/clustering precision. A lot of boisterous or even flawed info information regularly prompts a not exactly alluring algorithm progression. Expelling un-useful or dis-instructive information segments may for sure help the algorithm discover more broad grouping locales and principles and generally speaking accomplish better exhibitions on new data set.

Exploring the CAESAR database using dimensionality reduction techniques

NASA Astrophysics Data System (ADS)

Mendoza-Schrock, Olga; Raymer, Michael L.

2012-06-01

The Civilian American and European Surface Anthropometry Resource (CAESAR) database containing over 40 anthropometric measurements on over 4000 humans has been extensively explored for pattern recognition and classification purposes using the raw, original data [1-4]. However, some of the anthropometric variables would be impossible to collect in an uncontrolled environment. Here, we explore the use of dimensionality reduction methods in concert with a variety of classification algorithms for gender classification using only those variables that are readily observable in an uncontrolled environment. Several dimensionality reduction techniques are employed to learn the underlining structure of the data. These techniques include linear projections such as the classical Principal Components Analysis (PCA) and non-linear (manifold learning) techniques, such as Diffusion Maps and the Isomap technique. This paper briefly describes all three techniques, and compares three different classifiers, Naïve Bayes, Adaboost, and Support Vector Machines (SVM), for gender classification in conjunction with each of these three dimensionality reduction approaches.

Tensor Train Neighborhood Preserving Embedding

NASA Astrophysics Data System (ADS)

Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

2018-05-01

In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets.

Kaluza-Klein cosmology from five-dimensional Lovelock-Cartan theory

NASA Astrophysics Data System (ADS)

Castillo-Felisola, Oscar; Corral, Cristóbal; del Pino, Simón; Ramírez, Francisca

2016-12-01

We study the Kaluza-Klein dimensional reduction of the Lovelock-Cartan theory in five-dimensional spacetime, with a compact dimension of S1 topology. We find cosmological solutions of the Friedmann-Robertson-Walker class in the reduced spacetime. The torsion and the fields arising from the dimensional reduction induce a nonvanishing energy-momentum tensor in four dimensions. We find solutions describing expanding, contracting, and bouncing universes. The model shows a dynamical compactification of the extra dimension in some regions of the parameter space.

Usable Multi-factor Authentication and Risk-based Authorization

DTIC Science & Technology

2015-06-01

acceptance. In the previous section we described user studies that explored risks perceived by individuals using online banking and credit card purchases... iTunes purchases. We note that the fingerprint scanners in the current experiment are very different from what would be available in future. However

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

ERIC Educational Resources Information Center

Nash, Steve; Bangert, Art

2014-01-01

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

Obesity, hypertension and genetic variation in the TIGER Study

USDA-ARS?s Scientific Manuscript database

Obesity and hypertension are multifactoral conditions in which the onset and severity of the conditions are influenced by the interplay of genetic and environmental factors. We hypothesize that multiple genes and environmental factors account for a significant amount of variation in BMI and blood pr...

Emotional Intelligence and the Career Choice Process.

ERIC Educational Resources Information Center

Emmerling, Robert J.; Cherniss, Cary

2003-01-01

Emotional intelligence as conceptualized by Mayer and Salovey consists of perceiving emotions, using emotions to facilitate thoughts, understanding emotions, and managing emotions to enhance personal growth. The Multifactor Emotional Intelligence Scale has proven a valid and reliable measure that can be used to explore the implications of…

Is there a genetic solution to bovine respiratory disease complex?

USDA-ARS?s Scientific Manuscript database

Bovine respiratory disease complex (BRDC) is a complex multi-factor disease, which increases costs and reduces revenue from feedlot cattle. Multiple stressors and pathogens (viral and bacterial) have been implicated in the etiology of BRDC, therefore multiple approaches will be needed to evaluate a...

Probabilistic Multi-Factor Interaction Model for Complex Material Behavior

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2010-01-01

Complex material behavior is represented by a single equation of product form to account for interaction among the various factors. The factors are selected by the physics of the problem and the environment that the model is to represent. For example, different factors will be required for each to represent temperature, moisture, erosion, corrosion, etc. It is important that the equation represent the physics of the behavior in its entirety accurately. The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the external launch tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points - the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used were obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated. The problem lies in how to represent the divot weight with a single equation. A unique solution to this problem is a multi-factor equation of product form. Each factor is of the following form (1 xi/xf)ei, where xi is the initial value, usually at ambient conditions, xf the final value, and ei the exponent that makes the curve represented unimodal that meets the initial and final values. The exponents are either evaluated by test data or by technical judgment. A minor disadvantage may be the selection of exponents in the absence of any empirical data. This form has been used successfully in describing the foam ejected in simulated space environmental conditions. Seven factors were required to represent the ejected foam. The exponents were evaluated by least squares method from experimental data. The equation is used and it can represent multiple factors in other problems as well; for example, evaluation of fatigue life, creep life, fracture toughness, and structural fracture, as well as optimization functions. The software is rather simplistic. Required inputs are initial value, final value, and an exponent for each factor. The number of factors is open-ended. The value is updated as each factor is evaluated. If a factor goes to zero, the previous value is used in the evaluation.

Semisupervised kernel marginal Fisher analysis for face recognition.

PubMed

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

Advance study of fiber-reinforced self-compacting concrete

NASA Astrophysics Data System (ADS)

Mironova, M.; Ivanova, M.; Naidenov, V.; Georgiev, I.; Stary, J.

2015-10-01

Incorporation in concrete composition of steel macro- and micro - fiber reinforcement with structural function increases the degree of ductility of typically brittle cement-containing composites, which in some cases can replace completely or partially conventional steel reinforcement in the form of rods and meshes. Thus, that can reduce manufacturing, detailing and placement of conventional reinforcement, which enhances productivity and economic efficiency of the building process. In this paper, six fiber-reinforced with different amounts of steel fiber cement-containing self-compacting compositions are investigated. The results of some of their main strength-deformation characteristics are presented. Advance approach for the study of structural and material properties of these type composites is proposed by using the methods of industrial computed tomography. The obtained original tomography results about the microstructure and characteristics of individual structural components make it possible to analyze the effective macro-characteristics of the studied composites. The resulting analytical data are relevant for the purposes of multi-dimensional modeling of these systems. Multifactor structure-mechanical analysis of the obtained with different methods original scientific results is proposed. It is presented a conclusion of the capabilities and effectiveness of complex analysis in the studies to characterize the properties of self-compacting fiber-reinforced concrete.

Examining Dimensions of Self-Efficacy for Writing

ERIC Educational Resources Information Center

Bruning, Roger; Dempsey, Michael; Kauffman, Douglas F.; McKim, Courtney; Zumbrunn, Sharon

2013-01-01

A multifactor perspective on writing self-efficacy was examined in 2 studies. Three factors were proposed--self-efficacy for writing ideation, writing conventions, and writing self-regulation--and a scale constructed to reflect these factors. In Study 1, middle school students (N = 697) completed the Self-Efficacy for Writing Scale (SEWS), along…

Do Leadership Styles Influence Organizational Health? A Study in Educational Organizations

ERIC Educational Resources Information Center

Toprak, Mustafa; Inandi, Bulent; Colak, Ahmet Levent

2015-01-01

This research aims to investigate the effect of leadership styles of school principals on organizational health. Causal-comparative research model was used to analyze the relationships between leadership types and organizational health. For data collection, a Likert type Multifactor Leadership scale questionnaire and Organizational Health scale…

Transformational Leadership and the Leadership Performance of Oregon Secondary School Principals

ERIC Educational Resources Information Center

Breaker, Jason Lee

2009-01-01

A study of 118 secondary school principals in Oregon was conducted to examine the relationship of transformational leadership to secondary school principals' leadership performance. This study measured the transformational leadership of secondary school principals in Oregon using the "Multifactor Leadership Questionnaire (5X-Short)"…

Appropriate Use Policy | High-Performance Computing | NREL

Science.gov Websites

users of the National Renewable Energy Laboratory (NREL) High Performance Computing (HPC) resources government agency, National Laboratory, University, or private entity, the intellectual property terms (if issued a multifactor token which may be a physical token or a virtual token used with one-time password

The Negative Testing Effect and Multifactor Account

ERIC Educational Resources Information Center

Peterson, Daniel J.; Mulligan, Neil W.

2013-01-01

Across 3 experiments, we investigated the factors that dictate when taking a test improves subsequent memory performance (the "testing effect"). In Experiment 1, participants retrieving a set of targets during a retrieval practice phase ultimately recalled fewer of those targets compared with a group of participants who studied the…

Worker Traits Training Unit. MA Handbook No. 314.

ERIC Educational Resources Information Center

Manpower Administration (DOL), Washington, DC.

This training unit provides persons involved in employment interviewing, vocational counseling, curriculum planning, and other manpower activities with a multifactor approach for obtaining information from an individual and relating the data to job requirements. It is intended to result in the development of the bridge between client potential and…

Organizational Deviance and Multi-Factor Leadership

ERIC Educational Resources Information Center

Aksu, Ali

2016-01-01

Organizational deviant behaviors can be defined as behaviors that have deviated from standards and uncongenial to organization's expectations. When such behaviors have been thought to damage the organization, it can be said that reducing the deviation behaviors at minimum level is necessary for a healthy organization. The aim of this research is…

A Multifactor Approach to Research in Instructional Technology.

ERIC Educational Resources Information Center

Ragan, Tillman J.

In a field such as instructional design, explanations of educational outcomes must necessarily consider multiple input variables. To adequately understand the contribution made by the independent variables, it is helpful to have a visual conception of how the input variables interrelate. Two variable models are adequately represented by a two…

Teacher Perceptions of Principals' Leadership Qualities: A Mixed Methods Study

ERIC Educational Resources Information Center

Hauserman, Cal P.; Ivankova, Nataliya V.; Stick, Sheldon L.

2013-01-01

This mixed methods sequential explanatory study utilized the Multi-factor Leadership Questionnaire, responses to open-ended questions, and in-depth interviews to identify transformational leadership qualities that were present among principals in Alberta, Canada. The first quantitative phase consisted of a random sample of 135 schools (with…

Chaotic oscillator containing memcapacitor and meminductor and its dimensionality reduction analysis.

PubMed

Yuan, Fang; Wang, Guangyi; Wang, Xiaowei

2017-03-01

In this paper, smooth curve models of meminductor and memcapacitor are designed, which are generalized from a memristor. Based on these models, a new five-dimensional chaotic oscillator that contains a meminductor and memcapacitor is proposed. By dimensionality reducing, this five-dimensional system can be transformed into a three-dimensional system. The main work of this paper is to give the comparisons between the five-dimensional system and its dimensionality reduction model. To investigate dynamics behaviors of the two systems, equilibrium points and stabilities are analyzed. And the bifurcation diagrams and Lyapunov exponent spectrums are used to explore their properties. In addition, digital signal processing technologies are used to realize this chaotic oscillator, and chaotic sequences are generated by the experimental device, which can be used in encryption applications.

GIXSGUI : a MATLAB toolbox for grazing-incidence X-ray scattering data visualization and reduction, and indexing of buried three-dimensional periodic nanostructured films

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

Jiang, Zhang

GIXSGUIis a MATLAB toolbox that offers both a graphical user interface and script-based access to visualize and process grazing-incidence X-ray scattering data from nanostructures on surfaces and in thin films. It provides routine surface scattering data reduction methods such as geometric correction, one-dimensional intensity linecut, two-dimensional intensity reshapingetc. Three-dimensional indexing is also implemented to determine the space group and lattice parameters of buried organized nanoscopic structures in supported thin films.

Allocation and simulation study of carbon emission quotas among China's provinces in 2020.

PubMed

Zhou, Xing; Guan, Xueling; Zhang, Ming; Zhou, Yao; Zhou, Meihua

2017-03-01

China will form its carbon market in 2017 to focus on the allocation of regional carbon emission quota in order to cope with global warming. The rationality of the regional allocation has become an important consideration for the government in ensuring stable growth in different regions that are experiencing disparity in resource endowment and economic status. Based on constructing the quota allocation indicator system for carbon emission, the emission quota for each province in different scenarios and schemes in 2020 is simulated by the multifactor hybrid weighted Shannon entropy allocation model. The following conclusions are drawn: (1) The top 5 secondary-level indicators that influence provincial quota allocation in weight are as follows: per capita energy consumption, openness, per capita carbon emission, per capita disposable income, and energy intensity. (2) The ratio of carbon emission in 2020 is different from that in 2013 in many scenarios, and the variation is scenario 2 > scenario 1 > scenario 3, with Hubei and Guangdong the provinces with the largest increase and decrease ratios, respectively. (3) In the same scenario, the quota allocation varies in different reduction criteria emphases; if the government emphasizes reduction efficiency, scheme 1 will show obvious adjustment, that is, Hunan, Hubei, Guizhou, and Yunnan will have the largest decrease. The amounts are 4.28, 8.31, 4.04, and 5.97 million tons, respectively.

Multivariate Strategies in Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Hansen, Lars Kai

2007-01-01

We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a "mind reading" predictive multivariate fMRI model.

Two component-three dimensional catalysis

DOEpatents

Schwartz, Michael; White, James H.; Sammells, Anthony F.

2002-01-01

This invention relates to catalytic reactor membranes having a gas-impermeable membrane for transport of oxygen anions. The membrane has an oxidation surface and a reduction surface. The membrane is coated on its oxidation surface with an adherent catalyst layer and is optionally coated on its reduction surface with a catalyst that promotes reduction of an oxygen-containing species (e.g., O.sub.2, NO.sub.2, SO.sub.2, etc.) to generate oxygen anions on the membrane. The reactor has an oxidation zone and a reduction zone separated by the membrane. A component of an oxygen containing gas in the reduction zone is reduced at the membrane and a reduced species in a reactant gas in the oxidation zone of the reactor is oxidized. The reactor optionally contains a three-dimensional catalyst in the oxidation zone. The adherent catalyst layer and the three-dimensional catalyst are selected to promote a desired oxidation reaction, particularly a partial oxidation of a hydrocarbon.

Rigorous Model Reduction for a Damped-Forced Nonlinear Beam Model: An Infinite-Dimensional Analysis

NASA Astrophysics Data System (ADS)

Kogelbauer, Florian; Haller, George

2018-06-01

We use invariant manifold results on Banach spaces to conclude the existence of spectral submanifolds (SSMs) in a class of nonlinear, externally forced beam oscillations. SSMs are the smoothest nonlinear extensions of spectral subspaces of the linearized beam equation. Reduction in the governing PDE to SSMs provides an explicit low-dimensional model which captures the correct asymptotics of the full, infinite-dimensional dynamics. Our approach is general enough to admit extensions to other types of continuum vibrations. The model-reduction procedure we employ also gives guidelines for a mathematically self-consistent modeling of damping in PDEs describing structural vibrations.

Application of diffusion maps to identify human factors of self-reported anomalies in aviation.

PubMed

Andrzejczak, Chris; Karwowski, Waldemar; Mikusinski, Piotr

2012-01-01

A study investigating what factors are present leading to pilots submitting voluntary anomaly reports regarding their flight performance was conducted. Diffusion Maps (DM) were selected as the method of choice for performing dimensionality reduction on text records for this study. Diffusion Maps have seen successful use in other domains such as image classification and pattern recognition. High-dimensionality data in the form of narrative text reports from the NASA Aviation Safety Reporting System (ASRS) were clustered and categorized by way of dimensionality reduction. Supervised analyses were performed to create a baseline document clustering system. Dimensionality reduction techniques identified concepts or keywords within records, and allowed the creation of a framework for an unsupervised document classification system. Results from the unsupervised clustering algorithm performed similarly to the supervised methods outlined in the study. The dimensionality reduction was performed on 100 of the most commonly occurring words within 126,000 text records describing commercial aviation incidents. This study demonstrates that unsupervised machine clustering and organization of incident reports is possible based on unbiased inputs. Findings from this study reinforced traditional views on what factors contribute to civil aviation anomalies, however, new associations between previously unrelated factors and conditions were also found.

Justification of process of loading coal onto face conveyors by auger heads of shearer-loader machines

NASA Astrophysics Data System (ADS)

Nguyen, K. L.; Gabov, V. V.; Zadkov, D. A.; Le, T. B.

2018-03-01

This paper analyzes the processes of removing coal from the area of its dislodging and loading the disintegrated mass onto face conveyors by auger heads of shearer-loader machines. The loading process is assumed to consist of four subprocesses: dislodging coal, removal of the disintegrated mass by auger blades from the crushing area, passive transportation of the disintegrated mass, and forming the load flow on the bearing surface of a face conveyor. Each of the considered subprocesses is different in its physical nature, the number of factors influencing it, and can be complex or multifactor. Possibilities of improving the efficiency of loading coal onto a face conveyor are addressed. The selected criteria of loading efficiency are load rate, specific energy consumption, and coal size reduction. Efficiency is improved by reducing the resistance to movement of the disintegrated mass during loading by increasing the area of the loading window section and the volume of the loading area on the conveyor, as well as by coordination of intensity of flows related to the considered processes in local areas.

A Multi-Factor Analysis of Job Satisfaction among School Nurses

ERIC Educational Resources Information Center

Foley, Marcia; Lee, Julie; Wilson, Lori; Cureton, Virginia Young; Canham, Daryl

2004-01-01

Although job satisfaction has been widely studied among registered nurses working in traditional health care settings, little is known about the job-related values and perceptions of nurses working in school systems. Job satisfaction is linked to lower levels of job-related stress, burnout, and career abandonment among nurses. This study evaluated…

Investigating Teachers' Organizational Socialization Levels and Perceptions about Leadership Styles of Their Principals

ERIC Educational Resources Information Center

Kadi, Aysegül

2015-01-01

The purpose of this study is to investigate teachers' organizational socialization levels and perceptions about leadership styles of their principals. Research was conducted with 361 teachers. Research design is determined as survey and correlational. Multi-Factor Leadership Scale originally was developed by Bass (1999) and adapted to Turkish…

Authentic Leadership--Is It More than Emotional Intelligence?

ERIC Educational Resources Information Center

Duncan, Phyllis; Green, Mark; Gergen, Esther; Ecung, Wenonah

2017-01-01

One of the newest theories to gain widespread interest is authentic leadership. Part of the rationale for developing a model and subsequent instrument to measure authentic leadership was a concern that the more popular theory, the full range model of leadership and its instrument, the Multifactor Leadership Questionnaire (MLQ) (Bass & Avolio,…

Emotional Enhancement Effect of Memory: Removing the Influence of Cognitive Factors

ERIC Educational Resources Information Center

Sommer, Tobias; Glascher, Jan; Moritz, Steffen; Buchel, Christian

2008-01-01

According to the modulation hypothesis, arousal is the crucial factor in the emotional enhancement of memory (EEM). However, the multifactor theory of the EEM recently proposed that cognitive characteristics of emotional stimuli, e.g., relatedness and distinctiveness, also play an important role. The current study aimed to investigate the…

An ecological classification system for the central hardwoods region: The Hoosier National Forest

Treesearch

James E. Van Kley; George R. Parker

1993-01-01

This study, a multifactor ecological classification system, using vegetation, soil characteristics, and physiography, was developed for the landscape of the Hoosier National Forest in Southern Indiana. Measurements of ground flora, saplings, and canopy trees from selected stands older than 80 years were subjected to TWINSPAN classification and DECORANA ordination....

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Scoring Procedures

Cancer.gov

Scoring procedures were developed to convert a respondent's screener responses to estimates of individual dietary intake for percentage energy from fat, grams of fiber, and servings of fruits and vegetables, using USDA's 1994-96 Continuing Survey of Food Intakes of Individuals (CSFII 94-96) dietary recall data.

Technical Notes on the Multifactor Method of Elementary School Closing.

ERIC Educational Resources Information Center

Puleo, Vincent T.

This report provides preliminary technical information on a method for analyzing the factors involved in the closing of elementary schools. Included is a presentation of data and a brief discussion bearing on descriptive statistics, reliability, and validity. An intercorrelation matrix is also examined. The method employs 9 factors that have a…

Motivating Peak Performance: Leadership Behaviors That Stimulate Employee Motivation and Performance

ERIC Educational Resources Information Center

Webb, Kerry

2007-01-01

The impact of leader behaviors on motivation levels of employees was examined in this study. Two hundred twenty-three vice presidents and chief officers from 104 member colleges and universities in the Council for Christian Colleges and Universities were sampled. Leaders were administered the Multifactor Leadership Questionnaire (MLQ-rater…

Faculty Member Perceptions of Academic Leadership Styles at Private Colleges

ERIC Educational Resources Information Center

Gidman, Lori Kathleen

2013-01-01

The leadership style of academic leaders was studied through the eyes of faculty members. This empirical study looked at faculty perceptions of academic leadership with the use of a numerical survey as the basis for observation. Faculty members at six private liberal arts institutions completed the Multifactor Leadership Questionnaire (MLQ) in…

The Relationship between School Principals' Leadership Styles and Collective Teacher Efficacy

ERIC Educational Resources Information Center

Akan, Durdagi

2013-01-01

This study aims to determine the relationship between school administrators' leadership styles and the collective teacher efficacy based on teachers' perceptions. In line with this objective, the multifactor leadership style scale and the collective teacher efficacy scale were applied on 223 teachers who were working in the province of Erzurum.…

Predicting plant species diversity in a longleaf pine landscape

Treesearch

L. Katherine Kirkman; P. Charles Goebel; Brian J. Palik; Larry T. West

2004-01-01

In this study, we used a hierarchical, multifactor ecological classification system to examine how spatial patterns of biodiversity develop in one of the most species-rich ecosystems in North America, the fire-maintained longleaf pine-wiregrass ecosystem and associated depressional wetlands and riparian forests. Our goal was to determine which landscape features are...

Goal Oriented and Risk Taking Behavior: The Roles of Multiple Systems for Caucasian and Arab-American Adolescents

ERIC Educational Resources Information Center

Tynan, Joshua J.; Somers, Cheryl L.; Gleason, Jamie H.; Markman, Barry S.; Yoon, Jina

2015-01-01

With Bronfenbrenner's (1977) ecological theory and other multifactor models (e.g. Pianta, 1999; Prinstein, Boergers, & Spirito, 2001) underlying this study design, the purpose was to examine, simultaneously, key variables in multiple life contexts (microsystem, mesosystem, exosystem levels) for their individual and combined roles in predicting…

A Study of Secondary School Principals' Leadership Styles and School Dropout Rates

ERIC Educational Resources Information Center

Baggerly-Hinojosa, Barbara

2012-01-01

This study examined the relationship between the leadership styles of secondary school principals, measured by the self-report "Multifactor Leadership Questionnaire 5X short" (Bass & Avolio, 2000) and the school's dropout rates, as reported by the Texas Education Agency in the Academic Excellence Indicator System (AEIS) report while…

Can Multifactor Models of Teaching Improve Teacher Effectiveness Measures?

ERIC Educational Resources Information Center

Lazarev, Valeriy; Newman, Denis

2014-01-01

NCLB waiver requirements have led to development of teacher evaluation systems, in which student growth is a significant component. Recent empirical research has been focusing on metrics of student growth--value-added scores in particular--and their relationship to other metrics. An extensive set of recent teacher-evaluation studies conducted by…

Estimating multi-factor cumulative watershed effects on fish populations with an individual-based model

Treesearch

Bret C. Harvey; Steven F. Railsback

2007-01-01

While the concept of cumulative effects is prominent in legislation governing environmental management, the ability to estimate cumulative effects remains limited. One reason for this limitation is that important natural resources such as fish populations may exhibit complex responses to changes in environmental conditions, particularly to alteration of multiple...

Bureaucratic Abuse and the False Dichotomy between Intentional and Unintentional Child Injuries.

ERIC Educational Resources Information Center

Kotch, Jonathan B.; And Others

This paper examines the arbitrary distinctions between intentional and unintentional child injuries, noting that a careful review of the literature of both child abuse and unintentional child injury revealed similarities among the risk factors associated with the two outcomes. A single, multifactor model of injury etiology, the ecologic model, is…

Effect of five enological practices and of the general phenolic composition on fermentation-related aroma compounds in Mencia young red wines.

PubMed

Añón, Ana; López, Jorge F; Hernando, Diego; Orriols, Ignacio; Revilla, Eugenio; Losada, Manuel M

2014-04-01

The effects of five technological procedures and of the contents of total anthocyanins and condensed tannins on 19 fermentation-related aroma compounds of young red Mencia wines were studied. Multifactor ANOVA revealed that levels of those volatiles changed significantly over the length of storage in bottles and, to a lesser extent, due to other technological factors considered; total anthocyanins and condensed tannins also changed significantly as a result of the five practices assayed. Five aroma compounds possessed an odour activity value >1 in all wines, and another four in some wines. Linear correlation among volatile compounds and general phenolic composition revealed that total anthocyanins were highly related to 14 different aroma compounds. Multifactor ANOVA, considering the content of total anthocyanins as a sixth random factor, revealed that this parameter affected significantly the contents of ethyl lactate, ethyl isovalerate, 1-pentanol and ethyl octanoate. Thus, the aroma of young red Mencia wines may be affected by levels of total anthocyanins. Copyright © 2013 Elsevier Ltd. All rights reserved.

Computational simulation of coupled material degradation processes for probabilistic lifetime strength of aerospace materials

NASA Technical Reports Server (NTRS)

Boyce, Lola; Bast, Callie C.

1992-01-01

The research included ongoing development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects or primative variables. These primative variable may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above described constitutive equation using actual experimental materials data together with linear regression of that data, thereby predicting values for the empirical material constraints for each effect or primative variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from the open literature for materials typically of interest to those studying aerospace propulsion system components. Material data for Inconel 718 was analyzed using the developed methodology.

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

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

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn; Lin, Guang, E-mail: guanglin@purdue.edu

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Stable orthogonal local discriminant embedding for linear dimensionality reduction.

PubMed

Gao, Quanxue; Ma, Jingjie; Zhang, Hailin; Gao, Xinbo; Liu, Yamin

2013-07-01

Manifold learning is widely used in machine learning and pattern recognition. However, manifold learning only considers the similarity of samples belonging to the same class and ignores the within-class variation of data, which will impair the generalization and stableness of the algorithms. For this purpose, we construct an adjacency graph to model the intraclass variation that characterizes the most important properties, such as diversity of patterns, and then incorporate the diversity into the discriminant objective function for linear dimensionality reduction. Finally, we introduce the orthogonal constraint for the basis vectors and propose an orthogonal algorithm called stable orthogonal local discriminate embedding. Experimental results on several standard image databases demonstrate the effectiveness of the proposed dimensionality reduction approach.

Nonlinear dimensionality reduction of CT histogram based feature space for predicting recurrence-free survival in non-small-cell lung cancer

NASA Astrophysics Data System (ADS)

Kawata, Y.; Niki, N.; Ohmatsu, H.; Aokage, K.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2015-03-01

Advantages of CT scanners with high resolution have allowed the improved detection of lung cancers. In the recent release of positive results from the National Lung Screening Trial (NLST) in the US showing that CT screening does in fact have a positive impact on the reduction of lung cancer related mortality. While this study does show the efficacy of CT based screening, physicians often face the problems of deciding appropriate management strategies for maximizing patient survival and for preserving lung function. Several key manifold-learning approaches efficiently reveal intrinsic low-dimensional structures latent in high-dimensional data spaces. This study was performed to investigate whether the dimensionality reduction can identify embedded structures from the CT histogram feature of non-small-cell lung cancer (NSCLC) space to improve the performance in predicting the likelihood of RFS for patients with NSCLC.

TPSLVM: a dimensionality reduction algorithm based on thin plate splines.

PubMed

Jiang, Xinwei; Gao, Junbin; Wang, Tianjiang; Shi, Daming

2014-10-01

Dimensionality reduction (DR) has been considered as one of the most significant tools for data analysis. One type of DR algorithms is based on latent variable models (LVM). LVM-based models can handle the preimage problem easily. In this paper we propose a new LVM-based DR model, named thin plate spline latent variable model (TPSLVM). Compared to the well-known Gaussian process latent variable model (GPLVM), our proposed TPSLVM is more powerful especially when the dimensionality of the latent space is low. Also, TPSLVM is robust to shift and rotation. This paper investigates two extensions of TPSLVM, i.e., the back-constrained TPSLVM (BC-TPSLVM) and TPSLVM with dynamics (TPSLVM-DM) as well as their combination BC-TPSLVM-DM. Experimental results show that TPSLVM and its extensions provide better data visualization and more efficient dimensionality reduction compared to PCA, GPLVM, ISOMAP, etc.

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices and its application in brain-computer interfaces

NASA Astrophysics Data System (ADS)

Davoudi, Alireza; Shiry Ghidary, Saeed; Sadatnejad, Khadijeh

2017-06-01

Objective. In this paper, we propose a nonlinear dimensionality reduction algorithm for the manifold of symmetric positive definite (SPD) matrices that considers the geometry of SPD matrices and provides a low-dimensional representation of the manifold with high class discrimination in a supervised or unsupervised manner. Approach. The proposed algorithm tries to preserve the local structure of the data by preserving distances to local means (DPLM) and also provides an implicit projection matrix. DPLM is linear in terms of the number of training samples. Main results. We performed several experiments on the multi-class dataset IIa from BCI competition IV and two other datasets from BCI competition III including datasets IIIa and IVa. The results show that our approach as dimensionality reduction technique—leads to superior results in comparison with other competitors in the related literature because of its robustness against outliers and the way it preserves the local geometry of the data. Significance. The experiments confirm that the combination of DPLM with filter geodesic minimum distance to mean as the classifier leads to superior performance compared with the state of the art on brain-computer interface competition IV dataset IIa. Also the statistical analysis shows that our dimensionality reduction method performs significantly better than its competitors.

On the precision of quasi steady state assumptions in stochastic dynamics

NASA Astrophysics Data System (ADS)

Agarwal, Animesh; Adams, Rhys; Castellani, Gastone C.; Shouval, Harel Z.

2012-07-01

Many biochemical networks have complex multidimensional dynamics and there is a long history of methods that have been used for dimensionality reduction for such reaction networks. Usually a deterministic mass action approach is used; however, in small volumes, there are significant fluctuations from the mean which the mass action approach cannot capture. In such cases stochastic simulation methods should be used. In this paper, we evaluate the applicability of one such dimensionality reduction method, the quasi-steady state approximation (QSSA) [L. Menten and M. Michaelis, "Die kinetik der invertinwirkung," Biochem. Z 49, 333369 (1913)] for dimensionality reduction in case of stochastic dynamics. First, the applicability of QSSA approach is evaluated for a canonical system of enzyme reactions. Application of QSSA to such a reaction system in a deterministic setting leads to Michaelis-Menten reduced kinetics which can be used to derive the equilibrium concentrations of the reaction species. In the case of stochastic simulations, however, the steady state is characterized by fluctuations around the mean equilibrium concentration. Our analysis shows that a QSSA based approach for dimensionality reduction captures well the mean of the distribution as obtained from a full dimensional simulation but fails to accurately capture the distribution around that mean. Moreover, the QSSA approximation is not unique. We have then extended the analysis to a simple bistable biochemical network model proposed to account for the stability of synaptic efficacies; the substrate of learning and memory [J. E. Lisman, "A mechanism of memory storage insensitive to molecular turnover: A bistable autophosphorylating kinase," Proc. Natl. Acad. Sci. U.S.A. 82, 3055-3057 (1985)], 10.1073/pnas.82.9.3055. Our analysis shows that a QSSA based dimensionality reduction method results in errors as big as two orders of magnitude in predicting the residence times in the two stable states.

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap

NASA Astrophysics Data System (ADS)

Spiwok, Vojtěch; Králová, Blanka

2011-12-01

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling.

Conference Attendance Patterns of Outdoor Orientation Program Staff at Four-Year Colleges in the United States

ERIC Educational Resources Information Center

Bell, Brent J.

2009-01-01

One purpose of professional conference attendance is to enhance social support. Intentionally fostering this support is an important political aim that should be developed. Although many multifactor definitions of social support exist (Cobb, 1979; Cohen & Syme, 1985; Kahn, 1979; Shaefer et al., 1981; Weiss, 1974), all distinguish between an…

Revisiting a Cognitive Framework for Test Design: Applications for a Computerized Perceptual Speed Test.

ERIC Educational Resources Information Center

Alderton, David L.

This paper highlights the need for a systematic, content aware, and theoretically-based approach to test design. The cognitive components approach is endorsed, and is applied to the development of a computerized perceptual speed test. Psychometric literature is reviewed and shows that: every major multi-factor theory includes a clerical/perceptual…

Bullying in Adolescent Residential Care: The Influence of the Physical and Social Residential Care Environment

ERIC Educational Resources Information Center

Sekol, Ivana

2016-01-01

Background: To date, no study examined possible contributions of environmental factors to bullying and victimization in adolescent residential care facilities. Objective: By testing one part of the Multifactor Model of Bullying in Secure Setting (MMBSS; Ireland in "Int J Adolesc Med Health" 24(1):63-68, 2012), this research examined the…

Academic Administrator Leadership Styles and the Impact on Faculty Job Satisfaction

ERIC Educational Resources Information Center

Bateh, Justin; Heyliger, Wilton

2014-01-01

This article examines the impact of three leadership styles as a predictor of job satisfaction in a state university system. The Multifactor Leadership Questionnaire was used to identify the leadership style of an administrator as perceived by faculty members. Spector's Job Satisfaction Survey was used to assess a faculty member's level of job…

The Impact of Mentor Leadership Styles on First-Year Adult Student Retention

ERIC Educational Resources Information Center

Smith Staley, Charlesetta

2012-01-01

This quantitative study explored the leadership styles of mentors for retained first-year adult students to analyze whether the prevalent style had a higher impact on first-year adult student retention. The Multifactor Leadership Questionnaire (MLQ) 5x was used to collect data on the mentors' leadership styles from the perspective of retained…

A Preliminary Study for a New Model of Sense of Community

ERIC Educational Resources Information Center

Tartaglia, Stefano

2006-01-01

Although Sense of Community (SOC) is usually defined as a multidimensional construct, most SOC scales are unidimensional. To reduce the split between theory and empirical research, the present work identifies a multifactor structure for the Italian Sense of Community Scale (ISCS) that has already been validated as a unitary index of SOC. This…

Creativity in the Structure of Professionalism of a Higher School Teacher

ERIC Educational Resources Information Center

Gladilina, Irina Petrovna

2016-01-01

In the science, due to the absence of strict and exact criteria for differentiating between creative and non-creative activities of a human, there is no rather full definition of "creativity" notion despite that this matter was addressed by many scholars. Multifactor field in the science on creativity allows interpreting the essence of…

Multifactor Screener in the 2000 National Health Interview Survey Cancer Control Supplement: Definition of Acceptable Dietary Data Values

Cancer.gov

We used the U.S. Department of Agriculture's (USDA) 1994-96 Continuing Survey of Food Intakes of Individuals (CSFII) data on reported intakes over two days of 24-hour recall to make judgments about reasonable frequencies of consumption that were reported on a per day basis.

Evaluating the metagenome of two sampling locations in the nasal cavity of cattle with bovine respiratory disease complex

USDA-ARS?s Scientific Manuscript database

Bovine respiratory disease complex (BRDC) is a multi-factor disease, and disease incidence may be associated with an animal’s commensal microbiota (metagenome). Evaluation of the animal’s resident microbiota in the nasal cavity may help us to understand the impact of the metagenome on incidence of ...

Evaluating the microbiome of two sampling locations in the nasal cavity of cattle with bovine respiratory disease complex (BRDC)

USDA-ARS?s Scientific Manuscript database

Bovine respiratory disease complex (BRDC) is a multi-factor disease, and disease incidence may be associated with an animal’s commensal microbiota (metagenome). Evaluation of the animal’s resident microbiota in the nasal cavity may help us to understand the impact of the metagenome on incidence of ...

The Effects of Transformational Leadership and the Sense of Calling on Job Burnout among Special Education Teachers

ERIC Educational Resources Information Center

Gong, Tao; Zimmerli, Laurie; Hoffer, Harry E.

2013-01-01

This article examines the effects of transformational leadership of supervisors and the sense of calling on job burnout among special education teachers. A total of 256 special education teachers completed the Maslach Burnout Inventory and rated their supervisors on the Multifactor Leadership Questionnaire. The results reveal that transformational…

Identifying the Best Buys in U.S. Higher Education

ERIC Educational Resources Information Center

Eff, E. Anthon; Klein, Christopher C.; Kyle, Reuben

2012-01-01

Which U.S. institutions of higher education offer the best value to consumers? To answer this question, we evaluate U.S. institutions relative to a data envelopment analysis (DEA) multi-factor frontier based on 2000-2001 data for 1,179 4-year institutions. The resulting DEA "best buy" scores allow the ranking of institutions by a…

Inside The Zone of Proximal Development: Validating A Multifactor Model Of Learning Potential With Gifted Students And Their Peers

ERIC Educational Resources Information Center

Kanevsky, Lannie; Geake, John

2004-01-01

Kanevsky (1995b) proposed a model of learning potential based on Vygotsky?s notions of "good learning" and the zone of proximal development. This study investigated the contributions of general knowledge, information processing efficiency, and metacognition to differences in the learning potential of 5 gifted nongifted students.…

N-Dimensional LLL Reduction Algorithm with Pivoted Reflection

PubMed Central

Deng, Zhongliang; Zhu, Di

2018-01-01

The Lenstra-Lenstra-Lovász (LLL) lattice reduction algorithm and many of its variants have been widely used by cryptography, multiple-input-multiple-output (MIMO) communication systems and carrier phase positioning in global navigation satellite system (GNSS) to solve the integer least squares (ILS) problem. In this paper, we propose an n-dimensional LLL reduction algorithm (n-LLL), expanding the Lovász condition in LLL algorithm to n-dimensional space in order to obtain a further reduced basis. We also introduce pivoted Householder reflection into the algorithm to optimize the reduction time. For an m-order positive definite matrix, analysis shows that the n-LLL reduction algorithm will converge within finite steps and always produce better results than the original LLL reduction algorithm with n > 2. The simulations clearly prove that n-LLL is better than the original LLL in reducing the condition number of an ill-conditioned input matrix with 39% improvement on average for typical cases, which can significantly reduce the searching space for solving ILS problem. The simulation results also show that the pivoted reflection has significantly declined the number of swaps in the algorithm by 57%, making n-LLL a more practical reduction algorithm. PMID:29351224

Combined untargeted and targeted fingerprinting by comprehensive two-dimensional gas chromatography: revealing fructose-induced changes in mice urinary metabolic signatures.

PubMed

Bressanello, Davide; Liberto, Erica; Collino, Massimo; Chiazza, Fausto; Mastrocola, Raffaella; Reichenbach, Stephen E; Bicchi, Carlo; Cordero, Chiara

2018-04-01

This study exploits the information potential of comprehensive two-dimensional gas chromatography configured with a parallel dual secondary column-dual detection by mass spectrometry and flame ionization (GC×2GC-MS/FID) to study changes in urinary metabolic signatures of mice subjected to high-fructose diets. Samples are taken from mice fed with normal or fructose-enriched diets provided either in aqueous solution or in solid form and analyzed at three stages of the dietary intervention (1, 6, and 12 weeks). Automated Untargeted and Targeted fingerprinting for 2D data elaboration is adopted for the most inclusive data mining of GC×GC patterns. The UT fingerprinting strategy performs a fully automated peak-region features fingerprinting and combines results from pre-targeted compounds and unknowns across the sample-set. The most informative metabolites, with statistically relevant differences between sample groups, are obtained by unsupervised multivariate analysis (MVA) and cross-validated by multi-factor analysis (MFA) with external standard quantitation by GC-MS. Results indicate coherent clustering of mice urine signatures according to dietary manipulation. Notably, the metabolite fingerprints of mice fed with liquid fructose exhibited greater derangement in fructose, glucose, citric, pyruvic, malic, malonic, gluconic, cis-aconitic, succinic and 2-keto glutaric acids, glycine acyl derivatives (N-carboxy glycine, N-butyrylglycine, N-isovaleroylglycine, N-phenylacetylglycine), and hippuric acid. Untargeted fingerprinting indicates some analytes which were not a priori pre-targeted which provide additional insights: N-acetyl glucosamine, N-acetyl glutamine, malonyl glycine, methyl malonyl glycine, and glutaric acid. Visual features fingerprinting is used to track individual variations during experiments, thereby extending the panorama of possible data elaboration tools. Graphical abstract ᅟ.

A reduction for spiking integrate-and-fire network dynamics ranging from homogeneity to synchrony.

PubMed

Zhang, J W; Rangan, A V

2015-04-01

In this paper we provide a general methodology for systematically reducing the dynamics of a class of integrate-and-fire networks down to an augmented 4-dimensional system of ordinary-differential-equations. The class of integrate-and-fire networks we focus on are homogeneously-structured, strongly coupled, and fluctuation-driven. Our reduction succeeds where most current firing-rate and population-dynamics models fail because we account for the emergence of 'multiple-firing-events' involving the semi-synchronous firing of many neurons. These multiple-firing-events are largely responsible for the fluctuations generated by the network and, as a result, our reduction faithfully describes many dynamic regimes ranging from homogeneous to synchronous. Our reduction is based on first principles, and provides an analyzable link between the integrate-and-fire network parameters and the relatively low-dimensional dynamics underlying the 4-dimensional augmented ODE.

Understanding decay resistance, dimensional stability and strength changes in heat treated and acetylated wood

Treesearch

Roger M. Rowell; Rebecca E. Ibach; James McSweeny; Thomas Nilsson

2009-01-01

Reductions in hygroscopicity, increased dimensional stability and decay resistance of heat-treated wood depend on decomposition of a large portion of the hemicelluloses in the wood cell wall. In theory, these hemicelluloses are converted to small organic molecules, water and volatile furan-type intermediates that can polymerize in the cell wall. Reductions in...

Characterization of Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Daniel, I. M.; Chun, H. J.; Karalekas, D.

1994-01-01

Experimental methods were developed, adapted, and applied to the characterization of a metal matrix composite system, namely, silicon carbide/aluminim (SCS-2/6061 Al), and its constituents. The silicon carbide fiber was characterized by determining its modulus, strength, and coefficient of thermal expansion. The aluminum matrix was characterized thermomechanically up to 399 C (750 F) at two strain rates. The unidirectional SiC/Al composite was characterized mechanically under longitudinal, transverse, and in-plane shear loading up to 399 C (750 F). Isothermal and non-isothermal creep behavior was also measured. The applicability of a proposed set of multifactor thermoviscoplastic nonlinear constitutive relations and a computer code was investigated. Agreement between predictions and experimental results was shown in a few cases. The elastoplastic thermomechanical behavior of the composite was also described by a number of new analytical models developed or adapted for the material system studied. These models include the rule of mixtures, composite cylinder model with various thermoelastoplastic analyses and a model based on average field theory. In most cases satisfactory agreement was demonstrated between analytical predictions and experimental results for the cases of stress-strain behavior and thermal deformation behavior at different temperatures. In addition, some models yielded detailed three-dimensional stress distributions in the constituents within the composite.

A cross-national study on the multidimensional characteristics of the five-item psychological demands scale of the Job Content Questionnaire.

PubMed

Choi, BongKyoo; Kawakami, Norito; Chang, SeiJin; Koh, SangBaek; Bjorner, Jakob; Punnett, Laura; Karasek, Robert

2008-01-01

The five-item psychological demands scale of the Job Content Questionnaire (JCQ) has been assumed to be one-dimensional in practice. To examine whether the scale has sufficient internal consistency and external validity to be treated as a single scale, using the cross-national JCQ datasets from the United States, Korea, and Japan. Exploratory factor analyses with 22 JCQ items, confirmatory factor analyses with the five psychological demands items, and correlations analyses with mental health indexes. Generally, exploratory factor analyses displayed the predicted demand/control/support structure with three and four factors extracted. However, at more detailed levels of exploratory and confirmatory factor analyses, the demands scale showed clear evidence of multi-factor structure. The correlations of items and subscales of the demands scale with mental health indexes were similar to those of the full scale in the Korean and Japanese datasets, but not in the U.S. data. In 4 out of 16 sub-samples of the U.S. data, several significant correlations of the components of the demands scale with job dissatisfaction and life dissatisfaction were obscured by the full scale. The multidimensionality of the psychological demands scale should be considered in psychometric analysis and interpretation, occupational epidemiologic studies, and future scale extension.

Advance study of fiber-reinforced self-compacting concrete

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

Mironova, M., E-mail: mirona@imbm.bas.bg; Ivanova, M., E-mail: magdalena.ivanova@imbm.bas.bg; Naidenov, V., E-mail: valna53@mail.bg

2015-10-28

Incorporation in concrete composition of steel macro- and micro – fiber reinforcement with structural function increases the degree of ductility of typically brittle cement-containing composites, which in some cases can replace completely or partially conventional steel reinforcement in the form of rods and meshes. Thus, that can reduce manufacturing, detailing and placement of conventional reinforcement, which enhances productivity and economic efficiency of the building process. In this paper, six fiber-reinforced with different amounts of steel fiber cement-containing self-compacting compositions are investigated. The results of some of their main strength-deformation characteristics are presented. Advance approach for the study of structural andmore » material properties of these type composites is proposed by using the methods of industrial computed tomography. The obtained original tomography results about the microstructure and characteristics of individual structural components make it possible to analyze the effective macro-characteristics of the studied composites. The resulting analytical data are relevant for the purposes of multi-dimensional modeling of these systems. Multifactor structure-mechanical analysis of the obtained with different methods original scientific results is proposed. It is presented a conclusion of the capabilities and effectiveness of complex analysis in the studies to characterize the properties of self-compacting fiber-reinforced concrete.« less

Genetic predictors of long-term response to growth hormone (GH) therapy in children with GH deficiency and Turner syndrome: the influence of a SOCS2 polymorphism.

PubMed

Braz, Adriana F; Costalonga, Everlayny F; Trarbach, Ericka B; Scalco, Renata C; Malaquias, Alexsandra C; Guerra-Junior, Gil; Antonini, Sonir R R; Mendonca, Berenice B; Arnhold, Ivo J P; Jorge, Alexander A L

2014-09-01

There is great interindividual variability in the response to GH therapy. Ascertaining genetic factors can improve the accuracy of growth response predictions. Suppressor of cytokine signaling (SOCS)-2 is an intracellular negative regulator of GH receptor (GHR) signaling. The objective of the study was to assess the influence of a SOCS2 polymorphism (rs3782415) and its interactive effect with GHR exon 3 and -202 A/C IGFBP3 (rs2854744) polymorphisms on adult height of patients treated with recombinant human GH (rhGH). Genotypes were correlated with adult height data of 65 Turner syndrome (TS) and 47 GH deficiency (GHD) patients treated with rhGH, by multiple linear regressions. Generalized multifactor dimensionality reduction was used to evaluate gene-gene interactions. Baseline clinical data were indistinguishable among patients with different genotypes. Adult height SD scores of patients with at least one SOCS2 single-nucleotide polymorphism rs3782415-C were 0.7 higher than those homozygous for the T allele (P < .001). SOCS2 (P = .003), GHR-exon 3 (P= .016) and -202 A/C IGFBP3 (P = .013) polymorphisms, together with clinical factors accounted for 58% of the variability in adult height and 82% of the total height SD score gain. Patients harboring any two negative genotypes in these three different loci (homozygosity for SOCS2 T allele; the GHR exon 3 full-length allele and/or the -202C-IGFBP3 allele) were more likely to achieve an adult height at the lower quartile (odds ratio of 13.3; 95% confidence interval of 3.2-54.2, P = .0001). The SOCS2 polymorphism (rs3782415) has an influence on the adult height of children with TS and GHD after long-term rhGH therapy. Polymorphisms located in GHR, IGFBP3, and SOCS2 loci have an influence on the growth outcomes of TS and GHD patients treated with rhGH. The use of these genetic markers could identify among rhGH-treated patients those who are genetically predisposed to have less favorable outcomes.

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases.

PubMed

Heidema, A Geert; Boer, Jolanda M A; Nagelkerke, Nico; Mariman, Edwin C M; van der A, Daphne L; Feskens, Edith J M

2006-04-21

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases.

An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.

PubMed

Setsirichok, Damrongrit; Tienboon, Phuwadej; Jaroonruang, Nattapong; Kittichaijaroen, Somkit; Wongseree, Waranyu; Piroonratana, Theera; Usavanarong, Touchpong; Limwongse, Chanin; Aporntewan, Chatchawit; Phadoongsidhi, Marong; Chaiyaratana, Nachol

2013-01-01

This article presents the ability of an omnibus permutation test on ensembles of two-locus analyses (2LOmb) to detect pure epistasis in the presence of genetic heterogeneity. The performance of 2LOmb is evaluated in various simulation scenarios covering two independent causes of complex disease where each cause is governed by a purely epistatic interaction. Different scenarios are set up by varying the number of available single nucleotide polymorphisms (SNPs) in data, number of causative SNPs and ratio of case samples from two affected groups. The simulation results indicate that 2LOmb outperforms multifactor dimensionality reduction (MDR) and random forest (RF) techniques in terms of a low number of output SNPs and a high number of correctly-identified causative SNPs. Moreover, 2LOmb is capable of identifying the number of independent interactions in tractable computational time and can be used in genome-wide association studies. 2LOmb is subsequently applied to a type 1 diabetes mellitus (T1D) data set, which is collected from a UK population by the Wellcome Trust Case Control Consortium (WTCCC). After screening for SNPs that locate within or near genes and exhibit no marginal single-locus effects, the T1D data set is reduced to 95,991 SNPs from 12,146 genes. The 2LOmb search in the reduced T1D data set reveals that 12 SNPs, which can be divided into two independent sets, are associated with the disease. The first SNP set consists of three SNPs from MUC21 (mucin 21, cell surface associated), three SNPs from MUC22 (mucin 22), two SNPs from PSORS1C1 (psoriasis susceptibility 1 candidate 1) and one SNP from TCF19 (transcription factor 19). A four-locus interaction between these four genes is also detected. The second SNP set consists of three SNPs from ATAD1 (ATPase family, AAA domain containing 1). Overall, the findings indicate the detection of pure epistasis in the presence of genetic heterogeneity and provide an alternative explanation for the aetiology of T1D in the UK population.

Evidence for epistasis between SLC6A4 and ITGB3 in autism etiology and in the determination of platelet serotonin levels.

PubMed

Coutinho, Ana M; Sousa, Inês; Martins, Madalena; Correia, Catarina; Morgadinho, Teresa; Bento, Celeste; Marques, Carla; Ataíde, Assunção; Miguel, Teresa S; Moore, Jason H; Oliveira, Guiomar; Vicente, Astrid M

2007-04-01

Autism is a neurodevelopmental disorder of unclear etiology. The consistent finding of platelet hyperserotonemia in a proportion of patients and its heritability within affected families suggest that genes involved in the serotonin system play a role in this disorder. The role in autism etiology of seven candidate genes in the serotonin metabolic and neurotransmission pathways and mapping to autism linkage regions (SLC6A4, HTR1A, HTR1D, HTR2A, HTR5A, TPH1 and ITGB3) was analyzed in a sample of 186 nuclear families. The impact of interactions among these genes in autism was assessed using the multifactor-dimensionality reduction (MDR) method in 186 patients and 181 controls. We further evaluated whether the effect of specific gene variants or gene interactions associated with autism etiology might be mediated by their influence on serotonin levels, using the quantitative transmission disequilibrium test (QTDT) and the restricted partition method (RPM), in a sample of 109 autistic children. We report a significant main effect of the HTR5A gene in autism (P = 0.0088), and a significant three-locus model comprising a synergistic interaction between the ITGB3 and SLC6A4 genes with an additive effect of HTR5A (P < 0.0010). In addition to the previously reported contribution of SLC6A4, we found significant associations of ITGB3 haplotypes with serotonin level distribution (P = 0.0163). The most significant models contributing to serotonin distribution were found for interactions between TPH1 rs4537731 and SLC6A4 haplotypes (P = 0.002) and between HTR1D rs6300 and SLC6A4 haplotypes (P = 0.013). In addition to the significant independent effects, evidence for interaction between SLC6A4 and ITGB3 markers was also found. The overall results implicate SLC6A4 and ITGB3 gene interactions in autism etiology and in serotonin level determination, providing evidence for a common underlying genetic mechanism and a molecular explanation for the association of platelet hyperserotonemia with autism.

Multi-Locus Candidate Gene Analyses of Lipid Levels in a Pediatric Turkish Cohort: Lessons Learned on LPL, CETP, LIPC, ABCA1, and SHBG

PubMed Central

Eren, Fatih; Agirbasli, Deniz; White, Marquitta J.; Williams, Scott M

2013-01-01

Abstract Cardiovascular risk factors and atherosclerosis precursors were examined in 365 Turkish children and adolescents. Study participants were recruited at five different state schools. We tested single and multi-locus effects of six polymorphisms from five candidate genes, chosen based on prior known association with lipid levels in adults, for association with low (≤10th percentile) high density lipoprotein cholesterol (HDL-C) and high (≥90th percentile) triglycerides (TG), and the related continuous outcomes. We observed an association between CETP variant rs708272 and low HDL-C (allelic p=0.020, genotypic p=0.046), which was supported by an independent analysis, PRAT (PRAT control p=0.027). Sex-stratified logistic regression analysis showed that the B2 allele of rs708272 decreased odds of being in the lower tenth percentile of HDL-C measurements (OR=0.36, p=0.02) in girls; this direction of effect was also seen in boys but was not significant (OR=0.64, p=0.21). Logistic regression analysis also revealed that the T allele of rs6257 (SHBG) decreased odds of being in the top tenth percentile of TG measurements in boys (OR=0.43, p=0.03). Analysis of lipid levels as a continuous trait revealed a significant association between rs708272 (CETP) and LDL-C levels in males (p=0.02) with the B2B2 genotype group having the lowest mean LDL-C; the same direction of effect was also seen in females (p=0.05). An effect was also seen between rs708272 and HDL-C levels in girls (p=0.01), with the B2B2 genotype having the highest mean HDL-C levels. Multi-locus analysis, using quantitative multifactor dimensionality reduction (qMDR) identified the previously mentioned CETP variant as the best single locus model, and overall model, for predicting HDL-C levels in children. This study provides evidence for association between CETP and low HDL-C phenotype in children, but the results appear to be weaker in children than previous results in adults and may also be subject to gender effects. PMID:23988150

Robust and Comprehensive Analysis of 20 Osteoporosis Candidate Genes by Very High-Density Single-Nucleotide Polymorphism Screen Among 405 White Nuclear Families Identified Significant Association and Gene–Gene Interaction

PubMed Central

Xiong, Dong-Hai; Shen, Hui; Zhao, Lan-Juan; Xiao, Peng; Yang, Tie-Lin; Guo, Yan; Wang, Wei; Guo, Yan-Fang; Liu, Yong-Jun; Recker, Robert R; Deng, Hong-Wen

2007-01-01

Many “novel” osteoporosis candidate genes have been proposed in recent years. To advance our knowledge of their roles in osteoporosis, we screened 20 such genes using a set of high-density SNPs in a large family-based study. Our efforts led to the prioritization of those osteoporosis genes and the detection of gene–gene interactions. Introduction We performed large-scale family-based association analyses of 20 novel osteoporosis candidate genes using 277 single nucleotide polymorphisms (SNPs) for the quantitative trait BMD variation and the qualitative trait osteoporosis (OP) at three clinically important skeletal sites: spine, hip, and ultradistal radius (UD). Materials and Methods One thousand eight hundred seventy-three subjects from 405 white nuclear families were genotyped and analyzed with an average density of one SNP per 4 kb across the 20 genes. We conducted association analyses by SNP- and haplotype-based family-based association test (FBAT) and performed gene–gene interaction analyses using multianalytic approaches such as multifactor-dimensionality reduction (MDR) and conditional logistic regression. Results and Conclusions We detected four genes (DBP, LRP5, CYP17, and RANK) that showed highly suggestive associations (10,000-permutation derived empirical global p ≤ 0.01) with spine BMD/OP; four genes (CYP19, RANK, RANKL, and CYP17) highly suggestive for hip BMD/OP; and four genes (CYP19, BMP2, RANK, and TNFR2) highly suggestive for UD BMD/OP. The associations between BMP2 with UD BMD and those between RANK with OP at the spine, hip, and UD also met the experiment-wide stringent criterion (empirical global p ≤ 0.0007). Sex-stratified analyses further showed that some of the significant associations in the total sample were driven by either male or female subjects. In addition, we identified and validated a two-locus gene–gene interaction model involving GCR and ESR2, for which prior biological evidence exists. Our results suggested the prioritization of osteoporosis candidate genes from among the many proposed in recent years and revealed the significant gene–gene interaction effects influencing osteoporosis risk. PMID:17002564

Association of the variants in the BUD13-ZNF259 genes and the risk of hyperlipidaemia.

PubMed

Aung, Lynn Htet Htet; Yin, Rui-Xing; Wu, Dong-Feng; Wang, Wei; Liu, Cheng-Wu; Pan, Shang-Ling

2014-07-01

The single nucleotide polymorphisms (SNPs) in the BUD13 homolog (BUD13) and zinc finger protein 259 (ZNF259) genes have been associated with one or more serum lipid traits in the European populations. However, little is known about such association in the Chinese populations. Our objectives were to determine the association of the BUD13/ZNF259 SNPs and their haplotypes with hypercholesterolaemia (HCH)/hypertriglyceridaemia (HTG) and to identify the possible gene-gene interactions among these SNPs. Genotyping of 6 SNPs was performed in 634 hyperlipidaemic and 547 normolipidaemic participants. The ZNF259 rs2075290, ZNF259 rs964184 and BUD13 rs10790162 SNPs were significantly associated with serum lipid levels in both HCH and non-HCH populations (P < 0.008-0.001). On single locus analysis, only BUD13 rs10790162 was associated with HCH (OR: 2.23, 95% CI: 1.05, 4.75, P = 0.015). The G-G-A-A-C-C haplotype, carrying rs964184-G-allele, was associated with increased risk of HCH (OR: 1.35, 95% CI: 1.10, 1.66, P = 0.005) and HTG (OR: 1.75, 95% CI: 1.39, 2.21, P = 0.000). The A-C-G-G-C-C and A-C-A-G-T-C haplotypes, carrying rs964184-C-allele, were associated with reduced risk of HCH (OR: 0.77, 95% CI: 0.61, 0.99, P = 0.039 and OR: 0.66, 95% CI: 0.47, 0.94, P = 0.021 respectively). On multifactor dimensionality reduction analyses, the two- to three-locus models showed a significant association with HCH and HTG (P < 0.01-0.001). The BUD13/ZNF259 SNPs, which were significant in the European populations, are also replicable in the Southern Chinese population. Moreover, inter-locus interactions may exist among these SNPs. However, further functional studies are required to clarify how these SNPs and genes actually affect the serum lipid levels. © 2014 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Genetic Variants in CD44 and MAT1A Confer Susceptibility to Acute Skin Reaction in Breast Cancer Patients Undergoing Radiation Therapy

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

Mumbrekar, Kamalesh Dattaram; Bola Sadashiva, Satish Rao; Kabekkodu, Shama Prasada

Purpose: Heterogeneity in radiation therapy (RT)-induced normal tissue toxicity is observed in 10% of cancer patients, limiting the therapeutic outcomes. In addition to treatment-related factors, normal tissue adverse reactions also manifest from genetic alterations in distinct pathways majorly involving DNA damage–repair genes, inflammatory cytokine genes, cell cycle regulation, and antioxidant response. Therefore, the common sequence variants in these radioresponsive genes might modify the severity of normal tissue toxicity, and the identification of the same could have clinical relevance as a predictive biomarker. Methods and Materials: The present study was conducted in a cohort of patients with breast cancer to evaluatemore » the possible associations between genetic variants in radioresponsive genes described previously and the risk of developing RT-induced acute skin adverse reactions. We tested 22 genetic variants reported in 18 genes (ie, NFE2L2, OGG1, NEIL3, RAD17, PTTG1, REV3L, ALAD, CD44, RAD9A, TGFβR3, MAD2L2, MAP3K7, MAT1A, RPS6KB2, ZNF830, SH3GL1, BAX, and XRCC1) using TaqMan assay-based real-time polymerase chain reaction. At the end of RT, the severity of skin damage was scored, and the subjects were dichotomized as nonoverresponders (Radiation Therapy Oncology Group grade <2) and overresponders (Radiation Therapy Oncology Group grade ≥2) for analysis. Results: Of the 22 single nucleotide polymorphisms studied, the rs8193 polymorphism lying in the micro-RNA binding site of 3′-UTR of CD44 was significantly (P=.0270) associated with RT-induced adverse skin reactions. Generalized multifactor dimensionality reduction analysis showed significant (P=.0107) gene–gene interactions between MAT1A and CD44. Furthermore, an increase in the total number of risk alleles was associated with increasing occurrence of overresponses (P=.0302). Conclusions: The genetic polymorphisms in radioresponsive genes act as genetic modifiers of acute normal tissue toxicity outcomes after RT by acting individually (rs8193), by gene–gene interactions (MAT1A and CD44), and/or by the additive effects of risk alleles.« less

Interaction of TLR-IFN and HLA polymorphisms on susceptibility of chronic HBV infection in Southwest Han Chinese.

PubMed

He, Dengming; Tao, Shiqi; Guo, Shimin; Li, Maoshi; Wu, Junqiu; Huang, Hongfei; Guo, Xinwu; Yan, Guohua; Zhu, Peng; Wang, Yuming

2015-08-01

The toll-like receptor-interferon (TLR-IFN) signalling pathway plays a crucial role in HBV infection. Human leucocyte antigen (HLA) polymorphisms are associated with chronic HBV infection by genome wide association study (GWAS). We aimed to explore interaction between TLR-IFN and HLA gene polymorphisms in susceptibility of chronic HBV infection. In the Chinese Southwest Han population, 1191 chronic HBV infection patients and 273 HBV clearance were selected. A total of 39 single nucleotide polymorphism loci in 23 genes of the TLR-IFN pathway and four HLA polymorphism loci associated with chronic HBV infection identified by GWAS were selected for genotyping. SNPStats, QVALUE, and multifactor dimensionality reduction were used for statistical analysis. A significant association was seen in several of the TLR-IFN pathway genes, TLR9 rs352140 (OR = 0.70, P = 0.0088), IL1B rs16944 (OR = 0.67, P = 0.016), IL12B rs3212227 (OR = 1.38, P = 0.021), IFNGR1 rs3799488 (OR = 1.48, P = 0.0048), IFNGR2 rs1059293 (OR = 0.27, P = 0.011), MX1 rs467960 (OR = 0.68, P = 0.022), as well as four loci in HLA, rs3077 (OR = 0.55, P < 0.0001), rs2856718 (OR = 0.60, P = 4e-04), rs9277535 (OR = 0.54, P < 0.0001) and rs7453920 (OR = 0.43, P < 0.0001). A synergistic relationship was seen between rs9277535 and rs16944 (0.13%), rs1143623 and rs6613 (0.10%). The combination of rs9277535 in HLA and rs16944 in IL1B was the best model to predict chronic HBV infection (testing accuracy = 0.6040, P = 0.0010, cross-validation consistency = 10/10). TLR-IFN pathway gene polymorphisms are associated with chronic HBV infection. Interactions with polymorphisms in these genes may be one mechanism by which HLA polymorphisms influence susceptibility to chronic HBV infection, as specific single nucleotide polymorphism combinations are highly predictive of chronic HBV infection. © 2014 The Authors. Liver International Published by John Wiley & Sons Ltd.

Age- and gender-specific epistasis between ADA and TNF-α influences human life-expectancy.

PubMed

Napolioni, Valerio; Carpi, Francesco M; Giannì, Paola; Sacco, Roberto; Di Blasio, Luca; Mignini, Fiorenzo; Lucarini, Nazzareno; Persico, Antonio M

2011-11-01

Aging is a complex phenotype with multiple determinants but a strong genetic component significantly impacts on survival to extreme ages. The dysregulation of immune responses occurring with increasing age is believed to contribute to human morbidity and mortality. Conversely, some genetic determinants of successful aging might reside in those polymorphisms for the immune system genes regulating immune responses. Here we examined the main effects of single loci and multi-locus interactions to test the hypothesis that the adenosine deaminase (ADA) and tumor necrosis factor alpha (TNF-α) genes may influence human life-expectancy. ADA (22G>A, rs73598374) and TNF-α (-308G>A, rs1800629; -238G>A, rs361525) functional SNPs have been determined for 1071 unrelated healthy individuals from Central Italy (18-106 years old) divided into three gender-specific age classes defined according to demographic information and accounting for the different survivals between sexes: for men (women), the first class consists of individuals<66 years old (<73 years old), the second class of individuals 66-88 years old (73-91 years old), and the third class of individuals>88 years old (>91 years old). Single-locus analysis showed that only ADA 22G>A is significantly associated with human life-expectancy in males (comparison 1 (age class 2 vs. age class 1), O.R. 1.943, P=0.036; comparison 2 (age class 3 vs. age class 2), O.R. 0.320, P=0.0056). Age- and gender-specific patterns of epistasis between ADA and TNF-α were found using Generalized Multifactor Dimensionality Reduction (GMDR). In comparison 1, a significant two-loci interaction occurs in females between ADA 22G>A and TNF-α -238G>A (Sign Test P=0.011). In comparison 2, both two-loci and three-loci interaction are significant associated with increased life-expectancy over 88 years in males. In conclusion, we report that a combination of functional SNPs within ADA and TNF-α genes can influence life-expectancy in a gender-specific manner and that males and females follow different pathways to attain longevity. Copyright © 2011 Elsevier Ltd. All rights reserved.

The FOXO1 Gene-Obesity Interaction Increases the Risk of Type 2 Diabetes Mellitus in a Chinese Han Population.

PubMed

Gong, Lilin; Li, Rong; Ren, Wei; Wang, Zengchan; Wang, Zhihong; Yang, Maosheng; Zhang, Suhua

2017-02-01

Here, we aimed to study the effect of the forkhead box O1-insulin receptor substrate 2 (FOXO1-IRS2) gene interaction and the FOXO1 and IRS2 genes-environment interaction for the risk of type 2 diabetes mellitus (T2DM) in a Chinese Han population. We genotyped 7 polymorphism sites of FOXO1 gene and IRS2 gene in 780 unrelated Chinese Han people (474 cases of T2DM, 306 cases of healthy control). The risk of T2DM in individuals with AA genotype for rs7986407 and CC genotype for rs4581585 in FOXO1 gene was 2.092 and 2.57 times higher than that with GG genotype (odds ratio [OR] = 2.092; 95% confidence interval [CI] = 1.178-3.731; P = 0.011) and TT genotype (OR = 2.571; 95% CI = 1.404-4.695; P = 0.002), respectively. The risk of T2DM in individuals with GG genotype for Gly1057Asp in IRS2 gene was 1.42 times higher than that with AA genotype (OR = 1.422; 95% CI = 1.037-1.949; P = 0.029). The other 4 single nucleotide polymorphisms (SNPs) had no significant association with T2DM (P > 0.05). Multifactor dimensionality reduction (MDR) analysis showed that the interaction between SNPs rs7986407 and rs4325426 in FOXO1 gene and waist was the best model confirmed by interaction analysis, closely associating with T2DM. There was an increased risk for T2DM in the case of non-obesity with genotype combined AA/CC, AA/AC or AG/AA for rs7986407 and rs4325426, and obesity with genotype AA for rs7986407 or AA for rs4325426 (OR = 3.976; 95% CI = 1.156-13.675; P value from sign test [P(sign)] = 0.025; P value from permutation test [P(perm)] = 0.000-0.001). Together, this study indicates an association of FOXO1 and IRS2 gene polymorphisms with T2DM in Chinese Han population, supporting FOXO1-obesity interaction as a key factor for the risk of T2DM.

Predictive models to assess risk of type 2 diabetes, hypertension and comorbidity: machine-learning algorithms and validation using national health data from Kuwait—a cohort study

PubMed Central

Farran, Bassam; Channanath, Arshad Mohamed; Behbehani, Kazem; Thanaraj, Thangavel Alphonse

2013-01-01

Objective We build classification models and risk assessment tools for diabetes, hypertension and comorbidity using machine-learning algorithms on data from Kuwait. We model the increased proneness in diabetic patients to develop hypertension and vice versa. We ascertain the importance of ethnicity (and natives vs expatriate migrants) and of using regional data in risk assessment. Design Retrospective cohort study. Four machine-learning techniques were used: logistic regression, k-nearest neighbours (k-NN), multifactor dimensionality reduction and support vector machines. The study uses fivefold cross validation to obtain generalisation accuracies and errors. Setting Kuwait Health Network (KHN) that integrates data from primary health centres and hospitals in Kuwait. Participants 270 172 hospital visitors (of which, 89 858 are diabetic, 58 745 hypertensive and 30 522 comorbid) comprising Kuwaiti natives, Asian and Arab expatriates. Outcome measures Incident type 2 diabetes, hypertension and comorbidity. Results Classification accuracies of >85% (for diabetes) and >90% (for hypertension) are achieved using only simple non-laboratory-based parameters. Risk assessment tools based on k-NN classification models are able to assign ‘high’ risk to 75% of diabetic patients and to 94% of hypertensive patients. Only 5% of diabetic patients are seen assigned ‘low’ risk. Asian-specific models and assessments perform even better. Pathological conditions of diabetes in the general population or in hypertensive population and those of hypertension are modelled. Two-stage aggregate classification models and risk assessment tools, built combining both the component models on diabetes (or on hypertension), perform better than individual models. Conclusions Data on diabetes, hypertension and comorbidity from the cosmopolitan State of Kuwait are available for the first time. This enabled us to apply four different case–control models to assess risks. These tools aid in the preliminary non-intrusive assessment of the population. Ethnicity is seen significant to the predictive models. Risk assessments need to be developed using regional data as we demonstrate the applicability of the American Diabetes Association online calculator on data from Kuwait. PMID:23676796

Accelerating epistasis analysis in human genetics with consumer graphics hardware.

PubMed

Sinnott-Armstrong, Nicholas A; Greene, Casey S; Cancare, Fabio; Moore, Jason H

2009-07-24

Human geneticists are now capable of measuring more than one million DNA sequence variations from across the human genome. The new challenge is to develop computationally feasible methods capable of analyzing these data for associations with common human disease, particularly in the context of epistasis. Epistasis describes the situation where multiple genes interact in a complex non-linear manner to determine an individual's disease risk and is thought to be ubiquitous for common diseases. Multifactor Dimensionality Reduction (MDR) is an algorithm capable of detecting epistasis. An exhaustive analysis with MDR is often computationally expensive, particularly for high order interactions. This challenge has previously been met with parallel computation and expensive hardware. The option we examine here exploits commodity hardware designed for computer graphics. In modern computers Graphics Processing Units (GPUs) have more memory bandwidth and computational capability than Central Processing Units (CPUs) and are well suited to this problem. Advances in the video game industry have led to an economy of scale creating a situation where these powerful components are readily available at very low cost. Here we implement and evaluate the performance of the MDR algorithm on GPUs. Of primary interest are the time required for an epistasis analysis and the price to performance ratio of available solutions. We found that using MDR on GPUs consistently increased performance per machine over both a feature rich Java software package and a C++ cluster implementation. The performance of a GPU workstation running a GPU implementation reduces computation time by a factor of 160 compared to an 8-core workstation running the Java implementation on CPUs. This GPU workstation performs similarly to 150 cores running an optimized C++ implementation on a Beowulf cluster. Furthermore this GPU system provides extremely cost effective performance while leaving the CPU available for other tasks. The GPU workstation containing three GPUs costs $2000 while obtaining similar performance on a Beowulf cluster requires 150 CPU cores which, including the added infrastructure and support cost of the cluster system, cost approximately $82,500. Graphics hardware based computing provides a cost effective means to perform genetic analysis of epistasis using MDR on large datasets without the infrastructure of a computing cluster.

Application of back propagation artificial neural network on genetic variants in adiponectin ADIPOQ, peroxisome proliferator-activated receptor-γ, and retinoid X receptor-α genes and type 2 diabetes risk in a Chinese Han population.

PubMed

Shi, Hui; Lu, Ying; Du, Juan; Du, Wencong; Ye, Xinhua; Yu, Xiaofang; Ma, Jianhua; Cheng, Jinluo; Gao, Yanqin; Cao, Yuanyuan; Zhou, Ling; Li, Qian

2012-03-01

Our study was designed to explore the applied characteristics of the back propagation artificial neural network (BPANN) on studying the genetic variants in adipnectin ADIPOQ, peroxisome proliferator-activated receptor (PPAR)-γ, and retinoid X receptor-α (RXR-α) genes and type 2 diabetes mellitus (T2DM) risks in a Chinese Han population. We used BPANN as the fitting model based on data gathered from T2DM patients (n=913) and normal controls (n=1,001). The mean impact value (MIV) for each input variables were calculated, and the sequence of the factors according to their absolute MIVs was sorted. The results from BPANN were compared with multiple logistic regression analysis, and the generalized multifactor dimensionality reduction (GMDR) method was used to calculate the joint effects of ADIPOQ, PPAR-γ, and RXR-α genes. By BPANN analysis, the sequence according to the importance of the T2DM risk factors was in the order of serum adiponectin level, rs3856806, rs7649121, hypertension, rs3821799, rs17827276, rs12495941, rs4240711, age, rs16861194, waist circumference, rs2241767, rs2920502, rs1063539, alcohol drinking, smoking, hyperlipoproteinemia, gender, rs3132291, T2DM family history, rs4842194, rs822394, rs1801282, rs1045570, rs16861205, rs6537944, body mass index, rs266729, and rs1801282. However, compared with multiple logistic regression analysis, only 11 factors were statistically significant. After overweight and obesity were taken as environment adjustment factors into the analysis, model A2 B4 C5 C6 C8 (rs3856806, rs4240711, rs7649121, rs3821799, rs12495941) was the best model (coefficient of variation consistency=10/10, P=0.0107) in the GMDR method. These results suggested the interactions of ADIPOQ, PPAR-γ, and RXR-α genes might play a role in susceptibility to T2DM. BPANN could be used to analyze the risk factors of diseases and provide more complicated relationships between inputs and outputs.

Study of single nucleotide polymorphisms of tumour necrosis factors and HSP genes in nasopharyngeal carcinoma in North East India.

PubMed

Lakhanpal, Meena; Singh, Laishram Chandreshwor; Rahman, Tashnin; Sharma, Jagnnath; Singh, M Madhumangal; Kataki, Amal Chandra; Verma, Saurabh; Pandrangi, Santhi Latha; Singh, Y Mohan; Wajid, Saima; Kapur, Sujala; Saxena, Sunita

2016-01-01

Nasopharyngeal carcinoma (NPC) is an epithelial tumour with a distinctive racial and geographical distribution. High incidence of NPC has been reported from China, Southeast Asia, and northeast (NE) region of India. The immune mechanism plays incredibly role in pathogenesis of NPC. Tumour necrosis factors (TNFs) and heat shock protein 70 (HSP 70) constitute significant components of innate as well as adaptive host immunity. Multi-analytical approaches including logistic regression (LR), classification and regression tree (CART) and multifactor dimensionality reduction (MDR) were applied in 120 NPC cases and 100 controls to explore high order interactions among TNF-α (-308 G>A), TNF β (+252 A>G), HSP 70-1 (+190 G>C), HSP 70-hom (+2437 T>C) genes and environmental risk factors. TNF β was identified as the primary etiological factor by all three analytical approaches. Individual analysis of results showed protective effect of TNF β GG genotype (adjusted odds ratio (OR2) = 0.27, 95 % CI = 0.125-0.611, P = 0.001), HSP 70 (+2437) CC genotype (OR2 = 0.17, 95 % CI = 0.0430.69, P = 0.013), while AG genotype of TNF β was found significantly associated with risk of NPC (OR2 = 1.97, 95 % CI = 1.019-3.83, P = 0.04). Analysis of environmental factors demonstrated association of alcohol consumption, living in mud houses and use of firewood for cooking as major risk factors for NPC. Individual haplotype association analysis showed significant risk associated with GTGA haplotype (OR = 68.61, 95 % CI = 2.47-190.37, P = 0.013) while a protective effect with CCAA and GCGA haplotypes (OR = 0.19, 95 % CI = 0.05-0.75, P = 0.019; OR = 0.01 95 % CI = 0.05-0.30, P = 0.007). The multi-analytical approaches applied in this study helped in identification of distinct gene-gene and gene-environment interactions significant in risk assessment of NPC.

Synergistic effects of gene polymorphisms of the renin-angiotensin-aldosterone system on essential hypertension in Kazakhs in Xinjiang.

PubMed

Niu, Shudong; Zhang, Bin; Zhang, Keyong; Zhu, Pengcheng; Li, Jingping; Sun, Yujing; He, Ning; Zhang, Mingtao; Gao, Zhiying; Li, Xueyan; Simayi, Amuti; Ge, Jie; Cong, Mingyu; Zhou, Wenna; Qiu, Changchun

2016-01-01

To assess the synergistic effects of gene polymorphisms of the renin-angiotensin-aldosterone system (RAAS) on essential hypertension (EH) in Kazakhs in Xinjiang. A cross-sectional case-control association study was conducted in 52 1 hypertensive and 623 normotensive subjects of Kazakh ethnicity on eight common single nucleotide polymorphisms (SNPs) interspersed over five genes of the RAAS. SNPs were genotyped by polymerase chain reaction-restriction fragment length polymorphism. Interactions among the SNPs were analyzed by the multifactor dimensionality reduction method (MDR). In single-locus analysis, subjects with AGT -6G, ACE D, and CYP11B2 -344C had increased susceptibility to EH (OR: 1.249; 1.425; 1.201). When subgrouped by sex, males with the t allele of REN Taq I had decreased risk for EH (OR: 0.529), and those with AGT -6G and CYP11B2 -344 C had increased risk for EH (OR: 1.498; 1.449). In females, carrying ACE D increased the risk for EH. (OR: 1.327). In six AGT haplotypes, H1 was protective, while H3 increased susceptibility to EH (OR: 0.683; 2.025). Interaction analysis by MDR showed that there was a strong synergistic effect between ACE I/D and CY11B2 (T-344C) and a moderate interaction between both ACE I/D and CY11B2 T-344C and AGT A-6G. There was a strong synergistic effect between ACE I/D and CY11B2 T-344C and a moderate effect between both ACE I/D and CY11B2 T-344C and AGT A-6G. AGT -6G, ACE D, and CY11B2 -344C increased susceptibility to EH. REN Taq I, AGT -6G, CY11B2 -344 C and ACE D were associated with male and female EH, respectively. H1 and H3 of AGT were protective and risk haplotypes, respectively.

Interaction between juniper Juniperus communis L. and its fruit pest insects: Pest abundance, fruit characteristics and seed viability

NASA Astrophysics Data System (ADS)

García, Daniel

1998-12-01

The relationships between the fruit features of Juniperus communis and the presence of fruit pests were studied in Sierra Nevada, SE Spain. The abundance of two insect species — a pulp-sucking scale and a seed-predator wasp — was surveyed with respect both to fruit characteristics and to viability of seeds contained therein. Seed-predator pressure was not significantly related to any fruit characteristics; however, pulp suckers tended to be more abundant in plants with low pulp: seed ratios and high fruit-water content. In addition, fruits with high levels of pulp-sucker attack tended to have higher water content. A multi-factor ANOVA, considering the identity of the plant and the attack of the different pests as factors, showed that plant identity accounts for most of the variation in fruit characteristics. The viability of seeds tended to be lower in plants strongly attacked by both pests. Fruits attacked by seed predators showed significantly lower proportions of viable and unviable seeds than did unattacked fruits. Seed viability was also lower in those fruits heavily attacked by pulp suckers, but this pattern is strongly mediated by plant identity. Pest activity proved to be clearly associated with a direct decrease in juniper reproductive capacity. This loss involved a reduction of the viable-seed number, mainly related to the seed predator, as well as a reduction of fruit attractiveness to frugivorous dispersers, related to the pulp sucker.

Fractional exclusion and braid statistics in one dimension: a study via dimensional reduction of Chern-Simons theory

NASA Astrophysics Data System (ADS)

Ye, Fei; Marchetti, P. A.; Su, Z. B.; Yu, L.

2017-09-01

The relation between braid and exclusion statistics is examined in one-dimensional systems, within the framework of Chern-Simons statistical transmutation in gauge invariant form with an appropriate dimensional reduction. If the matter action is anomalous, as for chiral fermions, a relation between braid and exclusion statistics can be established explicitly for both mutual and nonmutual cases. However, if it is not anomalous, the exclusion statistics of emergent low energy excitations is not necessarily connected to the braid statistics of the physical charged fields of the system. Finally, we also discuss the bosonization of one-dimensional anyonic systems through T-duality. Dedicated to the memory of Mario Tonin.

Bullying among Adolescents in North Cyprus and Turkey: Testing a Multifactor Model

ERIC Educational Resources Information Center

Bayraktar, Fatih

2012-01-01

Peer bullying has been studied since the 1970s. Therefore, a vast literature has accumulated about the various predictors of bullying. However, to date there has been no study which has combined individual-, peer-, parental-, teacher-, and school-related predictors of bullying within a model. In this sense, the main aim of this study was to test a…

Electronic Health Records: Applying Diffusion of Innovation Theory to the Relationship between Multifactor Authentication and EHR Adoption

ERIC Educational Resources Information Center

Lockett, Daeron C.

2014-01-01

Electronic Health Record (EHR) systems are increasingly becoming accepted as future direction of medical record management systems. Programs such as the American Recovery and Reinvestment Act have provided incentives to hospitals that adopt EHR systems. In spite of these incentives, the perception of EHR adoption is that is has not achieved the…

Cross-Cultural Comparisons of University Students' Science Learning Self-Efficacy: Structural Relationships among Factors within Science Learning Self-Efficacy

ERIC Educational Resources Information Center

Wang, Ya-Ling; Liang, Jyh-Chong; Tsai, Chin-Chung

2018-01-01

Science learning self-efficacy could be regarded as a multi-factor belief which comprises different aspects such as cognitive skills, practical work, and everyday application. However, few studies have investigated the relationships among these factors that compose science learning self-efficacy. Also, culture may play an important role in…

The Four-Factor Model of Depressive Symptoms in Dementia Caregivers: A Structural Equation Model of Ethnic Differences

PubMed Central

Roth, David L.; Ackerman, Michelle L.; Okonkwo, Ozioma C.; Burgio, Louis D.

2008-01-01

Previous studies have suggested that 4 latent constructs (depressed affect, well-being, interpersonal problems, somatic symptoms) underlie the item responses on the Center for Epidemiological Studies Depression (CES-D) Scale. This instrument has been widely used in dementia caregiving research, but the fit of this multifactor model and the explanatory contributions of multifactor models have not been sufficiently examined for caregiving samples. The authors subjected CES-D data (N = 1,183) from the initial Resources for Enhancing Alzheimer’s Caregiver Health Study to confirmatory factor analysis methods and found that the 4-factor model provided excellent fit to the observed data. Invariance analyses suggested only minimal item-loading differences across race subgroups and supported the validity of race comparisons on the latent factors. Significant race differences were found on 3 of the 4 latent factors both before and after controlling for demographic covariates. African Americans reported less depressed affect and better well-being than White caregivers, who reported better well-being and fewer interpersonal problems than Hispanic caregivers. These findings clarify and extend previous studies of race differences in depression among diverse samples of dementia caregivers. PMID:18808246

[Risk factors in the living environment of early spontaneous abortion pregnant women].

PubMed

Liu, Xin-yan; Bian, Xu-ming; Han, Jing-xiu; Cao, Zhao-jin; Fan, Guang-sheng; Zhang, Chao; Zhang, Wen-li; Zhang, Shu-zhen; Sun, Xiao-guang

2007-10-01

To study the relationship between early spontaneous abortion and living environment, and explore the risk factors of spontaneous abortion. We conducted analysis based on the interview of 200 spontaneous abortion cases and the matched control (age +/- 2 years) by using multifactor Logistic regression analysis. The proportions of watching TV > or =10 hours/week, operating computer > or =45 hours/week, using copycat, microwave oven and mobile phone, electromagnetism equipment near the dwell or work place, e. g. switch room < or =50 m and launching tower < or =500 m in the cases are significantly higher than those in the controls in single factor analysis (all P < 0.05). After adjusted the effect of other risk factors by multifactor analysis, using microwave oven and mobile phone, contacting abnormal smell of fitment material > or =3 months, having emotional stress during the first term of pregnancy and spontaneous abortion history were significantly associated with risk of spontaneous abortion. The odds ratios of these risk factors were 2.23 and 4.63, respectively. Using microwave oven and mobile phone, contacting abnormal smell of fitment material > or =3 months, having emotional stress during the first term of pregnancy, and spontaneous abortion history are risk factors of early spontaneous abortion.

Fuzzy comprehensive evaluation of multiple environmental factors for swine building assessment and control.

PubMed

Xie, Qiuju; Ni, Ji-Qin; Su, Zhongbin

2017-10-15

In confined swine buildings, temperature, humidity, and air quality are all important for animal health and productivity. However, the current swine building environmental control is only based on temperature; and evaluation and control methods based on multiple environmental factors are needed. In this paper, fuzzy comprehensive evaluation (FCE) theory was adopted for multi-factor assessment of environmental quality in two commercial swine buildings using real measurement data. An assessment index system and membership functions were established; and predetermined weights were given using analytic hierarchy process (AHP) combined with knowledge of experts. The results show that multi-factors such as temperature, humidity, and concentrations of ammonia (NH 3 ), carbon dioxide (CO 2 ), and hydrogen sulfide (H 2 S) can be successfully integrated in FCE for swine building environment assessment. The FCE method has a high correlation coefficient of 0.737 compared with the method of single-factor evaluation (SFE). The FCE method can significantly increase the sensitivity and perform an effective and integrative assessment. It can be used as part of environmental controlling and warning systems for swine building environment management to improve swine production and welfare. Copyright © 2017 Elsevier B.V. All rights reserved.

Effects of Sulfate, Chloride, and Bicarbonate on Iron Stability in a PVC-U Drinking Pipe

PubMed Central

Wang, Jiaying; Tao, Tao; Yan, Hexiang

2017-01-01

In order to describe iron stability in plastic pipes and to ensure the drinking water security, the influence factors and rules for iron adsorption and release were studied, dependent on the Unplasticized poly (vinyl chloride) (PVC-U) drinking pipes employed in this research. In this paper, sulfate, chloride, and bicarbonate, as well as synthesized models, were chosen to investigate the iron stability on the inner wall of PVC-U drinking pipes. The existence of the three kinds of anions could significantly affect the process of iron adsorption, and a positive association was found between the level of anion concentration and the adsorption rate. However, the scaling formed on the inner surface of the pipes would be released into the water under certain conditions. The Larson Index (LI), used for a synthetic consideration of anion effects on iron stability, was selected to investigate the iron release under multi-factor conditions. Moreover, a well fitted linear model was established to gain a better understanding of iron release under multi-factor conditions. The simulation results demonstrated that the linear model was better fitted than the LI model for the prediction of iron release. PMID:28629192

Classification of molecular structure images by using ANN, RF, LBP, HOG, and size reduction methods for early stomach cancer detection

NASA Astrophysics Data System (ADS)

Aytaç Korkmaz, Sevcan; Binol, Hamidullah

2018-03-01

Patients who die from stomach cancer are still present. Early diagnosis is crucial in reducing the mortality rate of cancer patients. Therefore, computer aided methods have been developed for early detection in this article. Stomach cancer images were obtained from Fırat University Medical Faculty Pathology Department. The Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG) features of these images are calculated. At the same time, Sammon mapping, Stochastic Neighbor Embedding (SNE), Isomap, Classical multidimensional scaling (MDS), Local Linear Embedding (LLE), Linear Discriminant Analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Laplacian Eigenmaps methods are used for dimensional the reduction of the features. The high dimension of these features has been reduced to lower dimensions using dimensional reduction methods. Artificial neural networks (ANN) and Random Forest (RF) classifiers were used to classify stomach cancer images with these new lower feature sizes. New medical systems have developed to measure the effects of these dimensions by obtaining features in different dimensional with dimensional reduction methods. When all the methods developed are compared, it has been found that the best accuracy results are obtained with LBP_MDS_ANN and LBP_LLE_ANN methods.

Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification

NASA Astrophysics Data System (ADS)

Sharif, I.; Khare, S.

2014-11-01

With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achieving image classification. Spectral data reduction using Wavelet Decomposition could be useful because it preserves the distinction among spectral signatures. Daubechies wavelets optimally capture the polynomial trends while Haar wavelet is discontinuous and resembles a step function. The performance of these wavelets are compared in terms of classification accuracy and time complexity. This paper shows that wavelet reduction has more separate classes and yields better or comparable classification accuracy. In the context of the dimensionality reduction algorithm, it is found that the performance of classification of Daubechies wavelets is better as compared to Haar wavelet while Daubechies takes more time compare to Haar wavelet. The experimental results demonstrate the classification system consistently provides over 84% classification accuracy.

Metadynamics in the conformational space nonlinearly dimensionally reduced by Isomap.

PubMed

Spiwok, Vojtěch; Králová, Blanka

2011-12-14

Atomic motions in molecules are not linear. This infers that nonlinear dimensionality reduction methods can outperform linear ones in analysis of collective atomic motions. In addition, nonlinear collective motions can be used as potentially efficient guides for biased simulation techniques. Here we present a simulation with a bias potential acting in the directions of collective motions determined by a nonlinear dimensionality reduction method. Ad hoc generated conformations of trans,trans-1,2,4-trifluorocyclooctane were analyzed by Isomap method to map these 72-dimensional coordinates to three dimensions, as described by Brown and co-workers [J. Chem. Phys. 129, 064118 (2008)]. Metadynamics employing the three-dimensional embeddings as collective variables was applied to explore all relevant conformations of the studied system and to calculate its conformational free energy surface. The method sampled all relevant conformations (boat, boat-chair, and crown) and corresponding transition structures inaccessible by an unbiased simulation. This scheme allows to use essentially any parameter of the system as a collective variable in biased simulations. Moreover, the scheme we used for mapping out-of-sample conformations from the 72D to 3D space can be used as a general purpose mapping for dimensionality reduction, beyond the context of molecular modeling. © 2011 American Institute of Physics

Higher-dimensional Bianchi type-VIh cosmologies

NASA Astrophysics Data System (ADS)

Lorenz-Petzold, D.

1985-09-01

The higher-dimensional perfect fluid equations of a generalization of the (1 + 3)-dimensional Bianchi type-VIh space-time are discussed. Bianchi type-V and Bianchi type-III space-times are also included as special cases. It is shown that the Chodos-Detweiler (1980) mechanism of cosmological dimensional-reduction is possible in these cases.

A Recurrent Probabilistic Neural Network with Dimensionality Reduction Based on Time-series Discriminant Component Analysis.

PubMed

Hayashi, Hideaki; Shibanoki, Taro; Shima, Keisuke; Kurita, Yuichi; Tsuji, Toshio

2015-12-01

This paper proposes a probabilistic neural network (NN) developed on the basis of time-series discriminant component analysis (TSDCA) that can be used to classify high-dimensional time-series patterns. TSDCA involves the compression of high-dimensional time series into a lower dimensional space using a set of orthogonal transformations and the calculation of posterior probabilities based on a continuous-density hidden Markov model with a Gaussian mixture model expressed in the reduced-dimensional space. The analysis can be incorporated into an NN, which is named a time-series discriminant component network (TSDCN), so that parameters of dimensionality reduction and classification can be obtained simultaneously as network coefficients according to a backpropagation through time-based learning algorithm with the Lagrange multiplier method. The TSDCN is considered to enable high-accuracy classification of high-dimensional time-series patterns and to reduce the computation time taken for network training. The validity of the TSDCN is demonstrated for high-dimensional artificial data and electroencephalogram signals in the experiments conducted during the study.

Econo-ESA in semantic text similarity.

PubMed

Rahutomo, Faisal; Aritsugi, Masayoshi

2014-01-01

Explicit semantic analysis (ESA) utilizes an immense Wikipedia index matrix in its interpreter part. This part of the analysis multiplies a large matrix by a term vector to produce a high-dimensional concept vector. A similarity measurement between two texts is performed between two concept vectors with numerous dimensions. The cost is expensive in both interpretation and similarity measurement steps. This paper proposes an economic scheme of ESA, named econo-ESA. We investigate two aspects of this proposal: dimensional reduction and experiments with various data. We use eight recycling test collections in semantic text similarity. The experimental results show that both the dimensional reduction and test collection characteristics can influence the results. They also show that an appropriate concept reduction of econo-ESA can decrease the cost with minor differences in the results from the original ESA.

Higher-order gravity in higher dimensions: geometrical origins of four-dimensional cosmology?

NASA Astrophysics Data System (ADS)

Troisi, Antonio

2017-03-01

Determining the cosmological field equations is still very much debated and led to a wide discussion around different theoretical proposals. A suitable conceptual scheme could be represented by gravity models that naturally generalize Einstein theory like higher-order gravity theories and higher-dimensional ones. Both of these two different approaches allow one to define, at the effective level, Einstein field equations equipped with source-like energy-momentum tensors of geometrical origin. In this paper, the possibility is discussed to develop a five-dimensional fourth-order gravity model whose lower-dimensional reduction could provide an interpretation of cosmological four-dimensional matter-energy components. We describe the basic concepts of the model, the complete field equations formalism and the 5-D to 4-D reduction procedure. Five-dimensional f( R) field equations turn out to be equivalent, on the four-dimensional hypersurfaces orthogonal to the extra coordinate, to an Einstein-like cosmological model with three matter-energy tensors related with higher derivative and higher-dimensional counter-terms. By considering the gravity model with f(R)=f_0R^n the possibility is investigated to obtain five-dimensional power law solutions. The effective four-dimensional picture and the behaviour of the geometrically induced sources are finally outlined in correspondence to simple cases of such higher-dimensional solutions.

Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

PubMed Central

Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

2015-01-01

Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

Wake Management Strategies for Reduction of Turbomachinery Fan Noise

NASA Technical Reports Server (NTRS)

Waitz, Ian A.

1998-01-01

The primary objective of our work was to evaluate and test several wake management schemes for the reduction of turbomachinery fan noise. Throughout the course of this work we relied on several tools. These include 1) Two-dimensional steady boundary-layer and wake analyses using MISES (a thin-shear layer Navier-Stokes code), 2) Two-dimensional unsteady wake-stator interaction simulations using UNSFLO, 3) Three-dimensional, steady Navier-Stokes rotor simulations using NEWT, 4) Internal blade passage design using quasi-one-dimensional passage flow models developed at MIT, 5) Acoustic modeling using LINSUB, 6) Acoustic modeling using VO72, 7) Experiments in a low-speed cascade wind-tunnel, and 8) ADP fan rig tests in the MIT Blowdown Compressor.

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

PubMed

Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

The Correlation between Leadership Style and Leader Power

DTIC Science & Technology

2016-04-22

Article 3. DATES COVERED (From - To) 1 February 2015-31 October 2015 4. TITLE AND SUBTITLE The Correlation between Leadership Style and Leader Power...Transformational and Transactional leadership style and leader power. Leadership style was measured by the Multifactor Leadership Questionnaire (MLQ...between the factors representing Leadership Style and Leader Power. The CFA results are contrary to developer’s theories of both scales, but are

The Development of a Tactical-Level Full Range Leadership Measurement Instrument

DTIC Science & Technology

2010-03-01

full range leadership theory has become established as the predominant and most widely researched theory on leadership . The most commonly used survey...instrument to assess full range leadership theory is the Multifactor Leadership Questionnaire, originally developed by Bass in 1985. Although much...existing literature to develop a new full range leadership theory measurement instrument that effectively targets low- to mid-level supervisors, or

Early neurological and cognitive impairments in subclinical cerebrovascular disease.

PubMed

Atanassova, Penka A; Massaldjieva, Radka I; Dimitrov, Borislav D; Aleksandrov, Aleksandar S; Semerdjieva, Maria A; Tsvetkova, Silvia B; Chalakova, Nedka T; Chompalov, Kostadin A

2016-01-01

The subclinical cerebrovascular disease (SCVD) is an important public health problem with demonstrated prognostic significance for stroke, future cognitive decline, and progression to dementia. The earliest possible detection of the silent presence of SCVD in adults at age at risk with normal functioning is very important for both clinical doctors and scientists. Seventy-seven adult volunteers, recruited during the years 2005-2007, with mean age 58.7 (standard deviation 5.9) years, were assessed by four subtests from the Cambridge Neuropsychological Test Automated Battery (CANTAB)-Eclipse cognitive assessment system. We used a questionnaire survey for the presence of cerebrovascular risk factors (CVRFs) such as arterial hypertension, smoking and dyslipidemia, among others, as well as instrumental (Doppler examination) and neurological magnetic resonance imaging (MRI) procedures. Descriptive statistics, comparison (t-test, Chi-square) and univariate methods were used as followed by multifactor logistic regression and receiver operating characteristics analyses. The risk factor questionnaire revealed nonspecific symptoms in 44 (67.7%) of the subjects. In 42 (64.6%) of all 65 subjects, we found at least one of the conventional CVRFs. Abnormal findings from the extra- and trans-cranial Doppler examination were established in 38 (58.5%) of all studied volunteers. Thirty-four subjects had brain MRI (52.3%), and abnormal findings were found in 12 (35.3%) of them. Two of the four subtests of CANTAB tool appeared to be potentially promising predictors of the outcome, as found at the univariate analysis (spatial working memory 1 [SWM1] total errors; intra-extra dimensional set 1 [IED1] total errors [adjusted]; IED2 total trials [adjusted]). We established that the best accuracy of 82.5% was achieved by a multifactor interaction logistic regression model, with the role CVRF and combined CANTAB predictor "IED total ratio (errors/trials) × SWM1 total errors" (P = 0.006). Our results have contributed to the hypothesis that it is possible to identify, by noninvasive methods, subjects at age at risk who have mild degree of cognitive impairment and to establish the significant relationship of this impairment with existing CVRFs, nonspecific symptoms and subclinical abnormal brain Doppler/MRI findings. We created a combined neuropsychological predictor that was able to clearly distinguish between the presence and absence of abnormal Doppler/MRI findings. This pilot prognostic model showed a relatively high accuracy of >80%; therefore, the predictors may serve as biomarkers for SCVD in subjects at age at risk (51-65 years).

Simplifying the representation of complex free-energy landscapes using sketch-map

PubMed Central

Ceriotti, Michele; Tribello, Gareth A.; Parrinello, Michele

2011-01-01

A new scheme, sketch-map, for obtaining a low-dimensional representation of the region of phase space explored during an enhanced dynamics simulation is proposed. We show evidence, from an examination of the distribution of pairwise distances between frames, that some features of the free-energy surface are inherently high-dimensional. This makes dimensionality reduction problematic because the data does not satisfy the assumptions made in conventional manifold learning algorithms We therefore propose that when dimensionality reduction is performed on trajectory data one should think of the resultant embedding as a quickly sketched set of directions rather than a road map. In other words, the embedding tells one about the connectivity between states but does not provide the vectors that correspond to the slow degrees of freedom. This realization informs the development of sketch-map, which endeavors to reproduce the proximity information from the high-dimensionality description in a space of lower dimensionality even when a faithful embedding is not possible. PMID:21730167

Restoration of dimensional reduction in the random-field Ising model at five dimensions

NASA Astrophysics Data System (ADS)

Fytas, Nikolaos G.; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D -2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D =5 . We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3 ≤D <6 to their values in the pure Ising model at D -2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Restoration of dimensional reduction in the random-field Ising model at five dimensions.

PubMed

Fytas, Nikolaos G; Martín-Mayor, Víctor; Picco, Marco; Sourlas, Nicolas

2017-04-01

The random-field Ising model is one of the few disordered systems where the perturbative renormalization group can be carried out to all orders of perturbation theory. This analysis predicts dimensional reduction, i.e., that the critical properties of the random-field Ising model in D dimensions are identical to those of the pure Ising ferromagnet in D-2 dimensions. It is well known that dimensional reduction is not true in three dimensions, thus invalidating the perturbative renormalization group prediction. Here, we report high-precision numerical simulations of the 5D random-field Ising model at zero temperature. We illustrate universality by comparing different probability distributions for the random fields. We compute all the relevant critical exponents (including the critical slowing down exponent for the ground-state finding algorithm), as well as several other renormalization-group invariants. The estimated values of the critical exponents of the 5D random-field Ising model are statistically compatible to those of the pure 3D Ising ferromagnet. These results support the restoration of dimensional reduction at D=5. We thus conclude that the failure of the perturbative renormalization group is a low-dimensional phenomenon. We close our contribution by comparing universal quantities for the random-field problem at dimensions 3≤D<6 to their values in the pure Ising model at D-2 dimensions, and we provide a clear verification of the Rushbrooke equality at all studied dimensions.

Dimensional reduction for a SIR type model

NASA Astrophysics Data System (ADS)

Cahyono, Edi; Soeharyadi, Yudi; Mukhsar

2018-03-01

Epidemic phenomena are often modeled in the form of dynamical systems. Such model has also been used to model spread of rumor, spread of extreme ideology, and dissemination of knowledge. Among the simplest is SIR (susceptible, infected and recovered) model, a model that consists of three compartments, and hence three variables. The variables are functions of time which represent the number of subpopulations, namely suspect, infected and recovery. The sum of the three is assumed to be constant. Hence, the model is actually two dimensional which sits in three-dimensional ambient space. This paper deals with the reduction of a SIR type model into two variables in two-dimensional ambient space to understand the geometry and dynamics better. The dynamics is studied, and the phase portrait is presented. The two dimensional model preserves the equilibrium and the stability. The model has been applied for knowledge dissemination, which has been the interest of knowledge management.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

The Multi-factor Predictive Seis &Gis Model of Ecological, Genetical, Population Health Risk and Bio-geodynamic Processes In Geopathogenic Zones

NASA Astrophysics Data System (ADS)

Bondarenko, Y.

I. Goal and Scope. Human birth rate decrease, death-rate growth and increase of mu- tagenic deviations risk take place in geopathogenic and anthropogenic hazard zones. Such zones create unfavourable conditions for reproductive process of future genera- tions. These negative trends should be considered as a protective answer of the com- plex biosocial system to the appearance of natural and anthropogenic risk factors that are unfavourable for human health. The major goals of scientific evaluation and de- crease of risk of appearance of hazardous processes on the territory of Dnipropetrovsk, along with creation of the multi-factor predictive Spirit-Energy-Information Space "SEIS" & GIS Model of ecological, genetical and population health risk in connection with dangerous bio-geodynamic processes, were: multi-factor modeling and correla- tion of natural and anthropogenic environmental changes and those of human health; determination of indicators that show the risk of destruction structures appearance on different levels of organization and functioning of the city ecosystem (geophys- ical and geochemical fields, soil, hydrosphere, atmosphere, biosphere); analysis of regularities of natural, anthropogenic, and biological rhythms' interactions. II. Meth- ods. The long spatio-temporal researches (Y. Bondarenko, 1996, 2000) have proved that the ecological, genetic and epidemiological processes are in connection with de- velopment of dangerous bio-geophysical and bio-geodynamic processes. Mathemat- ical processing of space photos, lithogeochemical and geophysical maps with use of JEIS o and ERDAS o computer systems was executed at the first stage of forma- tion of multi-layer geoinformation model "Dnipropetrovsk ARC View GIS o. The multi-factor nonlinear correlation between solar activity and cosmic ray variations, geophysical, geodynamic, geochemical, atmospheric, technological, biological, socio- economical processes and oncologic case rate frequency, general and primary popula- tion sickness cases in Dnipropetrovsk City (1.2 million persons) are described by the multi-factor predictive SEIS & GIS model of geopathogenic zones that determines the human health risk and hazards. Results and Conclusions. We have created the SEIS system and multi-factor predictive SEIS model for the analysis of phase-metric spatio- 1 temporal nonlinear correlation and variations of rhythms of human health, ecological, genetic, epidemiological risks, demographic, socio-economic, bio-geophysical, bio- geodynamic processes in geopathogenic hazard zones. Cosmophotomaps "CPM" of vegetation index, anthropogenic-landscape and landscape-geophysical human health risk of Dnipropetrovsk City present synthesis-based elements of multi-layer GIS, which include multispectral images SPOT o, maps of different geophysical, geochem- ical, anthropogenic and citogenic risk factors, maps of integral oncologic case rate frequency, general and primary population sickness cases for administrative districts. Results of multi-layer spatio-temporal correlation of geophysical field parameters and variations of population sickness rate rhythms have enabled us to state grounds and to develop medico-biological and bio-geodynamic classification of geopathogenic zones. Bio-geodynamic model has served to define contours of anthropogenic-landscape and landscape-geophysical human health risk in Dnipropetrovsk City. Biorhythmic vari- ations give foundation for understanding physiological mechanisms of organism`s adaptation to extreme helio-geophysical and bio-geodynamic environmental condi- tions, which are dictated by changes in Multi-factor Correlation Stress Field "MCSF" with deformation of 5D SEIS. Interaction between organism and environment results in continuous superpositioning of external (exogenic) Nuclear-Molecular-Cristallic "NMC" MCSF rhythms on internal (endogenic) Nuclear-Molecular-Cellular "NMCl" MCSF rhythms. Their resonance wave (energy-information) integration and disinte- gration are responsible for structural and functional state of different physiological systems. Herewith, complex restructurization of defense functions blocks the adapta- tion process and may turn to be the primary reason for phase shifting, process and biorhythms hindering, appearance of different deseases. Interaction of biorhythms with natural and anthropogenic rhythms specify the peculiar features of environ- mental adaptation of living species. Such interaction results in correlation of sea- sonal rhythms in variations of thermo-baro-geodynamic "TBG" parameters of am- bient air with toxic concentration and human health risk in Dnipropetrovsk City. Bio-geodynamic analysis of medical and demographic situations has provided for search of spatio-temporal correlation between rhythms of general and primary pop- ulation sickness cases and oncologic case rate frequency, other medico-demographic rhythms, natural processes (helio-geophysical, thermodynamic, geodynamic) and an- thropogenic processes (industrial and houschold waste disposal, toxic emissions and their concentration in ambient air). The year of 1986, the year of minimum helio- geophysical activity "2G1dG1" and maximum anthropogenic processes associated with changes in sickness and death rates of the population of Earth were synchronized. With account of quantum character of SEIS rhythms, 5 reference levels of desyn- chronized helio-geophysical and bio-geodynamic processes affecting population sick- ness rate have been specified within bio-geodynamic models. The first reference level 2 of SEIS desynchronization includes rhythms with period of 22,5 years: ... 1958,2; 1980,7; 2003,2; .... The second reference level of SEIS desynchronization includes rhythms with period of 11,25 years: ... 1980,7; 1992; 2003,2;.... The third reference level covers 5,625-years periodic rhythms2:... 1980,7; 1986,3; 1992; 1997,6; 2003,2; .... The fourth quantum reference level includes rhythms 3 with period of 2,8125 years: ... 1980,7; 1983,5; 1986,3; 1989,1; 1992; 1994,8; 1997,6; 2000,4; 2003,2; .... Rhythms with 1,40625-years period fall is fifth reference level of SEIS desynchro- nization: ...1980,7; 1982,1; 1983,5; 1984,9; 1986,3; 1987,7; 1989,1; 1990,5; 1992; 1993,3; 1994,8; 1996,2; 1997,6; 1999; 2000,4; 2001,8; 2003,2;.... Analysis of alternat- ing medical and demographic situation in Ukraine (1981-1992)and in Dnipropetrovsk (1988-1995)has allowed to back up theoretical model of various-level rhythm quan- tum, with non-linear regularities due to phase-metric spatio-temporal deformation be- ing specified. Application of new technologies of Risk Analysis, Sinthesis and SEIS Modeling at the choice of a burial place for dangerous radioactive wastes in the zone of Chernobyl nuclear disaster (Shestopalov V., Bondarenko Y...., 1998) has shown their very high efficiency in comparison with GIS Analysis. IV.Recommendations and Outlook. In order to draw a conclusion regarding bio-geodynamic modeling of spatio-temporal structure of areas where common childhood sickness rate exists, it is necessary to mention that the only thing that can favour to exact predicting of where and when important catastrophes and epidemies will take place is correct and complex bio-geodynamic modeling. Imperfection of present GIS is the result of the lack of interactive facilities for multi-factor modeling of nonlinear natural and an- thropogenic processes. Equations' coefficients calculated for some areas are often irrelevant when applied to others. In this connection there arises a number of prob- lems concerning practical application and reliability of GIS-models that are used to carry out efficient ecological monitoring. References Bondarenko Y., 1997, Drawing up Cosmophotomaps and Multi-factor Forecasting of Hazard of Development of Dan- gerous Geodynamic Processes in Dnipropetrovsk,The Technically-Natural Problems of failures and catastrophes in connection with development of dangerous geological processes, Kiev, Ukraine, 1997. Bondarenko Y., 1997, The Methodology of a State the Value of Quality of the Ground and the House Level them Ecology-Genetic-Toxic of the human health risk based on multi-layer cartographical model", Experience of application GIS - Technologies for creating Cadastral Systems, Yalta, Ukraine, 1997, p. 39-40. Shestopalov V., Bondarenko Y., Zayonts I., Rudenko Y. , Bohuslavsky A., 1998, Complexation of Structural-Geodynamical and Hydrogeological Methods of Studying Areas to Reveal Geological Structural Perspectives for Deep Isolation of Radioactive Wastes, Field Testing and Associated Modeling of Potential High-Level Nuclear Waste Geologic Disposal Sites, Berkeley, USA, 1998, p.81-82. 3

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging.

PubMed

Ravi, Daniele; Fabelo, Himar; Callic, Gustavo Marrero; Yang, Guang-Zhong

2017-09-01

Recent advances in hyperspectral imaging have made it a promising solution for intra-operative tissue characterization, with the advantages of being non-contact, non-ionizing, and non-invasive. Working with hyperspectral images in vivo, however, is not straightforward as the high dimensionality of the data makes real-time processing challenging. In this paper, a novel dimensionality reduction scheme and a new processing pipeline are introduced to obtain a detailed tumor classification map for intra-operative margin definition during brain surgery. However, existing approaches to dimensionality reduction based on manifold embedding can be time consuming and may not guarantee a consistent result, thus hindering final tissue classification. The proposed framework aims to overcome these problems through a process divided into two steps: dimensionality reduction based on an extension of the T-distributed stochastic neighbor approach is first performed and then a semantic segmentation technique is applied to the embedded results by using a Semantic Texton Forest for tissue classification. Detailed in vivo validation of the proposed method has been performed to demonstrate the potential clinical value of the system.

Dimensionality reduction in epidemic spreading models

NASA Astrophysics Data System (ADS)

Frasca, M.; Rizzo, A.; Gallo, L.; Fortuna, L.; Porfiri, M.

2015-09-01

Complex dynamical systems often exhibit collective dynamics that are well described by a reduced set of key variables in a low-dimensional space. Such a low-dimensional description offers a privileged perspective to understand the system behavior across temporal and spatial scales. In this work, we propose a data-driven approach to establish low-dimensional representations of large epidemic datasets by using a dimensionality reduction algorithm based on isometric features mapping (ISOMAP). We demonstrate our approach on synthetic data for epidemic spreading in a population of mobile individuals. We find that ISOMAP is successful in embedding high-dimensional data into a low-dimensional manifold, whose topological features are associated with the epidemic outbreak. Across a range of simulation parameters and model instances, we observe that epidemic outbreaks are embedded into a family of closed curves in a three-dimensional space, in which neighboring points pertain to instants that are close in time. The orientation of each curve is unique to a specific outbreak, and the coordinates correlate with the number of infected individuals. A low-dimensional description of epidemic spreading is expected to improve our understanding of the role of individual response on the outbreak dynamics, inform the selection of meaningful global observables, and, possibly, aid in the design of control and quarantine procedures.

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Noé, Frank

2018-06-01

Inspired by the success of deep learning techniques in the physical and chemical sciences, we apply a modification of an autoencoder type deep neural network to the task of dimension reduction of molecular dynamics data. We can show that our time-lagged autoencoder reliably finds low-dimensional embeddings for high-dimensional feature spaces which capture the slow dynamics of the underlying stochastic processes—beyond the capabilities of linear dimension reduction techniques.

Modern methods for the quality management of high-rate melt solidification

NASA Astrophysics Data System (ADS)

Vasiliev, V. A.; Odinokov, S. A.; Serov, M. M.

2016-12-01

The quality management of high-rate melt solidification needs combined solution obtained by methods and approaches adapted to a certain situation. Technological audit is recommended to estimate the possibilities of the process. Statistical methods are proposed with the choice of key parameters. Numerical methods, which can be used to perform simulation under multifactor technological conditions, and an increase in the quality of decisions are of particular importance.

An Evaluation of the Relationship between Supervisory Techniques and Organizational Outcomes among the Supervisors in the Agricultural Extension Service in the Eastern Region Districts of Uganda. Summary of Research 81.

ERIC Educational Resources Information Center

Padde, Paul; And Others

A descriptive study examined the relationship between supervisory techniques and organizational outcomes among supervisors in the agricultural extension service in eight districts in eastern Uganda. Self-rating and rater forms of the Multifactor Leadership Questionnaire were sent to 220 extension agents, 8 field supervisors, and 8 deputy field…

Jackknife for Variance Analysis of Multifactor Experiments.

DTIC Science & Technology

1982-05-01

variance-covariance matrix is generated y a subroutine named CORAN (UNIVAC, 1969). The jackknife variances are then punched on computer cards in the same...LEVEL OF: InMte CALL cORAN (oaILa.NSUR.NOAY.D,*OXflRRORR.PCOF.2K.1’)I WRITE IP97111 )1RRN.4 .1:NDAY) 0 a 3fill1UR I .’t UN 001f’..1uŔ:1 .w100710n

FeynArts model file for MSSM transition counterterms from DREG to DRED

NASA Astrophysics Data System (ADS)

Stöckinger, Dominik; Varšo, Philipp

2012-02-01

The FeynArts model file MSSMdreg2dred implements MSSM transition counterterms which can convert one-loop Green functions from dimensional regularization to dimensional reduction. They correspond to a slight extension of the well-known Martin/Vaughn counterterms, specialized to the MSSM, and can serve also as supersymmetry-restoring counterterms. The paper provides full analytic results for the counterterms and gives one- and two-loop usage examples. The model file can simplify combining MS¯-parton distribution functions with supersymmetric renormalization or avoiding the renormalization of ɛ-scalars in dimensional reduction. Program summaryProgram title:MSSMdreg2dred.mod Catalogue identifier: AEKR_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKR_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: LGPL-License [1] No. of lines in distributed program, including test data, etc.: 7600 No. of bytes in distributed program, including test data, etc.: 197 629 Distribution format: tar.gz Programming language: Mathematica, FeynArts Computer: Any, capable of running Mathematica and FeynArts Operating system: Any, with running Mathematica, FeynArts installation Classification: 4.4, 5, 11.1 Subprograms used: Cat Id Title Reference ADOW_v1_0 FeynArts CPC 140 (2001) 418 Nature of problem: The computation of one-loop Feynman diagrams in the minimal supersymmetric standard model (MSSM) requires regularization. Two schemes, dimensional regularization and dimensional reduction are both common but have different pros and cons. In order to combine the advantages of both schemes one would like to easily convert existing results from one scheme into the other. Solution method: Finite counterterms are constructed which correspond precisely to the one-loop scheme differences for the MSSM. They are provided as a FeynArts [2] model file. Using this model file together with FeynArts, the (ultra-violet) regularization of any MSSM one-loop Green function is switched automatically from dimensional regularization to dimensional reduction. In particular the counterterms serve as supersymmetry-restoring counterterms for dimensional regularization. Restrictions: The counterterms are restricted to the one-loop level and the MSSM. Running time: A few seconds to generate typical Feynman graphs with FeynArts.

Multilevel Factorial Experiments for Developing Behavioral Interventions: Power, Sample Size, and Resource Considerations†

PubMed Central

Dziak, John J.; Nahum-Shani, Inbal; Collins, Linda M.

2012-01-01

Factorial experimental designs have many potential advantages for behavioral scientists. For example, such designs may be useful in building more potent interventions, by helping investigators to screen several candidate intervention components simultaneously and decide which are likely to offer greater benefit before evaluating the intervention as a whole. However, sample size and power considerations may challenge investigators attempting to apply such designs, especially when the population of interest is multilevel (e.g., when students are nested within schools, or employees within organizations). In this article we examine the feasibility of factorial experimental designs with multiple factors in a multilevel, clustered setting (i.e., of multilevel multifactor experiments). We conduct Monte Carlo simulations to demonstrate how design elements such as the number of clusters, the number of lower-level units, and the intraclass correlation affect power. Our results suggest that multilevel, multifactor experiments are feasible for factor-screening purposes, because of the economical properties of complete and fractional factorial experimental designs. We also discuss resources for sample size planning and power estimation for multilevel factorial experiments. These results are discussed from a resource management perspective, in which the goal is to choose a design that maximizes the scientific benefit using the resources available for an investigation. PMID:22309956

Cardiovascular disease prevention and lifestyle interventions: effectiveness and efficacy.

PubMed

Haskell, William L

2003-01-01

Over the past half century scientific data support the strong relationship between the way a person or population lives and their risk for developing or dying from cardiovascular disease (CVD). While heredity can be a major factor for some people, their personal health habits and environmental/cultural exposure are more important factors. CVD is a multifactor process that is contributed to by a variety of biological and behavioral characteristics of the person including a number of well-established and emerging risk factors. Not smoking, being physically active, eating a heart healthy diet, staying reasonably lean, and avoiding major stress and depression are the major components of an effective CVD prevention program. For people at high risk of CVD, medications frequently need to be added to a healthy lifestyle to minimize their risk of a heart attack or stroke, particularly in persons with conditions such as hypertension, hypercholesterolemia, or hyperglycemia. Maintaining an effective CVD prevention program in technologically advanced societies cannot be achieved by many high-risk persons without effective and sustained support from a well-organized health care system. Nurse-provided or nurse-coordinated care management programs using an integrated or multifactor approach have been highly effective in reducing CVD morbidity and mortality of high-risk persons.

Multifactor leadership styles and new exposure to workplace bullying: a six-month prospective study

PubMed Central

TSUNO, Kanami; KAWAKAMI, Norito

2014-01-01

This study investigated the prospective association between supervisor leadership styles and workplace bullying. Altogether 404 civil servants from a local government in Japan completed baseline and follow-up surveys. The leadership variables and exposure to bullying were measured by Multifactor Leadership Questionnaire and Negative Acts Questionnaire-Revised, respectively. The prevalence of workplace bullying was 14.8% at baseline and 15.1% at follow-up. Among respondents who did not experience bullying at baseline (n=216), those who worked under the supervisors as higher in passive laissez-faire leadership had a 4.3 times higher risk of new exposure to bullying. On the other hand, respondents whose supervisors with highly considerate of the individual had a 70% lower risk of new exposure to bullying. In the entire sample (n=317), passive laissez-faire leadership was significantly and positively associated, while charisma/inspiration, individual consideration, and contingent reward were negatively associated both after adjusting for demographic and occupational characteristics at baseline, life events during follow-up, and exposure to workplace bullying at baseline. Results indicated that passive laissez-faire and low individual consideration leadership style at baseline were strong predictors of new exposure to bullying and high individual consideration leadership of supervisors/managers could be a preventive factor against bullying. PMID:25382384

Multifactor leadership styles and new exposure to workplace bullying: a six-month prospective study.

PubMed

Tsuno, Kanami; Kawakami, Norito

2015-01-01

This study investigated the prospective association between supervisor leadership styles and workplace bullying. Altogether 404 civil servants from a local government in Japan completed baseline and follow-up surveys. The leadership variables and exposure to bullying were measured by Multifactor Leadership Questionnaire and Negative Acts Questionnaire-Revised, respectively. The prevalence of workplace bullying was 14.8% at baseline and 15.1% at follow-up. Among respondents who did not experience bullying at baseline (n=216), those who worked under the supervisors as higher in passive laissez-faire leadership had a 4.3 times higher risk of new exposure to bullying. On the other hand, respondents whose supervisors with highly considerate of the individual had a 70% lower risk of new exposure to bullying. In the entire sample (n=317), passive laissez-faire leadership was significantly and positively associated, while charisma/inspiration, individual consideration, and contingent reward were negatively associated both after adjusting for demographic and occupational characteristics at baseline, life events during follow-up, and exposure to workplace bullying at baseline. Results indicated that passive laissez-faire and low individual consideration leadership style at baseline were strong predictors of new exposure to bullying and high individual consideration leadership of supervisors/managers could be a preventive factor against bullying.

Sensitivity Analysis of Mechanical Parameters of Different Rock Layers to the Stability of Coal Roadway in Soft Rock Strata

PubMed Central

Zhao, Zeng-hui; Wang, Wei-ming; Gao, Xin; Yan, Ji-xing

2013-01-01

According to the geological characteristics of Xinjiang Ili mine in western area of China, a physical model of interstratified strata composed of soft rock and hard coal seam was established. Selecting the tunnel position, deformation modulus, and strength parameters of each layer as influencing factors, the sensitivity coefficient of roadway deformation to each parameter was firstly analyzed based on a Mohr-Columb strain softening model and nonlinear elastic-plastic finite element analysis. Then the effect laws of influencing factors which showed high sensitivity were further discussed. Finally, a regression model for the relationship between roadway displacements and multifactors was obtained by equivalent linear regression under multiple factors. The results show that the roadway deformation is highly sensitive to the depth of coal seam under the floor which should be considered in the layout of coal roadway; deformation modulus and strength of coal seam and floor have a great influence on the global stability of tunnel; on the contrary, roadway deformation is not sensitive to the mechanical parameters of soft roof; roadway deformation under random combinations of multi-factors can be deduced by the regression model. These conclusions provide theoretical significance to the arrangement and stability maintenance of coal roadway. PMID:24459447

Application of an Instrumental and Computational Approach for Improving the Vibration Behavior of Structural Panels Using a Lightweight Multilayer Composite

PubMed Central

Sánchez, Alberto; García, Manuel; Sebastián, Miguel Angel; Camacho, Ana María

2014-01-01

This work presents a hybrid (experimental-computational) application for improving the vibration behavior of structural components using a lightweight multilayer composite. The vibration behavior of a flat steel plate has been improved by the gluing of a lightweight composite formed by a core of polyurethane foam and two paper mats placed on its faces. This composite enables the natural frequencies to be increased and the modal density of the plate to be reduced, moving about the natural frequencies of the plate out of excitation range, thereby improving the vibration behavior of the plate. A specific experimental model for measuring the Operating Deflection Shape (ODS) has been developed, which enables an evaluation of the goodness of the natural frequencies obtained with the computational model simulated by the finite element method (FEM). The model of composite + flat steel plate determined by FEM was used to conduct parametric study, and the most influential factors for 1st, 2nd and 3rd mode were identified using a multifactor analysis of variance (Multifactor-ANOVA). The presented results can be easily particularized for other cases, as it may be used in cycles of continuous improvement as well as in the product development at the material, piece, and complete-system levels. PMID:24618779

Computational simulation of probabilistic lifetime strength for aerospace materials subjected to high temperature, mechanical fatigue, creep and thermal fatigue

NASA Technical Reports Server (NTRS)

Boyce, Lola; Bast, Callie C.; Trimble, Greg A.

1992-01-01

This report presents the results of a fourth year effort of a research program, conducted for NASA-LeRC by the University of Texas at San Antonio (UTSA). The research included on-going development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subject to a number of effects or primitive variables. These primitive variables may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above-described constitutive equation using actual experimental materials data together with regression analysis of that data, thereby predicting values for the empirical material constants for each effect or primitive variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from industry and the open literature for materials typically for applications in aerospace propulsion system components. Material data for Inconel 718 has been analyzed using the developed methodology.

Computational simulation of probabilistic lifetime strength for aerospace materials subjected to high temperature, mechanical fatigue, creep, and thermal fatigue

NASA Technical Reports Server (NTRS)

Boyce, Lola; Bast, Callie C.; Trimble, Greg A.

1992-01-01

The results of a fourth year effort of a research program conducted for NASA-LeRC by The University of Texas at San Antonio (UTSA) are presented. The research included on-going development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects or primitive variables. These primitive variables may include high temperature, fatigue, or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation was randomized and is included in the computer program, PROMISC. Also included in the research is the development of methodology to calibrate the above-described constitutive equation using actual experimental materials data together with regression analysis of that data, thereby predicting values for the empirical material constants for each effect or primitive variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from industry and the open literature for materials typically for applications in aerospace propulsion system components. Material data for Inconel 718 was analyzed using the developed methodology.

Multilevel factorial experiments for developing behavioral interventions: power, sample size, and resource considerations.

PubMed

Dziak, John J; Nahum-Shani, Inbal; Collins, Linda M

2012-06-01

Factorial experimental designs have many potential advantages for behavioral scientists. For example, such designs may be useful in building more potent interventions by helping investigators to screen several candidate intervention components simultaneously and to decide which are likely to offer greater benefit before evaluating the intervention as a whole. However, sample size and power considerations may challenge investigators attempting to apply such designs, especially when the population of interest is multilevel (e.g., when students are nested within schools, or when employees are nested within organizations). In this article, we examine the feasibility of factorial experimental designs with multiple factors in a multilevel, clustered setting (i.e., of multilevel, multifactor experiments). We conduct Monte Carlo simulations to demonstrate how design elements-such as the number of clusters, the number of lower-level units, and the intraclass correlation-affect power. Our results suggest that multilevel, multifactor experiments are feasible for factor-screening purposes because of the economical properties of complete and fractional factorial experimental designs. We also discuss resources for sample size planning and power estimation for multilevel factorial experiments. These results are discussed from a resource management perspective, in which the goal is to choose a design that maximizes the scientific benefit using the resources available for an investigation. (c) 2012 APA, all rights reserved

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

NASA Astrophysics Data System (ADS)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

Upon Generating (2+1)-dimensional Dynamical Systems

NASA Astrophysics Data System (ADS)

Zhang, Yufeng; Bai, Yang; Wu, Lixin

2016-06-01

Under the framework of the Adler-Gel'fand-Dikii(AGD) scheme, we first propose two Hamiltonian operator pairs over a noncommutative ring so that we construct a new dynamical system in 2+1 dimensions, then we get a generalized special Novikov-Veselov (NV) equation via the Manakov triple. Then with the aid of a special symmetric Lie algebra of a reductive homogeneous group G, we adopt the Tu-Andrushkiw-Huang (TAH) scheme to generate a new integrable (2+1)-dimensional dynamical system and its Hamiltonian structure, which can reduce to the well-known (2+1)-dimensional Davey-Stewartson (DS) hierarchy. Finally, we extend the binormial residue representation (briefly BRR) scheme to the super higher dimensional integrable hierarchies with the help of a super subalgebra of the super Lie algebra sl(2/1), which is also a kind of symmetric Lie algebra of the reductive homogeneous group G. As applications, we obtain a super 2+1 dimensional MKdV hierarchy which can be reduced to a super 2+1 dimensional generalized AKNS equation. Finally, we compare the advantages and the shortcomings for the three schemes to generate integrable dynamical systems.

Wall effects in wind tunnels

NASA Technical Reports Server (NTRS)

Chevallier, J. P.; Vaucheret, X.

1986-01-01

A synthesis of current trends in the reduction and computation of wall effects is presented. Some of the points discussed include: (1) for the two-dimensional, transonic tests, various control techniques of boundary conditions are used with adaptive walls offering high precision in determining reference conditions and residual corrections. A reduction in the boundary layer effects of the lateral walls is obtained at T2; (2) for the three-dimensional tests, the methods for the reduction of wall effects are still seldom applied due to a lesser need and to their complexity; (3) the supports holding the model of the probes have to be taken into account in the estimation of perturbatory effects.

Wideband radar cross section reduction using two-dimensional phase gradient metasurfaces

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

Li, Yongfeng; Qu, Shaobo; Wang, Jiafu

2014-06-02

Phase gradient metasurface (PGMs) are artificial surfaces that can provide pre-defined in-plane wave-vectors to manipulate the directions of refracted/reflected waves. In this Letter, we propose to achieve wideband radar cross section (RCS) reduction using two-dimensional (2D) PGMs. A 2D PGM was designed using a square combination of 49 split-ring sub-unit cells. The PGM can provide additional wave-vectors along the two in-plane directions simultaneously, leading to either surface wave conversion, deflected reflection, or diffuse reflection. Both the simulation and experiment results verified the wide-band, polarization-independent, high-efficiency RCS reduction induced by the 2D PGM.

Target oriented dimensionality reduction of hyperspectral data by Kernel Fukunaga-Koontz Transform

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Ochilov, Shuhrat; Alam, Mohammad S.; Bal, Abdullah

2017-02-01

Principal component analysis (PCA) is a popular technique in remote sensing for dimensionality reduction. While PCA is suitable for data compression, it is not necessarily an optimal technique for feature extraction, particularly when the features are exploited in supervised learning applications (Cheriyadat and Bruce, 2003) [1]. Preserving features belonging to the target is very crucial to the performance of target detection/recognition techniques. Fukunaga-Koontz Transform (FKT) based supervised band reduction technique can be used to provide this requirement. FKT achieves feature selection by transforming into a new space in where feature classes have complimentary eigenvectors. Analysis of these eigenvectors under two classes, target and background clutter, can be utilized for target oriented band reduction since each basis functions best represent target class while carrying least information of the background class. By selecting few eigenvectors which are the most relevant to the target class, dimension of hyperspectral data can be reduced and thus, it presents significant advantages for near real time target detection applications. The nonlinear properties of the data can be extracted by kernel approach which provides better target features. Thus, we propose constructing kernel FKT (KFKT) to present target oriented band reduction. The performance of the proposed KFKT based target oriented dimensionality reduction algorithm has been tested employing two real-world hyperspectral data and results have been reported consequently.

Symmetry reduction and exact solutions of two higher-dimensional nonlinear evolution equations.

PubMed

Gu, Yongyi; Qi, Jianming

2017-01-01

In this paper, symmetries and symmetry reduction of two higher-dimensional nonlinear evolution equations (NLEEs) are obtained by Lie group method. These NLEEs play an important role in nonlinear sciences. We derive exact solutions to these NLEEs via the [Formula: see text]-expansion method and complex method. Five types of explicit function solutions are constructed, which are rational, exponential, trigonometric, hyperbolic and elliptic function solutions of the variables in the considered equations.

Graph embedding and extensions: a general framework for dimensionality reduction.

PubMed

Yan, Shuicheng; Xu, Dong; Zhang, Benyu; Zhang, Hong-Jiang; Yang, Qiang; Lin, Stephen

2007-01-01

Over the past few decades, a large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to provide different solutions to the problem of dimensionality reduction. Despite the different motivations of these algorithms, we present in this paper a general formulation known as graph embedding to unify them within a common framework. In graph embedding, each algorithm can be considered as the direct graph embedding or its linear/kernel/tensor extension of a specific intrinsic graph that describes certain desired statistical or geometric properties of a data set, with constraints from scale normalization or a penalty graph that characterizes a statistical or geometric property that should be avoided. Furthermore, the graph embedding framework can be used as a general platform for developing new dimensionality reduction algorithms. By utilizing this framework as a tool, we propose a new supervised dimensionality reduction algorithm called Marginal Fisher Analysis in which the intrinsic graph characterizes the intraclass compactness and connects each data point with its neighboring points of the same class, while the penalty graph connects the marginal points and characterizes the interclass separability. We show that MFA effectively overcomes the limitations of the traditional Linear Discriminant Analysis algorithm due to data distribution assumptions and available projection directions. Real face recognition experiments show the superiority of our proposed MFA in comparison to LDA, also for corresponding kernel and tensor extensions.

Participatory three dimensional mapping for the preparation of landslide disaster risk reduction program

NASA Astrophysics Data System (ADS)

Kusratmoko, Eko; Wibowo, Adi; Cholid, Sofyan; Pin, Tjiong Giok

2017-07-01

This paper presents the results of applications of participatory three dimensional mapping (P3DM) method for fqcilitating the people of Cibanteng' village to compile a landslide disaster risk reduction program. Physical factors, as high rainfall, topography, geology and land use, and coupled with the condition of demographic and social-economic factors, make up the Cibanteng region highly susceptible to landslides. During the years 2013-2014 has happened 2 times landslides which caused economic losses, as a result of damage to homes and farmland. Participatory mapping is one part of the activities of community-based disaster risk reduction (CBDRR)), because of the involvement of local communities is a prerequisite for sustainable disaster risk reduction. In this activity, participatory mapping method are done in two ways, namely participatory two-dimensional mapping (P2DM) with a focus on mapping of disaster areas and participatory three-dimensional mapping (P3DM) with a focus on the entire territory of the village. Based on the results P3DM, the ability of the communities in understanding the village environment spatially well-tested and honed, so as to facilitate the preparation of the CBDRR programs. Furthermore, the P3DM method can be applied to another disaster areas, due to it becomes a medium of effective dialogue between all levels of involved communities.

Geometric mean for subspace selection.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2009-02-01

Subspace selection approaches are powerful tools in pattern classification and data visualization. One of the most important subspace approaches is the linear dimensionality reduction step in the Fisher's linear discriminant analysis (FLDA), which has been successfully employed in many fields such as biometrics, bioinformatics, and multimedia information management. However, the linear dimensionality reduction step in FLDA has a critical drawback: for a classification task with c classes, if the dimension of the projected subspace is strictly lower than c - 1, the projection to a subspace tends to merge those classes, which are close together in the original feature space. If separate classes are sampled from Gaussian distributions, all with identical covariance matrices, then the linear dimensionality reduction step in FLDA maximizes the mean value of the Kullback-Leibler (KL) divergences between different classes. Based on this viewpoint, the geometric mean for subspace selection is studied in this paper. Three criteria are analyzed: 1) maximization of the geometric mean of the KL divergences, 2) maximization of the geometric mean of the normalized KL divergences, and 3) the combination of 1 and 2. Preliminary experimental results based on synthetic data, UCI Machine Learning Repository, and handwriting digits show that the third criterion is a potential discriminative subspace selection method, which significantly reduces the class separation problem in comparing with the linear dimensionality reduction step in FLDA and its several representative extensions.

Exploring the effects of dimensionality reduction in deep networks for force estimation in robotic-assisted surgery

NASA Astrophysics Data System (ADS)

Aviles, Angelica I.; Alsaleh, Samar; Sobrevilla, Pilar; Casals, Alicia

2016-03-01

Robotic-Assisted Surgery approach overcomes the limitations of the traditional laparoscopic and open surgeries. However, one of its major limitations is the lack of force feedback. Since there is no direct interaction between the surgeon and the tissue, there is no way of knowing how much force the surgeon is applying which can result in irreversible injuries. The use of force sensors is not practical since they impose different constraints. Thus, we make use of a neuro-visual approach to estimate the applied forces, in which the 3D shape recovery together with the geometry of motion are used as input to a deep network based on LSTM-RNN architecture. When deep networks are used in real time, pre-processing of data is a key factor to reduce complexity and improve the network performance. A common pre-processing step is dimensionality reduction which attempts to eliminate redundant and insignificant information by selecting a subset of relevant features to use in model construction. In this work, we show the effects of dimensionality reduction in a real-time application: estimating the applied force in Robotic-Assisted Surgeries. According to the results, we demonstrated positive effects of doing dimensionality reduction on deep networks including: faster training, improved network performance, and overfitting prevention. We also show a significant accuracy improvement, ranging from about 33% to 86%, over existing approaches related to force estimation.

Visualizing phylogenetic tree landscapes.

PubMed

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D projections significantly increase the fit between the tree-to-tree distances and can facilitate the interpretation of the relationship among phylogenetic trees. We demonstrate that the choice of dimensionality reduction method can significantly influence the spatial relationship among a large set of competing phylogenetic trees. We highlight the importance of selecting a dimensionality reduction method to visualize large multi-locus phylogenetic landscapes and demonstrate that 3D projections of mitochondrial tree landscapes better capture the relationship among the trees being compared.

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

PubMed

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

Euclidean sections of protein conformation space and their implications in dimensionality reduction

PubMed Central

Duan, Mojie; Li, Minghai; Han, Li; Huo, Shuanghong

2014-01-01

Dimensionality reduction is widely used in searching for the intrinsic reaction coordinates for protein conformational changes. We find the dimensionality–reduction methods using the pairwise root–mean–square deviation as the local distance metric face a challenge. We use Isomap as an example to illustrate the problem. We believe that there is an implied assumption for the dimensionality–reduction approaches that aim to preserve the geometric relations between the objects: both the original space and the reduced space have the same kind of geometry, such as Euclidean geometry vs. Euclidean geometry or spherical geometry vs. spherical geometry. When the protein free energy landscape is mapped onto a 2D plane or 3D space, the reduced space is Euclidean, thus the original space should also be Euclidean. For a protein with N atoms, its conformation space is a subset of the 3N-dimensional Euclidean space R3N. We formally define the protein conformation space as the quotient space of R3N by the equivalence relation of rigid motions. Whether the quotient space is Euclidean or not depends on how it is parameterized. When the pairwise root–mean–square deviation is employed as the local distance metric, implicit representations are used for the protein conformation space, leading to no direct correspondence to a Euclidean set. We have demonstrated that an explicit Euclidean-based representation of protein conformation space and the local distance metric associated to it improve the quality of dimensionality reduction in the tetra-peptide and β–hairpin systems. PMID:24913095

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models.

PubMed

Ding, Jiarui; Condon, Anne; Shah, Sohrab P

2018-05-21

Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are either not able to uncover the clustering structures in the data or lose global information such as groups of clusters that are close to each other. We present a robust statistical model, scvis, to capture and visualize the low-dimensional structures in single-cell gene expression data. Simulation results demonstrate that low-dimensional representations learned by scvis preserve both the local and global neighbor structures in the data. In addition, scvis is robust to the number of data points and learns a probabilistic parametric mapping function to add new data points to an existing embedding. We then use scvis to analyze four single-cell RNA-sequencing datasets, exemplifying interpretable two-dimensional representations of the high-dimensional single-cell RNA-sequencing data.

Internal Kinematics of the Tongue Following Volume Reduction

PubMed Central

SHCHERBATYY, VOLODYMYR; PERKINS, JONATHAN A.; LIU, ZI-JUN

2008-01-01

This study was undertaken to determine the functional consequences following tongue volume reduction on tongue internal kinematics during mastication and neuromuscular stimulation in a pig model. Six ultrasonic-crystals were implanted into the tongue body in a wedge-shaped configuration which allows recording distance changes in the bilateral length (LENG) and posterior thickness (THICK), as well as anterior (AW), posterior dorsal (PDW), and ventral (PVW) widths in 12 Yucatan-minipigs. Six animals received a uniform mid-sagittal tongue volume reduction surgery (reduction), and the other six had identical incisions without tissue removal (sham). The initial-distances among each crystal-pairs were recorded before, and immediately after surgery to calculate the dimensional losses. Referring to the initial-distance there were 3−66% and 1−4% tongue dimensional losses by the reduction and sham surgeries, respectively. The largest deformation in sham animals during mastication was in AW, significantly larger than LENG, PDW, PVW, and THICK (P < 0.01−0.001). In reduction animals, however, these deformational changes significantly diminished and enhanced in the anterior and posterior tongue, respectively (P < 0.05−0.001). In both groups, neuromuscular stimulation produced deformational ranges that were 2−4 times smaller than those occurred during chewing. Furthermore, reduction animals showed significantly decreased ranges of deformation in PVW, LENG, and THICK (P < 0.05−0.01). These results indicate that tongue volume reduction alters the tongue internal kinematics, and the dimensional losses in the anterior tongue caused by volume reduction can be compensated by increased deformations in the posterior tongue during mastication. This compensatory effect, however, diminishes during stimulation of the hypoglossal nerve and individual tongue muscles. PMID:18484603

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

PubMed

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

A Review on Dimension Reduction

PubMed Central

Ma, Yanyuan; Zhu, Liping

2013-01-01

Summary Summarizing the effect of many covariates through a few linear combinations is an effective way of reducing covariate dimension and is the backbone of (sufficient) dimension reduction. Because the replacement of high-dimensional covariates by low-dimensional linear combinations is performed with a minimum assumption on the specific regression form, it enjoys attractive advantages as well as encounters unique challenges in comparison with the variable selection approach. We review the current literature of dimension reduction with an emphasis on the two most popular models, where the dimension reduction affects the conditional distribution and the conditional mean, respectively. We discuss various estimation and inference procedures in different levels of detail, with the intention of focusing on their underneath idea instead of technicalities. We also discuss some unsolved problems in this area for potential future research. PMID:23794782

Three New (2+1)-dimensional Integrable Systems and Some Related Darboux Transformations

NASA Astrophysics Data System (ADS)

Guo, Xiu-Rong

2016-06-01

We introduce two operator commutators by using different-degree loop algebras of the Lie algebra A1, then under the framework of zero curvature equations we generate two (2+1)-dimensional integrable hierarchies, including the (2+1)-dimensional shallow water wave (SWW) hierarchy and the (2+1)-dimensional Kaup-Newell (KN) hierarchy. Through reduction of the (2+1)-dimensional hierarchies, we get a (2+1)-dimensional SWW equation and a (2+1)-dimensional KN equation. Furthermore, we obtain two Darboux transformations of the (2+1)-dimensional SWW equation. Similarly, the Darboux transformations of the (2+1)-dimensional KN equation could be deduced. Finally, with the help of the spatial spectral matrix of SWW hierarchy, we generate a (2+1) heat equation and a (2+1) nonlinear generalized SWW system containing inverse operators with respect to the variables x and y by using a reduction spectral problem from the self-dual Yang-Mills equations. Supported by the National Natural Science Foundation of China under Grant No. 11371361, the Shandong Provincial Natural Science Foundation of China under Grant Nos. ZR2012AQ011, ZR2013AL016, ZR2015EM042, National Social Science Foundation of China under Grant No. 13BJY026, the Development of Science and Technology Project under Grant No. 2015NS1048 and A Project of Shandong Province Higher Educational Science and Technology Program under Grant No. J14LI58

Reduction of Large Dynamical Systems by Minimization of Evolution Rate

NASA Technical Reports Server (NTRS)

Girimaji, Sharath S.

1999-01-01

Reduction of a large system of equations to a lower-dimensional system of similar dynamics is investigated. For dynamical systems with disparate timescales, a criterion for determining redundant dimensions and a general reduction method based on the minimization of evolution rate are proposed.

Sample Dimensionality Effects on d' and Proportion of Correct Responses in Discrimination Testing.

PubMed

Bloom, David J; Lee, Soo-Yeun

2016-09-01

Products in the food and beverage industry have varying levels of dimensionality ranging from pure water to multicomponent food products, which can modify sensory perception and possibly influence discrimination testing results. The objectives of the study were to determine the impact of (1) sample dimensionality and (2) complex formulation changes on the d' and proportion of correct response of the 3-AFC and triangle methods. Two experiments were conducted using 47 prescreened subjects who performed either triangle or 3-AFC test procedures. In Experiment I, subjects performed 3-AFC and triangle tests using model solutions with different levels of dimensionality. Samples increased in dimensionality from 1-dimensional sucrose in water solution to 3-dimensional sucrose, citric acid, and flavor in water solution. In Experiment II, subjects performed 3-AFC and triangle tests using 3-dimensional solutions. Sample pairs differed in all 3 dimensions simultaneously to represent complex formulation changes. Two forms of complexity were compared: dilution, where all dimensions decreased in the same ratio, and compensation, where a dimension was increased to compensate for a reduction in another. The proportion of correct responses decreased for both methods when the dimensionality was increased from 1- to 2-dimensional samples. No reduction in correct responses was observed from 2- to 3-dimensional samples. No significant differences in d' were demonstrated between the 2 methods when samples with complex formulation changes were tested. Results reveal an impact on proportion of correct responses due to sample dimensionality and should be explored further using a wide range of sample formulations. © 2016 Institute of Food Technologists®

Actor-network Procedures: Modeling Multi-factor Authentication, Device Pairing, Social Interactions

DTIC Science & Technology

2011-08-29

unmodifiable properties of your body; or the capabilities that you cannot convey to others, such as your handwriting . An identity can thus be determined by...network, two principals with the same set of secrets but, say , different computational powers, can be distinguished by timing their responses. Or they... says that configurations are finite sets. Partially ordered multisets, or pomsets were introduced and extensively studied by Vaughan Pratt and his

A remote sensing-assisted risk rating study to predict oak decline and recovery in the Missouri Ozark Highlands, USA

Treesearch

Cuizhen Wang; Hong S. He; John M. Kabrick

2008-01-01

Forests in the Ozark Highlands underwent widespread oak decline affected by severe droughts in 1999-2000. In this study, the differential normalized difference water index was calculated to detect crown dieback. A multi-factor risk rating system was built to map risk levels of stands. As a quick response to drought, decline in 2000 mostly occurred in stands at low to...

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

NASA Astrophysics Data System (ADS)

Cui, Tiangang; Marzouk, Youssef; Willcox, Karen

2016-06-01

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

Nonlinear dimensionality reduction of data lying on the multicluster manifold.

PubMed

Meng, Deyu; Leung, Yee; Fung, Tung; Xu, Zongben

2008-08-01

A new method, which is called decomposition-composition (D-C) method, is proposed for the nonlinear dimensionality reduction (NLDR) of data lying on the multicluster manifold. The main idea is first to decompose a given data set into clusters and independently calculate the low-dimensional embeddings of each cluster by the decomposition procedure. Based on the intercluster connections, the embeddings of all clusters are then composed into their proper positions and orientations by the composition procedure. Different from other NLDR methods for multicluster data, which consider associatively the intracluster and intercluster information, the D-C method capitalizes on the separate employment of the intracluster neighborhood structures and the intercluster topologies for effective dimensionality reduction. This, on one hand, isometrically preserves the rigid-body shapes of the clusters in the embedding process and, on the other hand, guarantees the proper locations and orientations of all clusters. The theoretical arguments are supported by a series of experiments performed on the synthetic and real-life data sets. In addition, the computational complexity of the proposed method is analyzed, and its efficiency is theoretically analyzed and experimentally demonstrated. Related strategies for automatic parameter selection are also examined.

Clustering and Dimensionality Reduction to Discover Interesting Patterns in Binary Data

NASA Astrophysics Data System (ADS)

Palumbo, Francesco; D'Enza, Alfonso Iodice

The attention towards binary data coding increased consistently in the last decade due to several reasons. The analysis of binary data characterizes several fields of application, such as market basket analysis, DNA microarray data, image mining, text mining and web-clickstream mining. The paper illustrates two different approaches exploiting a profitable combination of clustering and dimensionality reduction for the identification of non-trivial association structures in binary data. An application in the Association Rules framework supports the theory with the empirical evidence.

Laser speckle reduction due to spatial and angular diversity introduced by fast scanning micromirror.

PubMed

Akram, M Nadeem; Tong, Zhaomin; Ouyang, Guangmin; Chen, Xuyuan; Kartashov, Vladimir

2010-06-10

We utilize spatial and angular diversity to achieve speckle reduction in laser illumination. Both free-space and imaging geometry configurations are considered. A fast two-dimensional scanning micromirror is employed to steer the laser beam. A simple experimental setup is built to demonstrate the application of our technique in a two-dimensional laser picture projection. Experimental results show that the speckle contrast factor can be reduced down to 5% within the integration time of the detector.

Argyres–Douglas theories, S 1 reductions, and topological symmetries

DOE PAGES

Buican, Matthew; Nishinaka, Takahiro

2015-12-21

In a recent paper, we proposed closed-form expressions for the superconformal indices of the (A(1), A(2n-3)) and(A(1), D-2n) Argyres-Douglas (AD) superconformal field theories (SCFTs) in the Schur limit. Following up on our results, we turn our attention to the small S-1 regime of these indices. As expected on general grounds, our study reproduces the S-3 partition functions of the resulting dimensionally reduced theories. However, we show that in all cases-with the exception of the reduction of the (A(1), D-4) SCFTcertain imaginary partners of real mass terms are turned on in the corresponding mirror theories. We interpret these deformations as Rmore » symmetry mixing with the topological symmetries of the direct S-1 reductions. Moreover, we argue that these shifts occur in any of our theories whose four-dimensional N = 2 superconformal U(1)(R) symmetry does not obey an SU(2) quantization condition. We then use our R symmetry map to find the fourdimensional ancestors of certain three-dimensional operators. Somewhat surprisingly, this picture turns out to imply that the scaling dimensions of many of the chiral operators of the four-dimensional theory are encoded in accidental symmetries of the three-dimensional theory. We also comment on the implications of our work on the space of general N = 2 SCFTs.« less

Argyres–Douglas theories, S 1 reductions, and topological symmetries

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

Buican, Matthew; Nishinaka, Takahiro

In a recent paper, we proposed closed-form expressions for the superconformal indices of the (A(1), A(2n-3)) and(A(1), D-2n) Argyres-Douglas (AD) superconformal field theories (SCFTs) in the Schur limit. Following up on our results, we turn our attention to the small S-1 regime of these indices. As expected on general grounds, our study reproduces the S-3 partition functions of the resulting dimensionally reduced theories. However, we show that in all cases-with the exception of the reduction of the (A(1), D-4) SCFTcertain imaginary partners of real mass terms are turned on in the corresponding mirror theories. We interpret these deformations as Rmore » symmetry mixing with the topological symmetries of the direct S-1 reductions. Moreover, we argue that these shifts occur in any of our theories whose four-dimensional N = 2 superconformal U(1)(R) symmetry does not obey an SU(2) quantization condition. We then use our R symmetry map to find the fourdimensional ancestors of certain three-dimensional operators. Somewhat surprisingly, this picture turns out to imply that the scaling dimensions of many of the chiral operators of the four-dimensional theory are encoded in accidental symmetries of the three-dimensional theory. We also comment on the implications of our work on the space of general N = 2 SCFTs.« less

Features in chemical kinetics. I. Signatures of self-emerging dimensional reduction from a general format of the evolution law

NASA Astrophysics Data System (ADS)

Nicolini, Paolo; Frezzato, Diego

2013-06-01

Simplification of chemical kinetics description through dimensional reduction is particularly important to achieve an accurate numerical treatment of complex reacting systems, especially when stiff kinetics are considered and a comprehensive picture of the evolving system is required. To this aim several tools have been proposed in the past decades, such as sensitivity analysis, lumping approaches, and exploitation of time scales separation. In addition, there are methods based on the existence of the so-called slow manifolds, which are hyper-surfaces of lower dimension than the one of the whole phase-space and in whose neighborhood the slow evolution occurs after an initial fast transient. On the other hand, all tools contain to some extent a degree of subjectivity which seems to be irremovable. With reference to macroscopic and spatially homogeneous reacting systems under isothermal conditions, in this work we shall adopt a phenomenological approach to let self-emerge the dimensional reduction from the mathematical structure of the evolution law. By transforming the original system of polynomial differential equations, which describes the chemical evolution, into a universal quadratic format, and making a direct inspection of the high-order time-derivatives of the new dynamic variables, we then formulate a conjecture which leads to the concept of an "attractiveness" region in the phase-space where a well-defined state-dependent rate function ω has the simple evolution dot{ω }= - ω ^2 along any trajectory up to the stationary state. This constitutes, by itself, a drastic dimensional reduction from a system of N-dimensional equations (being N the number of chemical species) to a one-dimensional and universal evolution law for such a characteristic rate. Step-by-step numerical inspections on model kinetic schemes are presented. In the companion paper [P. Nicolini and D. Frezzato, J. Chem. Phys. 138, 234102 (2013)], 10.1063/1.4809593 this outcome will be naturally related to the appearance (and hence, to the definition) of the slow manifolds.

Low-resistance gateless high electron mobility transistors using three-dimensional inverted pyramidal AlGaN/GaN surfaces

NASA Astrophysics Data System (ADS)

So, Hongyun; Senesky, Debbie G.

2016-01-01

In this letter, three-dimensional gateless AlGaN/GaN high electron mobility transistors (HEMTs) were demonstrated with 54% reduction in electrical resistance and 73% increase in surface area compared with conventional gateless HEMTs on planar substrates. Inverted pyramidal AlGaN/GaN surfaces were microfabricated using potassium hydroxide etched silicon with exposed (111) surfaces and metal-organic chemical vapor deposition of coherent AlGaN/GaN thin films. In addition, electrical characterization of the devices showed that a combination of series and parallel connections of the highly conductive two-dimensional electron gas along the pyramidal geometry resulted in a significant reduction in electrical resistance at both room and high temperatures (up to 300 °C). This three-dimensional HEMT architecture can be leveraged to realize low-power and reliable power electronics, as well as harsh environment sensors with increased surface area.

A data reduction package for multiple object spectroscopy

NASA Technical Reports Server (NTRS)

Hill, J. M.; Eisenhamer, J. D.; Silva, D. R.

1986-01-01

Experience with fiber-optic spectrometers has demonstrated improvements in observing efficiency for clusters of 30 or more objects that must in turn be matched by data reduction capability increases. The Medusa Automatic Reduction System reduces data generated by multiobject spectrometers in the form of two-dimensional images containing 44 to 66 individual spectra, using both software and hardware improvements to efficiently extract the one-dimensional spectra. Attention is given to the ridge-finding algorithm for automatic location of the spectra in the CCD frame. A simultaneous extraction of calibration frames allows an automatic wavelength calibration routine to determine dispersion curves, and both line measurements and cross-correlation techniques are used to determine galaxy redshifts.

Spectral Regression Discriminant Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Pan, Y.; Wu, J.; Huang, H.; Liu, J.

2012-08-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.

Stimulus Equalization: Temporary Reduction of Stimulus Complexity to Facilitate Discrimination Learning.

ERIC Educational Resources Information Center

Hoko, J. Aaron; LeBlanc, Judith M.

1988-01-01

Because disabled learners may profit from procedures using gradual stimulus change, this study utilized a microcomputer to investigate the effectiveness of stimulus equalization, an error reduction procedure involving an abrupt but temporary reduction of dimensional complexity. The procedure was found to be generally effective and implications for…

A two-dimensional lattice equation as an extension of the Heideman-Hogan recurrence

NASA Astrophysics Data System (ADS)

Kamiya, Ryo; Kanki, Masataka; Mase, Takafumi; Tokihiro, Tetsuji

2018-03-01

We consider a two dimensional extension of the so-called linearizable mappings. In particular, we start from the Heideman-Hogan recurrence, which is known as one of the linearizable Somos-like recurrences, and introduce one of its two dimensional extensions. The two dimensional lattice equation we present is linearizable in both directions, and has the Laurent and the coprimeness properties. Moreover, its reduction produces a generalized family of the Heideman-Hogan recurrence. Higher order examples of two dimensional linearizable lattice equations related to the Dana Scott recurrence are also discussed.

Performance and analysis of a three-dimensional nonorthogonal laser Doppler anemometer

NASA Technical Reports Server (NTRS)

Snyder, P. K.; Orloff, K. L.; Aoyagi, K.

1981-01-01

A three dimensional laser Doppler anemometer with a nonorthogonal third axis coupled by 14 deg was designed and tested. A highly three dimensional flow field of a jet in a crossflow was surveyed to test the three dimensional capability of the instrument. Sample data are presented demonstrating the ability of the 3D LDA to resolve three orthogonal velocity components. Modifications to the optics, signal processing electronics, and data reduction methods are suggested.

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

Fatigue failure of materials under broad band random vibrations

NASA Technical Reports Server (NTRS)

Huang, T. C.; Lanz, R. W.

1971-01-01

The fatigue life of material under multifactor influence of broad band random excitations has been investigated. Parameters which affect the fatigue life are postulated to be peak stress, variance of stress and the natural frequency of the system. Experimental data were processed by the hybrid computer. Based on the experimental results and regression analysis a best predicting model has been found. All values of the experimental fatigue lives are within the 95% confidence intervals of the predicting equation.

An Economical Multifactor within-Subject Design Robust against Trend and Carryover Effects.

DTIC Science & Technology

1985-10-17

ORGANIZATION REPORT NUMBER (S) S. MONIT ,,M.,,...---. 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Essex...Road Orlando, FL 32813 Orlando, FL 32803 Ba. NAME OF FUNDING/SPONSORING " Sb. OFFICE SYMBOL 9. PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER ...ORGANIZATION (If applicable) S6~1332- &/. 0.-/195𔃺 Sc. ADDRESS (City, State, and ZIP Code) 10. SOURCE OF FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT

[Chemical and sensory characterization of tea (Thea sinensis) consumed in Chile].

PubMed

Wittig de Penna, Emma; José Zúñiga, María; Fuenzalida, Regina; López-Planes, Reinaldo

2005-03-01

By means of descriptive analysis four varieties of tea (Thea sinensis) were assesed: Argentinean OP (orange pekoe) tea (black), Brazilian OP tea (black), Ceylan OP tea (black) and Darjeeling OP tea (green). The appearance of dry tea leaves were qualitatively characterized comparing with dry leaves standard. The attributes: colour, form, regularity of the leaves, fibre and stem cutting were evaluated The differences obtained were related to the differences produced by the effect of the fermentation process. Flavour and aroma descriptors of the tea liqueur were generated by a trained panel. Colour and astringency were evaluated in comparison with qualified standards using non structured linear scales. In order to relate the sensory analysis and the chemical composition for the different varieties of tea, following determinations were made: chemical moisture, dry material, aqueous extract, tannin and caffeine. Through multifactor regression analysis the equations in relation to the following chemical parameters were determined. Dry material, aqueous extract and tannins for colour and moisture, dry material and aqueous extract for astringency, respectively. Statistical analysis through ANOVA (3 variation sources: samples, judges and replications) showed for samples four significant different groups for astringency and three different groups for colour. No significant differences between judges or repetitions were found. By multifactor regression analysis of both, colour and astringency, on their dependence of chemist results were calculated in order to asses the corresponding equations.

A multi-factor designation method for mapping particulate-pollution control zones in China.

PubMed

Qin, Y; Xie, S D

2011-09-01

A multi-factor designation method for mapping particulate-pollution control zones was brought out through synthetically considering PM(10) pollution status, PM(10) anthropogenic emissions, fine particle pollution, long-range transport and economic situation. According to this method, China was divided into four different particulate-pollution control regions: PM Suspended Control Region, PM(10) Pollution Control Region, PM(2.5) Pollution Control Region and PM(10) and PM(2.5) Common Control Region, which accounted for 69.55%, 9.66%, 4.67% and 16.13% of China's territory, respectively. The PM(10) and PM(2.5) Common Control Region was mainly distributed in Bohai Region, Yangtze River Delta, Pearl River Delta, eastern of Sichuan province and Chongqing municipality, calling for immediate control of both PM(10) and PM(2.5). Cost-effective control effects can be achieved through concentrating efforts on PM(10) and PM(2.5) Common Control Region to address 60.32% of national PM(10) anthropogenic emissions. Air quality in districts belonging to PM(2.5) Pollution Control Region suggested that Chinese national ambient air quality standard for PM(10) was not strict enough. The result derived from application to China proved that this approach was feasible for mapping pollution control regions for a country with vast territory, complicated pollution characteristics and limited available monitoring data. Copyright © 2011 Elsevier B.V. All rights reserved.

Can elevated CO2 modify regeneration from seed banks of floating freshwater marshes subjected to rising sea-level?

USGS Publications Warehouse

Middleton, Beth A.; McKee, Karen L.

2012-01-01

Higher atmospheric concentrations of CO2 can offset the negative effects of flooding or salinity on plant species, but previous studies have focused on mature, rather than regenerating vegetation. This study examined how interacting environments of CO2, water regime, and salinity affect seed germination and seedling biomass of floating freshwater marshes in the Mississippi River Delta, which are dominated by C3 grasses, sedges, and forbs. Germination density and seedling growth of the dominant species depended on multifactor interactions of CO2 (385 and 720 μl l-1) with flooding (drained, +8-cm depth, +8-cm depth-gradual) and salinity (0, 6% seawater) levels. Of the three factors tested, salinity was the most important determinant of seedling response patterns. Species richness (total = 19) was insensitive to CO2. Our findings suggest that for freshwater marsh communities, seedling response to CO2 is species-specific and secondary to salinity and flooding effects. Elevated CO2 did not ameliorate flooding or salinity stress. Consequently, climate-related changes in sea level or human-caused alterations in hydrology may override atmospheric CO2 concentrations in driving shifts in this plant community. The results of this study suggest caution in making extrapolations from species-specific responses to community-level predictions without detailed attention to the nuances of multifactor responses.

An assessment of two-step linear regression and a multifactor probit analysis as alternatives to acute to chronic ratios in the estimation of chronic response from acute toxicity data to derive water quality guidelines.

PubMed

Slaughter, Andrew R; Palmer, Carolyn G; Muller, Wilhelmine J

2007-04-01

In aquatic ecotoxicology, acute to chronic ratios (ACRs) are often used to predict chronic responses from available acute data to derive water quality guidelines, despite many problems associated with this method. This paper explores the comparative protectiveness and accuracy of predicted guideline values derived from the ACR, linear regression analysis (LRA), and multifactor probit analysis (MPA) extrapolation methods applied to acute toxicity data for aquatic macroinvertebrates. Although the authors of the LRA and MPA methods advocate the use of extrapolated lethal effects in the 0.01% to 10% lethal concentration (LC0.01-LC10) range to predict safe chronic exposure levels to toxicants, the use of an extrapolated LC50 value divided by a safety factor of 5 was in addition explored here because of higher statistical confidence surrounding the LC50 value. The LRA LC50/5 method was found to compare most favorably with available experimental chronic toxicity data and was therefore most likely to be sufficiently protective, although further validation with the use of additional species is needed. Values derived by the ACR method were the least protective. It is suggested that there is an argument for the replacement of ACRs in developing water quality guidelines by the LRA LC50/5 method.

Soil moisture surpasses elevated CO2 and temperature as a control on soil carbon dynamics in a multi-factor climate change experiment

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

Garten Jr, Charles T; Classen, Aimee T; Norby, Richard J

2009-01-01

Some single-factor experiments suggest that elevated CO2 concentrations can increase soil carbon, but few experiments have examined the effects of interacting environmental factors on soil carbon dynamics. We undertook studies of soil carbon and nitrogen in a multi-factor (CO2 x temperature x soil moisture) climate change experiment on a constructed old-field ecosystem. After four growing seasons, elevated CO2 had no measurable effect on carbon and nitrogen concentrations in whole soil, particulate organic matter (POM), and mineral-associated organic matter (MOM). Analysis of stable carbon isotopes, under elevated CO2, indicated between 14 and 19% new soil carbon under two different watering treatmentsmore » with as much as 48% new carbon in POM. Despite significant belowground inputs of new organic matter, soil carbon concentrations and stocks in POM declined over four years under soil moisture conditions that corresponded to prevailing precipitation inputs (1,300 mm yr-1). Changes over time in soil carbon and nitrogen under a drought treatment (approximately 20% lower soil water content) were not statistically significant. Reduced soil moisture lowered soil CO2 efflux and slowed soil carbon cycling in the POM pool. In this experiment, soil moisture (produced by different watering treatments) was more important than elevated CO2 and temperature as a control on soil carbon dynamics.« less

Interaction effects among IFN-γ+874, IL-2-330, IL-10-1082, IL-10-592 and IL-4-589 polymorphisms on the clinical progression of subjects infected with hepatitis B virus and/or hepatitis C virus: a retrospective nested case–control study

PubMed Central

Gao, Qiu-Ju; Xie, Jia-Xin; Wang, Li-Min; Zhou, Qiang; Zhang, Shi-Yong

2017-01-01

Background The natural outcomes of hepatitis B virus (HBV) and/or hepatitis C virus (HCV) infections vary considerably among individuals The infection may heal naturally, or patients may succumb to chronic liver diseases, including chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. The mechanism is not fully understood. Objectives To evaluate the interaction among four single nucleotide polymorphisms (SNPs) and their influence on different clinical outcomes. Methods 277 individuals infected with HBV and/or HCV, including 81 patients with chronic hepatitis B and C, 122 asymptomatic HBV and/or HCV carriers and 74 controls who cleared HBV and HCV spontaneously, were involved in this study. The SNPs of four genes (rs2069762/−330 G/T of IL-2, rs2430561/+874A>T of IFN-γ, rs1800896/−1082G>A and rs1800872/−592C>A of IL-10 and rs2243250/−589C>T of IL-4) were analysed using restriction fragment length polymorphism-polymerase chain reaction or sequence-specific primer PCR. The gene–gene interactions were assessed using the multifactor-dimensionality reduction method. Results Interleukin (IL)-10-592 AC and IL-4-589 CC/CT showed a synergistic effect on liver inflammatory injury (p<0.01), whereas interferon (IFN)-γ+874  AA and IL-2-330 TT had a synergistic impact (p<0.05). IFN-γ+874  AA and IL-10-1082 AA had an antagonistic effect (p<0.01) on the clinical progression, including asymptomatic HBV and HCV carriers and chronic hepatitis. IL-2-330 TT and IL-10-1082 AA synergistically influenced the clinical outcome (p<0.05). IFN-γ+874 AA, IL-2-330 TT and IL-10-1082 AA interactively affected the clinical outcome including asymptomatic HBV and HCV carriers and chronic hepatitis (p<0.05). Conclusions Interactions among polymorphisms of IFN-γ+874 AA, IL-2-330 TT, IL-10-1082 AA, IL10-−592 AC and IL-4-589 CC/CT significantly influenced the clinical progression of the subjects with HBV and/or HCV infection. PMID:28838891

Interaction effects among IFN-γ+874, IL-2-330, IL-10-1082, IL-10-592 and IL-4-589 polymorphisms on the clinical progression of subjects infected with hepatitis B virus and/or hepatitis C virus: a retrospective nested case-control study.

PubMed

Gao, Qiu-Ju; Xie, Jia-Xin; Wang, Li-Min; Zhou, Qiang; Zhang, Shi-Yong

2017-08-23

The natural outcomes of hepatitis B virus (HBV) and/or hepatitis C virus (HCV) infections vary considerably among individuals The infection may heal naturally, or patients may succumb to chronic liver diseases, including chronic hepatitis, liver cirrhosis and hepatocellular carcinoma. The mechanism is not fully understood. To evaluate the interaction among four single nucleotide polymorphisms (SNPs) and their influence on different clinical outcomes. 277 individuals infected with HBV and/or HCV, including 81 patients with chronic hepatitis B and C, 122 asymptomatic HBV and/or HCV carriers and 74 controls who cleared HBV and HCV spontaneously, were involved in this study. The SNPs of four genes ( rs2069762/-330 G/T of IL-2 , rs2430561/+874A>T of IFN-γ, rs1800896/-1082G>A  and rs1800872/-592C>A of IL-10 and rs2243250/ -589 C>T of IL-4 ) were analysed using restriction fragment length polymorphism-polymerase chain reaction or sequence-specific primer PCR. The gene-gene interactions were assessed using the multifactor-dimensionality reduction method. Interleukin (IL)-10-592 AC and IL-4-589 CC/CT showed a synergistic effect on liver inflammatory injury (p<0.01), whereas interferon (IFN)-γ+874  AA and IL-2-330 TT had a synergistic impact (p<0.05). IFN-γ+874  AA and IL-10-1082 AA had an antagonistic effect (p<0.01) on the clinical progression, including asymptomatic HBV and HCV carriers and chronic hepatitis. IL-2-330 TT and IL-10-1082 AA synergistically influenced the clinical outcome (p<0.05). IFN-γ+874 AA, IL-2-330 TT and IL-10-1082 AA interactively affected the clinical outcome including asymptomatic HBV and HCV carriers and chronic hepatitis (p<0.05). Interactions among polymorphisms of IFN-γ+874 AA, IL-2-330 TT, IL-10-1082 AA, IL10--592 AC and IL-4-589 CC/CT significantly influenced the clinical progression of the subjects with HBV and/or HCV infection. © 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.

Combined study of genetic and epigenetic biomarker risperidone treatment efficacy in Chinese Han schizophrenia patients

PubMed Central

Shi, Y; Li, M; Song, C; Xu, Q; Huo, R; Shen, L; Xing, Q; Cui, D; Li, W; Zhao, J; He, L; Qin, S

2017-01-01

Nowadays, risperidone is an atypical antipsychotic drug that has been increasingly used for treatment and maintenance therapy in schizophrenia. However, partially affected by genetic or environmental factors, there is significant difference in treatment outcomes among patients. In this study, we aimed to interpret the difference between good and poor responders treated with risperidone in both genetic and epigenetic levels in 288 mainland Chinese patients. We recruited a Henan cohort including 98 patients as initial discovery group and then confirmed our results in Shanghai cohort. In genetic studies, we found 10 candidate single-nucleotide polymorphisms (SNPs) and 2 rare variants in Henan cohort by next-generation sequencing of 100 risperidone-response-related genes. After replication in Shanghai cohort by massarray platform, ultimately, rs6706232 and rs4818 were significantly associated with risperidone response in the two cohort meta-analysis (P=0.024 and 0.04, respectively). Besides, we also selected another reported 17 candidate SNPs associated with risperidone drug response to replicate in our mainland Chinese samples, while, we found no significant SNPs after Bonferroni correction. In epigenetic studies, we investigated the methylation status in promoters or gene-coding region of risperidone drug response-related genes including CYP3A4, CYP2D6, ABCB1, HTR2A, DRD2. Totally we found seven significant CpG sites in the meta-analysis with Bonferroni-corrected PCYP3A4_CpG_-36=0.0014, PCYP3A4_CpG_-258=0.0013, PCYP3A4_CpG_-296=0.0014, PCYP3A4_CpG_-367:-372:-374=0.028, PCYP2D6_CpG_193=0.012, PCYP2D6_CpG_242:244:250=0.00076 and PCYP2D6_CpG_284=0.034, respectively. As genetic and epigenetic factors may interactively affect drug response, we finally carried out a multivariant interaction analysis with multifactor dimensionality reduction and discovered a significant four-locus model (CYP3A4_CpG_-82:-86 +rs6280+rs1800497+rs6265, P=0.038) affecting drug response. These findings could partially explain different risperidone response outcome in Chinese population in a systematic level. PMID:28696411

Screening toll-like receptor markers to predict latent tuberculosis infection and subsequent tuberculosis disease in a Chinese population.

PubMed

Wu, Linlin; Hu, Yi; Li, Dange; Jiang, Weili; Xu, Biao

2015-04-01

We investigated whether polymorphisms in the toll-like receptor genes or gene-gene interactions are associated with susceptibility to latent tuberculosis infection (LTBI) or subsequent pulmonary tuberculosis (PTB) in a Chinese population. Two matched case-control studies were undertaken. Previously reported polymorphisms in the toll-like receptors (TLRs) were compared between 422 healthy controls (HC) and 205 LTBI patients and between 205 LTBI patients and 109 PTB patients, to assess whether these polymorphisms and their interactions are associated with LTBI or PTB. A PCR-based restriction fragment length polymorphism analysis was used to detect genetic polymorphisms in the TLR genes. Nonparametric multifactor dimensionality reduction (MDR) was used to analyze the effects of interactions between complex disease genes and other genes or environmental factors. Sixteen markers in TLR1, TLR2, TLR4, TLR6, TLR8, TLR9, and TIRAP were detected. In TLR2, the frequencies of the CC genotype (OR = 2.262; 95% CI: 1.433-3.570) and C allele (OR = 1.566; 95% CI: 1.223-1.900) in single-nucleotide polymorphism (SNP) rs3804100 were significantly higher in the LTBI group than in the HC group, whereas the GA genotype of SNP rs5743708 was associated with PTB (OR = 6.087; 95% CI: 1.687-21.968). The frequencies of the GG genotype of SNP rs7873784 in TLR4 (OR = 2.136; 95% CI: 1.312-3.478) and the CC genotype of rs3764879 in TLR8 (OR = 1.982; 95% CI: 1.292-3.042) were also significantly higher in the PTB group than in the HC group. The TC genotype frequency of SNP rs5743836 in TLR9 was significantly higher in the LTBI group than in the HC group (OR = 1.664; 95% CI: 1.201-2.306). An MDR analysis of gene-gene and gene-environment interactions identified three SNPs (rs10759932, rs7873784, and rs10759931) that predicted LTBI with 84% accuracy (p = 0.0004) and three SNPs (rs3804100, rs1898830, and rs10759931) that predicted PTB with 80% accuracy (p = 0.0001). Our results suggest that genetic variation in TLR2, 4, 8 and 9, implicating TLR-related pathways affecting the innate immunity response, modulate LTBI and PTB susceptibility in Chinese.

Gene ontology analysis of pairwise genetic associations in two genome-wide studies of sporadic ALS.

PubMed

Kim, Nora Chung; Andrews, Peter C; Asselbergs, Folkert W; Frost, H Robert; Williams, Scott M; Harris, Brent T; Read, Cynthia; Askland, Kathleen D; Moore, Jason H

2012-07-28

It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO). We first estimated all pairwise additive and nonadditive genetic effects using the multifactor dimensionality reduction (MDR) method that makes few assumptions about the underlying genetic model. Statistical significance was evaluated using permutation testing in two genome-wide association studies of ALS. The detection data consisted of 276 subjects with ALS and 271 healthy controls while the replication data consisted of 221 subjects with ALS and 211 healthy controls. Both studies included genotypes from approximately 550,000 single-nucleotide polymorphisms (SNPs). Each SNP was mapped to a gene if it was within 500 kb of the start or end. Each SNP was assigned a p-value based on its strongest joint effect with the other SNPs. We then used the Exploratory Visual Analysis (EVA) method and software to assign a p-value to each gene based on the overabundance of significant SNPs at the α = 0.05 level in the gene. We also used EVA to assign p-values to each GO group based on the overabundance of significant genes at the α = 0.05 level. A GO category was determined to replicate if that category was significant at the α = 0.05 level in both studies. We found two GO categories that replicated in both studies. The first, 'Regulation of Cellular Component Organization and Biogenesis', a GO Biological Process, had p-values of 0.010 and 0.014 in the detection and replication studies, respectively. The second, 'Actin Cytoskeleton', a GO Cellular Component, had p-values of 0.040 and 0.046 in the detection and replication studies, respectively. Pathway analysis of pairwise genetic associations in two GWAS of sporadic ALS revealed a set of genes involved in cellular component organization and actin cytoskeleton, more specifically, that were not reported by prior GWAS. However, prior biological studies have implicated actin cytoskeleton in ALS and other motor neuron diseases. This study supports the idea that pathway-level analysis of GWAS data may discover important associations not revealed using conventional one-SNP-at-a-time approaches.

Gene Polymorphism Association with Type 2 Diabetes and Related Gene-Gene and Gene-Environment Interactions in a Uyghur Population

PubMed Central

Xiao, Shan; Zeng, Xiaoyun; Fan, Yong; Su, Yinxia; Ma, Qi; Zhu, Jun; Yao, Hua

2016-01-01

Background We investigated the association between 8 single-nucleotide polymorphisms (SNPs) at 3 genetic loci (CDKAL1, CDKN2A/2B and FTO) with type 2 diabetes (T2D) in a Uyghur population. Material/Methods A case-control study of 879 Uyghur patients with T2D and 895 non-diabetic Uyghur controls was conducted at the Hospital of Xinjiang Medical University between 2010 and 2013. Eight SNPs in CDKAL1, CDKN2A/2B and FTO were analyzed using Sequenom MassARRAY®SNP genotyping. Factors associated with T2D were assessed by logistic regression analyses. Gene-gene and gene-environment interactions were analyzed by generalized multifactor dimensionality reduction. Results Genotype distributions of rs10811661 (CDKN2A/2B), rs7195539, rs8050136, and rs9939609 (FTO) and allele frequencies of rs8050136 and rs9939609 differed significantly between diabetes and control groups (all P<0.05). While rs10811661, rs8050136, and rs9939609 were eliminated after adjusting for covariates (P>0.05), rs7195539 distribution differed significantly in co-dominant and dominant models (P<0.05). In gene-gene interaction analysis, after adjusting for covariates the two-locus rs10811661-rs7195539 interaction model had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.5483 (P=0.014). In gene-environment interaction analysis, the 3-locus interaction model TG-HDL-family history of diabetes had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.7072 (P<0.001). The 4-locus interaction model, rs7195539-TG-HDL-family history of diabetes had a cross-validation consistency of 8/10 (P<0.001). Conclusions Polymorphisms in CDKN2A/2B and FTO, but not CDKAL1, may be associated with T2D, and alleles rs8050136 and rs9939609 are likely risk alleles for T2D in this population. There were potential interactions among CDKN2A/2B (rs10811661) – FTO (rs7195539) or FTO (rs7195539)-TG-HDL-family history of diabetes in the pathogenesis of T2D in a Uyghur population. PMID:26873362

[Relationship and interaction between folate and expression of methyl-CpG-binding protein 2 in cervical cancerization].

PubMed

Li, Q L; Ding, L; Nan, J; Liu, C L; Yang, Z K; Chen, F; Liang, Y L; Wang, J T

2016-07-01

To explore the interaction between folate and the expression of methyl-CpG-binding protein 2(MeCP2)in cervical cancerization. Forty one patients diagnosed with cervical squamous cell carcinoma(SCC), 71 patients diagnosed with cervical intraepithelial neoplasm(CIN1, n=34; CIN2 +, n=37)and 61 women with normal cervix(NC)were recruited in this study. Microbiological assay was conducted to detect the levels of serum folate and RBC folate, Western blot assay and real-time PCR were performed to detect the expression levels of MeCP2 protein and mRNA, respectively. The data were analyzed by Kruskal-Wallis H test, χ(2) test, trend χ(2) test and Spearman correlation with SPSS statistical software(version 20.0), and the interaction were evaluated by using generalized multifactor dimensionality reduction(GMDR)model. The levels of serum folate(H=44.71, P<0.001; trend χ(2)=24.48, P<0.001)and RBC folate(H=5.28, P<0.001; trend χ(2)=3.83, P<0.05)decreased gradually along with the severity of cervical lesions. There was a positive correlation between serum folate level and RBC folate level(r=0.270, P< 0.001). The expression levels of MeCP2 protein(H=33.72, P<0.001; trend χ(2)=14.74, P<0.001)and mRNA(H=19.50, P<0.001; trend χ(2)=10.74, P<0.001)increased gradually along with the severity of cervical lesions. There were negative correlation between folate level and the expression level of MeCP2 protein(serum folate: r=-0.226, P=0.003; RBC folate: r=-0.164, P=0.004). Moreover, the results by GMDR model revealed there were interaction among serum folate deficiency, RBC folate deficiency, MeCP2 protein high expression and MeCP2 mRNA high expression in SCC and CIN2 + patients. Folate deficiency and high expression of MeCP2 gene might increase the risk of cervical cancer and its precancerous lesions through interaction among serum folate deficiency, RBC folate deficiency, MeCP2 protein high expression and mRNA high expression in the progression of cervical cancerization.

The interaction of reward genes with environmental factors in contribution to alcoholism in mexican americans.

PubMed

Du, Yanlei; Wan, Yu-Jui Yvonne

2009-12-01

Alcoholism is a polygenic disorder resulting from reward deficiency; polymorphisms in reward genes including serotonin transporter (5-HTT)-linked polymorphic region (5-HTTLPR), A118G in opioid receptor mu1 (OPRM1), and -141C Insertion/Deletion (Ins/Del) in dopamine receptor D2 (DRD2) as well as environmental factors (education and marital status) might affect the risk of alcoholism. Objective of the current study was to examine the main and interacting effect of these 3 polymorphisms and 2 environmental factors in contribution to alcoholism in Mexican Americans. Genotyping of 5-HTTLPR, OPRM1 A118G, and DRD2-141C Ins/Del was performed in 365 alcoholics and 338 nonalcoholic controls of Mexican Americans who were gender- and age-matched. Alcoholics were stratified according to tertiles of MAXDRINKS, which denotes the largest number of drinks consumed in one 24-hour period. Data analysis was done in the entire data set and in each alcoholic stratum. Multinomial logistic regression was conducted to explore the main effect of 3 polymorphisms and 2 environmental factors (education and marital status); classification tree, generalized multifactor dimensionality reduction (GMDR) analysis, and polymorphism interaction analysis version 2.0 (PIA 2) program were used to study factor interaction. Main effect of education, OPRM1, and DRD2 was detected in alcoholic stratum of moderate and/or largest MAXDRINKS with education < or =12 years, OPRM1 118 A/A, and DRD2 -141C Ins/Ins being risk factors. Classification tree analysis, GMDR analysis, and PIA 2 program all supported education*OPRM1 interaction in alcoholics of largest MAXDRINKS with education < or =12 years coupled with OPRM1 A/A being a high risk factor; dendrogram showed synergistic interaction between these 2 factors; dosage-effect response was also observed for education*OPRM1 interaction. No definite effect of marital status and 5-HTTLPR in pathogenesis of alcoholism was observed. Our results suggest main effect of education background, OPRM1 A118G, and DRD2 -141C Ins/Del as well as education*OPRM1 interaction in contribution to moderate and/or severe alcoholism in Mexican Americans. Functional relevance of these findings still needs to be explored.

Gauged supergravities from M-theory reductions

NASA Astrophysics Data System (ADS)

Katmadas, Stefanos; Tomasiello, Alessandro

2018-04-01

In supergravity compactifications, there is in general no clear prescription on how to select a finite-dimensional family of metrics on the internal space, and a family of forms on which to expand the various potentials, such that the lower-dimensional effective theory is supersymmetric. We propose a finite-dimensional family of deformations for regular Sasaki-Einstein seven-manifolds M 7, relevant for M-theory compactifications down to four dimensions. It consists of integrable Cauchy-Riemann structures, corresponding to complex deformations of the Calabi-Yau cone M 8 over M 7. The non-harmonic forms we propose are the ones contained in one of the Kohn-Rossi cohomology groups, which is finite-dimensional and naturally controls the deformations of Cauchy-Riemann structures. The same family of deformations can be also described in terms of twisted cohomology of the base M 6, or in terms of Milnor cycles arising in deformations of M 8. Using existing results on SU(3) structure compactifications, we briefly discuss the reduction of M-theory on our class of deformed Sasaki-Einstein manifolds to four-dimensional gauged supergravity.

Extra-dimensional models on the lattice

DOE PAGES

Knechtli, Francesco; Rinaldi, Enrico

2016-08-05

In this paper we summarize the ongoing effort to study extra-dimensional gauge theories with lattice simulations. In these models the Higgs field is identified with extra-dimensional components of the gauge field. The Higgs potential is generated by quantum corrections and is protected from divergences by the higher dimensional gauge symmetry. Dimensional reduction to four dimensions can occur through compactification or localization. Gauge-Higgs unification models are often studied using perturbation theory. Numerical lattice simulations are used to go beyond these perturbative expectations and to include nonperturbative effects. We describe the known perturbative predictions and their fate in the strongly-coupled regime formore » various extra-dimensional models.« less

Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population

PubMed Central

Mathew, Boby; Léon, Jens; Sannemann, Wiebke; Sillanpää, Mikko J.

2018-01-01

Gene-by-gene interactions, also known as epistasis, regulate many complex traits in different species. With the availability of low-cost genotyping it is now possible to study epistasis on a genome-wide scale. However, identifying genome-wide epistasis is a high-dimensional multiple regression problem and needs the application of dimensionality reduction techniques. Flowering Time (FT) in crops is a complex trait that is known to be influenced by many interacting genes and pathways in various crops. In this study, we successfully apply Sure Independence Screening (SIS) for dimensionality reduction to identify two-way and three-way epistasis for the FT trait in a Multiparent Advanced Generation Inter-Cross (MAGIC) barley population using the Bayesian multilocus model. The MAGIC barley population was generated from intercrossing among eight parental lines and thus, offered greater genetic diversity to detect higher-order epistatic interactions. Our results suggest that SIS is an efficient dimensionality reduction approach to detect high-order interactions in a Bayesian multilocus model. We also observe that many of our findings (genomic regions with main or higher-order epistatic effects) overlap with known candidate genes that have been already reported in barley and closely related species for the FT trait. PMID:29254994

The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction

PubMed Central

Williamson, Ross S.; Sahani, Maneesh; Pillow, Jonathan W.

2015-01-01

Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron’s probability of spiking. One popular method, known as maximally informative dimensions (MID), uses an information-theoretic quantity known as “single-spike information” to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP) model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex. PMID:25831448

Three-dimensional collimation of in-plane-propagating light using silicon micromachined mirror

NASA Astrophysics Data System (ADS)

Sabry, Yasser M.; Khalil, Diaa; Saadany, Bassam; Bourouina, Tarik

2014-03-01

We demonstrate light collimation of single-mode optical fibers using deeply-etched three-dimensional curved micromirror on silicon chip. The three-dimensional curvature of the mirror is controlled by a process combining deep reactive ion etching and isotropic etching of silicon. The produced surface is astigmatic with out-of-plane radius of curvature that is about one half the in-plane radius of curvature. Having a 300-μm in-plane radius and incident beam inplane inclined with an angle of 45 degrees with respect to the principal axis, the reflected beam is maintained stigmatic with about 4.25 times reduction in the beam expansion angle in free space and about 12-dB reduction in propagation losses, when received by a limited-aperture detector.

Multi-label classification of chronically ill patients with bag of words and supervised dimensionality reduction algorithms.

PubMed

Bromuri, Stefano; Zufferey, Damien; Hennebert, Jean; Schumacher, Michael

2014-10-01

This research is motivated by the issue of classifying illnesses of chronically ill patients for decision support in clinical settings. Our main objective is to propose multi-label classification of multivariate time series contained in medical records of chronically ill patients, by means of quantization methods, such as bag of words (BoW), and multi-label classification algorithms. Our second objective is to compare supervised dimensionality reduction techniques to state-of-the-art multi-label classification algorithms. The hypothesis is that kernel methods and locality preserving projections make such algorithms good candidates to study multi-label medical time series. We combine BoW and supervised dimensionality reduction algorithms to perform multi-label classification on health records of chronically ill patients. The considered algorithms are compared with state-of-the-art multi-label classifiers in two real world datasets. Portavita dataset contains 525 diabetes type 2 (DT2) patients, with co-morbidities of DT2 such as hypertension, dyslipidemia, and microvascular or macrovascular issues. MIMIC II dataset contains 2635 patients affected by thyroid disease, diabetes mellitus, lipoid metabolism disease, fluid electrolyte disease, hypertensive disease, thrombosis, hypotension, chronic obstructive pulmonary disease (COPD), liver disease and kidney disease. The algorithms are evaluated using multi-label evaluation metrics such as hamming loss, one error, coverage, ranking loss, and average precision. Non-linear dimensionality reduction approaches behave well on medical time series quantized using the BoW algorithm, with results comparable to state-of-the-art multi-label classification algorithms. Chaining the projected features has a positive impact on the performance of the algorithm with respect to pure binary relevance approaches. The evaluation highlights the feasibility of representing medical health records using the BoW for multi-label classification tasks. The study also highlights that dimensionality reduction algorithms based on kernel methods, locality preserving projections or both are good candidates to deal with multi-label classification tasks in medical time series with many missing values and high label density. Copyright © 2014 Elsevier Inc. All rights reserved.

REBURNING THERMAL AND CHEMICAL PROCESSES IN A TWO-DIMENSIONAL PILOT-SCALE SYSTEM

EPA Science Inventory

The paper describes an experimental investigation of the thermal and chemical processes influencing NOx reduction by natural gas reburning in a two-dimensional pilot-scale combustion system. Reburning effectiveness for initial NOx levels of 50-500 ppm and reburn stoichiometric ra...

Thermomagnetic instabilities in a vertical layer of ferrofluid: nonlinear analysis away from a critical point

NASA Astrophysics Data System (ADS)

Dey, Pinkee; Suslov, Sergey A.

2016-12-01

A finite amplitude instability has been analysed to discover the exact mechanism leading to the appearance of stationary magnetoconvection patterns in a vertical layer of a non-conducting ferrofluid heated from the side and placed in an external magnetic field perpendicular to the walls. The physical results have been obtained using a version of a weakly nonlinear analysis that is based on the disturbance amplitude expansion. It enables a low-dimensional reduction of a full nonlinear problem in supercritical regimes away from a bifurcation point. The details of the reduction are given in comparison with traditional small-parameter expansions. It is also demonstrated that Squire’s transformation can be introduced for higher-order nonlinear terms thus reducing the full three-dimensional problem to its equivalent two-dimensional counterpart and enabling significant computational savings. The full three-dimensional instability patterns are subsequently recovered using the inverse transforms The analysed stationary thermomagnetic instability is shown to occur as a result of a supercritical pitchfork bifurcation.

Three-dimensional mapping of the lateral ventricles in autism

PubMed Central

Vidal, Christine N.; Nicolsonln, Rob; Boire, Jean-Yves; Barra, Vincent; DeVito, Timothy J.; Hayashi, Kiralee M.; Geaga, Jennifer A.; Drost, Dick J.; Williamson, Peter C.; Rajakumar, Nagalingam; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

In this study, a computational mapping technique was used to examine the three-dimensional profile of the lateral ventricles in autism. T1-weighted three-dimensional magnetic resonance images of the brain were acquired from 20 males with autism (age: 10.1 ± 3.5 years) and 22 male control subjects (age: 10.7 ± 2.5 years). The lateral ventricles were delineated manually and ventricular volumes were compared between the two groups. Ventricular traces were also converted into statistical three-dimensional maps, based on anatomical surface meshes. These maps were used to visualize regional morphological differences in the thickness of the lateral ventricles between patients and controls. Although ventricular volumes measured using traditional methods did not differ significantly between groups, statistical surface maps revealed subtle, highly localized reductions in ventricular size in patients with autism in the left frontal and occipital horns. These localized reductions in the lateral ventricles may result from exaggerated brain growth early in life. PMID:18502618

Multifactor Determinants of Visual Accommodation as a Critical Intervening Variable in the Perception of Size and Distance: Phase I Report

DTIC Science & Technology

1997-11-01

Expanded subset of the illustration to clarify the locus of the off-axis end point of retinal stimulation for correct accommodation. 55 Figure...12c. Expanded illustration to clarify the locus of the off -axis end point of retinal stimulation for myopic accommodation. 55 Figure 12d...Expanded illustration to clarify the locus of the off -axis end point of retinal stimulation for hyperopic accommodation. 56 Figure 13. Simplified

Multi-factor Effects on the Durability of Recycle Aggregate Concrete

NASA Astrophysics Data System (ADS)

Ma, Huan; Cui, Yu-Li; Zhu, Wen-Yu; Xie, Xian-Jie

2016-05-01

Recycled Aggregate Concrete (RAC) was prepared with different recycled aggregate replacement ratio, 0, 30%, 70% and 100% respectively. The performances of RAC were examined by the freeze-thaw cycle, carbonization and sulfate attack to assess the durability. Results show that test sequence has different effects on the durability of RAC; the durability is poorer when carbonation experiment was carried out firstly, and then other experiment was carried out again; the durability is better when recycled aggregate replacement ratio is 70%.

Multi-factor Analysis of Pre-control Fracture Simulations about Projectile Material

NASA Astrophysics Data System (ADS)

Wan, Ren-Yi; Zhou, Wei

2016-05-01

The study of projectile material pre-control fracture is helpful to improve the projectile metal effective fragmentation and the material utilization rate. Fragments muzzle velocity and lethality can be affected by the different explosive charge and the way of initiation. The finite element software can simulate the process of projectile explosive rupture which has a pre-groove in the projectile shell surface and analysis of typical node velocity change with time, to provides a reference for the design and optimization of precontrol frag.

PKPass

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

Adamson, Ryan M.

Password management solutions exist, but few are designed for enterprise systems administrators sharing oncall rotations. Due to the Multi-Factor Level of Assurance 4 effort, DOE is now distributing PIV cards with cryptographically signed certificate and private key pairs to administrators and other security-significant users. We utilize this public key infrastructure (PKI) to encrypt passwords for other recipients in a secure way. This is cross platform (works on OSX and Linux systems), and has already been adopted internally by the NCCS systems administration staff to replace their old password book system.

Similarity solutions of some two-space-dimensional nonlinear wave evolution equations

NASA Technical Reports Server (NTRS)

Redekopp, L. G.

1980-01-01

Similarity reductions of the two-space-dimensional versions of the Korteweg-de Vries, modified Korteweg-de Vries, Benjamin-Davis-Ono, and nonlinear Schroedinger equations are presented, and some solutions of the reduced equations are discussed. Exact dispersive solutions of the two-dimensional Korteweg-de Vries equation are obtained, and the similarity solution of this equation is shown to be reducible to the second Painleve transcendent.

Hidden symmetries of Eisenhart-Duval lift metrics and the Dirac equation with flux

NASA Astrophysics Data System (ADS)

Cariglia, Marco

2012-10-01

The Eisenhart-Duval lift allows embedding nonrelativistic theories into a Lorentzian geometrical setting. In this paper we study the lift from the point of view of the Dirac equation and its hidden symmetries. We show that dimensional reduction of the Dirac equation for the Eisenhart-Duval metric in general gives rise to the nonrelativistic Lévy-Leblond equation in lower dimension. We study in detail in which specific cases the lower dimensional limit is given by the Dirac equation, with scalar and vector flux, and the relation between lift, reduction, and the hidden symmetries of the Dirac equation. While there is a precise correspondence in the case of the lower dimensional massive Dirac equation with no flux, we find that for generic fluxes it is not possible to lift or reduce all solutions and hidden symmetries. As a by-product of this analysis, we construct new Lorentzian metrics with special tensors by lifting Killing-Yano and closed conformal Killing-Yano tensors and describe the general conformal Killing-Yano tensor of the Eisenhart-Duval lift metrics in terms of lower dimensional forms. Last, we show how, by dimensionally reducing the higher dimensional operators of the massless Dirac equation that are associated with shared hidden symmetries, it is possible to recover hidden symmetry operators for the Dirac equation with flux.

Simulation of Fluid Flow and Collection Efficiency for an SEA Multi-element Probe

NASA Technical Reports Server (NTRS)

Rigby, David L.; Struk, Peter M.; Bidwell, Colin

2014-01-01

Numerical simulations of fluid flow and collection efficiency for a Science Engineering Associates (SEA) multi-element probe are presented. Simulation of the flow field was produced using the Glenn-HT Navier-Stokes solver. Three dimensional unsteady results were produced and then time averaged for the collection efficiency results. Three grid densities were investigated to enable an assessment of grid dependence. Collection efficiencies were generated for three spherical particle sizes, 100, 20, and 5 micron in diameter, using the codes LEWICE3D and LEWICE2D. The free stream Mach number was 0.27, representing a velocity of approximately 86 ms. It was observed that a reduction in velocity of about 15-20 occurred as the flow entered the shroud of the probe.Collection efficiency results indicate a reduction in collection efficiency as particle size is reduced. The reduction with particle size is expected, however, the results tended to be lower than previous results generated for isolated two-dimensional elements. The deviation from the two-dimensional results is more pronounced for the smaller particles and is likely due to the effect of the protective shroud.

Inverse regression-based uncertainty quantification algorithms for high-dimensional models: Theory and practice

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

Li, Weixuan; Lin, Guang; Li, Bing

2016-09-01

A well-known challenge in uncertainty quantification (UQ) is the "curse of dimensionality". However, many high-dimensional UQ problems are essentially low-dimensional, because the randomness of the quantity of interest (QoI) is caused only by uncertain parameters varying within a low-dimensional subspace, known as the sufficient dimension reduction (SDR) subspace. Motivated by this observation, we propose and demonstrate in this paper an inverse regression-based UQ approach (IRUQ) for high-dimensional problems. Specifically, we use an inverse regression procedure to estimate the SDR subspace and then convert the original problem to a low-dimensional one, which can be efficiently solved by building a response surface model such as a polynomial chaos expansion. The novelty and advantages of the proposed approach is seen in its computational efficiency and practicality. Comparing with Monte Carlo, the traditionally preferred approach for high-dimensional UQ, IRUQ with a comparable cost generally gives much more accurate solutions even for high-dimensional problems, and even when the dimension reduction is not exactly sufficient. Theoretically, IRUQ is proved to converge twice as fast as the approach it uses seeking the SDR subspace. For example, while a sliced inverse regression method converges to the SDR subspace at the rate ofmore » $$O(n^{-1/2})$$, the corresponding IRUQ converges at $$O(n^{-1})$$. IRUQ also provides several desired conveniences in practice. It is non-intrusive, requiring only a simulator to generate realizations of the QoI, and there is no need to compute the high-dimensional gradient of the QoI. Finally, error bars can be derived for the estimation results reported by IRUQ.« less

Effects of band selection on endmember extraction for forestry applications

NASA Astrophysics Data System (ADS)

Karathanassi, Vassilia; Andreou, Charoula; Andronis, Vassilis; Kolokoussis, Polychronis

2014-10-01

In spectral unmixing theory, data reduction techniques play an important role as hyperspectral imagery contains an immense amount of data, posing many challenging problems such as data storage, computational efficiency, and the so called "curse of dimensionality". Feature extraction and feature selection are the two main approaches for dimensionality reduction. Feature extraction techniques are used for reducing the dimensionality of the hyperspectral data by applying transforms on hyperspectral data. Feature selection techniques retain the physical meaning of the data by selecting a set of bands from the input hyperspectral dataset, which mainly contain the information needed for spectral unmixing. Although feature selection techniques are well-known for their dimensionality reduction potentials they are rarely used in the unmixing process. The majority of the existing state-of-the-art dimensionality reduction methods set criteria to the spectral information, which is derived by the whole wavelength, in order to define the optimum spectral subspace. These criteria are not associated with any particular application but with the data statistics, such as correlation and entropy values. However, each application is associated with specific land c over materials, whose spectral characteristics present variations in specific wavelengths. In forestry for example, many applications focus on tree leaves, in which specific pigments such as chlorophyll, xanthophyll, etc. determine the wavelengths where tree species, diseases, etc., can be detected. For such applications, when the unmixing process is applied, the tree species, diseases, etc., are considered as the endmembers of interest. This paper focuses on investigating the effects of band selection on the endmember extraction by exploiting the information of the vegetation absorbance spectral zones. More precisely, it is explored whether endmember extraction can be optimized when specific sets of initial bands related to leaf spectral characteristics are selected. Experiments comprise application of well-known signal subspace estimation and endmember extraction methods on a hyperspectral imagery that presents a forest area. Evaluation of the extracted endmembers showed that more forest species can be extracted as endmembers using selected bands.

Entropic manifestations of topological order in three dimensions

NASA Astrophysics Data System (ADS)

Bullivant, Alex; Pachos, Jiannis K.

2016-03-01

We evaluate the entanglement entropy of exactly solvable Hamiltonians corresponding to general families of three-dimensional topological models. We show that the modification to the entropic area law due to three-dimensional topological properties is richer than the two-dimensional case. In addition to the reduction of the entropy caused by a nonzero vacuum expectation value of contractible loop operators, a topological invariant emerges that increases the entropy if the model consists of nontrivially braiding anyons. As a result the three-dimensional topological entanglement entropy provides only partial information about the two entropic topological invariants.

Kinetically Controlled Synthesis of Pt-Based One-Dimensional Hierarchically Porous Nanostructures with Large Mesopores as Highly Efficient ORR Catalysts

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

Fu, Shaofang; Zhu, Chengzhou; Song, Junhua

2016-12-28

Rational design and construction of Pt-based porous nanostructures with large mesopores have triggered significant considerations because of their high surface area and more efficient mass transport. Hydrochloric acid-induced kinetic reduction of metal precursors in the presence of soft template F-127 and hard template tellurium nanowires has been successfully demonstrated to construct one-dimensional hierarchical porous PtCu alloy nanostructures with large mesopores. Moreover, the electrochemical experiments demonstrated that the resultant PtCu hierarchically porous nanostructures with optimized composition exhibit enhanced electrocatalytic performance for oxygen reduction reaction.

Computation of partially invariant solutions for the Einstein Walker manifolds' identifying equations

NASA Astrophysics Data System (ADS)

Nadjafikhah, Mehdi; Jafari, Mehdi

2013-12-01

In this paper, partially invariant solutions (PISs) method is applied in order to obtain new four-dimensional Einstein Walker manifolds. This method is based on subgroup classification for the symmetry group of partial differential equations (PDEs) and can be regarded as the generalization of the similarity reduction method. For this purpose, those cases of PISs which have the defect structure δ=1 and are resulted from two-dimensional subalgebras are considered in the present paper. Also it is shown that the obtained PISs are distinct from the invariant solutions that obtained by similarity reduction method.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering.

PubMed

Ji, Shuiwang

2013-07-11

The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship.

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures.

PubMed

Cao, Peng; Liu, Xiaoli; Yang, Jinzhu; Zhao, Dazhe; Huang, Min; Zhang, Jian; Zaiane, Osmar

2017-12-01

Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their families. Making accurate diagnosis of AD based on brain magnetic resonance imaging (MRI) is becoming more and more critical and emphasized at the earliest stages. However, the high dimensionality and imbalanced data issues are two major challenges in the study of computer aided AD diagnosis. The greatest limitations of existing dimensionality reduction and over-sampling methods are that they assume a linear relationship between the MRI features (predictor) and the disease status (response). To better capture the complicated but more flexible relationship, we propose a multi-kernel based dimensionality reduction and over-sampling approaches. We combined Marginal Fisher Analysis with ℓ 2,1 -norm based multi-kernel learning (MKMFA) to achieve the sparsity of region-of-interest (ROI), which leads to simultaneously selecting a subset of the relevant brain regions and learning a dimensionality transformation. Meanwhile, a multi-kernel over-sampling (MKOS) was developed to generate synthetic instances in the optimal kernel space induced by MKMFA, so as to compensate for the class imbalanced distribution. We comprehensively evaluate the proposed models for the diagnostic classification (binary class and multi-class classification) including all subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. The experimental results not only demonstrate the proposed method has superior performance over multiple comparable methods, but also identifies relevant imaging biomarkers that are consistent with prior medical knowledge. Copyright © 2017 Elsevier Ltd. All rights reserved.

Vehicle Color Recognition with Vehicle-Color Saliency Detection and Dual-Orientational Dimensionality Reduction of CNN Deep Features

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Li, Jiafeng; Zhuo, Li; Zhang, Hui; Li, Xiaoguang

2017-12-01

Color is one of the most stable attributes of vehicles and often used as a valuable cue in some important applications. Various complex environmental factors, such as illumination, weather, noise and etc., result in the visual characteristics of the vehicle color being obvious diversity. Vehicle color recognition in complex environments has been a challenging task. The state-of-the-arts methods roughly take the whole image for color recognition, but many parts of the images such as car windows; wheels and background contain no color information, which will have negative impact on the recognition accuracy. In this paper, a novel vehicle color recognition method using local vehicle-color saliency detection and dual-orientational dimensionality reduction of convolutional neural network (CNN) deep features has been proposed. The novelty of the proposed method includes two parts: (1) a local vehicle-color saliency detection method has been proposed to determine the vehicle color region of the vehicle image and exclude the influence of non-color regions on the recognition accuracy; (2) dual-orientational dimensionality reduction strategy has been designed to greatly reduce the dimensionality of deep features that are learnt from CNN, which will greatly mitigate the storage and computational burden of the subsequent processing, while improving the recognition accuracy. Furthermore, linear support vector machine is adopted as the classifier to train the dimensionality reduced features to obtain the recognition model. The experimental results on public dataset demonstrate that the proposed method can achieve superior recognition performance over the state-of-the-arts methods.

Euclidean supergravity

NASA Astrophysics Data System (ADS)

de Wit, Bernard; Reys, Valentin

2017-12-01

Supergravity with eight supercharges in a four-dimensional Euclidean space is constructed at the full non-linear level by performing an off-shell time-like reduction of five-dimensional supergravity. The resulting four-dimensional theory is realized off-shell with the Weyl, vector and tensor supermultiplets and a corresponding multiplet calculus. Hypermultiplets are included as well, but they are themselves only realized with on-shell supersymmetry. We also briefly discuss the non-linear supermultiplet. The off-shell reduction leads to a full understanding of the Euclidean theory. A complete multiplet calculus is presented along the lines of the Minkowskian theory. Unlike in Minkowski space, chiral and anti-chiral multiplets are real and supersymmetric actions are generally unbounded from below. Precisely as in the Minkowski case, where one has different formulations of Poincaré supergravity upon introducing different compensating supermultiplets, one can also obtain different versions of Euclidean supergravity.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization.

PubMed

Glaser, Joshua I; Zamft, Bradley M; Church, George M; Kording, Konrad P

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.

National Defense Center of Excellence for Industrial Metrology and 3D Imaging

DTIC Science & Technology

2012-10-18

validation rather than mundane data-reduction/analysis tasks. Indeed, the new financial and technical resources being brought to bear by integrating CT...of extremely fast axial scanners. By replacing the single-spot detector by a detector array, a three-dimensional image is acquired by one depth scan...the number of acquired voxels per complete two-dimensional or three-dimensional image, the axial and lateral resolution, the depth range, the

Scalable Learning for Geostatistics and Speaker Recognition

DTIC Science & Technology

2011-01-01

of prior knowledge of the model or due to improved robustness requirements). Both these methods have their own advantages and disadvantages. The use...application. If the data is well-correlated and low-dimensional, any prior knowledge available on the data can be used to build a parametric model. In the...absence of prior knowledge , non-parametric methods can be used. If the data is high-dimensional, PCA based dimensionality reduction is often the first

The Analysis of Dimensionality Reduction Techniques in Cryptographic Object Code Classification

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

Jason L. Wright; Milos Manic

2010-05-01

This paper compares the application of three different dimension reduction techniques to the problem of locating cryptography in compiled object code. A simple classi?er is used to compare dimension reduction via sorted covariance, principal component analysis, and correlation-based feature subset selection. The analysis concentrates on the classi?cation accuracy as the number of dimensions is increased.

How multiple factors control evapotranspiration in North America evergreen needleleaf forests.

PubMed

Chen, Yueming; Xue, Yueju; Hu, Yueming

2018-05-01

Identifying the factors dominating ecosystem water flux is a critical step for predicting evapotranspiration (ET). Here, the fuzzy rough set with binary shuffled frog leaping (BSFL-FRSA) was used to identify both individual factors and multi-factor combinations that dominate the half-hourly ET variation at evergreen needleleaf forests (ENFs) sites across three different climatic zones in the North America. Among 21factors, air temperature (TA), atmospheric CO 2 concentration (CCO 2 ), soil temperature (TS), soil water content (SWC) and net radiation (NETRAD) were evaluated as dominant single factors, contributed to the ET variation averaged for all ENF sites by 48%, 36%, 32%, 18% and 13%, respectively. While the importance order would vary with climatic zones, and TA was assessed as the most influential factor at a single climatic zone level, counting a contribution rate of 54.7%, 49.9%, and 38.6% in the subarctic, warm summer continental, and Mediterranean climatic zones, respectively. In view of impacts of each multi-factors combination on ET, both TA and CCO 2 made a contribution of 71% across three climate zones; the combination of TA, CCO 2 and NETRAD was evaluated the most dominant at Mediterranean and subarctic ENF sites, and the combination of TA, CCO 2 and TS at warm summer continental sites. Our results suggest that temperature was most critical for ET variation at the warm summer continental ENF. Copyright © 2017 Elsevier B.V. All rights reserved.

Drug-target interaction prediction using ensemble learning and dimensionality reduction.

PubMed

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2017-10-01

Experimental prediction of drug-target interactions is expensive, time-consuming and tedious. Fortunately, computational methods help narrow down the search space for interaction candidates to be further examined via wet-lab techniques. Nowadays, the number of attributes/features for drugs and targets, as well as the amount of their interactions, are increasing, making these computational methods inefficient or occasionally prohibitive. This motivates us to derive a reduced feature set for prediction. In addition, since ensemble learning techniques are widely used to improve the classification performance, it is also worthwhile to design an ensemble learning framework to enhance the performance for drug-target interaction prediction. In this paper, we propose a framework for drug-target interaction prediction leveraging both feature dimensionality reduction and ensemble learning. First, we conducted feature subspacing to inject diversity into the classifier ensemble. Second, we applied three different dimensionality reduction methods to the subspaced features. Third, we trained homogeneous base learners with the reduced features and then aggregated their scores to derive the final predictions. For base learners, we selected two classifiers, namely Decision Tree and Kernel Ridge Regression, resulting in two variants of ensemble models, EnsemDT and EnsemKRR, respectively. In our experiments, we utilized AUC (Area under ROC Curve) as an evaluation metric. We compared our proposed methods with various state-of-the-art methods under 5-fold cross validation. Experimental results showed EnsemKRR achieving the highest AUC (94.3%) for predicting drug-target interactions. In addition, dimensionality reduction helped improve the performance of EnsemDT. In conclusion, our proposed methods produced significant improvements for drug-target interaction prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

Detecting a Clinically Meaningful Change in Tic Severity in Tourette Syndrome: A Comparison of Three Methods

PubMed Central

Jeon, Sangchoon; Walkup, John T; Woods, Douglas W.; Peterson, Alan; Piacentini, John; Wilhelm, Sabine; Katsovich, Lily; McGuire, Joseph F.; Dziura, James; Scahill, Lawrence

2014-01-01

Objective To compare three statistical strategies for classifying positive treatment response based on a dimensional measure (Yale Global Tic Severity Scale [YGTSS]) and a categorical measure (Clinical Global Impression-Improvement [CGI-I]). Method Subjects (N=232; 69.4% male; ages 9-69 years) with Tourette syndrome or chronic tic disorder participated in one of two 10-week, randomized controlled trials comparing behavioral treatment to supportive therapy. The YGTSS and CGI-I were rated by clinicians blind to treatment assignment. We examined the percent reduction in the YGTSS-Total Tic Score (TTS) against Much Improved or Very Much Improved on the CGI-I, computed a signal detection analysis (SDA) and built a mixture model to classify dimensional response based on the change in the YGTSS-TTS. Results A 25% decrease on the YGTSS-TTS predicted positive response on the CGI-I during the trial. The SDA showed that a 25% reduction in the YGTSS-TTS provided optimal sensitivity (87%) and specificity (84%) for predicting positive response. Using a mixture model without consideration of the CGI-I, the dimensional response was defined by 23% (or greater) reduction on the YGTSS-TTS. The odds ratio (OR) of positive response (OR=5.68, 95% CI=[2.99, 10.78]) on the CGI-I for behavioral intervention was greater than the dimensional response (OR=2.86, 95% CI=[1.65, 4.99]). Conclusion A twenty five percent reduction on the YGTSS-TTS is highly predictive of positive response by all three analytic methods. For trained raters, however, tic severity alone does not drive the classification of positive response. PMID:24001701

OBJECTIVE REDUCTION OF THE SPACE-TIME DOMAIN DIMENSIONALITY FOR EVALUATING MODEL PERFORMANCE

EPA Science Inventory

In the United States, photochemical air quality models are the principal tools used by governmental agencies to develop emission reduction strategies aimed at achieving National Ambient Air Quality Standards (NAAQS). Before they can be applied with confidence in a regulatory sett...

Phase reduction approach to synchronisation of nonlinear oscillators

NASA Astrophysics Data System (ADS)

Nakao, Hiroya

2016-04-01

Systems of dynamical elements exhibiting spontaneous rhythms are found in various fields of science and engineering, including physics, chemistry, biology, physiology, and mechanical and electrical engineering. Such dynamical elements are often modelled as nonlinear limit-cycle oscillators. In this article, we briefly review phase reduction theory, which is a simple and powerful method for analysing the synchronisation properties of limit-cycle oscillators exhibiting rhythmic dynamics. Through phase reduction theory, we can systematically simplify the nonlinear multi-dimensional differential equations describing a limit-cycle oscillator to a one-dimensional phase equation, which is much easier to analyse. Classical applications of this theory, i.e. the phase locking of an oscillator to a periodic external forcing and the mutual synchronisation of interacting oscillators, are explained. Further, more recent applications of this theory to the synchronisation of non-interacting oscillators induced by common noise and the dynamics of coupled oscillators on complex networks are discussed. We also comment on some recent advances in phase reduction theory for noise-driven oscillators and rhythmic spatiotemporal patterns.

Chaos and Robustness in a Single Family of Genetic Oscillatory Networks

PubMed Central

Fu, Daniel; Tan, Patrick; Kuznetsov, Alexey; Molkov, Yaroslav I.

2014-01-01

Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with delay. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows the range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with highly-regular periods likely have solely negative feedback. PMID:24667178

Complex Osteotomies of Tibial Plateau Malunions Using Computer-Assisted Planning and Patient-Specific Surgical Guides.

PubMed

Fürnstahl, Philipp; Vlachopoulos, Lazaros; Schweizer, Andreas; Fucentese, Sandro F; Koch, Peter P

2015-08-01

The accurate reduction of tibial plateau malunions can be challenging without guidance. In this work, we report on a novel technique that combines 3-dimensional computer-assisted planning with patient-specific surgical guides for improving reliability and accuracy of complex intraarticular corrective osteotomies. Preoperative planning based on 3-dimensional bone models was performed to simulate fragment mobilization and reduction in 3 cases. Surgical implementation of the preoperative plan using patient-specific cutting and reduction guides was evaluated; benefits and limitations of the approach were identified and discussed. The preliminary results are encouraging and show that complex, intraarticular corrective osteotomies can be accurately performed with this technique. For selective patients with complex malunions around the tibia plateau, this method might be an attractive option, with the potential to facilitate achieving the most accurate correction possible.

Metal-nitrogen doping of mesoporous carbon/graphene nanosheets by self-templating for oxygen reduction electrocatalysts.

PubMed

Li, Shuang; Wu, Dongqing; Liang, Haiwei; Wang, Jinzuan; Zhuang, Xiaodong; Mai, Yiyong; Su, Yuezeng; Feng, Xinliang

2014-11-01

We demonstrate a general and efficient self-templating strategy towards transition metal-nitrogen containing mesoporous carbon/graphene nanosheets with a unique two-dimensional (2D) morphology and tunable mesoscale porosity. Owing to the well-defined 2D morphology, nanometer-scale thickness, high specific surface area, and the simultaneous doping of the metal-nitrogen compounds, the as-prepared catalysts exhibits excellent electrocatalytic activity and stability towards the oxygen reduction reaction (ORR) in both alkaline and acidic media. More importantly, such a self-templating approach towards two-dimensional porous carbon hybrids with diverse metal-nitrogen doping opens up new avenues to mesoporous heteroatom-doped carbon materials as electrochemical catalysts for oxygen reduction and hydrogen evolution, with promising applications in fuel cell and battery technologies. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Guiding Exploration through Three-Dimensional Virtual Environments: A Cognitive Load Reduction Approach

ERIC Educational Resources Information Center

Chen, Chwen Jen; Fauzy Wan Ismail, Wan Mohd

2008-01-01

The real-time interactive nature of three-dimensional virtual environments (VEs) makes this technology very appropriate for exploratory learning purposes. However, many studies have shown that the exploration process may cause cognitive overload that affects the learning of domain knowledge. This article reports a quasi-experimental study that…

Unimodular gravity and the lepton anomalous magnetic moment at one-loop

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

Martín, Carmelo P., E-mail: carmelop@fis.ucm.es

We work out the one-loop contribution to the lepton anomalous magnetic moment coming from Unimodular Gravity. We use Dimensional Regularization and Dimensional Reduction to carry out the computations. In either case, we find that Unimodular Gravity gives rise to the same one-loop correction as that of General Relativity.

Local reduction of certain wave operators to one-dimensional form

NASA Technical Reports Server (NTRS)

Roe, Philip

1994-01-01

It is noted that certain common linear wave operators have the property that linear variation of the initial data gives rise to one-dimensional evolution in a plane defined by time and some direction in space. The analysis is given For operators arising in acoustics, electromagnetics, elastodynamics, and an abstract system.

A General Exponential Framework for Dimensionality Reduction.

PubMed

Wang, Su-Jing; Yan, Shuicheng; Yang, Jian; Zhou, Chun-Guang; Fu, Xiaolan

2014-02-01

As a general framework, Laplacian embedding, based on a pairwise similarity matrix, infers low dimensional representations from high dimensional data. However, it generally suffers from three issues: 1) algorithmic performance is sensitive to the size of neighbors; 2) the algorithm encounters the well known small sample size (SSS) problem; and 3) the algorithm de-emphasizes small distance pairs. To address these issues, here we propose exponential embedding using matrix exponential and provide a general framework for dimensionality reduction. In the framework, the matrix exponential can be roughly interpreted by the random walk over the feature similarity matrix, and thus is more robust. The positive definite property of matrix exponential deals with the SSS problem. The behavior of the decay function of exponential embedding is more significant in emphasizing small distance pairs. Under this framework, we apply matrix exponential to extend many popular Laplacian embedding algorithms, e.g., locality preserving projections, unsupervised discriminant projections, and marginal fisher analysis. Experiments conducted on the synthesized data, UCI, and the Georgia Tech face database show that the proposed new framework can well address the issues mentioned above.

Network embedding-based representation learning for single cell RNA-seq data.

PubMed

Li, Xiangyu; Chen, Weizheng; Chen, Yang; Zhang, Xuegong; Gu, Jin; Zhang, Michael Q

2017-11-02

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Enhanced thermoelectric performance in three-dimensional superlattice of topological insulator thin films

PubMed Central

2012-01-01

We show that certain three-dimensional (3D) superlattice nanostructure based on Bi2Te3 topological insulator thin films has better thermoelectric performance than two-dimensional (2D) thin films. The 3D superlattice shows a predicted peak value of ZT of approximately 6 for gapped surface states at room temperature and retains a high figure of merit ZT of approximately 2.5 for gapless surface states. In contrast, 2D thin films with gapless surface states show no advantage over bulk Bi2Te3. The enhancement of the thermoelectric performance originates from a combination of the reduction of lattice thermal conductivity by phonon-interface scattering, the high mobility of the topologically protected surface states, the enhancement of Seebeck coefficient, and the reduction of electron thermal conductivity by energy filtering. Our study shows that the nanostructure design of topological insulators provides a possible new way of ZT enhancement. PMID:23072433

Enhanced thermoelectric performance in three-dimensional superlattice of topological insulator thin films.

PubMed

Fan, Zheyong; Zheng, Jiansen; Wang, Hui-Qiong; Zheng, Jin-Cheng

2012-10-16

We show that certain three-dimensional (3D) superlattice nanostructure based on Bi2Te3 topological insulator thin films has better thermoelectric performance than two-dimensional (2D) thin films. The 3D superlattice shows a predicted peak value of ZT of approximately 6 for gapped surface states at room temperature and retains a high figure of merit ZT of approximately 2.5 for gapless surface states. In contrast, 2D thin films with gapless surface states show no advantage over bulk Bi2Te3. The enhancement of the thermoelectric performance originates from a combination of the reduction of lattice thermal conductivity by phonon-interface scattering, the high mobility of the topologically protected surface states, the enhancement of Seebeck coefficient, and the reduction of electron thermal conductivity by energy filtering. Our study shows that the nanostructure design of topological insulators provides a possible new way of ZT enhancement.

Multispectral x-ray CT: multivariate statistical analysis for efficient reconstruction

NASA Astrophysics Data System (ADS)

Kheirabadi, Mina; Mustafa, Wail; Lyksborg, Mark; Lund Olsen, Ulrik; Bjorholm Dahl, Anders

2017-10-01

Recent developments in multispectral X-ray detectors allow for an efficient identification of materials based on their chemical composition. This has a range of applications including security inspection, which is our motivation. In this paper, we analyze data from a tomographic setup employing the MultiX detector, that records projection data in 128 energy bins covering the range from 20 to 160 keV. Obtaining all information from this data requires reconstructing 128 tomograms, which is computationally expensive. Instead, we propose to reduce the dimensionality of projection data prior to reconstruction and reconstruct from the reduced data. We analyze three linear methods for dimensionality reduction using a dataset with 37 equally-spaced projection angles. Four bottles with different materials are recorded for which we are able to obtain similar discrimination of their content using a very reduced subset of tomograms compared to the 128 tomograms that would otherwise be needed without dimensionality reduction.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization

PubMed Central

Glaser, Joshua I.; Zamft, Bradley M.; Church, George M.; Kording, Konrad P.

2015-01-01

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, “puzzle imaging,” that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples. PMID:26192446

Integrating diffusion maps with umbrella sampling: Application to alanine dipeptide

NASA Astrophysics Data System (ADS)

Ferguson, Andrew L.; Panagiotopoulos, Athanassios Z.; Debenedetti, Pablo G.; Kevrekidis, Ioannis G.

2011-04-01

Nonlinear dimensionality reduction techniques can be applied to molecular simulation trajectories to systematically extract a small number of variables with which to parametrize the important dynamical motions of the system. For molecular systems exhibiting free energy barriers exceeding a few kBT, inadequate sampling of the barrier regions between stable or metastable basins can lead to a poor global characterization of the free energy landscape. We present an adaptation of a nonlinear dimensionality reduction technique known as the diffusion map that extends its applicability to biased umbrella sampling simulation trajectories in which restraining potentials are employed to drive the system into high free energy regions and improve sampling of phase space. We then propose a bootstrapped approach to iteratively discover good low-dimensional parametrizations by interleaving successive rounds of umbrella sampling and diffusion mapping, and we illustrate the technique through a study of alanine dipeptide in explicit solvent.

Evaluation of Different Disinfactants on Dimensional Accuracy and Surface Quality of Type IV Gypsum Casts Retrieved from Elastomeric Impression Materials.

PubMed

Pal, P K; Kamble, Suresh S; Chaurasia, Ranjitkumar Rampratap; Chaurasia, Vishwajit Rampratap; Tiwari, Samarth; Bansal, Deepak

2014-06-01

The present study was done to evaluate the dimensional stability and surface quality of Type IV gypsum casts retrieved from disinfected elastomeric impression materials. In an in vitro study contaminated impression material with known bacterial species was disinfected with disinfectants followed by culturing the swab sample to assess reduction in level of bacterial colony. Changes in surface detail reproduction of impression were assessed fallowing disinfection. All the three disinfectants used in the study produced a 100% reduction in colony forming units of the test organisms. All the three disinfectants produced complete disinfection, and didn't cause any deterioration in surface detail reproduction. How to cite the article: Pal PK, Kamble SS, Chaurasia RR, Chaurasia VR, Tiwari S, Bansal D. Evaluation of dimensional stability and surface quality of type IV gypsum casts retrieved from disinfected elastomeric impression materials. J Int Oral Health 2014;6(3):77-81.

Design of a 3-dimensional visual illusion speed reduction marking scheme.

PubMed

Liang, Guohua; Qian, Guomin; Wang, Ye; Yi, Zige; Ru, Xiaolei; Ye, Wei

2017-03-01

To determine which graphic and color combination for a 3-dimensional visual illusion speed reduction marking scheme presents the best visual stimulus, five parameters were designed. According to the Balanced Incomplete Blocks-Law of Comparative Judgment, three schemes, which produce strong stereoscopic impressions, were screened from the 25 initial design schemes of different combinations of graphics and colors. Three-dimensional experimental simulation scenes of the three screened schemes were created to evaluate four different effects according to a semantic analysis. The following conclusions were drawn: schemes with a red color are more effective than those without; the combination of red, yellow and blue produces the best visual stimulus; a larger area from the top surface and the front surface should be colored red; and a triangular prism should be painted as the graphic of the marking according to the stereoscopic impression and the coordination of graphics with the road.

Approximation of Quantum Stochastic Differential Equations for Input-Output Model Reduction

DTIC Science & Technology

2016-02-25

Approximation of Quantum Stochastic Differential Equations for Input-Output Model Reduction We have completed a short program of theoretical research...on dimensional reduction and approximation of models based on quantum stochastic differential equations. Our primary results lie in the area of...2211 quantum probability, quantum stochastic differential equations REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR

Reusing remediated CCA-treated wood

Treesearch

Carol A. Clausen

2003-01-01

Options for recycling and reusing chromated-copper-arsenate- (CCA) treated material include dimensional lumber and round wood size reduction, composites, and remediation. Size reduction by remilling, shaving, or resawing CCA-treated wood reduces the volume of landfilled waste material and provides many options for reusing used treated wood. Manufacturing composite...

Reducing democratic type II supergravity on SU(3) × SU(3) structures

NASA Astrophysics Data System (ADS)

Cassani, Davide

2008-06-01

Type II supergravity on backgrounds admitting SU(3) × SU(3) structure and general fluxes is considered. Using the generalized geometry formalism, we study dimensional reductions leading to N = 2 gauged supergravity in four dimensions, possibly with tensor multiplets. In particular, a geometric formula for the full N = 2 scalar potential is given. Then we implement a truncation ansatz, and derive the complete N = 2 bosonic action. While the NSNS contribution is obtained via a direct dimensional reduction, the contribution of the RR sector is computed starting from the democratic formulation and demanding consistency with the reduced equations of motion.

Symmetry Reductions and Group-Invariant Radial Solutions to the n-Dimensional Wave Equation

NASA Astrophysics Data System (ADS)

Feng, Wei; Zhao, Songlin

2018-01-01

In this paper, we derive explicit group-invariant radial solutions to a class of wave equation via symmetry group method. The optimal systems of one-dimensional subalgebras for the corresponding radial wave equation are presented in terms of the known point symmetries. The reductions of the radial wave equation into second-order ordinary differential equations (ODEs) with respect to each symmetry in the optimal systems are shown. Then we solve the corresponding reduced ODEs explicitly in order to write out the group-invariant radial solutions for the wave equation. Finally, several analytical behaviours and smoothness of the resulting solutions are discussed.

Mechanism of polymer drag reduction using a low-dimensional model.

PubMed

Roy, Anshuman; Morozov, Alexander; van Saarloos, Wim; Larson, Ronald G

2006-12-08

Using a retarded-motion expansion to describe the polymer stress, we derive a low-dimensional model to understand the effects of polymer elasticity on the self-sustaining process that maintains the coherent wavy streamwise vortical structures underlying wall-bounded turbulence. Our analysis shows that at small Weissenberg numbers, Wi, elasticity enhances the coherent structures. At higher Wi, however, polymer stresses suppress the streamwise vortices (rolls) by calming down the instability of the streaks that regenerates the rolls. We show that this behavior can be attributed to the nonmonotonic dependence of the biaxial extensional viscosity on Wi, and identify it as the key rheological property controlling drag reduction.

Kinetically Controlled Synthesis of Pt-Based One-Dimensional Hierarchically Porous Nanostructures with Large Mesopores as Highly Efficient ORR Catalysts.

PubMed

Fu, Shaofang; Zhu, Chengzhou; Song, Junhua; Engelhard, Mark H; Xia, Haibing; Du, Dan; Lin, Yuehe

2016-12-28

Rational design and construction of Pt-based porous nanostructures with large mesopores have triggered significant considerations because of their high surface area and more efficient mass transport. Hydrochloric acid-induced kinetically controlled reduction of metal precursors in the presence of soft template F-127 and hard template tellurium nanowires has been successfully demonstrated to construct one-dimensional hierarchical porous PtCu alloy nanostructures with large mesopores. Moreover, the electrochemical experiments demonstrated that the PtCu hierarchically porous nanostructures synthesized under optimized conditions exhibit enhanced electrocatalytic performance for oxygen reduction reaction in acid media.

Toward On-Demand Deep Brain Stimulation Using Online Parkinson's Disease Prediction Driven by Dynamic Detection.

PubMed

Mohammed, Ameer; Zamani, Majid; Bayford, Richard; Demosthenous, Andreas

2017-12-01

In Parkinson's disease (PD), on-demand deep brain stimulation is required so that stimulation is regulated to reduce side effects resulting from continuous stimulation and PD exacerbation due to untimely stimulation. Also, the progressive nature of PD necessitates the use of dynamic detection schemes that can track the nonlinearities in PD. This paper proposes the use of dynamic feature extraction and dynamic pattern classification to achieve dynamic PD detection taking into account the demand for high accuracy, low computation, and real-time detection. The dynamic feature extraction and dynamic pattern classification are selected by evaluating a subset of feature extraction, dimensionality reduction, and classification algorithms that have been used in brain-machine interfaces. A novel dimensionality reduction technique, the maximum ratio method (MRM) is proposed, which provides the most efficient performance. In terms of accuracy and complexity for hardware implementation, a combination having discrete wavelet transform for feature extraction, MRM for dimensionality reduction, and dynamic k-nearest neighbor for classification was chosen as the most efficient. It achieves a classification accuracy of 99.29%, an F1-score of 97.90%, and a choice probability of 99.86%.

Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.

PubMed

Liang, Junli; Yu, Guoyang; Chen, Badong; Zhao, Minghua

2016-11-01

This paper develops a novel decentralized dimensionality reduction algorithm for the distributed tensor data across sensor networks. The main contributions of this paper are as follows. First, conventional centralized methods, which utilize entire data to simultaneously determine all the vectors of the projection matrix along each tensor mode, are not suitable for the network environment. Here, we relax the simultaneous processing manner into the one-vector-by-one-vector (OVBOV) manner, i.e., determining the projection vectors (PVs) related to each tensor mode one by one. Second, we prove that in the OVBOV manner each PV can be determined without modifying any tensor data, which simplifies corresponding computations. Third, we cast the decentralized PV determination problem as a set of subproblems with consensus constraints, so that it can be solved in the network environment only by local computations and information communications among neighboring nodes. Fourth, we introduce the null space and transform the PV determination problem with complex orthogonality constraints into an equivalent hidden convex one without any orthogonality constraint, which can be solved by the Lagrange multiplier method. Finally, experimental results are given to show that the proposed algorithm is an effective dimensionality reduction scheme for the distributed tensor data across the sensor networks.

Shape component analysis: structure-preserving dimension reduction on biological shape spaces.

PubMed

Lee, Hao-Chih; Liao, Tao; Zhang, Yongjie Jessica; Yang, Ge

2016-03-01

Quantitative shape analysis is required by a wide range of biological studies across diverse scales, ranging from molecules to cells and organisms. In particular, high-throughput and systems-level studies of biological structures and functions have started to produce large volumes of complex high-dimensional shape data. Analysis and understanding of high-dimensional biological shape data require dimension-reduction techniques. We have developed a technique for non-linear dimension reduction of 2D and 3D biological shape representations on their Riemannian spaces. A key feature of this technique is that it preserves distances between different shapes in an embedded low-dimensional shape space. We demonstrate an application of this technique by combining it with non-linear mean-shift clustering on the Riemannian spaces for unsupervised clustering of shapes of cellular organelles and proteins. Source code and data for reproducing results of this article are freely available at https://github.com/ccdlcmu/shape_component_analysis_Matlab The implementation was made in MATLAB and supported on MS Windows, Linux and Mac OS. geyang@andrew.cmu.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Formation of dominant mode by evolution in biological systems

NASA Astrophysics Data System (ADS)

Furusawa, Chikara; Kaneko, Kunihiko

2018-04-01

A reduction in high-dimensional phenotypic states to a few degrees of freedom is essential to understand biological systems. Here, we show evolutionary robustness causes such reduction which restricts possible phenotypic changes in response to a variety of environmental conditions. First, global protein expression changes in Escherichia coli after various environmental perturbations were shown to be proportional across components, across different types of environmental conditions. To examine if such dimension reduction is a result of evolution, we analyzed a cell model—with a huge number of components, that reproduces itself via a catalytic reaction network—and confirmed that common proportionality in the concentrations of all components is shaped through evolutionary processes. We found that the changes in concentration across all components in response to environmental and evolutionary changes are constrained to the changes along a one-dimensional major axis, within a huge-dimensional state space. On the basis of these observations, we propose a theory in which such constraints in phenotypic changes are achieved both by evolutionary robustness and plasticity and formulate this proposition in terms of dynamical systems. Accordingly, broad experimental and numerical results on phenotypic changes caused by evolution and adaptation are coherently explained.

[Study on the influence of bioclogging on permeability of saturated porous media by experiments and models].

PubMed

Yang, Jing; Ye, Shu-jun; Wu, Ji-chun

2011-05-01

This paper studied on the influence of bioclogging on permeability of saturated porous media. Laboratory hydraulic tests were conducted in a two-dimensional C190 sand-filled cell (55 cm wide x 45 cm high x 1.28 cm thick) to investigate growth of the mixed microorganisms (KB-1) and influence of biofilm on permeability of saturated porous media under condition of rich nutrition. Biomass distributions in the water and on the sand in the cell were measured by protein analysis. The biofilm distribution on the sand was observed by confocal laser scanning microscopy. Permeability was measured by hydraulic tests. The biomass levels measured in water and on the sand increased with time, and were highest at the bottom of the cell. The biofilm on the sand at the bottom of the cell was thicker. The results of the hydraulic tests demonstrated that the permeability due to biofilm growth was estimated to be average 12% of the initial value. To investigate the spatial distribution of permeability in the two dimensional cell, three models (Taylor, Seki, and Clement) were used to calculate permeability of porous media with biofilm growth. The results of Taylor's model showed reduction in permeability of 2-5 orders magnitude. The Clement's model predicted 3%-98% of the initial value. Seki's model could not be applied in this study. Conclusively, biofilm growth could obviously decrease the permeability of two dimensional saturated porous media, however, the reduction was much less than that estimated in one dimensional condition. Additionally, under condition of two dimensional saturated porous media with rich nutrition, Seki's model could not be applied, Taylor's model predicted bigger reductions, and the results of Clement's model were closest to the result of hydraulic test.

[Clinical genealogy and genetic-mathematical study of families of probands with uterine cancer in the Chernovitsy Region].

PubMed

Galina, K P; Peresun'ko, A P; Glushchenko, N N

2001-01-01

Complex clinic-genealogical and genetic-mathematical investigation of 482 patients with uterus cancer from Chernovtsy region was carried out. It was proved that primary in the population is multifactoral origin of uterus cancer. Percentage of genetic component in general susceptibility to disease was 11.40 9.40. Recurrent risk of the malignant tumor in progeny has been estimated. Results of the investigation are the base for development and execution of uterus cancer precaution and segregated with it oncopathology in proband relatives.

Continuous Cultivation for Apparent Optimization of Defined Media for Cellulomonas sp. and Bacillus cereus

PubMed Central

Summers, R. J.; Boudreaux, D. P.; Srinivasan, V. R.

1979-01-01

Steady-state continuous culture was used to optimize lean chemically defined media for a Cellulomonas sp. and Bacillus cereus strain T. Both organisms were extremely sensitive to variations in trace-metal concentrations. However, medium optimization by this technique proved rapid, and multifactor screening was easily conducted by using a minimum of instrumentation. The optimized media supported critical dilution rates of 0.571 and 0.467 h−1 for Cellulomonas and Bacillus, respectively. These values approximated maximum growth rate values observed in batch culture. PMID:16345417

Assessment Methods of Groundwater Overdraft Area and Its Application

NASA Astrophysics Data System (ADS)

Dong, Yanan; Xing, Liting; Zhang, Xinhui; Cao, Qianqian; Lan, Xiaoxun

2018-05-01

Groundwater is an important source of water, and long-term large demand make groundwater over-exploited. Over-exploitation cause a lot of environmental and geological problems. This paper explores the concept of over-exploitation area, summarizes the natural and social attributes of over-exploitation area, as well as expounds its evaluation methods, including single factor evaluation, multi-factor system analysis and numerical method. At the same time, the different methods are compared and analyzed. And then taking Northern Weifang as an example, this paper introduces the practicality of appraisal method.

Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering

PubMed Central

2013-01-01

Background The structured organization of cells in the brain plays a key role in its functional efficiency. This delicate organization is the consequence of unique molecular identity of each cell gradually established by precise spatiotemporal gene expression control during development. Currently, studies on the molecular-structural association are beginning to reveal how the spatiotemporal gene expression patterns are related to cellular differentiation and structural development. Results In this article, we aim at a global, data-driven study of the relationship between gene expressions and neuroanatomy in the developing mouse brain. To enable visual explorations of the high-dimensional data, we map the in situ hybridization gene expression data to a two-dimensional space by preserving both the global and the local structures. Our results show that the developing brain anatomy is largely preserved in the reduced gene expression space. To provide a quantitative analysis, we cluster the reduced data into groups and measure the consistency with neuroanatomy at multiple levels. Our results show that the clusters in the low-dimensional space are more consistent with neuroanatomy than those in the original space. Conclusions Gene expression patterns and developing brain anatomy are closely related. Dimensionality reduction and visual exploration facilitate the study of this relationship. PMID:23845024

Machine Learning Based Dimensionality Reduction Facilitates Ligand Diffusion Paths Assessment: A Case of Cytochrome P450cam.

PubMed

Rydzewski, J; Nowak, W

2016-04-12

In this work we propose an application of a nonlinear dimensionality reduction method to represent the high-dimensional configuration space of the ligand-protein dissociation process in a manner facilitating interpretation. Rugged ligand expulsion paths are mapped into 2-dimensional space. The mapping retains the main structural changes occurring during the dissociation. The topological similarity of the reduced paths may be easily studied using the Fréchet distances, and we show that this measure facilitates machine learning classification of the diffusion pathways. Further, low-dimensional configuration space allows for identification of residues active in transport during the ligand diffusion from a protein. The utility of this approach is illustrated by examination of the configuration space of cytochrome P450cam involved in expulsing camphor by means of enhanced all-atom molecular dynamics simulations. The expulsion trajectories are sampled and constructed on-the-fly during molecular dynamics simulations using the recently developed memetic algorithms [ Rydzewski, J.; Nowak, W. J. Chem. Phys. 2015 , 143 ( 12 ), 124101 ]. We show that the memetic algorithms are effective for enforcing the ligand diffusion and cavity exploration in the P450cam-camphor complex. Furthermore, we demonstrate that machine learning techniques are helpful in inspecting ligand diffusion landscapes and provide useful tools to examine structural changes accompanying rare events.

Learning an intrinsic-variable preserving manifold for dynamic visual tracking.

PubMed

Qiao, Hong; Zhang, Peng; Zhang, Bo; Zheng, Suiwu

2010-06-01

Manifold learning is a hot topic in the field of computer science, particularly since nonlinear dimensionality reduction based on manifold learning was proposed in Science in 2000. The work has achieved great success. The main purpose of current manifold-learning approaches is to search for independent intrinsic variables underlying high dimensional inputs which lie on a low dimensional manifold. In this paper, a new manifold is built up in the training step of the process, on which the input training samples are set to be close to each other if the values of their intrinsic variables are close to each other. Then, the process of dimensionality reduction is transformed into a procedure of preserving the continuity of the intrinsic variables. By utilizing the new manifold, the dynamic tracking of a human who can move and rotate freely is achieved. From the theoretical point of view, it is the first approach to transfer the manifold-learning framework to dynamic tracking. From the application point of view, a new and low dimensional feature for visual tracking is obtained and successfully applied to the real-time tracking of a free-moving object from a dynamic vision system. Experimental results from a dynamic tracking system which is mounted on a dynamic robot validate the effectiveness of the new algorithm.

Strong anti-gravity Life in the shock wave

NASA Astrophysics Data System (ADS)

Fabbrichesi, Marco; Roland, Kaj

1992-12-01

Strong anti-gravity is the vanishing of the net force between two massive particles at rest, to all orders in Newton's constant. We study this phenomenon and show that it occurs in any effective theory of gravity which is obtained from a higher-dimensional model by compactification on a manifold with flat directions. We find the exact solution of the Einstein equations in the presence of a point-like source of strong anti-gravity by dimensional reduction of a shock-wave solution in the higher-dimensional model.

Landsat D Thematic Mapper image dimensionality reduction and geometric correction accuracy

NASA Technical Reports Server (NTRS)

Ford, G. E.

1986-01-01

To characterize and quantify the performance of the Landsat thematic mapper (TM), techniques for dimensionality reduction by linear transformation have been studied and evaluated and the accuracy of the correction of geometric errors in TM images analyzed. Theoretical evaluations and comparisons for existing methods for the design of linear transformation for dimensionality reduction are presented. These methods include the discrete Karhunen Loeve (KL) expansion, Multiple Discriminant Analysis (MDA), Thematic Mapper (TM)-Tasseled Cap Linear Transformation and Singular Value Decomposition (SVD). A unified approach to these design problems is presented in which each method involves optimizing an objective function with respect to the linear transformation matrix. From these studies, four modified methods are proposed. They are referred to as the Space Variant Linear Transformation, the KL Transform-MDA hybrid method, and the First and Second Version of the Weighted MDA method. The modifications involve the assignment of weights to classes to achieve improvements in the class conditional probability of error for classes with high weights. Experimental evaluations of the existing and proposed methods have been performed using the six reflective bands of the TM data. It is shown that in terms of probability of classification error and the percentage of the cumulative eigenvalues, the six reflective bands of the TM data require only a three dimensional feature space. It is shown experimentally as well that for the proposed methods, the classes with high weights have improvements in class conditional probability of error estimates as expected.

Reset noise suppression in two-dimensional CMOS photodiode pixels through column-based feedback-reset

NASA Technical Reports Server (NTRS)

Pain, B.; Cunningham, T. J.; Hancock, B.; Yang, G.; Seshadri, S.; Ortiz, M.

2002-01-01

We present new CMOS photodiode imager pixel with ultra-low read noise through on-chip suppression of reset noise via column-based feedback circuitry. The noise reduction is achieved without introducing any image lag, and with insignificant reduction in quantum efficiency and full well.

Multi-Level Reduced Order Modeling Equipped with Probabilistic Error Bounds

NASA Astrophysics Data System (ADS)

Abdo, Mohammad Gamal Mohammad Mostafa

This thesis develops robust reduced order modeling (ROM) techniques to achieve the needed efficiency to render feasible the use of high fidelity tools for routine engineering analyses. Markedly different from the state-of-the-art ROM techniques, our work focuses only on techniques which can quantify the credibility of the reduction which can be measured with the reduction errors upper-bounded for the envisaged range of ROM model application. Our objective is two-fold. First, further developments of ROM techniques are proposed when conventional ROM techniques are too taxing to be computationally practical. This is achieved via a multi-level ROM methodology designed to take advantage of the multi-scale modeling strategy typically employed for computationally taxing models such as those associated with the modeling of nuclear reactor behavior. Second, the discrepancies between the original model and ROM model predictions over the full range of model application conditions are upper-bounded in a probabilistic sense with high probability. ROM techniques may be classified into two broad categories: surrogate construction techniques and dimensionality reduction techniques, with the latter being the primary focus of this work. We focus on dimensionality reduction, because it offers a rigorous approach by which reduction errors can be quantified via upper-bounds that are met in a probabilistic sense. Surrogate techniques typically rely on fitting a parametric model form to the original model at a number of training points, with the residual of the fit taken as a measure of the prediction accuracy of the surrogate. This approach, however, does not generally guarantee that the surrogate model predictions at points not included in the training process will be bound by the error estimated from the fitting residual. Dimensionality reduction techniques however employ a different philosophy to render the reduction, wherein randomized snapshots of the model variables, such as the model parameters, responses, or state variables, are projected onto lower dimensional subspaces, referred to as the "active subspaces", which are selected to capture a user-defined portion of the snapshots variations. Once determined, the ROM model application involves constraining the variables to the active subspaces. In doing so, the contribution from the variables discarded components can be estimated using a fundamental theorem from random matrix theory which has its roots in Dixon's theory, developed in 1983. This theory was initially presented for linear matrix operators. The thesis extends this theorem's results to allow reduction of general smooth nonlinear operators. The result is an approach by which the adequacy of a given active subspace determined using a given set of snapshots, generated either using the full high fidelity model, or other models with lower fidelity, can be assessed, which provides insight to the analyst on the type of snapshots required to reach a reduction that can satisfy user-defined preset tolerance limits on the reduction errors. Reactor physics calculations are employed as a test bed for the proposed developments. The focus will be on reducing the effective dimensionality of the various data streams such as the cross-section data and the neutron flux. The developed methods will be applied to representative assembly level calculations, where the size of the cross-section and flux spaces are typically large, as required by downstream core calculations, in order to capture the broad range of conditions expected during reactor operation. (Abstract shortened by ProQuest.).

Sentinel Lymph Node Biopsy: Quantification of Lymphedema Risk Reduction

DTIC Science & Technology

2006-10-01

dimensional internal mammary lymphoscintigraphy: implications for radiation therapy treatment planning for breast carcinoma. Int J Radiat Oncol Biol Phys...techniques based on conventional photon beams, intensity modulated photon beams and proton beams for therapy of intact breast. Radiother Oncol. Feb...Harris JR. Three-dimensional internal mammary lymphoscintigraphy: implications for radiation therapy treatment planning for breast carcinoma. Int J

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

PubMed Central

Cowley, Benjamin R.; Kaufman, Matthew T.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2013-01-01

The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data) is typically greater than 3. However, direct plotting can only provide a 2D or 3D view. To address this limitation, we developed a Matlab graphical user interface (GUI) that allows the user to quickly navigate through a continuum of different 2D projections of the reduced-dimensional space. To demonstrate the utility and versatility of this GUI, we applied it to visualize population activity recorded in premotor and motor cortices during reaching tasks. Examples include single-trial population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded sequentially using single electrodes. Because any single 2D projection may provide a misleading impression of the data, being able to see a large number of 2D projections is critical for intuition- and hypothesis-building during exploratory data analysis. The GUI includes a suite of additional interactive tools, including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses. The use of visualization tools like the GUI developed here, in tandem with dimensionality reduction methods, has the potential to further our understanding of neural population activity. PMID:23366954

DataHigh: graphical user interface for visualizing and interacting with high-dimensional neural activity.

PubMed

Cowley, Benjamin R; Kaufman, Matthew T; Churchland, Mark M; Ryu, Stephen I; Shenoy, Krishna V; Yu, Byron M

2012-01-01

The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data) is typically greater than 3. However, direct plotting can only provide a 2D or 3D view. To address this limitation, we developed a Matlab graphical user interface (GUI) that allows the user to quickly navigate through a continuum of different 2D projections of the reduced-dimensional space. To demonstrate the utility and versatility of this GUI, we applied it to visualize population activity recorded in premotor and motor cortices during reaching tasks. Examples include single-trial population activity recorded using a multi-electrode array, as well as trial-averaged population activity recorded sequentially using single electrodes. Because any single 2D projection may provide a misleading impression of the data, being able to see a large number of 2D projections is critical for intuition-and hypothesis-building during exploratory data analysis. The GUI includes a suite of additional interactive tools, including playing out population activity timecourses as a movie and displaying summary statistics, such as covariance ellipses and average timecourses. The use of visualization tools like the GUI developed here, in tandem with dimensionality reduction methods, has the potential to further our understanding of neural population activity.

Enhanced Air Stability in REPb3 (RE = Rare Earths) by Dimensional Reduction Mediated Valence Transition.

PubMed

Subbarao, Udumula; Sarkar, Sumanta; Jana, Rajkumar; Bera, Sourav S; Peter, Sebastian C

2016-06-06

We conceptually selected the compounds REPb3 (RE = Eu, Yb), which are unstable in air, and converted them to the stable materials in ambient conditions by the chemical processes of "nanoparticle formation" and "dimensional reduction". The nanoparticles and the bulk counterparts were synthesized by the solvothermal and high-frequency induction furnace heating methods, respectively. The reduction of the particle size led to the valence transition of the rare earth atom, which was monitored through magnetic susceptibility and X-ray absorption near edge spectroscopy (XANES) measurements. The stability was checked by X-ray diffraction and thermogravimetric analysis over a period of seven months in oxygen and argon atmospheres and confirmed by XANES. The nanoparticles showed outstanding stability toward aerial oxidation over a period of seven months compared to the bulk counterpart, as the latter one is more prone to the oxidation within a few days.

The staircase method: integrals for periodic reductions of integrable lattice equations

NASA Astrophysics Data System (ADS)

van der Kamp, Peter H.; Quispel, G. R. W.

2010-11-01

We show, in full generality, that the staircase method (Papageorgiou et al 1990 Phys. Lett. A 147 106-14, Quispel et al 1991 Physica A 173 243-66) provides integrals for mappings, and correspondences, obtained as traveling wave reductions of (systems of) integrable partial difference equations. We apply the staircase method to a variety of equations, including the Korteweg-De Vries equation, the five-point Bruschi-Calogero-Droghei equation, the quotient-difference (QD)-algorithm and the Boussinesq system. We show that, in all these cases, if the staircase method provides r integrals for an n-dimensional mapping, with 2r, then one can introduce q <= 2r variables, which reduce the dimension of the mapping from n to q. These dimension-reducing variables are obtained as joint invariants of k-symmetries of the mappings. Our results support the idea that often the staircase method provides sufficiently many integrals for the periodic reductions of integrable lattice equations to be completely integrable. We also study reductions on other quad-graphs than the regular {\\ Z}^2 lattice, and we prove linear growth of the multi-valuedness of iterates of high-dimensional correspondences obtained as reductions of the QD-algorithm.

Influence of geomagnetic activity and earth weather changes on heart rate and blood pressure in young and healthy population

NASA Astrophysics Data System (ADS)

Ozheredov, V. A.; Chibisov, S. M.; Blagonravov, M. L.; Khodorovich, N. A.; Demurov, E. A.; Goryachev, V. A.; Kharlitskaya, E. V.; Eremina, I. S.; Meladze, Z. A.

2017-05-01

There are many references in the literature related to connection between the space weather and the state of human organism. The search of external factors influence on humans is a multi-factor problem and it is well known that humans have a meteo-sensitivity. A direct problem of finding the earth weather conditions, under which the space weather manifests itself most strongly, is discussed in the present work for the first time in the helio-biology. From a formal point of view, this problem requires identification of subset (magnetobiotropic region) in three-dimensional earth's weather parameters such as pressure, temperature, and humidity, corresponding to the days when the human body is the most sensitive to changes in the geomagnetic field variations and when it reacts by statistically significant increase (or decrease) of a particular physiological parameter. This formulation defines the optimization of the problem, and the solution of the latter is not possible without the involvement of powerful metaheuristic methods of searching. Using the algorithm of differential evolution, we prove the existence of magnetobiotropic regions in the earth's weather parameters, which exhibit magneto-sensitivity of systolic, diastolic blood pressure, and heart rate of healthy young subjects for three weather areas (combinations of atmospheric temperature, pressure, and humidity). The maximum value of the correlation confidence for the measurements attributable to the days of the weather conditions that fall into each of three magnetobiotropic areas is an order of 0.006, that is almost 10 times less than the confidence, equal to 0.05, accepted in many helio-biological researches.

Influence of geomagnetic activity and earth weather changes on heart rate and blood pressure in young and healthy population.

PubMed

Ozheredov, V A; Chibisov, S M; Blagonravov, M L; Khodorovich, N A; Demurov, E A; Goryachev, V A; Kharlitskaya, E V; Eremina, I S; Meladze, Z A

2017-05-01

There are many references in the literature related to connection between the space weather and the state of human organism. The search of external factors influence on humans is a multi-factor problem and it is well known that humans have a meteo-sensitivity. A direct problem of finding the earth weather conditions, under which the space weather manifests itself most strongly, is discussed in the present work for the first time in the helio-biology. From a formal point of view, this problem requires identification of subset (magnetobiotropic region) in three-dimensional earth's weather parameters such as pressure, temperature, and humidity, corresponding to the days when the human body is the most sensitive to changes in the geomagnetic field variations and when it reacts by statistically significant increase (or decrease) of a particular physiological parameter. This formulation defines the optimization of the problem, and the solution of the latter is not possible without the involvement of powerful metaheuristic methods of searching. Using the algorithm of differential evolution, we prove the existence of magnetobiotropic regions in the earth's weather parameters, which exhibit magneto-sensitivity of systolic, diastolic blood pressure, and heart rate of healthy young subjects for three weather areas (combinations of atmospheric temperature, pressure, and humidity). The maximum value of the correlation confidence for the measurements attributable to the days of the weather conditions that fall into each of three magnetobiotropic areas is an order of 0.006, that is almost 10 times less than the confidence, equal to 0.05, accepted in many helio-biological researches.

On the emergence of the ΛCDM model from self-interacting Brans-Dicke theory in d= 5

NASA Astrophysics Data System (ADS)

Reyes, Luz Marina; Perez Bergliaffa, Santiago Esteban

2018-01-01

We investigate whether a self-interacting Brans-Dicke theory in d=5 without matter and with a time-dependent metric can describe, after dimensional reduction to d=4, the FLRW model with accelerated expansion and non-relativistic matter. By rewriting the effective 4-dimensional theory as an autonomous 3-dimensional dynamical system and studying its critical points, we show that the ΛCDM cosmology cannot emerge from such a model. This result suggests that a richer structure in d=5 may be needed to obtain the accelerated expansion as well as the matter content of the 4-dimensional universe.

Perceived Gender Presentation Among Transgender and Gender Diverse Youth: Approaches to Analysis and Associations with Bullying Victimization and Emotional Distress.

PubMed

Gower, Amy L; Rider, G Nicole; Coleman, Eli; Brown, Camille; McMorris, Barbara J; Eisenberg, Marla E

2018-06-19

As measures of birth-assigned sex, gender identity, and perceived gender presentation are increasingly included in large-scale research studies, data analysis approaches incorporating such measures are needed. Large samples capable of demonstrating variation within the transgender and gender diverse (TGD) community can inform intervention efforts to improve health equity. A population-based sample of TGD youth was used to examine associations between perceived gender presentation, bullying victimization, and emotional distress using two data analysis approaches. Secondary data analysis of the Minnesota Student Survey included 2168 9th and 11th graders who identified as "transgender, genderqueer, genderfluid, or unsure about their gender identity." Youth reported their biological sex, how others perceived their gender presentation, experiences of four forms of bullying victimization, and four measures of emotional distress. Logistic regression and multifactor analysis of variance (ANOVA) were used to compare and contrast two analysis approaches. Logistic regressions indicated that TGD youth perceived as more gender incongruent had higher odds of bullying victimization and emotional distress relative to those perceived as very congruent with their biological sex. Multifactor ANOVAs demonstrated more variable patterns and allowed for comparisons of each perceived presentation group with all other groups, reflecting nuances that exist within TGD youth. Researchers should adopt data analysis strategies that allow for comparisons of all perceived gender presentation categories rather than assigning a reference group. Those working with TGD youth should be particularly attuned to youth perceived as gender incongruent as they may be more likely to experience bullying victimization and emotional distress.

Multi-factor challenge/response approach for remote biometric authentication

NASA Astrophysics Data System (ADS)

Al-Assam, Hisham; Jassim, Sabah A.

2011-06-01

Although biometric authentication is perceived to be more reliable than traditional authentication schemes, it becomes vulnerable to many attacks when it comes to remote authentication over open networks and raises serious privacy concerns. This paper proposes a biometric-based challenge-response approach to be used for remote authentication between two parties A and B over open networks. In the proposed approach, a remote authenticator system B (e.g. a bank) challenges its client A who wants to authenticate his/her self to the system by sending a one-time public random challenge. The client A responds by employing the random challenge along with secret information obtained from a password and a token to produce a one-time cancellable representation of his freshly captured biometric sample. The one-time biometric representation, which is based on multi-factor, is then sent back to B for matching. Here, we argue that eavesdropping of the one-time random challenge and/or the resulting one-time biometric representation does not compromise the security of the system, and no information about the original biometric data is leaked. In addition to securing biometric templates, the proposed protocol offers a practical solution for the replay attack on biometric systems. Moreover, we propose a new scheme for generating a password-based pseudo random numbers/permutation to be used as a building block in the proposed approach. The proposed scheme is also designed to provide protection against repudiation. We illustrate the viability and effectiveness of the proposed approach by experimental results based on two biometric modalities: fingerprint and face biometrics.

Reproducibility of three dimensional digital preoperative planning for the osteosynthesis of distal radius fractures.

PubMed

Yoshii, Yuichi; Kusakabe, Takuya; Akita, Kenichi; Tung, Wen Lin; Ishii, Tomoo

2017-12-01

A three-dimensional (3D) digital preoperative planning system for the osteosynthesis of distal radius fractures was developed for clinical practice. To assess the usefulness of the 3D planning for osteosynthesis, we evaluated the reproducibility of the reduction shapes and selected implants in the patients with distal radius fractures. Twenty wrists of 20 distal radius fracture patients who underwent osteosynthesis using volar locking plates were evaluated. The 3D preoperative planning was performed prior to each surgery. Four surgeons conducted the surgeries. The surgeons performed the reduction and the placement of the plate while comparing images between the preoperative plan and fluoroscopy. Preoperative planning and postoperative reductions were compared by measuring volar tilt and radial inclination of the 3D images. Intra-class correlation coefficients (ICCs) of the volar tilt and radial inclination were evaluated. For the implant choices, the ICCs for the screw lengths between the preoperative plan and the actual choices were evaluated. The ICCs were 0.644 (p < 0.01) and 0.625 (p < 0.01) for the volar tilt and radial inclination in the 3D measurements, respectively. The planned size of plate was used in all of the patients. The ICC for the screw length between preoperative planning and actual choice was 0.860 (p < 0.01). Good reproducibility for the reduction shape and excellent reproducibility for the implant choices were achieved using 3D preoperative planning for distal radius fracture. Three-dimensional digital planning was useful to visualize the reduction process and choose a proper implant for distal radius fractures. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2646-2651, 2017. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Biased normalized cuts for target detection in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Zhang, Xuewen; Dorado-Munoz, Leidy P.; Messinger, David W.; Cahill, Nathan D.

2016-05-01

The Biased Normalized Cuts (BNC) algorithm is a useful technique for detecting targets or objects in RGB imagery. In this paper, we propose modifying BNC for the purpose of target detection in hyperspectral imagery. As opposed to other target detection algorithms that typically encode target information prior to dimensionality reduction, our proposed algorithm encodes target information after dimensionality reduction, enabling a user to detect different targets in interactive mode. To assess the proposed BNC algorithm, we utilize hyperspectral imagery (HSI) from the SHARE 2012 data campaign, and we explore the relationship between the number and the position of expert-provided target labels and the precision/recall of the remaining targets in the scene.

Large Reduction of Hot Spot Temperature in Graphene Electronic Devices with Heat-Spreading Hexagonal Boron Nitride.

PubMed

Choi, David; Poudel, Nirakar; Park, Saungeun; Akinwande, Deji; Cronin, Stephen B; Watanabe, Kenji; Taniguchi, Takashi; Yao, Zhen; Shi, Li

2018-04-04

Scanning thermal microscopy measurements reveal a significant thermal benefit of including a high thermal conductivity hexagonal boron nitride (h-BN) heat-spreading layer between graphene and either a SiO 2 /Si substrate or a 100 μm thick Corning flexible Willow glass (WG) substrate. At the same power density, an 80 nm thick h-BN layer on the silicon substrate can yield a factor of 2.2 reduction of the hot spot temperature, whereas a 35 nm thick h-BN layer on the WG substrate is sufficient to obtain a factor of 4.1 reduction. The larger effect of the h-BN heat spreader on WG than on SiO 2 /Si is attributed to a smaller effective heat transfer coefficient per unit area for three-dimensional heat conduction into the thick, low-thermal conductivity WG substrate than for one-dimensional heat conduction through the thin oxide layer on silicon. Consequently, the h-BN lateral heat-spreading length is much larger on WG than on SiO 2 /Si, resulting in a larger degree of temperature reduction.

Relativistic collisions as Yang-Baxter maps

NASA Astrophysics Data System (ADS)

Kouloukas, Theodoros E.

2017-10-01

We prove that one-dimensional elastic relativistic collisions satisfy the set-theoretical Yang-Baxter equation. The corresponding collision maps are symplectic and admit a Lax representation. Furthermore, they can be considered as reductions of a higher dimensional integrable Yang-Baxter map on an invariant manifold. In this framework, we study the integrability of transfer maps that represent particular periodic sequences of collisions.

Black Hole Entropy from Bondi-Metzner-Sachs Symmetry at the Horizon.

PubMed

Carlip, S

2018-03-09

Near the horizon, the obvious symmetries of a black hole spacetime-the horizon-preserving diffeomorphisms-are enhanced to a larger symmetry group with a three-dimensional Bondi-Metzner-Sachs algebra. Using dimensional reduction and covariant phase space techniques, I investigate this augmented symmetry and show that it is strong enough to determine the black hole entropy in any dimension.

Chaos in plasma simulation and experiment

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

Watts, C.; Newman, D.E.; Sprott, J.C.

1993-09-01

We investigate the possibility that chaos and simple determinism are governing the dynamics of reversed field pinch (RFP) plasmas using data from both numerical simulations and experiment. A large repertoire of nonlinear analysis techniques is used to identify low dimensional chaos. These tools include phase portraits and Poincard sections, correlation dimension, the spectrum of Lyapunov exponents and short term predictability. In addition, nonlinear noise reduction techniques are applied to the experimental data in an attempt to extract any underlying deterministic dynamics. Two model systems are used to simulate the plasma dynamics. These are -the DEBS code, which models global RFPmore » dynamics, and the dissipative trapped electron mode (DTEM) model, which models drift wave turbulence. Data from both simulations show strong indications of low,dimensional chaos and simple determinism. Experimental data were obtained from the Madison Symmetric Torus RFP and consist of a wide array of both global and local diagnostic signals. None of the signals shows any indication of low dimensional chaos or other simple determinism. Moreover, most of the analysis tools indicate the experimental system is very high dimensional with properties similar to noise. Nonlinear noise reduction is unsuccessful at extracting an underlying deterministic system.« less

Principal component analysis on a torus: Theory and application to protein dynamics.

PubMed

Sittel, Florian; Filk, Thomas; Stock, Gerhard

2017-12-28

A dimensionality reduction method for high-dimensional circular data is developed, which is based on a principal component analysis (PCA) of data points on a torus. Adopting a geometrical view of PCA, various distance measures on a torus are introduced and the associated problem of projecting data onto the principal subspaces is discussed. The main idea is that the (periodicity-induced) projection error can be minimized by transforming the data such that the maximal gap of the sampling is shifted to the periodic boundary. In a second step, the covariance matrix and its eigendecomposition can be computed in a standard manner. Adopting molecular dynamics simulations of two well-established biomolecular systems (Aib 9 and villin headpiece), the potential of the method to analyze the dynamics of backbone dihedral angles is demonstrated. The new approach allows for a robust and well-defined construction of metastable states and provides low-dimensional reaction coordinates that accurately describe the free energy landscape. Moreover, it offers a direct interpretation of covariances and principal components in terms of the angular variables. Apart from its application to PCA, the method of maximal gap shifting is general and can be applied to any other dimensionality reduction method for circular data.

Principal component analysis on a torus: Theory and application to protein dynamics

NASA Astrophysics Data System (ADS)

Sittel, Florian; Filk, Thomas; Stock, Gerhard

2017-12-01

A dimensionality reduction method for high-dimensional circular data is developed, which is based on a principal component analysis (PCA) of data points on a torus. Adopting a geometrical view of PCA, various distance measures on a torus are introduced and the associated problem of projecting data onto the principal subspaces is discussed. The main idea is that the (periodicity-induced) projection error can be minimized by transforming the data such that the maximal gap of the sampling is shifted to the periodic boundary. In a second step, the covariance matrix and its eigendecomposition can be computed in a standard manner. Adopting molecular dynamics simulations of two well-established biomolecular systems (Aib9 and villin headpiece), the potential of the method to analyze the dynamics of backbone dihedral angles is demonstrated. The new approach allows for a robust and well-defined construction of metastable states and provides low-dimensional reaction coordinates that accurately describe the free energy landscape. Moreover, it offers a direct interpretation of covariances and principal components in terms of the angular variables. Apart from its application to PCA, the method of maximal gap shifting is general and can be applied to any other dimensionality reduction method for circular data.

Comparative analysis of methods for detecting interacting loci

PubMed Central

2011-01-01

Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. Conclusion This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list. PMID:21729295

Comparative analysis of methods for detecting interacting loci.

PubMed

Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue

2011-07-05

Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

The interactive effects of genetic polymorphisms within LFA-1/ICAM-1/GSK-3β pathway and environmental hazards on the development of Graves' opthalmopathy.

PubMed

Yang, Ge; Fu, Yang; Lu, Xiaoyan; Wang, Menghua; Dong, Hongtao; Li, Qiuming

2018-05-22

The purpose of this investigation was to explore the combined effects of single nucleotide polymorphisms (SNPs) within LFA-1/ICAM-1/GSK-3β pathway and environmental hazards on susceptibility to Graves' opthalmopathy (GO) among a Chinese Han population. Altogether 305 GO patients and 283 Graves' disease (GD) subjects were recruited. Information relevant to the participants' age, gender, body mass index (BMI), regular physical activity, smoking history, alcohol intake, stressful work environment, stress at work, family history of thyroid disease and 131 I treatment were summarized, and the participants' related SNPs of LFA-1/ICAM-1/GSK-3β were also detected. Then the gene-gene and gene-environment interactions were evaluated by logistic regression model and multi-factor dimensionality reduction (MDR) modeling. The results exhibited that age, BMI, smoking history, stressful work, stress at home, family history of thyroid disease and 131 I treatment appeared as potential indicators regulating GO risk, when either univariate or multivariate regression analysis was performed (all P < 0.05). Moreover, rs12716977 (T > C) and rs2230433 (G > C) of LFA-1, rs1799969 (G > A) and rs5498 (A > G) of ICAM-1, as well as rs6438552 (T > C) and rs334558 (T > C) of GSK-3β were significantly associated with altered susceptibility to GO under the allelic models (all P < 0.05). Also haplotype TGAATC acted as a protective factor against GO risk (P < 0.05), whereas haplotype CGAACC largely elevated risk of GO (P < 0.05). Besides, logistic regression analysis demonstrated that rs12716927, rs5498 and rs6438552 all would affect the influences exerted by age, BMI, smoking history, stressful work, stress at home, family history of thyroid disease or 131 I treatment on GO susceptibility (all P < 0.05). MDR modeling implied that the combined model of rs12716977, rs2230433 and rs1799969 was the supreme interactive model when BMI was co-assessed, and the interactive model of rs12716977, rs334558 and rs5491 was the most desirable among the smoking population. In conclusion, gene-gene and gene-environment interactions served as a crucial manner in affecting susceptibility to GO, providing solid evidences for screening effective GO-susceptible biomarkers and exploring potential GO treatment strategies. Copyright © 2018. Published by Elsevier Ltd.

Online dimensionality reduction using competitive learning and Radial Basis Function network.

PubMed

Tomenko, Vladimir

2011-06-01

The general purpose dimensionality reduction method should preserve data interrelations at all scales. Additional desired features include online projection of new data, processing nonlinearly embedded manifolds and large amounts of data. The proposed method, called RBF-NDR, combines these features. RBF-NDR is comprised of two modules. The first module learns manifolds by utilizing modified topology representing networks and geodesic distance in data space and approximates sampled or streaming data with a finite set of reference patterns, thus achieving scalability. Using input from the first module, the dimensionality reduction module constructs mappings between observation and target spaces. Introduction of specific loss function and synthesis of the training algorithm for Radial Basis Function network results in global preservation of data structures and online processing of new patterns. The RBF-NDR was applied for feature extraction and visualization and compared with Principal Component Analysis (PCA), neural network for Sammon's projection (SAMANN) and Isomap. With respect to feature extraction, the method outperformed PCA and yielded increased performance of the model describing wastewater treatment process. As for visualization, RBF-NDR produced superior results compared to PCA and SAMANN and matched Isomap. For the Topic Detection and Tracking corpus, the method successfully separated semantically different topics. Copyright © 2011 Elsevier Ltd. All rights reserved.

SPHARA--a generalized spatial Fourier analysis for multi-sensor systems with non-uniformly arranged sensors: application to EEG.

PubMed

Graichen, Uwe; Eichardt, Roland; Fiedler, Patrique; Strohmeier, Daniel; Zanow, Frank; Haueisen, Jens

2015-01-01

Important requirements for the analysis of multichannel EEG data are efficient techniques for signal enhancement, signal decomposition, feature extraction, and dimensionality reduction. We propose a new approach for spatial harmonic analysis (SPHARA) that extends the classical spatial Fourier analysis to EEG sensors positioned non-uniformly on the surface of the head. The proposed method is based on the eigenanalysis of the discrete Laplace-Beltrami operator defined on a triangular mesh. We present several ways to discretize the continuous Laplace-Beltrami operator and compare the properties of the resulting basis functions computed using these discretization methods. We apply SPHARA to somatosensory evoked potential data from eleven volunteers and demonstrate the ability of the method for spatial data decomposition, dimensionality reduction and noise suppression. When employing SPHARA for dimensionality reduction, a significantly more compact representation can be achieved using the FEM approach, compared to the other discretization methods. Using FEM, to recover 95% and 99% of the total energy of the EEG data, on average only 35% and 58% of the coefficients are necessary. The capability of SPHARA for noise suppression is shown using artificial data. We conclude that SPHARA can be used for spatial harmonic analysis of multi-sensor data at arbitrary positions and can be utilized in a variety of other applications.

Inflation from extra dimensions

NASA Astrophysics Data System (ADS)

Levin, Janna J.

1995-02-01

A gravity-driven inflation is shown to arise from a simple higher-dimensional universe. In vacuum, the shear of n > 1 contracting dimensions is able to inflate the remaining three spatial dimensions. Said another way, the expansion of the 3-volume is accelerated by the contraction of the n-volume. Upon dimensional reduction, the theory is equivalent to a four-dimensional cosmology with a dynamical Planck mass. A connection can therefore be made to recent examples of inflation powered by a dilaton kinetic energy. Unfortunately, the graceful exit problem encountered in dilaton cosmologies will haunt this cosmology as well.

Dimensional and compositional change of 1D chalcogen nanostructures leading to tunable localized surface plasmon resonances.

PubMed

Min, Yuho; Seo, Ho Jun; Choi, Jong-Jin; Hahn, Byung-Dong; Moon, Geon Dae

2018-08-24

As part of the oxygen family, chalcogen (Se, Te) nanostructures have been considered important elements for various practical fields and further exploited to constitute metal chalcogenides for each targeted application. Here, we report a controlled synthesis of well-defined one-dimensional chalcogen nanostructures such as nanowries, nanorods, and nanotubes by controlling reduction reaction rate to fine-tune the dimension and composition of the products. Tunable optical properties (localized surface plasmon resonances) of these chalcogen nanostructures are observed depending on their morphological, dimensional, and compositional variation.

The role of floodplain restoration in mitigating flood risk, Lower Missouri River, USA

USGS Publications Warehouse

Jacobson, Robert B.; Lindner, Garth; Bitner, Chance; Hudson, Paul F.; Middelkoop, Hans

2015-01-01

Recent extreme floods on the Lower Missouri River have reinvigorated public policy debate about the potential role of floodplain restoration in decreasing costs of floods and possibly increasing other ecosystem service benefits. The first step to addressing the benefits of floodplain restoration is to understand the interactions of flow, floodplain morphology, and land cover that together determine the biophysical capacity of the floodplain. In this article we address interactions between ecological restoration of floodplains and flood-risk reduction at 3 scales. At the scale of the Lower Missouri River corridor (1300 km) floodplain elevation datasets and flow models provide first-order calculations of the potential for Missouri River floodplains to store floods of varying magnitude and duration. At this same scale assessment of floodplain sand deposition from the 2011 Missouri River flood indicates the magnitude of flood damage that could potentially be limited by floodplain restoration. At the segment scale (85 km), 1-dimensional hydraulic modeling predicts substantial stage reductions with increasing area of floodplain restoration; mean stage reductions range from 0.12 to 0.66 m. This analysis also indicates that channel widening may contribute substantially to stage reductions as part of a comprehensive strategy to restore floodplain and channel habitats. Unsteady 1-dimensional flow modeling of restoration scenarios at this scale indicates that attenuation of peak discharges of an observed hydrograph from May 2007, of similar magnitude to a 10 % annual exceedance probability flood, would be minimal, ranging from 0.04 % (with 16 % floodplain restoration) to 0.13 % (with 100 % restoration). At the reach scale (15–20 km) 2-dimensional hydraulic models of alternative levee setbacks and floodplain roughness indicate complex processes and patterns of flooding including substantial variation in stage reductions across floodplains depending on topographic complexity and hydraulic roughness. Detailed flow patterns captured in the 2-dimensional model indicate that most floodplain storage occurs on the rising limb of the flood as water flows into floodplain bottoms from downstream; at a later time during the rising limb this pattern is reversed and the entire bottom conveys discharge down the valley. These results indicate that flood-risk reduction by attenuation is likely to be small on a large river like the Missouri and design strategies to optimize attenuation and ecological restoration should focus on frequent floods (20–50 % annual exceedance probability). Local stage reductions are a more certain benefit of floodplain restoration but local effects are highly dependent on magnitude of flood discharge and how floodplain vegetation communities contribute to hydraulic roughness. The most certain flood risk reduction benefit of floodplain restoration is avoidance of flood damages to crops and infrastructure.

A new approach for solving seismic tomography problems and assessing the uncertainty through the use of graph theory and direct methods

NASA Astrophysics Data System (ADS)

Bogiatzis, P.; Ishii, M.; Davis, T. A.

2016-12-01

Seismic tomography inverse problems are among the largest high-dimensional parameter estimation tasks in Earth science. We show how combinatorics and graph theory can be used to analyze the structure of such problems, and to effectively decompose them into smaller ones that can be solved efficiently by means of the least squares method. In combination with recent high performance direct sparse algorithms, this reduction in dimensionality allows for an efficient computation of the model resolution and covariance matrices using limited resources. Furthermore, we show that a new sparse singular value decomposition method can be used to obtain the complete spectrum of the singular values. This procedure provides the means for more objective regularization and further dimensionality reduction of the problem. We apply this methodology to a moderate size, non-linear seismic tomography problem to image the structure of the crust and the upper mantle beneath Japan using local deep earthquakes recorded by the High Sensitivity Seismograph Network stations.

Light-cone reduction vs. TsT transformations: a fluid dynamics perspective

NASA Astrophysics Data System (ADS)

Dutta, Suvankar; Krishna, Hare

2018-05-01

We compute constitutive relations for a charged (2+1) dimensional Schrödinger fluid up to first order in derivative expansion, using holographic techniques. Starting with a locally boosted, asymptotically AdS, 4 + 1 dimensional charged black brane geometry, we uplift that to ten dimensions and perform TsT transformations to obtain an effective five dimensional local black brane solution with asymptotically Schrödinger isometries. By suitably implementing the holographic techniques, we compute the constitutive relations for the effective fluid living on the boundary of this space-time and extract first order transport coefficients from these relations. Schrödinger fluid can also be obtained by reducing a charged relativistic conformal fluid over light-cone. It turns out that both the approaches result the same system at the end. Fluid obtained by light-cone reduction satisfies a restricted class of thermodynamics. Here, we see that the charged fluid obtained holographically also belongs to the same restricted class.

Effective dimensional reduction algorithm for eigenvalue problems for thin elastic structures: A paradigm in three dimensions

PubMed Central

Ovtchinnikov, Evgueni E.; Xanthis, Leonidas S.

2000-01-01

We present a methodology for the efficient numerical solution of eigenvalue problems of full three-dimensional elasticity for thin elastic structures, such as shells, plates and rods of arbitrary geometry, discretized by the finite element method. Such problems are solved by iterative methods, which, however, are known to suffer from slow convergence or even convergence failure, when the thickness is small. In this paper we show an effective way of resolving this difficulty by invoking a special preconditioning technique associated with the effective dimensional reduction algorithm (EDRA). As an example, we present an algorithm for computing the minimal eigenvalue of a thin elastic plate and we show both theoretically and numerically that it is robust with respect to both the thickness and discretization parameters, i.e. the convergence does not deteriorate with diminishing thickness or mesh refinement. This robustness is sine qua non for the efficient computation of large-scale eigenvalue problems for thin elastic structures. PMID:10655469

Holocinematographic velocimeter for measuring time-dependent, three-dimensional flows

NASA Technical Reports Server (NTRS)

Beeler, George B.; Weinstein, Leonard M.

1987-01-01

Two simulatneous, orthogonal-axis holographic movies are made of tracer particles in a low-speed water tunnel to determine the time-dependent, three-dimensional velocity field. This instrument is called a Holocinematographic Velocimeter (HCV). The holographic movies are reduced to the velocity field with an automatic data reduction system. This permits the reduction of large numbers of holograms (time steps) in a reasonable amount of time. The current version of the HCV, built for proof-of-concept tests, uses low-frame rate holographic cameras and a prototype of a new type of water tunnel. This water tunnel is a unique low-disturbance facility which has minimal wall effects on the flow. This paper presents the first flow field examined by the HCV, the two-dimensional von Karman vortex street downstream of an unswept circular cylinder. Key factors in the HCV are flow speed, spatial and temporal resolution required, measurement volume, film transport speed, and laser pulse length. The interactions between these factors are discussed.

Reductions in finite-dimensional integrable systems and special points of classical r-matrices

NASA Astrophysics Data System (ADS)

Skrypnyk, T.

2016-12-01

For a given 𝔤 ⊗ 𝔤-valued non-skew-symmetric non-dynamical classical r-matrices r(u, v) with spectral parameters, we construct the general form of 𝔤-valued Lax matrices of finite-dimensional integrable systems satisfying linear r-matrix algebra. We show that the reduction in the corresponding finite-dimensional integrable systems is connected with "the special points" of the classical r-matrices in which they become degenerated. We also propose a systematic way of the construction of additional integrals of the Lax-integrable systems associated with the symmetries of the corresponding r-matrices. We consider examples of the Lax matrices and integrable systems that are obtained in the framework of the general scheme. Among them there are such physically important systems as generalized Gaudin systems in an external magnetic field, ultimate integrable generalization of Toda-type chains (including "modified" or "deformed" Toda chains), generalized integrable Jaynes-Cummings-Dicke models, integrable boson models generalizing Bose-Hubbard dimer models, etc.

Neural networks for dimensionality reduction of fluorescence spectra and prediction of drinking water disinfection by-products.

PubMed

Peleato, Nicolas M; Legge, Raymond L; Andrews, Robert C

2018-06-01

The use of fluorescence data coupled with neural networks for improved predictability of drinking water disinfection by-products (DBPs) was investigated. Novel application of autoencoders to process high-dimensional fluorescence data was related to common dimensionality reduction techniques of parallel factors analysis (PARAFAC) and principal component analysis (PCA). The proposed method was assessed based on component interpretability as well as for prediction of organic matter reactivity to formation of DBPs. Optimal prediction accuracies on a validation dataset were observed with an autoencoder-neural network approach or by utilizing the full spectrum without pre-processing. Latent representation by an autoencoder appeared to mitigate overfitting when compared to other methods. Although DBP prediction error was minimized by other pre-processing techniques, PARAFAC yielded interpretable components which resemble fluorescence expected from individual organic fluorophores. Through analysis of the network weights, fluorescence regions associated with DBP formation can be identified, representing a potential method to distinguish reactivity between fluorophore groupings. However, distinct results due to the applied dimensionality reduction approaches were observed, dictating a need for considering the role of data pre-processing in the interpretability of the results. In comparison to common organic measures currently used for DBP formation prediction, fluorescence was shown to improve prediction accuracies, with improvements to DBP prediction best realized when appropriate pre-processing and regression techniques were applied. The results of this study show promise for the potential application of neural networks to best utilize fluorescence EEM data for prediction of organic matter reactivity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison of cryoablation with 3D mapping versus conventional mapping for the treatment of atrioventricular re-entrant tachycardia and right-sided paraseptal accessory pathways.

PubMed

Russo, Mario S; Drago, Fabrizio; Silvetti, Massimo S; Righi, Daniela; Di Mambro, Corrado; Placidi, Silvia; Prosperi, Monica; Ciani, Michele; Naso Onofrio, Maria T; Cannatà, Vittorio

2016-06-01

Aim Transcatheter cryoablation is a well-established technique for the treatment of atrioventricular nodal re-entry tachycardia and atrioventricular re-entry tachycardia in children. Fluoroscopy or three-dimensional mapping systems can be used to perform the ablation procedure. The aim of this study was to compare the success rate of cryoablation procedures for the treatment of right septal accessory pathways and atrioventricular nodal re-entry circuits in children using conventional or three-dimensional mapping and to evaluate whether three-dimensional mapping was associated with reduced patient radiation dose compared with traditional mapping. In 2013, 81 children underwent transcatheter cryoablation at our institution, using conventional mapping in 41 children - 32 atrioventricular nodal re-entry tachycardia and nine atrioventricular re-entry tachycardia - and three-dimensional mapping in 40 children - 24 atrioventricular nodal re-entry tachycardia and 16 atrioventricular re-entry tachycardia. Using conventional mapping, the overall success rate was 78.1 and 66.7% in patients with atrioventricular nodal re-entry tachycardia or atrioventricular re-entry tachycardia, respectively. Using three-dimensional mapping, the overall success rate was 91.6 and 75%, respectively (p=ns). The use of three-dimensional mapping was associated with a reduction in cumulative air kerma and cumulative air kerma-area product of 76.4 and 67.3%, respectively (p<0.05). The use of three-dimensional mapping compared with the conventional fluoroscopy-guided method for cryoablation of right septal accessory pathways and atrioventricular nodal re-entry circuits in children was associated with a significant reduction in patient radiation dose without an increase in success rate.

Dimensional reduction of a general advection–diffusion equation in 2D channels

NASA Astrophysics Data System (ADS)

Kalinay, Pavol; Slanina, František

2018-06-01

Diffusion of point-like particles in a two-dimensional channel of varying width is studied. The particles are driven by an arbitrary space dependent force. We construct a general recurrence procedure mapping the corresponding two-dimensional advection-diffusion equation onto the longitudinal coordinate x. Unlike the previous specific cases, the presented procedure enables us to find the one-dimensional description of the confined diffusion even for non-conservative (vortex) forces, e.g. caused by flowing solvent dragging the particles. We show that the result is again the generalized Fick–Jacobs equation. Despite of non existing scalar potential in the case of vortex forces, the effective one-dimensional scalar potential, as well as the corresponding quasi-equilibrium and the effective diffusion coefficient can be always found.

[New International Classification of Chronic Pancreatitis (M-ANNHEIM multifactor classification system, 2007): principles, merits, and demerits].

PubMed

Tsimmerman, Ia S

2008-01-01

The new International Classification of Chronic Pancreatitis (designated as M-ANNHEIM) proposed by a group of German specialists in late 2007 is reviewed. All its sections are subjected to analysis (risk group categories, clinical stages and phases, variants of clinical course, diagnostic criteria for "established" and "suspected" pancreatitis, instrumental methods and functional tests used in the diagnosis, evaluation of the severity of the disease using a scoring system, stages of elimination of pain syndrome). The new classification is compared with the earlier classification proposed by the author. Its merits and demerits are discussed.

[Typology and systematization of residual mental disorders in alcohol dependence].

PubMed

Klimenko, T V; Agafonova, S S

2007-01-01

The study of 85 patients with alcohol dependence appointed to forensic psychiatric expertise in the Serbsky research center of social and forensic psychiatry revealed the manifestation of polymorphic psychiatric and behavioral disorders (ICD-10 diagnosis F10.7--residual and late-onset psychotic disorders) after stopping the intoxication, withdrawal and post-withdralwal disorders. Taking into account the multifactor etiology of psychiatric disorders which are observed after ending of the direct effect of alcohol, a possibility of including other ICD-10 items to extend their diagnostics and thus provide the more accurate clinical verification of these states, is discussed.

Crop status evaluations and yield predictions

NASA Technical Reports Server (NTRS)

Haun, J. R.

1976-01-01

One phase of the large area crop inventory project is presented. Wheat yield models based on the input of environmental variables potentially obtainable through the use of space remote sensing were developed and demonstrated. By the use of a unique method for visually qualifying daily plant development and subsequent multifactor computer analyses, it was possible to develop practical models for predicting crop development and yield. Development of wheat yield prediction models was based on the discovery that morphological changes in plants are detected and quantified on a daily basis, and that this change during a portion of the season was proportional to yield.

Characteristics of group networks in the KOSPI and the KOSDAQ

NASA Astrophysics Data System (ADS)

Kim, Kyungsik; Ko, Jeung-Su; Yi, Myunggi

2012-02-01

We investigate the main feature of group networks in the KOSPI and KOSDAQ of Korean financial markets and analyze daily cross-correlations between price fluctuations for the 5-year time period from 2006 to 2010. We discuss the stabilities by undressing the market-wide effect using the Markowitz multi-factor model and the network-based approach. In particular we ascertain the explicit list of significant firms in the few largest eigenvectors from the undressed correlation matrix. Finally, we show the structure of group correlation by applying a network-based approach. In addition, the relation between market capitalizations and businesses is examined.

Building and verifying a severity prediction model of acute pancreatitis (AP) based on BISAP, MEWS and routine test indexes.

PubMed

Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei

2017-10-01

To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value<0.001), whereas RDW is not a prediction index of AP severity (P-value>0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value<0.001), and MEWS is not an independent prediction index of AP severity (P-value>0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-value<0.001). The constructed model is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP and serum Ca2+ individually (P-value<0.01). Verification of the internal validity of the models by bootstrapping is favorable. BISAP and serum Ca2+ have high predictive value for the severity of AP. However, the model built by combining BISAP and serum Ca2+ is remarkably superior to those of BISAP and serum Ca2+ individually. Furthermore, this model is simple, practical and appropriate for clinical use. Copyright © 2016. Published by Elsevier Masson SAS.

Vascular and parenchymal amyloid pathology in an Alzheimer disease knock-in mouse model: interplay with cerebral blood flow.

PubMed

Li, Hongmei; Guo, Qinxi; Inoue, Taeko; Polito, Vinicia A; Tabuchi, Katsuhiko; Hammer, Robert E; Pautler, Robia G; Taffet, George E; Zheng, Hui

2014-08-09

Accumulation and deposition of β-amyloid peptides (Aβ) in the brain is a central event in the pathogenesis of Alzheimer's disease (AD). Besides the parenchymal pathology, Aβ is known to undergo active transport across the blood-brain barrier and cerebral amyloid angiopathy (CAA) is a prominent feature in the majority of AD. Although impaired cerebral blood flow (CBF) has been implicated in faulty Aβ transport and clearance, and cerebral hypoperfusion can exist in the pre-clinical phase of Alzheimer's disease (AD), it is still unclear whether it is one of the causal factors for AD pathogenesis, or an early consequence of a multi-factor condition that would lead to AD at late stage. To study the potential interaction between faulty CBF and amyloid accumulation in clinical-relevant situation, we generated a new amyloid precursor protein (APP) knock-in allele that expresses humanized Aβ and a Dutch mutation in addition to Swedish/London mutations and compared this line with an equivalent knock-in line but in the absence of the Dutch mutation, both crossed onto the PS1M146V knock-in background. Introduction of the Dutch mutation results in robust CAA and parenchymal Aβ pathology, age-dependent reduction of spatial learning and memory deficits, and CBF reduction as detected by fMRI. Direct manipulation of CBF by transverse aortic constriction surgery on the left common carotid artery caused differential changes in CBF in the anterior and middle region of the cortex, where it is reduced on the left side and increased on the right side. However these perturbations in CBF resulted in the same effect: both significantly exacerbate CAA and amyloid pathology. Our study reveals a direct and positive link between vascular and parenchymal Aβ; both can be modulated by CBF. The new APP knock-in mouse model recapitulates many symptoms of AD including progressive vascular and parenchymal Aβ pathology and behavioral deficits in the absence of APP overexpression.

Travelling-wave solutions of a weakly nonlinear two-dimensional higher-order Kadomtsev-Petviashvili dynamical equation for dispersive shallow-water waves

NASA Astrophysics Data System (ADS)

Seadawy, Aly R.

2017-01-01

The propagation of three-dimensional nonlinear irrotational flow of an inviscid and incompressible fluid of the long waves in dispersive shallow-water approximation is analyzed. The problem formulation of the long waves in dispersive shallow-water approximation lead to fifth-order Kadomtsev-Petviashvili (KP) dynamical equation by applying the reductive perturbation theory. By using an extended auxiliary equation method, the solitary travelling-wave solutions of the two-dimensional nonlinear fifth-order KP dynamical equation are derived. An analytical as well as a numerical solution of the two-dimensional nonlinear KP equation are obtained and analyzed with the effects of external pressure flow.

Exact solutions to three-dimensional generalized nonlinear Schrödinger equations with varying potential and nonlinearities.

PubMed

Yan, Zhenya; Konotop, V V

2009-09-01

It is shown that using the similarity transformations, a set of three-dimensional p-q nonlinear Schrödinger (NLS) equations with inhomogeneous coefficients can be reduced to one-dimensional stationary NLS equation with constant or varying coefficients, thus allowing for obtaining exact localized and periodic wave solutions. In the suggested reduction the original coordinates in the (1+3) space are mapped into a set of one-parametric coordinate surfaces, whose parameter plays the role of the coordinate of the one-dimensional equation. We describe the algorithm of finding solutions and concentrate on power (linear and nonlinear) potentials presenting a number of case examples. Generalizations of the method are also discussed.

Robust video copy detection approach based on local tangent space alignment

NASA Astrophysics Data System (ADS)

Nie, Xiushan; Qiao, Qianping

2012-04-01

We propose a robust content-based video copy detection approach based on local tangent space alignment (LTSA), which is an efficient dimensionality reduction algorithm. The idea is motivated by the fact that the content of video becomes richer and the dimension of content becomes higher. It does not give natural tools for video analysis and understanding because of the high dimensionality. The proposed approach reduces the dimensionality of video content using LTSA, and then generates video fingerprints in low dimensional space for video copy detection. Furthermore, a dynamic sliding window is applied to fingerprint matching. Experimental results show that the video copy detection approach has good robustness and discrimination.

Finite-dimensional approximation for optimal fixed-order compensation of distributed parameter systems

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Rosen, I. G.

1988-01-01

In controlling distributed parameter systems it is often desirable to obtain low-order, finite-dimensional controllers in order to minimize real-time computational requirements. Standard approaches to this problem employ model/controller reduction techniques in conjunction with LQG theory. In this paper we consider the finite-dimensional approximation of the infinite-dimensional Bernstein/Hyland optimal projection theory. This approach yields fixed-finite-order controllers which are optimal with respect to high-order, approximating, finite-dimensional plant models. The technique is illustrated by computing a sequence of first-order controllers for one-dimensional, single-input/single-output, parabolic (heat/diffusion) and hereditary systems using spline-based, Ritz-Galerkin, finite element approximation. Numerical studies indicate convergence of the feedback gains with less than 2 percent performance degradation over full-order LQG controllers for the parabolic system and 10 percent degradation for the hereditary system.

Two-dimensional nanostructured Y{sub 2}O{sub 3} particles for viscosity modification

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

He, Xingliang; Xiao, Huaping; Liang, Hong, E-mail: hliang@tamu.edu

Nanoparticle additives have been shown to improve the mechanical and transport phenomena of various liquids; however, little has been done to try and explain the rheological modifications provided from such modifications from a theoretical standpoint. Here, we report a non-Einstein-like reduction of viscosity of mineral oil with the utilization of yttrium oxide nanosheet additives. Experimental results, coupled with generalized smoothed-particle hydrodynamics simulations, provide insight into the mechanism behind this reduction of fluid shear stress. The ordered inclination of these two-dimensional nanoparticle additives markedly improves the lubricating properties of the mineral oil, ultimately reducing the friction, and providing a way inmore » designing and understanding next generation of lubricants.« less

General solution of a cosmological model induced from higher dimensions using a kinematical constraint

NASA Astrophysics Data System (ADS)

Akarsu, Özgür; Dereli, Tekin; Katırcı, Nihan; Sheftel, Mikhail B.

2015-05-01

In a recent study Akarsu and Dereli (Gen. Relativ. Gravit. 45:1211, 2013) discussed the dynamical reduction of a higher dimensional cosmological model which is augmented by a kinematical constraint characterized by a single real parameter, correlating and controlling the expansion of both the external (physical) and internal spaces. In that paper explicit solutions were found only for the case of three dimensional internal space (). Here we derive a general solution of the system using Lie group symmetry properties, in parametric form for arbitrary number of internal dimensions. We also investigate the dynamical reduction of the model as a function of cosmic time for various values of and generate parametric plots to discuss cosmologically relevant results.

ODF Maxima Extraction in Spherical Harmonic Representation via Analytical Search Space Reduction

PubMed Central

Aganj, Iman; Lenglet, Christophe; Sapiro, Guillermo

2015-01-01

By revealing complex fiber structure through the orientation distribution function (ODF), q-ball imaging has recently become a popular reconstruction technique in diffusion-weighted MRI. In this paper, we propose an analytical dimension reduction approach to ODF maxima extraction. We show that by expressing the ODF, or any antipodally symmetric spherical function, in the common fourth order real and symmetric spherical harmonic basis, the maxima of the two-dimensional ODF lie on an analytically derived one-dimensional space, from which we can detect the ODF maxima. This method reduces the computational complexity of the maxima detection, without compromising the accuracy. We demonstrate the performance of our technique on both artificial and human brain data. PMID:20879302

Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals

DOE PAGES

Rai, Prashant; Sargsyan, Khachik; Najm, Habib N.

2018-03-20

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function asmore » a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.« less

Surrogate modelling for the prediction of spatial fields based on simultaneous dimensionality reduction of high-dimensional input/output spaces.

PubMed

Crevillén-García, D

2018-04-01

Time-consuming numerical simulators for solving groundwater flow and dissolution models of physico-chemical processes in deep aquifers normally require some of the model inputs to be defined in high-dimensional spaces in order to return realistic results. Sometimes, the outputs of interest are spatial fields leading to high-dimensional output spaces. Although Gaussian process emulation has been satisfactorily used for computing faithful and inexpensive approximations of complex simulators, these have been mostly applied to problems defined in low-dimensional input spaces. In this paper, we propose a method for simultaneously reducing the dimensionality of very high-dimensional input and output spaces in Gaussian process emulators for stochastic partial differential equation models while retaining the qualitative features of the original models. This allows us to build a surrogate model for the prediction of spatial fields in such time-consuming simulators. We apply the methodology to a model of convection and dissolution processes occurring during carbon capture and storage.

Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals

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

Rai, Prashant; Sargsyan, Khachik; Najm, Habib N.

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function asmore » a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.« less

Simulation of Fluid Flow and Collection Efficiency for an SEA Multi-element Probe

NASA Technical Reports Server (NTRS)

Rigby, David L.; Struk, Peter M.; Bidwell, Colin

2014-01-01

Numerical simulations of fluid flow and collection efficiency for a Science Engineering Associates (SEA) multi-element probe are presented. Simulation of the flow field was produced using the Glenn-HT Navier-Stokes solver. Three-dimensional unsteady results were produced and then time averaged for the heat transfer and collection efficiency results. Three grid densities were investigated to enable an assessment of grid dependence. Simulations were completed for free stream velocities ranging from 85-135 meters per second, and free stream total pressure of 44.8 and 93.1 kilopascals (6.5 and 13.5 pounds per square inch absolute). In addition, the effect of angle of attack and yaw were investigated by including 5 degree deviations from straight for one of the flow conditions. All but one of the cases simulated a probe in isolation (i.e. in a very large domain without any support strut). One case is included which represents a probe mounted on a support strut within a finite sized wind tunnel. Collection efficiencies were generated, using the LEWICE3D code, for four spherical particle sizes, 100, 50, 20, and 5 micron in diameter. It was observed that a reduction in velocity of about 20% occurred, for all cases, as the flow entered the shroud of the probe. The reduction in velocity within the shroud is not indicative of any error in the probe measurement accuracy. Heat transfer results are presented which agree quite well with a correlation for the circular cross section heated elements. Collection efficiency results indicate a reduction in collection efficiency as particle size is reduced. The reduction with particle size is expected, however, the results tended to be lower than the previous results generated for isolated two-dimensional elements. The deviation from the two-dimensional results is more pronounced for the smaller particles and is likely due to the reduced flow within the protective shroud. As particle size increases differences between the two-dimensional and three dimensional results become negligible. Taken as a group, the total collection efficiency of the elements including the effects of the shroud has been shown to be in the range of 0.93 to 0.99 for particles above 20 microns. The 3D model has improved the estimated collection efficiency for smaller particles where errors in previous estimates were more significant.

Hawking radiation as tunneling from squashed Kaluza-Klein black hole

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

Matsuno, Ken; Umetsu, Koichiro

2011-03-15

We discuss Hawking radiation from a five-dimensional squashed Kaluza-Klein black hole on the basis of the tunneling mechanism. A simple method, which was recently suggested by Umetsu, may be used to extend the original derivation by Parikh and Wilczek to various black holes. That is, we use the two-dimensional effective metric, which is obtained by the dimensional reduction near the horizon, as the background metric. Using the same method, we derive both the desired result of the Hawking temperature and the effect of the backreaction associated with the radiation in the squashed Kaluza-Klein black hole background.

Dimensionality-Driven Metal-Insulator Transition in Spin-Orbit-Coupled SrIrO3

NASA Astrophysics Data System (ADS)

Schütz, P.; Di Sante, D.; Dudy, L.; Gabel, J.; Stübinger, M.; Kamp, M.; Huang, Y.; Capone, M.; Husanu, M.-A.; Strocov, V. N.; Sangiovanni, G.; Sing, M.; Claessen, R.

2017-12-01

Upon reduction of the film thickness we observe a metal-insulator transition in epitaxially stabilized, spin-orbit-coupled SrIrO3 ultrathin films. By comparison of the experimental electronic dispersions with density functional theory at various levels of complexity we identify the leading microscopic mechanisms, i.e., a dimensionality-induced readjustment of octahedral rotations, magnetism, and electronic correlations. The astonishing resemblance of the band structure in the two-dimensional limit to that of bulk Sr2 IrO4 opens new avenues to unconventional superconductivity by "clean" electron doping through electric field gating.

[Clinical characteristics and prognostic factors of pulmonary tuberculosis with concurrent lung cancer].

PubMed

Gu, Yingchun; Song, Yelin; Liu, Yufeng

2014-09-30

To explore the clinical characteristics and prognostic factors of pulmonary tuberculosis with concurrent lung cancer. Comprehensive analyses were conducted for 58 cases of pulmonary tuberculosis patients with lung cancer. Their clinical symptoms, signs and imaging results were analyzed between January 1998 and January 2005 at Qingdao Chest Hospital. Kaplan-Meier method was utilized to calculate their survival rates. Nine prognostic characteristics were analyzed. Single factor analysis was performed with Logrank test and multi-factor analysis with Cox regression model. The initial symptoms were cough, chest tightness, fever and hemoptysis. Chest radiology showed the coexistence of two diseases was 36 in the same lobe and 22 in different lobes. And there were pulmonary nodules (n = 24), cavities (n = 19), infiltration (n = 8) and atelectasis (n = 7). According to the pathological characteristics, there were squamous carcinoma (n = 33), adenocarcinoma (n = 17), small cell carcinoma (n = 4) and unidentified (n = 4) respectively. The TNM stages were I (n = 13), II(n = 22), III (n = 16) and IV (n = 7) respectively. The median survival period was 24 months. And the 1, 3, 5-year survival rates were 65.5%, 65.5% and 29.0% respectively. Single factor analysis showed that lung cancer TNM staging (P = 0.000) and tuberculosis activity (P = 0.024) were significantly associated with patient prognosis. And multi-factor analysis showed that lung cancer TNM staging (RR = 2.629, 95%CI: 1.759-3.928, P = 0.000) and tuberculosis activity (RR = 1.885, 95%CI: 1.023-3.471, P = 0.042) were relatively independent prognostic factors. The clinical and radiological characteristics contribute jointly to early diagnosis and therapy of tuberculosis with concurrent lung cancer. And TNM staging of lung cancer and activity of tuberculosis are major prognostic factors.

Risk factors associated with sporadic salmonellosis in adults: a case-control study.

PubMed

Ziehm, D; Dreesman, J; Campe, A; Kreienbrock, L; Pulz, M

2013-02-01

In order to identify and assess recent risk factors for sporadic human infections with Salmonella enterica, we conducted a case-control study in Lower Saxony, Germany. The data collection was based on standardized telephone interviews with 1017 cases and 346 controls aged >14 years. Odds ratios were calculated in single-factor and multi-factor analyses for Salmonella cases and two different control groups, i.e. population controls and controls with rotavirus infection. Multi-factor analysis revealed associations between sporadic Salmonella infections for two exposures by both sets of controls: consumption of raw ground pork [adjusted odds ratio (aOR) 2·38, 95% confidence interval (CI) 1·27-4·44] and foreign travel (aOR 2·12, 95% CI 1·00-4·52). Other exposures included consumption of food items containing eggs (aOR 1·43, 95% CI 0·80-2·54), consumption of chicken meat (aOR 1·77, 95% CI 1·26-2·50), outdoor meals/barbecues (aOR 3·96, 95% CI 1·41-11·12) and taking gastric acidity inhibitors (aOR 2·42, 95% CI 1·19-4·92), all were significantly associated with respect to one of the two control groups. The impact of consuming food items containing eggs or chicken meat was lower than expected from the literature. This might be a consequence of Salmonella control programmes as well as increased public awareness of eggs and chicken products being a risk factor for salmonellosis. Efforts to reduce Salmonella infections due to raw pork products should be intensified.

The Multifactor Measure of Performance: Its Development, Norming, and Validation.

PubMed

Bar-On, Reuven

2018-01-01

This article describes the development as well as the initial norming and validation of the Multifactor Measure of Performance™ (MMP™), which is a psychometric instrument that is designed to study, assess and enhance key predictors of human performance to help individuals perform at a higher level. It was created by the author, for the purpose of going beyond existing conceptual and psychometric models that often focus on relatively few factors that are purported to assess performance at school, in the workplace and elsewhere. The relative sparsity of multifactorial pre-employment assessment instruments exemplifies, for the author, one of the important reasons for developing the MMP™, which attempts to comprehensively evaluate a wider array of factors that are thought to contribute to performance. In that this situation creates a need in the area of test-construction that should be addressed, the author sought to develop a multifactorial assessment and development instrument that could concomitantly evaluate a combination of physical, cognitive, intra-personal, inter-personal, and motivational factors that significantly contribute to performance. The specific aim of this article is to show why, how and if this could be done as well as to present and discuss the potential importance of the results obtained to date. The findings presented here will hopefully add to what is known about human performance and thus contribute to the professional literature, in addition to contribute to the continued development of the MMP™. The impetus for developing the MMP™ is first explained below, followed by a detailed description of the process involved and the findings obtained; and their potential application is then discussed as well as the possible limitations of the present research and the need for future studies to address them.