Spectral analysis by correlation

International Nuclear Information System (INIS)

Fauque, J.M.; Berthier, D.; Max, J.; Bonnet, G.

1969-01-01

The spectral density of a signal, which represents its power distribution along the frequency axis, is a function which is of great importance, finding many uses in all fields concerned with the processing of the signal (process identification, vibrational analysis, etc...). Amongst all the possible methods for calculating this function, the correlation method (correlation function calculation + Fourier transformation) is the most promising, mainly because of its simplicity and of the results it yields. The study carried out here will lead to the construction of an apparatus which, coupled with a correlator, will constitute a set of equipment for spectral analysis in real time covering the frequency range 0 to 5 MHz. (author) [fr

Two-dimensional multifractal cross-correlation analysis

International Nuclear Information System (INIS)

Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong

2017-01-01

Highlights: • We study the mathematical models of 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Present the definition of the two-dimensional N 2 -partitioned multiplicative cascading process. • Do the comparative analysis of 2D-MC by 2D-MFXPF, 2D-MFXDFA and 2D-MFXDMA. • Provide a reference on the choice and parameter settings of these methods in practice. - Abstract: There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross-correlations. This paper presents two-dimensional multifractal cross-correlation analysis based on the partition function (2D-MFXPF), two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) and two-dimensional multifractal cross-correlation analysis based on the detrended moving average analysis (2D-MFXDMA). We apply these methods to pairs of two-dimensional multiplicative cascades (2D-MC) to do a comparative study. Then, we apply the two-dimensional multifractal cross-correlation analysis based on the detrended fluctuation analysis (2D-MFXDFA) to real images and unveil intriguing multifractality in the cross correlations of the material structures. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms in the potential applications in the field of SAR image classification and detection.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

Science.gov (United States)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

Science.gov (United States)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Uncovering Black Womanhood in Engineering

Science.gov (United States)

Gibson, Sheree L.; Espino, Michelle M.

2016-01-01

Despite the growing research that outlines the experiences of Blacks and women undergraduates in engineering, little is known about Black women in this field. The purpose of this qualitative study was to uncover how eight Black undergraduate women in engineering understood their race and gender identities in a culture that can be oppressive to…

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

Science.gov (United States)

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A new methodology of spatial cross-correlation analysis.

Science.gov (United States)

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

A New Methodology of Spatial Cross-Correlation Analysis

Science.gov (United States)

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

Generalized canonical correlation analysis with missing values

NARCIS (Netherlands)

M. van de Velden (Michel); Y. Takane

2012-01-01

textabstractGeneralized canonical correlation analysis is a versatile technique that allows the joint analysis of several sets of data matrices. The generalized canonical correlation analysis solution can be obtained through an eigenequation and distributional assumptions are not required. When

Comparison between uncovered and covered self-expandable metal stent placement in malignant duodenal obstruction.

Science.gov (United States)

Kim, Ji Won; Jeong, Ji Bong; Lee, Kook Lae; Kim, Byeong Gwan; Ahn, Dong Won; Lee, Jae Kyung; Kim, Su Hwan

2015-02-07

To compare the clinical outcomes of uncovered and covered self-expandable metal stent placements in patients with malignant duodenal obstruction. A total of 67 patients were retrospectively enrolled from January 2003 to June 2013. All patients had symptomatic obstruction characterized by nausea, vomiting, reduced oral intake, and weight loss. The exclusion criteria included asymptomatic duodenal obstruction, perforation or peritonitis, concomitant small bowel obstruction, or duodenal obstruction caused by benign strictures. The technical and clinical success rate, complication rate, and stent patency were compared according to the placement of uncovered (n = 38) or covered (n = 29) stents. The technical and clinical success rates did not differ between the uncovered and covered stent groups (100% vs 96.6% and 89.5% vs 82.8%). There were no differences in the overall complication rates between the uncovered and covered stent groups (31.6% vs 41.4%). However, stent migration occurred more frequently with covered than uncovered stents [20.7% (6/29) vs 0% (0/38), P stent patency was longer in uncovered than in covered stents [251 d (95%CI: 149.8 d-352.2 d) vs 139 d (95%CI: 45.5 d-232.5 d), P stent (70 d) and covered stent groups (60 d). Uncovered stents may be preferable in malignant duodenal obstruction because of their greater resistance to stent migration and longer stent patency than covered stents.

Intermittency analysis of correlated data

International Nuclear Information System (INIS)

Wosiek, B.

1992-01-01

We describe the method of the analysis of the dependence of the factorial moments on the bin size in which the correlations between the moments computed for different bin sizes are taken into account. For large multiplicity nucleus-nucleus data inclusion of the correlations does not change the values of the slope parameter, but gives errors significantly reduced as compared to the case of fits with no correlations. (author)

Feminist Approaches to Triangulation: Uncovering Subjugated Knowledge and Fostering Social Change in Mixed Methods Research

Science.gov (United States)

Hesse-Biber, Sharlene

2012-01-01

This article explores the deployment of triangulation in the service of uncovering subjugated knowledge and promoting social change for women and other oppressed groups. Feminist approaches to mixed methods praxis create a tight link between the research problem and the research design. An analysis of selected case studies of feminist praxis…

Meta-analysis of cancer transcriptomes: A new approach to uncover molecular pathological events in different cancer tissues

Directory of Open Access Journals (Sweden)

Sundus Iqbal

2014-03-01

Full Text Available To explore secrets of metastatic cancers, individual expression of true sets of respective genes must spread across the tissue. In this study, meta-analysis for transcriptional profiles of oncogenes was carried out to hunt critical genes or networks helping in metastasizing cancers. For this, transcriptomic analysis of different cancerous tissues causing leukemia, lung, liver, spleen, colorectal, colon, breast, bladder, and kidney cancers was performed by extracting microarray expression data from online resource; Gene Expression Omnibus. A newly developed bioinformatics technique; Dynamic Impact Approach (DIA was applied for enrichment analysis of transcriptional profiles using Database for Annotation Visualization and Integrated Discovery (DAVID. Furthermore, oPOSSUM (v. 2.0 and Cytoscape (v. 2.8.2 were used for in-depth analysis of transcription factors and regulatory gene networks respectively. DAVID analysis uncovered the most significantly enriched pathways in molecular functions that were 'Ubiquitin thiolesterase activity' up regulated in blood, breast, bladder, colorectal, lung, spleen, prostrate cancer. 'Transforming growth factor beta receptor activity' was inhibited in all cancers except leukemia, colon and liver cancer. oPOSSUM further revealed highly over-represented Transcription Factors (TFs; Broad-complex_3, Broad-complex_4, and Foxd3 except for leukemia and bladder cancer. From these findings, it is possible to target genes and networks, play a crucial role in the development of cancer. In the future, these transcription factors can serve as potential candidates for the therapeutic drug targets which can impede the deadly spread.

Seeing the forest through the trees: uncovering phenomic complexity through interactive network visualization.

Science.gov (United States)

Warner, Jeremy L; Denny, Joshua C; Kreda, David A; Alterovitz, Gil

2015-03-01

Our aim was to uncover unrecognized phenomic relationships using force-based network visualization methods, based on observed electronic medical record data. A primary phenotype was defined from actual patient profiles in the Multiparameter Intelligent Monitoring in Intensive Care II database. Network visualizations depicting primary relationships were compared to those incorporating secondary adjacencies. Interactivity was enabled through a phenotype visualization software concept: the Phenomics Advisor. Subendocardial infarction with cardiac arrest was demonstrated as a sample phenotype; there were 332 primarily adjacent diagnoses, with 5423 relationships. Primary network visualization suggested a treatment-related complication phenotype and several rare diagnoses; re-clustering by secondary relationships revealed an emergent cluster of smokers with the metabolic syndrome. Network visualization reveals phenotypic patterns that may have remained occult in pairwise correlation analysis. Visualization of complex data, potentially offered as point-of-care tools on mobile devices, may allow clinicians and researchers to quickly generate hypotheses and gain deeper understanding of patient subpopulations. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An integrated approach to uncover quality marker underlying the effects of Alisma orientale on lipid metabolism, using chemical analysis and network pharmacology.

Science.gov (United States)

Liao, Maoliang; Shang, Haihua; Li, Yazhuo; Li, Tian; Wang, Miao; Zheng, Yanan; Hou, Wenbin; Liu, Changxiao

2018-06-01

Quality control of traditional Chinese medicines is currently a great concern, due to the correlation between the quality control indicators and clinic effect is often questionable. According to the "multi-components and multi-targets" property of TCMs, a new special quality and bioactivity evaluation system is urgently needed. Present study adopted an integrated approach to provide new insights relating to uncover quality marker underlying the effects of Alisma orientale (AO) on lipid metabolism. In this paper, guided by the concept of the quality marker (Q-marker), an integrated strategies "effect-compound-target-fingerprint" was established to discovery and screen the potential quality marker of AO based on network pharmacology and chemical analysis. Firstly, a bioactivity evaluation was performed to screen the main active fractions. Then the chemical compositions were rapidly identified by chemical analysis. Next, networks were constructed to illuminate the interactions between these component and their targets for lipid metabolism, and the potential Q-marker of AO was initially screened. Finally, the activity of the Q-markers was validated in vitro. 50% ethanol extract fraction was found to have the strongest lipid-lowering activity. Then, the network pharmacology was used to clarify the unique relationship between the Q-markers and their integral pharmacological action. Combined with the results obtained, five active ingredients in the 50% ethanol extract fraction were given special considerations to be representative Q-markers: Alisol A, Alisol B, Alisol A 23-acetate, Alisol B 23-acetate and Alisol A 24-acetate, respectively. The chromatographic fingerprints based Q-marker was establishment. The integrated Q-marker screen may offer an alternative quality assessment of herbal medicines. Copyright © 2018. Published by Elsevier GmbH.

77 FR 12227 - Long Term 2 Enhanced Surface Water Treatment Rule: Uncovered Finished Water Reservoirs; Public...

Science.gov (United States)

2012-02-29

... Water Treatment Rule: Uncovered Finished Water Reservoirs; Public Meeting AGENCY: Environmental... review of the uncovered finished water reservoir requirement in the Long Term 2 Enhanced Surface Water... uncovered finished water reservoir requirement and the agency's Six Year Review process. EPA also plans to...

A hybrid correlation analysis with application to imaging genetics

Science.gov (United States)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

Use of (Time-Domain) Vector Autoregressions to Test Uncovered Interest Parity

OpenAIRE

Takatoshi Ito

1984-01-01

In this paper, a vector autoregression model (VAR) is proposed in order to test uncovered interest parity (UIP) in the foreign exchange market. Consider a VAR system of the spot exchange rate (yen/dollar), the domestic (US) interest rate and the foreign (Japanese) interest rate, describing the interdependence of the domestic and international financia lmarkets. Uncovered interest parity is stated as a null hypothesis that the current difference between the two interest rates is equal to the d...

Comparison of Covered Versus Uncovered Stents for Benign Superior Vena Cava (SVC) Obstruction.

Science.gov (United States)

Haddad, Mustafa M; Simmons, Benjamin; McPhail, Ian R; Kalra, Manju; Neisen, Melissa J; Johnson, Matthew P; Stockland, Andrew H; Andrews, James C; Misra, Sanjay; Bjarnason, Haraldur

2018-05-01

To identify whether long-term symptom relief and stent patency vary with the use of covered versus uncovered stents for the treatment of benign SVC obstruction. We retrospectively identified all patients with benign SVC syndrome treated to stent placement between January 2003 and December 2015 (n = 59). Only cases with both clinical and imaging follow-up were included (n = 47). In 33 (70%) of the patients, the obstruction was due to a central line or pacemaker wires, and in 14 (30%), the cause was fibrosing mediastinitis. Covered stents were placed in 17 (36%) of the patients, and 30 (64%) patients had an uncovered stent. Clinical and treatment outcomes, complications, and the percent stenosis of each stent were evaluated. Technical success was achieved in all cases at first attempt. Average clinical and imaging follow-up in years was 2.7 (range 0.1-11.1) (covered) and 1.7 (range 0.2-10.5) (uncovered), respectively. There was a significant difference (p = 0.044) in the number of patients who reported a return of symptoms between the covered (5/17 or 29.4%) and uncovered (18/30 or 60%) groups. There was also a significant difference (p = stenosis after stent placement between the covered [17.9% (range 0-100) ± 26.2] and uncovered [48.3% (range 6.8-100) ± 33.5] groups. No significant difference (p = 0.227) was found in the time (days) between the date of the procedure and the date of clinical follow-up where a return of symptoms was reported [covered: 426.6 (range 28-1554) ± 633.9 and uncovered 778.1 (range 23-3851) ± 1066.8]. One patient in the uncovered group had non-endovascular surgical intervention (innominate to right atrial bypass), while none in the covered group required surgical intervention. One major complication (SIR grade C) occurred that consisted of a pericardial hemorrhagic effusion after angioplasty that required covered stent placement. There were no procedure-related deaths. Both covered and uncovered stents can be used for

Using brain stimulation to disentangle neural correlates of conscious vision

NARCIS (Netherlands)

de Graaf, T.A.; Sack, A.T.

2014-01-01

Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But

The uncovered parity properties of the Czech Koruna

Czech Academy of Sciences Publication Activity Database

Derviz, Alexis

2002-01-01

Roč. 11, č. 1 (2002), s. 17-37 ISSN 1210-0455 R&D Projects: GA AV ČR KSK1019101 Institutional research plan: CEZ:AV0Z1075907 Keywords : uncovered parity * asset prices * international consumption-based capital asset pricing model Subject RIV: AH - Economics

Uncovering transcriptional interactions via an adaptive fuzzy logic approach

Directory of Open Access Journals (Sweden)

Chen Chung-Ming

2009-12-01

Full Text Available Abstract Background To date, only a limited number of transcriptional regulatory interactions have been uncovered. In a pilot study integrating sequence data with microarray data, a position weight matrix (PWM performed poorly in inferring transcriptional interactions (TIs, which represent physical interactions between transcription factors (TF and upstream sequences of target genes. Inferring a TI means that the promoter sequence of a target is inferred to match the consensus sequence motifs of a potential TF, and their interaction type such as AT or RT is also predicted. Thus, a robust PWM (rPWM was developed to search for consensus sequence motifs. In addition to rPWM, one feature extracted from ChIP-chip data was incorporated to identify potential TIs under specific conditions. An interaction type classifier was assembled to predict activation/repression of potential TIs using microarray data. This approach, combining an adaptive (learning fuzzy inference system and an interaction type classifier to predict transcriptional regulatory networks, was named AdaFuzzy. Results AdaFuzzy was applied to predict TIs using real genomics data from Saccharomyces cerevisiae. Following one of the latest advances in predicting TIs, constrained probabilistic sparse matrix factorization (cPSMF, and using 19 transcription factors (TFs, we compared AdaFuzzy to four well-known approaches using over-representation analysis and gene set enrichment analysis. AdaFuzzy outperformed these four algorithms. Furthermore, AdaFuzzy was shown to perform comparably to 'ChIP-experimental method' in inferring TIs identified by two sets of large scale ChIP-chip data, respectively. AdaFuzzy was also able to classify all predicted TIs into one or more of the four promoter architectures. The results coincided with known promoter architectures in yeast and provided insights into transcriptional regulatory mechanisms. Conclusion AdaFuzzy successfully integrates multiple types of

Consolidity: Mystery of inner property of systems uncovered

Directory of Open Access Journals (Sweden)

Hassen T. Dorrah

2012-10-01

Full Text Available This paper uncovers the mystery of consolidity, an inner property of systems that was amazingly hidden. Consolidity also reveals the secrecy of why strong stable and highly controllable systems are not invulnerable of falling and collapsing. Consolidity is measured by its Consolidity Index, defined as the ratio of overall changes of output parameters over combined changes of input and system parameters, all operating in fully fuzzy environment. Under this notion, systems are classified into consolidated, quasi-consolidated, neutrally consolidated, unconsolidated, quasi-unconsolidated and mixed types. The strategy for the implementation of consolidity is elaborated for both natural and man-made existing systems as well as the new developed ones. An important critique arises that the by-product consolidity of natural or built-as-usual system could lead to trapping such systems into a completely undesired unconsolidity. This suggests that the ample number of conventional techniques that do not take system consolidity into account should gradually be changed, and adjusted with improved consolidity-based techniques. Four Golden Rules are highlighted for handling system consolidity, and applied to several illustrative case studies. These case studies cover the consolidity analysis of the Drug Concentration problem, Predator-Prey Population problem, Spread of Infectious Disease problem, AIDS Epidemic problem and Arm Race model. It is demonstrated that consolidity changes are contrary (opposite in sign to changes of both stability and controllability. This is a very significant result showing that our present practice of stressing on building strong stable and highly controllable systems could have already jeopardized the consolidity behavior of an ample family of existing real life systems. It is strongly recommended that the four Golden Rules of consolidity should be enforced as future strict regulations of systems modeling, analysis, design and

Uncovering the Links between Prospective Teachers' Personal Responsibility, Academic Optimism, Hope, and Emotions about Teaching: A Mediation Analysis

Science.gov (United States)

Eren, Altay

2014-01-01

Prospective teachers' sense of personal responsibility has not been examined together with their academic optimism, hope, and emotions about teaching in a single study to date. However, to consider hope, academic optimism, and emotions about teaching together with personal responsibility is important to uncover the factors affecting…

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

Directory of Open Access Journals (Sweden)

Rupert Faltermeier

2015-01-01

Full Text Available Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP and intracranial pressure (ICP. Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP, with the outcome of the patients represented by the Glasgow Outcome Scale (GOS. For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

Science.gov (United States)

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Uncovering student ideas in physical science

CERN Document Server

Keeley, Page

2014-01-01

If you and your students can't get enough of a good thing, Volume 2 of Uncovering Student Ideas in Physical Science is just what you need. The book offers 39 new formative assessment probes, this time with a focus on electric charge, electric current, and magnets and electromagnetism. It can help you do everything from demystify electromagnetic fields to explain the real reason balloons stick to the wall after you rub them on your hair.

Partially Covered Metal Stents May Not Prolong Stent Patency Compared to Uncovered Stents in Unresectable Malignant Distal Biliary Obstruction

Science.gov (United States)

Kim, Jae Yun; Ko, Gyu Bong; Lee, Tae Hoon; Park, Sang-Heum; Lee, Yun Nah; Cho, Young Sin; Jung, Yunho; Chung, Il-Kwun; Choi, Hyun Jong; Cha, Sang-Woo; Moon, Jong Ho; Cho, Young Deok; Kim, Sun-Joo

2017-01-01

Background/Aims Controversy still exists regarding the benefits of covered self-expandable metal stents (SEMSs) compared to uncovered SEMSs. We aimed to compare the patency and stent-related adverse events of partially covered SEMSs (PC-SEMSs) and uncovered SEMSs in unresectable malignant distal biliary obstruction. Methods A total of 134 patients who received a PC-SEMS or uncovered SEMS for palliation of unresectable malignant distal biliary obstruction were reviewed retrospectively. The main outcome measures were stent patency, stent-related adverse events, and overall survival. Results The median stent patency was 118 days (range, 3 to 802 days) with PC-SEMSs and 105 days (range, 2 to 485 days) with uncovered SEMSs (p=0.718). The overall endoscopic revision rate due to stent dysfunction was 36.6% (26/71) with PC-SEMSs and 36.5% (23/63) with uncovered SEMSs (p=0.589). Tumor ingrowth was more frequent with uncovered SEMSs (4.2% vs 19.1%, p=0.013), but migration was more frequent with PC-SEMSs (11.2% vs 1.5%, p=0.04). The incidence of stent-related adverse events was 2.8% (2/71) with PC-SEMSs and 9.5% (6/63) with uncovered SEMSs (p=0.224). The median overall survival was 166 days with PC-SEMSs and 168 days with uncovered SEMSs (p=0.189). Conclusions Compared to uncovered SEMSs, PC-SEMSs did not prolong stent patency in unresectable malignant distal biliary obstruction. Stent migration was more frequent with PC-SEMSs. However, tumor ingrowth was less frequent with PC-SEMSs compared to uncovered SEMSs. PMID:28208003

DOES UNCOVERED INTEREST RATE PARITY HOLD IN TURKEY?

Directory of Open Access Journals (Sweden)

Ozcan Karahan

2012-01-01

Full Text Available Most of the earlier empirical studies focusing on developed countries failed to give evidence in favor of the Uncovered Interest Rate Parity (UIP. After intensive financial liberalization processes and mostly preferred free exchange rate regimes, a new area of research starts to involve the investigation whether UIP holds for developing economies differently. Accordingly, we tested the UIP for Turkey’s monthly interest rate and exchange rate data between 2002 and 2011. We run conventional regressions in the form of Ordinary Least Squares (OLS and used a simple Generalized Autoregressive Conditional Heteroskedasticity (GARCH analysis. The empirical results of both methods do not support the validity of UIP for Turkey. Thus, together with most of the earlier empirical studies focusing on developed countries and detecting the invalidity of UIP, we can argue that the experience of Turkey and developed economies are not different.

Multicollinearity in canonical correlation analysis in maize.

Science.gov (United States)

Alves, B M; Cargnelutti Filho, A; Burin, C

2017-03-30

The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

Uncovering missing links with cold ends

Science.gov (United States)

Zhu, Yu-Xiao; Lü, Linyuan; Zhang, Qian-Ming; Zhou, Tao

2012-11-01

To evaluate the performance of prediction of missing links, the known data are randomly divided into two parts, the training set and the probe set. We argue that this straightforward and standard method may lead to terrible bias, since in real biological and information networks, missing links are more likely to be links connecting low-degree nodes. We therefore study how to uncover missing links with low-degree nodes, namely links in the probe set are of lower degree products than a random sampling. Experimental analysis on ten local similarity indices and four disparate real networks reveals a surprising result that the Leicht-Holme-Newman index [E.A. Leicht, P. Holme, M.E.J. Newman, Vertex similarity in networks, Phys. Rev. E 73 (2006) 026120] performs the best, although it was known to be one of the worst indices if the probe set is a random sampling of all links. We further propose an parameter-dependent index, which considerably improves the prediction accuracy. Finally, we show the relevance of the proposed index to three real sampling methods: acquaintance sampling, random-walk sampling and path-based sampling.

Uncovering Indicators of Commercial Sexual Exploitation.

Science.gov (United States)

Bounds, Dawn; Delaney, Kathleen R; Julion, Wrenetha; Breitenstein, Susan

2017-07-01

It is estimated that annually 100,000 to 300,000 youth are at risk for sex trafficking; a commercial sex act induced by force, fraud, or coercion, or any such act where the person induced to perform such an act is younger than 18 years of age. Increasingly, such transactions are occurring online via Internet-based sites that serve the commercial sex industry. Commercial sex transactions involving trafficking are illegal; thus, Internet discussions between those involved must be veiled. Even so, transactions around sex trafficking do occur. Within these transactions are innuendos that provide one avenue for detecting potential activity. The purpose of this study is to identify linguistic indicators of potential commercial sexual exploitation within the online comments of men posted on an Internet site. Six hundred sixty-six posts from five Midwest cities and 363 unique members were analyzed via content analysis. Three main indicators were found: the presence of youth or desire for youthfulness, presence of pimps, and awareness of vulnerability. These findings begin a much-needed dialogue on uncovering online risks of commercial sexual exploitation and support the need for further research on Internet indicators of sex trafficking.

Multivariate weighted recurrence network inference for uncovering oil-water transitional flow behavior in a vertical pipe.

Science.gov (United States)

Gao, Zhong-Ke; Yang, Yu-Xuan; Cai, Qing; Zhang, Shan-Shan; Jin, Ning-De

2016-06-01

Exploring the dynamical behaviors of high water cut and low velocity oil-water flows remains a contemporary and challenging problem of significant importance. This challenge stimulates us to design a high-speed cycle motivation conductance sensor to capture spatial local flow information. We systematically carry out experiments and acquire the multi-channel measurements from different oil-water flow patterns. Then we develop a novel multivariate weighted recurrence network for uncovering the flow behaviors from multi-channel measurements. In particular, we exploit graph energy and weighted clustering coefficient in combination with multivariate time-frequency analysis to characterize the derived complex networks. The results indicate that the network measures are very sensitive to the flow transitions and allow uncovering local dynamical behaviors associated with water cut and flow velocity. These properties render our method particularly useful for quantitatively characterizing dynamical behaviors governing the transition and evolution of different oil-water flow patterns.

Detrended cross-correlation analysis of electroencephalogram

International Nuclear Information System (INIS)

Wang Jun; Zhao Da-Qing

2012-01-01

In the paper we use detrended cross-correlation analysis (DCCA) to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject's brain function is healthy or not. (interdisciplinary physics and related areas of science and technology)

Malignant Gastroduodenal Obstruction: Treatment with Self-Expanding Uncovered Wallstent

International Nuclear Information System (INIS)

Gutzeit, Andreas; Binkert, Christoph A.; Schoch, Eric; Sautter, Thomas; Jost, Res; Zollikofer, Christoph L.

2009-01-01

Purpose: To retrospectively evaluate the clinical effectiveness of a self-expanding uncovered Wallstent in patients with malignant gastroduodenal obstruction. Materials and Methods: Under combined endoscopic and fluoroscopic guidance, 29 patients with a malignant gastroduodenal stenosis were treated with a self-expanding uncovered metallic Wallstent. A dysphagia score was assessed before and after the intervention to measure the success of this palliative therapy. The dysphagia score ranged between grade 0 to grade 4: grade 0 = able to tolerate solid food, grade 1 = able to tolerate soft food, grade 2 = able to tolerate thick liquids, grade 3 = able to tolerate water or clear fluids, and grade 4 = unable to tolerate anything perorally. Stent patency and patients survival rates were calculated. Results: The insertion of the gastroduodenal stent was technically successful in 28 patients (96.5%). After stenting, 25 patients (86.2%) showed clinical improvement by at least one score point. During follow-up, 22 (78.5%) of 28 patients showed no stent occlusion until death and did not have to undergo any further intervention. In six patients (20.6%), all of whom were treated with secondary stent insertions, occlusion with tumor ingrowth and/or overgrowth was observed after the intervention. The median period of primary stent patency in our study was 240 days. Conclusion: Placement of an uncovered Wallstent is clinically effective in patients with malignant gastroduodenal obstruction. Stent placement is associated with high technical success, good palliation effect, and high durability of stent function.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Uncovering transcriptional regulation of metabolism by using metabolic network topology

DEFF Research Database (Denmark)

Patil, Kiran Raosaheb; Nielsen, Jens

2005-01-01

in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic......Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional...... therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns...

Bayesian Correlation Analysis for Sequence Count Data.

Directory of Open Access Journals (Sweden)

Daniel Sánchez-Taltavull

Full Text Available Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities' measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low-especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities' signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset.

WGCNA: an R package for weighted correlation network analysis.

Science.gov (United States)

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

Multifractal detrended cross-correlation analysis in the MENA area

Science.gov (United States)

El Alaoui, Marwane; Benbachir, Saâd

2013-12-01

In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.

Percutaneous Transhepatic Biliary Stenting with Uncovered Self-Expandable Metallic Stents in Patients with Malignant Biliary Obstruction - Efficacy and Survival Analysis.

Science.gov (United States)

Pranculis, Andrius; Kievišas, Mantas; Kievišienė, Lina; Vaičius, Artūras; Vanagas, Tomas; Kaupas, Rytis Stasys; Dambrauskas, Žilvinas

2017-01-01

The aim of this study was to assess short- and long-term outcomes of malignant biliary obstruction (MBO) treatment by percutaneous transhepatic biliary stenting (PTBS) with uncovered selfexpandable metallic stents (SEMS), and to identify predictors of survival. A nine-year, single-centre study from a prospectively collected database included 222 patients with inoperable MBO treated by PTBS with uncovered nitinol SEMS. Technical and clinical success rates were 95.9% and 82.4%, respectively. The total rate of postprocedural complications was 14.4%. The mean durations of the primary and secondary stent patency were 114.7±15.1 and 146.4±21.2 days, respectively. The 30-day mortality rate was 15.3% with no procedure-related deaths. The mean estimated length of survival was 143.3±20.6 days. Independent predictors increasing the risk of death included higher than 115 μmol/L serum bilirubin 2-5 days after biliary stenting (HR 3.274, P =0.019), distal (non-hilar) obstruction of the bile ducts (HR 3.711, P =0.008), Bismuth-Corlette type IV stricture (HR 2.082, P =0.008), obstruction due to gallbladder cancer (HR 31.029, P =0.012) and only partial drainage of liver parenchyma (HR 4.158, P =0.040). PTBS with uncovered SEMS is an effective and safe method for palliative treatment of MBO. Serum bilirubin higher than 115 μmol/L 2-5 days after the procedure has a significant negative impact on patients' survival. Lower survival is also determined by distal bile duct obstruction, Bismuth- Corlette type IV stricture, biliary obstruction caused by gallbladder cancer and when only partial liver drainage is applied.

Structural Analysis of Covariance and Correlation Matrices.

Science.gov (United States)

Joreskog, Karl G.

1978-01-01

A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…

Calculation of strained BaTiO3 with different exchange correlation functionals examined with criterion by Ginzburg-Landau theory, uncovering expressions by crystallographic parameters

Science.gov (United States)

Watanabe, Yukio

2018-05-01

In the calculations of tetragonal BaTiO3, some exchange-correlation (XC) energy functionals such as local density approximation (LDA) have shown good agreement with experiments at room temperature (RT), e.g., spontaneous polarization (PS), and superiority compared with other XC functionals. This is due to the error compensation of the RT effect and, hence, will be ineffective in the heavily strained case such as domain boundaries. Here, ferroelectrics under large strain at RT are approximated as those at 0 K because the strain effect surpasses the RT effects. To find effective XC energy functionals for strained BaTiO3, we propose a new comparison, i.e., a criterion. This criterion is the properties at 0 K given by the Ginzburg-Landau (GL) theory because GL theory is a thermodynamic description of experiments working under the same symmetry-constraints as ab initio calculations. With this criterion, we examine LDA, generalized gradient approximations (GGA), meta-GGA, meta-GGA + local correlation potential (U), and hybrid functionals, which reveals the high accuracy of some XC functionals superior to XC functionals that have been regarded as accurate. This result is examined directly by the calculations of homogenously strained tetragonal BaTiO3, confirming the validity of the new criterion. In addition, the data points of theoretical PS vs. certain crystallographic parameters calculated with different XC functionals are found to lie on a single curve, despite their wide variations. Regarding these theoretical data points as corresponding to the experimental results, analytical expressions of the local PS using crystallographic parameters are uncovered. These expressions show the primary origin of BaTiO3 ferroelectricity as oxygen displacements. Elastic compliance and electrostrictive coefficients are estimated. For the comparison of strained results, we show that the effective critical temperature TC under strain 1000 K from an approximate method combining ab initio

Correlation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing.

Science.gov (United States)

Delis, Ioannis; Dmochowski, Jacek P; Sajda, Paul; Wang, Qi

2018-03-23

Many real-world decisions rely on active sensing, a dynamic process for directing our sensors (e.g. eyes or fingers) across a stimulus to maximize information gain. Though ecologically pervasive, limited work has focused on identifying neural correlates of the active sensing process. In tactile perception, we often make decisions about an object/surface by actively exploring its shape/texture. Here we investigate the neural correlates of active tactile decision-making by simultaneously measuring electroencephalography (EEG) and finger kinematics while subjects interrogated a haptic surface to make perceptual judgments. Since sensorimotor behavior underlies decision formation in active sensing tasks, we hypothesized that the neural correlates of decision-related processes would be detectable by relating active sensing to neural activity. Novel brain-behavior correlation analysis revealed that three distinct EEG components, localizing to right-lateralized occipital cortex (LOC), middle frontal gyrus (MFG), and supplementary motor area (SMA), respectively, were coupled with active sensing as their activity significantly correlated with finger kinematics. To probe the functional role of these components, we fit their single-trial-couplings to decision-making performance using a hierarchical-drift-diffusion-model (HDDM), revealing that the LOC modulated the encoding of the tactile stimulus whereas the MFG predicted the rate of information integration towards a choice. Interestingly, the MFG disappeared from components uncovered from control subjects performing active sensing but not required to make perceptual decisions. By uncovering the neural correlates of distinct stimulus encoding and evidence accumulation processes, this study delineated, for the first time, the functional role of cortical areas in active tactile decision-making. Copyright © 2018 Elsevier Inc. All rights reserved.

Gait Correlation Analysis Based Human Identification

Directory of Open Access Journals (Sweden)

Jinyan Chen

2014-01-01

Full Text Available Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x, vertical axis (y, and temporal axis (t. By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features’ dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance.

The Relation of Racial Identity, Ethnic Identity, and Racial Socialization to Discrimination-Distress: A Meta-Analysis of Black Americans

Science.gov (United States)

Lee, Debbiesiu L.; Ahn, Soyeon

2013-01-01

This meta-analysis synthesized the results of 27 studies examining the relations of racial identity, ethnic identity, and racial socialization to discrimination-distress for Black Americans. The purpose was to uncover which constructs connected to racial identity, ethnic identity, and racial socialization most strongly correlate with racial…

Meta-Analysis of Correlations Among Usability Measures

DEFF Research Database (Denmark)

Hornbæk, Kasper Anders Søren; Effie Lai Chong, Law

2007-01-01

are generally low: effectiveness measures (e.g., errors) and efficiency measures (e.g., time) has a correlation of .247 ± .059 (Pearson's product-moment correlation with 95% confidence interval), efficiency and satisfaction (e.g., preference) one of .196 ± .064, and effectiveness and satisfaction one of .164......Understanding the relation between usability measures seems crucial to deepen our conception of usability and to select the right measures for usability studies. We present a meta-analysis of correlations among usability measures calculated from the raw data of 73 studies. Correlations...... ± .062. Changes in task complexity do not influence these correlations, but use of more complex measures attenuates them. Standard questionnaires for measuring satisfaction appear more reliable than homegrown ones. Measures of users' perceptions of phenomena are generally not correlated with objective...

Uncovering the Density of Matter from Multiplicity Distribution

International Nuclear Information System (INIS)

Bialas, A.

2010-01-01

Multiplicity distributions in the form of superposition of Poisson distributions which are observed in multiparticle production are interpreted as reflection of a two-step nature of this process: the creation and evolution of the strongly interacting fluid, followed by its uncorrelated decay into observed hadrons. A method to uncover the density of the fluid from the observed multiplicity distribution is described. (author)

Correlation analysis in chemistry: recent advances

National Research Council Canada - National Science Library

Shorter, John; Chapman, Norman Bellamy

1978-01-01

..., and applications of LFER to polycyclic arenes, heterocyclic compounds, and olefinic systems. Of particular interest is the extensive critical compilation of substituent constants and the numerous applications of correlation analysis to spectroscopy...

Multi-frequency complex network from time series for uncovering oil-water flow structure.

Science.gov (United States)

Gao, Zhong-Ke; Yang, Yu-Xuan; Fang, Peng-Cheng; Jin, Ning-De; Xia, Cheng-Yi; Hu, Li-Dan

2015-02-04

Uncovering complex oil-water flow structure represents a challenge in diverse scientific disciplines. This challenge stimulates us to develop a new distributed conductance sensor for measuring local flow signals at different positions and then propose a novel approach based on multi-frequency complex network to uncover the flow structures from experimental multivariate measurements. In particular, based on the Fast Fourier transform, we demonstrate how to derive multi-frequency complex network from multivariate time series. We construct complex networks at different frequencies and then detect community structures. Our results indicate that the community structures faithfully represent the structural features of oil-water flow patterns. Furthermore, we investigate the network statistic at different frequencies for each derived network and find that the frequency clustering coefficient enables to uncover the evolution of flow patterns and yield deep insights into the formation of flow structures. Current results present a first step towards a network visualization of complex flow patterns from a community structure perspective.

Generalized canonical correlation analysis with missing values

NARCIS (Netherlands)

M. van de Velden (Michel); Y. Takane

2009-01-01

textabstractTwo new methods for dealing with missing values in generalized canonical correlation analysis are introduced. The first approach, which does not require iterations, is a generalization of the Test Equating method available for principal component analysis. In the second approach,

Comparative analysis of the Photorhabdus luminescens and the Yersinia enterocolitica genomes: uncovering candidate genes involved in insect pathogenicity

Directory of Open Access Journals (Sweden)

Fuchs Thilo M

2008-01-01

Full Text Available Abstract Background Photorhabdus luminescens and Yersinia enterocolitica are both enteric bacteria which are associated with insects. P. luminescens lives in symbiosis with soil nematodes and is highly pathogenic towards insects but not to humans. In contrast, Y. enterocolitica is widely found in the environment and mainly known to cause gastroenteritis in men, but has only recently been shown to be also toxic for insects. It is expected that both pathogens share an overlap of genetic determinants that play a role within the insect host. Results A selective genome comparison was applied. Proteins belonging to the class of two-component regulatory systems, quorum sensing, universal stress proteins, and c-di-GMP signalling have been analysed. The interorganismic synopsis of selected regulatory systems uncovered common and distinct signalling mechanisms of both pathogens used for perception of signals within the insect host. Particularly, a new class of LuxR-like regulators was identified, which might be involved in detecting insect-specific molecules. In addition, the genetic overlap unravelled a two-component system that is unique for the genera Photorhabdus and Yersinia and is therefore suggested to play a major role in the pathogen-insect relationship. Our analysis also highlights factors of both pathogens that are expressed at low temperatures as encountered in insects in contrast to higher (body temperature, providing evidence that temperature is a yet under-investigated environmental signal for bacterial adaptation to various hosts. Common degradative metabolic pathways are described that might be used to explore nutrients within the insect gut or hemolymph, thus enabling the proliferation of P. luminescens and Y. enterocolitica in their invertebrate hosts. A strikingly higher number of genes encoding insecticidal toxins and other virulence factors in P. luminescens compared to Y. enterocolitica correlates with the higher virulence of P

Correlation analysis of respiratory signals by using parallel coordinate plots.

Science.gov (United States)

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Cross-correlation time-of-flight analysis of molecular beam scattering

International Nuclear Information System (INIS)

Nowikow, C.V.; Grice, R.

1979-01-01

The theory of the cross-correlation method of time-of-flight analysis is presented in a form which highlights its formal similarity to the conventional method. A time-of-flight system for the analysis of crossed molecular beam scattering is described, which is based on a minicomputer interface and can operate in both the cross-correlation and conventional modes. The interface maintains the synchronisation of chopper disc rotation and channel advance indefinitely in the cross-correlation method and can acquire data in phase with the beam modulation in both methods. The shutter function of the cross-correlation method is determined and the deconvolution analysis of the data is discussed. (author)

Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

Science.gov (United States)

Yin, Yi; Shang, Pengjian

2014-06-01

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and

Percutaneous Transhepatic Biliary Stenting with Uncovered Self-Expandable Metallic Stents in Patients with Malignant Biliary Obstruction – Efficacy and Survival Analysis

Science.gov (United States)

Pranculis, Andrius; Kievišienė, Lina; Vaičius, Artūras; Vanagas, Tomas; Kaupas, Rytis Stasys; Dambrauskas, Žilvinas

2017-01-01

Summary Background The aim of this study was to assess short- and long-term outcomes of malignant biliary obstruction (MBO) treatment by percutaneous transhepatic biliary stenting (PTBS) with uncovered selfexpandable metallic stents (SEMS), and to identify predictors of survival. Material/Methods A nine-year, single-centre study from a prospectively collected database included 222 patients with inoperable MBO treated by PTBS with uncovered nitinol SEMS. Results Technical and clinical success rates were 95.9% and 82.4%, respectively. The total rate of postprocedural complications was 14.4%. The mean durations of the primary and secondary stent patency were 114.7±15.1 and 146.4±21.2 days, respectively. The 30-day mortality rate was 15.3% with no procedure-related deaths. The mean estimated length of survival was 143.3±20.6 days. Independent predictors increasing the risk of death included higher than 115 μmol/L serum bilirubin 2–5 days after biliary stenting (HR 3.274, P=0.019), distal (non-hilar) obstruction of the bile ducts (HR 3.711, P=0.008), Bismuth-Corlette type IV stricture (HR 2.082, P=0.008), obstruction due to gallbladder cancer (HR 31.029, P=0.012) and only partial drainage of liver parenchyma (HR 4.158, P=0.040). Conclusions PTBS with uncovered SEMS is an effective and safe method for palliative treatment of MBO. Serum bilirubin higher than 115 μmol/L 2–5 days after the procedure has a significant negative impact on patients’ survival. Lower survival is also determined by distal bile duct obstruction, Bismuth– Corlette type IV stricture, biliary obstruction caused by gallbladder cancer and when only partial liver drainage is applied. PMID:29662569

International Space Station Model Correlation Analysis

Science.gov (United States)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

The Uncovered Interest Parity in the Foreign Exchange (FX Markets

Directory of Open Access Journals (Sweden)

Silvio Ricardo Micheloto

2004-12-01

Full Text Available This work verifies the uncovered interest rates parity (UIP in the FX (foreign exchange emerging markets by using the panel cointegration technique. The data involves several developing countries that compose the EMBI+ Global Index. We compare the results of several panel estimators: OLS (ordinary list square, DOLS (dynamic OLS and FMOLS (fully modified OLS. This new panel technique can handle problems of either non-stationary series (spurious regression or small problem. This latter problem has being considered one of the main causes for distorting the UIP empirical results. By using this approach, we check the UIP in the FX (foreign exchange emerging markets. These markets are more critical because they have been subjected to changing FX regimes and speculative attacks. Our results do not corroborate the uncovered interest parity for the developing countries in the recent years. Thus, the forward premium puzzle may hold in the FX emergent markets.

Comparison of covered and uncovered self-expandable stents in the treatment of malignant biliary obstruction.

Science.gov (United States)

Flores Carmona, Diana Yamel; Alonso Lárraga, Juan Octavio; Hernández Guerrero, Angélica; Ramírez Solís, Mauro Eduardo

2016-05-01

Drainage with metallic stents is the treatment of choice in malignant obstructive jaundice. Technical and clinical success with metallic stents is obtained in over 90% and 80% of cases, respectively. There are self-expandable metallic stents designed to increase permeability. The aim of this study was to describe the results obtained with totally covered self-expandable and uncovered self-expandable metallic stents in the palliative treatment of malignant biliary obstruction. Sixty eight patients with malignant obstructive jaundice secondary to pancreatobiliary or metastatic disease not amenable to surgery were retrospectively included. Two groups were created: group A (covered self-expandable metallic stents) (n = 22) and group B (uncovered self-expandable metallic stents) (n = 46). Serum total bilirubin, direct bilirubin, alkaline phosphatase and gamma glutamyl transferase levels decreased in both groups and no statistically significant difference was detected (p = 0.800, p = 0.190, p = 0.743, p = 0.521). Migration was greater with covered stents but it was not statistically significant either (p = 0.101). Obstruction was greater in the group with uncovered stents but it was not statistically significant either (p = 0.476). There are no differences when using covered self-expandable stents or uncovered self-expandable stents in terms of technical and clinical success or complications in the palliative treatment of malignant obstructive jaundice.

Principal Component Analysis Based Two-Dimensional (PCA-2D) Correlation Spectroscopy: PCA Denoising for 2D Correlation Spectroscopy

International Nuclear Information System (INIS)

Jung, Young Mee

2003-01-01

Principal component analysis based two-dimensional (PCA-2D) correlation analysis is applied to FTIR spectra of polystyrene/methyl ethyl ketone/toluene solution mixture during the solvent evaporation. Substantial amount of artificial noise were added to the experimental data to demonstrate the practical noise-suppressing benefit of PCA-2D technique. 2D correlation analysis of the reconstructed data matrix from PCA loading vectors and scores successfully extracted only the most important features of synchronicity and asynchronicity without interference from noise or insignificant minor components. 2D correlation spectra constructed with only one principal component yield strictly synchronous response with no discernible a asynchronous features, while those involving at least two or more principal components generated meaningful asynchronous 2D correlation spectra. Deliberate manipulation of the rank of the reconstructed data matrix, by choosing the appropriate number and type of PCs, yields potentially more refined 2D correlation spectra

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis

Directory of Open Access Journals (Sweden)

Jianhua Ni

2016-08-01

Full Text Available The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Graphology and personality: a correlational analysis

OpenAIRE

2008-01-01

M.A. The title of this dissertation reads as follows: Graphology and Personality: A Correlational Analysis. The aim of this dissertation is to introduce a different projective technique (as of yet not very widely used) into the psychological arena of assessment. Graphology is a projective technique that allows the analyst to delve into the personality of the individual. Very shortly, graphology can be defined as the assessment or analysis of a person’s handwriting. When a child first attem...

Analytic uncertainty and sensitivity analysis of models with input correlations

Science.gov (United States)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Organization of physical interactomes as uncovered by network schemas.

Science.gov (United States)

Banks, Eric; Nabieva, Elena; Chazelle, Bernard; Singh, Mona

2008-10-01

Large-scale protein-protein interaction networks provide new opportunities for understanding cellular organization and functioning. We introduce network schemas to elucidate shared mechanisms within interactomes. Network schemas specify descriptions of proteins and the topology of interactions among them. We develop algorithms for systematically uncovering recurring, over-represented schemas in physical interaction networks. We apply our methods to the S. cerevisiae interactome, focusing on schemas consisting of proteins described via sequence motifs and molecular function annotations and interacting with one another in one of four basic network topologies. We identify hundreds of recurring and over-represented network schemas of various complexity, and demonstrate via graph-theoretic representations how more complex schemas are organized in terms of their lower-order constituents. The uncovered schemas span a wide range of cellular activities, with many signaling and transport related higher-order schemas. We establish the functional importance of the schemas by showing that they correspond to functionally cohesive sets of proteins, are enriched in the frequency with which they have instances in the H. sapiens interactome, and are useful for predicting protein function. Our findings suggest that network schemas are a powerful paradigm for organizing, interrogating, and annotating cellular networks.

Multifractal temporally weighted detrended cross-correlation analysis to quantify power-law cross-correlation and its application to stock markets

Science.gov (United States)

Wei, Yun-Lan; Yu, Zu-Guo; Zou, Hai-Long; Anh, Vo

2017-06-01

A new method—multifractal temporally weighted detrended cross-correlation analysis (MF-TWXDFA)—is proposed to investigate multifractal cross-correlations in this paper. This new method is based on multifractal temporally weighted detrended fluctuation analysis and multifractal cross-correlation analysis (MFCCA). An innovation of the method is applying geographically weighted regression to estimate local trends in the nonstationary time series. We also take into consideration the sign of the fluctuations in computing the corresponding detrended cross-covariance function. To test the performance of the MF-TWXDFA algorithm, we apply it and the MFCCA method on simulated and actual series. Numerical tests on artificially simulated series demonstrate that our method can accurately detect long-range cross-correlations for two simultaneously recorded series. To further show the utility of MF-TWXDFA, we apply it on time series from stock markets and find that power-law cross-correlation between stock returns is significantly multifractal. A new coefficient, MF-TWXDFA cross-correlation coefficient, is also defined to quantify the levels of cross-correlation between two time series.

Data analytics using canonical correlation analysis and Monte Carlo simulation

Science.gov (United States)

Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

2017-07-01

A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

Metrics correlation and analysis service (MCAS)

International Nuclear Information System (INIS)

Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya

2009-01-01

The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information 'pond' is disorganized, it a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by disjoint middleware.

Canonical correlation analysis of course and teacher evaluation

DEFF Research Database (Denmark)

Sliusarenko, Tamara; Ersbøll, Bjarne Kjær

2010-01-01

At the Technical University of Denmark course evaluations are performed by the students on a questionnaire. On one form the students are asked specific questions regarding the course. On a second form they are asked specific questions about the teacher. This study investigates the extent to which...... information obtained from the course evaluation form overlaps with information obtained from the teacher evaluation form. Employing canonical correlation analysis it was found that course and teacher evaluations are correlated. However, the structure of the canonical correlation is subject to change...

EPPUR SI MUOVE: POSITIONAL AND KINEMATIC CORRELATIONS OF SATELLITE PAIRS IN THE LOW Z UNIVERSE

International Nuclear Information System (INIS)

Ibata, Rodrigo A.; Famaey, Benoit; Martin, Nicolas; Lewis, Geraint F.; Ibata, Neil G.

2015-01-01

We have recently shown that pairs of satellite galaxies located diametrically opposite to each other around their host possess predominantly anti-correlated velocities. This is consistent with a scenario in which ≳50% of satellite galaxies belong to kinematically coherent rotating planar structures. Here we extend this analysis, examining satellites of giant galaxies drawn from an SDSS photometric redshift catalog. We find that there is a ∼17% overabundance (>3σ significance) of candidate satellites at positions diametrically opposite to a spectroscopically confirmed satellite. We show that ΛCDM cosmological simulations do not possess this property when contamination is included. After subtracting contamination, we find ∼2 times more satellites diametrically opposed to a spectroscopically confirmed satellite than at 90° from it, at projected distances ranging from 100 to 150 kpc from the host. This independent analysis thus strongly supports our previous results on anti-correlated velocities. We also find that those satellite pairs with anti-correlated velocities have a strong preference (∼3:1) to align with the major axis of the host whereas those with correlated velocities display the opposite behavior. We finally show that repeating a similar analysis to Ibata et al. with same-side satellites is generally hard to interpret, but is not inconsistent with our previous results when strong quality cuts are applied on the sample. This addresses all of the concerns recently raised by Cautun et al., who did not uncover any flaw in our previous analysis, but may simply have hinted at the physical extent of planar satellite structures by pointing out that the anti-correlation signal weakens at radii >150 kpc. All these unexpected positional and kinematic correlations strongly suggest that a substantial fraction of satellite galaxies are causally linked in their formation and evolution

EPPUR SI MUOVE: POSITIONAL AND KINEMATIC CORRELATIONS OF SATELLITE PAIRS IN THE LOW Z UNIVERSE

Energy Technology Data Exchange (ETDEWEB)

Ibata, Rodrigo A.; Famaey, Benoit; Martin, Nicolas [Observatoire astronomique de Strasbourg, Université de Strasbourg, CNRS, UMR 7550, 11 rue de l’Université, F-67000 Strasbourg (France); Lewis, Geraint F. [Sydney Institute of Astronomy, School of Physics A28, University of Sydney, NSW 2006 (Australia); Ibata, Neil G., E-mail: rodrigo.ibata@astro.unistra.fr [Trinity College, Trinity Street, Cambridge, CB2 1TQ (United Kingdom)

2015-05-20

We have recently shown that pairs of satellite galaxies located diametrically opposite to each other around their host possess predominantly anti-correlated velocities. This is consistent with a scenario in which ≳50% of satellite galaxies belong to kinematically coherent rotating planar structures. Here we extend this analysis, examining satellites of giant galaxies drawn from an SDSS photometric redshift catalog. We find that there is a ∼17% overabundance (>3σ significance) of candidate satellites at positions diametrically opposite to a spectroscopically confirmed satellite. We show that ΛCDM cosmological simulations do not possess this property when contamination is included. After subtracting contamination, we find ∼2 times more satellites diametrically opposed to a spectroscopically confirmed satellite than at 90° from it, at projected distances ranging from 100 to 150 kpc from the host. This independent analysis thus strongly supports our previous results on anti-correlated velocities. We also find that those satellite pairs with anti-correlated velocities have a strong preference (∼3:1) to align with the major axis of the host whereas those with correlated velocities display the opposite behavior. We finally show that repeating a similar analysis to Ibata et al. with same-side satellites is generally hard to interpret, but is not inconsistent with our previous results when strong quality cuts are applied on the sample. This addresses all of the concerns recently raised by Cautun et al., who did not uncover any flaw in our previous analysis, but may simply have hinted at the physical extent of planar satellite structures by pointing out that the anti-correlation signal weakens at radii >150 kpc. All these unexpected positional and kinematic correlations strongly suggest that a substantial fraction of satellite galaxies are causally linked in their formation and evolution.

Metrics correlation and analysis service (MCAS)

International Nuclear Information System (INIS)

Baranovski, Andrew; Dykstra, Dave; Garzoglio, Gabriele; Hesselroth, Ted; Mhashilkar, Parag; Levshina, Tanya

2010-01-01

The complexity of Grid workflow activities and their associated software stacks inevitably involves multiple organizations, ownership, and deployment domains. In this setting, important and common tasks such as the correlation and display of metrics and debugging information (fundamental ingredients of troubleshooting) are challenged by the informational entropy inherent to independently maintained and operated software components. Because such an information pool is disorganized, it is a difficult environment for business intelligence analysis i.e. troubleshooting, incident investigation, and trend spotting. The mission of the MCAS project is to deliver a software solution to help with adaptation, retrieval, correlation, and display of workflow-driven data and of type-agnostic events, generated by loosely coupled or fully decoupled middleware.

Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition

Directory of Open Access Journals (Sweden)

Tomoko Yamasaki

2018-05-01

Full Text Available Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT. Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

Nonlinear canonical correlation analysis with k sets of variables

NARCIS (Netherlands)

van der Burg, Eeke; de Leeuw, Jan

1987-01-01

The multivariate technique OVERALS is introduced as a non-linear generalization of canonical correlation analysis (CCA). First, two sets CCA is introduced. Two sets CCA is a technique that computes linear combinations of sets of variables that correlate in an optimal way. Two sets CCA is then

Sparse canonical correlation analysis: new formulation and algorithm.

Science.gov (United States)

Chu, Delin; Liao, Li-Zhi; Ng, Michael K; Zhang, Xiaowei

2013-12-01

In this paper, we study canonical correlation analysis (CCA), which is a powerful tool in multivariate data analysis for finding the correlation between two sets of multidimensional variables. The main contributions of the paper are: 1) to reveal the equivalent relationship between a recursive formula and a trace formula for the multiple CCA problem, 2) to obtain the explicit characterization for all solutions of the multiple CCA problem even when the corresponding covariance matrices are singular, 3) to develop a new sparse CCA algorithm, and 4) to establish the equivalent relationship between the uncorrelated linear discriminant analysis and the CCA problem. We test several simulated and real-world datasets in gene classification and cross-language document retrieval to demonstrate the effectiveness of the proposed algorithm. The performance of the proposed method is competitive with the state-of-the-art sparse CCA algorithms.

Mapping the fitness landscape of gene expression uncovers the cause of antagonism and sign epistasis between adaptive mutations.

Directory of Open Access Journals (Sweden)

Hsin-Hung Chou

2014-02-01

Full Text Available How do adapting populations navigate the tensions between the costs of gene expression and the benefits of gene products to optimize the levels of many genes at once? Here we combined independently-arising beneficial mutations that altered enzyme levels in the central metabolism of Methylobacterium extorquens to uncover the fitness landscape defined by gene expression levels. We found strong antagonism and sign epistasis between these beneficial mutations. Mutations with the largest individual benefit interacted the most antagonistically with other mutations, a trend we also uncovered through analyses of datasets from other model systems. However, these beneficial mutations interacted multiplicatively (i.e., no epistasis at the level of enzyme expression. By generating a model that predicts fitness from enzyme levels we could explain the observed sign epistasis as a result of overshooting the optimum defined by a balance between enzyme catalysis benefits and fitness costs. Knowledge of the phenotypic landscape also illuminated that, although the fitness peak was phenotypically far from the ancestral state, it was not genetically distant. Single beneficial mutations jumped straight toward the global optimum rather than being constrained to change the expression phenotypes in the correlated fashion expected by the genetic architecture. Given that adaptation in nature often results from optimizing gene expression, these conclusions can be widely applicable to other organisms and selective conditions. Poor interactions between individually beneficial alleles affecting gene expression may thus compromise the benefit of sex during adaptation and promote genetic differentiation.

Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

Science.gov (United States)

Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

2017-05-01

The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

Science.gov (United States)

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson

Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results

Science.gov (United States)

Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

1992-01-01

The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.

Analysis of charge-dependent azimuthal correlations with HADES

Energy Technology Data Exchange (ETDEWEB)

Kornas, Frederic [TU Darmstadt (Germany); Selyuzhenkov, Ilya [GSI (Germany); Galatyuk, Tetyana [TU Darmstadt (Germany); GSI (Germany); Collaboration: HADES-Collaboration

2016-07-01

Charge-dependent azimuthal correlations relative to the reaction plane have been proposed as a probe in the search for the chiral magnetic effect in relativistic heavy-ion collisions. These type of correlations have been measured at the RHIC BES by STAR and at the LHC by ALICE. This contribution discusses two charged particle correlations with respect to the reaction plane measured with high statistic sample of Au+Au collisions at 1.23 AGeV collected by HADES. The Forward wall detector allows to reconstruct the reaction plane using the spectator fragments. The status of the analysis with protons and charged pions will be presented.

Uncovering Student Ideas in Astronomy 45 Formative Assessment Probes

CERN Document Server

Keeley, Page

2012-01-01

What do your students know-or think they know-about what causes night and day, why days are shorter in winter, and how to tell a planet from a star? Find out with this book on astronomy, the latest in NSTA's popular Uncovering Student Ideas in Science series. The 45 astronomy probes provide situations that will pique your students' interest while helping you understand how your students think about key ideas related to the universe and how it operates.

Message Correlation Analysis Tool for NOvA

International Nuclear Information System (INIS)

Lu Qiming; Biery, Kurt A; Kowalkowski, James B

2012-01-01

A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic real-time correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the data acquisition (DAQ) of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.

Message Correlation Analysis Tool for NOvA

CERN Multimedia

CERN. Geneva

2012-01-01

A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic realtime correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the DAQ of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.

International Space Station Future Correlation Analysis Improvements

Science.gov (United States)

Laible, Michael R.; Pinnamaneni, Murthy; Sugavanam, Sujatha; Grygier, Michael

2018-01-01

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

Message correlation analysis tool for NOvA

Energy Technology Data Exchange (ETDEWEB)

Lu, Qiming [Fermilab; Biery, Kurt A. [Fermilab; Kowalkowski, James B. [Fermilab

2012-01-01

A complex running system, such as the NOvA online data acquisition, consists of a large number of distributed but closely interacting components. This paper describes a generic real-time correlation analysis and event identification engine, named Message Analyzer. Its purpose is to capture run time abnormalities and recognize system failures based on log messages from participating components. The initial design of analysis engine is driven by the data acquisition (DAQ) of the NOvA experiment. The Message Analyzer performs filtering and pattern recognition on the log messages and reacts to system failures identified by associated triggering rules. The tool helps the system maintain a healthy running state and to minimize data corruption. This paper also describes a domain specific language that allows the recognition patterns and correlation rules to be specified in a clear and flexible way. In addition, the engine provides a plugin mechanism for users to implement specialized patterns or rules in generic languages such as C++.

Signal correlations in biomass combustion. An information theoretic analysis

Energy Technology Data Exchange (ETDEWEB)

Ruusunen, M.

2013-09-01

Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied

CORRELATIONS BETWEEN FINDINGS OF OCCLUSAL AND MANUAL ANALYSIS IN TMD-PATIENTS

Directory of Open Access Journals (Sweden)

Mariana Dimova

2016-08-01

Full Text Available The aim of this study was to investigate and analyze the possible correlations between findings by manual functional analysis and clinical occlusal analysis in TMD-patients. Material and methods: Material of this study are 111 TMD-patients selected after visual diagnostics, functional brief review under Ahlers Jakstatt, intraoral examination and taking periodontal status. In the period September 2014 - March 2016 all patients were subjected to manual functional analysis and clinical occlusal analysis. 17 people (10 women and 7 men underwent imaging with cone-beam computed tomography. Results: There were found many statistically significant correlations between tests of the structural analysis that indicate the relationships between findings. Conclusion: The presence of statistically significant correlations between occlusal relationships, freedom in the centric and condition of the muscle complex of masticatory system and TMJ confirm the relationship between the state of occlusal components and TMD.

Auto-correlation analysis of wave heights in the Bay of Bengal

Indian Academy of Sciences (India)

Time series observations of significant wave heights in the Bay of Bengal were subjected to auto- correlation analysis to determine temporal variability scale. The analysis indicates an exponen- tial fall of auto-correlation in the first few hours with a decorrelation time scale of about six hours. A similar figure was found earlier ...

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

Science.gov (United States)

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

Science.gov (United States)

Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

Rich structure in the correlation matrix spectra in non-equilibrium steady states.

Science.gov (United States)

Biswas, Soham; Leyvraz, Francois; Monroy Castillero, Paulino; Seligman, Thomas H

2017-01-17

It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.

Epistemically Virtuous Risk Management : Financial Due Diligence and Uncovering the Madoff Fraud

NARCIS (Netherlands)

de Bruin, Boudewijn; Luetge, Christoph; Jauernig, Johanna

2014-01-01

The chapter analyses how Bernard Madoff’s Ponzi scheme was uncovered by Harry Markopolos, an employee of Rampart Investment Management, LLC, and the contribution of so-called epistemic virtues to Markopolos’ success. After Rampart had informed the firm about an allegedly highly successful hedge fund

Using Brain Stimulation to Disentangle Neural Correlates of Conscious Vision

Directory of Open Access Journals (Sweden)

Tom Alexander de Graaf

2014-09-01

Full Text Available Research into the neural correlates of consciousness (NCCs has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as fMRI or EEG do not always afford inference on the role these brain processes play in conscious vision. Such empirical neural correlates of consciousness could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical neural correlates of consciousness.

A distinctive avian assemblage (Aves: Passeriformes in Western Darién, Panama is uncovered through a disease surveillance program

Directory of Open Access Journals (Sweden)

Matthew J. Miller

2014-08-01

Full Text Available Basic knowledge about the distribution of flora and fauna is lacking for most tropical areas. Improving our knowledge of the tropical biota will help address contemporary global problems, including emerging tropical diseases. Less appreciated is the role that applied studies can have in improving our understanding of basic biological patterns and processes in the tropics. Here, I describe a novel avifauna assemblage uncovered in Western Darién province in the Republic of Panama that was uncovered during a vector-borne disease surveillance program. I compared the passerine bird species composition at 16 sites using records from recent ornithological expeditions sponsored by the Smithsonian Tropical Research Institute in Central and Eastern Panama. Based on the results of a Mantel test, geographic distance did not correlate with pairwise distinctiveness of sites. Instead, based on an index of distinctiveness modified from the Chao-Jaccard index, most sites were more or less similarly distinctive, with one site, Aruza Abajo, significantly more distinctive than the rest. I found that the distinctiveness of this site was due not only to the presence of several rare and range-restricted taxa, but also to the absence of taxa that are common elsewhere. This finding provides more evidence of high species composition turnover (beta-diversity in the Panamanian biota, which appears to be driven by a combination of soil and climate differences over narrow distances. Rev. Biol. Trop. 62 (2: 711-717. Epub 2014 June 01.

Study of relationship between MUF correlation and detection sensitivity of statistical analysis

International Nuclear Information System (INIS)

Tamura, Toshiaki; Ihara, Hitoshi; Yamamoto, Yoichi; Ikawa, Koji

1989-11-01

Various kinds of statistical analysis are proposed to NRTA (Near Real Time Materials Accountancy) which was devised to satisfy the timeliness goal of one of the detection goals of IAEA. It will be presumed that different statistical analysis results will occur between the case of considered rigorous error propagation (with MUF correlation) and the case of simplified error propagation (without MUF correlation). Therefore, measurement simulation and decision analysis were done using flow simulation of 800 MTHM/Y model reprocessing plant, and relationship between MUF correlation and detection sensitivity and false alarm of statistical analysis was studied. Specific character of material accountancy for 800 MTHM/Y model reprocessing plant was grasped by this simulation. It also became clear that MUF correlation decreases not only false alarm but also detection probability for protracted loss in case of CUMUF test and Page's test applied to NRTA. (author)

GIS and correlation analysis of geo-environmental variables ...

African Journals Online (AJOL)

Key words: Correlation, GIS, malaria geography, malaria incidence ... problems, as it has created the possibility for geocoding, extracting and spatial analysis of health ...... Bulletin of the World Health Organization, 78(12), 1438–1444. Carter ...

Cross-correlation analysis of Ge/Li/ spectra

International Nuclear Information System (INIS)

MacDonald, R.; Robertson, A.; Kennett, T.J.; Prestwich, W.V.

1974-01-01

A sensitive technique is proposed for activation analysis using cross-correlation and improved spectral orthogonality achieved through use of a rectangular zero area digital filter. To test the accuracy and reliability of the cross-correlation procedure five spectra obtained with a Ge/Li detector were combined in different proportions. Gaussian distributed statistics were then added to the composite spectra by means of a pseudo-random number generator. The basis spectra used were 76 As, 82 Br, 72 Ga, 77 Ge, and room background. In general, when the basis spectra were combined in roughly comparable proportions the accuracy of the techique proved to be excelent (>1%). However, of primary importance was the ability of the correlation technique to identify low intensity components in the presence of high intensity components. It was found that the detection threshold for Ge, for example, was not reached until the Ge content in the unfiltered spectrum was <0.16%. (T.G.)

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

Science.gov (United States)

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago.

Science.gov (United States)

Binaku, Katrina; O'Brien, Timothy; Schmeling, Martina; Fosco, Tinamarie

2013-09-01

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity's influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed's influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and

Uncovering beat deafness: detecting rhythm disorders with synchronized finger tapping and perceptual timing tasks.

Science.gov (United States)

Dalla Bella, Simone; Sowiński, Jakub

2015-03-16

A set of behavioral tasks for assessing perceptual and sensorimotor timing abilities in the general population (i.e., non-musicians) is presented here with the goal of uncovering rhythm disorders, such as beat deafness. Beat deafness is characterized by poor performance in perceiving durations in auditory rhythmic patterns or poor synchronization of movement with auditory rhythms (e.g., with musical beats). These tasks include the synchronization of finger tapping to the beat of simple and complex auditory stimuli and the detection of rhythmic irregularities (anisochrony detection task) embedded in the same stimuli. These tests, which are easy to administer, include an assessment of both perceptual and sensorimotor timing abilities under different conditions (e.g., beat rates and types of auditory material) and are based on the same auditory stimuli, ranging from a simple metronome to a complex musical excerpt. The analysis of synchronized tapping data is performed with circular statistics, which provide reliable measures of synchronization accuracy (e.g., the difference between the timing of the taps and the timing of the pacing stimuli) and consistency. Circular statistics on tapping data are particularly well-suited for detecting individual differences in the general population. Synchronized tapping and anisochrony detection are sensitive measures for identifying profiles of rhythm disorders and have been used with success to uncover cases of poor synchronization with spared perceptual timing. This systematic assessment of perceptual and sensorimotor timing can be extended to populations of patients with brain damage, neurodegenerative diseases (e.g., Parkinson's disease), and developmental disorders (e.g., Attention Deficit Hyperactivity Disorder).

Revisiting Uncovered Interest Rate Parity: Switching Between UIP and the Random Walk

NARCIS (Netherlands)

R. Huisman (Ronald); R.J. Mahieu (Ronald)

2007-01-01

textabstractIn this paper, we examine in which periods uncovered interest rate parity was likely to hold. Empirical research has shown mixed evidence on UIP. The main finding is that it doesn’t hold, although some researchers were not able to reject UIP in periods with large interest differentials

General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures

OpenAIRE

WenJun Zhang; Xin Li

2015-01-01

Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

Science.gov (United States)

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

[Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

Science.gov (United States)

Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

2013-10-01

In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

Probabilistic leak-before-break analysis with correlated input parameters

International Nuclear Information System (INIS)

Qian Guian; Niffenegger, Markus; Karanki, Durga Rao; Li Shuxin

2013-01-01

Highlights: ► The correlation of crack growth has the most significant impact on LBB behavior. ► The correlation impact increases with the correlation coefficients. ► The correlation impact increases with the number of cracks. ► Independent assumption may lead to nonconservative result. - Abstract: The paper presents a probabilistic methodology considering the correlations between the input variables for the analysis of leak-before-break (LBB) behavior of a pressure tube. A computer program based on Monte Carlo (MC) simulation with Nataf transformation has been developed to allow the proposed methodology to calculate both the time from the first leakage to unstable fracture and the time from leakage detection to unstable fracture. The results show that the correlation of the crack growth rates between different cracks has the most significant impact on the LBB behavior of the pressure tube. The impact of the parameters correlation on LBB behavior increases with the crack numbers. If the correlations between different parameters for an individual crack are not considered, the predicted results are nonconservative when the cumulative probability is below 50% and conservative when it is above 50%.

Model-independent analysis with BPM correlation matrices

International Nuclear Information System (INIS)

Irwin, J.; Wang, C.X.; Yan, Y.T.; Bane, K.; Cai, Y.; Decker, F.; Minty, M.; Stupakov, G.; Zimmermann, F.

1998-06-01

The authors discuss techniques for Model-Independent Analysis (MIA) of a beamline using correlation matrices of physical variables and Singular Value Decomposition (SVD) of a beamline BPM matrix. The beamline matrix is formed from BPM readings for a large number of pulses. The method has been applied to the Linear Accelerator of the SLAC Linear Collider (SLC)

Analyzing the Cross-Correlation Between Onshore and Offshore RMB Exchange Rates Based on Multifractal Detrended Cross-Correlation Analysis (MF-DCCA)

Science.gov (United States)

Xie, Chi; Zhou, Yingying; Wang, Gangjin; Yan, Xinguo

We use the multifractal detrended cross-correlation analysis (MF-DCCA) method to explore the multifractal behavior of the cross-correlation between exchange rates of onshore RMB (CNY) and offshore RMB (CNH) against US dollar (USD). The empirical data are daily prices of CNY/USD and CNH/USD from May 1, 2012 to February 29, 2016. The results demonstrate that: (i) the cross-correlation between CNY/USD and CNH/USD is persistent and its fluctuation is smaller when the order of fluctuation function is negative than that when the order is positive; (ii) the multifractal behavior of the cross-correlation between CNY/USD and CNH/USD is significant during the sample period; (iii) the dynamic Hurst exponents obtained by the rolling windows analysis show that the cross-correlation is stable when the global economic situation is good and volatile in bad situation; and (iv) the non-normal distribution of original data has a greater effect on the multifractality of the cross-correlation between CNY/USD and CNH/USD than the temporary correlation.

Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective

Science.gov (United States)

Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita

2016-12-01

The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

Science.gov (United States)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Uncovering cognitive processes: Different techniques that can contribute to cognitive load research and instruction

NARCIS (Netherlands)

Van Gog, Tamara; Kester, Liesbeth; Nievelstein, Fleurie; Giesbers, Bas; Fred, Paas

2009-01-01

Van Gog, T., Kester, L., Nievelstein, F., Giesbers, B., & Paas, F. (2009). Uncovering cognitive processes: Different techniques that can contribute to cognitive load research and instruction. Computers in Human Behavior, 25, 325-331.

Information-Pooling Bias in Collaborative Security Incident Correlation Analysis.

Science.gov (United States)

Rajivan, Prashanth; Cooke, Nancy J

2018-03-01

Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.

L2 Reading Comprehension and Its Correlates: A Meta-Analysis

Science.gov (United States)

Jeon, Eun Hee; Yamashita, Junko

2014-01-01

The present meta-analysis examined the overall average correlation (weighted for sample size and corrected for measurement error) between passage-level second language (L2) reading comprehension and 10 key reading component variables investigated in the research domain. Four high-evidence correlates (with 18 or more accumulated effect sizes: L2…

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

OpenAIRE

Han, Fang; Liu, Han

2016-01-01

Correlation matrices play a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, it is not an effective estimator when facing heavy-tailed distributions. As a robust alternative, Han and Liu [J. Am. Stat. Assoc. 109 (2015) 275-2...

Climate change adaptation: Uncovering constraints to the use of adaptation strategies among food crop farmers in South-west, Nigeria using principal component analysis (PCA

Directory of Open Access Journals (Sweden)

Moradeyo Adebanjo Otitoju

2016-12-01

Full Text Available This study focused on the constraints to the use of climate variability/change adaptation strategies in South-west Nigeria. Multistage random technique was employed to select the location and the respondents. Descriptive statistics and principal component analysis (PCA were the analytical tools engaged in this study. The constraints to climate variability and change examined before did not use PCA but generalized factor analysis. Hence, there is need to examine these constraints extensively using PCA. Uncovering the constraints to the use of climate variability/change adaptation strategies among crop framers is important to give a realistic direction in the development of farmer-inclusive climate policies in Nigeria. The PCA result showed that the principal constraints that the farmers faced in climate change adaptation were public, institutional and labour constraint; land, neighbourhood norms and religious beliefs constraint; high cost of inputs, technological and information constraint; farm distance, access to climate information, off-farm job and credit constraint; and poor agricultural programmes and service delivery constraint. These findings pointed out the need for both the government and non-government organizations to intensify efforts on institutional, technological and farmers’ friendly land tenure and information systems as effective measures to guide inclusive climate change adaptation policies and development in South-west Nigeria.

Ten Years Trend Analysis of Malaria Prevalence and its Correlation ...

African Journals Online (AJOL)

The data were analyzed using SPSS software package 16.0. Pearson's correlation analysis was conducted to see the correlation between plasmodium species and climatic variables. Within the last decade (2004–2013) a total of 30,070 blood films were examined for malaria in Sire health center and of this 6036 (20.07%) ...

Hepatitis C virus host cell interactions uncovered

DEFF Research Database (Denmark)

Gottwein, Judith; Bukh, Jens

2007-01-01

  Insights into virus-host cell interactions as uncovered by Randall et al. (1) in a recent issue of PNAS further our understanding of the hepatitis C virus (HCV) life cycle, persistence, and pathogenesis and might lead to the identification of new therapeutic targets. HCV persistently infects 180...... million individuals worldwide, causing chronic hepatitis, liver cirrhosis, and hepatocellular carcinoma. The only approved treatment, combination therapy with IFN- and ribavirin, targets cellular pathways (2); however, a sustained virologic response is achieved only in approximately half of the patients...... treated. Therefore, there is a pressing need for the identification of novel drugs against hepatitis C. Although most research focuses on the development of HCV-specific antivirals, such as protease and polymerase inhibitors (3), cellular targets could be pursued and might allow the development of broad...

Correlations between MRI and Information Processing Speed in MS: A Meta-Analysis

Directory of Open Access Journals (Sweden)

S. M. Rao

2014-01-01

Full Text Available Objectives. To examine relationships between conventional MRI measures and the paced auditory serial addition test (PASAT and symbol digit modalities test (SDMT. Methods. A systematic literature review was conducted. Included studies had ≥30 multiple sclerosis (MS patients, administered the SDMT or PASAT, and measured T2LV or brain atrophy. Meta-analysis of MRI/information processing speed (IPS correlations, analysis of MRI/IPS significance tests to account for reporting bias, and binomial testing to detect trends when comparing correlation strengths of SDMT versus PASAT and T2LV versus atrophy were conducted. Results. The 39 studies identified frequently reported only significant correlations, suggesting reporting bias. Direct meta-analysis was only feasible for correlations between SDMT and T2LV (r=-0.45, P<0.001 and atrophy in patients with mixed-MS subtypes (r=-0.54, P<0.001. Familywise Holm-Bonferroni testing found that selective reporting was not the source of at least half of significant results reported. Binomial tests (P=0.006 favored SDMT over PASAT in strength of MRI correlations. Conclusions. A moderate-to-strong correlation exists between impaired IPS and MRI in mixed MS populations. Correlations with MRI were stronger for SDMT than for PASAT. Neither heterogeneity among populations nor reporting bias appeared to be responsible for these findings.

Gene Expression Deconvolution for Uncovering Molecular Signatures in Response to Therapy in Juvenile Idiopathic Arthritis.

Directory of Open Access Journals (Sweden)

Ang Cui

Full Text Available Gene expression-based signatures help identify pathways relevant to diseases and treatments, but are challenging to construct when there is a diversity of disease mechanisms and treatments in patients with complex diseases. To overcome this challenge, we present a new application of an in silico gene expression deconvolution method, ISOpure-S1, and apply it to identify a common gene expression signature corresponding to response to treatment in 33 juvenile idiopathic arthritis (JIA patients. Using pre- and post-treatment gene expression profiles only, we found a gene expression signature that significantly correlated with a reduction in the number of joints with active arthritis, a measure of clinical outcome (Spearman rho = 0.44, p = 0.040, Bonferroni correction. This signature may be associated with a decrease in T-cells, monocytes, neutrophils and platelets. The products of most differentially expressed genes include known biomarkers for JIA such as major histocompatibility complexes and interleukins, as well as novel biomarkers including α-defensins. This method is readily applicable to expression datasets of other complex diseases to uncover shared mechanistic patterns in heterogeneous samples.

Transcriptomic Analysis of Long Non-Coding RNAs and Coding Genes Uncovers a Complex Regulatory Network That Is Involved in Maize Seed Development

Directory of Open Access Journals (Sweden)

Ming Zhu

2017-10-01

Full Text Available Long non-coding RNAs (lncRNAs have been reported to be involved in the development of maize plant. However, few focused on seed development of maize. Here, we identified 753 lncRNA candidates in maize genome from six seed samples. Similar to the mRNAs, lncRNAs showed tissue developmental stage specific and differential expression, indicating their putative role in seed development. Increasing evidence shows that crosstalk among RNAs mediated by shared microRNAs (miRNAs represents a novel layer of gene regulation, which plays important roles in plant development. Functional roles and regulatory mechanisms of lncRNAs as competing endogenous RNAs (ceRNA in plants, particularly in maize seed development, are unclear. We combined analyses of consistently altered 17 lncRNAs, 840 mRNAs and known miRNA to genome-wide investigate potential lncRNA-mediated ceRNA based on “ceRNA hypothesis”. The results uncovered seven novel lncRNAs as potential functional ceRNAs. Functional analyses based on their competitive coding-gene partners by Gene Ontology (GO and KEGG biological pathway demonstrated that combined effects of multiple ceRNAs can have major impacts on general developmental and metabolic processes in maize seed. These findings provided a useful platform for uncovering novel mechanisms of maize seed development and may provide opportunities for the functional characterization of individual lncRNA in future studies.

Process correlation analysis model for process improvement identification.

Science.gov (United States)

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

GIS and correlation analysis of geo-environmental variables ...

African Journals Online (AJOL)

GIS and correlation analysis of geo-environmental variables influencing malaria prevalence in the Saboba district of Northern Ghana. ... The study also applied spline interpolation technique to map malaria prevalence in the district using standardised malaria incidence. The result indicates that distance to marshy areas is ...

Correlates and consequences of internalized stigma for people living with mental illness: a systematic review and meta-analysis.

Science.gov (United States)

Livingston, James D; Boyd, Jennifer E

2010-12-01

An expansive body of research has investigated the experiences and adverse consequences of internalized stigma for people with mental illness. This article provides a systematic review and meta-analysis of the extant research regarding the empirical relationship between internalized stigma and a range of sociodemographic, psychosocial, and psychiatric variables for people who live with mental illness. An exhaustive review of the research literature was performed on all articles published in English that assessed a statistical relationship between internalized stigma and at least one other variable for adults who live with mental illness. In total, 127 articles met the inclusion criteria for systematic review, of which, data from 45 articles were extracted for meta-analyses. None of the sociodemographic variables that were included in the study were consistently or strongly correlated with levels of internalized stigma. The review uncovered a striking and robust negative relationship between internalized stigma and a range of psychosocial variables (e.g., hope, self-esteem, and empowerment). Regarding psychiatric variables, internalized stigma was positively associated with psychiatric symptom severity and negatively associated with treatment adherence. The review draws attention to the lack of longitudinal research in this area of study which has inhibited the clinical relevance of findings related to internalized stigma. The study also highlights the need for greater attention on disentangling the true nature of the relationship between internalized stigma and other psychosocial variables. Copyright © 2010 Elsevier Ltd. All rights reserved.

Uncovering the Motivating Factors behind Writing in English in en EFL Context

Science.gov (United States)

Büyükyavuz, Oya; Çakir, Ismail

2014-01-01

Writing in a language, whether the target or native, is regarded as a complex activity operating on multiple cognitive levels. This study aimed to uncover the factors which motivate teacher trainees of English to write in English in an EFL context. The study also investigated the differences in the ways teacher trainees are motivated in terms of…

Robustness analysis of geodetic networks in the case of correlated observations

Directory of Open Access Journals (Sweden)

Mevlut Yetkin

Full Text Available GPS (or GNSS networks are invaluable tools for monitoring natural hazards such as earthquakes. However, blunders in GPS observations may be mistakenly interpreted as deformation. Therefore, robust networks are needed in deformation monitoring using GPS networks. Robustness analysis is a natural merger of reliability and strain and defined as the ability to resist deformations caused by the maximum undetecle errors as determined from internal reliability analysis. However, to obtain rigorously correct results; the correlations among the observations must be considered while computing maximum undetectable errors. Therefore, we propose to use the normalized reliability numbers instead of redundancy numbers (Baarda's approach in robustness analysis of a GPS network. A simple mathematical relation showing the ratio between uncorrelated and correlated cases for maximum undetectable error is derived. The same ratio is also valid for the displacements. Numerical results show that if correlations among observations are ignored, dramatically different displacements can be obtained depending on the size of multiple correlation coefficients. Furthermore, when normalized reliability numbers are small, displacements get large, i.e., observations with low reliability numbers cause bigger displacements compared to observations with high reliability numbers.

Correlative SEM SERS for quantitative analysis of dimer nanoparticles.

Science.gov (United States)

Timmermans, F J; Lenferink, A T M; van Wolferen, H A G M; Otto, C

2016-11-14

A Raman microscope integrated with a scanning electron microscope was used to investigate plasmonic structures by correlative SEM-SERS analysis. The integrated Raman-SEM microscope combines high-resolution electron microscopy information with SERS signal enhancement from selected nanostructures with adsorbed Raman reporter molecules. Correlative analysis is performed for dimers of two gold nanospheres. Dimers were selected on the basis of SEM images from multi aggregate samples. The effect of the orientation of the dimer with respect to the polarization state of the laser light and the effect of the particle gap size on the Raman signal intensity is observed. Additionally, calculations are performed to simulate the electric near field enhancement. These simulations are based on the morphologies observed by electron microscopy. In this way the experiments are compared with the enhancement factor calculated with near field simulations and are subsequently used to quantify the SERS enhancement factor. Large differences between experimentally observed and calculated enhancement factors are regularly detected, a phenomenon caused by nanoscale differences between the real and 'simplified' simulated structures. Quantitative SERS experiments reveal the structure induced enhancement factor, ranging from ∼200 to ∼20 000, averaged over the full nanostructure surface. The results demonstrate correlative Raman-SEM microscopy for the quantitative analysis of plasmonic particles and structures, thus enabling a new analytical method in the field of SERS and plasmonics.

Significant Locus and Metabolic Genetic Correlations Revealed in Genome-Wide Association Study of Anorexia Nervosa.

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Duncan, Laramie; Yilmaz, Zeynep; Gaspar, Helena; Walters, Raymond; Goldstein, Jackie; Anttila, Verneri; Bulik-Sullivan, Brendan; Ripke, Stephan; Thornton, Laura; Hinney, Anke; Daly, Mark; Sullivan, Patrick F; Zeggini, Eleftheria; Breen, Gerome; Bulik, Cynthia M

2017-09-01

The authors conducted a genome-wide association study of anorexia nervosa and calculated genetic correlations with a series of psychiatric, educational, and metabolic phenotypes. Following uniform quality control and imputation procedures using the 1000 Genomes Project (phase 3) in 12 case-control cohorts comprising 3,495 anorexia nervosa cases and 10,982 controls, the authors performed standard association analysis followed by a meta-analysis across cohorts. Linkage disequilibrium score regression was used to calculate genome-wide common variant heritability (single-nucleotide polymorphism [SNP]-based heritability [h 2 SNP ]), partitioned heritability, and genetic correlations (r g ) between anorexia nervosa and 159 other phenotypes. Results were obtained for 10,641,224 SNPs and insertion-deletion variants with minor allele frequencies >1% and imputation quality scores >0.6. The h 2 SNP of anorexia nervosa was 0.20 (SE=0.02), suggesting that a substantial fraction of the twin-based heritability arises from common genetic variation. The authors identified one genome-wide significant locus on chromosome 12 (rs4622308) in a region harboring a previously reported type 1 diabetes and autoimmune disorder locus. Significant positive genetic correlations were observed between anorexia nervosa and schizophrenia, neuroticism, educational attainment, and high-density lipoprotein cholesterol, and significant negative genetic correlations were observed between anorexia nervosa and body mass index, insulin, glucose, and lipid phenotypes. Anorexia nervosa is a complex heritable phenotype for which this study has uncovered the first genome-wide significant locus. Anorexia nervosa also has large and significant genetic correlations with both psychiatric phenotypes and metabolic traits. The study results encourage a reconceptualization of this frequently lethal disorder as one with both psychiatric and metabolic etiology.

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

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Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Testing and interpreting uncovered interest parity in Russia

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Dmitry Vasilyev

2017-06-01

Full Text Available The failure of uncovered interest rate parity (UIP is a well-known phenomenon of the last thirty years. UIP failure is more prominent in advanced economies than in emerging market economies. Typically, UIP estimation for an advanced economy generates a negative coefficient, meaning that a higher interest rate in advanced economy A will result in the appreciation of economy A's exchange rate. For emerging market economies, higher interest rates usually correspond to future depreciation, although this depreciation is not sufficient for UIP to hold. This paper shows that UIP holds in Russia better than in other emerging market economies when the UIP equation accounts for a constant risk premium. Consequently, there is no forward premium puzzle for Russian data for 2001–2014. To determine the results for Russia and to compare them with the results for other countries, we estimate UIP first for Russia and then for advanced and emerging market economies using seemingly unrelated regressions and panel data analysis. By comparing the profitability of static and dynamic carry trade strategies, we also confirm that in emerging market economies, risk premiums are often constant, whereas in advanced economies, risk premiums are almost always volatile. This may explain why UIP holds better in emerging market economies. It also enables us to formulate a hypothesis that macroeconomic policies of emerging market economies (e.g., the accumulation of large foreign exchange reserves stabilize risk premiums.

ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.

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Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey

2018-06-21

Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.

Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data

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Delignières, Didier; Marmelat, Vivien

2014-01-01

In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.

Covered versus Uncovered Self-Expandable Metal Stents for Managing Malignant Distal Biliary Obstruction: A Meta-Analysis.

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Li, Jinjin; Li, Tong; Sun, Ping; Yu, Qihong; Wang, Kun; Chang, Weilong; Song, Zifang; Zheng, Qichang

2016-01-01

To compare the efficacy of using covered self-expandable metal stents (CSEMSs) and uncovered self-expandable metal stents (UCSEMSs) to treat objective jaundice caused by an unresectable malignant tumor. We performed a comprehensive electronic search from 1980 to May 2015. All randomized controlled trials comparing the use of CSEMSs and UCSEMSs to treat malignant distal biliary obstruction were included. The analysis included 1417 patients enrolled in 14 trials. We did not detect significant differences between the UCSEMS group and the CSEMS group in terms of cumulative stent patency (hazard ratio (HR) 0.93, 95% confidence interval (CI) 0.19-4.53; p = 0.93, I2 = 0%), patient survival (HR 0.77, 95% CI 0.05-10.87; p = 0.85, I2 = 0%), overall stent dysfunction (relative ratio (RR) 0.85, M-H, random, 95% CI 0.57-1.25; p = 0.83, I2 = 63%), the overall complication rate (RR 1.26, M-H, fixed, 95% CI 0.94-1.68; p = 0.12, I2 = 0%) or the change in serum bilirubin (weighted mean difference (WMD) -0.13, IV fixed, 95% CI 0.56-0.3; p = 0.55, I2 = 0%). However, we did detect a significant difference in the main causes of stent dysfunction between the two groups. In particular, the CSEMS group exhibited a lower rate of tumor ingrowth (RR 0.25, M-H, random, 95% CI 0.12-0.52; p = 0.002, I2 = 40%) but a higher rate of tumor overgrowth (RR 1.76, M-H, fixed, 95% CI 1.03-3.02; p = 0.04, I2 = 0%). Patients with CSEMSs also exhibited a higher migration rate (RR 9.33, M-H, fixed, 95% CI 2.54-34.24; p = 0.008, I2 = 0%) and a higher rate of sludge formation (RR 2.47, M-H, fixed, 95% CI 1.36-4.50; p = 0.003, I2 = 0%). Our meta-analysis indicates that there is no significant difference in primary stent patency and stent dysfunction between CSEMSs and UCSEMSs during the period from primary stent insertion to primary stent dysfunction or patient death. However, when taking further management for occluded stents into consideration, CSEMSs is a better choice for patients with malignant biliary

Correlation Factor Analysis of Retinal Microvascular Changes in Patients With Essential Hypertension

Institute of Scientific and Technical Information of China (English)

Huang Duru; Huang Zhongning

2006-01-01

Objectives To investigate correlation between retinal microvascular signs and essential hypertension classification. Methods The retinal microvascular signs in patients with essential hypertension were assessed with the indirect biomicroscopy lens, the direct and the indirect ophthalmoscopes were used to determine the hypertensive retinopathy grades and retinal arteriosclerosis grades.The rank correlation analysis was used to analysis the correlation these grades with the risk factors concerned with hypertension. Results Of 72 cases with essential hypertension, 28 cases complicated with coronary disease, 20 cases diabetes, 41 cases stroke,17 cases renal malfunction. Varying extent retinal arterioscleroses were found in 71 cases, 1 case with retinal hemorrhage, 2 cases with retina edema, 4 cases with retinal hard exudation, 5 cases with retinal hemorrhage complicated by hard exudation, 2 cases with retinal hemorrhage complicated by hard exudation and cotton wool spot, 1 case with retinal hemorrhage complicated by hard exudation and microaneurysms,1 case with retinal edema and hard exudation, 1 case with retinal microaneurysms, 1 case with branch retinal vein occlusion. The rank correlation analysis showed that either hypertensive retinopathy grades or retinal arteriosclerosis grades were correlated with risk factor lamination of hypertension (r=0.25 or 0.31, P＜0.05), other correlation factors included age and blood high density lipoprotein concerned about hypertensive retinopathy grades or retinal arteriosclerosis grades, but other parameters, namely systolic or diastolic pressure, total cholesterol, triglyceride, low density lipoprotein cholesterol, fasting blood glucose,blood urea nitrogen and blood creatinine were not confirmed in this correlation analysis (P ＞ 0.05).Conclusions Either hypertensive retinopathy grade or retinal arteriosclerosis grade is close with the hypertension risk factor lamination, suggesting that the fundus examination of patients with

Statistical analysis of correlated experimental data and neutron cross section evaluation

International Nuclear Information System (INIS)

Badikov, S.A.

1998-01-01

The technique for evaluation of neutron cross sections on the basis of statistical analysis of correlated experimental data is presented. The most important stages of evaluation beginning from compilation of correlation matrix for measurement uncertainties till representation of the analysis results in the ENDF-6 format are described in details. Special attention is paid to restrictions (positive uncertainty) on covariation matrix of approximate parameters uncertainties generated within the method of least square fit which is derived from physical reasons. The requirements for source experimental data assuring satisfaction of the restrictions mentioned above are formulated. Correlation matrices of measurement uncertainties in particular should be also positively determined. Variants of modelling the positively determined correlation matrices of measurement uncertainties in a situation when their consequent calculation on the basis of experimental information is impossible are discussed. The technique described is used for creating the new generation of estimates of dosimetric reactions cross sections for the first version of the Russian dosimetric file (including nontrivial covariation information)

Group sparse canonical correlation analysis for genomic data integration.

Science.gov (United States)

Lin, Dongdong; Zhang, Jigang; Li, Jingyao; Calhoun, Vince D; Deng, Hong-Wen; Wang, Yu-Ping

2013-08-12

The emergence of high-throughput genomic datasets from different sources and platforms (e.g., gene expression, single nucleotide polymorphisms (SNP), and copy number variation (CNV)) has greatly enhanced our understandings of the interplay of these genomic factors as well as their influences on the complex diseases. It is challenging to explore the relationship between these different types of genomic data sets. In this paper, we focus on a multivariate statistical method, canonical correlation analysis (CCA) method for this problem. Conventional CCA method does not work effectively if the number of data samples is significantly less than that of biomarkers, which is a typical case for genomic data (e.g., SNPs). Sparse CCA (sCCA) methods were introduced to overcome such difficulty, mostly using penalizations with l-1 norm (CCA-l1) or the combination of l-1and l-2 norm (CCA-elastic net). However, they overlook the structural or group effect within genomic data in the analysis, which often exist and are important (e.g., SNPs spanning a gene interact and work together as a group). We propose a new group sparse CCA method (CCA-sparse group) along with an effective numerical algorithm to study the mutual relationship between two different types of genomic data (i.e., SNP and gene expression). We then extend the model to a more general formulation that can include the existing sCCA models. We apply the model to feature/variable selection from two data sets and compare our group sparse CCA method with existing sCCA methods on both simulation and two real datasets (human gliomas data and NCI60 data). We use a graphical representation of the samples with a pair of canonical variates to demonstrate the discriminating characteristic of the selected features. Pathway analysis is further performed for biological interpretation of those features. The CCA-sparse group method incorporates group effects of features into the correlation analysis while performs individual feature

Linear and Nonlinear Multiset Canonical Correlation Analysis (invited talk)

DEFF Research Database (Denmark)

Hilger, Klaus Baggesen; Nielsen, Allan Aasbjerg; Larsen, Rasmus

2002-01-01

This paper deals with decompositioning of multiset data. Friedman's alternating conditional expectations (ACE) algorithm is extended to handle multiple sets of variables of different mixtures. The new algorithm finds estimates of the optimal transformations of the involved variables that maximize...... the sum of the pair-wise correlations over all sets. The new algorithm is termed multi-set ACE (MACE) and can find multiple orthogonal eigensolutions. MACE is a generalization of the linear multiset correlations analysis (MCCA). It handles multivariate multisets of arbitrary mixtures of both continuous...

A multimodal stress monitoring system with canonical correlation analysis.

Science.gov (United States)

Unsoo Ha; Changhyeon Kim; Yongsu Lee; Hyunki Kim; Taehwan Roh; Hoi-Jun Yoo

2015-08-01

The multimodal stress monitoring headband is proposed for mobile stress management system. It is composed of headband and earplugs. Electroencephalography (EEG), hemoencephalography (HEG) and heart-rate variability (HRV) can be achieved simultaneously in the proposed system for user status estimation. With canonical correlation analysis (CCA) and temporal-kernel CCA (tkCCA) algorithm, those different signals can be combined for maximum correlation. Thanks to the proposed combination algorithm, the accuracy of the proposed system increased up to 19 percentage points than unimodal monitoring system in n-back task.

Inverse correlation of population similarity and introduction date for invasive ascidians.

Directory of Open Access Journals (Sweden)

Nathan Silva

2008-06-01

Full Text Available The genomes of many marine invertebrates, including the purple sea urchin and the solitary ascidians Ciona intestinalis and Ciona savignyi, show exceptionally high levels of heterozygosity, implying that these populations are highly polymorphic. Analysis of the C. savignyi genome found little evidence to support an elevated mutation rate, but rather points to a large population size contributing to the polymorphism level. In the present study, the relative genetic polymorphism levels in sampled populations of ten different ascidian species were determined using a similarity index generated by AFLP analysis. The goal was to determine the range of polymorphism within the populations of different species, and to uncover factors that may contribute to the high level of polymorphism. We observe that, surprisingly, the levels of polymorphism within these species show a negative correlation with the reported age of invasive populations, and that closely related species show substantially different levels of genetic polymorphism. These findings show exceptions to the assumptions that invasive species start with a low level of genetic polymorphism that increases over time and that closely related species have similar levels of genetic polymorphism.

Irregular Liesegang-type patterns in gas phase revisited. II. Statistical correlation analysis

Science.gov (United States)

Torres-Guzmán, José C.; Martínez-Mekler, Gustavo; Müller, Markus F.

2016-05-01

We present a statistical analysis of Liesegang-type patterns formed in a gaseous HCl-NH3 system by ammonium chloride precipitation along glass tubes, as described in Paper I [J. C. Torres-Guzmán et al., J. Chem. Phys. 144, 174701 (2016)] of this work. We focus on the detection and characterization of short and long-range correlations within the non-stationary sequence of apparently irregular precipitation bands. To this end we applied several techniques to estimate spatial correlations stemming from different fields, namely, linear auto-correlation via the power spectral density, detrended fluctuation analysis (DFA), and methods developed in the context of random matrix theory (RMT). In particular RMT methods disclose well pronounced long-range correlations over at least 40 bands in terms of both, band positions and intensity values. By using a variant of the DFA we furnish proof of the nonlinear nature of the detected long-range correlations.

Correlation between detrended fluctuation analysis and the Lempel-Ziv complexity in nonlinear time series analysis

International Nuclear Information System (INIS)

Tang You-Fu; Liu Shu-Lin; Jiang Rui-Hong; Liu Ying-Hui

2013-01-01

We study the correlation between detrended fluctuation analysis (DFA) and the Lempel-Ziv complexity (LZC) in nonlinear time series analysis in this paper. Typical dynamic systems including a logistic map and a Duffing model are investigated. Moreover, the influence of Gaussian random noise on both the DFA and LZC are analyzed. The results show a high correlation between the DFA and LZC, which can quantify the non-stationarity and the nonlinearity of the time series, respectively. With the enhancement of the random component, the exponent a and the normalized complexity index C show increasing trends. In addition, C is found to be more sensitive to the fluctuation in the nonlinear time series than α. Finally, the correlation between the DFA and LZC is applied to the extraction of vibration signals for a reciprocating compressor gas valve, and an effective fault diagnosis result is obtained

Generalization of proposed tendon friction correlation and its application to PCCV structural analysis

International Nuclear Information System (INIS)

Kashiwase, Takako; Nagasaka, Hideo

2000-01-01

The present paper dealt with the extension of tendon friction coefficient correlation as a function of loading end load and circumferential angle, proposed in the former paper. The extended correlation further included the effects of the number of strands contacted with sheath, tendon diameter, politicization of tendon and tendon local curvature. The validity of the correlation was confirmed by several published measured data. The structural analysis of middle cylinder part of 1/4 PCCV (Prestressed Concrete Containment Vessel) model was conducted using the present friction coefficient correlation. The results were compared with the analysis using constant friction coefficient, focused on the tendon tension force distribution. (author)

High genetic diversity and fine-scale spatial structure in the marine flagellate Oxyrrhis marina (Dinophyceae uncovered by microsatellite loci.

Directory of Open Access Journals (Sweden)

Chris D Lowe

2010-12-01

Full Text Available Free-living marine protists are often assumed to be broadly distributed and genetically homogeneous on large spatial scales. However, an increasing application of highly polymorphic genetic markers (e.g., microsatellites has provided evidence for high genetic diversity and population structuring on small spatial scales in many free-living protists. Here we characterise a panel of new microsatellite markers for the common marine flagellate Oxyrrhis marina. Nine microsatellite loci were used to assess genotypic diversity at two spatial scales by genotyping 200 isolates of O. marina from 6 broad geographic regions around Great Britain and Ireland; in one region, a single 2 km shore line was sampled intensively to assess fine-scale genetic diversity. Microsatellite loci resolved between 1-6 and 7-23 distinct alleles per region in the least and most variable loci respectively, with corresponding variation in expected heterozygosities (H(e of 0.00-0.30 and 0.81-0.93. Across the dataset, genotypic diversity was high with 183 genotypes detected from 200 isolates. Bayesian analysis of population structure supported two model populations. One population was distributed across all sampled regions; the other was confined to the intensively sampled shore, and thus two distinct populations co-occurred at this site. Whilst model-based analysis inferred a single UK-wide population, pairwise regional F(ST values indicated weak to moderate population sub-division (0.01-0.12, but no clear correlation between spatial and genetic distance was evident. Data presented in this study highlight extensive genetic diversity for O. marina; however, it remains a substantial challenge to uncover the mechanisms that drive genetic diversity in free-living microorganisms.

Protein structure similarity from principle component correlation analysis

Directory of Open Access Journals (Sweden)

Chou James

2006-01-01

Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

Using Text Mining to Uncover Students' Technology-Related Problems in Live Video Streaming

Science.gov (United States)

Abdous, M'hammed; He, Wu

2011-01-01

Because of their capacity to sift through large amounts of data, text mining and data mining are enabling higher education institutions to reveal valuable patterns in students' learning behaviours without having to resort to traditional survey methods. In an effort to uncover live video streaming (LVS) students' technology related-problems and to…

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

International Nuclear Information System (INIS)

Wang Shijun; Yao Jianhua; Liu Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.

2009-01-01

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.

Correlation analysis for forced vibration test of the Hualien large scale seismic test (LSST) program

International Nuclear Information System (INIS)

Sugawara, Y.; Sugiyama, T.; Kobayashi, T.; Yamaya, H.; Kitamura, E.

1995-01-01

The correlation analysis for a forced vibration test of a 1/4-scale containment SSI test model constructed in Hualien, Taiwan was carried out for the case of after backfilling. Prior to this correlation analysis, the structural properties were revised to adjust the calculated fundamental frequency in the fixed base condition to that derived from the test results. A correlation analysis was carried out using the Lattice Model which was able to estimate the soil-structure effects with embedment. The analysis results coincide well with test results and it is concluded that the mathematical soil-structure interaction model established by the correlation analysis is efficient in estimating the dynamic soil-structure interaction effect with embedment. This mathematical model will be applied as a basic model for simulation analysis of earthquake observation records. (author). 3 refs., 12 figs., 2 tabs

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

Science.gov (United States)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

Use of fuel failure correlations in accident analysis

International Nuclear Information System (INIS)

O'Dell, L.D.; Baars, R.E.; Waltar, A.E.

1975-05-01

The MELT-III code for analysis of a Transient Overpower (TOP) accident in an LMFBR is briefly described, including failure criteria currently applied in the code. Preliminary results of calculations exploring failure patterns in time and space in the reactor core are reported and compared for the two empirical fuel failure correlations employed in the code. (U.S.)

76 FR 4290 - Uncovered Innerspring Units From the People's Republic of China: Final Results of First...

Science.gov (United States)

2011-01-25

... Avenue, NW., Washington, DC 20230; telephone: (202) 482-1655. Case History With the issuance of the... material and then glued together in a linear fashion. Uncovered innersprings are classified under...

Multiset Canonical Correlations Analysis and Multispectral, Truly Multitemporal Remote Sensing Data

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg

2002-01-01

This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multi-source, multiset or multi-temporal exploratory data analysis. These techniques transform multivariate multiset data into new orthogonal variables called canonical variates (CVs) which when applied...... in remote sensing exhibit ever decreasing similarity (as expressed by correlation measures) over sets consisting of 1) spectral variables at fixed points in time (R-mode analysis), or 2) temporal variables with fixed wavelengths (T-mode analysis). The CVs are invariant to linear and affine transformations...... of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device. In a case study CVs are calculated from Landsat TM data with six spectral bands over six consecutive years. Both R- and T-mode CVs clearly exhibit...

Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

Directory of Open Access Journals (Sweden)

Rupert Faltermeier

2015-01-01

Full Text Available Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

Science.gov (United States)

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

System Reliability Analysis Considering Correlation of Performances

Energy Technology Data Exchange (ETDEWEB)

Kim, Saekyeol; Lee, Tae Hee [Hanyang Univ., Seoul (Korea, Republic of); Lim, Woochul [Mando Corporation, Seongnam (Korea, Republic of)

2017-04-15

Reliability analysis of a mechanical system has been developed in order to consider the uncertainties in the product design that may occur from the tolerance of design variables, uncertainties of noise, environmental factors, and material properties. In most of the previous studies, the reliability was calculated independently for each performance of the system. However, the conventional methods cannot consider the correlation between the performances of the system that may lead to a difference between the reliability of the entire system and the reliability of the individual performance. In this paper, the joint probability density function (PDF) of the performances is modeled using a copula which takes into account the correlation between performances of the system. The system reliability is proposed as the integral of joint PDF of performances and is compared with the individual reliability of each performance by mathematical examples and two-bar truss example.

System Reliability Analysis Considering Correlation of Performances

International Nuclear Information System (INIS)

Kim, Saekyeol; Lee, Tae Hee; Lim, Woochul

2017-01-01

Reliability analysis of a mechanical system has been developed in order to consider the uncertainties in the product design that may occur from the tolerance of design variables, uncertainties of noise, environmental factors, and material properties. In most of the previous studies, the reliability was calculated independently for each performance of the system. However, the conventional methods cannot consider the correlation between the performances of the system that may lead to a difference between the reliability of the entire system and the reliability of the individual performance. In this paper, the joint probability density function (PDF) of the performances is modeled using a copula which takes into account the correlation between performances of the system. The system reliability is proposed as the integral of joint PDF of performances and is compared with the individual reliability of each performance by mathematical examples and two-bar truss example.

Correlation analysis between ceramic insulator pollution and acoustic emissions

Directory of Open Access Journals (Sweden)

Benjamín Álvarez-Nasrallah

2015-01-01

Full Text Available Most of the studies related to insulator pollution are normally performed based on individual analysis among leakage current, relative humidity and equivalent salt deposit density (ESDD. This paper presents a correlation analysis between the leakage current and the acoustic emissions measured in a 230 kV electrical substations in the city of Barranquilla, Colombia. Furthermore, atmospheric variables were considered to develop a characterization model of the insulator contamination process. This model was used to demonstrate that noise emission levels are a reliable indicator to detect and characterize pollution on high voltage insulators. The correlation found amount the atmospheric, electrical and sound variables allowed to determine the relations for the maintenance of ceramic insulators in high-polluted areas. In this article, the results on the behavior of the leakage current in ceramic insulators and the sound produced with different atmospheric conditions are shown, which allow evaluating the best time to clean the insulator at the substation. Furthermore, by experimentation on site and using statistical models, the correlation between ambient variables and the leakage current of insulators in an electrical substation was obtained. Some of the problems that bring the external noise were overcome using multiple microphones and specialized software that enabled properly filter the sound and better measure the variables.

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

Science.gov (United States)

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Partially covered versus uncovered self-expandable nitinol stents with anti-migration properties for the palliation of malignant distal biliary obstruction: A randomized controlled trial.

Science.gov (United States)

Yang, Min Jae; Kim, Jin Hong; Yoo, Byung Moo; Hwang, Jae Chul; Yoo, Jun Hwan; Lee, Ki Seong; Kang, Joon Koo; Kim, Soon Sun; Lim, Sun Gyo; Shin, Sung Jae; Cheong, Jae Youn; Lee, Kee Myung; Lee, Kwang Jae; Cho, Sung Won

2015-01-01

Covered self-expandable metal stents (SEMSs) are increasingly used as alternatives to uncovered SEMSs for the palliation of inoperable malignant distal biliary obstruction to counteract tumor ingrowth. We aimed to compare the outcomes of partially covered and uncovered SEMSs with identical mesh structures and anti-migration properties, such as low axial force and flared ends. One hundred and three patients who were diagnosed with inoperable malignant distal biliary obstruction between January 2006 and August 2013 were randomly assigned to either the partially covered (n = 51) or uncovered (n = 52) SEMS group. There were no significant differences in the cumulative stent patency, overall patient survival, stent dysfunction-free survival and overall adverse events, including pancreatitis and cholecystitis, between the two groups. Compared to the uncovered group, stent migration (5.9% vs. 0%, p = 0.118) and tumor overgrowth (7.8% vs. 1.9%, p = 0.205) were non-significantly more frequent in the partially covered group, whereas tumor ingrowth showed a significantly higher incidence in the uncovered group (5.9% vs. 19.2%, p = 0.041). Stent migration in the partially covered group occurred only in patients with short stenosis of the utmost distal bile duct (two in ampullary cancer, one in bile duct cancer), and did not occur in any patients with pancreatic cancer. For the palliation of malignant distal biliary obstruction, endoscopic placement of partially covered SEMSs with anti-migration designs and identical mesh structures to uncovered SEMSs failed to prolong cumulative stent patency or reduce stent migration.

Cross-Correlations between Energy and Emissions Markets: New Evidence from Fractal and Multifractal Analysis

Directory of Open Access Journals (Sweden)

Gang-Jin Wang

2014-01-01

Full Text Available We supply a new perspective to describe and understand the behavior of cross-correlations between energy and emissions markets. Namely, we investigate cross-correlations between oil and gas (Oil-Gas, oil and CO2 (Oil-CO2, and gas and CO2 (Gas-CO2 based on fractal and multifractal analysis. We focus our study on returns of the oil, gas, and CO2 during the period of April 22, 2005–April 30, 2013. In the empirical analysis, by using the detrended cross-correlation analysis (DCCA method, we find that cross-correlations for Oil-Gas, Oil-CO2, and Gas-CO2 obey a power-law and are weakly persistent. Then, we adopt the method of DCCA cross-correlation coefficient to quantify cross-correlations between energy and emissions markets. The results show that their cross-correlations are diverse at different time scales. Next, based on the multifractal DCCA method, we find that cross-correlated markets have the nonlinear and multifractal nature and that the multifractality strength for three cross-correlated markets is arranged in the order of Gas-CO2 > Oil-Gas > Oil-CO2. Finally, by employing the rolling windows method, which can be used to investigate time-varying cross-correlation scaling exponents, we analyze short-term and long-term market dynamics and find that the recent global financial crisis has a notable influence on short-term and long-term market dynamics.

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

Science.gov (United States)

Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

Community Mapping in Action: Uncovering Resources and Assets for Young Children and Their Families

Science.gov (United States)

Ordonez-Jasis, Rosario; Myck-Wayne, Janice

2012-01-01

Community mapping is a promising practice that can assist early intervention/early childhood special education (EI/ECSE) professionals uncover the depth and diversity of community needs, resources, and learning opportunities, in the neighborhoods surrounding their schools. Community mapping is an inquiry-based method that situates learning in the…

Biallelic mutations in the 3' exonuclease TOE1 cause pontocerebellar hypoplasia and uncover a role in snRNA processing

DEFF Research Database (Denmark)

Lardelli, Rea M.; Schaffer, Ashleigh E.; Eggens, Veerle R C

2017-01-01

) is a unique recessive syndrome characterized by neurodegeneration and ambiguous genitalia. We studied 12 human families with PCH7, uncovering biallelic, loss-of-function mutations in TOE1, which encodes an unconventional deadenylase. toe1-morphant zebrafish displayed midbrain and hindbrain degeneration...... of TOE1 accumulated 3'-end-extended pre-snRNAs, and the immunoisolated TOE1 complex was sufficient for 3'-end maturation of snRNAs. Our findings identify the cause of a neurodegenerative syndrome linked to snRNA maturation and uncover a key factor involved in the processing of snRNA 3' ends....

The Neural Correlates of Moral Thinking: A Meta-Analysis

OpenAIRE

Douglas J. Bryant; Wang F; Kelley Deardeuff; Emily Zoccoli; Chang S. Nam

2016-01-01

We conducted a meta-analysis to evaluate current research that aims to map the neural correlates of two typical conditions of moral judgment: right-wrong moral judgments and decision-making in moral dilemmas. Utilizing the activation likelihood estimation (ALE) method, we conducted a meta-analysis using neuroimaging data obtained from twenty-one previous studies that measured responses in one or the other of these conditions. We found that across the studies (n = 400), distinct neural circuit...

Comparative analysis of heat transfer correlations for forced convection boiling

International Nuclear Information System (INIS)

Guglielmini, G.; Nannei, E.; Pisoni, C.

1978-01-01

A critical survey was conducted of the most relevant correlations of boiling heat transfer in forced convection flow. Most of the investigations carried out on partial nucleate boiling and fully developed nucleate boiling have led to the formulation of correlations that are not able to cover a wide range of operating conditions, due to the empirical approach of the problem. A comparative analysis is therefore required in order to delineate the relative accuracy of the proposed correlations, on the basis of the experimental data presently available. The survey performed allows the evaluation of the accuracy of the different calculating procedure; the results obtained, moreover, indicate the most reliable heat transfer correlations for the different operating conditions investigated. This survey was developed for five pressure range (up to 180bar) and for both saturation and subcooled boiling condition

Uncovering client retention antecedents in service organizations

Directory of Open Access Journals (Sweden)

Mari Jansen van Rensburg

2014-01-01

Full Text Available This paper develops a multi-dimensional model of retention to provide a more complete and integrated view of client retention and its determinants in service contexts. To uncover the antecedents of client retention, social and economic exchanges were reviewed under the fundamental ideas of the Social Exchange Theory. Findings from a survey of senior South African advertising executives suggest that client retention is the result of evaluative as well as relational factors that can influence client responses. Despite contractual obligations, advertisers are willing to pay the costs and make the sacrifices of switching should their expectations be unmet. An important contribution of this study is the use of multi-item scales to measure retention. The model developed provides valuable insight to agencies on client retention management and the optimal allocation of resources for maximum customer equity. This model may also be applied to other service organisations to provide insight to client retention.

Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index

Science.gov (United States)

Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng

2017-02-01

In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.

Correlation dimension based nonlinear analysis of network traffics with different application protocols

International Nuclear Information System (INIS)

Wang Jun-Song; Yuan Jing; Li Qiang; Yuan Rui-Xi

2011-01-01

This paper uses a correlation dimension based nonlinear analysis approach to analyse the dynamics of network traffics with three different application protocols—HTTP, FTP and SMTP. First, the phase space is reconstructed and the embedding parameters are obtained by the mutual information method. Secondly, the correlation dimensions of three different traffics are calculated and the results of analysis have demonstrated that the dynamics of the three different application protocol traffics is different from each other in nature, i.e. HTTP and FTP traffics are chaotic, furthermore, the former is more complex than the later; on the other hand, SMTP traffic is stochastic. It is shown that correlation dimension approach is an efficient method to understand and to characterize the nonlinear dynamics of HTTP, FTP and SMTP protocol network traffics. This analysis provided insight into and a more accurate understanding of nonlinear dynamics of internet traffics which have a complex mixture of chaotic and stochastic components. (general)

Empirical analysis of online human dynamics

Science.gov (United States)

Zhao, Zhi-Dan; Zhou, Tao

2012-06-01

Patterns of human activities have attracted increasing academic interests, since the quantitative understanding of human behavior is helpful to uncover the origins of many socioeconomic phenomena. This paper focuses on behaviors of Internet users. Six large-scale systems are studied in our experiments, including the movie-watching in Netflix and MovieLens, the transaction in Ebay, the bookmark-collecting in Delicious, and the posting in FreindFeed and Twitter. Empirical analysis reveals some common statistical features of online human behavior: (1) The total number of user's actions, the user's activity, and the interevent time all follow heavy-tailed distributions. (2) There exists a strongly positive correlation between user's activity and the total number of user's actions, and a significantly negative correlation between the user's activity and the width of the interevent time distribution. We further study the rescaling method and show that this method could to some extent eliminate the different statistics among users caused by the different activities, yet the effectiveness depends on the data sets.

Correlation of Descriptive Analysis and Instrumental Puncture Testing of Watermelon Cultivars.

Science.gov (United States)

Shiu, J W; Slaughter, D C; Boyden, L E; Barrett, D M

2016-06-01

The textural properties of 5 seedless watermelon cultivars were assessed by descriptive analysis and the standard puncture test using a hollow probe with increased shearing properties. The use of descriptive analysis methodology was an effective means of quantifying watermelon sensory texture profiles for characterizing specific cultivars' characteristics. Of the 10 cultivars screened, 71% of the variation in the sensory attributes was measured using the 1st 2 principal components. Pairwise correlation of the hollow puncture probe and sensory parameters determined that initial slope, maximum force, and work after maximum force measurements all correlated well to the sensory attributes crisp and firm. These findings confirm that maximum force correlates well with not only firmness in watermelon, but crispness as well. The initial slope parameter also captures the sensory crispness of watermelon, but is not as practical to measure in the field as maximum force. The work after maximum force parameter is thought to reflect cellular arrangement and membrane integrity that in turn impact sensory firmness and crispness. Watermelon cultivar types were correctly predicted by puncture test measurements in heart tissue 87% of the time, although descriptive analysis was correct 54% of the time. © 2016 Institute of Food Technologists®

A study on the effect of the CHF correlations to the LOCA analysis

International Nuclear Information System (INIS)

Kim, Ho Kee

1998-02-01

The critical heat flux (CHF) is a major parameter which determines the cooling performance and therefore the prediction of CHF is of importance for the design and safety analysis in boiling systems; such as nuclear reactors, conventional boilers, and other various two-phase flow systems. Until now, many CHF correlations have been developed and for the actual design a correlation has been selected in consideration of its characteristics. For the analysis of Loss of Coolant Accident (LOCA) in a Nuclear Power Plant, which shows the drastic parameters change during the system transient, a correlation having a reasonable degree of accuracy over a wide range is preferred, rather than that having accuracy for a specific range. It is required to have tangible insight about the effects of the CHF correlation to the LOCA analysis for the purpose of computer code development and nuclear regulation. The related research is further recommended. The purpose of this research is to obtain an insight and/or intuition about the above effect and to evaluate the selected CHF correlations. To achieve these purposes LOCA is analysed for the UL-JIN 3 and 4 nuclear power plant, the Korea Standard Type Nuclear Power Plant and the Loss of Flow Test (LOFT) L2-5 experiment is simulated using the RELAP5/MOD3.1 computer code for each selected CHF correlation. The selected correlations are the AECL-UO Lookup Table, adapted in RELAP5 code; the K110 CHF correlation, developed by KAERI; and the original W-3 CHF correlation, developed by L.S. Tong. LOFT is also simulated using the AECL-UO Lookup Table having the CHF multiplication factors 0.5 and 1.5, and then compared with the result of the original Lookup Table and the experiment result. In the LOCA analysis, the CHF correlations affect the magnitude of peak cladding temperatures, but does not seriously affect the occurrence points of time. The effect of each CHF correlation to the fuel cladding temperature behavior becomes apparent at the end of

Sieve analysis in HIV-1 vaccine efficacy trials.

Science.gov (United States)

Edlefsen, Paul T; Gilbert, Peter B; Rolland, Morgane

2013-09-01

The genetic characterization of HIV-1 breakthrough infections in vaccine and placebo recipients offers new ways to assess vaccine efficacy trials. Statistical and sequence analysis methods provide opportunities to mine the mechanisms behind the effect of an HIV vaccine. The release of results from two HIV-1 vaccine efficacy trials, Step/HVTN-502 (HIV Vaccine Trials Network-502) and RV144, led to numerous studies in the last 5 years, including efforts to sequence HIV-1 breakthrough infections and compare viral characteristics between the vaccine and placebo groups. Novel genetic and statistical analysis methods uncovered features that distinguished founder viruses isolated from vaccinees from those isolated from placebo recipients, and identified HIV-1 genetic targets of vaccine-induced immune responses. Studies of HIV-1 breakthrough infections in vaccine efficacy trials can provide an independent confirmation to correlates of risk studies, as they take advantage of vaccine/placebo comparisons, whereas correlates of risk analyses are limited to vaccine recipients. Through the identification of viral determinants impacted by vaccine-mediated host immune responses, sieve analyses can shed light on potential mechanisms of vaccine protection.

Correlation function analysis of the COBE differential microwave radiometer sky maps

Energy Technology Data Exchange (ETDEWEB)

Lineweaver, Charles Howe [Univ. of California, Berkeley, CA (United States). Space Sciences Lab.

1994-08-01

The Differential Microwave Radiometer (DMR) aboard the COBE satellite has detected anisotropies in the cosmic microwave background (CMB) radiation. A two-point correlation function analysis which helped lead to this discovery is presented in detail. The results of a correlation function analysis of the two year DMR data set is presented. The first and second year data sets are compared and found to be reasonably consistent. The positive correlation for separation angles less than ~20° is robust to Galactic latitude cuts and is very stable from year to year. The Galactic latitude cut independence of the correlation function is strong evidence that the signal is not Galactic in origin. The statistical significance of the structure seen in the correlation function of the first, second and two year maps is respectively > 9σ, > 10σ and > 18σ above the noise. The noise in the DMR sky maps is correlated at a low level. The structure of the pixel temperature covariance matrix is given. The noise covariance matrix of a DMR sky map is diagonal to an accuracy of better than 1%. For a given sky pixel, the dominant noise covariance occurs with the ring of pixels at an angular separation of 60° due to the 60° separation of the DMR horns. The mean covariance of 60° is 0.45%$+0.18\\atop{-0.14}$ of the mean variance. The noise properties of the DMR maps are thus well approximated by the noise properties of maps made by a single-beam experiment. Previously published DMR results are not significantly affected by correlated noise.

Time Correlations of Lightning Flash Sequences in Thunderstorms Revealed by Fractal Analysis

Science.gov (United States)

Gou, Xueqiang; Chen, Mingli; Zhang, Guangshu

2018-01-01

By using the data of lightning detection and ranging system at the Kennedy Space Center, the temporal fractal and correlation of interevent time series of lightning flash sequences in thunderstorms have been investigated with Allan factor (AF), Fano factor (FF), and detrended fluctuation analysis (DFA) methods. AF, FF, and DFA methods are powerful tools to detect the time-scaling structures and correlations in point processes. Totally 40 thunderstorms with distinguishing features of a single-cell storm and apparent increase and decrease in the total flash rate were selected for the analysis. It is found that the time-scaling exponents for AF (αAF) and FF (αFF) analyses are 1.62 and 0.95 in average, respectively, indicating a strong time correlation of the lightning flash sequences. DFA analysis shows that there is a crossover phenomenon—a crossover timescale (τc) ranging from 54 to 195 s with an average of 114 s. The occurrence of a lightning flash in a thunderstorm behaves randomly at timescales τc but shows strong time correlation at scales >τc. Physically, these may imply that the establishment of an extensive strong electric field necessary for the occurrence of a lightning flash needs a timescale >τc, which behaves strongly time correlated. But the initiation of a lightning flash within a well-established extensive strong electric field may involve the heterogeneities of the electric field at a timescale τc, which behave randomly.

Epistemically Virtuous Risk Management: Financial Due Diligence and Uncovering the Madoff Fraud

OpenAIRE

de Bruin, Boudewijn; Luetge, Christoph; Jauernig, Johanna

2014-01-01

The chapter analyses how Bernard Madoff’s Ponzi scheme was uncovered by Harry Markopolos, an employee of Rampart Investment Management, LLC, and the contribution of so-called epistemic virtues to Markopolos’ success. After Rampart had informed the firm about an allegedly highly successful hedge fund run by Madoff, Markopolos used qualitative and quantitative methods from financial due diligence to examine Madoff’s risks, returns and strategy, ultimately to conclude that Madoff was running a l...

78 FR 17635 - Uncovered Innerspring Units From the People's Republic of China: Final Results of Antidumping...

Science.gov (United States)

2013-03-22

... DEPARTMENT OF COMMERCE International Trade Administration [A-570-928] Uncovered Innerspring Units... AGENCY: Import Administration, International Trade Administration, Department of Commerce. SUMMARY: On... Operations, Office 9, Import Administration, International Trade Administration, U.S. Department of Commerce...

Correlated Topics in a Scalable Multidimensional Text Cube: Algorithms and Aviation Safety Case Study

Science.gov (United States)

Zhao, Bo; Lin, Cindy X.; Srivastava, Ashok N.; Oza, Nikunj C.; Han, Jiawei

2010-01-01

As world-wide air traffic continues to grow even at a modest pace, the overall complexity of the system will increase significantly. This increased complexity can lead to a larger number of fatalities per year even if the extremely low fatality rate that we currently enjoy is maintained. One important source of information about the safety of the aviation system is in Aviation Safety Text Reports which are written by members of the flight crew, air traffic controllers, and other parties involved with the aviation system. These anonymized narrative reports contain fixed-field contextual information about the flight but also contain free-form narratives that describe, in the author s own words, the nature of the safety incident and, in many cases, the contributing factors that led to the safety incident. Several thousand such reports are filed each month, each of which is read and analyzed by highly trained experts. However, it is possible that there are emerging safety issues due to the fact that they may be reported very infrequently and in different contexts with different descriptions. The goal of this research paper is to develop correlated topic models which uncover correlations in the subspaces defined by the intersection of numerous fixed fields and discovered correlated topics. This task requires the discovery of latent topics in the text reports and the creation of a topic cube. Furthermore, because the number of potential cells in the topic cube is very large, we discuss novel methods of pruning the search space in the topic cells, thereby making the analysis feasible. We demonstrate the new algorithms on an analysis of pilot fatigue and its contributing factors, as well as the safety incidents that are correlated with this phenomenon.

Variability, correlation and path coefficient analysis of seedling traits ...

African Journals Online (AJOL)

Indirect selection is a useful means for improving yield in cotton crop. The objective of the present study was to determine the genetic variability, broad sense heritability, genetic advance and correlation among the six seedling traits and their direct and indirect effects on cotton yield by using path coefficient analysis.

Evaluating the thermal and electrical performance of several uncovered PVT collectors with a field test

NARCIS (Netherlands)

de Keizer, C.; de Jong, M.; Mendes, T.; Katiyar, M.; Folkerts, W.; Rindt, C.C.M.; Zondag, H.A.

Recently, there has been a lot of interest in PV thermal systems, which generate both heat and power. Within the WenSDak project, several companies and research institutes work together to (further) develop several uncovered PVT collectors. The outdoor performance of prototypes of these collectors

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study.

Science.gov (United States)

Proescholdt, Martin A; Faltermeier, Rupert; Bele, Sylvia; Brawanski, Alexander

2017-01-01

Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

Directory of Open Access Journals (Sweden)

Martin A. Proescholdt

2017-01-01

Full Text Available Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca, correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp. In this study we compared the results of the sca with the pressure reactivity index (PRx, an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc. The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

Analytical X-ray line profile analysis based upon correlated dislocations

International Nuclear Information System (INIS)

Rao, S.; Houska, C.R.

1988-01-01

Recent advances describing X-ray line profiles analytically, in terms of a minimum number of parameters, are related to a theory based upon correlated dislocations. It is shown that a multiple convolution approach, based upon the Warren-Averbach (W-A) analysis, leads to a form that closely approximates the strain coefficient obtained by Krivoglaz, Martynenko and Ryaboshopka. This connection enables one to determine the dislocation density and the ratio of the correlation range parameter to the mean particle size. These two results are obtained most accurately from previous analytical approaches which make use of a statistical least-squares analysis. The W-A Fourier-series approach provides redundant information and does not focus on the critical parameters that relate to dislocation theory. Results so far are limited to b.c.c. materials. Results for cold-worked W, Mo, Nb, Cr and V are compared with highly imperfect sputtered films of Mo. A major difference is relatable to higher correlation of dislocations in cold-worked metals than is found in sputtered films deposited at low temperatures. However, in each case, the dislocation density is high. (orig.)

Uncovering growth-suppressive MicroRNAs in lung cancer

DEFF Research Database (Denmark)

Liu, Xi; Sempere, Lorenzo F; Galimberti, Fabrizio

2009-01-01

PURPOSE: MicroRNA (miRNA) expression profiles improve classification, diagnosis, and prognostic information of malignancies, including lung cancer. This study uncovered unique growth-suppressive miRNAs in lung cancer. EXPERIMENTAL DESIGN: miRNA arrays were done on normal lung tissues...... and adenocarcinomas from wild-type and proteasome degradation-resistant cyclin E transgenic mice to reveal repressed miRNAs in lung cancer. Real-time and semiquantitative reverse transcription-PCR as well as in situ hybridization assays validated these findings. Lung cancer cell lines were derived from each......-malignant human lung tissue bank. RESULTS: miR-34c, miR-145, and miR-142-5p were repressed in transgenic lung cancers. Findings were confirmed by real-time and semiquantitative reverse transcription-PCR as well as in situ hybridization assays. Similar miRNA profiles occurred in human normal versus malignant lung...

An improved method for bivariate meta-analysis when within-study correlations are unknown.

Science.gov (United States)

Hong, Chuan; D Riley, Richard; Chen, Yong

2018-03-01

Multivariate meta-analysis, which jointly analyzes multiple and possibly correlated outcomes in a single analysis, is becoming increasingly popular in recent years. An attractive feature of the multivariate meta-analysis is its ability to account for the dependence between multiple estimates from the same study. However, standard inference procedures for multivariate meta-analysis require the knowledge of within-study correlations, which are usually unavailable. This limits standard inference approaches in practice. Riley et al proposed a working model and an overall synthesis correlation parameter to account for the marginal correlation between outcomes, where the only data needed are those required for a separate univariate random-effects meta-analysis. As within-study correlations are not required, the Riley method is applicable to a wide variety of evidence synthesis situations. However, the standard variance estimator of the Riley method is not entirely correct under many important settings. As a consequence, the coverage of a function of pooled estimates may not reach the nominal level even when the number of studies in the multivariate meta-analysis is large. In this paper, we improve the Riley method by proposing a robust variance estimator, which is asymptotically correct even when the model is misspecified (ie, when the likelihood function is incorrect). Simulation studies of a bivariate meta-analysis, in a variety of settings, show a function of pooled estimates has improved performance when using the proposed robust variance estimator. In terms of individual pooled estimates themselves, the standard variance estimator and robust variance estimator give similar results to the original method, with appropriate coverage. The proposed robust variance estimator performs well when the number of studies is relatively large. Therefore, we recommend the use of the robust method for meta-analyses with a relatively large number of studies (eg, m≥50). When the

Correlates of Unwanted Births in Bangladesh: A Study through Path Analysis.

Science.gov (United States)

Roy, Tapan Kumar; Singh, Brijesh P

2016-01-01

Unwanted birth is an important public health concern due to its negative association with adverse outcomes of mothers and children as well as socioeconomic development of a country. Although a number of studies have been investigated the determinants of unwanted births through logistic regression analysis, an extensive assessment using path model is lacking. In the current study, we applied path analysis to know the important covariates for unwanted births in Bangladesh. The study used data extracted from Bangladesh Demographic and Health Survey (BDHS) 2011. It considered sub-sample consisted of 7,972 women who had given most recent births five years preceding the date of interview or who were currently pregnant at survey time. Correlation analysis was used to find out the significant association with unwanted births. This study provided the factors affecting unwanted births in Bangladesh. The path model was used to determine the direct, indirect and total effects of socio-demographic factors on unwanted births. The result exhibited that more than one-tenth of the recent births were unwanted in Bangladesh. The differentials of unwanted births were women's age, education, age at marriage, religion, socioeconomic status, exposure of mass-media and use of family planning. In correlation analysis, it showed that unwanted births were positively correlated with women age and place of residence and these relationships were significant. On the contrary, unwanted births were inversely significantly correlated with education and social status. The total effects of endogenous variables such as women age, place of residence and use of family planning methods had favorable effect on unwanted births. Policymakers and program planners need to design programs and services carefully to reduce unwanted births in Bangladesh, especially, service should focus on helping those groups of women who were identified in the analysis as being at increased risks of unwanted births- older women

Correlates of Unwanted Births in Bangladesh: A Study through Path Analysis.

Directory of Open Access Journals (Sweden)

Tapan Kumar Roy

Full Text Available Unwanted birth is an important public health concern due to its negative association with adverse outcomes of mothers and children as well as socioeconomic development of a country. Although a number of studies have been investigated the determinants of unwanted births through logistic regression analysis, an extensive assessment using path model is lacking. In the current study, we applied path analysis to know the important covariates for unwanted births in Bangladesh.The study used data extracted from Bangladesh Demographic and Health Survey (BDHS 2011. It considered sub-sample consisted of 7,972 women who had given most recent births five years preceding the date of interview or who were currently pregnant at survey time. Correlation analysis was used to find out the significant association with unwanted births. This study provided the factors affecting unwanted births in Bangladesh. The path model was used to determine the direct, indirect and total effects of socio-demographic factors on unwanted births.The result exhibited that more than one-tenth of the recent births were unwanted in Bangladesh. The differentials of unwanted births were women's age, education, age at marriage, religion, socioeconomic status, exposure of mass-media and use of family planning. In correlation analysis, it showed that unwanted births were positively correlated with women age and place of residence and these relationships were significant. On the contrary, unwanted births were inversely significantly correlated with education and social status. The total effects of endogenous variables such as women age, place of residence and use of family planning methods had favorable effect on unwanted births.Policymakers and program planners need to design programs and services carefully to reduce unwanted births in Bangladesh, especially, service should focus on helping those groups of women who were identified in the analysis as being at increased risks of unwanted

Linearized spectrum correlation analysis for line emission measurements.

Science.gov (United States)

Nishizawa, T; Nornberg, M D; Den Hartog, D J; Sarff, J S

2017-08-01

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

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Hesse Morten

2005-05-01

Full Text Available Abstract Background Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. Methods The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133, and (b a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. Results It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. Conclusion The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.

Long-range correlation analysis of urban traffic data

International Nuclear Information System (INIS)

Peng, Sheng; Jun-Feng, Wang; Shu-Long, Zhao; Tie-Qiao, Tang

2010-01-01

This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discusses the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by the obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions (vehicles with special numbered plates only run in a special workday) enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation. (general)

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

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Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

Antisocial behaviour and psychopathy: Uncovering the externalizing link in the P3 modulation.

Science.gov (United States)

Pasion, Rita; Fernandes, Carina; Pereira, Mariana R; Barbosa, Fernando

2017-03-22

In 2009, Gao and Raine's meta-analysis analysed P3 modulation over the antisocial spectrum. However, some questions remained open regarding the P3 modulation patterns across impulsive and violent manifestations of antisocial behaviour, phenotypic components of psychopathy, and P3 components. A systematic review of 36 studies was conducted (N=3514) to extend previous results and to address these unresolved questions. A clear link between decreased P3 amplitude and antisocial behaviour was found. In psychopathy, dimensional approaches become more informative than taxonomic models. Distinct etiological pathways of psychopathy were evidenced in cognitive tasks: impulsive-antisocial psychopathic traits mainly predicted blunted P3 amplitude, while interpersonal-affective psychopathic traits explained enhanced P3 amplitude. Supporting the low fear hypothesis, the interpersonal-affective traits were associated with reduced P3 amplitude in emotional-affective learning tasks. From the accumulated knowledge we propose a framework of P3 amplitude modulation that uncovers the externalizing link between psychopathy and antisocial behaviour. However, the main hypotheses are exploratory and call for more data before stablishing robust conclusions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparative genomics of Beauveria bassiana: uncovering signatures of virulence against mosquitoes.

Science.gov (United States)

Valero-Jiménez, Claudio A; Faino, Luigi; Spring In't Veld, Daphne; Smit, Sandra; Zwaan, Bas J; van Kan, Jan A L

2016-12-01

Entomopathogenic fungi such as Beauveria bassiana are promising biological agents for control of malaria mosquitoes. Indeed, infection with B. bassiana reduces the lifespan of mosquitoes in the laboratory and in the field. Natural isolates of B. bassiana show up to 10-fold differences in virulence between the most and the least virulent isolate. In this study, we sequenced the genomes of five isolates representing the extremes of low/high virulence and three RNA libraries, and applied a genome comparison approach to uncover genetic mechanisms underpinning virulence. A high-quality, near-complete genome assembly was achieved for the highly virulent isolate Bb8028, which was compared to the assemblies of the four other isolates. Whole genome analysis showed a high level of genetic diversity between the five isolates (2.85-16.8 SNPs/kb), which grouped into two distinct phylogenetic clusters. Mating type gene analysis revealed the presence of either the MAT1-1-1 or the MAT1-2-1 gene. Moreover, a putative new MAT gene (MAT1-2-8) was detected in the MAT1-2 locus. Comparative genome analysis revealed that Bb8028 contains 163 genes exclusive for this isolate. These unique genes have a tendency to cluster in the genome and to be often located near the telomeres. Among the genes unique to Bb8028 are a Non-Ribosomal Peptide Synthetase (NRPS) secondary metabolite gene cluster, a polyketide synthase (PKS) gene, and five genes with homology to bacterial toxins. A survey of candidate virulence genes for B. bassiana is presented. Our results indicate several genes and molecular processes that may underpin virulence towards mosquitoes. Thus, the genome sequences of five isolates of B. bassiana provide a better understanding of the natural variation in virulence and will offer a major resource for future research on this important biological control agent.

Uncovering phenotypes of poor-pitch singing: the Sung Performance Battery (SPB)

Science.gov (United States)

Berkowska, Magdalena; Dalla Bella, Simone

2013-01-01

Singing is as natural as speaking for humans. Increasing evidence shows that the layman can carry a tune (e.g., when asked to sing a well-known song or to imitate single pitches, intervals and short melodies). Yet, important individual differences exist in the general population with regard to singing proficiency. Some individuals are particularly inaccurate or imprecise in producing or imitating pitch information (poor-pitch singers), thus showing a variety of singing phenotypes. Unfortunately, so far there is not a standard set of tasks for assessing singing proficiency in the general population, allowing to uncover and characterize individual profiles of poor-pitch singing. Different tasks and analysis methods are typically used in various experiments, making the comparison of the results across studies arduous. To fill this gap we propose here a new tool for assessing singing proficiency (the Sung Performance Battery, SPB). The SPB starts from the assessment of participants' vocal range followed by five tasks: (1) single-pitch matching, (2) pitch-interval matching, (3) novel-melody matching, (4) singing from memory of familiar melodies (with lyrics and on a syllable), and (5) singing of familiar melodies (with lyrics and on a syllable) at a slow tempo indicated by a metronome. Data analysis via acoustical methods provides objective measures of pitch accuracy and precision in terms of absolute and relative pitch. The SPB has been tested in a group of 50 occasional singers. The results indicate that the battery is useful for characterizing proficient singing and for detecting cases of inaccurate and/or imprecise singing. PMID:24151475

Uncovering highly obfuscated plagiarism cases using fuzzy semantic-based similarity model

Directory of Open Access Journals (Sweden)

Salha M. Alzahrani

2015-07-01

Full Text Available Highly obfuscated plagiarism cases contain unseen and obfuscated texts, which pose difficulties when using existing plagiarism detection methods. A fuzzy semantic-based similarity model for uncovering obfuscated plagiarism is presented and compared with five state-of-the-art baselines. Semantic relatedness between words is studied based on the part-of-speech (POS tags and WordNet-based similarity measures. Fuzzy-based rules are introduced to assess the semantic distance between source and suspicious texts of short lengths, which implement the semantic relatedness between words as a membership function to a fuzzy set. In order to minimize the number of false positives and false negatives, a learning method that combines a permission threshold and a variation threshold is used to decide true plagiarism cases. The proposed model and the baselines are evaluated on 99,033 ground-truth annotated cases extracted from different datasets, including 11,621 (11.7% handmade paraphrases, 54,815 (55.4% artificial plagiarism cases, and 32,578 (32.9% plagiarism-free cases. We conduct extensive experimental verifications, including the study of the effects of different segmentations schemes and parameter settings. Results are assessed using precision, recall, F-measure and granularity on stratified 10-fold cross-validation data. The statistical analysis using paired t-tests shows that the proposed approach is statistically significant in comparison with the baselines, which demonstrates the competence of fuzzy semantic-based model to detect plagiarism cases beyond the literal plagiarism. Additionally, the analysis of variance (ANOVA statistical test shows the effectiveness of different segmentation schemes used with the proposed approach.

Uncovering phenotypes of poor-pitch singing: The Sung Performance Battery (SPB

Directory of Open Access Journals (Sweden)

Magdalena eBerkowska

2013-10-01

Full Text Available Singing is as natural as speaking for humans. Increasing evidence shows that the layman can carry a tune (e.g., when asked to sing a well-known song or to imitate single pitches, intervals and short melodies. Yet, important individual differences exist in the general population with regard to singing proficiency. Some individuals are particularly inaccurate or imprecise in producing or imitating pitch information (poor-pitch singers, thus showing a variety of singing phenotypes. Unfortunately, so far there is not a standard set of tasks for assessing singing proficiency in the general population, allowing to uncover and characterize individual profiles of poor-pitch singing. Different tasks and analysis methods are typically used in various experiments, making the comparison of the results across studies arduous. To fill this gap we propose here a new tool for assessing singing proficiency (the Sung Performance Battery, SPB. The SPB starts from the assessment of participants’ vocal range followed by five tasks: 1 single-pitch matching, 2 pitch-interval matching, 3 novel-melody matching, 4 singing from memory of familiar melodies (with lyrics and on a syllable, and 5 singing of familiar melodies (with lyrics and on a syllable at a slow tempo indicated by a metronome. Data analysis via acoustical methods provides objective measures of pitch accuracy and precision in terms of absolute and relative pitch. The SPB has been tested in a group of 50 occasional singers. The results indicate that the battery is useful for characterizing proficient singing and for detecting cases of inaccurate and/or imprecise singing.

Correlates of perceived stigma for people living with epilepsy: A meta-analysis.

Science.gov (United States)

Shi, Ying; Wang, Shouqi; Ying, Jie; Zhang, Meiling; Liu, Pengcheng; Zhang, Huanhuan; Sun, Jiao

2017-05-01

Epilepsy, one of the most common, serious chronic neurological diseases, is accompanied by different levels of perceived stigma that affects people in almost all age groups. This stigma can negatively impact the physical and mental health of people living with epilepsy (PLWE). Good knowledge of perceived stigma for PLWE is important. In this study, we conducted a meta-analysis to identify the correlates of perceived stigma for PLWE. Studies on factors associated with perceived stigma for PLWE, including sociodemographic, psychosocial, and disease-related variables, were searched in PubMed, PsychINFO, EMBASE, and Web of Science. Nineteen variables (k>1) were included in the meta-analysis. For sociodemographic characteristics, findings revealed that the significant weighted mean correlation (R) for "residence" and "poor financial status" were 0.177 and 0.286, respectively. For disease-related characteristics, all variables of significance, including "seizure severity," "seizure frequency," "number of medicines," and "adverse event" (R ranging from 0.190 to 0.362), were positively correlated with perceived stigma. For psychosocial characteristics, "depression" and "anxiety" with R values of 0.414 and 0.369 were significantly associated with perceived stigma. In addition, "social support," "quality of life (QOLIE-31,89)," "knowledge," and "attitude," with R values ranging from -0.444 to -0.200 indicating negative correlation with perceived stigma. The current meta-analysis evaluated the correlates of perceived stigma for PLWE. Results can serve as a basis for policymakers and healthcare professionals for formulating health promotion and prevention strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

FEM correlation and shock analysis of a VNC MEMS mirror segment

Science.gov (United States)

Aguayo, Eduardo J.; Lyon, Richard; Helmbrecht, Michael; Khomusi, Sausan

2014-08-01

Microelectromechanical systems (MEMS) are becoming more prevalent in today's advanced space technologies. The Visible Nulling Coronagraph (VNC) instrument, being developed at the NASA Goddard Space Flight Center, uses a MEMS Mirror to correct wavefront errors. This MEMS Mirror, the Multiple Mirror Array (MMA), is a key component that will enable the VNC instrument to detect Jupiter and ultimately Earth size exoplanets. Like other MEMS devices, the MMA faces several challenges associated with spaceflight. Therefore, Finite Element Analysis (FEA) is being used to predict the behavior of a single MMA segment under different spaceflight-related environments. Finite Element Analysis results are used to guide the MMA design and ensure its survival during launch and mission operations. A Finite Element Model (FEM) has been developed of the MMA using COMSOL. This model has been correlated to static loading on test specimens. The correlation was performed in several steps—simple beam models were correlated initially, followed by increasingly complex and higher fidelity models of the MMA mirror segment. Subsequently, the model has been used to predict the dynamic behavior and stresses of the MMA segment in a representative spaceflight mechanical shock environment. The results of the correlation and the stresses associated with a shock event are presented herein.

Analysis of the influences of thermal correlations on neutronic–thermohydraulic coupling calculation of SCWR

International Nuclear Information System (INIS)

Xu, Weifeng; Cai, Jiejin; Liu, Shichang; Tang, Qi

2015-01-01

Highlights: • Different thermal correlations for supercritical water are summarized. • Influences of thermal correlations on neutronic–thermohydraulic coupling calculation are analyzed. • Sensitivity analysis has been done for the thermal correlations. - Abstract: The neutronic–thermohydraulic coupling (N–T coupling) calculation is important on core design, security and stability analysis of supercritical water-coolant reactor (SCWR), and a suitable thermal correlation is also necessary for the N–T coupling calculation. In this paper, the scheme of the U.S. SCWR design and the process of the N–T coupling will be introduced as well as some of different thermal correlations firstly. Then, based on the N–T coupling system ARNT, the U.S. SCWR design is simulated to analyze the influences of thermal correlations on N–T coupling calculation of SCWR so as to find out which correlation is best. The result shows that all thermal correlations are suitable. However, using different correlations for calculation leads to a great difference in safety margin of SCWR. What's more, the Bishop and Jackson correlations are more suitable and conservative, but the Griem correlation is not very precise. And the effect of buoyancy lift makes little influence on the calculation of heat transfer of SCWR. This research is also of great significance for the further study of N–T coupling of SCWR

Analysis of Cell Phone Usage Using Correlation Techniques

OpenAIRE

T S R MURTHY; D. SIVA RAMA KRISHNA

2011-01-01

The present paper is a sample survey analysis, examined based on correlation techniques. The usage ofmobile phones is clearly almost un-avoidable these days and as such the authors have made a systematicsurvey through a well prepared questionnaire on making use of mobile phones to the maximum extent.These samples are various economical groups across a population of over one-lakh people. The resultsare scientifically categorized and interpreted to match the ground reality.

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

Science.gov (United States)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

Neural Network-Based Coronary Heart Disease Risk Prediction Using Feature Correlation Analysis

Directory of Open Access Journals (Sweden)

Jae Kwon Kim

2017-01-01

Full Text Available Background. Of the machine learning techniques used in predicting coronary heart disease (CHD, neural network (NN is popularly used to improve performance accuracy. Objective. Even though NN-based systems provide meaningful results based on clinical experiments, medical experts are not satisfied with their predictive performances because NN is trained in a “black-box” style. Method. We sought to devise an NN-based prediction of CHD risk using feature correlation analysis (NN-FCA using two stages. First, the feature selection stage, which makes features acceding to the importance in predicting CHD risk, is ranked, and second, the feature correlation analysis stage, during which one learns about the existence of correlations between feature relations and the data of each NN predictor output, is determined. Result. Of the 4146 individuals in the Korean dataset evaluated, 3031 had low CHD risk and 1115 had CHD high risk. The area under the receiver operating characteristic (ROC curve of the proposed model (0.749 ± 0.010 was larger than the Framingham risk score (FRS (0.393 ± 0.010. Conclusions. The proposed NN-FCA, which utilizes feature correlation analysis, was found to be better than FRS in terms of CHD risk prediction. Furthermore, the proposed model resulted in a larger ROC curve and more accurate predictions of CHD risk in the Korean population than the FRS.

A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

International Nuclear Information System (INIS)

Shen, Chen-Hua

2015-01-01

To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

Energy Technology Data Exchange (ETDEWEB)

Shen, Chen-Hua, E-mail: shenandchen01@163.com [College of Geographical Science, Nanjing Normal University, Nanjing 210046 (China); Jiangsu Center for Collaborative Innovation in Geographical Information Resource, Nanjing 210046 (China); Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing 210046 (China)

2015-12-04

To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

Science.gov (United States)

Takaishi, Tetsuya

2016-08-01

We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, crosscorrelation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile.

Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2016-01-01

We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, crosscorrelation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile. (paper)

Uncovering the nutritional landscape of food.

Directory of Open Access Journals (Sweden)

Seunghyeon Kim

Full Text Available Recent progresses in data-driven analysis methods, including network-based approaches, are revolutionizing many classical disciplines. These techniques can also be applied to food and nutrition, which must be studied to design healthy diets. Using nutritional information from over 1,000 raw foods, we systematically evaluated the nutrient composition of each food in regards to satisfying daily nutritional requirements. The nutrient balance of a food was quantified and termed nutritional fitness; this measure was based on the food's frequency of occurrence in nutritionally adequate food combinations. Nutritional fitness offers a way to prioritize recommendable foods within a global network of foods, in which foods are connected based on the similarities of their nutrient compositions. We identified a number of key nutrients, such as choline and α-linolenic acid, whose levels in foods can critically affect the nutritional fitness of the foods. Analogously, pairs of nutrients can have the same effect. In fact, two nutrients can synergistically affect the nutritional fitness, although the individual nutrients alone may not have an impact. This result, involving the tendency among nutrients to exhibit correlations in their abundances across foods, implies a hidden layer of complexity when exploring for foods whose balance of nutrients within pairs holistically helps meet nutritional requirements. Interestingly, foods with high nutritional fitness successfully maintain this nutrient balance. This effect expands our scope to a diverse repertoire of nutrient-nutrient correlations, which are integrated under a common network framework that yields unexpected yet coherent associations between nutrients. Our nutrient-profiling approach combined with a network-based analysis provides a more unbiased, global view of the relationships between foods and nutrients, and can be extended towards nutritional policies, food marketing, and personalized nutrition.

Uncovering the Nutritional Landscape of Food

Science.gov (United States)

Kim, Seunghyeon; Sung, Jaeyun; Foo, Mathias; Jin, Yong-Su; Kim, Pan-Jun

2015-01-01

Recent progresses in data-driven analysis methods, including network-based approaches, are revolutionizing many classical disciplines. These techniques can also be applied to food and nutrition, which must be studied to design healthy diets. Using nutritional information from over 1,000 raw foods, we systematically evaluated the nutrient composition of each food in regards to satisfying daily nutritional requirements. The nutrient balance of a food was quantified and termed nutritional fitness; this measure was based on the food’s frequency of occurrence in nutritionally adequate food combinations. Nutritional fitness offers a way to prioritize recommendable foods within a global network of foods, in which foods are connected based on the similarities of their nutrient compositions. We identified a number of key nutrients, such as choline and α-linolenic acid, whose levels in foods can critically affect the nutritional fitness of the foods. Analogously, pairs of nutrients can have the same effect. In fact, two nutrients can synergistically affect the nutritional fitness, although the individual nutrients alone may not have an impact. This result, involving the tendency among nutrients to exhibit correlations in their abundances across foods, implies a hidden layer of complexity when exploring for foods whose balance of nutrients within pairs holistically helps meet nutritional requirements. Interestingly, foods with high nutritional fitness successfully maintain this nutrient balance. This effect expands our scope to a diverse repertoire of nutrient-nutrient correlations, which are integrated under a common network framework that yields unexpected yet coherent associations between nutrients. Our nutrient-profiling approach combined with a network-based analysis provides a more unbiased, global view of the relationships between foods and nutrients, and can be extended towards nutritional policies, food marketing, and personalized nutrition. PMID:25768022

76 FR 80337 - Uncovered Innerspring Units From the People's Republic of China: Rescission of Antidumping Duty...

Science.gov (United States)

2011-12-23

... fashion. Uncovered innersprings are classified under subheading 9404.29.9010, 9404.29.9005 and 9404.29... (``APO'') of their responsibility concerning the return or destruction of proprietary information... written notification of the return or destruction of APO materials or conversion to judicial protective...

Ionome changes in Xylella fastidiosa-infected Nicotiana tabacum correlate with virulence and discriminate between subspecies of bacterial isolates.

Science.gov (United States)

Oliver, J E; Sefick, S A; Parker, J K; Arnold, T; Cobine, P A; De La Fuente, L

2014-10-01

Characterization of ionomes has been used to uncover the basis of nutrient utilization and environmental adaptation of plants. Here, ionomic profiles were used to understand the phenotypic response of a plant to infection by genetically diverse isolates of Xylella fastidiosa, a gram-negative, xylem-limited bacterial plant pathogen. In this study, X. fastidiosa isolates were used to infect a common model host (Nicotiana tabacum 'SR1'), and leaf and sap concentrations of eleven elements together with plant colonization and symptoms were assessed. Multivariate statistical analysis revealed that changes in the ionome were significantly correlated with symptom severity and bacterial populations in host petioles. Moreover, plant ionome modification by infection could be used to differentiate the X. fastidiosa subspecies with which the plant was infected. This report establishes host ionome modification as a phenotypic response to infection.

Denial-of-service attack detection based on multivariate correlation analysis

NARCIS (Netherlands)

Tan, Zhiyuan; Jamdagni, Aruna; He, Xiangjian; Nanda, Priyadarsi; Liu, Ren Ping; Lu, Bao-Liang; Zhang, Liqing; Kwok, James

2011-01-01

The reliability and availability of network services are being threatened by the growing number of Denial-of-Service (DoS) attacks. Effective mechanisms for DoS attack detection are demanded. Therefore, we propose a multivariate correlation analysis approach to investigate and extract second-order

Local wavelet correlation: applicationto timing analysis of multi-satellite CLUSTER data

Directory of Open Access Journals (Sweden)

J. Soucek

2004-12-01

Full Text Available Multi-spacecraft space observations, such as those of CLUSTER, can be used to infer information about local plasma structures by exploiting the timing differences between subsequent encounters of these structures by individual satellites. We introduce a novel wavelet-based technique, the Local Wavelet Correlation (LWC, which allows one to match the corresponding signatures of large-scale structures in the data from multiple spacecraft and determine the relative time shifts between the crossings. The LWC is especially suitable for analysis of strongly non-stationary time series, where it enables one to estimate the time lags in a more robust and systematic way than ordinary cross-correlation techniques. The technique, together with its properties and some examples of its application to timing analysis of bow shock and magnetopause crossing observed by CLUSTER, are presented. We also compare the performance and reliability of the technique with classical discontinuity analysis methods. Key words. Radio science (signal processing – Space plasma physics (discontinuities; instruments and techniques

Volatility-constrained multifractal detrended cross-correlation analysis: Cross-correlation among Mainland China, US, and Hong Kong stock markets

Science.gov (United States)

Cao, Guangxi; Zhang, Minjia; Li, Qingchen

2017-04-01

This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.

Analysis of the Correlation between GDP and the Final Consumption

Directory of Open Access Journals (Sweden)

Constantin ANGHELACHE

2011-09-01

Full Text Available This paper presents the results of the researches performed by the author regarding the evolution of Gross Domestic Product. One of the main aspects of GDP analysis is the correlation with the final consumption, an important macroeconomic indicator. The evolution of the Gross Domestic Product is highly influenced by the evolution of the final consumption. To analyze the correlation, the paper proposes the use of the linear regression model, as one of the most appropriate instruments for such scientific approach. The regression model described in the article uses the GDP as resultant variable and the final consumption as factorial variable.

Climate Prediction Center(CPC)Ensemble Canonical Correlation Analysis Forecast of Temperature

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) temperature forecast is a 90-day (seasonal) outlook of US surface temperature anomalies. The ECCA uses Canonical...

The effects of observational correlated noises on multifractal detrended fluctuation analysis

Science.gov (United States)

Gulich, Damián; Zunino, Luciano

2012-08-01

We have numerically investigated the effects that observational correlated noises have on the generalized Hurst exponents, h(q), estimated by using the multifractal generalization of detrended fluctuation analysis (MF-DFA). More precisely, artificially generated stochastic binomial multifractals with increased amount of colored noises were analyzed via MF-DFA. It has been recently shown that for moderate additions of white noise, the generalized Hurst exponents are significantly underestimated for qeffects of additive noise, short- term memory and periodic trends, Physica A 390 (2011) 2480-2490]. In this paper, we have found that h(q) with q≥2 are also affected when correlated noises are considered. This is due to the fact that the spurious correlations influence the scaling behaviors associated to large fluctuations. The results obtained are significant for practical situations, where noises with different correlations are inherently present.

77 FR 21961 - Uncovered Innerspring Units From the People's Republic of China: Final Results and Final...

Science.gov (United States)

2012-04-12

... material and then glued together in a linear fashion. Uncovered innersprings are classified under... responsibility concerning the return or destruction of proprietary information disclosed under the APO, which... notification of the return/destruction of APO materials or conversion to judicial protective order is hereby...

Uncovering the Best Skill Multimap by Constraining the Error Probabilities of the Gain-Loss Model

Science.gov (United States)

Anselmi, Pasquale; Robusto, Egidio; Stefanutti, Luca

2012-01-01

The Gain-Loss model is a probabilistic skill multimap model for assessing learning processes. In practical applications, more than one skill multimap could be plausible, while none corresponds to the true one. The article investigates whether constraining the error probabilities is a way of uncovering the best skill assignment among a number of…

Groundwater travel time uncertainty analysis. Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

International Nuclear Information System (INIS)

Clifton, P.M.

1985-03-01

This study examines the sensitivity of the travel time distribution predicted by a reference case model to (1) scale of representation of the model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross correlations between transmissivity and effective thickness. The basis for the reference model is the preliminary stochastic travel time model previously documented by the Basalt Waste Isolation Project. Results of this study show the following. The variability of the predicted travel times can be adequately represented when the ratio between the size of the zones used to represent the model parameters and the log-transmissivity correlation range is less than about one-fifth. The size of the model domain and the types of boundary conditions can have a strong impact on the distribution of travel times. Longer log-transmissivity correlation ranges cause larger variability in the predicted travel times. Positive cross correlation between transmissivity and effective thickness causes a decrease in the travel time variability. These results demonstrate the need for a sound conceptual model prior to conducting a stochastic travel time analysis

The invisible Web uncovering information sources search engines can't see

CERN Document Server

Sherman, Chris

2001-01-01

Enormous expanses of the Internet are unreachable with standard web search engines. This book provides the key to finding these hidden resources by identifying how to uncover and use invisible web resources. Mapping the invisible Web, when and how to use it, assessing the validity of the information, and the future of Web searching are topics covered in detail. Only 16 percent of Net-based information can be located using a general search engine. The other 84 percent is what is referred to as the invisible Web-made up of information stored in databases. Unlike pages on the visible Web, informa

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

Science.gov (United States)

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

Correlation between weather and incidence of selected ophthalmological diagnoses: a database analysis

Directory of Open Access Journals (Sweden)

Kern C

2016-08-01

Full Text Available Christoph Kern, Karsten Kortüm, Michael Müller, Florian Raabe, Wolfgang Johann Mayer, Siegfried Priglinger, Thomas Christian Kreutzer University Eye Hospital Munich, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany Purpose: Our aim was to correlate the overall patient volume and the incidence of several ophthalmological diseases in our emergency department with weather data. Patients and methods: For data analysis, we used our clinical data warehouse and weather data. We investigated the weekly overall patient volume and the average weekly incidence of all encoded diagnoses of “conjunctivitis”, “foreign body”, “acute iridocyclitis”, and “corneal abrasion”. A Spearman’s correlation was performed to link these data with the weekly average sunshine duration, temperature, and wind speed. Results: We noticed increased patient volume in correlation with increasing sunshine duration and higher temperature. Moreover, we found a positive correlation between the weekly incidences of conjunctivitis and of foreign body and weather data. Conclusion: The results of this data analysis reveal the possible influence of external conditions on the health of a population and can be used for weather-dependent resource allocation. Keywords: corneal injury, trauma, uveitis, conjunctivitis, weather

Serum adiponectin levels are inversely correlated with leukemia: A meta-analysis

Directory of Open Access Journals (Sweden)

Jun-Jie Ma

2016-01-01

Conclusion: Our meta-analysis suggested that serum ADPN levels may be inversely correlated with leukemia, and ADPN levels can be used as an effective biologic marker in early diagnosis and therapeutic monitoring of leukemia.

The cross-correlation analysis of multi property of stock markets based on MM-DFA

Science.gov (United States)

Yang, Yujun; Li, Jianping; Yang, Yimei

2017-09-01

In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.

Resilience among caregivers of children with chronic conditions: a concept analysis.

Science.gov (United States)

Lin, Fang-Yi; Rong, Jiin-Ru; Lee, Tzu-Ying

2013-08-29

The purpose of this concept analysis is to uncover the essential elements involved in caregivers' resilience in the context of caring for children with chronic conditions. Walker and Avant's methodology guided the analysis. The study includes a literature review of conceptual definitions of caregiver resilience in caring for children with chronic conditions. The defining attributes and correlates of caregiver resilience are reviewed. Concept analysis findings in a review of the nursing and health-related literature show that caregiver resilience in the context of caring for chronically ill children can be defined within four main dimensions, ie, disposition patterns, situational patterns, relational patterns, and cultural patterns. Empiric measurements of the impact of caregiver resilience applied to caregivers with children with chronic conditions are also reported in the analysis. The findings of this concept analysis could help nurses and health care providers to apply the concept of caregiver resilience in allied health care and be applied to further studies.

Uncovering Listeria monocytogenes hypervirulence by harnessing its biodiversity

Science.gov (United States)

Charlier, Caroline; Touchon, Marie; Chenal-Francisque, Viviane; Leclercq, Alexandre; Criscuolo, Alexis; Gaultier, Charlotte; Roussel, Sophie; Brisabois, Anne; Disson, Olivier; Rocha, Eduardo P. C.; Brisse, Sylvain; Lecuit, Marc

2016-01-01

Microbial pathogenesis studies are typically performed with reference strains, thereby overlooking microbial intra-species virulence heterogeneity. Here we integrated human epidemiological and clinical data with bacterial population genomics to harness the biodiversity of the model foodborne pathogen Listeria monocytogenes and decipher the basis of its neural and placental tropisms. Taking advantage of the clonal structure of this bacterial species, we identify clones epidemiologically associated with either food or human central nervous system (CNS) and maternal-neonatal (MN) listeriosis. The latter are also most prevalent in patients without immunosuppressive comorbidities. Strikingly, CNS and MN clones are hypervirulent in a humanized mouse model of listeriosis. By integrating epidemiological data and comparative genomics, we uncovered multiple novel putative virulence factors and demonstrated experimentally the contribution of the first gene cluster mediating Listeria monocytogenes neural and placental tropisms. This study illustrates the exceptional power of harnessing microbial biodiversity to identify clinically relevant microbial virulence attributes. PMID:26829754

Low Carbon-Oriented Optimal Reliability Design with Interval Product Failure Analysis and Grey Correlation Analysis

Directory of Open Access Journals (Sweden)

Yixiong Feng

2017-03-01

Full Text Available The problem of large amounts of carbon emissions causes wide concern across the world, and it has become a serious threat to the sustainable development of the manufacturing industry. The intensive research into technologies and methodologies for green product design has significant theoretical meaning and practical value in reducing the emissions of the manufacturing industry. Therefore, a low carbon-oriented product reliability optimal design model is proposed in this paper: (1 The related expert evaluation information was prepared in interval numbers; (2 An improved product failure analysis considering the uncertain carbon emissions of the subsystem was performed to obtain the subsystem weight taking the carbon emissions into consideration. The interval grey correlation analysis was conducted to obtain the subsystem weight taking the uncertain correlations inside the product into consideration. Using the above two kinds of subsystem weights and different caution indicators of the decision maker, a series of product reliability design schemes is available; (3 The interval-valued intuitionistic fuzzy sets (IVIFSs were employed to select the optimal reliability and optimal design scheme based on three attributes, namely, low carbon, correlation and functions, and economic cost. The case study of a vertical CNC lathe proves the superiority and rationality of the proposed method.

Non-linear canonical correlation for joint analysis of MEG signals from two subjects

Directory of Open Access Journals (Sweden)

Cristina eCampi

2013-06-01

Full Text Available We consider the problem of analysing magnetoencephalography (MEG data measured from two persons undergoing the same experiment, and we propose a method that searches for sources with maximally correlated energies. Our method is based on canonical correlation analysis (CCA, which provides linear transformations, one for each subject, such that the correlation between the transformed MEG signals is maximized. Here, we present a nonlinear version of CCA which measures the correlation of energies. Furthermore, we introduce a delay parameter in the modelto analyse, e.g., leader-follower changes in experiments where the two subjects are engaged in social interaction.

Prediction of East African Seasonal Rainfall Using Simplex Canonical Correlation Analysis.

Science.gov (United States)

Ntale, Henry K.; Yew Gan, Thian; Mwale, Davison

2003-06-01

A linear statistical model, canonical correlation analysis (CCA), was driven by the Nelder-Mead simplex optimization algorithm (called CCA-NMS) to predict the standardized seasonal rainfall totals of East Africa at 3-month lead time using SLP and SST anomaly fields of the Indian and Atlantic Oceans combined together by 24 simplex optimized weights, and then `reduced' by the principal component analysis. Applying the optimized weights to the predictor fields produced better March-April-May (MAM) and September-October-November (SON) seasonal rain forecasts than a direct application of the same, unweighted predictor fields to CCA at both calibration and validation stages. Northeastern Tanzania and south-central Kenya had the best SON prediction results with both validation correlation and Hanssen-Kuipers skill scores exceeding +0.3. The MAM season was better predicted in the western parts of East Africa. The CCA correlation maps showed that low SON rainfall in East Africa is associated with cold SSTs off the Somali coast and the Benguela (Angola) coast, and low MAM rainfall is associated with a buildup of low SSTs in the Indian Ocean adjacent to East Africa and the Gulf of Guinea.

Methods uncovering usability issues in medication-related alerting functions: results from a systematic review.

Science.gov (United States)

Marcilly, Romaric; Vasseur, Francis; Ammenwerth, Elske; Beuscart-Zephir, Marie-Catherine

2014-01-01

This paper aims at listing the methods used to evaluate the usability of medication-related alerting functions and at knowing what type of usability issues those methods allow to detect. A sub-analysis of data from this systematic review has been performed. Methods applied in the included papers were collected. Then, included papers were sorted in four types of evaluation: "expert evaluation", "user- testing/simulation", "on site observation" and "impact studies". The types of usability issues (usability flaws, usage problems and negative outcomes) uncovered by those evaluations were analyzed. Results show that a large set of methods are used. The largest proportion of papers uses "on site observation" evaluation. This is the only evaluation type for which every kind of usability flaws, usage problems and outcomes are detected. It is somehow surprising that, in a usability systematic review, most of the papers included use a method that is not often presented as a usability method. Results are discussed about the opportunity to provide usability information collected after the implementation of the technology during their design process, i.e. before their implementation.

The work is never ending: uncovering teamwork sustainability using realistic evaluation.

Science.gov (United States)

Frykman, Mandus; von Thiele Schwarz, Ulrica; Muntlin Athlin, Åsa; Hasson, Henna; Mazzocato, Pamela

2017-03-20

Purpose The purpose of this paper is to uncover the mechanisms influencing the sustainability of behavior changes following the implementation of teamwork. Design/methodology/approach Realistic evaluation was combined with a framework (DCOM®) based on applied behavior analysis to study the sustainability of behavior changes two and a half years after the initial implementation of teamwork at an emergency department. The DCOM® framework was used to categorize the mechanisms of behavior change interventions (BCIs) into the four categories of direction, competence, opportunity, and motivation. Non-participant observation and interview data were used. Findings The teamwork behaviors were not sustained. A substantial fallback in managerial activities in combination with a complex context contributed to reduced direction, opportunity, and motivation. Reduced direction made staff members unclear about how and why they should work in teams. Deterioration of opportunity was evident from the lack of problem-solving resources resulting in accumulated barriers to teamwork. Motivation in terms of management support and feedback was reduced. Practical implications The implementation of complex organizational changes in complex healthcare contexts requires continuous adaption and managerial activities well beyond the initial implementation period. Originality/value By integrating the DCOM® framework with realistic evaluation, this study responds to the call for theoretically based research on behavioral mechanisms that can explain how BCIs interact with context and how this interaction influences sustainability.

Error analysis of supercritical water correlations using ATHLET system code under DHT conditions

Energy Technology Data Exchange (ETDEWEB)

Samuel, J., E-mail: jeffrey.samuel@uoit.ca [Univ. of Ontario Inst. of Tech., Oshawa, ON (Canada)

2014-07-01

The thermal-hydraulic computer code ATHLET (Analysis of THermal-hydraulics of LEaks and Transients) is used for analysis of anticipated and abnormal plant transients, including safety analysis of Light Water Reactors (LWRs) and Russian Graphite-Moderated High Power Channel-type Reactors (RBMKs). The range of applicability of ATHLET has been extended to supercritical water by updating the fluid-and transport-properties packages, thus enabling the code to the used in analysis of SuperCritical Water-cooled Reactors (SCWRs). Several well-known heat-transfer correlations for supercritical fluids were added to the ATHLET code and a numerical model was created to represent an experimental test section. In this work, the error in the Heat Transfer Coefficient (HTC) calculation by the ATHLET model is studied along with the ability of the various correlations to predict different heat transfer regimes. (author)

Topic Correlation Analysis for Bearing Fault Diagnosis Under Variable Operating Conditions

Science.gov (United States)

Chen, Chao; Shen, Fei; Yan, Ruqiang

2017-05-01

This paper presents a Topic Correlation Analysis (TCA) based approach for bearing fault diagnosis. In TCA, Joint Mixture Model (JMM), a model which adapts Probability Latent Semantic Analysis (PLSA), is constructed first. Then, JMM models the shared and domain-specific topics using “fault vocabulary” . After that, the correlations between two kinds of topics are computed and used to build a mapping matrix. Furthermore, a new shared space spanned by the shared and mapped domain-specific topics is set up where the distribution gap between different domains is reduced. Finally, a classifier is trained with mapped features which follow a different distribution and then the trained classifier is tested on target bearing data. Experimental results justify the superiority of the proposed approach over the stat-of-the-art baselines and it can diagnose bearing fault efficiently and effectively under variable operating conditions.

Econometric analysis of realised covariation: high frequency covariance, regression and correlation in financial economics

OpenAIRE

Ole E. Barndorff-Nielsen; Neil Shephard

2002-01-01

This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...

Structure function analysis of long-range correlations in plasma turbulence

International Nuclear Information System (INIS)

Yu, C.X.; Gilmore, M.; Peebles, W.A.; Rhodes, T.L.

2003-01-01

Long-range correlations (temporal and spatial) have been predicted in a number of different turbulence models, both analytical and numerical. These long-range correlations are thought to significantly affect cross-field turbulent transport in magnetically confined plasmas. The Hurst exponent, H - one of a number of methods to identify the existence of long-range correlations in experimental data - can be used to quantify self-similarity scalings and correlations in the mesoscale temporal range. The Hurst exponent can be calculated by several different algorithms, each of which has particular advantages and disadvantages. One method for calculating H is via structure functions (SFs). The SF method is a robust technique for determining H with several inherent advantages that has not yet been widely used in plasma turbulence research. In this article, the SF method and its advantages are discussed in detail, using both simulated and measured fluctuation data from the DIII-D tokamak [J. L. Luxon and L. G. Davis, Fusion Technol. 8, 441 (1985)]. In addition, it is shown that SFs used in conjunction with rescaled range analysis (another method for calculating H) can be used to mitigate the effects of coherent modes in some cases

NEW SUNS IN THE COSMOS. III. MULTIFRACTAL SIGNATURE ANALYSIS

Energy Technology Data Exchange (ETDEWEB)

Freitas, D. B. de; Nepomuceno, M. M. F.; Junior, P. R. V. de Moraes; Chagas, M. L. Das; Bravo, J. P.; Costa, A. D.; Martins, B. L. Canto; Medeiros, J. R. De [Departamento de Física, Universidade Federal do Rio Grande do Norte, 59072-970 Natal, RN (Brazil); Lopes, C. E. F. [SUPA Wide-Field Astronomy Unit, Institute for Astronomy, School of Physics and Astronomy, University of Edinburgh, Royal Observatory, Blackford Hill, Edinburgh EH9 3HJ (United Kingdom); Leão, I. C. [European Southern Observatory, Karl-Schwarzschild-Str. 2, D-85748 Garching (Germany)

2016-11-01

In the present paper, we investigate the multifractality signatures in hourly time series extracted from the CoRoT spacecraft database. Our analysis is intended to highlight the possibility that astrophysical time series can be members of a particular class of complex and dynamic processes, which require several photometric variability diagnostics to characterize their structural and topological properties. To achieve this goal, we search for contributions due to a nonlinear temporal correlation and effects caused by heavier tails than the Gaussian distribution, using a detrending moving average algorithm for one-dimensional multifractal signals (MFDMA). We observe that the correlation structure is the main source of multifractality, while heavy-tailed distribution plays a minor role in generating the multifractal effects. Our work also reveals that the rotation period of stars is inherently scaled by the degree of multifractality. As a result, analyzing the multifractal degree of the referred series, we uncover an evolution of multifractality from shorter to larger periods.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

Science.gov (United States)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Nanoscale protein diffusion by STED-based pair correlation analysis.

Directory of Open Access Journals (Sweden)

Paolo Bianchini

Full Text Available We describe for the first time the combination between cross-pair correlation function analysis (pair correlation analysis or pCF and stimulated emission depletion (STED to obtain diffusion maps at spatial resolution below the optical diffraction limit (super-resolution. Our approach was tested in systems characterized by high and low signal to noise ratio, i.e. Capsid Like Particles (CLPs bearing several (>100 active fluorescent proteins and monomeric fluorescent proteins transiently expressed in living Chinese Hamster Ovary cells, respectively. The latter system represents the usual condition encountered in living cell studies on fluorescent protein chimeras. Spatial resolution of STED-pCF was found to be about 110 nm, with a more than twofold improvement over conventional confocal acquisition. We successfully applied our method to highlight how the proximity to nuclear envelope affects the mobility features of proteins actively imported into the nucleus in living cells. Remarkably, STED-pCF unveiled the existence of local barriers to diffusion as well as the presence of a slow component at distances up to 500-700 nm from either sides of nuclear envelope. The mobility of this component is similar to that previously described for transport complexes. Remarkably, all these features were invisible in conventional confocal mode.

Correlation analysis of the physiological factors controlling fundamental voice frequency.

Science.gov (United States)

Atkinson, J E

1978-01-01

A technique has been developed to obtain a quantitative measure of correlation between electromyographic (EMG) activity of various laryngeal muscles, subglottal air pressure, and the fundamental frequency of vibration of the vocal folds (Fo). Data were collected and analyzed on one subject, a native speaker of American English. The results show that an analysis of this type can provide a useful measure of correlation between the physiological and acoustical events in speech and, furthermore, can yield detailed insights into the organization and nature of the speech production process. In particular, based on these results, a model is suggested of Fo control involving laryngeal state functions that seems to agree with present knowledge of laryngeal control and experimental evidence.

Financial liberalization and stock market cross-correlation: MF-DCCA analysis based on Shanghai-Hong Kong Stock Connect

Science.gov (United States)

Ruan, Qingsong; Zhang, Shuhua; Lv, Dayong; Lu, Xinsheng

2018-02-01

Based on the implementation of Shanghai-Hong Kong Stock Connect in China, this paper examines the effects of financial liberalization on stock market comovement using both multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods. Results based on MF-DFA confirm the multifractality of Shanghai and Hong Kong stock markets, and the market efficiency of Shanghai stock market increased after the implementation of this connect program. Besides, analysis based on MF-DCCA has verified the existence of persistent cross-correlation between Shanghai and Hong Kong stock markets, and the cross-correlation gets stronger after the launch of this liberalization program. Finally, we find that fat-tail distribution is the main source of multifractality in the cross-correlations before the stock connect program, while long-range correlation contributes to the multifractality after this program.

METHODS OF DISTANCE MEASUREMENT’S ACCURACY INCREASING BASED ON THE CORRELATION ANALYSIS OF STEREO IMAGES

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V. L. Kozlov

2018-01-01

Full Text Available To solve the problem of increasing the accuracy of restoring a three-dimensional picture of space using two-dimensional digital images, it is necessary to use new effective techniques and algorithms for processing and correlation analysis of digital images. Actively developed tools that allow you to reduce the time costs for processing stereo images, improve the quality of the depth maps construction and automate their construction. The aim of the work is to investigate the possibilities of using various techniques for processing digital images to improve the measurements accuracy of the rangefinder based on the correlation analysis of the stereo image. The results of studies of the influence of color channel mixing techniques on the distance measurements accuracy for various functions realizing correlation processing of images are presented. Studies on the analysis of the possibility of using integral representation of images to reduce the time cost in constructing a depth map areproposed. The results of studies of the possibility of using images prefiltration before correlation processing when distance measuring by stereo imaging areproposed.It is obtained that using of uniform mixing of channels leads to minimization of the total number of measurement errors, and using of brightness extraction according to the sRGB standard leads to an increase of errors number for all of the considered correlation processing techniques. Integral representation of the image makes it possible to accelerate the correlation processing, but this method is useful for depth map calculating in images no more than 0.5 megapixels. Using of image filtration before correlation processing can provide, depending on the filter parameters, either an increasing of the correlation function value, which is useful for analyzing noisy images, or compression of the correlation function.

Phenomenological analysis of angular correlations in 7 TeV proton-proton collisions from the CMS experiment

International Nuclear Information System (INIS)

Ray, R. L.

2011-01-01

A phenomenological analysis is presented of recent two-particle angular correlation data on relative pseudorapidity (η) and azimuth reported by the Compact Muon Solenoid (CMS) Collaboration for √(s)=7 TeV proton-proton collisions. The data are described with an empirical jetlike model developed for similar angular correlation measurements obtained from heavy-ion collisions at the Relativistic Heavy-Ion Collider (RHIC). The sameside (small relative azimuth), η-extended correlation structure, referred to as the ridge, is compared with three phenomenological correlation structures suggested by theoretical analysis. These include additional angular correlations due to soft gluon radiation in 2→3 partonic processes, a one-dimensional sameside correlation ridge on azimuth motivated, for example, by color-glass condensate models, and an azimuth quadrupole similar to that required to describe heavy-ion angular correlations. The quadrupole model provides the best overall description of the CMS data, including the ridge, based on χ 2 minimization in agreement with previous studies. Implications of these results with respect to possible mechanisms for producing the CMS sameside correlation ridge are discussed.

Pet Bottle Design, Correlation Analysis Of Pet Bottle Characteristics Subjective Judgment

Directory of Open Access Journals (Sweden)

Darko Avramović

2012-06-01

Full Text Available Ability to predict consumer’s reaction to particular design solution of the product is very important. Gathering andanalysis of subjective judgments of particular characteristics, based on which the aesthetic of the product is judged,is one of predicting the consumer’s reaction in the future. Knowledge gathered this manner can serve as a referencefor further studies of determining factors for aesthetic results and design quality. There are two opposed opinionsregarding prediction of aesthetic impression. One opinion is that taste of individual cannot be discussed because itis extremely variable and the possibility of meaningful analysis of aesthetic impression is rejected. Other opinionstates that there is a consistent preference of certain aesthetic characteristics despite individual and group differences.Main goal of this paper is to examine the correlation between subjective judgments of certain PET bottlecharacteristics. Analysis showed meaningful correlation between some of the PET bottle characteristics while othercharacteristics showed less correlation. It can be concluded that not all of the characteristics have the same influenceon the aesthetics and design quality of the PET bottle form. Emphasizing the characteristics relative to aesthetics ofthe product can produce better market results, taking in to account that consumer’s buy the product they consider tobe more attractive if other parameters of the product are similar.

Structural and phylogenetic analysis of Rhodobacter capsulatus NifF: uncovering general features of nitrogen-fixation (nif)-flavodoxins.

Science.gov (United States)

Pérez-Dorado, Inmaculada; Bortolotti, Ana; Cortez, Néstor; Hermoso, Juan A

2013-01-09

Analysis of the crystal structure of NifF from Rhodobacter capsulatus and its homologues reported so far reflects the existence of unique structural features in nif flavodoxins: a leucine at the re face of the isoalloxazine, an eight-residue insertion at the C-terminus of the 50's loop and a remarkable difference in the electrostatic potential surface with respect to non-nif flavodoxins. A phylogenetic study on 64 sequences from 52 bacterial species revealed four clusters, including different functional prototypes, correlating the previously defined as "short-chain" with the firmicutes flavodoxins and the "long-chain" with gram-negative species. The comparison of Rhodobacter NifF structure with other bacterial flavodoxin prototypes discloses the concurrence of specific features of these functional electron donors to nitrogenase.

The correlation between apparent diffusion coefficient and tumor cellularity in patients: a meta-analysis.

Science.gov (United States)

Chen, Lihua; Liu, Min; Bao, Jing; Xia, Yunbao; Zhang, Jiuquan; Zhang, Lin; Huang, Xuequan; Wang, Jian

2013-01-01

To perform a meta-analysis exploring the correlation between the apparent diffusion coefficient (ADC) and tumor cellularity in patients. We searched medical and scientific literature databases for studies discussing the correlation between the ADC and tumor cellularity in patients. Only studies that were published in English or Chinese prior to November 2012 were considered for inclusion. Summary correlation coefficient (r) values were extracted from each study, and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses were performed to investigate potential heterogeneity. Of 189 studies, 28 were included in the meta-analysis, comprising 729 patients. The pooled r for all studies was -0.57 (95% CI: -0.62, -0.52), indicating notable heterogeneity (Pcorrelation between the ADC and cellularity for brain tumors. There was no notable evidence of publication bias. There is a strong negative correlation between the ADC and tumor cellularity in patients, particularly in the brain. However, larger, prospective studies are warranted to validate these findings in other cancer types.

Diagrammatic analysis of correlations in polymer fluids: Cluster diagrams via Edwards' field theory

International Nuclear Information System (INIS)

Morse, David C.

2006-01-01

Edwards' functional integral approach to the statistical mechanics of polymer liquids is amenable to a diagrammatic analysis in which free energies and correlation functions are expanded as infinite sums of Feynman diagrams. This analysis is shown to lead naturally to a perturbative cluster expansion that is closely related to the Mayer cluster expansion developed for molecular liquids by Chandler and co-workers. Expansion of the functional integral representation of the grand-canonical partition function yields a perturbation theory in which all quantities of interest are expressed as functionals of a monomer-monomer pair potential, as functionals of intramolecular correlation functions of non-interacting molecules, and as functions of molecular activities. In different variants of the theory, the pair potential may be either a bare or a screened potential. A series of topological reductions yields a renormalized diagrammatic expansion in which collective correlation functions are instead expressed diagrammatically as functionals of the true single-molecule correlation functions in the interacting fluid, and as functions of molecular number density. Similar renormalized expansions are also obtained for a collective Ornstein-Zernicke direct correlation function, and for intramolecular correlation functions. A concise discussion is given of the corresponding Mayer cluster expansion, and of the relationship between the Mayer and perturbative cluster expansions for liquids of flexible molecules. The application of the perturbative cluster expansion to coarse-grained models of dense multi-component polymer liquids is discussed, and a justification is given for the use of a loop expansion. As an example, the formalism is used to derive a new expression for the wave-number dependent direct correlation function and recover known expressions for the intramolecular two-point correlation function to first-order in a renormalized loop expansion for coarse-grained models of

Correlation of transcriptomic responses and metal bioaccumulation in Mytilus edulis L. reveals early indicators of stress

Energy Technology Data Exchange (ETDEWEB)

Poynton, Helen C., E-mail: helen.poynton@umb.edu; Robinson, William E.; Blalock, Bonnie J.; Hannigan, Robyn E.

2014-10-15

Highlights: • Gene expression and metal tissue concentrations were compared in Mytilus edulis. • Expression levels of several transcripts correlated with metal concentrations. • Transcripts involved in the unfolded protein response (UPR) were induced. • Integration of transcriptomics and tissue levels provides insight to toxicity. - Abstract: Marine biomonitoring programs in the U.S. and Europe have historically relied on monitoring tissue concentrations of bivalves to monitor contaminant levels and ecosystem health. By integrating ‘omic methods with these tissue residue approaches we can uncover mechanistic insight to link tissue concentrations to potential toxic effects. In an effort to identify novel biomarkers and better understand the molecular toxicology of metal bioaccumulation in bivalves, we exposed the blue mussel, Mytilus edulis L., to sub-lethal concentrations (0.54 μM) of cadmium, lead, and a Cd + Pb mixture. Metal concentrations were measured in gill tissues at 1, 2, and 4 weeks, and increased linearly over the 4 week duration. In addition, there was evidence that Pb interfered with Cd uptake in the mixture treatment. Using a 3025 sequence microarray for M. edulis, we performed transcriptomic analysis, identifying 57 differentially expressed sequences. Hierarchical clustering of these sequences successfully distinguished the different treatment groups demonstrating that the expression profiles were reproducible among the treatments. Enrichment analysis of gene ontology terms identified several biological processes that were perturbed by the treatments, including nucleoside phosphate biosynthetic processes, mRNA metabolic processes, and response to stress. To identify transcripts whose expression level correlated with metal bioaccumulation, we performed Pearson correlation analysis. Several transcripts correlated with gill metal concentrations including mt10, mt20, and contig 48, an unknown transcript containing a wsc domain. In addition

Reliability analysis based on a novel density estimation method for structures with correlations

Directory of Open Access Journals (Sweden)

Baoyu LI

2017-06-01

Full Text Available Estimating the Probability Density Function (PDF of the performance function is a direct way for structural reliability analysis, and the failure probability can be easily obtained by integration in the failure domain. However, efficiently estimating the PDF is still an urgent problem to be solved. The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation, whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs. While in fact, structures with correlated inputs always exist in engineering, thus this paper improves the maximum entropy method, and applies the Unscented Transformation (UT technique to compute the fractional moments of the performance function for structures with correlations, which is a very efficient moment estimation method for models with any inputs. The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations. Besides, the number of function evaluations of the proposed method in reliability analysis, which is determined by UT, is really small. Several examples are employed to illustrate the accuracy and advantages of the proposed method.

TIME HORIZON AND UNCOVERED INTEREST PARITY IN EMERGING ECONOMIES

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Norlida Hanim Mohd Salleh

2011-07-01

Full Text Available The aim of this study is to re-examine the well-known empirical puzzle of uncovered interest parity (UIP for emerging market economies with different prediction time horizons. The empirical results obtained using dynamic panel and time series techniques for monthly data from January 1995 to December 2009 eventually show that the panel data estimates are more powerful than those obtained by applying individual time series estimations and the significant contribution of the exchange rate prediction horizons in determining the status of UIP. This finding reveals that at the longer time horizon, the model has better econometric specification and thus more predictive power for exchange rate movements compared to the shorter time period. The findings can also be a signalling of well-integrated currency markets and a reliable guide to international investors as well as for the orderly conduct of monetary authorities.

Correlation Between Minimum Apparent Diffusion Coefficient (ADCmin) and Tumor Cellularity: A Meta-analysis.

Science.gov (United States)

Surov, Alexey; Meyer, Hans Jonas; Wienke, Andreas

2017-07-01

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique based on measure of water diffusion that can provide information about tissue microstructure, especially about cell count. Increase of cell density induces restriction of water diffusion and decreases apparent diffusion coefficient (ADC). ADC can be divided into three sub-parameters: ADC minimum or ADC min , mean ADC or ADC mean and ADC maximum or ADC max Some studies have suggested that ADC min shows stronger correlations with cell count in comparison to other ADC fractions and may be used as a parameter for estimation of tumor cellularity. The aim of the present meta-analysis was to summarize correlation coefficients between ADC min and cellularity in different tumors based on large patient data. For this analysis, MEDLINE database was screened for associations between ADC and cell count in different tumors up to September 2016. For this work, only data regarding ADC min were included. Overall, 12 publications with 317 patients were identified. Spearman's correlation coefficient was used to analyze associations between ADC min and cellularity. The reported Pearson correlation coefficients in some publications were converted into Spearman correlation coefficients. The pooled correlation coefficient for all included studies was ρ=-0.59 (95% confidence interval (CI)=-0.72 to -0.45), heterogeneity Tau 2 =0.04 (pcorrelated moderately with tumor cellularity. The calculated correlation coefficient is not stronger in comparison to the reported coefficient for ADC mean and, therefore, ADC min does not represent a better means to reflect cellularity. Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Minimizing the trend effect on detrended cross-correlation analysis with empirical mode decomposition

International Nuclear Information System (INIS)

Zhao Xiaojun; Shang Pengjian; Zhao Chuang; Wang Jing; Tao Rui

2012-01-01

Highlights: ► Investigate the effects of linear, exponential and periodic trends on DCCA. ► Apply empirical mode decomposition to extract trend term. ► Strong and monotonic trends are successfully eliminated. ► Get the cross-correlation exponent in a persistent behavior without crossover. - Abstract: Detrended cross-correlation analysis (DCCA) is a scaling method commonly used to estimate long-range power law cross-correlation in non-stationary signals. However, the susceptibility of DCCA to trends makes the scaling results difficult to analyze due to spurious crossovers. We artificially generate long-range cross-correlated signals and systematically investigate the effect of linear, exponential and periodic trends. Specifically to the crossovers raised by trends, we apply empirical mode decomposition method which decomposes underlying signals into several intrinsic mode functions (IMF) and a residual trend. After the removal of residual term, strong and monotonic trends such as linear and exponential trends are successfully eliminated. But periodic trend cannot be separated out according to the criterion of IMF, which can be eliminated by Fourier transform. As a special case of DCCA, detrended fluctuation analysis presents similar results.

From micro-correlations to macro-correlations

International Nuclear Information System (INIS)

Eliazar, Iddo

2016-01-01

Random vectors with a symmetric correlation structure share a common value of pair-wise correlation between their different components. The symmetric correlation structure appears in a multitude of settings, e.g. mixture models. In a mixture model the components of the random vector are drawn independently from a general probability distribution that is determined by an underlying parameter, and the parameter itself is randomized. In this paper we study the overall correlation of high-dimensional random vectors with a symmetric correlation structure. Considering such a random vector, and terming its pair-wise correlation “micro-correlation”, we use an asymptotic analysis to derive the random vector’s “macro-correlation” : a score that takes values in the unit interval, and that quantifies the random vector’s overall correlation. The method of obtaining macro-correlations from micro-correlations is then applied to a diverse collection of frameworks that demonstrate the method’s wide applicability.

Solar activity and terrestrial climate: an analysis of some purported correlations

DEFF Research Database (Denmark)

Laut, Peter

2003-01-01

claimed to support solar hypotheses. My analyses show that the apparent strong correlations displayed on these graphs have been obtained by an incorrect handling of the physical data. Since the graphs are still widely referred to in the literature and their misleading character has not yet been generally......The last decade has seen a revival of various hypotheses claiming a strong correlation between solar activity and a number of terrestrial climate parameters: Links between cosmic rays and cloud cover, first total cloud cover and then only low clouds, and between solar cycle lengths and Northern...... the existence of important links between solar activity and terrestrial climate. Such links have over the years been demonstrated by many authors. The sole objective of the present analysis is to draw attention to the fact that some of the widely publicized, apparent correlations do not properly reflect...

Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

Science.gov (United States)

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

Using a system of differential equations that models cattle growth to uncover the genetic basis of complex traits.

Science.gov (United States)

Freua, Mateus Castelani; Santana, Miguel Henrique de Almeida; Ventura, Ricardo Vieira; Tedeschi, Luis Orlindo; Ferraz, José Bento Sterman

2017-08-01

The interplay between dynamic models of biological systems and genomics is based on the assumption that genetic variation of the complex trait (i.e., outcome of model behavior) arises from component traits (i.e., model parameters) in lower hierarchical levels. In order to provide a proof of concept of this statement for a cattle growth model, we ask whether model parameters map genomic regions that harbor quantitative trait loci (QTLs) already described for the complex trait. We conducted a genome-wide association study (GWAS) with a Bayesian hierarchical LASSO method in two parameters of the Davis Growth Model, a system of three ordinary differential equations describing DNA accretion, protein synthesis and degradation, and fat synthesis. Phenotypic and genotypic data were available for 893 Nellore (Bos indicus) cattle. Computed values for parameter k 1 (DNA accretion rate) ranged from 0.005 ± 0.003 and for α (constant for energy for maintenance requirement) 0.134 ± 0.024. The expected biological interpretation of the parameters is confirmed by QTLs mapped for k 1 and α. QTLs within genomic regions mapped for k 1 are expected to be correlated with the DNA pool: body size and weight. Single nucleotide polymorphisms (SNPs) which were significant for α mapped QTLs that had already been associated with residual feed intake, feed conversion ratio, average daily gain (ADG), body weight, and also dry matter intake. SNPs identified for k 1 were able to additionally explain 2.2% of the phenotypic variability of the complex ADG, even when SNPs for k 1 did not match the genomic regions associated with ADG. Although improvements are needed, our findings suggest that genomic analysis on component traits may help to uncover the genetic basis of more complex traits, particularly when lower biological hierarchies are mechanistically described by mathematical simulation models.

Prospects of Frequency-Time Correlation Analysis for Detecting Pipeline Leaks by Acoustic Emission Method

International Nuclear Information System (INIS)

Faerman, V A; Cheremnov, A G; Avramchuk, V V; Luneva, E E

2014-01-01

In the current work the relevance of nondestructive test method development applied for pipeline leak detection is considered. It was shown that acoustic emission testing is currently one of the most widely spread leak detection methods. The main disadvantage of this method is that it cannot be applied in monitoring long pipeline sections, which in its turn complicates and slows down the inspection of the line pipe sections of main pipelines. The prospects of developing alternative techniques and methods based on the use of the spectral analysis of signals were considered and their possible application in leak detection on the basis of the correlation method was outlined. As an alternative, the time-frequency correlation function calculation is proposed. This function represents the correlation between the spectral components of the analyzed signals. In this work, the technique of time-frequency correlation function calculation is described. The experimental data that demonstrate obvious advantage of the time-frequency correlation function compared to the simple correlation function are presented. The application of the time-frequency correlation function is more effective in suppressing the noise components in the frequency range of the useful signal, which makes maximum of the function more pronounced. The main drawback of application of the time- frequency correlation function analysis in solving leak detection problems is a great number of calculations that may result in a further increase in pipeline time inspection. However, this drawback can be partially reduced by the development and implementation of efficient algorithms (including parallel) of computing the fast Fourier transform using computer central processing unit and graphic processing unit

Uncovering values-based practice: VBP's implicit commitments to subjectivism and relativism.

Science.gov (United States)

Cassidy, Ben

2013-06-01

Despite assertions to the contrary, KWM Fulford's values-based practice is implicitly committed to subjectivism when it comes to reasoning about values. This renders the approach unworkable. The act of merely uncovering underlying values is not enough to effect change and, therefore, resolve problems if we have no way, even in principle, of determining which values are right and which are wrong. Fulford's only departure from subjectivism about value is his commitment to 'framework values', which seems grounded in a version of ethical relativism. I argue that we need to reject both subjectivism and relativism if progress within ethical discussions about practice is to be meaningful and a real possibility. © 2013 John Wiley & Sons Ltd.

Radiologic Placement of Uncovered Stents for the Treatment of Malignant Colonic Obstruction Proximal to the Descending Colon

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jehong; Kwon, Se Hwan, E-mail: Kwon98@khu.ac.kr [Kyung Hee University, Department of Radiology, College of Medicine (Korea, Republic of); Lee, Chang-Kyun [Kyung Hee University, Department of Internal Medicine, College of Medicine (Korea, Republic of); Park, Sun Jin [Kyung Hee University, Department of Surgery, College of Medicine (Korea, Republic of); Oh, Ji Young [Kyung Hee University Hospital at Gangdong, Department of Radiology (Korea, Republic of); Oh, Joo Hyeong [Kyung Hee University, Department of Radiology, College of Medicine (Korea, Republic of)

2017-01-15

PurposeTo evaluate the safety, feasibility, and patency rates of radiologic placement of uncovered stents for the treatment of malignant colonic obstruction proximal to the descending colon.Materials and MethodsThis was a retrospective, single-center study. From May 2003 to March 2015, 53 image-guided placements of uncovered stents (44 initial placements, 9 secondary placements) were attempted in 44 patients (male:female = 23:21; mean age, 71.8 years). The technical and clinical success, complication rates, and patency rates of the stents were also evaluated. Technical success was defined as the successful deployment of the stent under fluoroscopic guidance alone and clinical success was defined as the relief of obstructive symptoms or signs within 48 h of stent deployment.ResultsIn total, 12 (27.3 %) patients underwent preoperative decompression, while 32 (72.7 %) underwent decompression with palliative intent. The technical success rate was 93.2 % (41/44) for initial placement and 88.9 % (8/9) for secondary placement. Secondary stent placement in the palliative group was required in nine patients after successful initial stent placement due to stent obstruction from tumor ingrowth (n = 7) and stent migration (n = 2). The symptoms of obstruction were relieved in all successful cases (100 %). In the palliative group, the patency rates were 94.4 % at 1 month, 84.0 % at 3 months, 64.8 % at 6 months, and 48.6 % at 12 months.ConclusionsThe radiologic placement of uncovered stents for the treatment of malignant obstruction proximal to the descending colon is feasible and safe, and provides acceptable clinical results.

Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

International Nuclear Information System (INIS)

Costa, Valter Magalhaes

2011-01-01

was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables using neural networks. (author)

Structural and Phylogenetic Analysis of Rhodobacter capsulatus NifF: Uncovering General Features of Nitrogen-fixation (nif-Flavodoxins

Directory of Open Access Journals (Sweden)

Inmaculada Pérez-Dorado

2013-01-01

Full Text Available Analysis of the crystal structure of NifF from Rhodobacter capsulatus and its homologues reported so far reflects the existence of unique structural features in nif flavodoxins: a leucine at the re face of the isoalloxazine, an eight-residue insertion at the C-terminus of the 50’s loop and a remarkable difference in the electrostatic potential surface with respect to non-nif flavodoxins. A phylogenetic study on 64 sequences from 52 bacterial species revealed four clusters, including different functional prototypes, correlating the previously defined as “short-chain” with the firmicutes flavodoxins and the “long-chain” with gram-negative species. The comparison of Rhodobacter NifF structure with other bacterial flavodoxin prototypes discloses the concurrence of specific features of these functional electron donors to nitrogenase.

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

Science.gov (United States)

Kujala, Jan; Sudre, Gustavo; Vartiainen, Johanna; Liljeström, Mia; Mitchell, Tom; Salmelin, Riitta

2014-01-01

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG–fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing. PMID:24518260

Neutron Activation Analysis and Moessbauer Correlations of Archaeological Pottery from Amazon Basin for Classification Studies

International Nuclear Information System (INIS)

Bellido, A. V. B.; Latini, R. M.; Nicoli, I.; Scorzelli, R. B.; Solorzano, P. M.

2011-01-01

The aim of the present work was to investigate the correlation between data obtained by means of two analytical methods, instrumental neutron activation analysis (INAA) and Moessbauer Spectroscopy of pottery samples combined with multivariate statistical analysis in order to optimize quantitative analysis in the classification studies. Ceramics recently discovered in archaeological earth circular structures sites in Acre state Brazil. 199 samples were analyzed by INAA, allowing simultaneous determination of twenty elements chemical concentrations, and 44 samples by using Moessbauer Spectroscopy, allowing the determination of fourteen hyperfine parameters. For the correlation study, data were treated by two multivariate statistical methods: cluster analysis for the classification and the principal component analysis for the data correlations. INAA data show that some of REE (rare earth elements) were the discriminating variables for this technique. Mossbauer parameters that exhibit the same behavior are being investigated, remarkable improve can be seem for the combined REE and the Mossbauer variables showing a good results considering the limited number of samples. This data matrix is being used for the understanding in the studies of classification and provenance of ceramics prehistory of the Amazonic basin.

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data

DEFF Research Database (Denmark)

Tan, Qihua; Thomassen, Mads; Burton, Mark

2017-01-01

the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....

Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

Science.gov (United States)

Sulistyo, A.; Purwantoro; Sari, K. P.

2018-01-01

Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

Analysis of angiography findings in cerebral arteriovenous malformations: Correlation with hemorrhage

Energy Technology Data Exchange (ETDEWEB)

Kim, Jae Hyoung; Kim, Hyung Jin; Jung, Jin Myung; Ha, Choong Kun; Chung, Sung Hoon [Gyeongsang National University College of Medicine, Chinju (Korea, Republic of)

1993-07-15

Intracerebral hemorrhage is the most serious complication of cerebral arteriovenous malformations (AVM). To identify angiographic characteristics of AVM which correlate with a history of hemorrhage, we retrospectively analyzed angiographic findings of 25 patients with AVM. Nine characteristic were evaluated; these include nidus size, location, arterial aneurysm, intranidal aneurysm, angiomatous change, venous drainage pattern, venous stenosis, delayed drainage and venous ectasia. The characteristic were correlated with hemorrhage,which was seen in 18 (72%) patients on CT or MR images. Venous stenosis (P<0.5) and delaved venous drainage (P<0.5) well correlated with a history of hemorrhage. Arterial aneurysm and intranidal aneurysm also had a tendency hemorrhage although they did not prove to be statistically significant. Detailed analysis of angiographic finding of AVM is important for recognition of characteristic which are related to hemorrhage and may contribute to establishing a prognosis and treatment planning.

Uncovering Aberrant Mutant PKA Function with Flow Cytometric FRET

Directory of Open Access Journals (Sweden)

Shin-Rong Lee

2016-03-01

Full Text Available Biology has been revolutionized by tools that allow the detection and characterization of protein-protein interactions (PPIs. Förster resonance energy transfer (FRET-based methods have become particularly attractive as they allow quantitative studies of PPIs within the convenient and relevant context of living cells. We describe here an approach that allows the rapid construction of live-cell FRET-based binding curves using a commercially available flow cytometer. We illustrate a simple method for absolutely calibrating the cytometer, validating our binding assay against the gold standard isothermal calorimetry (ITC, and using flow cytometric FRET to uncover the structural and functional effects of the Cushing-syndrome-causing mutation (L206R on PKA’s catalytic subunit. We discover that this mutation not only differentially affects PKAcat’s binding to its multiple partners but also impacts its rate of catalysis. These findings improve our mechanistic understanding of this disease-causing mutation, while illustrating the simplicity, general applicability, and power of flow cytometric FRET.

Uncovering the Geometry of Barrierless Reactions Using Lagrangian Descriptors.

Science.gov (United States)

Junginger, Andrej; Hernandez, Rigoberto

2016-03-03

Transition-state theories describing barrierless chemical reactions, or more general activated problems, are often hampered by the lack of a saddle around which the dividing surface can be constructed. For example, the time-dependent transition-state trajectory uncovering the nonrecrossing dividing surface in thermal reactions in the framework of the Langevin equation has relied on perturbative approaches in the vicinity of the saddle. We recently obtained an alternative approach using Lagrangian descriptors to construct time-dependent and recrossing-free dividing surfaces. This is a nonperturbative approach making no reference to a putative saddle. Here we show how the Lagrangian descriptor can be used to obtain the transition-state geometry of a dissipated and thermalized reaction across barrierless potentials. We illustrate the method in the case of a 1D Brownian motion for both barrierless and step potentials; however, the method is not restricted and can be directly applied to different kinds of potentials and higher dimensional systems.

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks

NARCIS (Netherlands)

Waaijenborg, S.; Zwinderman, A.H.

2009-01-01

ABSTRACT: BACKGROUND: We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the

Using brain stimulation to disentangle neural correlates of conscious vision.

Science.gov (United States)

de Graaf, Tom A; Sack, Alexander T

2014-01-01

Research into the neural correlates of consciousness (NCCs) has blossomed, due to the advent of new and increasingly sophisticated brain research tools. Neuroimaging has uncovered a variety of brain processes that relate to conscious perception, obtained in a range of experimental paradigms. But methods such as functional magnetic resonance imaging or electroencephalography do not always afford inference on the functional role these brain processes play in conscious vision. Such empirical NCCs could reflect neural prerequisites, neural consequences, or neural substrates of a conscious experience. Here, we take a closer look at the use of non-invasive brain stimulation (NIBS) techniques in this context. We discuss and review how NIBS methodology can enlighten our understanding of brain mechanisms underlying conscious vision by disentangling the empirical NCCs.

Correlating lesion size and location to deficits after ischemic stroke: the influence of accounting for altered peri-necrotic tissue and incidental silent infarcts

Directory of Open Access Journals (Sweden)

Black Sandra E

2010-01-01

Full Text Available Abstract Background Investigators frequently quantify and evaluate the location and size of stroke lesions to help uncover cerebral anatomical correlates of deficits observed after first-ever stroke. However, it is common to discover silent infarcts such as lacunes in patients identified clinically as 'first-ever' stroke, and it is unclear if including these incidental findings may impact lesion-based investigations of brain-behaviour relationships. There is also debate concerning how to best define the boundaries of necrotic stroke lesions that blend in an ill-defined way into surrounding tissue, as it is unclear whether including this altered peri-necrotic tissue region may influence studies of brain-behaviour relationships. Therefore, for patients with clinically overt stroke, we examined whether including altered peri-necrotic tissue and incidental silent strokes influenced either lesion volume correlations with a measure of sensorimotor impairment or the anatomical localization of this impairment established using subtraction lesion analysis. Methods Chronic stroke lesions of 41 patients were manually traced from digital T1-MRI to sequentially include the: necrotic lesion core, altered peri-necrotic tissue, silent lesions in the same hemisphere as the index lesion, and silent lesions in the opposite hemisphere. Lesion volumes for each region were examined for correlation with motor impairment scores, and subtraction analysis was used to highlight anatomical lesion loci associated with this deficit. Results For subtraction lesion analysis, including peri-necrotic tissue resulted in a larger region of more frequent damage being seen in the basal ganglia. For correlational analysis, only the volume of the lesion core was significantly associated with motor impairment scores (r = -0.35, p = 0.025. In a sub-analysis of patients with small subcortical index lesions, adding silent lesions in the opposite hemisphere to the volume of the index

Importance analysis for models with correlated variables and its sparse grid solution

International Nuclear Information System (INIS)

Li, Luyi; Lu, Zhenzhou

2013-01-01

For structural models involving correlated input variables, a novel interpretation for variance-based importance measures is proposed based on the contribution of the correlated input variables to the variance of the model output. After the novel interpretation of the variance-based importance measures is compared with the existing ones, two solutions of the variance-based importance measures of the correlated input variables are built on the sparse grid numerical integration (SGI): double-loop nested sparse grid integration (DSGI) method and single loop sparse grid integration (SSGI) method. The DSGI method solves the importance measure by decreasing the dimensionality of the input variables procedurally, while SSGI method performs importance analysis through extending the dimensionality of the inputs. Both of them can make full use of the advantages of the SGI, and are well tailored for different situations. By analyzing the results of several numerical and engineering examples, it is found that the novel proposed interpretation about the importance measures of the correlated input variables is reasonable, and the proposed methods for solving importance measures are efficient and accurate. -- Highlights: •The contribution of correlated variables to the variance of the output is analyzed. •A novel interpretation for variance-based indices of correlated variables is proposed. •Two solutions for variance-based importance measures of correlated variables are built

A learning algorithm for adaptive canonical correlation analysis of several data sets.

Science.gov (United States)

Vía, Javier; Santamaría, Ignacio; Pérez, Jesús

2007-01-01

Canonical correlation analysis (CCA) is a classical tool in statistical analysis to find the projections that maximize the correlation between two data sets. In this work we propose a generalization of CCA to several data sets, which is shown to be equivalent to the classical maximum variance (MAXVAR) generalization proposed by Kettenring. The reformulation of this generalization as a set of coupled least squares regression problems is exploited to develop a neural structure for CCA. In particular, the proposed CCA model is a two layer feedforward neural network with lateral connections in the output layer to achieve the simultaneous extraction of all the CCA eigenvectors through deflation. The CCA neural model is trained using a recursive least squares (RLS) algorithm. Finally, the convergence of the proposed learning rule is proved by means of stochastic approximation techniques and their performance is analyzed through simulations.

Uncovering Sundanese Values by Analyzing Symbolic Meaning of Ménak Priangan Clothing (1800-1942)

Science.gov (United States)

Karmila, M.; Suciati; Widiaty, I.

2016-04-01

This study investigates symbolic meanings found in the Sunda ethnic clothing, particularly the Menak Priangan clothing. This study aims to uncover and document those symbolic meanings found in the Menak Priangan clothing as an effort to develop Sunda cultural artefacts of West Java. This study on Menak Priangan clothing applies ethnography (visual) and aesthetic methods. The visual method is utilized in order to uncover local cultural (Sunda) values found in Menak Priangan clothing visualization, including: design, model, name, and representing colours, which then directed towards local Sundanese aesthetic concepts living within the Priangan community. Furthermore, aesthetic method is used to explore role of aesthetic values in empowering visual cultural values within certain community, particularly Sunda aesthetic values. The study results show that since the 19th century, Sunda ethnic clothing was limited to Priangan Sunda only, while traditional clothing wearing by Priangan people reflects their social strata, consisting of: a. Menak Gede (Menak pangluhurna: mayor), bearing raden title, b. Menak Leutik/Santana (mayor assistant), titles: asep, mas, agus, ujang, (Nyimas for woman), c. Somah/Cacah: ordinary people/lower class. Clothing is a cultural phenomenon within certain culture reflecting such society experiences. For Menak people, clothing and its accessories have important meanings. They wear such traditional clothing and accessories as a symbol of power they have within bureaucratic structure and as a symbol of social status they bear within traditional community structure.

Spatial correlation analysis of urban traffic state under a perspective of community detection

Science.gov (United States)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease

Directory of Open Access Journals (Sweden)

Shengming Deng

2017-01-01

Full Text Available The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC on diffusion-weighted MR and the standard uptake value (SUV of 18F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included, EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher’s r-to-z transformation, correlation coefficient (r values were extracted from each study and 95% confidence intervals (CIs were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was −0.35 (95% CI: −0.42–0.28 and exhibited a notable heterogeneity (I2 = 78.4%; P < 0.01. In terms of the cancer type subgroup analysis, combined correlation coefficients of ADC/SUV range from −0.12 (lymphoma, n = 5 to −0.59 (pancreatic cancer, n = 2. We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

Analysis of the synaptotagmin family during reconstituted membrane fusion. Uncovering a class of inhibitory isoforms.

Science.gov (United States)

Bhalla, Akhil; Chicka, Michael C; Chapman, Edwin R

2008-08-01

Ca(2+)-triggered exocytosis in neurons and neuroendocrine cells is regulated by the Ca(2+)-binding protein synaptotagmin (syt) I. Sixteen additional isoforms of syt have been identified, but little is known concerning their biochemical or functional properties. Here, we assessed the abilities of fourteen syt isoforms to directly regulate SNARE (soluble N-ethylmaleimide-sensitive factor (NSF) attachment protein receptor)-catalyzed membrane fusion. One group of isoforms stimulated neuronal SNARE-mediated fusion in response to Ca(2+), while another set inhibited SNARE catalyzed fusion in both the absence and presence of Ca(2+). Biochemical analysis revealed a strong correlation between the ability of syt isoforms to bind 1,2-dioleoyl phosphatidylserine (PS) and t-SNAREs in a Ca(2+)-promoted manner with their abilities to enhance fusion, further establishing PS and SNAREs as critical effectors for syt action. The ability of syt I to efficiently stimulate fusion was specific for certain SNARE pairs, suggesting that syts might contribute to the specificity of intracellular membrane fusion reactions. Finally, a subset of inhibitory syts down-regulated the ability of syt I to activate fusion, demonstrating that syt isoforms can modulate the function of each other.

Structural Analysis of Correlated Factors: Lessons from the Verbal-Performance Dichotomy of the Wechsler Scales.

Science.gov (United States)

Macmann, Gregg M.; Barnett, David W.

1994-01-01

Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

Lagged correlation networks

Science.gov (United States)

Curme, Chester

Technological advances have provided scientists with large high-dimensional datasets that describe the behaviors of complex systems: from the statistics of energy levels in complex quantum systems, to the time-dependent transcription of genes, to price fluctuations among assets in a financial market. In this environment, where it may be difficult to infer the joint distribution of the data, network science has flourished as a way to gain insight into the structure and organization of such systems by focusing on pairwise interactions. This work focuses on a particular setting, in which a system is described by multivariate time series data. We consider time-lagged correlations among elements in this system, in such a way that the measured interactions among elements are asymmetric. Finally, we allow these interactions to be characteristically weak, so that statistical uncertainties may be important to consider when inferring the structure of the system. We introduce a methodology for constructing statistically validated networks to describe such a system, extend the methodology to accommodate interactions with a periodic component, and show how consideration of bipartite community structures in these networks can aid in the construction of robust statistical models. An example of such a system is a financial market, in which high frequency returns data may be used to describe contagion, or the spreading of shocks in price among assets. These data provide the experimental testing ground for our methodology. We study NYSE data from both the present day and one decade ago, examine the time scales over which the validated lagged correlation networks exist, and relate differences in the topological properties of the networks to an increasing economic efficiency. We uncover daily periodicities in the validated interactions, and relate our findings to explanations of the Epps Effect, an empirical phenomenon of financial time series. We also study bipartite community

Analysis method of high-order collective-flow correlations based on the concept of correlative degree

International Nuclear Information System (INIS)

Zhang Weigang

2000-01-01

Based on the concept of correlative degree, a new method of high-order collective-flow measurement is constructed, with which azimuthal correlations, correlations of final state transverse momentum magnitude and transverse correlations can be inspected respectively. Using the new method the contributions of the azimuthal correlations of particles distribution and the correlations of transverse momentum magnitude of final state particles to high-order collective-flow correlations are analyzed respectively with 4π experimental events for 1.2 A GeV Ar + BaI 2 collisions at the Bevalac stream chamber. Comparing with the correlations of transverse momentum magnitude, the azimuthal correlations of final state particles distribution dominate high-order collective-flow correlations in experimental samples. The contributions of correlations of transverse momentum magnitude of final state particles not only enhance the strength of the high-order correlations of particle group, but also provide important information for the measurement of the collectivity of collective flow within the more constraint district

T2 relaxation time analysis in patients with multiple sclerosis: correlation with magnetization transfer ratio

International Nuclear Information System (INIS)

Papanikolaou, Nickolas; Papadaki, Eufrosini; Karampekios, Spyros; Maris, Thomas; Prassopoulos, Panos; Gourtsoyiannis, Nicholas; Spilioti, Martha

2004-01-01

The aim of the current study was to perform T2 relaxation time measurements in multiple sclerosis (MS) patients and correlate them with magnetization transfer ratio (MTR) measurements, in order to investigate in more detail the various histopathological changes that occur in lesions and normal-appearing white matter (NAWM). A total number of 291 measurements of MTR and T2 relaxation times were performed in 13 MS patients and 10 age-matched healthy volunteers. Measurements concerned MS plaques (105), NAWM (80), and ''dirty'' white matter (DWM; 30), evenly divided between the MS patients, and normal white matter (NWM; 76) in the healthy volunteers. Biexponential T2 relaxation-time analysis was performed, and also possible linearity between MTR and mean T2 relaxation times was evaluated using linear regression analysis in all subgroups. Biexponential relaxation was more pronounced in ''black-hole'' lesions (16.6%) and homogeneous enhancing plaques (10%), whereas DWM, NAWM, and mildly hypointense lesions presented biexponential behavior with a lower frequency(6.6, 5, and 3.1%, respectively). Non-enhancing isointense lesions and normal white matter did not reveal any biexponentional behavior. Linear regression analysis between monoexponential T2 relaxation time and MTR measurements demonstrated excellent correlation for DWM(r=-0.78, p<0.0001), very good correlation for black-hole lesions(r=-0.71, p=0.002), good correlation for isointense lesions(r=-0.60, p=0.005), moderate correlation for mildly hypointense lesions(r=-0.34, p=0.007), and non-significant correlation for homogeneous enhancing plaques, NAWM, and NWM. Biexponential T2 relaxation-time behavior is seen in only very few lesions (mainly on plaques with high degree of demyelination and axonal loss). A strong correlation between MTR and monoexponential T2 values was found in regions where either inflammation or demyelination predominates; however, when both pathological conditions coexist, this linear

Association analysis of multiple traits by an approach of combining ...

Indian Academy of Sciences (India)

Lili Chen

diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic ... genthaler and Thilly 2007), the combined multivariate and ... Because of using reverse regression model, our.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

Science.gov (United States)

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (phistogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

Energy Technology Data Exchange (ETDEWEB)

Costa, Valter Magalhaes; Pereira, Iraci Martinez, E-mail: valter.costa@usp.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

2011-07-01

The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

Analysis of input variables of an artificial neural network using bivariate correlation and canonical correlation

International Nuclear Information System (INIS)

Costa, Valter Magalhaes; Pereira, Iraci Martinez

2011-01-01

The monitoring of variables and diagnosis of sensor fault in nuclear power plants or processes industries is very important because a previous diagnosis allows the correction of the fault and, like this, to prevent the production stopped, improving operator's security and it's not provoking economics losses. The objective of this work is to build a set, using bivariate correlation and canonical correlation, which will be the set of input variables of an artificial neural network to monitor the greater number of variables. This methodology was applied to the IEA-R1 Research Reactor at IPEN. Initially, for the input set of neural network we selected the variables: nuclear power, primary circuit flow rate, control/safety rod position and difference in pressure in the core of the reactor, because almost whole of monitoring variables have relation with the variables early described or its effect can be result of the interaction of two or more. The nuclear power is related to the increasing and decreasing of temperatures as well as the amount radiation due fission of the uranium; the rods are controls of power and influence in the amount of radiation and increasing and decreasing of temperatures; the primary circuit flow rate has the function of energy transport by removing the nucleus heat. An artificial neural network was trained and the results were satisfactory since the IEA-R1 Data Acquisition System reactor monitors 64 variables and, with a set of 9 input variables resulting from the correlation analysis, it was possible to monitor 51 variables. (author)

Partial correlation analysis method in ultrarelativistic heavy-ion collisions

Science.gov (United States)

Olszewski, Adam; Broniowski, Wojciech

2017-11-01

We argue that statistical data analysis of two-particle longitudinal correlations in ultrarelativistic heavy-ion collisions may be efficiently carried out with the technique of partial covariance. In this method, the spurious event-by-event fluctuations due to imprecise centrality determination are eliminated via projecting out the component of the covariance influenced by the centrality fluctuations. We bring up the relationship of the partial covariance to the conditional covariance. Importantly, in the superposition approach, where hadrons are produced independently from a collection of sources, the framework allows us to impose centrality constraints on the number of sources rather than hadrons, that way unfolding of the trivial fluctuations from statistical hadronization and focusing better on the initial-state physics. We show, using simulated data from hydrodynamics followed with statistical hadronization, that the technique is practical and very simple to use, giving insight into the correlations generated in the initial stage. We also discuss the issues related to separation of the short- and long-range components of the correlation functions and show that in our example the short-range component from the resonance decays is largely reduced by considering pions of the same sign. We demonstrate the method explicitly on the cases where centrality is determined with a single central control bin or with two peripheral control bins.

Analysis of the impact of correlated benchmark experiments on the validation of codes for criticality safety analysis

International Nuclear Information System (INIS)

Bock, M.; Stuke, M.; Behler, M.

2013-01-01

The validation of a code for criticality safety analysis requires the recalculation of benchmark experiments. The selected benchmark experiments are chosen such that they have properties similar to the application case that has to be assessed. A common source of benchmark experiments is the 'International Handbook of Evaluated Criticality Safety Benchmark Experiments' (ICSBEP Handbook) compiled by the 'International Criticality Safety Benchmark Evaluation Project' (ICSBEP). In order to take full advantage of the information provided by the individual benchmark descriptions for the application case, the recommended procedure is to perform an uncertainty analysis. The latter is based on the uncertainties of experimental results included in most of the benchmark descriptions. They can be performed by means of the Monte Carlo sampling technique. The consideration of uncertainties is also being introduced in the supplementary sheet of DIN 25478 'Application of computer codes in the assessment of criticality safety'. However, for a correct treatment of uncertainties taking into account the individual uncertainties of the benchmark experiments is insufficient. In addition, correlations between benchmark experiments have to be handled correctly. For example, these correlations can arise due to different cases of a benchmark experiment sharing the same components like fuel pins or fissile solutions. Thus, manufacturing tolerances of these components (e.g. diameter of the fuel pellets) have to be considered in a consistent manner in all cases of the benchmark experiment. At the 2012 meeting of the Expert Group on 'Uncertainty Analysis for Criticality Safety Assessment' (UACSA) of the OECD/NEA a benchmark proposal was outlined that aimed for the determination of the impact on benchmark correlations on the estimation of the computational bias of the neutron multiplication factor (k eff ). The analysis presented here is based on this proposal. (orig.)

Multiset canonical correlations analysis and multispectral, truly multitemporal remote sensing data.

Science.gov (United States)

Nielsen, Allan Aasbjerg

2002-01-01

This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multisource, multiset, or multitemporal exploratory data analysis. These techniques transform multivariate multiset data into new orthogonal variables called canonical variates (CVs) which, when applied in remote sensing, exhibit ever-decreasing similarity (as expressed by correlation measures) over sets consisting of 1) spectral variables at fixed points in time (R-mode analysis), or 2) temporal variables with fixed wavelengths (T-mode analysis). The CVs are invariant to linear and affine transformations of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device. In a case study, CVs are calculated from Landsat Thematic Mapper (TM) data with six spectral bands over six consecutive years. Both Rand T-mode CVs clearly exhibit the desired characteristic: they show maximum similarity for the low-order canonical variates and minimum similarity for the high-order canonical variates. These characteristics are seen both visually and in objective measures. The results from the multiset CCA R- and T-mode analyses are very different. This difference is ascribed to the noise structure in the data. The CCA methods are related to partial least squares (PLS) methods. This paper very briefly describes multiset CCA-based multiset PLS. Also, the CCA methods can be applied as multivariate extensions to empirical orthogonal functions (EOF) techniques. Multiset CCA is well-suited for inclusion in geographical information systems (GIS).

Many-body Tunneling and Nonequilibrium Dynamics of Doublons in Strongly Correlated Quantum Dots.

Science.gov (United States)

Hou, WenJie; Wang, YuanDong; Wei, JianHua; Zhu, ZhenGang; Yan, YiJing

2017-05-30

Quantum tunneling dominates coherent transport at low temperatures in many systems of great interest. In this work we report a many-body tunneling (MBT), by nonperturbatively solving the Anderson multi-impurity model, and identify it a fundamental tunneling process on top of the well-acknowledged sequential tunneling and cotunneling. We show that the MBT involves the dynamics of doublons in strongly correlated systems. Proportional to the numbers of dynamical doublons, the MBT can dominate the off-resonant transport in the strongly correlated regime. A T 3/2 -dependence of the MBT current on temperature is uncovered and can be identified as a fingerprint of the MBT in experiments. We also prove that the MBT can support the coherent long-range tunneling of doublons, which is well consistent with recent experiments on ultracold atoms. As a fundamental physical process, the MBT is expected to play important roles in general quantum systems.

Automated modal parameter estimation using correlation analysis and bootstrap sampling

Science.gov (United States)

Yaghoubi, Vahid; Vakilzadeh, Majid K.; Abrahamsson, Thomas J. S.

2018-02-01

The estimation of modal parameters from a set of noisy measured data is a highly judgmental task, with user expertise playing a significant role in distinguishing between estimated physical and noise modes of a test-piece. Various methods have been developed to automate this procedure. The common approach is to identify models with different orders and cluster similar modes together. However, most proposed methods based on this approach suffer from high-dimensional optimization problems in either the estimation or clustering step. To overcome this problem, this study presents an algorithm for autonomous modal parameter estimation in which the only required optimization is performed in a three-dimensional space. To this end, a subspace-based identification method is employed for the estimation and a non-iterative correlation-based method is used for the clustering. This clustering is at the heart of the paper. The keys to success are correlation metrics that are able to treat the problems of spatial eigenvector aliasing and nonunique eigenvectors of coalescent modes simultaneously. The algorithm commences by the identification of an excessively high-order model from frequency response function test data. The high number of modes of this model provides bases for two subspaces: one for likely physical modes of the tested system and one for its complement dubbed the subspace of noise modes. By employing the bootstrap resampling technique, several subsets are generated from the same basic dataset and for each of them a model is identified to form a set of models. Then, by correlation analysis with the two aforementioned subspaces, highly correlated modes of these models which appear repeatedly are clustered together and the noise modes are collected in a so-called Trashbox cluster. Stray noise modes attracted to the mode clusters are trimmed away in a second step by correlation analysis. The final step of the algorithm is a fuzzy c-means clustering procedure applied to

A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways

Science.gov (United States)

Yang, Yunlai; Arouri, Khaled

2016-03-01

A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

A Simple Geotracer Compositional Correlation Analysis Reveals Oil Charge and Migration Pathways.

Science.gov (United States)

Yang, Yunlai; Arouri, Khaled

2016-03-11

A novel approach, based on geotracer compositional correlation analysis is reported, which reveals the oil charge sequence and migration pathways for five oil fields in Saudi Arabia. The geotracers utilised are carbazoles, a family of neutral pyrrolic nitrogen compounds known to occur naturally in crude oils. The approach is based on the concept that closely related fields, with respect to filling sequence, will show a higher carbazole compositional correlation, than those fields that are less related. That is, carbazole compositional correlation coefficients can quantify the charge and filling relationships among different fields. Consequently, oil migration pathways can be defined based on the established filling relationships. The compositional correlation coefficients of isomers of C1 and C2 carbazoles, and benzo[a]carbazole for all different combination pairs of the five fields were found to vary extremely widely (0.28 to 0.94). A wide range of compositional correlation coefficients allows adequate differentiation of separate filling relationships. Based on the established filling relationships, three distinct migration pathways were inferred, with each apparently being charged from a different part of a common source kitchen. The recognition of these charge and migration pathways will greatly aid the search for new accumulations.

Scalable and Flexible Multiview MAX-VAR Canonical Correlation Analysis

Science.gov (United States)

Fu, Xiao; Huang, Kejun; Hong, Mingyi; Sidiropoulos, Nicholas D.; So, Anthony Man-Cho

2017-08-01

Generalized canonical correlation analysis (GCCA) aims at finding latent low-dimensional common structure from multiple views (feature vectors in different domains) of the same entities. Unlike principal component analysis (PCA) that handles a single view, (G)CCA is able to integrate information from different feature spaces. Here we focus on MAX-VAR GCCA, a popular formulation which has recently gained renewed interest in multilingual processing and speech modeling. The classic MAX-VAR GCCA problem can be solved optimally via eigen-decomposition of a matrix that compounds the (whitened) correlation matrices of the views; but this solution has serious scalability issues, and is not directly amenable to incorporating pertinent structural constraints such as non-negativity and sparsity on the canonical components. We posit regularized MAX-VAR GCCA as a non-convex optimization problem and propose an alternating optimization (AO)-based algorithm to handle it. Our algorithm alternates between {\\em inexact} solutions of a regularized least squares subproblem and a manifold-constrained non-convex subproblem, thereby achieving substantial memory and computational savings. An important benefit of our design is that it can easily handle structure-promoting regularization. We show that the algorithm globally converges to a critical point at a sublinear rate, and approaches a global optimal solution at a linear rate when no regularization is considered. Judiciously designed simulations and large-scale word embedding tasks are employed to showcase the effectiveness of the proposed algorithm.

Econometric analysis of realized covariation: high frequency based covariance, regression, and correlation in financial economics

DEFF Research Database (Denmark)

Barndorff-Nielsen, Ole Eiler; Shephard, N.

2004-01-01

This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....

Reliability Worth Analysis of Distribution Systems Using Cascade Correlation Neural Networks

DEFF Research Database (Denmark)

Heidari, Alireza; Agelidis, Vassilios; Pou, Josep

2018-01-01

Reliability worth analysis is of great importance in the area of distribution network planning and operation. The reliability worth's precision can be affected greatly by the customer interruption cost model used. The choice of the cost models can change system and load point reliability indices....... In this study, a cascade correlation neural network is adopted to further develop two cost models comprising a probabilistic distribution model and an average or aggregate model. A contingency-based analytical technique is adopted to conduct the reliability worth analysis. Furthermore, the possible effects...

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

International Nuclear Information System (INIS)

Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T

2013-01-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods for its correction in correlation analyses have been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows that our method accurately corrects the artificial increase in both types of correlation studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlation examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. While it is demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined. (special issue article)

Uncovering the mechanism(s) of deep brain stimulation

International Nuclear Information System (INIS)

Li Gang; Yu Chao; Lin Ling; Lu, Stephen C-Y

2005-01-01

Deep brain stimulators, often called 'pacemakers for the brain', are implantable devices which continuously deliver impulse stimulation to specific targeted nuclei of deep brain structure, namely deep brain stimulation (DBS). To date, deep brain stimulation (DBS) is the most effective clinical technique for the treatment of several medically refractory movement disorders (e.g., Parkinson's disease, essential tremor, and dystonia). In addition, new clinical applications of DBS for other neurologic and psychiatric disorders (e.g., epilepsy and obsessive-compulsive disorder) have been put forward. Although DBS has been effective in the treatment of movement disorders and is rapidly being explored for the treatment of other neurologic disorders, the scientific understanding of its mechanisms of action remains unclear and continues to be debated in the scientific community. Optimization of DBS technology for present and future therapeutic applications will depend on identification of the therapeutic mechanism(s) of action. The goal of this review is to address our present knowledge of the effects of high-frequency stimulation within the central nervous system and comment on the functional implications of this knowledge for uncovering the mechanism(s) of DBS

NMR-based metabonomics and correlation analysis reveal potential biomarkers associated with chronic atrophic gastritis.

Science.gov (United States)

Cui, Jiajia; Liu, Yuetao; Hu, Yinghuan; Tong, Jiayu; Li, Aiping; Qu, Tingli; Qin, Xuemei; Du, Guanhua

2017-01-05

Chronic atrophic gastritis (CAG) is one of the most important pre-cancerous states with a high prevalence. Exploring of the underlying mechanism and potential biomarkers is of significant importance for CAG. In the present work, 1 H NMR-based metabonomics with correlative analysis was performed to analyze the metabolic features of CAG. 19 plasma metabolites and 18 urine metabolites were enrolled to construct the circulatory and excretory metabolome of CAG, which was in response to alterations of energy metabolism, inflammation, immune dysfunction, as well as oxidative stress. 7 plasma biomarkers and 7 urine biomarkers were screened to elucidate the pathogenesis of CAG based on the further correlation analysis with biochemical indexes. Finally, 3 plasma biomarkers (arginine, succinate and 3-hydroxybutyrate) and 2 urine biomarkers (α-ketoglutarate and valine) highlighted the potential to indicate risks of CAG in virtue of correlation with pepsin activity and ROC analysis. Here, our results paved a way for elucidating the underlying mechanisms in the development of CAG, and provided new avenues for the diagnosis of CAG and presented potential drug targets for treatment of CAG. Copyright © 2016 Elsevier B.V. All rights reserved.

On discriminant analysis techniques and correlation structures in high dimensions

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder

This paper compares several recently proposed techniques for performing discriminant analysis in high dimensions, and illustrates that the various sparse methods dier in prediction abilities depending on their underlying assumptions about the correlation structures in the data. The techniques...... the methods in two: Those who assume independence between the variables and thus use a diagonal estimate of the within-class covariance matrix, and those who assume dependence between the variables and thus use an estimate of the within-class covariance matrix, which also estimates the correlations between...... variables. The two groups of methods are compared and the pros and cons are exemplied using dierent cases of simulated data. The results illustrate that the estimate of the covariance matrix is an important factor with respect to choice of method, and the choice of method should thus be driven by the nature...

Network-based analysis of proteomic profiles

KAUST Repository

Wong, Limsoon

2016-01-26

Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

Science.gov (United States)

Ma, Chuang; Wang, Xiangfeng

2012-09-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

Structural insight to mutation effects uncover a common allosteric site in class C GPCRs

DEFF Research Database (Denmark)

Harpsøe, Kasper; Boesgaard, Michael W; Munk, Christian

2017-01-01

MOTIVATION: Class C G protein-coupled receptors (GPCRs) regulate important physiological functions and allosteric modulators binding to the transmembrane domain constitute an attractive and, due to a lack of structural insight, a virtually unexplored potential for therapeutics and the food industry....... Combining pharmacological site-directed mutagenesis data with the recent class C GPCR experimental structures will provide a foundation for rational design of new therapeutics. RESULTS: We uncover one common site for both positive and negative modulators with different amino acid layouts that can...

Automatic analysis of dividing cells in live cell movies to detect mitotic delays and correlate phenotypes in time.

Science.gov (United States)

Harder, Nathalie; Mora-Bermúdez, Felipe; Godinez, William J; Wünsche, Annelie; Eils, Roland; Ellenberg, Jan; Rohr, Karl

2009-11-01

Live-cell imaging allows detailed dynamic cellular phenotyping for cell biology and, in combination with small molecule or drug libraries, for high-content screening. Fully automated analysis of live cell movies has been hampered by the lack of computational approaches that allow tracking and recognition of individual cell fates over time in a precise manner. Here, we present a fully automated approach to analyze time-lapse movies of dividing cells. Our method dynamically categorizes cells into seven phases of the cell cycle and five aberrant morphological phenotypes over time. It reliably tracks cells and their progeny and can thus measure the length of mitotic phases and detect cause and effect if mitosis goes awry. We applied our computational scheme to annotate mitotic phenotypes induced by RNAi gene knockdown of CKAP5 (also known as ch-TOG) or by treatment with the drug nocodazole. Our approach can be readily applied to comparable assays aiming at uncovering the dynamic cause of cell division phenotypes.

Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System

Science.gov (United States)

Niu, Hongli; Wang, Jun

We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.

Levey-Jennings Analysis Uncovers Unsuspected Causes of Immunohistochemistry Stain Variability.

Science.gov (United States)

Vani, Kodela; Sompuram, Seshi R; Naber, Stephen P; Goldsmith, Jeffrey D; Fulton, Regan; Bogen, Steven A

Almost all clinical laboratory tests use objective, quantitative measures of quality control (QC), incorporating Levey-Jennings analysis and Westgard rules. Clinical immunohistochemistry (IHC) testing, in contrast, relies on subjective, qualitative QC review. The consequences of using Levey-Jennings analysis for QC assessment in clinical IHC testing are not known. To investigate this question, we conducted a 1- to 2-month pilot test wherein the QC for either human epidermal growth factor receptor 2 (HER-2) or progesterone receptor (PR) in 3 clinical IHC laboratories was quantified and analyzed with Levey-Jennings graphs. Moreover, conventional tissue controls were supplemented with a new QC comprised of HER-2 or PR peptide antigens coupled onto 8 μm glass beads. At institution 1, this more stringent analysis identified a decrease in the HER-2 tissue control that had escaped notice by subjective evaluation. The decrement was due to heterogeneity in the tissue control itself. At institution 2, we identified a 1-day sudden drop in the PR tissue control, also undetected by subjective evaluation, due to counterstain variability. At institution 3, a QC shift was identified, but only with 1 of 2 controls mounted on each slide. The QC shift was due to use of the instrument's selective reagent drop zones dispense feature. None of these events affected patient diagnoses. These case examples illustrate that subjective QC evaluation of tissue controls can detect gross assay failure but not subtle changes. The fact that QC issues arose from each site, and in only a pilot study, suggests that immunohistochemical stain variability may be an underappreciated problem.

Correlation Analysis of Personality Characteristics of Children with TIC Disorder with Family Factors

Institute of Scientific and Technical Information of China (English)

LI Rui; WANG Liqun; MA Chunxia; MA Lixian

2016-01-01

Objective To explore the personality characteristics of children with tic disorders and their relationship with family factors.Methods Sixty cases of children with tic disorders diagnosed in our hospital were selected as the case group and 65 cases of normal children were selected as the control group.The children of two groups were assessed using Eysenck Personality Questionnaire (EPQ),Family Environment Scale (FES-CV) and general situation questionnaire of family (GSQ),respectively.The scores of EPQ personality characteristics,FES-CV and GSQ scores were compared for the children in the two groups.The Person correlation analysis method was used to analyze the correlation between personality scores of children in case group and family environment factors.Results The general situation questionnaire results showed that there was significant statistically difference in parenting style,parental education level and family types of the children between case group and control group (P ＜ 0.05);EPQ results showed that the neuroticism and psychoticism scores of children in the case group were significantly higher than those in the control group (P＜ 0.05) and the lying degree scores in the control group were significantly higher than those in the case group (P＜ 0.05);FES-CV results showed that the family cohesion scores of the case group were significantly lower than those of the control group (P＜0.05),and the family conflict scores in the case group were significantly higher than those in the control group (P＜0.05).The Person correlation analysis results indicated that the psychoticism score was negatively correlated with the score of family cohesion (P＜0.05),and positively correlated with family conflict (P＜0.05),while the neuroticism score was positively correlated with family conflict score (P＜0.05).Conclusion The children with tic disorders have significant personality deviation compared to the normal children,and the personality deviation degree is

[Correlation analysis between residual displacement and hip function after reconstruction of acetabular fractures].

Science.gov (United States)

Ma, Kunlong; Fang, Yue; Luan, Fujun; Tu, Chongqi; Yang, Tianfu

2012-03-01

To investigate the relationships between residual displacement of weight-bearing and non weight-bearing zones (gap displacement and step displacement) and hip function by analyzing the CT images after reconstruction of acetabular fractures. The CT measures and clinical outcome were retrospectively analyzed from 48 patients with displaced acetabular fracture between June 2004 and June 2009. All patients were treated by open reduction and internal fixation, and were followed up 24 to 72 months (mean, 36 months); all fractures healed after operation. The residual displacement involved the weight-bearing zone in 30 cases (weight-bearing group), and involved the non weight-bearing zone in 18 cases (non weight-bearing group). The clinical outcomes were evaluated by Merle d'Aubigné-Postel criteria, and the reduction of articular surface by CT images, including the maximums of two indexes (gap displacement and step displacement). All the data were analyzed in accordance with the Spearman rank correlation coefficient analysis. There was strong negative correlation between the hip function and the residual displacement values in weight-bearing group (r(s) = -0.722, P = 0.001). But there was no correlation between the hip function and the residual displacement values in non weight-bearing group (r(s) = 0.481, P = 0.059). The results of clinical follow-up were similar to the correlation analysis results. In weight-bearing group, the hip function had strong negative correlation with step displacement (r(s) = 0.825, P = 0.002), but it had no correlation with gap displacement (r(s) = 0.577, P = 0.134). In patients with acetabular fracture, the hip function has correlation not only with the extent of the residual displacement but also with the location of the residual displacement, so the residual displacement of weight-bearing zone is a key factor to affect the hip function. In patients with residual displacement in weight-bearing zone, the bigger the step displacement is, the

Research on criticality analysis method of CNC machine tools components under fault rate correlation

Science.gov (United States)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

The proteome and phosphoproteome of maize pollen uncovers fertility candidate proteins.

Science.gov (United States)

Chao, Qing; Gao, Zhi-Fang; Wang, Yue-Feng; Li, Zhe; Huang, Xia-He; Wang, Ying-Chun; Mei, Ying-Chang; Zhao, Biligen-Gaowa; Li, Liang; Jiang, Yu-Bo; Wang, Bai-Chen

2016-06-01

Maize is unique since it is both monoecious and diclinous (separate male and female flowers on the same plant). We investigated the proteome and phosphoproteome of maize pollen containing modified proteins and here we provide a comprehensive pollen proteome and phosphoproteome which contain 100,990 peptides from 6750 proteins and 5292 phosphorylated sites corresponding to 2257 maize phosphoproteins, respectively. Interestingly, among the total 27 overrepresented phosphosite motifs we identified here, 11 were novel motifs, which suggested different modification mechanisms in plants compared to those of animals. Enrichment analysis of pollen phosphoproteins showed that pathways including DNA synthesis/chromatin structure, regulation of RNA transcription, protein modification, cell organization, signal transduction, cell cycle, vesicle transport, transport of ions and metabolisms, which were involved in pollen development, the following germination and pollen tube growth, were regulated by phosphorylation. In this study, we also found 430 kinases and 105 phosphatases in the maize pollen phosphoproteome, among which calcium dependent protein kinases (CDPKs), leucine rich repeat kinase, SNF1 related protein kinases and MAPK family proteins were heavily enriched and further analyzed. From our research, we also uncovered hundreds of male sterility-associated proteins and phosphoproteins that might influence maize productivity and serve as targets for hybrid maize seed production. At last, a putative complex signaling pathway involving CDPKs, MAPKs, ubiquitin ligases and multiple fertility proteins was constructed. Overall, our data provides new insight for further investigation of protein phosphorylation status in mature maize pollen and construction of maize male sterile mutants in the future.

Multivariate correlation analysis of eye cyclotorsion degree in corneal refractive surgery

Directory of Open Access Journals (Sweden)

Xiao-Guang Niu

2015-06-01

Full Text Available AIM: To explore the correlation between eye cyclotorsion degrees and patient's age, gender, diopter and other factors in corneal refractive surgery. METHODS: A total of 762 wavefront-guided LASIK patients with 1524 eyes were retrospectively analyzed from January 2010 to December 2013 in our hospital. Iris recognition was accomplished successfully and eye cyclotorsion degrees were recorded intraoperatively for all the patients. The correlations between eye cyclotorsion degrees and patient's age, gender, different eye, diopter and the dominant eye or not were statistically analyzed. In which correlation analysis was used to analyze the relationship between eye cyclotorsion degrees and age and diopter, while the correlations with gender, different eye and the dominant eye or not were analyzed using t-test.RESULTS: The eye cyclotorsion degrees of patients were 0 to 9.7 degrees with an average of 3.08±2.22 degrees. Amongst the average cyclotorsion of 444 men with 888 eyes were 3.05±2.26 degrees, 318 women with 636 eyes were 3.12±2.15 degrees and there were no significant differences(t=1.905, P=0.168. The average age of all the patients was 22.6±5.4y. No significant correlation was found between cyclotorsion degrees and age(r=-0.012, P=0.748. The mean spherical equivalent was -4.76±1.77 degrees, and there was no significant correlation between the eye cyclotorsion degrees and spherical equivalent(r=0.017, P=0.633. The mean cylinder was -0.60±0.64 degrees of no significant correlation with eye cyclotorsion degrees(r=-0.004, P=0.910. The cyclotorsion of dominant eyes of all the patients was 3.0±2.17 degrees, and the non-dominant eyes were 3.11±2.12 degrees. No significant differences were found(t=-0.521,P=0.603. CONCLUSION: The eye cyclotorsion degrees occurred in LASIK surgery had no correlation with age, gender, different eye, diopter and the dominant eye or not.

Personality Traits as Predictors of Shopping Motivations and Behaviors: A Canonical Correlation Analysis

Directory of Open Access Journals (Sweden)

Ali Gohary

2014-10-01

Full Text Available This study examines the relationship between Big Five personality traits with shopping motivation variables consisting of compulsive and impulsive buying, hedonic and utilitarian shopping values. Two hundred forty seven college students were recruited to participate in this research. Bivariate correlation demonstrates an overlap between personality traits; consequently, canonical correlation was performed to prevent this phenomenon. The results of multiple regression analysis suggested conscientiousness, neuroticism and openness as predictors of compulsive buying, impulsive buying and utilitarian shopping values. In addition, the results showed significant differences between males and females on conscientiousness, neuroticism, openness, compulsive buying and hedonic shopping value. Besides, using hierarchical regression analysis, we examined sex as moderator between Big Five personality traits and shopping variables, but we didn’t find sufficient evidence to prove it.

Estimation of the biserial correlation and its sampling variance for use in meta-analysis.

Science.gov (United States)

Jacobs, Perke; Viechtbauer, Wolfgang

2017-06-01

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying continuous variables. Unlike the point-biserial correlation coefficient, biserial correlation coefficients can therefore be integrated with product-moment correlation coefficients in the same meta-analysis. The present article describes the estimation of the biserial correlation coefficient for meta-analytic purposes and reports simulation results comparing different methods for estimating the coefficient's sampling variance. The findings indicate that commonly employed methods yield inconsistent estimates of the sampling variance across a broad range of research situations. In contrast, consistent estimates can be obtained using two methods that appear to be unknown in the meta-analytic literature. A variance-stabilizing transformation for the biserial correlation coefficient is described that allows for the construction of confidence intervals for individual coefficients with close to nominal coverage probabilities in most of the examined conditions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Gene coexpression network analysis of fruit transcriptomes uncovers a possible mechanistically distinct class of sugar/acid ratio-associated genes in sweet orange.

Science.gov (United States)

Qiao, Liang; Cao, Minghao; Zheng, Jian; Zhao, Yihong; Zheng, Zhi-Liang

2017-10-30

The ratio of sugars to organic acids, two of the major metabolites in fleshy fruits, has been considered the most important contributor to fruit sweetness. Although accumulation of sugars and acids have been extensively studied, whether plants evolve a mechanism to maintain, sense or respond to the fruit sugar/acid ratio remains a mystery. In a prior study, we used an integrated systems biology tool to identify a group of 39 acid-associated genes from the fruit transcriptomes in four sweet orange varieties (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). We reanalyzed the prior sweet orange fruit transcriptome data, leading to the identification of 72 genes highly correlated with the fruit sugar/acid ratio. The majority of these sugar/acid ratio-related genes are predicted to be involved in regulatory functions such as transport, signaling and transcription or encode enzymes involved in metabolism. Surprisingly, only three of these sugar/acid ratio-correlated genes are weakly correlated with sugar level and none of them overlaps with the acid-associated genes. Weighted Gene Coexpression Network Analysis (WGCNA) has revealed that these genes belong to four modules, Blue, Grey, Brown and Turquoise, with the former two modules being unique to the sugar/acid ratio control. Our results indicate that orange fruits contain a possible mechanistically distinct class of genes that may potentially be involved in maintaining fruit sugar/acid ratios and/or responding to the cellular sugar/acid ratio status. Therefore, our analysis of orange transcriptomes provides an intriguing insight into the potentially novel genetic or molecular mechanisms controlling the sugar/acid ratio in fruits.

Knowledge Enrichment Analysis for Human Tissue- Specific Genes Uncover New Biological Insights

Directory of Open Access Journals (Sweden)

Gong Xiu-Jun

2012-06-01

Full Text Available The expression and regulation of genes in different tissues are fundamental questions to be answered in biology. Knowledge enrichment analysis for tissue specific (TS and housekeeping (HK genes may help identify their roles in biological process or diseases and gain new biological insights.In this paper, we performed the knowledge enrichment analysis for 17,343 genes in 84 human tissues using Gene Set Enrichment Analysis (GSEA and Hypergeometric Analysis (HA against three biological ontologies: Gene Ontology (GO, KEGG pathways and Disease Ontology (DO respectively.The analyses results demonstrated that the functions of most gene groups are consistent with their tissue origins. Meanwhile three interesting new associations for HK genes and the skeletal muscle tissuegenes are found. Firstly, Hypergeometric analysis against KEGG database for HK genes disclosed that three disease terms (Parkinson’s disease, Huntington’s disease, Alzheimer’s disease are intensively enriched.Secondly, Hypergeometric analysis against the KEGG database for Skeletal Muscle tissue genes shows that two cardiac diseases of “Hypertrophic cardiomyopathy (HCM” and “Arrhythmogenic right ventricular cardiomyopathy (ARVC” are heavily enriched, which are also considered as no relationship with skeletal functions.Thirdly, “Prostate cancer” is intensively enriched in Hypergeometric analysis against the disease ontology (DO for the Skeletal Muscle tissue genes, which is a much unexpected phenomenon.

Health Detectives: Uncovering the Mysteries of Disease (LBNL Science at the Theater)

Energy Technology Data Exchange (ETDEWEB)

Bissell, Mina; Canaria, Christie; Celnicker, Susan; Karpen, Gary

2012-04-23

In this April 23, 2012 Science at the Theater event, Berkeley Lab scientists discuss how they uncover the mysteries of disease in unlikely places. Speakers and topics include: World-renowned cancer researcher Mina Bissell's pioneering research on the role of the cellular microenvironment in breast cancer has changed the conversation about the disease. How does DNA instability cause disease? To find out, Christie Canaria images neural networks to study disorders such as Huntington's disease. Fruit flies can tell us a lot about ourselves. Susan Celniker explores the fruit fly genome to learn how our genome works. DNA is not destiny. Gary Karpen explores how environmental factors shape genome function and disease through epigenetics.

Quantum diffraction and interference of spatially correlated photon pairs and its Fourier-optical analysis

International Nuclear Information System (INIS)

Shimizu, Ryosuke; Edamatsu, Keiichi; Itoh, Tadashi

2006-01-01

We present one- and two-photon diffraction and interference experiments involving parametric down-converted photon pairs. By controlling the divergence of the pump beam in parametric down-conversion, the diffraction-interference pattern produced by an object changes from a quantum (perfectly correlated) case to a classical (uncorrelated) one. The observed diffraction and interference patterns are accurately reproduced by Fourier-optical analysis taking into account the quantum spatial correlation. We show that the relation between the spatial correlation and the object size plays a crucial role in the formation of both one- and two-photon diffraction-interference patterns

Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients

DEFF Research Database (Denmark)

Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte

2017-01-01

-derived food waste amounted to 2.21 ± 3.12% with a confidence interval of (−4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson’s correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste...... and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data......, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients....

Multifractal detrended cross-correlation analysis on gold, crude oil and foreign exchange rate time series

Science.gov (United States)

Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.

2014-12-01

We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.

Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

Directory of Open Access Journals (Sweden)

Yang Dan

2008-12-01

Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

Energy Technology Data Exchange (ETDEWEB)

Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)

2017-01-15

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

Generalized canonical correlation analysis of matrices with missing rows : A simulation study

NARCIS (Netherlands)

van de Velden, Michel; Bijmolt, Tammo H. A.

A method is presented for generalized canonical correlation analysis of two or more matrices with missing rows. The method is a combination of Carroll's (1968) method and the missing data approach of the OVERALS technique (Van der Burg, 1988). In a simulation study we assess the performance of the

Network analysis reveals that bacteria and fungi form modules that correlate independently with soil parameters.

Science.gov (United States)

de Menezes, Alexandre B; Prendergast-Miller, Miranda T; Richardson, Alan E; Toscas, Peter; Farrell, Mark; Macdonald, Lynne M; Baker, Geoff; Wark, Tim; Thrall, Peter H

2015-08-01

Network and multivariate statistical analyses were performed to determine interactions between bacterial and fungal community terminal restriction length polymorphisms as well as soil properties in paired woodland and pasture sites. Canonical correspondence analysis (CCA) revealed that shifts in woodland community composition correlated with soil dissolved organic carbon, while changes in pasture community composition correlated with moisture, nitrogen and phosphorus. Weighted correlation network analysis detected two distinct microbial modules per land use. Bacterial and fungal ribotypes did not group separately, rather all modules comprised of both bacterial and fungal ribotypes. Woodland modules had a similar fungal : bacterial ribotype ratio, while in the pasture, one module was fungal dominated. There was no correspondence between pasture and woodland modules in their ribotype composition. The modules had different relationships to soil variables, and these contrasts were not detected without the use of network analysis. This study demonstrated that fungi and bacteria, components of the soil microbial communities usually treated as separate functional groups as in a CCA approach, were co-correlated and formed distinct associations in these adjacent habitats. Understanding these distinct modular associations may shed more light on their niche space in the soil environment, and allow a more realistic description of soil microbial ecology and function. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Asymmetric correlation matrices: an analysis of financial data

Science.gov (United States)

Livan, G.; Rebecchi, L.

2012-06-01

We analyse the spectral properties of correlation matrices between distinct statistical systems. Such matrices are intrinsically non-symmetric, and lend themselves to extend the spectral analyses usually performed on standard Pearson correlation matrices to the realm of complex eigenvalues. We employ some recent random matrix theory results on the average eigenvalue density of this type of matrix to distinguish between noise and non-trivial correlation structures, and we focus on financial data as a case study. Namely, we employ daily prices of stocks belonging to the American and British stock exchanges, and look for the emergence of correlations between two such markets in the eigenvalue spectrum of their non-symmetric correlation matrix. We find several non trivial results when considering time-lagged correlations over short lags, and we corroborate our findings by additionally studying the asymmetric correlation matrix of the principal components of our datasets.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Science.gov (United States)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

Directory of Open Access Journals (Sweden)

Jinchao Feng

2018-03-01

Full Text Available We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data. The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

Science.gov (United States)

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill

2013-02-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.

Statistical analysis of solid waste composition data: Arithmetic mean, standard deviation and correlation coefficients.

Science.gov (United States)

Edjabou, Maklawe Essonanawe; Martín-Fernández, Josep Antoni; Scheutz, Charlotte; Astrup, Thomas Fruergaard

2017-11-01

Data for fractional solid waste composition provide relative magnitudes of individual waste fractions, the percentages of which always sum to 100, thereby connecting them intrinsically. Due to this sum constraint, waste composition data represent closed data, and their interpretation and analysis require statistical methods, other than classical statistics that are suitable only for non-constrained data such as absolute values. However, the closed characteristics of waste composition data are often ignored when analysed. The results of this study showed, for example, that unavoidable animal-derived food waste amounted to 2.21±3.12% with a confidence interval of (-4.03; 8.45), which highlights the problem of the biased negative proportions. A Pearson's correlation test, applied to waste fraction generation (kg mass), indicated a positive correlation between avoidable vegetable food waste and plastic packaging. However, correlation tests applied to waste fraction compositions (percentage values) showed a negative association in this regard, thus demonstrating that statistical analyses applied to compositional waste fraction data, without addressing the closed characteristics of these data, have the potential to generate spurious or misleading results. Therefore, ¨compositional data should be transformed adequately prior to any statistical analysis, such as computing mean, standard deviation and correlation coefficients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Resilience among caregivers of children with chronic conditions: a concept analysis

Directory of Open Access Journals (Sweden)

Lin FY

2013-08-01

Full Text Available Fang-Yi Lin, Jiin-Ru Rong, Tzu-Ying Lee Department of Nursing, School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan, Republic of China Abstract: The purpose of this concept analysis is to uncover the essential elements involved in caregivers' resilience in the context of caring for children with chronic conditions. Walker and Avant's methodology guided the analysis. The study includes a literature review of conceptual definitions of caregiver resilience in caring for children with chronic conditions. The defining attributes and correlates of caregiver resilience are reviewed. Concept analysis findings in a review of the nursing and health-related literature show that caregiver resilience in the context of caring for chronically ill children can be defined within four main dimensions, ie, disposition patterns, situational patterns, relational patterns, and cultural patterns. Empiric measurements of the impact of caregiver resilience applied to caregivers with children with chronic conditions are also reported in the analysis. The findings of this concept analysis could help nurses and health care providers to apply the concept of caregiver resilience in allied health care and be applied to further studies. Keywords: caregiver resilience, children, chronic conditions, concept analysis

An Econometric Analysis of Modulated Realised Covariance, Regression and Correlation in Noisy Diffusion Models

DEFF Research Database (Denmark)

Kinnebrock, Silja; Podolskij, Mark

This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....

New insights into the correlation structure of DSM-IV depression symptoms in the general population v. subsamples of depressed individuals.

Science.gov (United States)

Foster, S; Mohler-Kuo, M

2018-06-01

Previous research failed to uncover a replicable dimensional structure underlying the symptoms of depression. We aimed to examine two neglected methodological issues in this research: (a) adjusting symptom correlations for overall depression severity; and (b) analysing general population samples v. subsamples of currently depressed individuals. Using population-based cross-sectional and longitudinal data from two nations (Switzerland, 5883 young men; USA, 2174 young men and 2244 young women) we assessed the dimensions of the nine DSM-IV depression symptoms in young adults. In each general-population sample and each subsample of currently depressed participants, we conducted a standardised process of three analytical steps, based on exploratory and confirmatory factor and bifactor analysis, to reveal any replicable dimensional structure underlying symptom correlations while controlling for overall depression severity. We found no evidence of a replicable dimensional structure across samples when adjusting symptom correlations for overall depression severity. In the general-population samples, symptoms correlated strongly and a single dimension of depression severity was revealed. Among depressed participants, symptom correlations were surprisingly weak and no replicable dimensions were identified, regardless of severity-adjustment. First, caution is warranted when considering studies assessing dimensions of depression because general population-based studies and studies of depressed individuals generate different data that can lead to different conclusions. This problem likely generalises to other models based on the symptoms' inter-relationships such as network models. Second, whereas the overall severity aligns individuals on a continuum of disorder intensity that allows non-affected individuals to be distinguished from affected individuals, the clinical evaluation and treatment of depressed individuals should focus directly on each individual's symptom profile.

Meta-Analysis of the Correlation between Apparent Diffusion Coefficient and Standardized Uptake Value in Malignant Disease.

Science.gov (United States)

Deng, Shengming; Wu, Zhifang; Wu, Yiwei; Zhang, Wei; Li, Jihui; Dai, Na; Zhang, Bin; Yan, Jianhua

2017-01-01

The objective of this meta-analysis is to explore the correlation between the apparent diffusion coefficient (ADC) on diffusion-weighted MR and the standard uptake value (SUV) of 18 F-FDG on PET/CT in patients with cancer. Databases such as PubMed (MEDLINE included), EMBASE, and Cochrane Database of Systematic Review were searched for relevant original articles that explored the correlation between SUV and ADC in English. After applying Fisher's r -to- z transformation, correlation coefficient ( r ) values were extracted from each study and 95% confidence intervals (CIs) were calculated. Sensitivity and subgroup analyses based on tumor type were performed to investigate the potential heterogeneity. Forty-nine studies were eligible for the meta-analysis, comprising 1927 patients. Pooled r for all studies was -0.35 (95% CI: -0.42-0.28) and exhibited a notable heterogeneity ( I 2 = 78.4%; P correlation coefficients of ADC/SUV range from -0.12 (lymphoma, n = 5) to -0.59 (pancreatic cancer, n = 2). We concluded that there is an average negative correlation between ADC and SUV in patients with cancer. Higher correlations were found in the brain tumor, cervix carcinoma, and pancreas cancer. However, a larger, prospective study is warranted to validate these findings in different cancer types.

Revelando sentidos na prática docente: a abordagem de corpus na análise do discurso Uncovering meanings in pedagogical practice: the corpus approach in discourse analysis

Directory of Open Access Journals (Sweden)

Vander Viana

2011-01-01

Full Text Available Este artigo discute a viabilidade da utilização de ferramentas da Linguística de Corpus na análise do discurso pedagógico. Para tanto, são apresentados dois estudos de caso. O primeiro focaliza o discurso de professores de língua inglesa de um renomado curso de idiomas do Rio de Janeiro acerca da implementação de recursos tecnológicos na sala de aula. O segundo estudo, por sua vez, busca perceber qual é o posicionamento de professores universitários de literaturas em língua inglesa sobre literatura e seu ensino. Os resultados apontam para a riqueza dos dados contextuais que podem ser depreendidos a partir de uma análise linguística de base empírica. Em última análise, o artigo revela a importância e a flexibilidade da abordagem de corpus na análise do discurso, que pode ser aplicada a inúmeros contextos.This paper discusses the feasibility of using Corpus Linguistics tools in the analysis of pedagogic discourse. For doing this, two case studies are presented. The first one focuses on the discourse of English language teachers of a well-known languages course in Rio de Janeiro about the implementation of technological resources in the classroom. The second study, in its turn, seeks to realize the position held by university professors of literatures in English language with regard to literature and its teaching. The results point out to the richness of contextual data which can be inferred from a linguistic analysis with an empirical basis. All in all, the paper uncovers the importance and flexibility of the corpus approach in discourse analysis, which may be applied to several contexts.

Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.

Science.gov (United States)

Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver

2018-02-15

Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R

Analysis of Baryon Angular Correlations with Pythia

CERN Document Server

Mccune, Amara

2017-01-01

Our current understanding of baryon production is encompassed in the framework of the Lund String Fragmentation Model, which is then encoded in the Monte Carlo event generator program Pythia. In proton-proton collisions, daughter particles of the same baryon number produce an anti-correlation in $\\Delta\\eta\\Delta\\varphi$ space in ALICE data, while Pythia programs predict a correlation. To understand this unusual effect, where it comes from, and where our models of baryon production go wrong, correlation functions were systematically generated with Pythia. Effects of energy scaling, color reconnection, and popcorn parameters were investigated.

Regression of uveal malignant melanomas following cobalt-60 plaque. Correlates between acoustic spectrum analysis and tumor regression

International Nuclear Information System (INIS)

Coleman, D.J.; Lizzi, F.L.; Silverman, R.H.; Ellsworth, R.M.; Haik, B.G.; Abramson, D.H.; Smith, M.E.; Rondeau, M.J.

1985-01-01

Parameters derived from computer analysis of digital radio-frequency (rf) ultrasound scan data of untreated uveal malignant melanomas were examined for correlations with tumor regression following cobalt-60 plaque. Parameters included tumor height, normalized power spectrum and acoustic tissue type (ATT). Acoustic tissue type was based upon discriminant analysis of tumor power spectra, with spectra of tumors of known pathology serving as a model. Results showed ATT to be correlated with tumor regression during the first 18 months following treatment. Tumors with ATT associated with spindle cell malignant melanoma showed over twice the percentage reduction in height as those with ATT associated with mixed/epithelioid melanomas. Pre-treatment height was only weakly correlated with regression. Additionally, significant spectral changes were observed following treatment. Ultrasonic spectrum analysis thus provides a noninvasive tool for classification, prediction and monitoring of tumor response to cobalt-60 plaque

The discriminatory analysis about factors correlative with the early hypothyroidism after 131I therapy for hyperthyroidism

International Nuclear Information System (INIS)

Xiong Lingjing; Liang Changhua; Deng Haoyu; Li Xinhui; Hu Shuo

2002-01-01

Objective: To explore the factors correlative with the early hypothyroidism after 131 I therapy for Graves' hyperthyroidism so as to cure it and decrease the early hypothyroidism occurring and prevent it from becoming irreversible hypothyroidism. Methods: Logistic regression discriminatory analysis by introducing multiple factors from group data and forward stepwise selection of 11 independent variables of 240 hyperthyroidism patients from clinical data and 1 dependent variable from follow-up data after 131 I therapy was conducted. Univariate analysis of each observed factor was performed, too. Results: (1)The results of multivariate analysis showed that the age of patients, the weight of thyroid, the suffering situation, the curve of 131 I absorption rate and the giving 131 I dosage/g thyroid tissue were correlated to early hypothyroidism. The results of univariate analysis showed that the weight of thyroid, the highest absorption of 131 I, the total treatment dosage of 131 I were correlated to early hypothyroidism. (2) The logistic regression equation was statistically significant. (3) The positive and negative predicting accuracy of the early hypothyroidism occurring was 64.08 %, 78.83 %, respectively, the overall predicting accuracy was 72.50%. Conclusions: The dosage of 131 I for treatment of hyperthyroid is the key factor according to the five correlative factors which are relating to the early hypothyroidism and the discriminatory classification. Enhanced follow-up and in time supplement of thyroid hormone are important measures for preventing the early hypothyroidism from becoming irreversible hypothyroidism

Heuristic Artificial Bee Colony Algorithm for Uncovering Community in Complex Networks

Directory of Open Access Journals (Sweden)

Yuquan Guo

2017-01-01

Full Text Available Community structure is important for us to understand the functions and structure of the complex networks. In this paper, Heuristic Artificial Bee Colony (HABC algorithm based on swarm intelligence is proposed for uncovering community. The proposed HABC includes initialization, employed bee searching, onlooker searching, and scout bee searching. In initialization stage, the nectar sources with simple community structure are generated through network dynamic algorithm associated with complete subgraph. In employed bee searching and onlooker searching stages, the searching function is redefined to address the community problem. The efficiency of searching progress can be improved by a heuristic function which is an average agglomerate probability of two neighbor communities. Experiments are carried out on artificial and real world networks, and the results demonstrate that HABC will have better performance in terms of comparing with the state-of-the-art algorithms.

Climate Prediction Center (CPC)Ensemble Canonical Correlation Analysis 90-Day Seasonal Forecast of Precipitation

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Ensemble Canonical Correlation Analysis (ECCA) precipitation forecast is a 90-day (seasonal) outlook of US surface precipitation anomalies. The ECCA uses...

Correlation among the spectral parameters for qualitative analysis of Alpha Liquid Scintillation Spectra

International Nuclear Information System (INIS)

Bhade, Sonali P.D.; Reddy, P.J.; Kolekar, R.V.; Singh, Rajvir; Pradeepkumar, K.S.

2014-01-01

The potential use of alpha LSC technique is nowadays recognized widely. However the energy resolution of α particle is poor with liquid scintillators. Moreover, α peak positions are influenced by the level of quenching in the samples. To overcome this problem, a thorough study of all concerned parameters that affect spectral information was carried out. The parameters such as peak's centroid, quenching, % resolution, energy of α particle were investigated and the correlation between them was evaluated. In the present work, the qualitative analysis of α spectrum was carried out. Correlations between the energy of α particle and various parameters affecting the peaks of the collected spectra with respect to quenching were established. These correlations will be useful for the deconvolution studies of composite samples containing different alpha radionuclides

Uncertainty evaluation in correlated quantities: application to elemental analysis of atmospheric aerosols

International Nuclear Information System (INIS)

Espinosa, A.; Miranda, J.; Pineda, J. C.

2010-01-01

One of the aspects that are frequently overlooked in the evaluation of uncertainty in experimental data is the possibility that the involved quantities are correlated among them, due to different causes. An example in the elemental analysis of atmospheric aerosols using techniques like X-ray Fluorescence (X RF) or Particle Induced X-ray Emission (PIXE). In these cases, the measured elemental concentrations are highly correlated, and then are used to obtain information about other variables, such as the contribution from emitting sources related to soil, sulfate, non-soil potassium or organic matter. This work describes, as an example, the method required to evaluate the uncertainty in variables determined from correlated quantities from a set of atmospheric aerosol samples collected in the Metropolitan Area of the Mexico Valley and analyzed with PIXE. The work is based on the recommendations of the Guide for the Evaluation of Uncertainty published by the International Organization for Standardization. (Author)

Statistical analysis of angular correlation measurements

International Nuclear Information System (INIS)

Oliveira, R.A.A.M. de.

1986-01-01

Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author) [pt

Characterizing the correlations between local phase fractions of gas–liquid two-phase flow with wire-mesh sensor

Science.gov (United States)

Liu, W. L.; Dong, F.

2016-01-01

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas–liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas–liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue ‘Supersensing through industrial process tomography’. PMID:27185959

Characterizing the correlations between local phase fractions of gas-liquid two-phase flow with wire-mesh sensor.

Science.gov (United States)

Tan, C; Liu, W L; Dong, F

2016-06-28

Understanding of flow patterns and their transitions is significant to uncover the flow mechanics of two-phase flow. The local phase distribution and its fluctuations contain rich information regarding the flow structures. A wire-mesh sensor (WMS) was used to study the local phase fluctuations of horizontal gas-liquid two-phase flow, which was verified through comparing the reconstructed three-dimensional flow structure with photographs taken during the experiments. Each crossing point of the WMS is treated as a node, so the measurement on each node is the phase fraction in this local area. An undirected and unweighted flow pattern network was established based on connections that are formed by cross-correlating the time series of each node under different flow patterns. The structure of the flow pattern network reveals the relationship of the phase fluctuations at each node during flow pattern transition, which is then quantified by introducing the topological index of the complex network. The proposed analysis method using the WMS not only provides three-dimensional visualizations of the gas-liquid two-phase flow, but is also a thorough analysis for the structure of flow patterns and the characteristics of flow pattern transition. This article is part of the themed issue 'Supersensing through industrial process tomography'. © 2016 The Author(s).

Uncovering configurations of HRM service provider intellectual capital and worker human capital for creating high HRM service value using fsQCA

NARCIS (Netherlands)

Meijerink, Jeroen Gerard; Bondarouk, Tatiana

Although traditionally applied independently, this study combines two theoretical perspectives – the intellectual capital theory and the consumer perspective – to uncover value-creating configurations of human resource management (HRM) service providers' and workers' knowledge resources. We examined

Phenomenological analysis of quantum level correlations and classical repulsion effects in SU(3) model

International Nuclear Information System (INIS)

Fujiwara, Shigeyasu; Sakata, Fumihiko

2003-01-01

The quantum level fluctuation in various systems has been shown to be characterized by the random matrix theory, and to be related to a regular-to-chaos transition in classical system. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of quantum level density is inversely proportional to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)

Inflatable penile prosthesis implant length with baseline characteristic correlations: preliminary analysis of the PROPPER study.

Science.gov (United States)

Bennett, Nelson; Henry, Gerard; Karpman, Edward; Brant, William; Jones, LeRoy; Khera, Mohit; Kohler, Tobias; Christine, Brian; Rhee, Eugene; Kansas, Bryan; Bella, Anthony J

2017-12-01

"Prospective Registry of Outcomes with Penile Prosthesis for Erectile Restoration" (PROPPER) is a large, multi-institutional, prospective clinical study to collect, analyze, and report real-world outcomes for men implanted with penile prosthetic devices. We prospectively correlated co-morbid conditions and demographic data with implanted penile prosthesis size to enable clinicians to better predict implanted penis size following penile implantation. We present many new data points for the first time in the literature and postulate that radical prostatectomy (RP) is negatively correlated with penile corporal length. Patient demographics, medical history, baseline characteristics and surgical details were compiled prospectively. Pearson correlation coefficient was generated for the correlation between demographic, etiology of ED, duration of ED, co-morbid conditions, pre-operative penile length (flaccid and stretched) and length of implanted penile prosthesis. Multivariate analysis was performed to define predictors of implanted prosthesis length. From June 2011 to June 2017, 1,135 men underwent primary implantation of penile prosthesis at a total of 11 study sites. Malleable (Spectra), 2-piece Ambicor, and 3-piece AMS 700 CX/LGX were included in the analysis. The most common patient comorbidities were CV disease (26.1%), DM (11.1%), and PD (12.4%). Primary etiology of ED: RP (27.4%), DM (20.3%), CVD (18.0%), PD (10.3%), and Priapism (1.4%), others (22.6%). Mean duration of ED is 6.2¡À4.1 years. Implant length was weakly negatively correlated with White/Caucasian (r=-0.18; Pprosthesis length is negatively correlated with some ethnic groups, prostatectomy, and incontinence. Positive correlates include CV disease, preoperative stretched penile length, and flaccid penile length.

Quantifying NMR relaxation correlation and exchange in articular cartilage with time domain analysis

Science.gov (United States)

Mailhiot, Sarah E.; Zong, Fangrong; Maneval, James E.; June, Ronald K.; Galvosas, Petrik; Seymour, Joseph D.

2018-02-01

Measured nuclear magnetic resonance (NMR) transverse relaxation data in articular cartilage has been shown to be multi-exponential and correlated to the health of the tissue. The observed relaxation rates are dependent on experimental parameters such as solvent, data acquisition methods, data analysis methods, and alignment to the magnetic field. In this study, we show that diffusive exchange occurs in porcine articular cartilage and impacts the observed relaxation rates in T1-T2 correlation experiments. By using time domain analysis of T2-T2 exchange spectroscopy, the diffusive exchange time can be quantified by measurements that use a single mixing time. Measured characteristic times for exchange are commensurate with T1 in this material and so impacts the observed T1 behavior. The approach used here allows for reliable quantification of NMR relaxation behavior in cartilage in the presence of diffusive fluid exchange between two environments.

Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging

OpenAIRE

Natalia Y Bilenko; Jack L Gallant; Jack L Gallant

2016-01-01

In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Py...

Covariance, correlation matrix, and the multiscale community structure of networks.

Science.gov (United States)

Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing

2010-07-01

Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.

Analysis of Correlation Tendency between Wind and Solar from Various Spatio-temporal Perspectives

Science.gov (United States)

Wang, X.; Weihua, X.; Mei, Y.

2017-12-01

Analysis of correlation between wind resources and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by the fossil energy. In this paper, we discuss the correlation between wind and solar from various spatio-temporal perspectives (from east to west, in terms of plain, plateau, hill, and mountain, from hourly to daily, ten days and monthly) with observed data and modeled data from NOAA (National Oceanic and Atmospheric Administration) and NERL (National Renewable Energy Laboratory). With investigation of wind speed time series and solar radiation time series (period: 10 years, resolution: 1h) of 72 stations located in various landform and distributed dispersedly in USA, the results show that the correlation coefficient, Kendall's rank correlation coefficient, changes negative to positive value from east coast to west coast of USA, and this phenomena become more obvious when the time scale of resolution increases from daily to ten days and monthly. Furthermore, considering the differences of landforms which influence the local meteorology the Kendall coefficients of diverse topographies are compared and it is found that the coefficients descend from mountain to hill, plateau and plain. However, no such evident tendencies could be found in daily scale. According to this research, it is proposed that the complementary feature of wind resources and solar resources in the east or in the mountain area of USA is conspicuous. Subsequent study would try to further verify this analysis by investigating the operation status of wind power station and solar power station.

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

Science.gov (United States)

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

On minimizing the influence of the noise tail of correlation functions in operational modal analysis

DEFF Research Database (Denmark)

Tarpø, Marius; Olsen, Peter; Amador, Sandro

2017-01-01

on the identification results (random errors) when the noise tail is included in the identification. On the other hand, if the correlation function is truncated too much, then important information is lost. In other to minimize this error, a suitable truncation based on manual inspection of the correlation function......In operational modal analysis (OMA) correlation functions are used by all classical time-domain modal identification techniques that uses the impulse response function (free decays) as primary data. However, the main difference between the impulse response and the correlation functions estimated...... from the operational responses is that the latter present a higher noise level. This is due to statistical errors in the estimation of the correlation function and it causes random noise in the end of the function and this is called the noise tail. This noise might have significant influence...

Digital image correlation in analysis of striffness in local zones of welded joints

Czech Academy of Sciences Publication Activity Database

Milosevic, M.; Milosevic, N.J.; Sedmak, S.; Tatic, U.; Mitrovic, N.; Hloch, Sergej; Jovicic, R.

2016-01-01

Roč. 23, č. 1 (2016), s. 19-24 ISSN 1330-3651 Institutional support: RVO:68145535 Keywords : Aramis software * digital image correlation * strain analysis * stiffness * welded joints Subject RIV: JQ - Machines ; Tools Impact factor: 0.723, year: 2016 http://hrcak.srce.hr/file/225545

Thanatophoric dysplasia. Correlation among bone X-ray morphometry, histopathology, and gene analysis

International Nuclear Information System (INIS)

Pazzaglia, Ugo E.; Donzelli, Carla M.; Izzi, Claudia; Baldi, Maurizia; Di Gaetano, Giuseppe; Bondioni, MariaPia

2014-01-01

Documentation through X-ray morphometry and histology of the steady phenotype expressed by FGFR3 gene mutation and interpolation of mechanical factors on spine and long bones dysmorphism. Long bones and spine of eight thanatophoric dysplasia and three age-matched controls without skeletal dysplasia were studied after pregnancy termination between the 18th and the 22nd week with X-ray morphometry, histology, and molecular analysis. Statistical analysis with comparison between TD cases and controls and intraobserver/interobserver variation were applied to X-ray morphometric data. Generalized shortening of long bones was observed in TD. A variable distribution of axial deformities was correlated with chondrocyte proliferation inhibition, defective seriate cell columns organization, and final formation of the primary metaphyseal trabeculae. The periosteal longitudinal growth was not equally inhibited, so that decoupling with the cartilage growth pattern produced the typical lateral spurs around the metaphyseal growth plates. In spine, platyspondyly was due to a reduced height of the vertebral body anterior ossification center, while its enlargement in the transversal plane was not restricted. The peculiar radiographic and histopathological features of TD bones support the hypothesis of interpolation of mechanical factors with FGFR3 gene mutations. The correlated observations of X-ray morphometry, histopathology, and gene analysis prompted the following diagnostic workup for TD: (1) prenatal sonography suspicion of skeletal dysplasia; (2) post-mortem X-ray morphometry for provisional diagnosis; (3) confirmation by genetic tests (hot-spot exons 7, 10, 15, and 19 analysis with 80-90 % sensibility); (4) in negative cases if histopathology confirms TD diagnosis, research of rare mutations through sequential analysis of FGFR3 gene. (orig.)

Thanatophoric dysplasia. Correlation among bone X-ray morphometry, histopathology, and gene analysis

Energy Technology Data Exchange (ETDEWEB)

Pazzaglia, Ugo E. [University of Brescia, Orthopaedic Clinic, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Brescia (Italy); Donzelli, Carla M. [Spedali Civili di Brescia, Morbid Anatomy Department, Brescia (Italy); Izzi, Claudia [University of Brescia, Prenatal Diagnosis Unit, Department of Obstetrics and Gynaecology, Brescia (Italy); Baldi, Maurizia [Hospital Galliera, Human Genetic Laboratory, Genova (Italy); Di Gaetano, Giuseppe; Bondioni, MariaPia [University of Brescia, Paediatric Radiology, Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, Brescia (Italy)

2014-09-15

Documentation through X-ray morphometry and histology of the steady phenotype expressed by FGFR3 gene mutation and interpolation of mechanical factors on spine and long bones dysmorphism. Long bones and spine of eight thanatophoric dysplasia and three age-matched controls without skeletal dysplasia were studied after pregnancy termination between the 18th and the 22nd week with X-ray morphometry, histology, and molecular analysis. Statistical analysis with comparison between TD cases and controls and intraobserver/interobserver variation were applied to X-ray morphometric data. Generalized shortening of long bones was observed in TD. A variable distribution of axial deformities was correlated with chondrocyte proliferation inhibition, defective seriate cell columns organization, and final formation of the primary metaphyseal trabeculae. The periosteal longitudinal growth was not equally inhibited, so that decoupling with the cartilage growth pattern produced the typical lateral spurs around the metaphyseal growth plates. In spine, platyspondyly was due to a reduced height of the vertebral body anterior ossification center, while its enlargement in the transversal plane was not restricted. The peculiar radiographic and histopathological features of TD bones support the hypothesis of interpolation of mechanical factors with FGFR3 gene mutations. The correlated observations of X-ray morphometry, histopathology, and gene analysis prompted the following diagnostic workup for TD: (1) prenatal sonography suspicion of skeletal dysplasia; (2) post-mortem X-ray morphometry for provisional diagnosis; (3) confirmation by genetic tests (hot-spot exons 7, 10, 15, and 19 analysis with 80-90 % sensibility); (4) in negative cases if histopathology confirms TD diagnosis, research of rare mutations through sequential analysis of FGFR3 gene. (orig.)

Comparison of JADE and canonical correlation analysis for ECG de-noising.

Science.gov (United States)

Kuzilek, Jakub; Kremen, Vaclav; Lhotska, Lenka

2014-01-01

This paper explores differences between two methods for blind source separation within frame of ECG de-noising. First method is joint approximate diagonalization of eigenmatrices, which is based on estimation of fourth order cross-cummulant tensor and its diagonalization. Second one is the statistical method known as canonical correlation analysis, which is based on estimation of correlation matrices between two multidimensional variables. Both methods were used within method, which combines the blind source separation algorithm with decision tree. The evaluation was made on large database of 382 long-term ECG signals and the results were examined. Biggest difference was found in results of 50 Hz power line interference where the CCA algorithm completely failed. Thus main power of CCA lies in estimation of unstructured noise within ECG. JADE algorithm has larger computational complexity thus the CCA perfomed faster when estimating the components.

Study on insomnia and sleep quality in adolescents and their correlation analysis

Directory of Open Access Journals (Sweden)

Xian LUO

2017-09-01

Full Text Available Objective To investigate the correlation between insomnia and sleep quality in adolescents. Methods According to Insomnia Severity Index (ISI Chinese Version, 3342 students technician training in school were divided into non insomnia group (N = 2345 and insomnia group (N = 997. Sleep and emotional state were assessed by ISI Chinese Version, Pittsburgh Sleep Quality Index (PSQI, Epworth Sleepiness Scale (ESS, Self?Rating Anxiety Scale (SAS and Beck Depression Inventory (BDI. The social demographic data were collected simultaneously. Results The number of insomnia, daytime sleepiness, anxiety and depression in the population was 997 (29.83%, 568 (17.00%, 243 (7.27% and 1287 (38.51%, respectively. The comparison of social demographic data between 2 groups showed that the proportion of female (P = 0.000, poor physical condition (P = 0.000, non?only child (P = 0.006, high learning pressure (P = 0.000 and smoking (P = 0.027 in insomnia group were significantly higher than those in non insomnia group. The total scores of ISI Chinese Version (P = 0.000, ESS (P = 0.000, SAS (P = 0.000 and BDI (P = 0.000 in insomnia group were significantly higher than those in non insomnia group. Pearson correlation analysis showed that ISI Chinese Version and PSQI scores were positively correlated with ESS score (r = 0.361, P = 0.000; r = 0.064, P = 0.000, SAS score (r = 0.326, P = 0.000; r = 0.069, P = 0.000 and BDI score (r = 0.529, P = 0.000; r = 0.067, P = 0.000, and ISI Chinese Version had higher correlation (r = 0.300-0.600 with the above scores than PSQI (r < 0.100. Further partial correlation analysis showed that ISI Chinese Version score was negatively correlated with PSQI score (r = - 0.056, P = 0.001. Conclusions Higher proportion of female, worse physical condition, more non?only child, greater learning pressure and higher smoking rate were observed in insomnia group. Daytime sleepiness, anxiety and depression in insomnia group were more serious than those

Contagious ideas and cognitive artefacts : the SWOT Analysis evolution in business

NARCIS (Netherlands)

Puyt, R.W.; Lie, Finn Birger; de Graaf, F.J.

2017-01-01

This historical review uncovers the institutionalisation and diffusion of the SWOT analysis by assessing academic literature, seminar materials, proprietary research reports and interviews with experts from the virus theory perspective. We suggest that reviews of the SWOT analysis using the

Detailed analysis of two-particle correlations in central Pb - Au collisions at 158 GeV per nucleon

CERN Document Server

Dariusz, Antonczyk

This thesis presents a two-particle correlation analysis of the fully calibrated high statistics CERES Pb+Au collision data at the top SPS energy, with the emphasis on the pion-proton correlations and the event-plane dependence of the correlation radii. CERES is a dilepton spectrometer at CERN SPS. After the upgrade, which improved the momentum resolution and extended the detector capabilities to hadrons, CERES collected 30 million Pb+Au events at 158 AGeV in the year 2000. A previous Hanbury-Brown-Twiss (HBT) analysis of pion pairs in a subset of these data, together with the results obtained at other beam energies, lead to a new freeze-out criterion [AAA+03]. In this work, the detailed transverse momentum and event-plane dependence of the pion correlation radii, as well as the pion-proton correlations, are discussed in the framework of the blast wave model of the expanding fireball. Furthermore, development of an electron drift velocity gas monitor for the ALICE TPC sub-detector is presented. The new method...

Correlation in the statistical analysis of a reverse Fourier neutron time-of-flight experiment. Pt. 2

International Nuclear Information System (INIS)

Tilli, K.J.

1982-01-01

The significance of the correlation in the statistical analysis of reverse Fourier neutron time-of-flight observations has been evaluated by applying different methods of estimation to diffraction patterns containing peaks with Gaussian line shapes. Effects of the correlation between adjacent channels of a spectrum arise both from the incorrect weighting of the experiment's independent variables and from the misinterpretation of the number of independent observations in the data. The incorrect weighting bears the greatest effects on the width parameter of a Gaussian profile, and it leads to an increase in the relative weights of the broadest peaks of the diffraction pattern. If the correlation is ignored in the analysis, the estimates obtained for the parameters of a model will not be exactly the same as those evaluated from the minimum variance estimation, in which the correlation is taken into account. However, the differences will not be statistically significant. Nevertheless, the standard deviations will then be underestimated typically by a factor of two, which will have serious consequences on every aspect of the statistical inference. (orig.)

Generalized canonical analysis based on optimizing matrix correlations and a relation with IDIOSCAL

NARCIS (Netherlands)

Kiers, Henk A.L.; Cléroux, R.; Ten Berge, Jos M.F.

1994-01-01

Carroll's method for generalized canonical analysis of two or more sets of variables is shown to optimize the sum of squared inner-product matrix correlations between a consensus matrix and matrices with canonical variates for each set of variables. In addition, the method that analogously optimizes

Multifractal Detrended Cross-Correlation Analysis of agricultural futures markets

International Nuclear Information System (INIS)

He Lingyun; Chen Shupeng

2011-01-01

Highlights: → We investigated cross-correlations between China's and US agricultural futures markets. → Power-law cross-correlations are found between the geographically far but correlated markets. → Multifractal features are significant in all the markets. → Cross-correlation exponent is less than averaged GHE when q 0. - Abstract: We investigated geographically far but temporally correlated China's and US agricultural futures markets. We found that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the markets. It is very interesting that the geographically far markets show strong cross-correlations and share much of their multifractal structure. Furthermore, we found that for all the agricultural futures markets in our studies, the cross-correlation exponent is less than the averaged generalized Hurst exponents (GHE) when q 0.

Potential ligand-binding residues in rat olfactory receptors identified by correlated mutation analysis

Science.gov (United States)

Singer, M. S.; Oliveira, L.; Vriend, G.; Shepherd, G. M.

1995-01-01

A family of G-protein-coupled receptors is believed to mediate the recognition of odor molecules. In order to identify potential ligand-binding residues, we have applied correlated mutation analysis to receptor sequences from the rat. This method identifies pairs of sequence positions where residues remain conserved or mutate in tandem, thereby suggesting structural or functional importance. The analysis supported molecular modeling studies in suggesting several residues in positions that were consistent with ligand-binding function. Two of these positions, dominated by histidine residues, may play important roles in ligand binding and could confer broad specificity to mammalian odor receptors. The presence of positive (overdominant) selection at some of the identified positions provides additional evidence for roles in ligand binding. Higher-order groups of correlated residues were also observed. Each group may interact with an individual ligand determinant, and combinations of these groups may provide a multi-dimensional mechanism for receptor diversity.

Motivational Basis of Personality Traits: A Meta-Analysis of Value-Personality Correlations.

Science.gov (United States)

Fischer, Ronald; Boer, Diana

2015-10-01

We investigated the relationships between personality traits and basic value dimensions. Furthermore, we developed novel country-level hypotheses predicting that contextual threat moderates value-personality trait relationships. We conducted a three-level v-known meta-analysis of correlations between Big Five traits and Schwartz's (1992) 10 values involving 9,935 participants from 14 countries. Variations in contextual threat (measured as resource threat, ecological threat, and restrictive social institutions) were used as country-level moderator variables. We found systematic relationships between Big Five traits and human values that varied across contexts. Overall, correlations between Openness traits and the Conservation value dimension and Agreeableness traits and the Transcendence value dimension were strongest across all samples. Correlations between values and all personality traits (except Extraversion) were weaker in contexts with greater financial, ecological, and social threats. In contrast, stronger personality-value links are typically found in contexts with low financial and ecological threats and more democratic institutions and permissive social context. These effects explained on average more than 10% of the variability in value-personality correlations. Our results provide strong support for systematic linkages between personality and broad value dimensions, but they also point out that these relations are shaped by contextual factors. © 2014 Wiley Periodicals, Inc.

Text Analysis of Chemistry Thesis and Dissertation Titles

Science.gov (United States)

Scalfani, Vincent F.

2017-01-01

Programmatic text analysis can be used to understand patterns and reveal trends in data that would otherwise be difficult or impossible to uncover with manual coding methods. This work uses programmatic text analysis, specifically term frequency counts, to study nearly 10,000 chemistry thesis and dissertation titles from 1911-2015. The thesis and…

Analysis of correlations between sites in models of protein sequences

International Nuclear Information System (INIS)

Giraud, B.G.; Lapedes, A.; Liu, L.C.

1998-01-01

A criterion based on conditional probabilities, related to the concept of algorithmic distance, is used to detect correlated mutations at noncontiguous sites on sequences. We apply this criterion to the problem of analyzing correlations between sites in protein sequences; however, the analysis applies generally to networks of interacting sites with discrete states at each site. Elementary models, where explicit results can be derived easily, are introduced. The number of states per site considered ranges from 2, illustrating the relation to familiar classical spin systems, to 20 states, suitable for representing amino acids. Numerical simulations show that the criterion remains valid even when the genetic history of the data samples (e.g., protein sequences), as represented by a phylogenetic tree, introduces nonindependence between samples. Statistical fluctuations due to finite sampling are also investigated and do not invalidate the criterion. A subsidiary result is found: The more homogeneous a population, the more easily its average properties can drift from the properties of its ancestor. copyright 1998 The American Physical Society

Multifractal analysis of the long-range correlations in the cardiac dynamics of Drosophila melanogaster

International Nuclear Information System (INIS)

Vitanov, Nikolay K.; Yankulova, Elka D.

2006-01-01

By means of the multifractal detrended fluctuation analysis (MFDFA) we investigate long-range correlations in the interbeat time series of heart activity of Drosophila melanogaster-the classical object of research in genetics. Our main investigation tool are the fractal spectra f(α) and h(q) by means of which we trace the correlation properties of Drosophila heartbeat dynamics for three consequent generations of species. We observe that opposite to the case of humans the time series of the heartbeat activity of healthy Drosophila do not have scaling properties. Time series from species with genetic defects can be long-range correlated. Different kinds of genetic heart defects lead to different shape of the fractal spectra. The fractal heartbeat dynamics of Drosophila is transferred from generation to generation

Uncovering multiple populations with washington photometry. I. The globular cluster NGC 1851

Energy Technology Data Exchange (ETDEWEB)

Cummings, Jeffrey D.; Geisler, D.; Villanova, S. [Departamento de Astronomía, Casilla 160-C, Universidad de Concepción (Chile); Carraro, G. [ESO, Alonso de Cordova 3107, Casilla 19001, Santiago de Chile (Chile)

2014-08-01

The analysis of multiple populations (MPs) in globular clusters (GCs) has become a forefront area of research in astronomy. Multiple red giant branches (RGBs), subgiant branches (SGBs), and even main sequences (MSs) have now been observed photometrically in many GCs, while broad abundance distributions of certain elements have been detected spectroscopically in most, if not all, GCs. UV photometry has been crucial in discovering and analyzing these MPs, but the Johnson U and the Stromgren and Sloan u filters that have generally been used are relatively inefficient and very sensitive to reddening and atmospheric extinction. In contrast, the Washington C filter is much broader and redder than these competing UV filters, making it far more efficient at detecting MPs and much less sensitive to reddening and extinction. Here, we investigate the use of the Washington system to uncover MPs using only a 1 m telescope. Our analysis of the well-studied GC NGC 1851 finds that the C filter is both very efficient and effective at detecting its previously discovered MPs in the RGB and SGB. Remarkably, we have also detected an intrinsically broad MS best characterized by two distinct but heavily overlapping populations that cannot be explained by binaries, field stars, or photometric errors. The MS distribution is in very good agreement with that seen on the RGB, with ∼30% of the stars belonging to the second population. There is also evidence for two sequences in the red horizontal branch, but this appears to be unrelated to the MPs in this cluster. Neither of these latter phenomena have been observed previously in this cluster. The redder MS stars are also more centrally concentrated than the blue MS. This is the first time MPs in an MS have been discovered from the ground, and using only a 1 m telescope. The Washington system thus proves to be a very powerful tool for investigating MPs, and holds particular promise for extragalactic objects where photons are limited.

Pierre Bourdieu's Theory of Practice offers nurses a framework to uncover embodied knowledge of patients living with disabilities or illnesses: A discussion paper.

Science.gov (United States)

Oerther, Sarah; Oerther, Daniel B

2018-04-01

To discuss how Bourdieu's theory of practice can be used by nurse researchers to better uncover the embodied knowledge of patients living with disability and illness. Bourdieu's theory of practice has been used in social and healthcare researches. This theory emphasizes that an individual's everyday practices are not always explicit and mediated by language, but instead an individual's everyday practices are often are tacit and embodied. Discussion paper. Ovid MEDLINE, CINAHL and SCOPUS were searched for concepts from Bourdieu's theory that was used to understand embodied knowledge of patients living with disability and illness. The literature search included articles from 2003 - 2017. Nurse researchers should use Bourdieu's theory of practice to uncover the embodied knowledge of patients living with disability and illness, and nurse researchers should translate these discoveries into policy recommendations and improved evidence-based best practice. The practice of nursing should incorporate an understanding of embodied knowledge to support disabled and ill patients as these patients modify "everyday practices" in the light of their disabilities and illnesses. Bourdieu's theory enriches nursing because the theory allows for consideration of both the objective and the subjective through the conceptualization of capital, habitus and field. Uncovering individuals embodied knowledge is critical to implement best practices that assist patients as they adapt to bodily changes during disability and illness. © 2017 John Wiley & Sons Ltd.

Clinicopathological correlates of hyperparathyroidism.

Science.gov (United States)

Duan, Kai; Gomez Hernandez, Karen; Mete, Ozgur

2015-10-01

Hyperparathyroidism is a common endocrine disorder with potential complications on the skeletal, renal, neurocognitive and cardiovascular systems. While most cases (95%) occur sporadically, about 5% are associated with a hereditary syndrome: multiple endocrine neoplasia syndromes (MEN-1, MEN-2A, MEN-4), hyperparathyroidism-jaw tumour syndrome (HPT-JT), familial hypocalciuric hypercalcaemia (FHH-1, FHH-2, FHH-3), familial hypercalciuric hypercalcaemia, neonatal severe hyperparathyroidism and isolated familial hyperparathyroidism. Recently, molecular mechanisms underlying possible tumour suppressor genes (MEN1, CDC73/HRPT2, CDKIs, APC, SFRPs, GSK3β, RASSF1A, HIC1, RIZ1, WT1, CaSR, GNA11, AP2S1) and proto-oncogenes (CCND1/PRAD1, RET, ZFX, CTNNB1, EZH2) have been uncovered in the pathogenesis of hyperparathyroidism. While bi-allelic inactivation of CDC73/HRPT2 seems unique to parathyroid malignancy, aberrant activation of cyclin D1 and Wnt/β-catenin signalling has been reported in benign and malignant parathyroid tumours. Clinicopathological correlates of primary hyperparathyroidism include parathyroid adenoma (80-85%), hyperplasia (10-15%) and carcinoma (hyperparathyroidism generally presents with diffuse parathyroid hyperplasia, whereas tertiary hyperparathyroidism reflects the emergence of autonomous parathyroid hormone (PTH)-producing neoplasm(s) from secondary parathyroid hyperplasia. Surgical resection of abnormal parathyroid tissue remains the only curative treatment in primary hyperparathyroidism, and parathyroidectomy specimens are frequently encountered in this setting. Clinical and biochemical features, including intraoperative PTH levels, number, weight and size of the affected parathyroid gland(s), are crucial parameters to consider when rendering an accurate diagnosis of parathyroid proliferations. This review provides an update on the expanding knowledge of hyperparathyroidism and highlights the clinicopathological correlations of this prevalent

Correlation of quantitative histopathological morphology and quantitative radiological analysis during aseptic loosening of hip endoprostheses.

Science.gov (United States)

Bertz, S; Kriegsmann, J; Eckardt, A; Delank, K-S; Drees, P; Hansen, T; Otto, M

2006-01-01

Aseptic hip prosthesis loosening is the most important long-term complication in total hip arthroplasty. Polyethylene (PE) wear is the dominant etiologic factor in aseptic loosening, which together with other factors induces mechanisms resulting in bone loss, and finally in implant loosening. The single-shot radiograph analysis (EBRA, abbreviation for the German term "Einzel-Bild-Röntgenanalyse") is a computerized method for early radiological prediction of aseptic loosening. In this study, EBRA parameters were correlated with histomorphological parameters of the periprosthetic membrane. Periprosthetic membranes obtained from 19 patients during revision surgery of loosened ABG I-type total hip pros-theses were analyzed histologically and morphometrically. The pre-existing EBRA parameters, the thickness of the PE debris lay-er and the dimension of inclination and anteversion, were compared with the density of macrophages and giant cells. Addi-tionally, the semiquantitatively determined density of lymphocytes, plasma cells, giant cells and the size of the necrotic areas were correlated with the EBRA results. All periprosthetic membranes were classified as debris-induced type membranes. We found a positive correlation between the number of giant cells and the thickness of the PE debris layer. There was no significant correlation between the number of macrophages or all semiquantitative parameters and EBRA parameters. The number of giant cells decreased with implant duration. The morphometrically measured number of foreign body giant cells more closely reflects the results of the EBRA. The semiquantitative estimation of giant cell density could not substitute for the morphometrical analysis. The density of macrophages, lymphocytes, plasma cells and the size of necrotic areas did not correlate with the EBRA parameters, indicating that there is no correlation with aseptic loosening.

Multidimensional correlation among plan complexity, quality and deliverability parameters for volumetric-modulated arc therapy using canonical correlation analysis.

Science.gov (United States)

Shen, Lanxiao; Chen, Shan; Zhu, Xiaoyang; Han, Ce; Zheng, Xiaomin; Deng, Zhenxiang; Zhou, Yongqiang; Gong, Changfei; Xie, Congying; Jin, Xiance

2018-03-01

A multidimensional exploratory statistical method, canonical correlation analysis (CCA), was applied to evaluate the impact of complexity parameters on the plan quality and deliverability of volumetric-modulated arc therapy (VMAT) and to determine parameters in the generation of an ideal VMAT plan. Canonical correlations among complexity, quality and deliverability parameters of VMAT, as well as the contribution weights of different parameters were investigated with 71 two-arc VMAT nasopharyngeal cancer (NPC) patients, and further verified with 28 one-arc VMAT prostate cancer patients. The average MU and MU per control point (MU/CP) for two-arc VMAT plans were 702.6 ± 55.7 and 3.9 ± 0.3 versus 504.6 ± 99.2 and 5.6 ± 1.1 for one-arc VMAT plans, respectively. The individual volume-based 3D gamma passing rates of clinical target volume (γCTV) and planning target volume (γPTV) for NPC and prostate cancer patients were 85.7% ± 9.0% vs 92.6% ± 7.8%, and 88.0% ± 7.6% vs 91.2% ± 7.7%, respectively. Plan complexity parameters of NPC patients were correlated with plan quality (P = 0.047) and individual volume-based 3D gamma indices γ(IV) (P = 0.01), in which, MU/CP and segment area (SA) per control point (SA/CP) were weighted highly in correlation with γ(IV) , and SA/CP, percentage of CPs with SA plan quality with coefficients of 0.98, 0.68 and -0.99, respectively. Further verification with one-arc VMAT plans demonstrated similar results. In conclusion, MU, SA-related parameters and PTV volume were found to have strong effects on the plan quality and deliverability.

Void fraction correlations analysis and their influence on heat transfer of helical double-pipe vertical evaporator

International Nuclear Information System (INIS)

Parrales, Arianna; Colorado, Dario; Huicochea, Armando; Díaz, Juan; Alfredo Hernández, J.

2014-01-01

Highlights: • 50 void fraction correlations were evaluated on heat transfer in vertical evaporators. • Two-phase flow model based on control volume formulation was used. • The drift flux parameter is common in all correlations with satisfactory results. - Abstract: An analysis of 50 void fraction correlations available in the literature was performed to describe two-phase flow mechanism inside two helical double-pipe vertical evaporators. The evaporators considered water as working fluid connected in countercurrent so the change of phase was carried out into the internal tube. The discretized equations of continuity, momentum and energy in each flow were coupled using an implicit step by step method. The selection of the void fraction correlations for the mathematical model was based on inclusion of some theoretical limits. The results of this analysis were compared with the experimental data in steady state for two different evaporators, obtaining good agreement in the evaporation process for only 7 void fraction correlations. The Armand and Massena correlation had a mean percentage error (MPE) of 3.08%, followed by Rouhanni and Axelsson I adquired MPE=3.16%, Chisholm and Armand obtained MPE=3.18%, Steiner as well as Rouhanni and Axelsson II with MPE=3.19%, Bestion reached MPE=3.20% and Flanigan presented MPE=3.21%. Furthermore, the experimental and simulated heat flux were acceptable (R 2 =0.939). Finally, the results showed that the drift flux parameter was important to evaluate the void fraction

Circulating prolactin level in systemic lupus erythematosus and its correlation with disease activity: a meta-analysis.

Science.gov (United States)

Song, G G; Lee, Y H

2017-10-01

Objective This study aimed to evaluate the relationship between circulating prolactin level and systemic lupus erythematosus (SLE), and to establish a correlation between plasma/serum prolactin levels and SLE activity. Methods We performed a meta-analysis comparing the plasma/serum prolactin levels in patients with SLE to controls, and examined correlation coefficients between circulating prolactin level and SLE disease activity. Results Twenty-five studies with a total of 1056 SLE patients and 426 controls were included. Prolactin levels were significantly higher overall in the SLE group than in the control group (standardized mean difference (SMD) = 0.987, 95% CI = 0.512-1.463, p = 4.7 × 10 -5 ). Stratification by ethnicity showed significantly elevated prolactin levels in the SLE group in Asian, Latin American, and mixed populations (SMD = 0.813, 95% CI = 0.137-1.490, p = 0.018; SMD = 0.981, 95% CI = 0.307-1.655, p = 0.004; SMD = 1.469, 95% CI = 0.443-2.495, p = 0.005, respectively), but not in the European population. Subgroup analysis by sample size showed significantly higher prolactin levels in the SLE group by small ( n  30). Meta-analysis of correlation coefficients showed a significantly positive correlation between circulating prolactin level and SLE activity (correlation coefficient = 0.379, 95% CI = 0.026-0.487, p = 4.0 × 10 -9 ). Circulating prolactin levels were positively associated with SLE activity in European, Asian, and mixed populations (SMD = 0.532, 95% CI = 0.443-0.609  p < 1.0 × 10 -8 ; SMD = 0.427, 95% CI = 0.240-0.583, p = 2.4 × 10 -5 ; SMD = 0.433, 95% CI = 0.212-0.591, p = 2.7 × 10 -5 , respectively). Conclusions Our meta-analysis demonstrated that circulating prolactin levels are higher in patients with SLE, and that a significantly positive correlation exists between prolactin levels and SLE activity.

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

Science.gov (United States)

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Genome-Wide Association Uncovers Shared Genetic Effects Among Personality Traits and Mood States

NARCIS (Netherlands)

Luciano, Michelle; Huffman, Jennifer E.; Arias-Vásquez, Alejandro; Vinkhuyzen, Anna A. E.; Middeldorp, Christel M.; Giegling, Ina; Payton, Antony; Davies, Gail; Zgaga, Lina; Janzing, Joost; Ke, Xiayi; Galesloot, Tessel; Hartmann, Annette M.; Ollier, William; Tenesa, Albert; Hayward, Caroline; Verhagen, Maaike; Montgomery, Grant W.; Hottenga, Jouke-Jan; Konte, Bettina; Starr, John M.; Vitart, Veronique; Vos, Pieter E.; Madden, Pamela A. F.; Willemsen, Gonneke; Konnerth, Heike; Horan, Michael A.; Porteous, David J.; Campbell, Harry; Vermeulen, Sita H.; Heath, Andrew C.; Wright, Alan; Polasek, Ozren; Kovacevic, Sanja B.; Hastie, Nicholas D.; Franke, Barbara; Boomsma, Dorret I.; Martin, Nicholas G.; Rujescu, Dan; Wilson, James F.; Buitelaar, Jan; Pendleton, Neil; Rudan, Igor; Deary, Ian J.

2012-01-01

Measures of personality and psychological distress are correlated and exhibit genetic covariance. We conducted univariate genome-wide SNP (similar to 2.5 million) and gene-based association analyses of these traits and examined the overlap in results across traits, including a prediction analysis of

MARS A Cosmic Stepping Stone Uncovering Humanity’s Cosmic Context

CERN Document Server

Nolan, Kevin

2008-01-01

The questions of our origin and cosmic abundance of life are among the most compelling facing humanity. We have determined much about the nature and origin of the Universe and our place in it, but with virtually all evidence of our origin long since gone from our world and an unimaginably vast Universe still to explore, defining answers are difficult to obtain. For all of the difficulties facing us however, the planet Mars may act as a ‘cosmic stepping stone’ in uncovering some of the answers. Although different today, the origin and early history of both Earth and Mars may have been similar enough to consider an origin to life on both. But because Mars’ planetary processes collapsed over three billion years ago – just as life was beginning to flourish on Earth – a significant and unique record of activity from that era perhaps relevant to the origin of life still resides there today. In recognition of this, both the US and Europe are currently engaged in one of the most ambitious programs of explor...

Groundwater travel time uncertainty analysis: Sensitivity of results to model geometry, and correlations and cross correlations among input parameters

International Nuclear Information System (INIS)

Clifton, P.M.

1984-12-01

The deep basalt formations beneath the Hanford Site are being investigated for the Department of Energy (DOE) to assess their suitability as a host medium for a high level nuclear waste repository. Predicted performance of the proposed repository is an important part of the investigation. One of the performance measures being used to gauge the suitability of the host medium is pre-waste-emplacement groundwater travel times to the accessible environment. Many deterministic analyses of groundwater travel times have been completed by Rockwell and other independent organizations. Recently, Rockwell has completed a preliminary stochastic analysis of groundwater travel times. This document presents analyses that show the sensitivity of the results from the previous stochastic travel time study to: (1) scale of representation of model parameters, (2) size of the model domain, (3) correlation range of log-transmissivity, and (4) cross-correlation between transmissivity and effective thickness. 40 refs., 29 figs., 6 tabs

Correlation analysis of trace elemental data obtained from blood sera of ovarian cancer patients using PIXE

International Nuclear Information System (INIS)

Naidu, B.G.; Sarita, P.; Naga Raju, G.J.

2017-01-01

Proton induced X-ray emission (PIXE) technique is used for analysis of trace elements present in the blood sera of ovarian cancer patients and healthy controls. This work is also intended to establish the role played by trace elements in carcinogenic process. It is observed that the concentrations of elements Ti, V, Cr, Mn, Fe, Ni, Rb and Sr are lower and the concentration of Cu is higher in the cancer patients when compared to controls. However, no change in concentration is found in the elements Co, Zn, As, Se and Br. Correlation analysis of the data using SPSS 16.0 has revealed a strong positive correlation between Ti-V, Ni-Co, Cu-Fe, As-Ti, Br-Ti, Br-V and Sr-Fe while strong negative correlations are observed for Cu-Ti, As-Cu and Br-Cu. Changes in trace elemental content are probably associated with ovarian carcinogenesis. (author)

Parent heparin and daughter LMW heparin correlation analysis using LC-MS and NMR

Energy Technology Data Exchange (ETDEWEB)

Liu, Xinyue, E-mail: liux22@rpi.edu [National Glycoengineering Research Center, Shandong Provincial Key Laboratory of Carbohydrate Chemistry and Glycobiology, State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong, 250100 (China); Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); St Ange, Kalib, E-mail: stangk2@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); Wang, Xiaohua, E-mail: wangx35@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); School of Computer and Information, Hefei University of Technology, Hefei (China); Lin, Lei, E-mail: Linl5@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); Zhang, Fuming, E-mail: zhangf2@rpi.edu [Department of Chemistry and Chemical Biology, Department of Chemical and Biological Engineering, Department of Biology, Department of Biomedical Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY, 12180 (United States); and others

2017-04-08

Heparin is a structurally complex, polysaccharide anticoagulant derived from livestock, primarily porcine intestinal tissues. Low molecular weight (LMW) heparins are derived through the controlled partial depolymerization of heparin. Increased manufacturing and regulatory concerns have provided the motivation for the development of more sophisticated analytical methods for determining both their structure and pedigree. A strategy, for the comprehensive comparison of parent heparins and their LMW heparin daughters, is described that relies on the analysis of monosaccharide composition, disaccharide composition, and oligosaccharide composition. Liquid chromatography-mass spectrometry is rapid, robust, and amenable to automated processing and interpretation of both top-down and bottom-up analyses. Nuclear magnetic resonance spectroscopy provides complementary top-down information on the chirality of the uronic acid residues and glucosamine substitution. Principal component analysis (PCA) was applied to the normalized abundance of oligosaccharides, calculated in the bottom-up analysis, to show parent and daughter correlation in oligosaccharide composition. Using these approaches, six pairs of parent heparins and their daughter generic enoxaparins from two different manufacturers were comprehensively analyzed. Enoxaparin is the most widely used LMW heparin and is prepared through controlled chemical β-eliminative cleavage of porcine intestinal heparin. Lovenox{sup ®}, the innovator version of enoxaparin marketed in the US, was analyzed as a reference for the daughter LMW heparins. The results, show similarities between LMW heparins from two different manufacturers with Lovenox{sup ®}, excellent lot-to-lot consistency of products from each manufacturer, and detects a correlation between each parent heparin and daughter LMW heparin. - Highlights: • Low molecular weight heparins prepared from different heparin parents were analyzed. • An integrated analytical

Parent heparin and daughter LMW heparin correlation analysis using LC-MS and NMR

International Nuclear Information System (INIS)

Liu, Xinyue; St Ange, Kalib; Wang, Xiaohua; Lin, Lei; Zhang, Fuming

2017-01-01

Heparin is a structurally complex, polysaccharide anticoagulant derived from livestock, primarily porcine intestinal tissues. Low molecular weight (LMW) heparins are derived through the controlled partial depolymerization of heparin. Increased manufacturing and regulatory concerns have provided the motivation for the development of more sophisticated analytical methods for determining both their structure and pedigree. A strategy, for the comprehensive comparison of parent heparins and their LMW heparin daughters, is described that relies on the analysis of monosaccharide composition, disaccharide composition, and oligosaccharide composition. Liquid chromatography-mass spectrometry is rapid, robust, and amenable to automated processing and interpretation of both top-down and bottom-up analyses. Nuclear magnetic resonance spectroscopy provides complementary top-down information on the chirality of the uronic acid residues and glucosamine substitution. Principal component analysis (PCA) was applied to the normalized abundance of oligosaccharides, calculated in the bottom-up analysis, to show parent and daughter correlation in oligosaccharide composition. Using these approaches, six pairs of parent heparins and their daughter generic enoxaparins from two different manufacturers were comprehensively analyzed. Enoxaparin is the most widely used LMW heparin and is prepared through controlled chemical β-eliminative cleavage of porcine intestinal heparin. Lovenox"®, the innovator version of enoxaparin marketed in the US, was analyzed as a reference for the daughter LMW heparins. The results, show similarities between LMW heparins from two different manufacturers with Lovenox"®, excellent lot-to-lot consistency of products from each manufacturer, and detects a correlation between each parent heparin and daughter LMW heparin. - Highlights: • Low molecular weight heparins prepared from different heparin parents were analyzed. • An integrated analytical approach relied

Automated measurement and classification of pulmonary blood-flow velocity patterns using phase-contrast MRI and correlation analysis.

Science.gov (United States)

van Amerom, Joshua F P; Kellenberger, Christian J; Yoo, Shi-Joon; Macgowan, Christopher K

2009-01-01

An automated method was evaluated to detect blood flow in small pulmonary arteries and classify each as artery or vein, based on a temporal correlation analysis of their blood-flow velocity patterns. The method was evaluated using velocity-sensitive phase-contrast magnetic resonance data collected in vitro with a pulsatile flow phantom and in vivo in 11 human volunteers. The accuracy of the method was validated in vitro, which showed relative velocity errors of 12% at low spatial resolution (four voxels per diameter), but was reduced to 5% at increased spatial resolution (16 voxels per diameter). The performance of the method was evaluated in vivo according to its reproducibility and agreement with manual velocity measurements by an experienced radiologist. In all volunteers, the correlation analysis was able to detect and segment peripheral pulmonary vessels and distinguish arterial from venous velocity patterns. The intrasubject variability of repeated measurements was approximately 10% of peak velocity, or 2.8 cm/s root-mean-variance, demonstrating the high reproducibility of the method. Excellent agreement was obtained between the correlation analysis and radiologist measurements of pulmonary velocities, with a correlation of R2=0.98 (P<.001) and a slope of 0.99+/-0.01.

Uncertainty analysis with statistically correlated failure data

International Nuclear Information System (INIS)

Modarres, M.; Dezfuli, H.; Roush, M.L.

1987-01-01

Likelihood of occurrence of the top event of a fault tree or sequences of an event tree is estimated from the failure probability of components that constitute the events of the fault/event tree. Component failure probabilities are subject to statistical uncertainties. In addition, there are cases where the failure data are statistically correlated. At present most fault tree calculations are based on uncorrelated component failure data. This chapter describes a methodology for assessing the probability intervals for the top event failure probability of fault trees or frequency of occurrence of event tree sequences when event failure data are statistically correlated. To estimate mean and variance of the top event, a second-order system moment method is presented through Taylor series expansion, which provides an alternative to the normally used Monte Carlo method. For cases where component failure probabilities are statistically correlated, the Taylor expansion terms are treated properly. Moment matching technique is used to obtain the probability distribution function of the top event through fitting the Johnson Ssub(B) distribution. The computer program, CORRELATE, was developed to perform the calculations necessary for the implementation of the method developed. (author)

Meconium microbiome analysis identifies bacteria correlated with premature birth.

Directory of Open Access Journals (Sweden)

Alexandria N Ardissone

Full Text Available Preterm birth is the second leading cause of death in children under the age of five years worldwide, but the etiology of many cases remains enigmatic. The dogma that the fetus resides in a sterile environment is being challenged by recent findings and the question has arisen whether microbes that colonize the fetus may be related to preterm birth. It has been posited that meconium reflects the in-utero microbial environment. In this study, correlations between fetal intestinal bacteria from meconium and gestational age were examined in order to suggest underlying mechanisms that may contribute to preterm birth.Meconium from 52 infants ranging in gestational age from 23 to 41 weeks was collected, the DNA extracted, and 16S rRNA analysis performed. Resulting taxa of microbes were correlated to clinical variables and also compared to previous studies of amniotic fluid and other human microbiome niches.Increased detection of bacterial 16S rRNA in meconium of infants of <33 weeks gestational age was observed. Approximately 61·1% of reads sequenced were classified to genera that have been reported in amniotic fluid. Gestational age had the largest influence on microbial community structure (R = 0·161; p = 0·029, while mode of delivery (C-section versus vaginal delivery had an effect as well (R = 0·100; p = 0·044. Enterobacter, Enterococcus, Lactobacillus, Photorhabdus, and Tannerella, were negatively correlated with gestational age and have been reported to incite inflammatory responses, suggesting a causative role in premature birth.This provides the first evidence to support the hypothesis that the fetal intestinal microbiome derived from swallowed amniotic fluid may be involved in the inflammatory response that leads to premature birth.

Regression analysis of longitudinal data with correlated censoring and observation times.

Science.gov (United States)

Li, Yang; He, Xin; Wang, Haiying; Sun, Jianguo

2016-07-01

Longitudinal data occur in many fields such as the medical follow-up studies that involve repeated measurements. For their analysis, most existing approaches assume that the observation or follow-up times are independent of the response process either completely or given some covariates. In practice, it is apparent that this may not be true. In this paper, we present a joint analysis approach that allows the possible mutual correlations that can be characterized by time-dependent random effects. Estimating equations are developed for the parameter estimation and the resulted estimators are shown to be consistent and asymptotically normal. The finite sample performance of the proposed estimators is assessed through a simulation study and an illustrative example from a skin cancer study is provided.

Assessment of SIP Buildings for Sustainable Development in Rural China Using AHP-Grey Correlation Analysis.

Science.gov (United States)

Bai, Libiao; Wang, Hailing; Shi, Chunming; Du, Qiang; Li, Yi

2017-10-25

Traditional rural residential construction has the problems of high energy consumption and severe pollution. In general, with sustainable development in the construction industry, rural residential construction should be aimed towards low energy consumption and low carbon emissions. To help achieve this objective, in this paper, we evaluated four different possible building structures using AHP-Grey Correlation Analysis, which consists of the Analytic Hierarchy Process (AHP) and the Grey Correlation Analysis. The four structures included the traditional and currently widely used brick and concrete structure, as well as structure insulated panels (SIPs). Comparing the performances of economic benefit and carbon emission, the conclusion that SIPs have the best overall performance can be obtained, providing a reference to help builders choose the most appropriate building structure in rural China.

Research of diagnosis sensors fault based on correlation analysis of the bridge structural health monitoring system

Science.gov (United States)

Hu, Shunren; Chen, Weimin; Liu, Lin; Gao, Xiaoxia

2010-03-01

Bridge structural health monitoring system is a typical multi-sensor measurement system due to the multi-parameters of bridge structure collected from the monitoring sites on the river-spanning bridges. Bridge structure monitored by multi-sensors is an entity, when subjected to external action; there will be different performances to different bridge structure parameters. Therefore, the data acquired by each sensor should exist countless correlation relation. However, complexity of the correlation relation is decided by complexity of bridge structure. Traditionally correlation analysis among monitoring sites is mainly considered from physical locations. unfortunately, this method is so simple that it cannot describe the correlation in detail. The paper analyzes the correlation among the bridge monitoring sites according to the bridge structural data, defines the correlation of bridge monitoring sites and describes its several forms, then integrating the correlative theory of data mining and signal system to establish the correlation model to describe the correlation among the bridge monitoring sites quantificationally. Finally, The Chongqing Mashangxi Yangtze river bridge health measurement system is regards as research object to diagnosis sensors fault, and simulation results verify the effectiveness of the designed method and theoretical discussions.

Correlated randomness and switching phenomena

Science.gov (United States)

Stanley, H. E.; Buldyrev, S. V.; Franzese, G.; Havlin, S.; Mallamace, F.; Kumar, P.; Plerou, V.; Preis, T.

2010-08-01

One challenge of biology, medicine, and economics is that the systems treated by these serious scientific disciplines have no perfect metronome in time and no perfect spatial architecture-crystalline or otherwise. Nonetheless, as if by magic, out of nothing but randomness one finds remarkably fine-tuned processes in time and remarkably fine-tuned structures in space. Further, many of these processes and structures have the remarkable feature of “switching” from one behavior to another as if by magic. The past century has, philosophically, been concerned with placing aside the human tendency to see the universe as a fine-tuned machine. Here we will address the challenge of uncovering how, through randomness (albeit, as we shall see, strongly correlated randomness), one can arrive at some of the many spatial and temporal patterns in biology, medicine, and economics and even begin to characterize the switching phenomena that enables a system to pass from one state to another. Inspired by principles developed by A. Nihat Berker and scores of other statistical physicists in recent years, we discuss some applications of correlated randomness to understand switching phenomena in various fields. Specifically, we present evidence from experiments and from computer simulations supporting the hypothesis that water’s anomalies are related to a switching point (which is not unlike the “tipping point” immortalized by Malcolm Gladwell), and that the bubbles in economic phenomena that occur on all scales are not “outliers” (another Gladwell immortalization). Though more speculative, we support the idea of disease as arising from some kind of yet-to-be-understood complex switching phenomenon, by discussing data on selected examples, including heart disease and Alzheimer disease.

Uncovering genes with divergent mRNA-protein dynamics in Streptomyces coelicolor.

Directory of Open Access Journals (Sweden)

Karthik P Jayapal

2008-05-01

Full Text Available Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels. Systems analyses of such processes incorporating large-scale transcriptome or proteome profiling can be quite revealing. Although consistency between mRNA and proteins is often implicitly assumed in many studies, examples of divergent trends are frequently observed. Here, we present a comparative transcriptome and proteome analysis of growth and stationary phase adaptation in Streptomyces coelicolor, taking the time-dynamics of process into consideration. These processes are of immense interest in microbiology as they pertain to the physiological transformations eliciting biosynthesis of many naturally occurring therapeutic agents. A shotgun proteomics approach based on mass spectrometric analysis of isobaric stable isotope labeled peptides (iTRAQ enabled identification and rapid quantification of approximately 14% of the theoretical proteome of S. coelicolor. Independent principal component analyses of this and DNA microarray-derived transcriptome data revealed that the prominent patterns in both protein and mRNA domains are surprisingly well correlated. Despite this overall correlation, by employing a systematic concordance analysis, we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends. Integrating this data with biological information, we discovered that certain groups of functionally related genes exhibit mRNA-protein discordance in a similar fashion. Our observations suggest that differences between mRNA and protein synthesis/degradation mechanisms are prominent in microbes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level.

Canonical correlation analysis for gene-based pleiotropy discovery.

Directory of Open Access Journals (Sweden)

Jose A Seoane

2014-10-01

Full Text Available Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy and for testing multiple variants for association with a single phenotype (gene-based association tests. Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study, we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1 with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels.

Canonical correlation analysis of professional stress,social support,and professional burnout among low-rank army officers

Directory of Open Access Journals (Sweden)

Chuan-yun LI

2011-12-01

Full Text Available Objective The present study investigates the influence of professional stress and social support on professional burnout among low-rank army officers.Methods The professional stress,social support,and professional burnout scales among low-rank army officers were used as test tools.Moreover,the officers of established units(battalion,company,and platoon were chosen as test subjects.Out of the 260 scales sent,226 effective scales were received.The descriptive statistic and canonical correlation analysis models were used to analyze the influence of each variable.Results The scores of low-rank army officers in the professional stress,social support,and professional burnout scales were more than average,except on two factors,namely,interpersonal support and de-individualization.The canonical analysis identified three groups of canonical correlation factors,of which two were up to a significant level(P < 0.001.After further eliminating the social support variable,the canonical correlation analysis of professional stress and burnout showed that the canonical correlation coefficients P corresponding to 1 and 2 were 0.62 and 0.36,respectively,and were up to a very significant level(P < 0.001.Conclusion The low-rank army officers experience higher professional stress and burnout levels,showing a lower sense of accomplishment,emotional exhaustion,and more serious depersonalization.However,social support can reduce the onset and seriousness of professional burnout among these officers by lessening pressure factors,such as career development,work features,salary conditions,and other personal factors.

Exploring anti-correlated radio/X-ray modes in transitional millisecond pulsars

Science.gov (United States)

Jaodand, Amruta

2017-09-01

Recently, using coordinated VLA+Chandra observations, Bogdanov et al.(2017) have uncovered a stunning anti-correlation in the LMXB state of the tMSP PSR J1023+0038. They see that radio luminosity consistently peaks during the X-ray `low' luminosity modes. Also, we have found a promising candidate tMSP, 3FGL J1544-1125(J1544) (Bogdanov and Halpern 2015; currently only tMSP candidate apart from J1023 in a persistent LMXB state). Using VLA and simultaneous Swift observations we see that it lies on the proposed tMSP track in radio vs. X-ray luminosity (L_ R/L_X) diagram. This finding strengthens its classification as a tMSP and provides an excellent opportunity to a)determine universality of radio/X-ray brightness anti-correlatio and b)understand jet/outflow formation in tMSPs.

THE CORRELATION ANALYSIS OF SUBSIDENCE MONITORING BY D-INSAR AND THE CHANGE OF URBAN CONSTRUCTION LAND

Directory of Open Access Journals (Sweden)

K. J. Yang

2017-05-01

Full Text Available The change of urban construction land affect the subsidence directly or indirectly, the method of D-InSAR has centimeter level or even millimeter accuracy that can provide a reliable and accurate data for the research of correlation analysis of subsidence monitoring by D-InSAR and the change of urban construction land. This article takes Guiyang, Nanning city as example, using 3m level TerraSAR data to construct the Subsidence model by interferometric measurement, then compared with the Chinese national land use change remote sensing survey database at the same measure time to have a correlation analysis GIS research between subsidence and the change of urban construction land. The results shows that the integral correlation coefficient achieved 0.78 between subsidence and the change of urban construction land, the major construction area and the high density construction area are with severe land subsidence. In addition, the correlation coefficient increased from the main city to the suburbs, indicates that some of the main city causes permanent settlement and is difficult to recover. It also shows that some area subsidence caused by long-term mining or other natural factors has no strong correlation with the change of urban construction land, therefore, the results of D-InSAR subsidence monitoring have a reaction on urban construction planning, guiding urban planning to high stability, low settlement area.

Correlated Light Microscopy and Electron Microscopy

NARCIS (Netherlands)

Sjollema, Klaas A.; Schnell, Ulrike; Kuipers, Jeroen; Kalicharan, Ruby; Giepmans, Ben N. G.; MullerReichert, T; Verkade, P

2012-01-01

Understanding where, when, and how biomolecules (inter)act is crucial to uncover fundamental mechanisms in cell biology. Recent developments in fluorescence light microscopy (FLM) allow protein imaging in living cells and at the near molecular level. However, fluorescence microscopy only reveals

Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

Science.gov (United States)

Ma, Chuang; Wang, Xiangfeng

2012-01-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655

ResStock Analysis Tool | Buildings | NREL

Science.gov (United States)

Energy and Cost Savings for U.S. Homes Contact Eric Wilson to learn how ResStock can benefit your approach to large-scale residential energy analysis by combining: Large public and private data sources uncovered $49 billion in potential annual utility bill savings through cost-effective energy efficiency

Sparse and smooth canonical correlation analysis through rank-1 matrix approximation

Science.gov (United States)

Aïssa-El-Bey, Abdeldjalil; Seghouane, Abd-Krim

2017-12-01

Canonical correlation analysis (CCA) is a well-known technique used to characterize the relationship between two sets of multidimensional variables by finding linear combinations of variables with maximal correlation. Sparse CCA and smooth or regularized CCA are two widely used variants of CCA because of the improved interpretability of the former and the better performance of the later. So far, the cross-matrix product of the two sets of multidimensional variables has been widely used for the derivation of these variants. In this paper, two new algorithms for sparse CCA and smooth CCA are proposed. These algorithms differ from the existing ones in their derivation which is based on penalized rank-1 matrix approximation and the orthogonal projectors onto the space spanned by the two sets of multidimensional variables instead of the simple cross-matrix product. The performance and effectiveness of the proposed algorithms are tested on simulated experiments. On these results, it can be observed that they outperform the state of the art sparse CCA algorithms.

CORRELATION ANALYSIS BETWEEN TIBET AS-γ TeV COSMIC RAY AND WMAP NINE-YEAR DATA

Energy Technology Data Exchange (ETDEWEB)

Yin, Qian-Qing; Zhang, Shuang-Nan, E-mail: zhangsn@ihep.ac.cn [Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Beijing 100049 (China)

2015-08-01

The WMAP team subtracted template-based foreground models to produce foreground-reduced maps, and masked point sources and uncertain sky regions directly; however, whether foreground residuals exist in the WMAP foreground-reduced maps is still an open question. Here, we use Pearson correlation coefficient analysis with AS-γ TeV cosmic ray (CR) data to probe possible foreground residuals in the WMAP nine-year data. The correlation results between the CR and foreground-contained maps (WMAP foreground-unreduced maps, WMAP template-based, and Maximum Entropy Method foreground models) suggest that: (1) CRs can trace foregrounds in the WMAP data; (2) at least some TeV CRs originate from the Milky Way; (3) foregrounds may be related to the existence of CR anisotropy (loss-cone and tail-in structures); (4) there exist differences among different types of foregrounds in the decl. range of <15°. Then, we generate 10,000 mock cosmic microwave background (CMB) sky maps to describe the cosmic variance, which is used to measure the effect of the fluctuations of all possible CMB maps to the correlations between CR and CMB maps. Finally, we do correlation analysis between the CR and WMAP foreground-reduced maps, and find that: (1) there are significant anticorrelations; and (2) the WMAP foreground-reduced maps are credible. However, the significant anticorrelations may be accidental, and the higher signal-to-noise ratio Planck SMICA map cannot reject the hypothesis of accidental correlations. We therefore can only conclude that the foreground residuals exist with ∼95% probability.

Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis.

Science.gov (United States)

Tam, Roger C; Traboulsee, Anthony; Riddehough, Andrew; Li, David K B

2012-01-01

The change in T 1-hypointense lesion ("black hole") volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi-)automated segmentation methods first compute the T 2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T 1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T 2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T 2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.

Quantitative CT analysis of honeycombing area in idiopathic pulmonary fibrosis: Correlations with pulmonary function tests.

Science.gov (United States)

Nakagawa, Hiroaki; Nagatani, Yukihiro; Takahashi, Masashi; Ogawa, Emiko; Tho, Nguyen Van; Ryujin, Yasushi; Nagao, Taishi; Nakano, Yasutaka

2016-01-01

The 2011 official statement of idiopathic pulmonary fibrosis (IPF) mentions that the extent of honeycombing and the worsening of fibrosis on high-resolution computed tomography (HRCT) in IPF are associated with the increased risk of mortality. However, there are few reports about the quantitative computed tomography (CT) analysis of honeycombing area. In this study, we first proposed a computer-aided method for quantitative CT analysis of honeycombing area in patients with IPF. We then evaluated the correlations between honeycombing area measured by the proposed method with that estimated by radiologists or with parameters of PFTs. Chest HRCTs and pulmonary function tests (PFTs) of 36 IPF patients, who were diagnosed using HRCT alone, were retrospectively evaluated. Two thoracic radiologists independently estimated the honeycombing area as Identified Area (IA) and the percentage of honeycombing area to total lung area as Percent Area (PA) on 3 axial CT slices for each patient. We also developed a computer-aided method to measure the honeycombing area on CT images of those patients. The total honeycombing area as CT honeycombing area (HA) and the percentage of honeycombing area to total lung area as CT %honeycombing area (%HA) were derived from the computer-aided method for each patient. HA derived from three CT slices was significantly correlated with IA (ρ=0.65 for Radiologist 1 and ρ=0.68 for Radiologist 2). %HA derived from three CT slices was also significantly correlated with PA (ρ=0.68 for Radiologist 1 and ρ=0.70 for Radiologist 2). HA and %HA derived from all CT slices were significantly correlated with FVC (%pred.), DLCO (%pred.), and the composite physiologic index (CPI) (HA: ρ=-0.43, ρ=-0.56, ρ=0.63 and %HA: ρ=-0.60, ρ=-0.49, ρ=0.69, respectively). The honeycombing area measured by the proposed computer-aided method was correlated with that estimated by expert radiologists and with parameters of PFTs. This quantitative CT analysis of

Performance of Modified Test Statistics in Covariance and Correlation Structure Analysis under Conditions of Multivariate Nonnormality.

Science.gov (United States)

Fouladi, Rachel T.

2000-01-01

Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…

The Correlation between Polybrominated Diphenyl Ethers (PBDEs) and Thyroid Hormones in the General Population: A Meta-Analysis.

Science.gov (United States)

Zhao, Xuemin; Wang, Hailong; Li, Jing; Shan, Zhongyan; Teng, Weiping; Teng, Xiaochun

2015-01-01

Certain epidemiological studies have suggested exposure to polybrominated diphenyl ethers (PBDEs) affect the production and secretion of thyroid hormones (TH); however, conflicting results have been reported in different studies. There is not a convincing conclusion about this debate to date. To perform a meta-analysis determining if there are correlations between PBDEs exposure and the serum levels of TH. Medical and scientific literature databases were searched for articles that met the eligibility criteria. The included articles were assessed for methodological quality. The correlation coefficient values or regression coefficient values between PBDEs and thyroid stimulating hormone (TSH) or total thyroxine (TT4) from each article were used for analysis. Sixteen articles were included in this meta-analysis. Pearson correlation coefficients (r) were directly collected or calculated from data given in the articles. Then, Fisher's z transformation was performed to convert each correlation coefficient to an approximately normal distribution. For z values between PBDEs exposure and TSH levels, the pooled z value for 18 studies was 0.08 (95% CI: -0.06, 0.22), and indicated significant heterogeneity (I2 values = 90.7%). Subgroup analysis was performed based on the median values of serum PBDEs in each study, there was not significant heterogeneity in each of the four subgroups (I2 values <30%). In meta-analysis of z values between PBDEs exposure and the levels of TT4, the pooled z value for 11 studies was -0.02 (95% CI: -0.11, 0.08), and also indicated significant heterogeneity (I2 values = 57.6%). Similar subgroup analysis was done for the PBDEs exposures and the levels of TT4. No significant heterogeneity was shown in either of the two subgroups (I2 values = 0). The findings in our meta-analysis indicate the effects of PBDEs on thyroid function may mainly depend on PBDEs exposure and their levels found in serum. The relationship between PBDEs exposure and changes in

The Correlation between Polybrominated Diphenyl Ethers (PBDEs and Thyroid Hormones in the General Population: A Meta-Analysis.

Directory of Open Access Journals (Sweden)

Xuemin Zhao

Full Text Available Certain epidemiological studies have suggested exposure to polybrominated diphenyl ethers (PBDEs affect the production and secretion of thyroid hormones (TH; however, conflicting results have been reported in different studies. There is not a convincing conclusion about this debate to date.To perform a meta-analysis determining if there are correlations between PBDEs exposure and the serum levels of TH. Medical and scientific literature databases were searched for articles that met the eligibility criteria. The included articles were assessed for methodological quality. The correlation coefficient values or regression coefficient values between PBDEs and thyroid stimulating hormone (TSH or total thyroxine (TT4 from each article were used for analysis.Sixteen articles were included in this meta-analysis. Pearson correlation coefficients (r were directly collected or calculated from data given in the articles. Then, Fisher's z transformation was performed to convert each correlation coefficient to an approximately normal distribution. For z values between PBDEs exposure and TSH levels, the pooled z value for 18 studies was 0.08 (95% CI: -0.06, 0.22, and indicated significant heterogeneity (I2 values = 90.7%. Subgroup analysis was performed based on the median values of serum PBDEs in each study, there was not significant heterogeneity in each of the four subgroups (I2 values <30%. In meta-analysis of z values between PBDEs exposure and the levels of TT4, the pooled z value for 11 studies was -0.02 (95% CI: -0.11, 0.08, and also indicated significant heterogeneity (I2 values = 57.6%. Similar subgroup analysis was done for the PBDEs exposures and the levels of TT4. No significant heterogeneity was shown in either of the two subgroups (I2 values = 0.The findings in our meta-analysis indicate the effects of PBDEs on thyroid function may mainly depend on PBDEs exposure and their levels found in serum. The relationship between PBDEs exposure and changes

Importance of the Correlation between Width and Length in the Shape Analysis of Nanorods: Use of a 2D Size Plot To Probe Such a Correlation.

Science.gov (United States)

Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe

2016-08-22

Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On the Analysis of Case-Control Studies in Cluster-correlated Data Settings.

Science.gov (United States)

Haneuse, Sebastien; Rivera-Rodriguez, Claudia

2018-01-01

In resource-limited settings, long-term evaluation of national antiretroviral treatment (ART) programs often relies on aggregated data, the analysis of which may be subject to ecological bias. As researchers and policy makers consider evaluating individual-level outcomes such as treatment adherence or mortality, the well-known case-control design is appealing in that it provides efficiency gains over random sampling. In the context that motivates this article, valid estimation and inference requires acknowledging any clustering, although, to our knowledge, no statistical methods have been published for the analysis of case-control data for which the underlying population exhibits clustering. Furthermore, in the specific context of an ongoing collaboration in Malawi, rather than performing case-control sampling across all clinics, case-control sampling within clinics has been suggested as a more practical strategy. To our knowledge, although similar outcome-dependent sampling schemes have been described in the literature, a case-control design specific to correlated data settings is new. In this article, we describe this design, discuss balanced versus unbalanced sampling techniques, and provide a general approach to analyzing case-control studies in cluster-correlated settings based on inverse probability-weighted generalized estimating equations. Inference is based on a robust sandwich estimator with correlation parameters estimated to ensure appropriate accounting of the outcome-dependent sampling scheme. We conduct comprehensive simulations, based in part on real data on a sample of N = 78,155 program registrants in Malawi between 2005 and 2007, to evaluate small-sample operating characteristics and potential trade-offs associated with standard case-control sampling or when case-control sampling is performed within clusters.

Detecting long-range correlation with detrended fluctuation analysis: Application to BWR stability

Energy Technology Data Exchange (ETDEWEB)

Espinosa-Paredes, Gilberto [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)]. E-mail: gepe@xanum.uam.mx; Alvarez-Ramirez, Jose [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico); Vazquez, Alejandro [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico, DF 09340 (Mexico)

2006-11-15

The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study boiling water reactor stability. DFA is a scaling method commonly used for detecting long-range correlations in non-stationary time series. This method is based on the random walk theory and was applied to neutronic power signal of Forsmark stability benchmark. Our results shows that the scaling properties breakdown during unstable oscillations.

Detecting long-range correlation with detrended fluctuation analysis: Application to BWR stability

International Nuclear Information System (INIS)

Espinosa-Paredes, Gilberto; Alvarez-Ramirez, Jose; Vazquez, Alejandro

2006-01-01

The aim of this paper is to explore the application of detrended fluctuation analysis (DFA) to study boiling water reactor stability. DFA is a scaling method commonly used for detecting long-range correlations in non-stationary time series. This method is based on the random walk theory and was applied to neutronic power signal of Forsmark stability benchmark. Our results shows that the scaling properties breakdown during unstable oscillations

Amplitude correlation analysis of W7-AS Mirnov-coil array data and other transport relevant diagnostics

International Nuclear Information System (INIS)

Pokol, G.; Por, G.; Zoletnik, S.; Basse, N.P.

2005-01-01

This work is based on the amplitude correlation analysis of the signals from a poloidal Mirnov-coil array on the Wendelstein 7 - Advanced Stellarator (W7-AS). The motivation behind this work is an earlier finding, that changes in the RMS amplitude of Mirnov-coil signals are correlated with the amplitude of small scale density turbulence measured by CO2 Laser Scattering. Based on this and other measurements, the hypothesis was set, that some of the magnetic fluctuations are caused by transient MHD modes excited by large turbulent structures. The statistical dependencies between the power modulations of different eigenmodes can provide information about the statistics of these structures. Our amplitude correlation method is based on linear continuous time-frequency representations of the signal, we use Short-Time Fourier Transformation (STFT) with Gabor-atoms to map the signal onto the time-frequency plane, as two dimensional power density distributions. From these transforms we can recover the power modulation of different frequency bands. Provided the selection of the resolution of the transforms and the limits of the frequency bands were correct, the time series calculated this way resembles the original power fluctuation of the selected eigenmode. The only distortion introduced is a convolution smoothing by the time-window used in the transformation. Detailed correlation analysis between different bandpowers of the Mirnov-coil array signals were carried out and presented in bad and good confinement states. In order to reveal the true structure and cause of magnetic fluctuations Mirnov-coil diagnostic signals were also compared with Lithium beam and CO2 Laser Scattering measurements. In our analysis we have found, that there was a strong and systematic difference in the cross-correlations of power bands between different confinement states. (author)

Robust canonical correlations: A comparative study

OpenAIRE

Branco, JA; Croux, Christophe; Filzmoser, P; Oliveira, MR

2005-01-01

Several approaches for robust canonical correlation analysis will be presented and discussed. A first method is based on the definition of canonical correlation analysis as looking for linear combinations of two sets of variables having maximal (robust) correlation. A second method is based on alternating robust regressions. These methods axe discussed in detail and compared with the more traditional approach to robust canonical correlation via covariance matrix estimates. A simulation study ...

Uncovering China’s transport CO2 emission patterns at the regional level

International Nuclear Information System (INIS)

Guo, Bin; Geng, Yong; Franke, Bernd; Hao, Han; Liu, Yaxuan; Chiu, Anthony

2014-01-01

With China’s rapid economic development, its transport sector has experienced a dramatic growth, leading to a large amount of related CO 2 emission. This paper aims to uncover China’s transport CO 2 emission patterns at the regional and provincial level. We first present the CO 2 emission features from transport sector in 30 Chinese provinces, including per capita emissions, emission intensities, and historical evolution of annual CO 2 emission. We then quantify the related driving forces by adopting both period-wise and time-series LMDI analysis. Results indicate that significant regional CO 2 emission disparities exist in China’s transport sector. The eastern region had higher total CO 2 emissions and per capita CO 2 emissions, but lower CO 2 emission intensities in its transport sector. The western region had higher CO 2 emission intensities and experienced a rapid CO 2 emission increase. The CO 2 emission increments in the eastern provinces were mainly contributed by both economic activity effect and population effect, while energy intensity partially offset the emission growth and energy structure had a marginal effect. However, in the central and western provinces, both economic activity effect and energy intensity effect induced the CO 2 emission increases, while the effects from population and energy structure change were limited. - Highlights: • The CO 2 emission features from transport sector in 30 Chinese provinces were presented. • The driving forces of CO 2 emissions from transport sector were quantified. • Regional disparities on China’s transport sector CO 2 emission exist. • Region-specific mitigation policies on transport sector CO 2 emission are needed

Correlation analysis of quantum fluctuations and repulsion effects of classical dynamics in SU(3) model

International Nuclear Information System (INIS)

Fujiwara, Shigeyasu; Sakata, Fumihiko

2003-01-01

In many quantum systems, random matrix theory has been used to characterize quantum level fluctuations, which is known to be a quantum correspondent to a regular-to-chaos transition in classical systems. We present a new qualitative analysis of quantum and classical fluctuation properties by exploiting correlation coefficients and variances. It is shown that the correlation coefficient of the quantum level density is roughly inversely proportional relation to the variance of consecutive phase-space point spacings on the Poincare section plane. (author)

Analysis of light particles correlation selected by neutron calorimetry in the reaction 208 Pb+93 Nb at 29 MeV/u

International Nuclear Information System (INIS)

Ghisalberti, C.

1994-01-01

This work deals with the analysis of light particles correlation selected by neutrons calorimetry in the reaction : 208 Pb+ 93 Nb at 29 MeV/u. In the first part are described the interest of correlation functions, the proton-proton correlation function study, the classical model developed for describing the correlations of two light particles emitted by a nucleus in thermal equilibrium, the quantum model and some notions about exclusive sources and measures. The second part is a description of the experience : 208 Pb+ 93 Nb at 29 MeV/u. The analysis of experimental data and of experimental correlation functions are given respectively in the third and the fourth parts. (O.L.). 38 refs., 82 figs., 11 tabs

Bottomside sinusoidal irregularities in the equatorial F region. II - Cross-correlation and spectral analysis

Science.gov (United States)

Cragin, B. L.; Hanson, W. B.; Mcclure, J. P.; Valladares, C. E.

1985-01-01

Equatorial bottomside sinusoidal (BSS) irregularities have been studied by applying techniques of cross-correlation and spectral analysis to the Atmosphere Explorer data set. The phase of the cross-correlations of the plasma number density is discussed and the two drift velocity components observed using the retarding potential analyzer and ion drift meter on the satellite are discussed. Morphology is addressed, presenting the geographical distributions of the occurrence of BSS events for the equinoxes and solstices. Physical processes including the ion Larmor flux, interhemispheric plasma flows, and variations in the lower F region Pedersen conductivity are invoked to explain the findings.

Interactive Correlation Analysis and Visualization of Climate Data

Energy Technology Data Exchange (ETDEWEB)

Ma, Kwan-Liu [Univ. of California, Davis, CA (United States)

2016-09-21

The relationship between our ability to analyze and extract insights from visualization of climate model output and the capability of the available resources to make those visualizations has reached a crisis point. The large volume of data currently produced by climate models is overwhelming the current, decades-old visualization workflow. The traditional methods for visualizing climate output also have not kept pace with changes in the types of grids used, the number of variables involved, and the number of different simulations performed with a climate model or the feature-richness of high-resolution simulations. This project has developed new and faster methods for visualization in order to get the most knowledge out of the new generation of high-resolution climate models. While traditional climate images will continue to be useful, there is need for new approaches to visualization and analysis of climate data if we are to gain all the insights available in ultra-large data sets produced by high-resolution model output and ensemble integrations of climate models such as those produced for the Coupled Model Intercomparison Project. Towards that end, we have developed new visualization techniques for performing correlation analysis. We have also introduced highly scalable, parallel rendering methods for visualizing large-scale 3D data. This project was done jointly with climate scientists and visualization researchers at Argonne National Laboratory and NCAR.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity

Directory of Open Access Journals (Sweden)

Shaun P. Stice

2018-02-01

Full Text Available Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA and repetitive extragenic palindrome repeat (rep-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study.

Outage Performance Analysis of Cooperative Diversity with MRC and SC in Correlated Lognormal Channels

Directory of Open Access Journals (Sweden)

Skraparlis D

2009-01-01

Full Text Available Abstract The study of relaying systems has found renewed interest in the context of cooperative diversity for communication channels suffering from fading. This paper provides analytical expressions for the end-to-end SNR and outage probability of cooperative diversity in correlated lognormal channels, typically found in indoor and specific outdoor environments. The system under consideration utilizes decode-and-forward relaying and Selection Combining or Maximum Ratio Combining at the destination node. The provided expressions are used to evaluate the gains of cooperative diversity compared to noncooperation in correlated lognormal channels, taking into account the spectral and energy efficiency of the protocols and the half-duplex or full-duplex capability of the relay. Our analysis demonstrates that correlation and lognormal variances play a significant role on the performance gain of cooperative diversity against noncooperation.

Clustering stocks using partial correlation coefficients

Science.gov (United States)

Jung, Sean S.; Chang, Woojin

2016-11-01

A partial correlation analysis is performed on the Korean stock market (KOSPI). The difference between Pearson correlation and the partial correlation is analyzed and it is found that when conditioned on the market return, Pearson correlation coefficients are generally greater than those of the partial correlation, which implies that the market return tends to drive up the correlation between stock returns. A clustering analysis is then performed to study the market structure given by the partial correlation analysis and the members of the clusters are compared with the Global Industry Classification Standard (GICS). The initial hypothesis is that the firms in the same GICS sector are clustered together since they are in a similar business and environment. However, the result is inconsistent with the hypothesis and most clusters are a mix of multiple sectors suggesting that the traditional approach of using sectors to determine the proximity between stocks may not be sufficient enough to diversify a portfolio.

Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis.

Science.gov (United States)

Chen, Jun; Bushman, Frederic D; Lewis, James D; Wu, Gary D; Li, Hongzhe

2013-04-01

Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary relationships among bacterial taxa. Our ssCCA formulation utilizes a phylogenetic structure-constrained penalty function to impose certain smoothness on the linear coefficients according to the phylogenetic relationships among the taxa. An efficient coordinate descent algorithm is developed for optimization. A human gut microbiome data set is used to illustrate this method. Both simulations and real data applications show that ssCCA performs better than the standard sparse CCA in identifying meaningful variables when there are structures in the data.

Brillouin Optical Correlation Domain Analysis in Composite Material Beams.

Science.gov (United States)

Stern, Yonatan; London, Yosef; Preter, Eyal; Antman, Yair; Diamandi, Hilel Hagai; Silbiger, Maayan; Adler, Gadi; Levenberg, Eyal; Shalev, Doron; Zadok, Avi

2017-10-02

Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both), however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA) protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a) monitoring the production and curing of a composite beam over 60 h; (b) estimating the stiffness and Young's modulus of a composite beam; and (c) distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.

Brillouin Optical Correlation Domain Analysis in Composite Material Beams

Directory of Open Access Journals (Sweden)

Yonatan Stern

2017-10-01

Full Text Available Structural health monitoring is a critical requirement in many composites. Numerous monitoring strategies rely on measurements of temperature or strain (or both, however these are often restricted to point-sensing or to the coverage of small areas. Spatially-continuous data can be obtained with optical fiber sensors. In this work, we report high-resolution distributed Brillouin sensing over standard fibers that are embedded in composite structures. A phase-coded, Brillouin optical correlation domain analysis (B-OCDA protocol was employed, with spatial resolution of 2 cm and sensitivity of 1 °K or 20 micro-strain. A portable measurement setup was designed and assembled on the premises of a composite structures manufacturer. The setup was successfully utilized in several structural health monitoring scenarios: (a monitoring the production and curing of a composite beam over 60 h; (b estimating the stiffness and Young’s modulus of a composite beam; and (c distributed strain measurements across the surfaces of a model wing of an unmanned aerial vehicle. The measurements are supported by the predictions of structural analysis calculations. The results illustrate the potential added values of high-resolution, distributed Brillouin sensing in the structural health monitoring of composites.

Correlation and network analysis of global financial indices.

Science.gov (United States)

Kumar, Sunil; Deo, Nivedita

2012-08-01

Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

An efficient sensitivity analysis method for modified geometry of Macpherson suspension based on Pearson correlation coefficient

Science.gov (United States)

Shojaeefard, Mohammad Hasan; Khalkhali, Abolfazl; Yarmohammadisatri, Sadegh

2017-06-01

The main purpose of this paper is to propose a new method for designing Macpherson suspension, based on the Sobol indices in terms of Pearson correlation which determines the importance of each member on the behaviour of vehicle suspension. The formulation of dynamic analysis of Macpherson suspension system is developed using the suspension members as the modified links in order to achieve the desired kinematic behaviour. The mechanical system is replaced with an equivalent constrained links and then kinematic laws are utilised to obtain a new modified geometry of Macpherson suspension. The equivalent mechanism of Macpherson suspension increased the speed of analysis and reduced its complexity. The ADAMS/CAR software is utilised to simulate a full vehicle, Renault Logan car, in order to analyse the accuracy of modified geometry model. An experimental 4-poster test rig is considered for validating both ADAMS/CAR simulation and analytical geometry model. Pearson correlation coefficient is applied to analyse the sensitivity of each suspension member according to vehicle objective functions such as sprung mass acceleration, etc. Besides this matter, the estimation of Pearson correlation coefficient between variables is analysed in this method. It is understood that the Pearson correlation coefficient is an efficient method for analysing the vehicle suspension which leads to a better design of Macpherson suspension system.

Asset correlations and credit portfolio risk: an empirical analysis

OpenAIRE

Düllmann, Klaus; Scheicher, Martin; Schmieder, Christian

2007-01-01

In credit risk modelling, the correlation of unobservable asset returns is a crucial component for the measurement of portfolio risk. In this paper, we estimate asset correlations from monthly time series of Moody's KMV asset values for around 2,000 European firms from 1996 to 2004. We compare correlation and value-atrisk (VaR) estimates in a one-factor or market model and a multi-factor or sector model. Our main finding is a complex interaction of credit risk correlations and default probabi...

Two-Dimensional Raman Correlation Analysis of Diseased Esophagus in a Rat

Science.gov (United States)

Takanezawa, Sota; Morita, Shin-ichi; Maruyama, Atsushi; Murakami, Takurou N.; Kawashima, Norimichi; Endo, Hiroyuki; Iijima, Katsunori; Asakura, Tohru; Shimosegawa, Tooru; Sato, Hidetoshi

2010-07-01

Generalized two-dimensional (2D) Raman correlation analysis effectively distinguished a benign tumor from normal tissue. Line profiling Raman spectra of a rat esophagus, including a benign tumor, were measured and the generalized 2D synchronous and asynchronous spectra were calculated. In the autocorrelation area of the amide I band of proteins in the asynchronous map, a cross-like pattern was observed. A simulation study indicated that the pattern was caused by a sharp band component in the amide I band region. We considered that the benign tumor corresponded to the sharp component.

Identifying compromised systems through correlation of suspicious traffic from malware behavioral analysis

Science.gov (United States)

Camilo, Ana E. F.; Grégio, André; Santos, Rafael D. C.

2016-05-01

Malware detection may be accomplished through the analysis of their infection behavior. To do so, dynamic analysis systems run malware samples and extract their operating system activities and network traffic. This traffic may represent malware accessing external systems, either to steal sensitive data from victims or to fetch other malicious artifacts (configuration files, additional modules, commands). In this work, we propose the use of visualization as a tool to identify compromised systems based on correlating malware communications in the form of graphs and finding isomorphisms between them. We produced graphs from over 6 thousand distinct network traffic files captured during malware execution and analyzed the existing relationships among malware samples and IP addresses.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy

International Nuclear Information System (INIS)

Jesse, Stephen; Kalinin, Sergei V

2009-01-01

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Comprehensive analysis of electron correlations in three-electron atoms